%0 Journal Article %1 Jackson2004 %A Jackson, Thomas J. %A Chen, Daoyi %A Cosh, Michael %A Li, Fuqin %A Anderson, Martha %A Walthall, Charles %A Doriaswamy, Paul %A Hunt, E. Ray %B 2002 Soil Moisture Experiment (SMEX02) %D 2004 %J Remote Sensing of Environment %K Soil drought evaporation moisture ndwi reflectance remotesensing satellite soilmoisture stress vegetation %N 4 %P 475--482 %T Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans %U http://www.sciencedirect.com/science/article/B6V6V-4B8BWHY-1/1/bcff206f3a4c9678088761e8bc7d7e98 %V 92 %X Information about vegetation water content (VWC) has widespread utility in agriculture, forestry, and hydrology. It is also useful in retrieving soil moisture from microwave remote sensing observations. Providing a VWC estimate allows us to control a degree of freedom in the soil moisture retrieval process. However, these must be available in a timely fashion in order to be of value to routine applications, especially soil moisture retrieval. As part of the Soil Moisture Experiments 2002 (SMEX02), the potential of using satellite spectral reflectance measurements to map and monitor VWC for corn and soybean canopies was evaluated. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data and ground-based VWC measurements were used to establish relationships based on remotely sensed indices. The two indices studied were the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI). The NDVI saturated during the study period while the NDWI continued to reflect changes in VWC. NDWI was found to be superior based upon a quantitative analysis of bias and standard error. The method developed was used to map daily VWC for the watershed over the 1-month experiment period. It was also extended to a larger regional domain. In order to develop more robust and operational methods, we need to look at how we can utilize the MODIS instruments on the Terra and Aqua platforms, which can provide daily temporal coverage.

@article{Jackson2004, abstract = {Information about vegetation water content (VWC) has widespread utility in agriculture, forestry, and hydrology. It is also useful in retrieving soil moisture from microwave remote sensing observations. Providing a VWC estimate allows us to control a degree of freedom in the soil moisture retrieval process. However, these must be available in a timely fashion in order to be of value to routine applications, especially soil moisture retrieval. As part of the Soil Moisture Experiments 2002 (SMEX02), the potential of using satellite spectral reflectance measurements to map and monitor VWC for corn and soybean canopies was evaluated. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data and ground-based VWC measurements were used to establish relationships based on remotely sensed indices. The two indices studied were the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI). The NDVI saturated during the study period while the NDWI continued to reflect changes in VWC. NDWI was found to be superior based upon a quantitative analysis of bias and standard error. The method developed was used to map daily VWC for the watershed over the 1-month experiment period. It was also extended to a larger regional domain. In order to develop more robust and operational methods, we need to look at how we can utilize the MODIS instruments on the Terra and Aqua platforms, which can provide daily temporal coverage.}, added-at = {2008-07-03T18:17:33.000+0200}, author = {Jackson, Thomas J. and Chen, Daoyi and Cosh, Michael and Li, Fuqin and Anderson, Martha and Walthall, Charles and Doriaswamy, Paul and Hunt, E. Ray}, biburl = {https://www.bibsonomy.org/bibtex/29ff1efcaa6d2e7d83c5fcb36f7cf5f39/jgomezdans}, booktitle = {2002 Soil Moisture Experiment (SMEX02)}, description = {ScienceDirect - Remote Sensing of Environment : Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans}, interhash = {3dfb74ae99078f10132ec946f27b760d}, intrahash = {9ff1efcaa6d2e7d83c5fcb36f7cf5f39}, journal = {Remote Sensing of Environment}, keywords = {Soil drought evaporation moisture ndwi reflectance remotesensing satellite soilmoisture stress vegetation}, month = Sep, number = 4, pages = {475--482}, timestamp = {2008-07-03T18:17:33.000+0200}, title = {Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans}, url = {http://www.sciencedirect.com/science/article/B6V6V-4B8BWHY-1/1/bcff206f3a4c9678088761e8bc7d7e98}, volume = 92, year = 2004 }