This remote sensing project was completed as an assignment for my Master’s program course, Environmental Data Science 220: Remote Sensing.
Project Details
This project was created to provide an introduction to using satellite data from the USGS Landsat 8 Level 2, Collection 2, Tier 1 sourced from Google Earth Engine for analysis to identify soil composition.
Landsat 8 is a joint effort between USGS and NASA, with data collected from 2013-04-11 to the present. This particular dataset is the atmospherically corrected surface reflectance and land surface temperature from the Landsat 8 OLI/TIRS sensors.
This project used the Google Earth Engine API to download Landsat 8 data in order to explore potential habitat for an endangered plant species. By comparing Normalized Difference Vegetation Index (NVDI) and optimal index factor (OIF) bands, this study was able to determine possible regions of high gypsum concentration in the Guadalupe Mountains. All analysis was completed in Jupyter Lab using Python.
Installation
Python Packages
eegeemappandaspprint
Usage
Identifying Gypsic Soils Using Landsat 8 Data Mapping habitat suitability for the identification and conservation of the Guadalupe Mountain necklacepod (Sophora gypsophila)
Sophora gypsophila is a G1 Critically Endangered shrub in the pea family endemic to a small area surrounding the Guadalupe mountains in Southeastern New Mexico and Western Texas. Part of what puts S. gypsophila at risk is the fact that it is a substrate obligate - in other words, it can only survive in a specific soil type. But this also gives us an advantage: it means that we can identify potentially suitable habitat simply by mapping the gypsic areas in the vicinity of existing populations of S. gypsophila and subsetting these areas by the plant’s known elevation range. This can be done using Landsat bands 1, 5, and 7, taking advantage of the fact that gypsic soils are highly reflective in band 5 but particularly nonreflective in band 7.
Real-color Landsat visualization
Potential suitable habitat for Sophora gypsophila is located in the Guadalupe Mountain range of southern New Mexico and western Texas. This region of interest was defined through research by Stafford et al. (2008). We set the parameters that will be needed for this analysis by creating a buffer with a 50km radius around the known species habitat area. The Landsat images that correspond with this region of interest were downloaded using the Google Earth Engine API.
Analysis parameters
First, we use the difference between bands 6 and 7 divided by their sum (normalized ratio similar to NDVI calculation) to identify the normalized difference gypsum index for gypsic soils. The equation is (Band 6 - Band 7)/(Band 6 + Band 7). We expect to produce a map that displays white for potential areas with high gypsic content.
Results
We expected a map to display areas with high gypsic soils as white. There was a problem with the initial result as some areas area clearly identified as crop circles show up white in addition to soils with high gypsum content. This means that vegetation is also being detected by our normalized difference gypsum index band - not what we want.
To fix this, we added another band, this time calculating NDVI with the same math we used to calculate the normalized difference gypsum index, but using bands 4 (red) and 5 (near-infrared).
NDVI is a dimensionless index that captures the difference between visible and near-infrared reflectance used to estimate vegetation cover.
By mapping normalized difference gypsum index and NDVI together, we should be able to differentiate between soil and vegetation: this is because vegetation will appear in both bands (show in purple below), but gypsic soils will only appear in normalized difference gypsum index (shown in red below).
In summary, this project used the Google Earth Engine API to download Landsat 8 data in order to explore potential habitat for an endangered plant species. Sophora gypsophila is endangered, therefore data for known locations is not available to the public. By comparing NDVI and normalized difference gypsum index bands, this study was able to determine possible regions of high gypsum concentration in the Guadalupe Mountains. These gypsic soil regions are potential suitable habitat to rare, endemic species such as Sophora gypsophila.
Gypsic soil areas were mapped using the difference ratio of Bands 6 and 7. After plotting the normalized difference gypsum index with the NDVI, we can see areas that are presumed to be gypics soils standout much more compared to areas that are known to have vegetation.
