| 摘要: |
| 该研究借助遥感与GIS技术，考虑影响农业生态系统的关键因素，选取植被指数、地表温度、降 水距平以及自然灾害等主要指标，建立了我国农业生态评价的指标体系。根据研究所提出的指标体系以及 评价方法，开展了2006年3月上旬到10月上旬的全国农业生态综合评价，并详细分析了每个月我国各地 区的生态状况，结果表明我国2006年农业生态总体状况比较好，只有个别地区比较差。该研究所提出的基 于遥感与GIS的农业生态指数评价方法，可以及时有效地获取全国范围内农业生态系统状况，而且可以考 虑长期业务化运行，它将能为全面掌握我国农业生产状况，保障我国农业平稳发展有非常重要的意义。 |
| 关键词: 农业生态指数 遥感监测 MODIS数据 |
| DOI：10.7621/cjarrp.1005-9121.20100113 |
| 分类号: |
| 基金项目: |
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| AN INDEX APPROACH FOR EVALUATION OF AGRICULTURAL ECOSYSTEM PERFORMANCE USING MODIS REMOTE SENSING DATA IN CHINA |
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Gao Maofang, Qiu Jianjun, Ren Tianzhi, Qin Zhihao
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Institute of Agricultural Resources and Regional Planning， Chinese Academy of Agricultural Sciences， Beijing 100081
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| Abstract: |
| Agricultural ecosystem is a complicated system with various factors. At present， evaluation of agricultur- al ecosystem performance has been done mainly on the basis of socioeconomic statistics data in a comparatively small area. With the development of science and technology， it is possible to monitor the ecosystem performance dynamically in a large area using remote sensing data. In this study we proposed a new approach to evaluate the performance of agricultural ecosystem in the whole China. The approach is an index method with data inputs from remote sensing and Geographical Information System（GIS）. Considering key factors determining the functioning of agricultural ecosystem in a large scale， we choose the following indicators to develop a model for the evaluation: vegetation index， land surface temperature， precipitation index and disaster index. These factors indicate the per- formance and functioning of agricultural system and have been considered in the study as the key factors in evalua- tion of the system in a large scale. Using the approach， we integrated the four factors into a model with vegetation index and land surface temperature retrieved from MODIS data and precipitation index and disaster index from GIS of agricultural statistics. Performance of agricultural system of the entire China from March to October in 2006 has been evaluated in the study. Comprehensive analysis of the performance for various regions and detailed results of the analysis has also been presented. The results indicate that the performance in general is very encouraging in the whole China. Only a few regions within a specified period of time， for example， Guangdong and Guangxi in spring and Chongqing in August， have low level of performance. Our study confirms that the applicability of the proposed approach for a rapid evaluation and monitoring of agricultural ecosystem performance in the entire China. |
| Key words: agricultural ecosystem remote sensing monitoring |
