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Vegetation drought monitoring from MODIS imagery and soil moisture data in Oklahoma Mesonet sites

dc.creatorVanegas, Diana Ximena
dc.creatorXiao, Xiangming
dc.creatorBasara, Jeffrey
dc.date2016-10-10
dc.date.accessioned2020-08-21T20:40:24Z
dc.date.available2020-08-21T20:40:24Z
dc.identifierhttps://revistas.unbosque.edu.co/index.php/RevTec/article/view/1879
dc.identifier10.18270/rt.v13i2.1879
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/10763
dc.descriptionDrought is a normal and recurrent climatic phenomenon, and is considered one of the most costly natural disasters in the United States. Grassland vegetation is sensitive to weather and climate, and persistent drought impacts goods and ecological services that grasslands provide (e.g., wildlife habitats, feedstock for the livestock industry, and recreational services). Droughts have extremely large spatial and temporal variations in areal coverage and intensity making drought monitoring a challenging task. Using soil and atmospheric data from the Oklahoma Mesonet and surface reflectance data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, this study examined the hypothesis that the satellite-derived Land Surface Water Index (LSWI) is sensitive to drought conditions and can potentially be used as an indicator or tool for drought monitoring. The sensitivity of LSWI to summer drought was first analyzed at 10 Mesonet sites that are homogeneous and representative of different types of grassland vegetation, soils and climate across Oklahoma. A summer drought event is defined, based on threshold values of LSWI and the Fractional Water Index (FWI) derived from soil moisture data at each site.Secondly, the LSWI-based drought algorithm was evaluated at103 Oklahoma Mesonet sites. Finally, the LSWI-based droughtalgorithm was used to map spatial patterns and temporal dynamicsof drought-affected land surface during 2001-2010 acrossOklahoma. The results from this study demonstrated the potentialof LSWI-based drought algorithm for tracking and mappingdrought-affected grassland vegetation in Oklahoma with 3%commission error in the Oklahoma Mesonet sites during 2001-2010.La sequía es un fenómeno climático normal y recurrente, y es considerado uno de los desastres naturales más costosos en Estados Unidos. La vegetación de pastizales es sensible al estado del tiempo y el clima, y la persistencia de la sequía afecta a los bienes y servicios ecológicos que proporcionan los pastizales (por ejemplo, son hábitats de vida silvestre, proveen materia prima para la industria ganadera, así como servicios de esparcimiento). La cobertura de área e intensidad de las sequías presentan grandes variaciones espaciales y temporales, haciendo que el monitorea de sequías sea una tarea difícil. Usando datos atmosféricos y de suelos de la Oklahoma Mesonet, y datos de reflectancia de la superficie terrestre del espectrorradiómetro de imágenes de resolución moderada (MODIS, por sus siglas en inglés) a bordo de los satélites Terra y Aqua, este estudio examinó la hipótesis de que el índice de agua de la superficie del terreno (LSWI, por sus siglas en inglés) es sensible a condiciones de sequía y potencialmente puede utilizarse como un indicador o herramienta para la monitoreo de sequías. La sensibilidad del LSWI a la sequía estival se analizó inicialmente en 10 sitios Mesonet que son homogéneos y representativos de los diferentes tipos de vegetación de pastizales, los suelos y el clima a través de Oklahoma. Un evento de sequía estival se define, en base a los valores de umbral de LSWI y el Índice de Agua fraccional (FWI) derivado de los datos de humedad del suelo en cada sitio. Posteriormente, el algoritmo de sequía basado en LSWI se evaluó en 103 sitios Oklahoma Mesonet. Por último, se utilizó el algoritmo de sequía basado en LSWI para mapear los patrones espaciales y la dinámica temporal de la superficie de la tierra afectada por la sequía durante 2001-2010 a través de Oklahoma. Los resultados de este estudio demostraron el potencial del algoritmo de sequía basado en LSWI para el seguimiento y la cartografía de vegetación de pradera afectada por la sequía en Oklahoma con un 3% de error de comisión en los sitios Oklahoma Mesonet durante 2001-2010en-US
dc.formatapplication/pdf
dc.languagespa
dc.publisherUniversidad El Bosquees-ES
dc.relationhttps://revistas.unbosque.edu.co/index.php/RevTec/article/view/1879/1448
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dc.rightsDerechos de autor 2014 Journal of Technologyes-ES
dc.sourceJournal of Technology; Vol 13 No 2 (2014): Hábitat que educa para la sostenibilidad; 10-27en-US
dc.sourceRevista de Tecnología; ##issue.vol## 13 ##issue.no## 2 (2014): Hábitat que educa para la sostenibilidad; 10-27es-AR
dc.sourceRevista de Tecnología; Vol. 13 Núm. 2 (2014): Hábitat que educa para la sostenibilidad; 10-27es-ES
dc.source1692-1399
dc.titleVegetation drought monitoring from MODIS imagery and soil moisture data in Oklahoma Mesonet sitesen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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