Posts tagged Geospatial

The figure above is a [very] simple model displaying isostatic rebound of Greenland if its ice sheet were not present. The Greenland ice sheet (GISh) is 2,500 km north-south, 1,000 km east-west, 3 km thick, and covers almost 2 million square kilometers (or 80% of the island). Because of the weight of GISh, the continental lithosphere is depressed in an elastic motion. If the GISh were to be removed, the lithosphere would rise in reaction. This rebounding process is known as isostasy and in case of ice sheets, glacial rebound. Underneath any vast ice sheet is a land surface not unlike any other ice-free surface on earth. It has valleys, hills, plains, etc. Therefore, we see that in Greenland the underlying topography, the Bedrock (or simply the Bed), is shaped as a concave, and with the removal of the ice sheet it rises and assumes a less curved form. PS: Please note that this is purely for visualization purposes and not to be used in scientific analysis.

The figure above is a [very] simple model displaying isostatic rebound of Greenland if its ice sheet were not present. The Greenland ice sheet (GISh) is 2,500 km north-south, 1,000 km east-west, 3 km thick, and covers almost 2 million square kilometers (or 80% of the island). Because of the weight of GISh, the continental lithosphere is depressed in an elastic motion. If the GISh were to be removed, the lithosphere would rise in reaction. This rebounding process is known as isostasy and in case of ice sheets, glacial rebound.

Underneath any vast ice sheet is a land surface not unlike any other ice-free surface on earth. It has valleys, hills, plains, etc. Therefore, we see that in Greenland the underlying topography, the Bedrock (or simply the Bed), is shaped as a concave, and with the removal of the ice sheet it rises and assumes a less curved form.

PS: Please note that this is purely for visualization purposes and not to be used in scientific analysis.

Day in the life of a GIS Analyst

 

An abbreviated version of a typical day involving the duties of a GIS Analyst and Developer. Or maybe it’s just me.

Hour 1

Arrive to work before the sun does. Grab some coffee, catch up on email. Peruse the latest ArcUser and ArcNews and look at how easy it all should be.

Hour 2

Crap, all the Arc licenses are in use. Send out mass email to all users asking if someone can free one up. Ok, you have a license. One of your SDE databases is down, a ticket to ESRI has been sent. Use an old slower SDE. Begin running a geoprocessing task on a couple million polygons.

Hour 3

More coffee. Discover some internal web applications are not working because that single SDE is down. Send out email to users notifying of situation. Development IDE of choice crashes or freezes a few times to remind you that you are a bad person.

Hour 4

ArcMap crashes in the middle of editing. Try again, crap, cashed again. Try this one more… forget it, no more editing, just use draw tools to make quick exhibits.

Hour 5

More coffee. Given a PDF map that came from a consultant and asked make changes. That’s it, just a PDF. You do things to make this happen that make you feel dirty.

Hour 6

Lunch time. Ninety-percent of solutions to GIS questions or development issues are found on web sites that are blocked as Social Media or Blogs. Twitter rant (vis smartphone). Check that geoprocessing task is still running.

Hour 7

Rush request for exhibit that needs data on the SDE that is down. That particular dataset can also be found on an external hard drive. The enclosure died last month. Pry open enclosure, rip out hard drive, pop open work pc and manually plug it in to extract the data. Cross your fingers that no one from IT department walks in as the internals of your gutted work machine are exposed.

Hour 8

Seriously reconsidering your life decisions.

Hour 9

Geoprocessing task failed around the 8-hour 5-minute mark with geometry errors. After 40 minutes is still cancelling itself. Go home and drink to forget.

Note: No actual analysis got done, as the failed geoprocessing task squashed that goal.

Source: Rene R.

odoe.net

One of the projects we’re working on here at the Lamont-Doherty Earth Observatory is assessing spatial extent of subglacial features under the Greenland ice sheet using airborne geophysics. This is to better understand the dynamics of the ice sheet and to monitor the affects of climate change on its flow.

