Monitoring the effects of land use and cover type changes on soil moisture using remote-sensing data: A case study in China's Yongding River basin

Wang, Hong; Li, Xiaobing; Huang, Long; Xu, Xu; Bao, Yun

doi:10.1016/j.catena.2010.05.008

Cited by 51 publications

(21 citation statements)

References 16 publications

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“…There is a close relationship between soil moisture and LUCC (Fu et al 1999;Huang et al 2005;Wang et al 2010;Rahimzadeh et al 2013). The soil moisture could affect the growth of plants, while the LUCC and vegetation cover could also affect the distribution and content of water in soil (Fu et al 1999;Chen et al 2006).…”

Section: The Spatiotemporal Development Of Tvdimentioning

confidence: 99%

An improvement of the Ts-NDVI space drought monitoring method and its applications in the Mongolian plateau with MODIS, 2000–2012

2016

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Surface soil moisture is a key variable to describe water and energy exchanges at the surface/atm interface and measure drought and aridification. The Ts-NDVI space is an effective method to monitor regional surface soil moisture status. Due to the disturbance of multiple factors, the established dry or wet boundary with monotemporal remote sensing data is unstable. This paper developed a Ts-NDVI triangle space with MODIS NDVI dataset to monitor soil moisture in the Mongolian Plateau in 2000-2012. Based on the temperature vegetation dryness index (TVDI), the spatiotemporal variations of drought were studied. The results indicated that (1) the general Ts-NDVI space method is an effective way to monitor regional soil moisture. However, if the single time space shows perfect structure, there would be no differences between the inverted results of the single time space and the general space. (2) The TVDI calculated in the paper is expected to show the water deficit for the region from low (bare soil) to high (full vegetation cover) NDVI values, and it is found to be in close negative agreement with precipitation and soil moisture; changes in the TVDI are dependent on the water status in the study area. (3) In the Mongolian Plateau, TVDI presented a zonal distribution with changes in Land Use/Land Cover types, vegetation cover, and latitude. Drought was serious in bare land, construction land, and grassland. Drought was widely spread throughout the Mongolian Plateau, and there was aridification in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.

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Section: The Spatiotemporal Development Of Tvdimentioning

confidence: 99%

An improvement of the Ts-NDVI space drought monitoring method and its applications in the Mongolian plateau with MODIS, 2000–2012

2016

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“…Since then, more researchers have used TVDI or have improved the TVDI to assess and predict drought [16][17][18][19], and they have fit the TVDI value and observed value of soil moisture to the inverse of the soil moisture [20,21]. The results from a large number of studies [22][23][24][25][26] have demonstrated that it is more advantageous to use the combined vegetation index and the surface temperature to monitor drought or even to investigate the regional soil moisture distribution.…”

Section: Introductionmentioning

confidence: 99%

The Spatiotemporal Variation of Drought in the Beijing-Tianjin-Hebei Metropolitan Region (BTHMR) Based on the Modified TVDI

et al. 2016

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This study proposes a modified vegetation-dependent temperature-vegetation dryness index (TVDI) model for analyzing regional drought disasters in the Beijing-Tianjin-Hebei Metropolitan Region (BTHMR) of China. First, MODIS monthly normalized difference vegetation index (NDVI), land surface temperature (LST) data and land use/cover data (Land cover type2) were pre-processed as a consistent big dataset. The land use/cover data were modified and integrated into six primary types. Then, these land types were used as the base data layer to calculate the TVDI by parameterizing the relationship between the MODIS NDVI and LST data. By emphasizing different types of land uses, this study was able to compare and analyze the differences of the TVDI indices between the entire study area (no consideration of the land types) and the six classified land uses. The soil moisture data were used to validate the modified TVDI values based on different land uses, which confirmed that the modified model more effectively reflected drought conditions. Finally, the aforementioned model was used to analyze the temporal and spatial variation of drought experienced by vegetation cover from 2000 to 2014. The results of the modified model were validated with the synchronized soil moisture and precipitation data. The case study clearly demonstrated that the modified TVDI model, which is based on different vegetation indexes, could better reflect the drought conditions of the study area.

