Sensitivity analysis of vegetation indices to drought over two tallgrass prairie sites

Bajgain, Rajen; Xiao, Xiangming; Wagle, Pradeep; Basara, Jeffrey B.; Zhou, Yuting

doi:10.1016/j.isprsjprs.2015.07.004

Cited by 81 publications

(45 citation statements)

References 53 publications

(53 reference statements)

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“…No obstante un elemento que dificulto la comparación y validación de datos, fue la presentación de la información, en nuestro caso los registros de eventos presentados por el IDEAM en el ENA14. Estos registros eran presentados de una forma demasiado ambigua, pues si bien trabajaron con una escala de acumulación i meses SPI variable (1,3,6,12) en algunos registros su detección se limitaba a mencionar Meta o Cravo Norte; dificultando la validación ya que si bien se contaban con registros en la zona hidrográfica nuestros resultados para el SPI,SSI, SRI y LSWI mostraban que la intensidad se concentraba más en unas zonas que en otras sobre esa área, por lo cual la ambigüedad de los reportes dificultó la validación. Por ejemplo, el nombre Cravo Norte se asocia a un río y también a un municipio; y si bien mencionaban un río, no especificaban sobre que sección del mismo y se encontró que su afectación asociada al evento no era extremo para la totalidad del cauce.…”

Section: Mapa 7 Lswi Zoom Ciudad De Villavicenciounclassified

Evaluación del nivel de mejora en el monitoreo de sequías a escala regional en Colombia, a partir de indicadores ecohidrologicos basados en teledetección

Rodríguez

Arrieta

Beltran

2017

RevTec

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Evaluación del nivel de mejora en el monitoreo de sequías a escala regional en Colombia, a partir de indicadores ecohidrologicos basados en teledetecciónEvaluation of the improvement level in drought monitoring in colombia from the integration of ecohydrological indices based on remote sensing Celis Rodríguez, Jorge Andrés; Vanegas Beltrán, Diana Ximena; Vergara Arrieta, Humberto José Resumen a sequía es un complejo fenómeno natural recurrente que se da en diferentes partes del mundo (Liu, y otros, 2016) y según la FAO sus estragos principalmente se asocian a riesgos en la seguridad; en este fenómeno intervienen gran número de variables hidrológicas lo cual dificulta aún más su detección. (National Drought Mitigation Center, 2016) Categoriza las sequías principalmente en meteorológica, agrícola e hidrológica; típicamente se utiliza un índice de detección independiente para cada una de estas sequías. El objetivo principal de esta investigación es evaluar la mejora que existe en la detección de sequías mediante el uso integrado de indicadores eco hidrológicos estimados con datos de monitoreo remoto en comparación con la habilidad individual del índice de precipitación. La zona de estudio determinada correspondió a la cuenca del Río Meta la cual con un área de cerca de 105,000Km2, es un afluente del Orinoco y se ubica en una zona con gran actividad agrícola, ganadera, piscícola y minero energética. Abstractrought is a worldwide phenomenon representing a risk for food security and water resources management. Predicting drought presents difficulties due the number of hydrological variables and processes involved in it. Drought is usually categorized and estimated with individual indices targeting a specific nature: meteorological, hydrological or agricultural drought. The main objective of this research was to evaluate the improvement on drought detection through the integrated use of multiple remote-sensing based ecological and hydrological indices compared to the individual use of each of the indices. The study area was the Meta River catchment, an affluent of the Orinoco River with an approximated drainage of 105,000 km2 and located on the eastern region of Colombia. A motivation of this study is that the proposed remote-sensing based approach can serve as a complementary tool for drought detection in this region; wherein-situ ground measurement stations with limited spatial coverage represent the only source of information.Recibido /

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Section: Mapa 7 Lswi Zoom Ciudad De Villavicenciounclassified

Evaluación del nivel de mejora en el monitoreo de sequías a escala regional en Colombia, a partir de indicadores ecohidrologicos basados en teledetección

