GC33C-1293
Remote Sensing of Water Quality in the Niger River Basin

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Chase Mueller1,2, Sherry L. Palacios1, Cristina Milesi1, Cindy Schmidt1,2, Oliwia N Baney3,4, Ase Mitchell4,5, Emily 'Chippie' Kislik4,5 and Laura Jean Palmer-Moloney6, (1)NASA Ames Research Center, Moffett Field, CA, United States, (2)Bay Area Environmental Research Institute Moffett Field, Moffett Field, CA, United States, (3)University of California Los Angeles, Los Angeles, CA, United States, (4)DEVELOP National Program, NASA Ames Research Center, Moffett Field, CA, United States, (5)University of California Berkeley, Berkeley, CA, United States, (6)US Army Corp of Engineers, Geospatial Lab, Washington, DC, United States
Abstract:
An overarching goal of the National Geospatial Intelligence Agency (NGA) Anticipatory Analytics- -GEOnarrative program is to establish water linkages with energy, food, and climate and to understand how these linkages relate to national security and stability. Recognizing that geopolitical stability is tied to human health, agricultural productivity, and natural ecosystems’ vitality, NGA partnered with NASA Ames Research Center to use satellite remote sensing to assess water quality in West Africa, specifically the Niger River Basin. Researchers from NASA Ames used MODIS and Landsat imagery to apply two water quality indices-- the Floating Algal Index (FAI) and the Turbidity Index (TI)--to large rivers, lakes and reservoirs within the Niger Basin. These indices were selected to evaluate which observations were most suitable for monitoring water quality in a region where coincident in situ measurements are not available. In addition, the FAI and TI indices were derived using data from the Hyperspectral Imagery for the Coastal Ocean (HICO) sensor for Lake Erie in the United States to determine how increased spectral resolution and in-situ measurements would improve the ability to measure the spatio-temporal variations in water quality. Results included the comparison of outputs from sensors with different spectral and spatial resolution characteristics for water quality monitoring. Approaches, such as the GEOnarrative, that incorporate water quality will enable analysts and decision-makers to recognize the current and potentially future impacts of changing water quality on regional security and stability.