Ainong Li

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Accurate, objective, reliable, and timely predictions of crop yield over large areas are critical to helping ensure the adequacy of a nation's food supply and aiding policy makers on import/export plans and prices. Development of objective mathematical models of crop yield prediction using remote sensing is highly desirable. In this study, we develop a new(More)
Remotely sensed data, with high spatial and temporal resolutions, can hardly be provided by only one sensor due to the tradeoff in sensor designs that balance spatial resolutions and temporal coverage. However, they are urgently needed for improving the ability of monitoring rapid landscape changes at fine scales (e.g., 30 m). One approach to acquire them(More)
The upper reaches of Minjiang River-valley, located on the eastern edge of Qinghai–Tibet Plain, is characterized by the complex distribution of hills and valleys. It is a typical and key mountainous region with apparent upland ecosystem vulnerability and sensitivity according to National Eco-environmental Renovating Scheme of china. In order to analyze(More)
Maximal light use efficiency (LUE) is an important ecological index of a vegetation essential attribute, and a key parameter of the LUE-based model for estimating large-scale vegetation productivity by remote sensing technology. However, although currently used in different models there still exists extensive controversy. This paper takes the Zoige Plateau(More)
Time series remote sensing products with both fine spatial and dense temporal resolutions are urgently needed for many earth system studies. The development of small satellite constellations with identical sensors affords novel opportunities to provide such kind of earth observations. In this paper, a new dense time series 30-m image product was proposed(More)
Land surface is normally considered as a mixture of soil and vegetation. Many applications, such as drought monitoring and crop-yield estimation, benefit from accurate retrieval of both soil and vegetation temperatures through satellite observation. A preliminary study has been conducted in this study on the estimation of land surface soil and vegetation(More)
Soil moisture is a vital parameter in various land surface processes, and microwave remote sensing is widely used to estimate regional soil moisture. However, the application of the retrieved soil moisture data is restricted by its coarse spatial resolution. To overcome this weakness, many methods were proposed to downscale microwave soil moisture data. The(More)
The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI) dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS) was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in(More)