Methods

To complete this project, we will be applying NDVI change detection to the three study areas nightlight analysis to the study areas and Syria as a whole.

Nightlight Data

For the nightlight imagery, we used Defense Meteorological Satellite Program (DMSP) data. We downloaded cloud-free composite imagery for the years 2010, 2011, 2012, and 2013. The imagery covers the time period of the ongoing Syrian Civil War, but more recent DMSP data is not available to represent ISIS occupation. For this reason, we also downloaded Tile 2 Visible Infrared Imaging Radiometer Suite (VIIRS) for the dates January 1, 2014 and January 1, 2015. Data from 2016 is not currently available. The DMSP and VIIRS data was downloaded from the NOAA/NCEI Earth Observation Group database. Additionally, vector shapefiles of Syrian boundaries and cities were downloaded to overlay on the satellite imagery.

Initially, the DMSP images (2010, 2011, 2012, 2013) were loaded into the software ENVI for analysis. The vector shapefiles of Syria were also uploaded. A Linear 1% stretch was applied to better view the nightlight contrast. The DMSP images were all subsetted using the Syria shapefile to create a more targetted analysis. Each subdistrict was also subsetted out so that the study areas could have specific change statistics obtained. After subsetting, a change detection was done using 2010 as the initial and 2013 as the final image. The resulting image was loaded into ArcMap software for further editing and final map production. In ArcMap, the raster change detection image had the color scheme changed from the default (which has blue as loss and red as gain) to something more appropriate. Boundary outlines and labels were added for clarity. The DMSP subsetted imagery was also uploaded into ArcMap so that brightness value maps for all of Syria could be created, using the digital number 0-63 that represents light intensity. The compute statistics function was applied for each year and study area. The average nightlight value was recorded and put into a line graph to show the change over time. The percentage change was also calculated and put into a bar graph. This exact process was repeated for each year and study area. For the VIIRS imagery, the same process was executed, but the January 1, 2014 image was the initial and the January 1, 2015 image was the final for the change detection. The VIIRS data is more suited for ISIS analysis while the DMSP data shows the Syrian Civil War changes well, due to date availability.

The results of the nightlight study were uploaded into Google Earth and the .kmz files are available.

NDVI Change Detection

In order to study the effects of ISIS on Syria first we downloaded data from GLOVIS using images from the Landsat 5 and Landsat 8 satellites. The sensors used were Thematic Mapper (TM) from Landsat 5 and the Operational Land Imager (OLI) on Landsat 8. We picked months that were consistent to eliminate seasonal variability from plant quality change. Cloud cover was also considered when data sets were downloaded, which are why Ar-Raqqa and Tadmor use different months in our analysis.

In the software platform ENVI, images were analyzed using a combination of bands, 3-4-3 (Landsat 5) and 4-5-4 (Landsat 8), that utilizes a combination of infrared and red visible light wavelengths to create an image that highlights healthy biomass. We also viewed the imagery in the band combination 5-6-4 (Landsat 8) to emphasize land and water. Next, a Normalized Difference Vegetation Index (NDVI) was applied to the regions of interest. The NDVI measures the greenness of the areas which is an indicator of healthy agriculture in the region. After applying an NDVI analysis to images taken before ISIS occupation and images taken during the occupation of Syria, a difference map was compiled. This difference map measures the NDVI difference and clearly shows areas of increased greenness and areas where vegetation has diminished. The dates differ depending on the study area due to the differing times of ISIS occupation. The before imagery date for Ar-Raqqa was September 9, 2011 and the after imagery date was October 10, 2015. The before imagery date for Tadmor was November 30, 2014, and the after imagery date was November 1, 2015. The before imagery date for Lake Assad was September 9, 2011, and the after imagery date was October 10, 2015. The imagery dates are the same for Lake Assad and Ar-Raqqa because they are in the same path/row, but difference region of interests were used for each study area.