Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has b...Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies.However,most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space.This requires extensive data from a vast study area,and may lead to subjective results.In this study,a Modified Temperature-Vegetation Dryness Index(MTVDI)was used to monitor surface soil moisture status using MODIS(Moderate-resolution Imaging Spectroradiometer)remote sensing data,in which the dry edge conditions were determined at the pixel scale based on surface energy balance.The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index(TVDI).The results showed that the R^(2) for MTVDI and soil moisture obviously improved(0.45 for TVDI,0.69 for MTVDI).As for spatial changes,MTVDI can also better reflect the actual soil moisture condition than TVDI.As a result,MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.展开更多
Using Moderate Resolution Imaging Spectroradiometer(MODIS) data from the dry season during 2010–2012 over the whole Yunnan Province, an improved temperature vegetation dryness index(iTVDI), in which a parabolic dry-e...Using Moderate Resolution Imaging Spectroradiometer(MODIS) data from the dry season during 2010–2012 over the whole Yunnan Province, an improved temperature vegetation dryness index(iTVDI), in which a parabolic dry-edge equation replaces the traditional linear dry-edge equation, was developed, to reveal the regional drought regime in the dry season. After calculating the correlation coefficient, root-mean-square error, and standard deviation between the iTVDI and observed topsoil moisture at 10 and 20 cm for seven sites, the effectiveness of the new index in depicting topsoil moisture conditions was verified. The drought area indicated by iTVDI mapping was then compared with the drought-affected area reported by the local government. The results indicated that the iTVDI can monitor drought more accurately than the traditional TVDI during the dry season in Yunnan Province. Using iTVDI facilitates drought warning and irrigation scheduling, and the expectation is that this new index can be broadly applied in other areas.展开更多
Moderate resolution imaging spectroradiometer （MODIS） data are very suitable for vast extent, long term and dynamic drought monitoring for its high temporal resolution, high spectral resolution and moderate spatial ...Moderate resolution imaging spectroradiometer （MODIS） data are very suitable for vast extent, long term and dynamic drought monitoring for its high temporal resolution, high spectral resolution and moderate spatial resolution. The composite Enhanced Vegetation Index （EVI） and composite land surface temperature （Ts） obtained from MODIS data MOD11A2 and MOD13A2 were used to construct the EVI-Ts space. And Temperature Vegetation Dryness Index （TVDI） was calculated to evaluate the agriculture drought in Guangxi province, China in October of 2006. The results showed that the drought area in Guangxi was evidently increasing and continuously deteriorating from the middle of September to the middle of November. The TVDI, coming from the EVI-Ts space, could effectively indicate the spatial distribution and temporal evolution of drought, so that it could provide a strong technical support for the forecasting agricultural drought in south China.展开更多
The temperature-vegetation index space coupled with information of surface temperature and vegetation, is an important method to realize soil moisture estimation and agricultural drought monitoring. In order to estima...The temperature-vegetation index space coupled with information of surface temperature and vegetation, is an important method to realize soil moisture estimation and agricultural drought monitoring. In order to estimate the soil moisture in the study area, we collected soil relative humidity of Agricultural meteorological station and downloaded Moderate Resolution Imaging Spectrometer (MODIS) image data. Then, the temperature vegetation dryness index was calculated based on the MODIS Normalized difference vegetation index (NDVI) and land surface temperature (LST). A correlation analysis of TVDI and soil relative humidity at depth of 10 cm was carried out and an empirical model of moisture estimation was established. Finally, another set of data was used to validate the accuracy of model. The results show that the TVDI method can be used to achieve the soil moisture in the study area. The empirical model has certain universality in the study area, and obtains a high accuracy of soil moisture estimation with an R2 of 0.374 and RMSE of 11.73%.展开更多
Soil moisture has been considered as one of the main indicators that are widely used in the fields of hydrology,climate,ecology and others.The land surface temperature-vegetation index(LST-VI) space has comprehensive ...Soil moisture has been considered as one of the main indicators that are widely used in the fields of hydrology,climate,ecology and others.The land surface temperature-vegetation index(LST-VI) space has comprehensive information of the sensor from the visible to thermal infrared band and can well reflect the regional soil moisture conditions.In this study,9 pairs of moderate-resolution imaging spectroradiometer(MODIS) products(MOD09A1 and M0D11A2),covering 5 provinces in Southwest China,were chosen to construct the LST-VI space,and then the spatial distribution of soil moisture in 5 provinces of Southwest China was monitored by the temperature vegetation dryness index(TVDI).Three LST-VI spaces were constructed by normalized difference vegetation index(NDVI),enhanced vegetation index(EVI),and modified soil-adjusted vegetation index(MSAVI),respectively.The correlations between the soil moisture data from 98 sites and the 3 TVDIs calculated by LST-NDVI,LST-EVI and LST-MSAVI,respectively,were analyzed.The results showed that TVDI was a useful parameter for soil surface moisture conditions.The TVDI calculated from the LST-EVI space(TVDIE) revealed a better correlation with soil moisture than those calculated from the LST-NDVI and LST-MSAVI spaces.Prom the different stages of the TVDIE space,it is concluded that TVDIE can effectively show the temporal and spatial differences of soil moisture,and is an effective approach to monitor soil moisture condition.展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.41801180)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2020JQ415,2019JQ-767)。
文摘Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies.However,most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space.This requires extensive data from a vast study area,and may lead to subjective results.In this study,a Modified Temperature-Vegetation Dryness Index(MTVDI)was used to monitor surface soil moisture status using MODIS(Moderate-resolution Imaging Spectroradiometer)remote sensing data,in which the dry edge conditions were determined at the pixel scale based on surface energy balance.The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index(TVDI).The results showed that the R^(2) for MTVDI and soil moisture obviously improved(0.45 for TVDI,0.69 for MTVDI).As for spatial changes,MTVDI can also better reflect the actual soil moisture condition than TVDI.As a result,MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.
