caa a22 4500 445301147 CHVBK 20180317142558.0 cr unu---uuuuu 170323e20101101xx s 000 0 eng 10.1007/s11430-010-4078-9 doi (NATIONALLICENCE)springer-10.1007/s11430-010-4078-9 Crop area and leaf area index simultaneous retrieval based on spatial scaling transformation [Elektronische Daten] [WenJie Fan, BinYan Yan, XiRu Xu] Accurate estimation of crop yields is crucial for ensuring food security. However, crops are distributed so fragmentally in China that mixed pixels account for a large proportion in moderate and coarse resolution remote sensing images. As a result, unmixing of mixed pixel becomes a major problem to estimate crop yield by means of remote sensing method. Aimed at mixed pixels, we developed a new method to introduce additional information contained in the spatial scaling transformation equation to the canopy reflectance model. The crop area and LAI can be retrieved simultaneously. On the basis of a precise and simple canopy reflectance model, directional second derivative method was chosen to retrieve LAI from optimal bands of hyper-spectral data; this method can reduce the impact of the canopy non-isotropic features and soil background. To evaluate the performance of the method, Yingke Oasis, Zhangye City, Gansu Province, was chosen as the validation area. This area was covered mainly by maize and wheat. A Hyperion/EO-1 image with the 30 m spatial resolution was acquired on July 15, 2008. Images of 180 m and 1080 m resolutions were generated by linearly interpolating the original Hyperion image to coarser resolutions. Then a multi-scale image serial was obtained. Using the proposed method, we calculated crop area and the average LAI of every 1080 m pixel. A SPOT-5 classification figure serves as the validation data of crop area proportion. Results show that the pattern of crop distribution accords with the classification figure. The errors are restrained mainly to −0.1-0.1, and approximate a Normal Distribution. Meanwhile, 85 LAI values obtained using LAI-2000 Plant Canopy Analyzer, equipped with GPS, were taken as the ground reference. Results show that the standard deviation of the errors is 0.340. The method proposed in the paper is reliable. Science China Press and Springer-Verlag Berlin Heidelberg, 2010 scale transformation nationallicence remote sensing nationallicence crop yield estimation nationallicence simultaneous retrieval nationallicence crop area nationallicence leaf area index nationallicence Fan WenJie Institute of RS and GIS, Peking University, 100871, Beijing, China aut Yan BinYan Institute of RS and GIS, Peking University, 100871, Beijing, China aut Xu XiRu Institute of RS and GIS, Peking University, 100871, Beijing, China aut Science China Earth Sciences SP Science China Press 53/11(2010-11-01), 1709-1716 1674-7313 53:11<1709 2010 53 11430 https://doi.org/10.1007/s11430-010-4078-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11430-010-4078-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Fan WenJie Institute of RS and GIS, Peking University, 100871, Beijing, China aut NATIONALLICENCE 700 1- Yan BinYan Institute of RS and GIS, Peking University, 100871, Beijing, China aut NATIONALLICENCE 700 1- Xu XiRu Institute of RS and GIS, Peking University, 100871, Beijing, China aut NATIONALLICENCE 773 0- Science China Earth Sciences SP Science China Press 53/11(2010-11-01), 1709-1716 1674-7313 53:11<1709 2010 53 11430 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer