NDLI: Study on information extraction of rape acreage based on TM remote sensing image

Content Provider	IEEE Xplore Digital Library
Author	Li Dandan Liu Jia Zhou Qingbo Wang Limin Huang Qing
Copyright Year	2011
Description	Author affiliation: Key Laboratory of Resources Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China (Li Dandan; Liu Jia; Zhou Qingbo; Wang Limin; Huang Qing)
Abstract	China's rape acreage and total output of rapeseeds ranks among the top in the world, accounting for more than 30% of the world's total rape acreage and output of rapeseeds. This paper takes Landsat TM as the main data source in conducting the study of extracting rape acreage information in the Shou County, Anhui Province. Through analysis and calculations of phenological diversity, spectral discrimination, etc. of various main vegetations, with remote sensing image in each growth stages of rape within the studied area, this paper concludes that the optimal time period for information extraction of rape acreage based on TM image is the flowering period for rape. This paper adopts confusion matrix calculation to compare non-supervised and supervised classification methods in extracting rape acreage information using remote sensing image. The results show that the classification results of Mahalanobis Distance method and Isodate non-supervised classification method yielded relatively good results. In which, the Isodate non-supervised classification method combined with human visual inspection can extract the rape planting area information with higher precision and efficiency. The study shows that the method by utilizing TM remote sensing data to extract information of rape acreage can get a relatively satisfactory result. We believe the rape acreage remote sensing identification technology can provide a scientific reference to the understanding of China's rape planting situation.
Starting Page	3323
Ending Page	3326
File Size	346822
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6049931
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Data mining Agriculture Monitoring Humans Inspection Buildings J-M calculation Rape Acreage information extracting TM Remote Sensing Image
Content Type	Text
Resource Type	Article

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