基金supported by the National Key Research and Development Program of China (2016YFA0601601)National Natural Science Foundation of China (Grants Nos. U1502233,41405001)+1 种基金the Jiangsu Collaborative Innovation Center for Climate ChangePh.D. Programs Foundation of Ministry of Education of China (20135301120010)
文摘Using Moderate Resolution Imaging Spectroradiometer(MODIS) data from the dry season during 2010–2012 over the whole Yunnan Province, an improved temperature vegetation dryness index(iTVDI), in which a parabolic dry-edge equation replaces the traditional linear dry-edge equation, was developed, to reveal the regional drought regime in the dry season. After calculating the correlation coefficient, root-mean-square error, and standard deviation between the iTVDI and observed topsoil moisture at 10 and 20 cm for seven sites, the effectiveness of the new index in depicting topsoil moisture conditions was verified. The drought area indicated by iTVDI mapping was then compared with the drought-affected area reported by the local government. The results indicated that the iTVDI can monitor drought more accurately than the traditional TVDI during the dry season in Yunnan Province. Using iTVDI facilitates drought warning and irrigation scheduling, and the expectation is that this new index can be broadly applied in other areas.
基金the National Natural Science Foundation of China (40461001)
文摘Moderate resolution imaging spectroradiometer （MODIS） data are very suitable for vast extent, long term and dynamic drought monitoring for its high temporal resolution, high spectral resolution and moderate spatial resolution. The composite Enhanced Vegetation Index （EVI） and composite land surface temperature （Ts） obtained from MODIS data MOD11A2 and MOD13A2 were used to construct the EVI-Ts space. And Temperature Vegetation Dryness Index （TVDI） was calculated to evaluate the agriculture drought in Guangxi province, China in October of 2006. The results showed that the drought area in Guangxi was evidently increasing and continuously deteriorating from the middle of September to the middle of November. The TVDI, coming from the EVI-Ts space, could effectively indicate the spatial distribution and temporal evolution of drought, so that it could provide a strong technical support for the forecasting agricultural drought in south China.
文摘The temperature-vegetation index space coupled with information of surface temperature and vegetation, is an important method to realize soil moisture estimation and agricultural drought monitoring. In order to estimate the soil moisture in the study area, we collected soil relative humidity of Agricultural meteorological station and downloaded Moderate Resolution Imaging Spectrometer (MODIS) image data. Then, the temperature vegetation dryness index was calculated based on the MODIS Normalized difference vegetation index (NDVI) and land surface temperature (LST). A correlation analysis of TVDI and soil relative humidity at depth of 10 cm was carried out and an empirical model of moisture estimation was established. Finally, another set of data was used to validate the accuracy of model. The results show that the TVDI method can be used to achieve the soil moisture in the study area. The empirical model has certain universality in the study area, and obtains a high accuracy of soil moisture estimation with an R2 of 0.374 and RMSE of 11.73%.
基金Supported by the National Key Technologies Research and Development Program of the Ministry of Science and Technology of China during the 12th Five-Year Plan Period(Nos.2011BAD32B01 and 2012BAH29B02)
文摘Soil moisture has been considered as one of the main indicators that are widely used in the fields of hydrology,climate,ecology and others.The land surface temperature-vegetation index(LST-VI) space has comprehensive information of the sensor from the visible to thermal infrared band and can well reflect the regional soil moisture conditions.In this study,9 pairs of moderate-resolution imaging spectroradiometer(MODIS) products(MOD09A1 and M0D11A2),covering 5 provinces in Southwest China,were chosen to construct the LST-VI space,and then the spatial distribution of soil moisture in 5 provinces of Southwest China was monitored by the temperature vegetation dryness index(TVDI).Three LST-VI spaces were constructed by normalized difference vegetation index(NDVI),enhanced vegetation index(EVI),and modified soil-adjusted vegetation index(MSAVI),respectively.The correlations between the soil moisture data from 98 sites and the 3 TVDIs calculated by LST-NDVI,LST-EVI and LST-MSAVI,respectively,were analyzed.The results showed that TVDI was a useful parameter for soil surface moisture conditions.The TVDI calculated from the LST-EVI space(TVDIE) revealed a better correlation with soil moisture than those calculated from the LST-NDVI and LST-MSAVI spaces.Prom the different stages of the TVDIE space,it is concluded that TVDIE can effectively show the temporal and spatial differences of soil moisture,and is an effective approach to monitor soil moisture condition.