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“…Por conseguinte, os resultados sugerem que seria fundamental observar a evolução da degradação na região, conforme estudo realizado por Wang et al (2010) que verificaram o impacto da mudança do uso e cobertura do solo na umidade em uma bacia hidrográfica, através do modelo TemperaturaVegetação utilizando 34 pontos de validação. Esta análise seria sugerida em relação ao avanço da desertificação, particularmente por meio da dinâmica de borda referente aos parâmetros biofísicos modelados e se verificando sua influência no avanço do risco à desertificação, através de comparações espaço-temporal, conforme metodologia aplicada por Lopes et al (2009) do Seridó a vegetação natural já não consegue se recompor, permanecendo com porte pequeno e de forma raleada, deixando áreas expressivas da superfície do solo expostas aos processos erosivos.…”

Section: Figura 1 Localização Geográfica Do Núcleo De Desertificaçãounclassified

Espacialização da umidade do solo por meio da temperatura da superfície e índice de vegetação

Lopes

Accioly

Silva

et al. 2011

Rev. bras. eng. agríc. ambient.

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R ESU M OO estudo da umidade do solo é fundamental não só para a determinação da resiliência de ecossistemas e sua recuperação, mas também na modelagem da relação água-vegetação-atmosfera. Na aquisição dessas informações o sensoriamento remoto perfaz uma ferramenta importante e de potencial adequado para monitoramento e mapeamento. Visando à espacialização de índices relacionados à umidade, vários métodos têm sido propostos, embora sua aplicação ainda seja limitada. Neste trabalho se aplicou o modelo de índice de umidade do solo (IUS) cujos objetivos foram: espacializar o IUS, estabelecer graus de desertificação, delimitar a área em processo de desertificação e verificar possíveis relações do IUS com parâmetros de água no solo. Na aplicação deste modelo se utilizaram, como dados de entrada, o NDVI (índice de vegetação da diferença normalizada) e a LST (temperatura da superfície) e se observou que o IUS representado pela média dos valores desses índices pode ser empregado na determinação do grau de degradação da superfície e para gerar classificação legendada, discriminando vários níveis de degradação ambiental. Constatou-se também que não houve relação direta do IUS com parâmetros físicos de retenção de umidade do solo. Desta forma, o sensoriamento remoto mostrou ser uma ferramenta significativa na avaliação de índices de umidade do solo em áreas degradadas tal como para delinear a dinâmica de borda em núcleo de desertificação.Palavras-chave: índice de umidade do solo, NDVI, Seridó, desertificação Spatial distribution of soil moisture using land surface temperature and vegetation indices A B ST R A C TThe study of soil moisture is important in determining the resilience of ecosystems and their recovery, as well as in the modeling of water-vegetation-atmosphere relationship. Remote sensing is an important tool for the acquisition, mapping and monitoring soil moisture through the surface temperature and vegetation indices. For the soil moisture content assessment, several methods have been proposed, however its application is still limited. In this work the soil moisture index (SMI) was applied and modeled with the objectives: to establish and delineate areas with different levels of desertification through SMI mapping and to map the dynamic of border, as well as to verify possible relationships betweem SMI and soil water parameters. In the application of this model as input data was used: NDVI (normalized difference vegetation index) and LST (land surface temperature). It was observed that SMI accessed by the average of the SMI derived by NDVI and LST can be used in the determination of soil surface degradation and in the production of maps showing different levels of this degradation. It was also verified, that there was no direct relationship between SMI and physical parameters of soil moisture content. Remote sensing showed to be an important tool in the evaluation of soil moisture indices in degraded areas and to delineate the border effect in this desertification nucleus.

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Monitoring the effects of land use and cover type changes on soil moisture using remote-sensing data: A case study in China's Yongding River basin

Cited by 51 publications

References 16 publications

An improvement of the Ts-NDVI space drought monitoring method and its applications in the Mongolian plateau with MODIS, 2000–2012

An improvement of the Ts-NDVI space drought monitoring method and its applications in the Mongolian plateau with MODIS, 2000–2012

The Spatiotemporal Variation of Drought in the Beijing-Tianjin-Hebei Metropolitan Region (BTHMR) Based on the Modified TVDI

Espacialização da umidade do solo por meio da temperatura da superfície e índice de vegetação

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