Scientia Agricultura Sinica ›› 2010, Vol. 43 ›› Issue (14): 2879-2888 .doi: 10.3864/j.issn.0578-1752.2010.14.006

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY • Previous Articles     Next Articles

Recent Progresses in Monitoring Crop Spatial Patterns by Using Remote Sensing Technologies

TANG Hua-jun, WU Wen-bin, YANG Peng, ZHOU Qing-bo, CHEN Zhong-xin
  

  1. (中国农业科学院农业资源与农业区划研究所/农业部资源遥感与数字农业重点开放实验室)
  • Received:2010-03-08 Revised:2010-04-22 Online:2010-07-15 Published:2010-07-15

Abstract:

As a new high-technology with an advantage of high temporal resolution, wide coverage and low cost, remote sensing is currently used in a wide arrange of earth observation activities and thus provides a useful tool to detect and monitor the spatial patterns of crop cultivation. Based on the systematic summary of the progress of studies in remote-sensing-based monitoring of spatial patterns of agricultural crops in the latest decade, including its theories, methods and applications, a series of problems that should be urgently resolved in the study are put forward, and some important study directions and priorities for future are viewed. Studies show that crop acreage can be monitored according to the differences in spectral characteristics of different crops, which are normally recorded by the satellite sensors. There are three major approaches used for crop acreage monitoring: spectral-based identification, phenology-based identification and multiple data-fusion-based identification methods. Mapping multiple cropping systems using remote sensing is mainly based on the crop growth curves, which can be derived from the smoothed time-series vegetation index (VI) data. Furthermore, cropping patterns can be also examined through discriminating the crop growth period from variations in time-series VI data and characteristics of different cropping patterns. How to construct the theoretical and technological systems, to develop and verify the image classification methods, to optimize the smoothing methods for time-series data and to improve the capability of automatic extraction of information could be the major development trends of this field in the future.

Key words: remote sensing, spatial patterns, crop acreage, multiple cropping system, cropping pattern

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