One of the projects we’re working on here at the Lamont-Doherty Earth Observatory is assessing spatial extent of subglacial features under the Greenland ice sheet using airborne geophysics. This is to better understand the dynamics of the ice sheet and to monitor the affects of climate change on its flow.

Urbanization in Dubai Between 1973 and 2006

Urbanization of Dubai, United Arab Emirates

Larger Images: 

Between 1973 and 2006 dramatic changes along the coast of the United Arab Emirates follow the development of Dubai, one of the country’s seven emirates. The country is located along the eastern coast of the Arabian Peninsula where the land tapers to a sharp tip that nearly separates the Persian Gulf to the north from the Gulf of Oman to the south. This trio of images from NASA’s series of Landsat satellites shows the remarkable transformation.

Going back in time, the evidence of human engineering nearly vanishes. In the top image, captured on October 11, 2006, artificial islands shaped like palm trees stretch along the shore. Inland, irrigated vegetation stands out in red (the image is enhanced with infrared light) against the tan-colored desert. Developed areas, including numerous roads, appear cement-colored. In the middle image, captured on August 28, 1990, the number and density of roads and buildings is far less than in 2006. The area to the southwest of image center is particularly less developed. Going all the way back to January 22, 1973, the roads reaching into the desert from the coast are indistinct or absent. Very little development appears to exist along the coast. Empty sand stretches southwestward from the inlet in image center.

The city of Dubai is home to more than 1.2 million people, and it is still growing rapidly. The city’s emergence as a major metropolis and tourist destination is evident in these images.

earthobservatory.nasa.gov

NASA Earth Observatory - Pakistan Floods

Flooding in Southern Pakistanacquired September 21, 2011 - download large image (9 MB, JPEG)

Flooding in Southern Pakistanacquired September 22, 2009 - download large image (7 MB, JPEG)

Flood waters lingered in southern Pakistan in late September 2011, where heavy rains inundated Balochistan and Sindh Provinces. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured the top image on September 21, 2011. For comparison, the bottom image shows the same region two years earlier, on September 22, 2009.

These images show a portion of the Indus River Valley where it nears the coast. Both images use a combination of infrared and visible light to increase contrast between water and land. Water varies in color from electric blue to navy. Vegetation is green and bare ground is pinkish brown. Clouds are pale blue-green and cast shadows.

In 2010, floods devastated much of the country. The floods that struck in 2011 were concentrated in the south—an unusual location for heavy monsoon rains.

Northwest of the Indus River, water lingers on normally arid land in Balochistan Province in late September 2011, although the flooding here appears slightly less severe than earlier in the month. Pools of water also occur along the coast west of Karachi.

An extensive irrigation network surrounds to the Indus River, designed to make use of water that is normally scarce. Canals link Lake Hamal and Manchhar (or Manchar) Lake. Compared to 2009, water is higher in these lakes in 2011, although this may be partly due to lingering effects of the 2010 floods. Water is also higher in the Indus River.

The highest water is apparent in Sindh Province east of the Indus. Large pools of flood water rest on what was dry land two years earlier. According to The International News, the Humanitarian Coordinator for the United Nations stated that 1.8 million people had been displaced in Pakistan, 64 percent of the Pakistanis in the flood-affected areas lacked clean drinking water, and 67 percent of the region’s food stock had been lost.

References

  1. The International News. (2011, September 19). UN launches $356 million appeal for flood-hit Pakistan. Accessed September 21, 2011.
  2. Associated Press of Pakistan. (2011, September 18). Devastation far beyond initially presumed, says Gilani. The Express Tribune. Accessed September 21, 2011.

NASA image courtesy MODIS Rapid Response Team at NASA GSFC. Caption by Michon Scott.

earthobservatory.nasa.gov

The organized chaos of my desk at work.

The organized chaos of my desk at work.

