Vegetation Indices Products 16 and Monthly time scales & 250m-5600m resolution
The 500m 16-day Vegetation Indices product provides consistency for usage and centers blue at 469nm, red at 645nm, and NIR to 858nm which are used to defined daily vegetation indices. It tries to maintain sensitivity over dense areas (which we are interested in) and uses the EVI(Enhanced Vegetation Index) to correct for atmospheric contamination by smoke and sub-pixel thin clouds. The product is computed from a corrected product. The data is aimed for use in monitoring land cover changes as well as inputs for modeling climate change.
The lower resolution MOD13A2 is the same sort of thing but at 1000m instead. The 250m band since it lacks a 250m blue band it uses the 500m to correct for atmospheric effects. The image of this one looks less crisp than the 500m one. The 1000m monthly image uses a weighted average of the the data if it is cloud free.
Burned Area Monthly 500m
Uses daily surface reflectance values to look for rapid changes indicative of burning and maps the extent of recent fires only. It gives a quality "score" per pixel. It is based on 3 months of corrected daily reflectance data
Thermal Anomalies and fire at 1000m and 5 min, Daily, and 8 day time scales
It derives these areas from micrometer radiances based on its difference from background and is used to advance the monitoring of fires globally. The Daily one has three dimensions, the fire-mask, fire radiative power, and are given for an 8-day period. The 8 day product gives the average of these days which gives a fire-mask and the algorithm quality.
Leaf Area Index 8 day time scale 1000m resolution
It defines the number of equivalent layers of leaves per unit ground area and are used to calculated surface photosynthesis etc.
Land Cover Type Yearly Time scale and 1000m and 5600m
Taking a years worth of data it classifies the areas into 17 different classes defined by the International geosphere Biosphere Programme.
Opinion
The one 250m product seems too derived to work well but the multiple 500m look useful. However, these are much bigger than we really want to use. The 1000m are useful if we want to look at more 'general' trends that is not the focus. I think the combined burned, a vegetation index, and a leaf area index would be most useful. Preferably at 500m and looking at the daily to 16-day cycles rather than the monthly.
Thursday, April 28, 2011
Day 7-Readings
So yesterday I was able to catch up on some reading mostly on remote sensing projects in the Mediterranean region. Each article had a different focus and use different data sources, two of which were not sensors we had thought to use in this project. These are summaries for only two of them.
Estimating spectral separability of satellite derived parameters for burned areas mapping in the Calabria region by using SPOT-Vegetation data 2006
The study area for this article was Southern Italy and compared known burned areas to their image on remotely sensed data. They chose to do this because of the affect of wildfires in the Mediterranean region since a small fire can in fact have a big impact. Their overarching purpose was to see if remote sensing could help to evaluate the disturbance by fire of and testing fire models. They used 10-image composites from June till September 1998 received from the Vlaamse Instelling voor Technologisch Ondersock (VITO) Image Processing center which has free vegetation products. They then compared this to the Italian National Forestry Services record of fires for that time period. They eventually came up with different indices depending on the area within their study zone. They suggest that a better exploration would be to discrimination of areas depending on the land cover type, such as pasture v. forests, and that their processes could be applied using different sensors, such as MODIS-Terra.
An integrated spatial and spectral approach to the classification of Mediterranean land cover types: the SSC Method 2004
This explores a new way of classifying remotely sensed data by taking into account the idea that undefined pixels are most likely to be closely related to those nearby. It wants to use this principle to help define "open" types of land cover that do not have definite boundaries, such as shrub vegetation or vineyards. They used ENVI to do their project and relied on three main steps in their method.
1) Stratification: which was used to find "homogeneous" regions based on spatial and spectral data.
2) Classification of those homogeneous regions
3) Classification of the rest of the "heterogeneous" image
They used a lot of equations to defined exactly how "similar" mixed pixels were and whether or not they could be incorporated into a closer homogeneous area. Using these principles and equations they compared their remotely sensed classification to ground proofing classifications. They tested two regions, one most open land and the other mostly farmland. They found that this method classified open area 8% better than the regular method but that "closed" areas did not have an improved classification. In their acknowledgements they state that their methods are available on request which might be useful for the what we are doing. However, its in ENVI which I don't know how to use.
