#then wrote my dissertation without AI

[am-i-the-asshole-official]

AITA for telling my sister that I didn't find her instagram post funny and that I didn't want her to send me things like that again?

I (32f) have never had a good relationship with my sister (34f). We have gotten somewhat better over time, but we have always had a strained relationship. We are about as opposite as you can be. Social rights issues? No compromise. ACAB? Constant disagreements. Politics: best never mention them. TV Shows? No interest at all. Music? We cannot stand each other's music. We genuinely have nothing except our blood and the fact we were raised by the same people in common.

I am currently in the process of finishing my PhD and live on a different continent to her. We have been vaguely trying to talk and maintain a cordial friendship from afar.

For the past four months I had been preparing for a conference that I was organizing, leading, and moderating. It was a massive project that will be a huge part of my dissertation research, and it went very well. The day after the conference I had a long career planning discussion with some academic advisors, and spent about three hours talking in my second language with my own advisor. The combination of everything left me genuinely exhausted to the point that I woke up the day after it all still too tired to move.

After I woke up, I realized I had a text from her containing an instagram link - no comment, no notes, no context, just the link. I know I wasn't in a perfect headspace and still needed more sleep, but I clicked it because usually she just spam sends me instagram videos about random baby rearing things she finds funny. I don't find any of them amusing, but tolerate them because she seems to enjoy it. I usually just nod my head or offer a few responses to show I've seen it and move on.

But this video was different. This video was, as far as I can tell, an influencer attempt at selling an AI. It had a young woman walk into a classroom with the onscreen text describing how "my professor is the same age as us and she has her phd!" and when she was asked how she got it, the video shows how the "teacher" went onto Youtube, put Youtube videos into this AI which created an algorithm to summarize the video. It ends with the words "University is a joke in 2024".

I was....genuinely offended. After everything I had been through working on this conference and with years of thesis work, I was just hurt. I watched it a few times, trying to understand what it was even trying to say, and could come up with no good reason for why she would just send it to me. So I wrote back to her "idk how you even want me to respond."

She said she thought it was funny, and I asked her if she understood why I wouldn't find it funny. She wrote back "because you lack my sense of humor smh." I tried explaining why I was upset and reframed it in the context of her job. She doubled down that she thought it was funny, but that it was because she thought it was amusing anyone would think they could get any kind of degree like that.

I explained that AI is genuinely a problem in universities right now and that our students are using it to get through their classes and it's causing a lot of chaos with profs trying to crack down on it. Then I told her it felt like she sent me something just to annoy me.

The argument continued from there. I asked her not to send me stuff like that again, and she asked how she was supposed to know I would be triggered by an AI video, and that I was being oversensitive, and how it was my fault for always assuming that she is plotting to piss me off and that she can never show an interest in my life without me having a "feelings dumpfest" and calling her out for being a bully.

I don't understand how she could think sending a video to me saying "university is a joke in 2024" with no context at all would be taken as a joke in the first place. And I felt like if I didn't tell her I didn't like this kind of video and why it made me upset she would keep sending things like this to me I'd have to keep seeing and ignoring future posts.

AITA for telling her I didn't think it was funny and to stop?

Should I have just ignored it and gone back to sleep? (At this point that's what I felt like I should have done...)

What are these acronyms?

[raymondshieldsofficial]

was talking with my parents about AI today and they had some genuinely really interesting perspectives on it

my mum is an oncology pharmacist and said that AI could be really useful for analysing test results and identifying potentially cancerous tumours in patients’ scans. essentially, it could highlight areas that the oncologist looking over the results may want to focus on. but they’d never leave it up to AI to diagnose the patient (ignoring that this would likely lead to biopsies and further tests, etc)

my dad is a software engineer. he’s 61 and wrote his dissertation on a typewriter because word processors either weren’t invented or not common enough that a university student could have one. he’s worked with computers pretty much since they were invented (in the modern sense). he put some code he was working on into the AI at his work just to see how good it was. it pulled up one line of code, that was abnormal for a specific reason that helped it to do what it needed to do. he told it the reason and apparently the AI was like “oh yeah.” and ran another analysis and the code was fine. which he knew because coding chips for household appliances is relatively simple compared to working on the Opportunity rover. but he still checked it over because he’s an old tech guy and will die before he has a “smart” appliance. real.

my point is, that they both used AI for things that actively helped their jobs. it could help increase the productivity of oncologists, in my mum’s case, and if you know anything about cancer you know that time is of the essence. in my dad’s case, it potentially could have highlighted a potential error that needed to be fixed before the code was sent off for second testing or whatever the fuck- I don’t know, I used to work in oncology myself but never in tech. but it could’ve saved him embarrassment and also several weeks of crashing out over broken code, which has happened in the past. he’s on first name terms with the guy who runs the test branch in Vietnam now. but my point is, no one took AI’s answer for granted. they used it and analysed it. there is not ever going to be a world where an oncologist will look at an AI result and feed back to a patient without fully analysing it, using AI as an assist if that.

my current job is in corporate and they’re desperately pushing for us to use it more - for emails, customer communications, etc, because it’s “quicker”.

another thing about my parents is that they’re both artists. my mum is a traditional artist and my dad is a photographer. they’ve both won awards. I’m an aspiring writer. one thing we all agreed on is that AI needs to stay the fuck out of creative industries. when I push to publish, I am going to have a clause in my contract that AI cannot be used in any capacity relating to my work.

I am currently the reason our area manager has to ban discussing the morals of AI every time he mentions the implementation in meetings.

AI could be brilliant for the medical field. it could stop stupid errors going through in the tech field. but it needs human oversight.

[scarefox]

friend: I found out about this new AI thing that can write you job applications and stuff

me: tbh I am not a big fan of AI atm the way it endangers my whole work industry

friend: oh, yea I understand that. I was just testing and playing around with it anyways haha

- later after ranting a bit about AI art bros -

me: and there are also people who let their whole dissertation get written by AI now... Isn’t that just unfair to you, me and everyone who just wrote months on our final papers?

friend: really, people do that? I only let it write some paragraphs to look how it would form the sentences... and the summary too

me:

(the fact that you have to put a page at the end of your work explaining that you wrote that whole scientific paper by yourself without help and have to sign it with your name......)

[smartecky]

Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but lidar has proven transformative. The latest accomplishment using laser-based imaging maps thousands of square kilometers of an ancient Mayan city once millions strong, but the researchers make it clear that there’s no technological substitute for experience and a good eye.

The Pacunam Lidar Initiative began two years ago, bringing together a group of scholars and local authorities to undertake the largest-yet survey of a protected and long-studied region in Guatemala. Some 2,144 square kilometers of the Maya Biosphere Reserve in Petén were scanned, inclusive of and around areas known to be settled, developed or otherwise of importance.

Preliminary imagery and data illustrating the success of the project were announced earlier this year, but the researchers have now performed their actual analyses on the data, and the resulting paper summarizing their wide-ranging results has been published in the journal Science.

The areas covered by the initiative, as you can see, spread over perhaps a fifth of the country.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a data set like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, told me. He worked on the project with numerous others, including Tulane colleague Marcello Canuto. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another nine months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he said. “They may have seemed exaggerated to some.”

The lidar data was collected not by self-driving cars, which seem to be the only vehicles bearing lidar we ever hear about, nor even by drones, but by traditional airplane. That may sound cumbersome, but the distances and landscapes involved permitted nothing else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli explained. “In our case it was actually a twin-engine plane flown down from Texas.”

The plane made dozens of passes over a given area, a chosen “polygon” perhaps 30 kilometers long and 20 wide. Mounted underneath was “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which pretty much says it all: this is a heavy-duty instrument, the size of a refrigerator. But you need that kind of system to pierce the canopy and image the underlying landscape.

The many overlapping passes were then collated and calibrated into a single digital landscape of remarkable detail.

“It identified features that I had walked over — a hundred times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But these structures don’t identify themselves. There’s no computer labeling system that looks at the 3D model and says, “this is a pyramid, this is a wall,” and so on. That’s a job that only archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli said. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery revealed, for example, lots of low linear features that could be man-made or natural. It’s not always easy to tell the difference, but context and existing scholarship fill in the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli said — in case you were wondering why it took nine months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations on the maps. It should be noted that many of these features had by this point been verified by field expeditions. By consulting existing maps and getting ground truth in person, they had made sure that these weren’t phantom structures or wishful thinking. “We’re confident that they’re all there,” he told me.

“Next is the quantitative step,” he continued. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other data set: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the point where the imagery starts to go from point cloud to academic study. After all, it’s well known that the Maya had a large city in this area; it’s been intensely studied for decades. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) study was meant to advance beyond the traditional methods employed previously.

“It’s a huge data set. It’s a huge cross-section of the Maya lowlands,” Estrada-Belli said. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he said, slightly wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a result the paper includes all kinds of new theories and conclusions, from population and economy estimates, to cultural and engineering knowledge, to the timing and nature of conflicts with neighbors.

The resulting report doesn’t just advance the knowledge of Mayan culture and technology, but the science of archaeology itself. It’s iterative, of course, like everything else — Estrada-Belli noted that they were inspired by work done by colleagues in Belize and Cambodia; their contribution, however, exemplifies new approaches to handling large areas and large data sets.

The more experiments and field work, the more established these methods will become, and the greater they will be accepted and replicated. Already they have proven themselves invaluable, and this study is perhaps the best example of lidar’s potential in the field.

WTF is lidar?

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” explained co-author Stephen Houston, of Brown University, in an email. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” pointed out co-author, Ithaca College’s Thomas Garrison, in an email. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery can also show the extent of looting, he wrote, and help cultural authorities provide against it by being aware of relics and sites before the looters are.

The researchers are already planning a second, even larger set of flyovers, founded on the success of the first experiment. Perhaps by the time the initial physical work is done the trendier tools of the last few years will make themselves applicable.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli suggested. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s also excited by the idea of putting the data online so citizen archaeologists can help pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he said.

But as his colleagues point out, even years in this line of work are necessarily preliminary.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was published today in Science; you can learn about their conclusions (which are of more interest to the archaeologists and anthropologists among our readers) there, and follow other work being undertaken by the Fundación Pacunam at its website.

Read more: https://techcrunch.com/2018/09/27/how-aerial-lidar-illuminated-a-mayan-megalopolis/

How aerial lidar illuminated a Mayan megalopolis Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but…

[peach5200-blog]

Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but lidar has proven transformative. The latest accomplishment using laser-based imaging maps thousands of square kilometers of an ancient Mayan city once millions strong, but the researchers make it clear that there’s no technological substitute for experience and a good eye.

The Pacunam Lidar Initiative began two years ago, bringing together a group of scholars and local authorities to undertake the largest-yet survey of a protected and long-studied region in Guatemala. Some 2,144 square kilometers of the Maya Biosphere Reserve in Petén were scanned, inclusive of and around areas known to be settled, developed or otherwise of importance.

Preliminary imagery and data illustrating the success of the project were announced earlier this year, but the researchers have now performed their actual analyses on the data, and the resulting paper summarizing their wide-ranging results has been published in the journal Science.

The areas covered by the initiative, as you can see, spread over perhaps a fifth of the country.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a data set like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, told me. He worked on the project with numerous others, including Tulane colleague Marcello Canuto. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another nine months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he said. “They may have seemed exaggerated to some.”

The lidar data was collected not by self-driving cars, which seem to be the only vehicles bearing lidar we ever hear about, nor even by drones, but by traditional airplane. That may sound cumbersome, but the distances and landscapes involved permitted nothing else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli explained. “In our case it was actually a twin-engine plane flown down from Texas.”

The plane made dozens of passes over a given area, a chosen “polygon” perhaps 30 kilometers long and 20 wide. Mounted underneath was “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which pretty much says it all: this is a heavy-duty instrument, the size of a refrigerator. But you need that kind of system to pierce the canopy and image the underlying landscape.

The many overlapping passes were then collated and calibrated into a single digital landscape of remarkable detail.

“It identified features that I had walked over — a hundred times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But these structures don’t identify themselves. There’s no computer labeling system that looks at the 3D model and says, “this is a pyramid, this is a wall,” and so on. That’s a job that only archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli said. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery revealed, for example, lots of low linear features that could be man-made or natural. It’s not always easy to tell the difference, but context and existing scholarship fill in the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli said — in case you were wondering why it took nine months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations on the maps. It should be noted that many of these features had by this point been verified by field expeditions. By consulting existing maps and getting ground truth in person, they had made sure that these weren’t phantom structures or wishful thinking. “We’re confident that they’re all there,” he told me.

“Next is the quantitative step,” he continued. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other data set: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the point where the imagery starts to go from point cloud to academic study. After all, it’s well known that the Maya had a large city in this area; it’s been intensely studied for decades. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) study was meant to advance beyond the traditional methods employed previously.

“It’s a huge data set. It’s a huge cross-section of the Maya lowlands,” Estrada-Belli said. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he said, slightly wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a result the paper includes all kinds of new theories and conclusions, from population and economy estimates, to cultural and engineering knowledge, to the timing and nature of conflicts with neighbors.

The resulting report doesn’t just advance the knowledge of Mayan culture and technology, but the science of archaeology itself. It’s iterative, of course, like everything else — Estrada-Belli noted that they were inspired by work done by colleagues in Belize and Cambodia; their contribution, however, exemplifies new approaches to handling large areas and large data sets.

The more experiments and field work, the more established these methods will become, and the greater they will be accepted and replicated. Already they have proven themselves invaluable, and this study is perhaps the best example of lidar’s potential in the field.

WTF is lidar?

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” explained co-author Stephen Houston, of Brown University, in an email. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” pointed out co-author, Ithaca College’s Thomas Garrison, in an email. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery can also show the extent of looting, he wrote, and help cultural authorities provide against it by being aware of relics and sites before the looters are.

The researchers are already planning a second, even larger set of flyovers, founded on the success of the first experiment. Perhaps by the time the initial physical work is done the trendier tools of the last few years will make themselves applicable.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli suggested. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s also excited by the idea of putting the data online so citizen archaeologists can help pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he said.

But as his colleagues point out, even years in this line of work are necessarily preliminary.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was published today in Science; you can learn about their conclusions (which are of more interest to the archaeologists and anthropologists among our readers) there, and follow other work being undertaken by the Fundación Pacunam at its website.

Source: gadgets

How aerial lidar illuminated a Mayan megalopolis Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but…

[thegloober]

How aerial lidar illuminated a Mayan megalopolis

Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but lidar has proven transformative. The latest accomplishment using laser-based imaging maps thousands of square kilometers of an ancient Mayan city once millions strong, but the researchers make it clear that there’s no technological substitute for experience and a good eye.

The Pacunam Lidar Initiative began two years ago, bringing together a group of scholars and local authorities to undertake the largest yet survey of a protected and long-studied region in Guatemala. Some 2,144 square kilometers of the Maya Biosphere Reserve in Petén were scanned, inclusive of and around areas known to be settled, developed, or otherwise of importance.

Preliminary imagery and data illustrating the success of the project were announced earlier this year, but the researchers have now performed their actual analyses on the data, and the resulting paper summarizing their wide-ranging results has been published in the journal Science.

The areas covered by the initiative, as you can see, spread over perhaps a fifth of the country.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a dataset like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, told me. He worked on the project with numerous others, including his colleagues Marcello Canuto and Stephen Houston. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another 9 months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he said. “They may have seemed exaggerated to some.”

The lidar data was collected not by self-driving cars, which seem to be the only vehicles bearing lidar we ever hear about, nor even by drones, but by traditional airplane. That may sound cumbersome, but the distances and landscapes involved permitted nothing else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli explained. “In our case it was actually a twin engine plane flown down from Texas.”

The plane would made dozens of passes over a given area, a chosen “polygon” perhaps 30 kilometers long and 20 wide. Mounted underneath was “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which pretty much says it all: this is a heavy duty instrument, the size of a refrigerator. But you need that kind of system to pierce the canopy and image the underlying landscape.

The many overlapping passes were then collated and calibrated into a single digital landscape of remarkable detail.

“It identified features that I had walked over — a hundred of times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But these structures don’t identify themselves. There’s no computer labeling system that looks at the 3D model and says, “this is a pyramid, this is a wall,” and so on. That’s a job that only archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli said. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery revealed, for example, lots of low linear features that could be man-made or natural. It’s not always easy to tell the difference, but context and existing scholarship fill in the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli said — in case you were wondering why it took nine months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations on the maps. It should be noted that many of these features had by this point been verified by field expeditions. By consulting existing maps and getting ground truth in person, they had made sure that these weren’t phantom structures or wishful thinking. “We’re confident that they’re all there,” he told me.

“Next is the quantitative step,” he continued. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other dataset: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the point where the imagery starts to go from point cloud to academic study. After all, it’s well known that the Maya had a large city in this area; it’s been intensely studied for decades. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) study was meant to advance beyond the traditional methods employed previously.

“It’s a huge dataset. It’s a huge cross section of the Maya lowlands,” Estrada-Belli said. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he said, slightly wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a result the paper includes all kinds of new theories and conclusions, from population and economy estimates, to cultural and engineering knowledge, to the timing and nature of conflicts with neighbors.

The resulting report doesn’t just advance the knowledge of Mayan culture and technology, but the science of archaeology itself. It’s iterative, of course, like everything else — Estrada-Belli noted that they were inspired by work done by colleagues in Belize and Cambodia; their contribution, however, exemplifies new approaches to handling large areas and large datasets.

The more experiments and field work, the more established these methods will become, and the greater they will be accepted and replicated. Already they have proven themselves invaluable, and this study is perhaps the best example of lidar’s potential in the field.

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” explained co-author Stephen Houston (also from Tulane) in an email. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” pointed out co-author Thomas Garrison in an email. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery can also show the extent of looting, he wrote, and help cultural authorities provide against it by being aware of relics and sites before the looters are.

The researchers are already planning a second, even larger set of flyovers, founded on the success of the first experiment. Perhaps by the time the initial physical work is done the trendier tools of the last few years will make themselves applicable.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli suggested. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s also excited by the idea of putting the data online so citizen archaeologists can help pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he said.

But as his colleagues point out, even years in this line of work are necessarily preliminary.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was published today in Science; you can learn about their conclusions (which are of more interest to the archaeologists and anthropologists among our readers) there, and follow other work being undertaken by the Fundación Pacunam at its website.

Source: https://bloghyped.com/how-aerial-lidar-illuminated-a-mayan-megalopolis/

[roberttbertton]

Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but lidar has proven transformative. The latest accomplishment using laser-based imaging maps thousands of square kilometers of an ancient Mayan city once millions strong, but the researchers make it clear that there’s no technological substitute for experience and a good eye.

The Pacunam Lidar Initiative began two years ago, bringing together a group of scholars and local authorities to undertake the largest yet survey of a protected and long-studied region in Guatemala. Some 2,144 square kilometers of the Maya Biosphere Reserve in Petén were scanned, inclusive of and around areas known to be settled, developed, or otherwise of importance.

Preliminary imagery and data illustrating the success of the project were announced earlier this year, but the researchers have now performed their actual analyses on the data, and the resulting paper summarizing their wide-ranging results has been published in the journal Science.

The areas covered by the initiative, as you can see, spread over perhaps a fifth of the country.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a dataset like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, told me. He worked on the project with numerous others, including his colleagues Marcello Canuto and Stephen Houston. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another 9 months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he said. “They may have seemed exaggerated to some.”

The lidar data was collected not by self-driving cars, which seem to be the only vehicles bearing lidar we ever hear about, nor even by drones, but by traditional airplane. That may sound cumbersome, but the distances and landscapes involved permitted nothing else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli explained. “In our case it was actually a twin engine plane flown down from Texas.”

The plane would made dozens of passes over a given area, a chosen “polygon” perhaps 30 kilometers long and 20 wide. Mounted underneath was “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which pretty much says it all: this is a heavy duty instrument, the size of a refrigerator. But you need that kind of system to pierce the canopy and image the underlying landscape.

The many overlapping passes were then collated and calibrated into a single digital landscape of remarkable detail.

“It identified features that I had walked over — a hundred of times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But these structures don’t identify themselves. There’s no computer labeling system that looks at the 3D model and says, “this is a pyramid, this is a wall,” and so on. That’s a job that only archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli said. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery revealed, for example, lots of low linear features that could be man-made or natural. It’s not always easy to tell the difference, but context and existing scholarship fill in the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli said — in case you were wondering why it took nine months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations on the maps. It should be noted that many of these features had by this point been verified by field expeditions. By consulting existing maps and getting ground truth in person, they had made sure that these weren’t phantom structures or wishful thinking. “We’re confident that they’re all there,” he told me.

“Next is the quantitative step,” he continued. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other dataset: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the point where the imagery starts to go from point cloud to academic study. After all, it’s well known that the Maya had a large city in this area; it’s been intensely studied for decades. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) study was meant to advance beyond the traditional methods employed previously.

“It’s a huge dataset. It’s a huge cross section of the Maya lowlands,” Estrada-Belli said. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he said, slightly wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a result the paper includes all kinds of new theories and conclusions, from population and economy estimates, to cultural and engineering knowledge, to the timing and nature of conflicts with neighbors.

The resulting report doesn’t just advance the knowledge of Mayan culture and technology, but the science of archaeology itself. It’s iterative, of course, like everything else — Estrada-Belli noted that they were inspired by work done by colleagues in Belize and Cambodia; their contribution, however, exemplifies new approaches to handling large areas and large datasets.

The more experiments and field work, the more established these methods will become, and the greater they will be accepted and replicated. Already they have proven themselves invaluable, and this study is perhaps the best example of lidar’s potential in the field.

WTF is lidar?

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” explained co-author Stephen Houston (also from Tulane) in an email. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” pointed out co-author Thomas Garrison in an email. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery can also show the extent of looting, he wrote, and help cultural authorities provide against it by being aware of relics and sites before the looters are.

The researchers are already planning a second, even larger set of flyovers, founded on the success of the first experiment. Perhaps by the time the initial physical work is done the trendier tools of the last few years will make themselves applicable.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli suggested. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s also excited by the idea of putting the data online so citizen archaeologists can help pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he said.

But as his colleagues point out, even years in this line of work are necessarily preliminary.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was published today in Science; you can learn about their conclusions (which are of more interest to the archaeologists and anthropologists among our readers) there, and follow other work being undertaken by the Fundación Pacunam at its website.

Source TechCrunch https://ift.tt/2OYGQsR

How aerial lidar illuminated a Mayan megalopolis – BerTTon Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but…

[fmservers]

How aerial lidar illuminated a Mayan megalopolis

Archaeology may not be the most likely place to find the latest in technology — AI and robots are of dubious utility in the painstaking fieldwork involved — but lidar has proven transformative. The latest accomplishment using laser-based imaging maps thousands of square kilometers of an ancient Mayan city once millions strong, but the researchers make it clear that there’s no technological substitute for experience and a good eye.

The Pacunam Lidar Initiative began two years ago, bringing together a group of scholars and local authorities to undertake the largest yet survey of a protected and long-studied region in Guatemala. Some 2,144 square kilometers of the Maya Biosphere Reserve in Petén were scanned, inclusive of and around areas known to be settled, developed, or otherwise of importance.

Preliminary imagery and data illustrating the success of the project were announced earlier this year, but the researchers have now performed their actual analyses on the data, and the resulting paper summarizing their wide-ranging results has been published in the journal Science.

The areas covered by the initiative, as you can see, spread over perhaps a fifth of the country.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a dataset like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, told me. He worked on the project with numerous others, including his colleagues Marcello Canuto and Stephen Houston. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another 9 months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he said. “They may have seemed exaggerated to some.”

The lidar data was collected not by self-driving cars, which seem to be the only vehicles bearing lidar we ever hear about, nor even by drones, but by traditional airplane. That may sound cumbersome, but the distances and landscapes involved permitted nothing else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli explained. “In our case it was actually a twin engine plane flown down from Texas.”

The plane would made dozens of passes over a given area, a chosen “polygon” perhaps 30 kilometers long and 20 wide. Mounted underneath was “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which pretty much says it all: this is a heavy duty instrument, the size of a refrigerator. But you need that kind of system to pierce the canopy and image the underlying landscape.

The many overlapping passes were then collated and calibrated into a single digital landscape of remarkable detail.

“It identified features that I had walked over — a hundred of times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But these structures don’t identify themselves. There’s no computer labeling system that looks at the 3D model and says, “this is a pyramid, this is a wall,” and so on. That’s a job that only archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli said. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery revealed, for example, lots of low linear features that could be man-made or natural. It’s not always easy to tell the difference, but context and existing scholarship fill in the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli said — in case you were wondering why it took nine months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations on the maps. It should be noted that many of these features had by this point been verified by field expeditions. By consulting existing maps and getting ground truth in person, they had made sure that these weren’t phantom structures or wishful thinking. “We’re confident that they’re all there,” he told me.

[gallery ids="1721959,1721960,1721957,1721961,1721958"]

“Next is the quantitative step,” he continued. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other dataset: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the point where the imagery starts to go from point cloud to academic study. After all, it’s well known that the Maya had a large city in this area; it’s been intensely studied for decades. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) study was meant to advance beyond the traditional methods employed previously.

“It’s a huge dataset. It’s a huge cross section of the Maya lowlands,” Estrada-Belli said. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he said, slightly wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a result the paper includes all kinds of new theories and conclusions, from population and economy estimates, to cultural and engineering knowledge, to the timing and nature of conflicts with neighbors.

The resulting report doesn’t just advance the knowledge of Mayan culture and technology, but the science of archaeology itself. It’s iterative, of course, like everything else — Estrada-Belli noted that they were inspired by work done by colleagues in Belize and Cambodia; their contribution, however, exemplifies new approaches to handling large areas and large datasets.

The more experiments and field work, the more established these methods will become, and the greater they will be accepted and replicated. Already they have proven themselves invaluable, and this study is perhaps the best example of lidar’s potential in the field.

WTF is lidar?

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” explained co-author Stephen Houston (also from Tulane) in an email. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” pointed out co-author Thomas Garrison in an email. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery can also show the extent of looting, he wrote, and help cultural authorities provide against it by being aware of relics and sites before the looters are.

The researchers are already planning a second, even larger set of flyovers, founded on the success of the first experiment. Perhaps by the time the initial physical work is done the trendier tools of the last few years will make themselves applicable.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli suggested. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s also excited by the idea of putting the data online so citizen archaeologists can help pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he said.

But as his colleagues point out, even years in this line of work are necessarily preliminary.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was published today in Science; you can learn about their conclusions (which are of more interest to the archaeologists and anthropologists among our readers) there, and follow other work being undertaken by the Fundación Pacunam at its website.

Via Devin Coldewey https://techcrunch.com

[nuttytriumphenthusiast-blog]

Archaeology would possibly not be the perhaps position to search out the newest in generation — AI and robots are of doubtful software within the painstaking fieldwork concerned — however lidar has confirmed transformative. The newest accomplishment the usage of laser-based imaging maps 1000’s of sq. kilometers of an historical Mayan town as soon as thousands and thousands robust, however the researchers make it transparent that there’s no technological change for revel in and a just right eye.

The Pacunam Lidar Initiative started two years in the past, bringing in combination a team of students and native government to adopt the most important but survey of a secure and long-studied area in Guatemala. Some 2,144 sq. kilometers of the Maya Biosphere Reserve in Petén had been scanned, inclusive of and round spaces identified to be settled, advanced, or in a different way of significance.

Preliminary imagery and knowledge illustrating the good fortune of the venture had been introduced previous this yr, however the researchers have now carried out their precise analyses at the information, and the ensuing paper summarizing their wide-ranging effects has been revealed within the magazine Science.

The spaces lined through the initiative, as you’ll be able to see, unfold over in all probability a 5th of the rustic.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a dataset like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, advised me. He labored at the venture with a large number of others, together with his colleagues Marcello Canuto and Stephen Houston. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another 9 months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he stated. “They may have seemed exaggerated to some.”

The lidar information was once amassed no longer through self-driving vehicles, which appear to be the one automobiles bearing lidar we ever listen about, nor even through drones, however through conventional plane. That would possibly sound bulky, however the distances and landscapes concerned authorized not anything else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli defined. “In our case it was actually a twin engine plane flown down from Texas.”

The aircraft would made dozens of passes over a given house, a selected “polygon” in all probability 30 kilometers lengthy and 20 huge. Mounted beneath was once “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which just about says all of it: that is a heavy responsibility software, the scale of a fridge. But you wish to have that more or less device to pierce the cover and symbol the underlying panorama.

The many overlapping passes had been then collated and calibrated into a unmarried virtual panorama of exceptional element.

“It identified features that I had walked over — a hundred of times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But those buildings don’t determine themselves. There’s no laptop labeling device that appears on the three-D type and says, “this is a pyramid, this is a wall,” and so forth. That’s a process that handiest archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli stated. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery printed, for instance, a number of low linear options which may be natural or synthetic. It’s no longer all the time simple to inform the adaptation, however context and current scholarship fill within the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli stated — if you happen to had been questioning why it took 9 months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations at the maps. It must be famous that many of those options had through this level been verified through box expeditions. By consulting current maps and getting floor fact in particular person, they’d made positive that those weren’t phantom buildings or wishful considering. “We’re confident that they’re all there,” he advised me.

“Next is the quantitative step,” he persisted. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other dataset: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the purpose the place the imagery begins to move from level cloud to educational learn about. After all, it’s widely recognized that the Maya had a massive town on this house; it’s been intensely studied for many years. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) learn about was once supposed to advance past the normal strategies hired prior to now.

“It’s a massive dataset. It’s a massive pass phase of the Maya lowlands,” Estrada-Belli stated. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he stated, quite wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a consequence the paper comprises a wide variety of latest theories and conclusions, from inhabitants and financial system estimates, to cultural and engineering wisdom, to the timing and nature of conflicts with neighbors.

The ensuing file doesn’t simply advance the data of Mayan tradition and generation, however the science of archaeology itself. It’s iterative, in fact, like the whole thing else — Estrada-Belli famous that they had been impressed through paintings finished through colleagues in Belize and Cambodia; their contribution, then again, exemplifies new approaches to dealing with massive spaces and big datasets.

