Taking Droughts From Earth to Space

Earthzine2015 Spring VPS, Assessing Agriculture and Ecosystems, DEVELOP Virtual Poster Session

Category: Assessing Agriculture and Ecosystems

Project Team: Uruguay Agriculture II

Team Location: International Research Institute for Climate and Society (IRI) ‰ÛÒ Palisades, New York

Map showing the degree of correlation between the DSI using NDWI for Januarys during the study period and the percent available water from station data. Image Credit: Uruguay Agriculture II Team


Jerrod Lessel

Alex Sweeney


Dr. Pietro Ceccato (Research Scientist, Lead Environmental Monitoring Program, The International Research Institute for Climate and Society, The Earth Institute, Columbia University)


The importance of monitoring drought is indispensable for countries whose economic viability is strongly tied to agriculture. Droughts are a major concern for the country of Uruguay, affecting their agricultural and energy sectors. The development of a remotely-sensed drought monitoring tool that can aid government agencies in disseminating drought information to local stakeholders will be helpful in sustaining these important economic sectors. This study tested the ability of an existing Drought Severity Index (DSI) to monitor drought within Uruguay using remotely sensed products. The DSI, based off of methodology from Rhee et al. (2010), uses the climatological anomalies of NASA’s Moderate Resolution Imaging Spectrometer (MODIS) land surface temperature (LST) data, precipitation data from the Tropical Rainfall Measuring Mission (TRMM), and MODIS Normalized Difference Water Index (NDWI) data. By comparing the DSI to soil water balance (SWB) data from meteorological stations provided by the Instituto Nacional de InvestigaciÌ_n Agropecuaria (INIA), this study was able to validate a remotely sensed drought index with station data, which has been used as the standard to define droughts within Uruguay. In addition to the validation of the DSI, the SWB data was compared to a series of modified DSIs. NOAA’s CPC Morphing Technique (CMORPH) was substituted in for TRMM data, while alternative vegetation indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) were exchanged for NDWI. This modified DSI has the potential to aid INIA and the Ministry of Agriculture in informing land managers, insurance providers, and policymakers in drought preparation and mitigation practices.

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