A review of data assimilation of remote sensing and crop models

A comprehensive drought monitoring method integrating MODIS and TRMM data

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=3085&context=usdaarsfacpub

Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model

Assimilation of remote sensing into crop growth models: Current status and perspectives

Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

Monitoring winter wheat growth in North China by combining a crop model and remote sensing data

Desertification was defined as “land degradation in arid, semi-arid or sub-humid dry areas resulting from various factors including climatic variations and human activities” in the United Nations Convention to Combat Desertification (UNCCD) About two-thirds of the countries of the world, one-fifth of the global population and one-fourth of the land of the earth are now affected by desertification with a direct economic loss about US$ 423 billion every year Desertification has become a source of poverty and a constraint to socioeconomic sustainable development Combating desertification, ecological improvement and sustainable development is an imperative hard task for the world

/pdf/coping-strategies-with-desertification-in-china-3twz2whkhw.pdf

Coping Strategies with Desertification in China

Winter wheat growth simulation under water stress by remote sensing in north China

In order to assess the climatical and ecological effect which returned the farmland to pasture or forest,the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification.Compared with the data from Statistical Department and actual investigation,the precision of the classified result was above 85%.

The vegetation classification of the return farmland to pasture or forest region in Shaanxi-Gansu-Ningxia based on SPOT/VEGETATION data.

The senior author of this second introduction lectures in China almost annually and is involved in research in China since 1996, initially particularly in Nanjing, Beijing and Inner Mongolia. A new project, presently core funded by the China Meteorological Administration (CMA), was originally prepared (and largely funded) by the Asian Picnic Model Project (APMP, Agromet Vision) and China Agricultural University (CAU), Beijing, from 2004 till 2007, in several missions by Zheng Dawei (CAU) and Kees Stigter (APMP) to five provinces and a preliminary project submission to CMA in 2007.

Wang Shili

Papers

Monitoring winter wheat growth in North China by combining a crop model and remote sensing data

Coping Strategies with Desertification in China

Winter wheat growth simulation under water stress by remote sensing in north China

The vegetation classification of the return farmland to pasture or forest region in Shaanxi-Gansu-Ningxia based on SPOT/VEGETATION data.

Introduction to Part II (CMA/CAU/APMP Examples)