Extraction of Winter Wheat Area and Growth Analysis Based on Remote Sensing Imagery of Adjacent Tracks

• Main Authors: LIN Fen, ZHAO Geng-xing, CHANG Chun-yan
• Format: Article
• Language: zho
• Published: Agro-Environmental Protection Institute, Ministry of Agriculture 2016-07-01
• Series: Journal of Agricultural Resources and Environment
• Subjects: remote sensing; winter wheat; area; growing situations
• Online Access: http://www.aed.org.cn/nyzyyhjxb/html/2016/4/20160412.htm

Winter wheat is one of the most valuable crops in Northern China, so getting a good knowledge of real-time information of its area and growing situation can help the manager of agricultural production and financial departments to make better decisions, meanwhile it can also increase the output capacity and farmers' income. In this paper, Binzhou City and Dongying City of Shandong Province were taken as the research areas. We extracted the information of winter wheat from ETM+ remote sensing image based on a combined method of principal component analysis, supervised and unsupervised classification. The growing situation of winter wheat in Binzhou was estimated through clustering analysis in SPSS, and winter wheat growing situation in Dongying was predicted by building vegetation growing situation hierarchical model in adjacent tracks using the distance-weighted method. The results showed that the mean extracting precision was 93.79%. There was a clear tendency of its distribution with characteristics of concentrated in the west and in the south other than that in the east and in the north. Also the regions where the wheat was concentrately distributed had better growth in general. We found that the vegetation growing situation hierarchical model built with distance-weighted method in the overlapping areas could eliminate the time differences between two remote sensing images in adjacent tracks to some extent, and it was beneficial for winter wheat growth analysis in large-scale regions.