NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space

Gao, Bo‐Cai

doi:10.1016/s0034-4257(96)00067-3

Cited by 5,008 publications

(2,707 citation statements)

References 17 publications

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“…Ji et al [25] suggested that the NDWI may not be suitable in complex areas, especially where vegetation is partially submerged. This may be attributed to NDWI using the NIR band, which is very sensitive to the vegetation water content [55]. In addition, because of the low resolution of MODIS data, the inundation area contained many mixed pixels, thus increasing the sensitivity of the NDWI to vegetation [56].…”

Section: Uncertainties Of the Water Index Methodsmentioning

confidence: 99%

Changes in the Lake Area of Tonle Sap: Possible Linkage to Runoff Alterations in the Lancang River?

Luo

et al. 2018

Remote Sensing

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Tonle Sap Lake is the largest freshwater lake in Southeast Asia. Water development infrastructures are increasingly being constructed in the Lancang-Mekong River Basin, which is a major concern considering its potential impact on Tonle Sap Lake. This study aimed to investigate variations in the area of the lake and discuss their possible linkage to runoff alterations in the Lancang River (Upper Mekong) by comparing runoff at the Yunjinghong hydrological station before and after significant changes in runoff trends that occurred in 2008. First, four commonly used water body extraction methods (MNDWI, NDWI, NDVI, and EVI) were compared and MNDWI was found to provide a better and more stable performance. Based on MOD09A1 data, MNDWI was used to extract the water area of the lake from 2000 to 2014, and characteristics of variations in the area before and after 2008 were analyzed. The water area of Tonle Sap Lake displayed an overall decreasing trend, and specifically decreased by 8.3% during the flood season and by 1.5% on average during the dry season after 2008. Seasonal variations in the water area of Tonle Sap Lake were dominantly influenced by runoff from the Mekong River. Compared with the period 2000-2007, runoff at Yunjinghong station were increased during the dry season (20.74%) and decreased during the flood season (34.25%) between 2008 and 2014. Changes in upstream runoff contributed to runoff at the Stung Treng station in the lower Mekong River by 6.17% (dry season) and −2.41% (flood season). Evidently, the operation of dams in the Lancang River does not primarily account for the area decrease of Tonle Sap Lake during the flood season. In contrast, runoff increase during the dry season mitigates the area decrease of Tonle Sap Lake to a certain extent.

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Section: Uncertainties Of the Water Index Methodsmentioning

confidence: 99%

Changes in the Lake Area of Tonle Sap: Possible Linkage to Runoff Alterations in the Lancang River?

Luo

et al. 2018

Remote Sensing

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“…Likewise NDVI, the Normalized Difference Water Index (NDWI) [40] is a radiometric index that exploits a typical absorption/reflection pattern for water mapping purposes. After [41], the NDWI is computed according to the following equation:…”

Section: Analysis Of Multi-temporal Imagery Datasetmentioning

confidence: 99%

Multi-Temporal Image Analysis for Fluvial Morphological Characterization with Application to Albanian Rivers

Spada

Molinari

Bertoldi

et al. 2018

IJGI

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Abstract:A procedure for the characterization of the temporal evolution of river morphology is presented. Wet and active river channels are obtained from the processing of imagery datasets. Information about channel widths and active channel surface subdivision in water, vegetation and gravel coverage classes are evaluated along with channel centerline lengths and sinuosity indices. The analysis is carried out on a series of optical remotely-sensed imagery acquired by different satellite missions during the time period between 1968 and 2017. Data from the CORONA, LANDSAT and Sentinel-2 missions were considered. Besides satellite imagery, a digital elevation model and aerial ortho-photos were also used. The procedure was applied to three, highly dynamic, Albanian rivers: Shkumbin, Seman and Vjosë, showing a high potential for application in contexts with limitations in ground data availability. The results of the procedure were assessed against reference data produced by means of expert interpretation of a reference set of river reaches. The results differ from reference values by just a few percentage points (<6%). The time evolution of hydromorphological parameters is well characterized, and the results support the design of future studies aimed at the understanding of the relations between climatic and anthropogenic controls and the response of river morphological trajectories. Moreover, the high spatial and temporal resolution of the Sentinel-2 mission motivates the development of an automatic monitoring system based on a rolling application of the defined procedure.

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“…Para isso, empregaram-se as bandas espectrais 0,52-0,59μm (verde -VERDE); 0,62-0,68μm (vermelho -VERM); 0,77-0,86μm (infravermelho próximo -IVP) e 1,55-1,70μm (infravermelho médio -IVM). Os índices espectrais elaborados foram: Índice de Umidade por Diferença Normalizada para estresse hídrico (NDWI1) (GAO, 1996), Índice de Umidade por Diferença Normalizada para lâmina d'água (NDWI2) (MCFEETERS, 1996), Razão Simples (RS), Índice de Vegetação por Diferença Normalizada (NDVI) (TUCKER, 1979) e Índice de Vegetação ajustado ao Solo (SAVI) (HUETE, 1988). O SAVI possui a constante L, que é um fator de ajuste de substrato do dossel.…”

Section: Dados De Sensoriamento Remotounclassified

Árvore de decisão e a densidade mínima de amostras no mapeamento da cobertura da terra

2014

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NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space

Cited by 5,008 publications

References 17 publications

Changes in the Lake Area of Tonle Sap: Possible Linkage to Runoff Alterations in the Lancang River?

Changes in the Lake Area of Tonle Sap: Possible Linkage to Runoff Alterations in the Lancang River?

Multi-Temporal Image Analysis for Fluvial Morphological Characterization with Application to Albanian Rivers

Árvore de decisão e a densidade mínima de amostras no mapeamento da cobertura da terra

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