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Phenological metrics-based crop classification using HJ-1 CCD images and Landsat 8 imagery

International Journal of Digital Earth 2018年第12期11卷 1219-1240页

作者： Xiaochun Zhang Qinxue Xiong Liping Di Junmei Tang Jin Yang Huayi Wu Yan Qin Rongrui Su Wei Zhou State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhanPeople’s Republic of China College of Agriculture Yangtze UniversityJingZhouPeople’s Republic of China Center for Spatial Information Science and Systems(CSISS) George Mason University(GMU)FairfaxVAUSA Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijingPeople’s Republic of China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanPeople’s Republic of China Jingzhou Agricultural Meteorologic Trial Station JingzhouPeople’s Republic of China

Crop type data are an important piece of information for many applications in *** crop type using remote sensing is not easy because multiple crops are usually planted into small parcels with limited availability of satellite images due to weather *** this research,we aim at producing crop maps for areas with abundant rainfall and small-sized parcels by making full use of Landsat 8 and HJ-1 charge-coupled device(CCD)*** masked out non-vegetation areas by using Landsat 8 images and then extracted a crop map from a longterm time-series of HJ-1 CCD satellite images acquired at 30-m spatial resolution and two-day temporal *** increase accuracy,four key phenological metrics of crops were extracted from time-series Normalized Difference Vegetation Index curves plotted from the HJ-1 CCD *** phenological metrics were used to further identify each of the crop types with less,but easier to access,ancillary field survey *** used crop area data from the Jingzhou statistical yearbook and 5.8-m spatial resolution ZY-3 satellite images to perform an accuracy *** results show that our classification accuracy was 92%when compared with the highly accurate but limited ZY-3 images and matched up to 80%to the statistical crop areas.

关键词： Crop type classification multi-temporal satellite images HJ-1 CCD

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