The extra experiments and box paintings, the extra established those strategies will change into, and the better they are going to be authorised and replicated. Already they have got confirmed themselves helpful, and this learn about is in all probability the most productive instance of lidar’s possible within the box.

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” defined co-author Stephen Houston (additionally from Tulane) in an e-mail. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” identified co-author Thomas Garrison in an e-mail. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery too can display the level of looting, he wrote, and assist cultural government supply in opposition to it through being acutely aware of relics and websites prior to the looters are.

The researchers are already making plans a 2d, even better set of flyovers, based at the good fortune of the primary experiment. Perhaps by the point the preliminary bodily paintings is finished the trendier equipment of the previous couple of years will make themselves appropriate.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli prompt. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s additionally keen on the speculation of striking the knowledge on-line so citizen archaeologists can assist pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he stated.

But as his colleagues indicate, even years on this line of labor are essentially initial.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was once revealed these days in Science; you’ll be able to find out about their conclusions (which might be of extra passion to the archaeologists and anthropologists amongst our readers) there, and practice different paintings being undertaken through the Fundación Pacunam at its site.

How aerial lidar illuminated a Mayan megalopolis – TechCrunch

Archaeology would possibly not be the perhaps position to search out the newest in generation — AI and robots are of doubtful software within the painstaking fieldwork concerned — however lidar has confirmed transformative.

How aerial lidar illuminated a Mayan megalopolis – TechCrunch Archaeology would possibly not be the perhaps position to search out the newest in generation — AI and robots are of doubtful software within the painstaking fieldwork concerned — however lidar has confirmed transformative.

[saltysuittaco-blog]

Archaeology would possibly not be the perhaps position to search out the newest in generation — AI and robots are of doubtful software within the painstaking fieldwork concerned — however lidar has confirmed transformative. The newest accomplishment the usage of laser-based imaging maps 1000’s of sq. kilometers of an historical Mayan town as soon as thousands and thousands robust, however the researchers make it transparent that there’s no technological change for revel in and a just right eye.

The Pacunam Lidar Initiative started two years in the past, bringing in combination a team of students and native government to adopt the most important but survey of a secure and long-studied area in Guatemala. Some 2,144 sq. kilometers of the Maya Biosphere Reserve in Petén had been scanned, inclusive of and round spaces identified to be settled, advanced, or in a different way of significance.

Preliminary imagery and knowledge illustrating the good fortune of the venture had been introduced previous this yr, however the researchers have now carried out their precise analyses at the information, and the ensuing paper summarizing their wide-ranging effects has been revealed within the magazine Science.

The spaces lined through the initiative, as you’ll be able to see, unfold over in all probability a 5th of the rustic.

“We’ve never been able to see an ancient landscape at this scale all at once. We’ve never had a dataset like this. But in February really we hadn’t done any analysis, really, in a quantitative sense,” co-author Francisco Estrada-Belli, of Tulane University, advised me. He labored at the venture with a large number of others, together with his colleagues Marcello Canuto and Stephen Houston. “Basically we announced we had found a huge urban sprawl, that we had found agricultural features on a grand scale. After another 9 months of work we were able to quantify all that and to get some numerical confirmations for the impressions we’d gotten.”

“It’s nice to be able to confirm all our claims,” he stated. “They may have seemed exaggerated to some.”

The lidar information was once amassed no longer through self-driving vehicles, which appear to be the one automobiles bearing lidar we ever listen about, nor even through drones, however through conventional plane. That would possibly sound bulky, however the distances and landscapes concerned authorized not anything else.

“A drone would never have worked — it could never have covered that area,” Estrada-Belli defined. “In our case it was actually a twin engine plane flown down from Texas.”

The aircraft would made dozens of passes over a given house, a selected “polygon” in all probability 30 kilometers lengthy and 20 huge. Mounted beneath was once “a Teledyne Optech Titan MultiWave multichannel, multi-spectral, narrow-pulse width lidar system,” which just about says all of it: that is a heavy responsibility software, the scale of a fridge. But you wish to have that more or less device to pierce the cover and symbol the underlying panorama.

The many overlapping passes had been then collated and calibrated into a unmarried virtual panorama of exceptional element.

“It identified features that I had walked over — a hundred of times!” he laughed. “Like a major causeway, I walked over it, but it was so subtle, and it was covered by huge vegetation, underbrush, trees, you know, jungle — I’m sure that in another 20 years I wouldn’t have noticed it.”

But those buildings don’t determine themselves. There’s no laptop labeling device that appears on the three-D type and says, “this is a pyramid, this is a wall,” and so forth. That’s a process that handiest archaeologists can do.

“It actually begins with manipulating the surface data,” Estrada-Belli stated. “We get these surface models of the natural landscape; each pixel in the image is basically the elevation. Then we do a series of filters to simulate light being projected on it from various angles to enhance the relief, and we combine these visualizations with transparencies and different ways of sharpening or enhancing them. After all this process, basically looking at the computer screen for a long time, then we can start digitizing it.”

