A Review of Remote Sensing Application in Crop Type Discrimination

doi:10.11924/j.issn.1000-6850.2014-0380

Abstract

Abstract: Timely crop planting acreage and yield information are important basis for researching regional balance of food supplies, predicting overall agricultural productivity and population carrying capacity. Remote sensing technology has become an important means to extract crop acreage, while the prerequisite is crop type discrimination. In order to illuminate the current status of research in this field at home and abroad, based on the remote sensing application in crop type discrimination, this paper firstly introduced the remote sensing data commonly used in crop type discrimination researches, including Landsat satellite imagery, meteorological satellite imagery, high resolution imagery, hyperspectral remote sensing imagery, and microwave remote sensing imagery, then further analyzed the advantages, disadvantages and practicability of each type of remote sensing data. Moreover, this paper summarized three types of crop type discrimination methods based on remote sensing, namely, the methods based on spectral characteristic, those based on phenology differences and the combination of both methods, and analyzed the characteristics of various methods. Finally this paper pointed out and discussed the current problems in the crop type remote sensing discrimination researches, for instance, the balance of image spatial resolution and price, comprehensive application of multi- resolution remote sensing data, the impact of phenological differences on crop type discrimination, etc. The author considered that the combination of different resolution remote sensing data could compensate for their lack; temporal selection of remote sensing images was the key to improve the discrimination accuracy; in addition, more interpretation signs need to be applied besides spectrum and phenology. Therefore, the author recommended further development crop discrimination mechanism and multi-scale image data fusion method, making research results more accurate and practical. The study could provide the references for the remote sensing crop type discrimination in-depth research.

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