Estimating spectral separability of satellite derived parameters for burned areas mapping in the Calabria region by using SPOT-Vegetation data 2006
The study area for this article was Southern Italy and compared known burned areas to their image on remotely sensed data. They chose to do this because of the affect of wildfires in the Mediterranean region since a small fire can in fact have a big impact. Their overarching purpose was to see if remote sensing could help to evaluate the disturbance by fire of and testing fire models. They used 10-image composites from June till September 1998 received from the Vlaamse Instelling voor Technologisch Ondersock (VITO) Image Processing center which has free vegetation products. They then compared this to the Italian National Forestry Services record of fires for that time period. They eventually came up with different indices depending on the area within their study zone. They suggest that a better exploration would be to discrimination of areas depending on the land cover type, such as pasture v. forests, and that their processes could be applied using different sensors, such as MODIS-Terra.
An integrated spatial and spectral approach to the classification of Mediterranean land cover types: the SSC Method 2004
This explores a new way of classifying remotely sensed data by taking into account the idea that undefined pixels are most likely to be closely related to those nearby. It wants to use this principle to help define "open" types of land cover that do not have definite boundaries, such as shrub vegetation or vineyards. They used ENVI to do their project and relied on three main steps in their method.
1) Stratification: which was used to find "homogeneous" regions based on spatial and spectral data.
2) Classification of those homogeneous regions
3) Classification of the rest of the "heterogeneous" image
They used a lot of equations to defined exactly how "similar" mixed pixels were and whether or not they could be incorporated into a closer homogeneous area. Using these principles and equations they compared their remotely sensed classification to ground proofing classifications. They tested two regions, one most open land and the other mostly farmland. They found that this method classified open area 8% better than the regular method but that "closed" areas did not have an improved classification. In their acknowledgements they state that their methods are available on request which might be useful for the what we are doing. However, its in ENVI which I don't know how to use.
Monday, April 25, 2011
Day 6-Landsat 5 and Landsat 7
So the Landsat System is a collection of satellites that have provided continuous information about the earth's surface. There have been 7 launches one of which (landsat 6) failed. The ones we want to focus on in this project are Landsat 5 and Landsat 7, although the strict focus is on landsat 5 since landsat 7 has some malfunctions causing spots on the images. They follow a ground track in a 185km swath that goes from north to south and around the same time every 16 or 18 days it passes over the same spot on the earth.
Landsat 5 combines a Multispectral scanner (MSS) with a Thematic Mapper (TM) to have four spectral bands from visible green to near-infrared and a shortwave infrared and an improve resolution of 120m with the thermal-IR band and of 30m on the rest of the available 6 bands. The .pdf at http://pubs.usgs.gov/fs/2010/3026/pdf/FS2010-3026.pdf also explains what each band means and what it can be used for. It also gives a pretty good description of landsat 7.
The malfunction I mentioned is described in this document as a "scan line corrector failure". I don't think its that great. There is apparently a way to "fix" it using the data but looking at figure 6 I don't think it is really as accurate as they want it to be.
Landsat 5 combines a Multispectral scanner (MSS) with a Thematic Mapper (TM) to have four spectral bands from visible green to near-infrared and a shortwave infrared and an improve resolution of 120m with the thermal-IR band and of 30m on the rest of the available 6 bands. The .pdf at http://pubs.usgs.gov/fs/2010/3026/pdf/FS2010-3026.pdf also explains what each band means and what it can be used for. It also gives a pretty good description of landsat 7.
The malfunction I mentioned is described in this document as a "scan line corrector failure". I don't think its that great. There is apparently a way to "fix" it using the data but looking at figure 6 I don't think it is really as accurate as they want it to be.
Day 6-Landsat
Much better website and the two interfaces to look for data are much better. However, the question or accessibility to cost eludes me. From the information in Sarah Parcak's book it could range from nothing to $600. The search tool on the Landsat website seems to make no reference to cost and on at least one page (http://pubs.usgs.gov/fs/2010/3026/pdf/FS2010-3026.pdf) there is a disclaimer stating "All USGS Landsat data acquired from 1972 to the present are available over the Internet at no charge and with no user restrictions." So it seems possible.
