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Li G.,Hulunber State Station of Grassland Ecosystem Field Observation and Scientific Research | Li G.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Li G.,Chinese Academy of Agricultural Sciences | Zhang H.,Chinese Academy of Agricultural Sciences | And 6 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2010

The accuracy validation of the MODIS/FAPAR product is a prerequisite for using it to estimate local net primary production (NPP), and to supply service for monitoring the balance of region carbon and arranging production of grassland animal husbandry rationally. For this purpose, we designed and carried out in-situ measurements of FAPAR in two 2 km×2 km areas within the temperate meadow-steppe grassland in Hulunber during growing season in 2008, and analyzed heterogeneity of the two sites using image of Beijing-1 satellite with resolution of 32 m, and then scaled up and validated MODIS/FAPAR products with in-situ measured data in grassland area. The results showed that the MODIS FAPAR product reflected very well the seasonal dynamics of in-situ FAPAR, but tended to overestimate the value with averaged relative error of 13.7% in the Stipa Baicalensis site and 18.7% in the Leymus Chinensis site. The MODIS/FAPAR algorithm was derived based on the global land cover map, which may be too broad for local areas. More fieldworks for various types of the grasslands are necessary.


Zhang H.,Hulunbuir Grassland Ecosystem Observation and Research Station | Zhang H.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Zhang H.,Chinese Academy of Agricultural Sciences | Yang G.,Hulunbuir Grassland Ecosystem Observation and Research Station | And 10 more authors.
2010 World Automation Congress, WAC 2010 | Year: 2010

This paper demonstrates the design of inter database retrieval system based on Multi-Agent. Interface agent, cooperation agent, collection agent, retrieval agent are used to realize intelligence in this system. A mobile agent is adopted to communicate with other agents. They coordinate with each other to complete retrieval tasks. The system is an important research project in the field of Web database retrieval. It can meet the user's demand of inter database retrieval. At the same time the hotspot issues in the system are studied and discussed.


Jiang L.,Chinese Academy of Sciences | Zhang H.,Hulunbuir Grassland Ecosystem Observation and Research Station | Zhang H.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Zhang H.,Chinese Academy of Agricultural Sciences
2010 World Automation Congress, WAC 2010 | Year: 2010

With the increasing web information and structure diversity of multi-element heterogeneous information, traditional information collection is limited in application. Individual information collection service and intelligence of web information collection become the focus. This paper adopts the technology of individual web spider and designs a multi-agent - based individual web spider system. The individual web spider model is the emphasis of this paper, besides system architecture, work mechanism and system components. The system consists of delivering agent, processing agent, analyzing agent, cooperation agent and adopts cooperation agent to resolve cooperation problems among agents. This system has been proved to be very effective through many experiments in different conditions.


Huang Q.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Huang Q.,Chinese Academy of Agricultural Sciences | Zhang L.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Zhang L.,Chinese Academy of Agricultural Sciences | And 4 more authors.
2010 2nd IITA International Conference on Geoscience and Remote Sensing, IITA-GRS 2010 | Year: 2010

Crop growth monitoring timely and accurately during the growing season is of great importance for accurate yield estimation, which can provide information support for making and adjusting agricultural policies. In this paper, a MODIS-NDVI-based method for operational crop growth monitoring in China Agriculture Remote Sensing Monitoring System (CHARMS) was presented. Some meteorological data such as temperature, precipitation and sunshine, as well as the field observation data were used to modify the models parameters. The crop growth conditions were categorized into three classes, better than usual, usual and worse than usual. Finally, the application of this method to spring wheat, winter wheat, spring maize, summer maize, cotton, soybean and paddy rice and its results were introduced. © 2010 IEEE.


Huang Q.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Huang Q.,Chinese Academy of Agricultural Sciences | Zhou Q.,Key Laboratory of Resource Remote Sensing and Digital Agriculture | Zhou Q.,Chinese Academy of Agricultural Sciences | And 6 more authors.
Intelligent Automation and Soft Computing | Year: 2012

This paper presents a method used in China Agriculture Remote Sensing Monitoring System (CHARMS) for automatically identifying crop planting areas and monitoring crop growth conditions at a large scale based on time-series of MODIS NDVI Datasets. In doing that, the characteristics of NDVI time series of spring wheat, spring corn, soybean and rice in Northeastern China were firstly analyzed to determine the threshold values used for extracting different crops. Then using these thresholds, extraction models for above-mentioned four major crops were established and applied to obtain the spatial distribution of these four crops in Northeastern China in 2009. In comparison with the average statistic data of several years, the total extraction accuracy is over 87%, which suggests its feasibility to extract planting areas of different crops at a large scale using MODIS data. Based on the extracted crop planting areas, the same MODIS NDVI time series data were used to monitor crop growth conditions in 2009 and compared with the average crop growth of last five years. The crop growth conditions were categorized into three classes, better than usual, usual and worse than usual. The results showed that crop growth conditions in Northeastern China varied over both spatial and temporal scales. © 2012 Copyright TSI® Press.

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