Rodríguez

Arrieta

Beltran

2017

RevTec

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“…The LSWI-based algorithm uses LSWI as an indicator to assess agricultural drought in tallgrass prairie (Bajgain et al 2015). Generally, green vegetation has positive LSWI values (>0) and dry vegetation has negative LSWI values (<0).…”

Section: Lswi-based Agricultural Drought-monitoring Algorithmmentioning

confidence: 99%

“…The water-related vegetation index is a measurement of liquid water in vegetation canopies and hence is sensitive to the total amount of liquid water contained in vegetation when the vegetation cover is high. Some recent studies (Bajgain et al 2015;Chandrasekara et al 2011;Wagle et al 2014) have identified LSWI as an index in extracting the vegetation water status and in drought detection.…”

Section: Introductionmentioning

confidence: 99%

“…Because agricultural drought occurs due to lack of soil moisture and the consequent water stress in the vegetation, a water-based index should also be used along with the greenness-related indices such as normalized difference vegetative index (NDVI) and enhanced vegetative index (EVI) to develop systematic and effective method of agriculture drought assessment (Bajgain et al 2015;Chandrasekara et al 2011;Tian et al 2013;Wagle et al 2014). The Moderate Resolution Imaging Spectrometer (MODIS) sensor on board the NASA Terra satellite platform provides continuous daily observations of the land surface.…”

Section: Introductionmentioning

confidence: 99%

“…2. Is LSWI-based drought-monitoring algorithm developed for two tallgrass prairie sites (Bajgain et al 2015) applicable to quantify drought intensity over 113 Mesonet sites comprising various land cover and soil types in Oklahoma?…”

Section: Introductionmentioning

confidence: 99%

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Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS

et al. 2016

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Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI <0 (DNLSWI) during summer months (June-August). Summer rainfall anomalies and LSWI anomalies followed a similar seasonal dynamics and showed strong correlations (r = 0.62-0.73) during drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % (D class, moderate drought) to 77 % (0 and D class, no drought) for different drought intensity classes and varied from ∼30 % (western Oklahoma) to>80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

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Evaluating the sensitivity of vegetation and water indices to monitor drought for three Mediterranean crops

et al. 2021

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Understanding drought effects on vegetative health for crop producing locations, such as the Seferihisar‐Kavakdere region in western Turkey, is vital for water and crop management. This study used Landsat‐derived spectral vegetation indices, specifically normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and land surface water index (LSWI) to evaluate and compare their performance and sensitivity for three major crops (citrus, grape, and olive) under dry (2008), wet (2010), and normal (2015) climatic conditions. Results showed that all three crops were affected by drought despite two (citrus and grape) being irrigated. However, grape and olive were more affected by drought than citrus. Drought conditions were exacerbated during September and October because of lack of precipitation and because irrigation is not a common practice during these months in this region. Therefore, this study aimed to use and compare drought sensitivities of Landsat‐derived spectral vegetation indices. All studied indices were closely related (.48 ≤ R2 ≤ .98) for citrus, grape, and olive. The EVI and LSWI were greater than NDVI when NDVI values were greater than 0.65 for citrus, and LSWI values were larger than NDVI when NDVI values were greater than 0.6 for grape and olive during the wet year. The results showed that different vegetation indices are needed to detect drought from one crop to another under different climatic conditions. Our findings indicate that the irrigation applications in 2008 (drought year) were not sufficient to alleviate the severe drought stress experienced throughout the winter and growing seasons.

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Sensitivity analysis of vegetation indices to drought over two tallgrass prairie sites

Cited by 81 publications

References 53 publications

Evaluación del nivel de mejora en el monitoreo de sequías a escala regional en Colombia, a partir de indicadores ecohidrologicos basados en teledetección

Evaluación del nivel de mejora en el monitoreo de sequías a escala regional en Colombia, a partir de indicadores ecohidrologicos basados en teledetección

Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS

Evaluating the sensitivity of vegetation and water indices to monitor drought for three Mediterranean crops

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