Accessing Data
The two different interfaces one can use to access the data are much better than those for MODIS and ASTER, though I think you can use them and I really should. Glovis (http://glovis.usgs.gov/)and EarthExplorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/) are graphical so you can look at the images you want to download. Although there is sort of odd coverage of places. I also think I need to register to download stuff directly. But much better than ASTER!
Accessing Data
The two different interfaces one can use to access the data are much better than those for MODIS and ASTER, though I think you can use them and I really should. Glovis (http://glovis.usgs.gov/)and EarthExplorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/) are graphical so you can look at the images you want to download. Although there is sort of odd coverage of places. I also think I need to register to download stuff directly. But much better than ASTER!
Day 6-ASTER, Cost
After poking around on a very, very bad website I finally found a costs table for the different data types available from ERSDAC website. Data levels 1-2 are 9,800 yen per scene which, at the current exchange rate, is about $120. Not too much, but truly not great, if we wanted to use more than one image that starts getting to be more than I'd like to spend. Also I am not quite sure if this is accurate anymore since it hasn't been updated sine March 2004 (at least this section of the webpage). I would assume then that it has gone up in the recent years but I can't know until I put in an order, which I am reluctant to do at the moment.
Though they do give a good flow chart as to what you should do with the webpage, found at http://www.gds.aster.ersdac.or.jp/gds_www2002/exhibition_e/a_products_e/set_a_produ_e.html.
On to Landsat-5
Though they do give a good flow chart as to what you should do with the webpage, found at http://www.gds.aster.ersdac.or.jp/gds_www2002/exhibition_e/a_products_e/set_a_produ_e.html.
On to Landsat-5
Day 6-ASTER, Data and Cost
The important stuff with this project is the cost of course and so I am going to explore some more the types of products and how much they will cost. I don't remember exactly what we were going to use the ASTER data for (I am pretty sure it was a veg index) but I'm not sure if its going to be of a resolution that we can use since 15m is still pretty big. Although it might not be too bad since it at least cuts down the patches we are looking at.
Data
Looking at http://asterweb.jpl.nasa.gov/data_products.asp for the data products. Each one has a labeled "level", "product" (by which they mean name), "description", "release status" (which relates to the accuracy of the data and its ability to be used in scientific publications), and "release notes".
Looking at the descriptions and a couple of the more in-depth descriptions provided by clicking on the "product" hyperlinks, I am unsure as to which product we want to be looking at. I think we want a "radiance" product preferably corrected for Atmospheric and topographic corrections. Actually I think we want Surface reflectance since I believe that is what will give a good spectral signature (for the maquis). That would therefore be the level 2 data. They have differing amounts of corrections for each but looking at AST07 Surface reflectance-VNIR,SWIR which has derived surface radiance with topographic corrections I am unsure about the product background info. It doesn't look like its been updated since 2002 and I wonder if there are better ways of looking at these things. It also has to be ordered, which I think is fine.
This particular product looks at 9 bands (band 1- band 9) as defined by March 2002 information. I apparently have to order all of my data through Glovis or WIST and the page doesn't really give good information about obtaining the data or using it and some of the links that it provides don't work. However, going to a different site does give more information ( https://lpdaac.usgs.gov/lpdaac/products/aster_products_table/on_demand/surface_radiance_vnir_crosstalk_corrected_swir/v1/ast_09xt) on these products.
Cost
Looking at the better ASTER information via the LP DAAC site it looks like only a global DEM and the ASTER L1B for the US and territories data is available at no charge and is available through WIST and GloVis. Higher Level data is available through Japan's Earth Remote Sensing Data Analysis Center (ERSDAC) at a charge. I will follow the link to see what sorts of charges there will be.
Data
Looking at http://asterweb.jpl.nasa.gov/data_products.asp for the data products. Each one has a labeled "level", "product" (by which they mean name), "description", "release status" (which relates to the accuracy of the data and its ability to be used in scientific publications), and "release notes".