After having been to northern Greenland (Thule Air Base) for the first time back in May (see Part I & Part II), there might be a chance that I’ll travel down to the southern tip of South America in November. The Antarctic part of NASA Operation IceBridge (OIB) is based at Punta Arenas, Chile, and involves science flights on the NASA DC-8 over Antarctica to take airborne remote sensing measurements similar to those taken in the Arctic. The image above displays a segment of the flight plan over Antarctica that covers Recovery (including Recovery Ice Stream), Slessor Glaciers and the Bailey Ice Stream. There will also be flights that go further inland to the Recovery Subglacial Lakes, part of which was covered by the AGAP project during the International Polar Year 2007/2008.

After having been to northern Greenland (Thule Air Base) for the first time back in May (see Part I & Part II), there might be a chance that I’ll travel down to the southern tip of South America in November. The Antarctic part of NASA Operation IceBridge (OIB) is based at Punta Arenas, Chile, and involves science flights on the NASA DC-8 over Antarctica to take airborne remote sensing measurements similar to those taken in the Arctic.

The image above displays a segment of the flight plan over Antarctica that covers Recovery (including Recovery Ice Stream), Slessor Glaciers and the Bailey Ice Stream. There will also be flights that go further inland to the Recovery Subglacial Lakes, part of which was covered by the AGAP project during the International Polar Year 2007/2008.

This month marks my one year anniversary working at the Lamont-Doherty Earth Observatory of Columbia University. One of the earliest projects I’ve been working on was the Antarctica’s Gamburtsev Province (AGAP). The figures above display the bedrock topography of central Antarctica under the East Antarctic Ice Sheet. The “Before” figure is a subset of the digital elevation model of Antarctic bedrock created by the British Antarctic Survey (BAS) using data from surveys from the past 50 years. BAS is currently working on a second version of BEDMAP. The “After” figure displays a grid of study area using data collected during AGAP. As you can see, AGAP provided the scientific community with previously unknown topographic detail of the Antarctic bedrock. Both “Before” and “After” figures have outline vectors of the AGAP survey flights overlain. Here is a quick primer on the AGAP project: During the International Polar Year 2007 – 2009, scientists from six nations collaborated on a multi-disciplinary investigation of the Gamburtsevs, the least explored mountain range on Earth buried beneath the East Antarctic Ice Sheet, as part of the Antarctic Gamburtsev Province (AGAP) project. The AGAP project collected more than 120,000 line km of new aerogeophysical data using two Twin Otter aircraft.  Data included ice penetrating radar, magnetometer, gravimeter and laser altimeter measurements. The main AGAP survey grid included north-south lines spaced 5 km apart, with crossing lines every 33 km and transects over the Vostok Subglacial Highlands, South Pole and southern Recovery lakes region. 150-MHz ice penetrating radars with bandwidths of 15 to 20 MHz measured ice thickness, bedrock topography, sub-ice hydrology, and produced high-resolution images of the internal structure of the East Antarctic Ice Sheet. Magnetic data map geologic structures across the mountain range, while gravity data provide new insights into the tectonic evolution and crustal thickness of the region. A swath-scanning laser altimeter with a spatial resolution of 2 meters measured elevation and details of the ice surface.

This month marks my one year anniversary working at the Lamont-Doherty Earth Observatory of Columbia University. One of the earliest projects I’ve been working on was the Antarctica’s Gamburtsev Province (AGAP).

The figures above display the bedrock topography of central Antarctica under the East Antarctic Ice Sheet. The “Before” figure is a subset of the digital elevation model of Antarctic bedrock created by the British Antarctic Survey (BAS) using data from surveys from the past 50 years. BAS is currently working on a second version of BEDMAP. The “After” figure displays a grid of study area using data collected during AGAP. As you can see, AGAP provided the scientific community with previously unknown topographic detail of the Antarctic bedrock. Both “Before” and “After” figures have outline vectors of the AGAP survey flights overlain.