“The first step is to visually identify features. Of course, pyramids are easy, but there are subtler features that, even once you identify them, it’s hard to figure out what they are.”

The lidar imagery printed, for instance, a number of low linear options which may be natural or synthetic. It’s no longer all the time simple to inform the adaptation, however context and current scholarship fill within the gaps.

“Then we proceeded to digitize all these features… there were 61,000 structures, and everything had to be done manually,” Estrada-Belli stated — if you happen to had been questioning why it took 9 months. “There’s really no automation because the digitizing has to be done based on experience. We looked into AI, and we hope that maybe in the near future we’ll be able to apply that, but for now an experienced archaeologist’s eye can discern the features better than a computer.”

You can see the density of the annotations at the maps. It must be famous that many of those options had through this level been verified through box expeditions. By consulting current maps and getting floor fact in particular person, they’d made positive that those weren’t phantom buildings or wishful considering. “We’re confident that they’re all there,” he advised me.

“Next is the quantitative step,” he persisted. “You measure the length and the areas and you put it all together, and you start analyzing them like you’d analyze other dataset: the structure density of some area, the size of urban sprawl or agricultural fields. Finally we even figured a way to quantify the potential production of agriculture.”

This is the purpose the place the imagery begins to move from level cloud to educational learn about. After all, it’s widely recognized that the Maya had a massive town on this house; it’s been intensely studied for many years. But the Pacunam (which stands for Patrimonio Cultural y Natural Maya) learn about was once supposed to advance past the normal strategies hired prior to now.

“It’s a massive dataset. It’s a massive pass phase of the Maya lowlands,” Estrada-Belli stated. “Big data is the buzzword now, right? You truly can see things that you would never see if you only looked at one site at a time. We could never have put together these grand patterns without lidar.”

“For example, in my area, I was able to map 47 square kilometers over the course of 15 years,” he stated, quite wistfully. “And in two weeks the lidar produced 308 square kilometers, to a level of detail that I could never match.”

As a consequence the paper comprises a wide variety of latest theories and conclusions, from inhabitants and financial system estimates, to cultural and engineering wisdom, to the timing and nature of conflicts with neighbors.

The ensuing file doesn’t simply advance the data of Mayan tradition and generation, however the science of archaeology itself. It’s iterative, in fact, like the whole thing else — Estrada-Belli famous that they had been impressed through paintings finished through colleagues in Belize and Cambodia; their contribution, then again, exemplifies new approaches to dealing with massive spaces and big datasets.

The extra experiments and box paintings, the extra established those strategies will change into, and the better they are going to be authorised and replicated. Already they have got confirmed themselves helpful, and this learn about is in all probability the most productive instance of lidar’s possible within the box.

“We simply would not have seen these massive fortifications. Even on the ground, many of their details remain unclear. Lidar makes most human-made features clear, coherent, understandable,” defined co-author Stephen Houston (additionally from Tulane) in an e-mail. “AI and pattern recognition may help to refine the detection of features, and drones may, we hope, bring down the cost of this technology.”

“These technologies are important not only for discovery, but also for conservation,” identified co-author Thomas Garrison in an e-mail. “3D scanning of monuments and artifacts provide detailed records and also allow for the creation of replicas via 3D printing.”

Lidar imagery too can display the level of looting, he wrote, and assist cultural government supply in opposition to it through being acutely aware of relics and websites prior to the looters are.

The researchers are already making plans a 2d, even better set of flyovers, based at the good fortune of the primary experiment. Perhaps by the point the preliminary bodily paintings is finished the trendier equipment of the previous couple of years will make themselves appropriate.

“I doubt the airplanes are going to get less expensive but the instruments will be more powerful,” Estrada-Belli prompt. “The other line is the development of artificial intelligence that can speed up the project; at least it can rule out areas, so we don’t waste any time, and we can zero in on the areas with the greatest potential.”

He’s additionally keen on the speculation of striking the knowledge on-line so citizen archaeologists can assist pore over it. “Maybe they don’t have the same experience we do, but like artificial intelligence they can certainly generate a lot of good data in a short time,” he stated.

But as his colleagues indicate, even years on this line of labor are essentially initial.

“We have to emphasize: it’s a first step, leading to innumerable ideas to test. Dozens of doctoral dissertations,” wrote Houston. “Yet there must always be excavation to look under the surface and to extract clear dates from the ruins.”

“Like many disciplines in the social sciences and humanities, archaeology is embracing digital technologies. Lidar is just one example,” wrote Garrison. “At the same time, we need to be conscious of issues in digital archiving (particularly the problem of obsolete file formatting) and be sure to use technology as a complement to, and not a replacement for methods of documentation that have proven tried and true for over a century.”

The researchers’ paper was once revealed these days in Science; you’ll be able to find out about their conclusions (which might be of extra passion to the archaeologists and anthropologists amongst our readers) there, and practice different paintings being undertaken through the Fundación Pacunam at its site.

How aerial lidar illuminated a Mayan megalopolis – TechCrunch Archaeology would possibly not be the perhaps position to search out the newest in generation — AI and robots are of doubtful software within the painstaking fieldwork concerned — however lidar has confirmed transformative.