Looking at the descriptions and a couple of the more in-depth descriptions provided by clicking on the "product" hyperlinks, I am unsure as to which product we want to be looking at. I think we want a "radiance" product preferably corrected for Atmospheric and topographic corrections. Actually I think we want Surface reflectance since I believe that is what will give a good spectral signature (for the maquis). That would therefore be the level 2 data. They have differing amounts of corrections for each but looking at AST07 Surface reflectance-VNIR,SWIR which has derived surface radiance with topographic corrections I am unsure about the product background info. It doesn't look like its been updated since 2002 and I wonder if there are better ways of looking at these things. It also has to be ordered, which I think is fine.
This particular product looks at 9 bands (band 1- band 9) as defined by March 2002 information. I apparently have to order all of my data through Glovis or WIST and the page doesn't really give good information about obtaining the data or using it and some of the links that it provides don't work. However, going to a different site does give more information ( https://lpdaac.usgs.gov/lpdaac/products/aster_products_table/on_demand/surface_radiance_vnir_crosstalk_corrected_swir/v1/ast_09xt) on these products.
Cost
Looking at the better ASTER information via the LP DAAC site it looks like only a global DEM and the ASTER L1B for the US and territories data is available at no charge and is available through WIST and GloVis. Higher Level data is available through Japan's Earth Remote Sensing Data Analysis Center (ERSDAC) at a charge. I will follow the link to see what sorts of charges there will be.
Day 6-ASTER, Intro and Instruments
Look at the ASTER Mission statement at http://asterweb.jpl.nasa.gov/mission.asp. It doesn't have as good of an interface as MODIS but it is not the worst I have ever seen. It collects 14 different bands of high spatial resolution data and goes from the visible to the thermal infrared wavelengths and can create DEMs. It give some suggestions for things you can do with the data, on their "science page". A few of the things they list, such as the "vegetation and ecosystem dynamics", "hazard monitoring", and "Land surface and land coverage change" are things that I am interested in. I just hope that they are not things that I would have to do myself.
Instruments
Under the instrument page (http://asterweb.jpl.nasa.gov/instrument.asp) they have some pretty cool semi-interactive drawings of the satellite but they are not of use to me. However, the exploration and explanation of the three subsystems are useful.
VNIR (visible and near infrared) has a resolution of 15m (better than MODIS!) and is probably the subsystem they use for making their DEMS. They use a combination of different filters to allow different bands to inspect the same ground with the a data rate of 62Mbps (don't know what that means exactly).
Shortwave Infrared (SWIR) which I think what was mentioned for use as a veg index but I don't remember. The SWIR has a 30m resolution but because of the combination of filters/detectors there is a parallax error of .5 pixels per 900m and it operates in 6 spectral bands in the near-IR region.
Thermal Infrared (TIR)of course looks at thermal infrared in 5 bands with a resolution of 90m. I am unsure exactly how we could use this and especially because this has the lowest resolution but it is still better than MODIS.
Instruments
Under the instrument page (http://asterweb.jpl.nasa.gov/instrument.asp) they have some pretty cool semi-interactive drawings of the satellite but they are not of use to me. However, the exploration and explanation of the three subsystems are useful.
VNIR (visible and near infrared) has a resolution of 15m (better than MODIS!) and is probably the subsystem they use for making their DEMS. They use a combination of different filters to allow different bands to inspect the same ground with the a data rate of 62Mbps (don't know what that means exactly).
Shortwave Infrared (SWIR) which I think what was mentioned for use as a veg index but I don't remember. The SWIR has a 30m resolution but because of the combination of filters/detectors there is a parallax error of .5 pixels per 900m and it operates in 6 spectral bands in the near-IR region.
Thermal Infrared (TIR)of course looks at thermal infrared in 5 bands with a resolution of 90m. I am unsure exactly how we could use this and especially because this has the lowest resolution but it is still better than MODIS.
