As the human population continues to grow exponentially we develop more and more natural land to build cities, factories, croplands, and numerous other man-made structures. Since 2001 the population in Asia alone has grown by more than a billion people, with 50% of people living in urban areas. It is important to be able to visualize this human impact on the natural world as we move towards a future where more and more resources and space will be necessary to keep up with the growing population. In the animation above we can see this human encroachment in Asia (with urban areas and cropland represented by red and green respectively) on undeveloped land (in white) throughout 2001-2018.
The data visualized above is the Land Cover Climate Modeling Grid collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor that is onboard the Terra1 and Aqua2 satellites. Terra passes from north to south across the equator each morning, while Aqua passes south to north over the equator each afternoon. The data contains values representing different land cover types ranging from 0 to 16.
MODIS Land Cover Type data sets were downloaded in HDF3format (specifically hdf4) from the Land Processes Distributed Active Archive Center (LP DAAC) for each year from 2001-2018. Each HDF4 file contained multiple subdatasets, data from “Majority_Land_Cover_Type_1” variable were extracted from each file and put into yearly raster files (.txt) in ASCII format with a computer program written in Python4 with the assistance of gdal5. To better show urbanization and development of land, all undeveloped land cover types were reclassified as value 1, cropland as value 2, and urban land cover as 3. Water remained the same as 0.
For each raster file, the data was visualized in QGIS6 and exported to PNG7 image format. Each image was loaded into GIMP8, zoomed in onto Asia and exported as an animated GIF9. This GIF was then converted to a .mp4 using FFmpeg10.
Original Data Set Values:
| Land Cover Type | Raster Value |
|---|---|
| Water | 0 |
| Evergreen Needleleaf Forest | 1 |
| Evergreen Broadleaf Forest | 2 |
| Deciduous Needleleaf Forest | 3 |
| Deciduous Broadleaf Forest | 4 |
| Mixed Forests | 5 |
| Closed Shrublands | 6 |
| Open Shrublands | 7 |
| Woody Savannas | 8 |
| Savannas | 9 |
| Grasslands | 10 |
| Permanent Wetlands | 11 |
| Croplands | 12 |
| Urban and Built-up | 13 |
| Natural Vegetation Mosaic | 14 |
| Snow and Ice | 15 |
| Barren or Sparsely Vegetated | 16 |
Modified Data Set Values:
| Land Cover Type | Raster Value |
|---|---|
| Water | 0 |
| Undeveloped Land (1-11, 14-16) | 1 |
| Croplands | 2 |
| Urban and Built-up | 3 |
Author: Emma Strickland. Last edited: 2020-04-28
About Terra. NASA.gov. Online: https://terra.nasa.gov/about↩︎
About Aqua. Nasa.gov. Accessed 2020-04-28. Online: https://eospso.nasa.gov/missions/aqua↩︎
Hierarchical Data Format. Copyright 2006–2019. The HDF Group. Online: https://www.hdfgroup.org/↩︎
Python. Copyright (C) 2001–2019. Python Software Foundation. Online: https://www.python.org/↩︎
Translator library for raster and vector geospatial data format. Online: https://gdal.org/↩︎
QGIS. Software released through CC-BY-SA by the QGIS Development Team. Online: https://www.qgis.org↩︎
Portable Network Graphics (PNG). Copyright 1995–2019 Greg Roelofs. Online: http://www.libpng.org/pub/png/↩︎
GNU Image Manipulation Program (GIMP). Software released through CC-BY-SA by The GIMP Development Team. Online: https://www.gimp.org/↩︎
Graphics Interchange Format (GIF). Copyright 1987–1990 CompuServe. Online: https://www.w3.org/Graphics/GIF/spec-gif89a.txt↩︎
Moving Picture Experts Group Standard 4 (MPEG-4). Online: https://mpeg.chiariglione.org/↩︎