Monitoring and Management of Agriculture with Remote Sensing

  • Zhongxin Chen
  • Sen Li
  • Jianqiang Ren
  • Pan Gong
  • Mingwei Zhang
  • Limin Wang
  • Shenliang Xiao
  • Daohui Jiang

The intrinsic characteristics of agriculture make remote sensing an ideal technique for its monitoring and management (Chen et al., 2004). These characteristics include: (a) Agricultural activities are usually carried out in large spatial regions, which makes the conventional field survey or census time-consuming and usually costly; (b) the per-unit-area economic output from agriculture is not so significant in comparison with other industries; (c) most of the crops are annual herbs having different growth and development stages in different seasons which means that agricultural activities have obvious phenological rhythms and the intra-annual change may be very drastic; (d) agriculture is strongly affected by human activities and management where timely and accurate monitoring information is required. These intrinsic characteristics of agriculture demand novel techniques in the monitoring of crop growth and agricultural productions. Remote sensing technology meets these requirements by its rapidness, accuracy, economy, timing, dynamic and repetitive monitoring capacity. Remote sensing technology has been applied in agriculture extensively since its early stage in the 1960s. Now several global and national operational systems of monitoring agriculture with remote sensing have been operated. The number of similar operational systems at regional scale is much more. These systems provide timely and valuable information for agricultural production, management and policy-making. On the other hand, the demands arising from the applications in agricultural sectors have also enhanced the progress and innovation in remote sensing technology. The main applications of remote sensing in agriculture management and monitoring include: crop identification and cropland mapping, crop growth monitoring and yield estimation/prediction, inversion of key biophysical, biochemical and environmental parameters, crop damage/disaster monitoring, precision farming, etc. In this paper, crop mapping, yield prediction, soil moisture monitoring and crop phenology monitoring with remote sensing are reviewed.


Soil Moisture Normalize Difference Vegetation Index Land Surface Temperature Thermal Inertia Microwave Radiometer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V 2008

Authors and Affiliations

  • Zhongxin Chen
    • 1
  • Sen Li
    • 2
  • Jianqiang Ren
    • 2
  • Pan Gong
    • 2
  • Mingwei Zhang
    • 2
  • Limin Wang
    • 1
  • Shenliang Xiao
    • 2
  • Daohui Jiang
    • 2
  1. 1.Key Laboratory of Resource Remote Sensing & Digital AgricultureMinistry of AgricultureChina
  2. 2.Institute of Agricultural Resources & Regional PlanningChinese Academy of Agricultural SciencesChina

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