Wednesday, April 20, 2011
Day 5-In Search of more readings
After last week's meeting I have more defined goals for what to do in the next couple of weeks:
1.) look for a spectral signature for Maquis
2.) And look for cost related things
3.) Tracking wild fires
I have found some reading material but they do require me to physically go places to collect the articles. I need to go to the engineering library to get a copy of the International Journal of Applied Earth Observation and Geoinformation, v2001 n2 which on pages 176-183 has an article about spectral signatures and Maquis.
I also found this downloadable article called "Mapping Mediterranean scrub with satellite imagery: biomass estimation and spectral behaviour" in the International Journal of Remote Sensing 2004. its about 11 pages and the study area is south central Portugal. It looks like they may be using a different sort of sensor than I'd like but the methods may be interesting and give me an idea of what I need to be looking for.
With my search words those were the only two articles that seem relevant to my topic.
However, I did find some more important articles that had to relate to tracking fires and the ASTER sensor we'd like to use (although not for burned data exactly). "Estimating subpixel fire sizes and temperatures from ASTER using multiple endmember spectral mixture analysis" is the article and its from 2009 so its one of the more recent publications and I can download it from UW to read. I also put on hold a different book from summit that deals with Mediterranean ecosystems and "wildland" fires.
Now I need time to read.
1.) look for a spectral signature for Maquis
2.) And look for cost related things
3.) Tracking wild fires
I have found some reading material but they do require me to physically go places to collect the articles. I need to go to the engineering library to get a copy of the International Journal of Applied Earth Observation and Geoinformation, v2001 n2 which on pages 176-183 has an article about spectral signatures and Maquis.
I also found this downloadable article called "Mapping Mediterranean scrub with satellite imagery: biomass estimation and spectral behaviour" in the International Journal of Remote Sensing 2004. its about 11 pages and the study area is south central Portugal. It looks like they may be using a different sort of sensor than I'd like but the methods may be interesting and give me an idea of what I need to be looking for.
With my search words those were the only two articles that seem relevant to my topic.
However, I did find some more important articles that had to relate to tracking fires and the ASTER sensor we'd like to use (although not for burned data exactly). "Estimating subpixel fire sizes and temperatures from ASTER using multiple endmember spectral mixture analysis" is the article and its from 2009 so its one of the more recent publications and I can download it from UW to read. I also put on hold a different book from summit that deals with Mediterranean ecosystems and "wildland" fires.
Now I need time to read.
Tuesday, April 12, 2011
Day 4-Continued-Success...
So, I have successfully downloaded tiles in the area that I am interested in! They look quite nice and I have georeferenced one of them to another one (benefits of this I am not yet sure). I did this since one of the tiles that I download did not have any spatial reference data so it was worthwhile to have it oriented in a similar fashion as the other stuff.
All of the following tiles (which I believe are the 16 or 8 day cycles of the burned terra product) seem to fit snugly around there. However, the 1km resolution that MODIS has really takes its toll on detail. The coastline is very rough and I am unsure in certain regions if the difference in value for the pixel is because of a burning event (as assumed by the title) or because it is under cloud cover.
The formation above some of these suggest cloud cover. However, I am still learning about this whole remote sensing dealio so I at least have good questions.
All of the following tiles (which I believe are the 16 or 8 day cycles of the burned terra product) seem to fit snugly around there. However, the 1km resolution that MODIS has really takes its toll on detail. The coastline is very rough and I am unsure in certain regions if the difference in value for the pixel is because of a burning event (as assumed by the title) or because it is under cloud cover.
The formation above some of these suggest cloud cover. However, I am still learning about this whole remote sensing dealio so I at least have good questions.
Day 4- Week 3
So I was able to open the .hdf file in ArcMap and fuss around with the colors so it looked like something I understood. Its still projected in the MODIS unique sinusoidal thing so although it looked a little bit (really really really little bit) like the coast I remember using for my midterm it is in fact not this area.
I thought it looked a bit like North Africa and southern Sardinia, which it is, at least when compared to google maps. I first opened it and added it as a RGB file because when you add the files singularly I couldn't make it look like anything. I had to change the symbology to stretched from RGB composite. Still playing around with it but there is quite a bit, in relation to options in the image, that I am unsure of what to do with.