Future Research and Other Use Cases
This analysis use case allows biologist to prioritize areas of potential habitat suitability for survey for rare, threatened species such as S. gypsophila. Field surveys could be conducted to determine predictive accuracy via ground truthing. Another consideration to calculate more precise estimates for S. gypsophila habitat would be to overlay an elevation map and select for gypsic soil and elevation range. The known elevation range of S. gypsophila populations is between 1,000 and 5,000 feet above sea level. Combining both areas of high gypsic soil and elevation data would provide more precise suitabile habitat areas. An additional step in adapting Landsat data for conservation purposes would be comparing the identified potential Sophora habitat with land ownership maps in the region to target separate management solutions for public and private land.
General uses for this type of analysis is far reaching. Federal agencies or renewable energy developers could use this analysis to predict areas where rare or threatened plant species may be located but there is a lack of accurate population distribution documentation, areas coined as “botanical black holes”. Identifying areas that may have high level of endemism may assist with environmental impact assessments or future graduate research sites. This analysis could also be used identifying locations for new agricultural areas or for potential renewable energy development suitablility. Similar case studies have successfully identified soils with high salts content.
References
Binte Mostafiz, R.; Noguchi, R.; Ahamed, T. Agricultural Land Suitability Assessment Using Satellite Remote Sensing-Derived Soil-Vegetation Indices. Land 2021, 10, 223. https://doi.org/10.3390/land10020223
Boettinger, J., Ramsey, R., Bodily, J., Cole, N., Kienast-brown, S., Nield, S., Saunders, A., & Stum, A. (2008). Landsat Spectral Data for Digital Soil Mapping. Digital Soil Mapping with Limited Data. https://doi.org/10.1007/978-1-4020-8592-5_16
Browning, D. M., & Duniway, M. C. (2011). Digital Soil Mapping in the Absence of Field Training Data: A Case Study Using Terrain Attributes and Semiautomated Soil Signature Derivation to Distinguish Ecological Potential. Applied and Environmental Soil Science, 2011, e421904. https://doi.org/10.1155/2011/421904
Landsat Collection 2 Summary and Sample Metadata Now Available. (2019). Landsat Science. Retrieved November 28, 2021, from https://landsat.gsfc.nasa.gov/article/landsat-collection-2-summary-and-sample-metadata-now-available
Landsat 8 data courtesy of the U.S. Geological Survey. https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2#image-properties
Nield, S. J., Boettinger, J. L., & Ramsey, R. D. (2007). Digitally Mapping Gypsic and Natric Soil Areas Using Landsat ETM Data. Soil Science Society of America Journal, 71(1), 245–252. https://doi.org/10.2136/sssaj2006-0049
Ridwan, M. A., Radzi, N., Ahmad, W., Mustafa, I., Din, N., Jalil, Y., Isa, A., Othman A., Zaki, W. Applications of Landsat-8 Data: Survey. Internation Journal of Engineering & Techonology 2018, 11, 436-441. DOI:10.14419/ijet.v7i4.35.22858
Sophora gypsophila | NatureServe Explorer. (n.d.). Retrieved November 16, 2021, from https://explorer.natureserve.org/Taxon/ELEMENT_GLOBAL.2.155365/Sophora_gypsophila
Soil Survey Manual - Ch. 5. Digital Soil Mapping | NRCS Soils. (n.d.). Retrieved November 16, 2021, from https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/ref/?cid=nrcs142p2_054255
Stafford, K., Rosales Lagarde, L., & Boston, P. (2008). Castile evaporite karst potential map of the Gypsum Plain, Eddy County New Mexico and Culberson County, Texas: A GIS methodological comparison. J Cave Karst Stud, 70.
Texas Native Plants Database. (n.d.). Retrieved November 16, 2021, from https://aggie-horticulture.tamu.edu/ornamentals/nativeshrubs/sophoragypsophila.htm
Vermote, E., Justice, C., Claverie, M., & Franch, B. (2016). Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sensing of Environment, 185, 46-56.