Here is a quick primer on the AGAP project:

During the International Polar Year 2007 – 2009, scientists from six nations collaborated on a multi-disciplinary investigation of the Gamburtsevs, the least explored mountain range on Earth buried beneath the East Antarctic Ice Sheet, as part of the Antarctic Gamburtsev Province (AGAP) project.

The AGAP project collected more than 120,000 line km of new aerogeophysical data using two Twin Otter aircraft.  Data included ice penetrating radar, magnetometer, gravimeter and laser altimeter measurements. The main AGAP survey grid included north-south lines spaced 5 km apart, with crossing lines every 33 km and transects over the Vostok Subglacial Highlands, South Pole and southern Recovery lakes region. 150-MHz ice penetrating radars with bandwidths of 15 to 20 MHz measured ice thickness, bedrock topography, sub-ice hydrology, and produced high-resolution images of the internal structure of the East Antarctic Ice Sheet. Magnetic data map geologic structures across the mountain range, while gravity data provide new insights into the tectonic evolution and crustal thickness of the region. A swath-scanning laser altimeter with a spatial resolution of 2 meters measured elevation and details of the ice surface.

Over the past rainy NYC weekend, I was working on Landsat ETM+ imagery of Dubai from 2008. However, the ETM+ Scan Line Corrector (SLC) being inoperational since May 2003, there were a number of data gaps in the form of diagonal striations (A). Most of Dubai lies in the unaffected zone, and the part that is affected is comprised of relatively narrow bands that were 150m wide at their thickest and 60m wide at their narrowest. So, the data gaps had to be filled since NoData values tend to corrupt analyses of the imagery. I used a cubic spline interpolation algorithm in MATLAB to fill the regions that had no data because the interpolation error was low even when using low degree polynomials for the spline. MATLAB performs a one-dimensional interpolation by fitting the supplied data with polynomial functions between data points and evaluating the appropriate function at the desired interpolation points. This technique proved successful, as the resultant scene (B) was free of data gaps.  Some readers have contacted me asking if they could have a copy of the MATLAB script, so I’ve uploaded here. Enjoy!

Over the past rainy NYC weekend, I was working on Landsat ETM+ imagery of Dubai from 2008. However, the ETM+ Scan Line Corrector (SLC) being inoperational since May 2003, there were a number of data gaps in the form of diagonal striations (A). Most of Dubai lies in the unaffected zone, and the part that is affected is comprised of relatively narrow bands that were 150m wide at their thickest and 60m wide at their narrowest. So, the data gaps had to be filled since NoData values tend to corrupt analyses of the imagery.

I used a cubic spline interpolation algorithm in MATLAB to fill the regions that had no data because the interpolation error was low even when using low degree polynomials for the spline. MATLAB performs a one-dimensional interpolation by fitting the supplied data with polynomial functions between data points and evaluating the appropriate function at the desired interpolation points. This technique proved successful, as the resultant scene (B) was free of data gaps. 

Some readers have contacted me asking if they could have a copy of the MATLAB script, so I’ve uploaded here. Enjoy!

IceBridge, a six-year NASA mission, is the largest airborne survey of Earth’s polar ice ever flown. It will yield an unprecedented three-dimensional view of Arctic and Antarctic ice sheets, ice shelves and sea ice. These flights will provide a yearly, multi-instrument look at the behavior of the rapidly changing features of the Greenland and Antarctic ice.

Data collected during IceBridge will help scientists bridge the gap in polar observations between NASA’s Ice, Cloud and Land Elevation Satellite (ICESat) — in orbit since 2003 — and ICESat-2, planned for late 2015. ICESat stopped collecting science data in 2009, making IceBridge critical for ensuring a continuous series of observations.

IceBridge will use airborne instruments to map Arctic and Antarctic areas once a year. IceBridge flights were conducted in March/May 2009 and 2010 over Greenland and in October/November 2009 and 2010 over Antarctica. Other smaller airborne surveys around the world are also part of the IceBridge campaign.