However, the main problem is that the tile actually does not show the area I'm interested in! I need to look in another zone for it. So the search continues.
I thought it looked a bit like North Africa and southern Sardinia, which it is, at least when compared to google maps. I first opened it and added it as a RGB file because when you add the files singularly I couldn't make it look like anything. I had to change the symbology to stretched from RGB composite. Still playing around with it but there is quite a bit, in relation to options in the image, that I am unsure of what to do with.
However, the main problem is that the tile actually does not show the area I'm interested in! I need to look in another zone for it. So the search continues.
Monday, April 11, 2011
Day Something-Download
Downloading a modis tile from 2005 it takes a long time since there is so much data. I hope that I can open it.
Monday, April 4, 2011
Over the Weekend (aka Day 2)
Book 1
Read about 80 pages of Sarah Parcak's Satellite Remote Sensing for Archaeology. It gives a good (and brief) summary of the history of remote sensing in its second chapter and introduces some of the topics she will cover later in the book.
More important than that, although valuable, was her summary of the different types of satellite data available. She covered Landsat and ASTER, two of the sensors we thought about using, in detail and gave me a better feel for how to download the data.
Along with that help (including information about resolution etc. without having to go to individual sites although I will anyways) she talked about how to obtain the data. While she did not provide a step-by-step walkthrough of how to download the data (description of the interfaces), she did explain how some of the rights to the data worked and how to use them together (ie multiple band layers). The summaries suggest that in order to use some of the ASTER data some e-mails would need to be sent to their people in order to get the data for no cost. The only thing that she states as being free from ASTER are the DEMs. I need to look into this more especially since my advisor mentioned having an account so maybe extra e-mails would be unneccessary.
note to self attempt download of ASTER DEM
Complications with her discussion thus far
There is a significant difference between what Parcak is doing in her book and what exactly this project is about. The focus of the book is on the detection of archaeological sites from satellite data rather than picking places for survey which is the focus of this project. However, the two do come together when she talks about the detection particular tells that surrounded a known fortress.
So far as I understand the project, specific identification of archaeological material is not what we want. The steps I am taking are to pick good areas for survey only and ground proofing, instead of exploring the importance of the site, would be done to assess how well the categorization of land based on remote sensing data accurately represented good places to survey.
I hope she goes a bit more into the data analysis portion of remote sensing so that I have a better understanding for what I will be doing when it comes to looking and understanding the data.
Read about 80 pages of Sarah Parcak's Satellite Remote Sensing for Archaeology. It gives a good (and brief) summary of the history of remote sensing in its second chapter and introduces some of the topics she will cover later in the book.
More important than that, although valuable, was her summary of the different types of satellite data available. She covered Landsat and ASTER, two of the sensors we thought about using, in detail and gave me a better feel for how to download the data.
Along with that help (including information about resolution etc. without having to go to individual sites although I will anyways) she talked about how to obtain the data. While she did not provide a step-by-step walkthrough of how to download the data (description of the interfaces), she did explain how some of the rights to the data worked and how to use them together (ie multiple band layers). The summaries suggest that in order to use some of the ASTER data some e-mails would need to be sent to their people in order to get the data for no cost. The only thing that she states as being free from ASTER are the DEMs. I need to look into this more especially since my advisor mentioned having an account so maybe extra e-mails would be unneccessary.
note to self attempt download of ASTER DEM
Complications with her discussion thus far
There is a significant difference between what Parcak is doing in her book and what exactly this project is about. The focus of the book is on the detection of archaeological sites from satellite data rather than picking places for survey which is the focus of this project. However, the two do come together when she talks about the detection particular tells that surrounded a known fortress.
So far as I understand the project, specific identification of archaeological material is not what we want. The steps I am taking are to pick good areas for survey only and ground proofing, instead of exploring the importance of the site, would be done to assess how well the categorization of land based on remote sensing data accurately represented good places to survey.
I hope she goes a bit more into the data analysis portion of remote sensing so that I have a better understanding for what I will be doing when it comes to looking and understanding the data.
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