应用遥感、GIS对稻田生态系统健康程度的监测评价研究--以长江下游平原为例

Monitoring and evaluating the health degree of paddy agricultural ecosystem utilizing remote sensing and GIS data:Application to Lower Yangtze River Plain

稻田生态系统是在一定时间和地区内由作物、动物、微生物和环境因素共同构成的农业生产体系,具有时空动态性,受人工调控性和环境影响很大。由于稻谷是我国最主要的粮食作物,因此稻田生态系统健康程度直接关系着稻谷产出水平和国家粮食安全。开展我国稻田生态系统健康程度的动态监测,具有十分重要的现实意义。该研究利用遥感、GIS技术快速获取和分析区域尺度范围内的地表时空信息数据的优势,建立一套能够客观全面地监测评价稻田生态系统运行状态的指标体系和评价方法。该方法主要是根据稻田生态系统的构成要素,分别建立作物长势指数(CGI)、稻田环境指数(EI)、病虫害指数(PIDI)三个指数表征这些要素。最后,确定各个指数的权重,建立生态系统健康程度综合指数(EHDCI),客观、全面地反映稻田生态系统的健康状况。这里,作物长势指数指示作物长势,通过EVI归一化计算得到。稻田环境指数分为温度指数(TI)和降水指数(PI)分别指代水、热条件对生态系统的胁迫。病虫害指数主要通过官方农业网站发布的病虫害信息确定得到。本文以长江下游平原稻田为例,对孕穗期、抽穗期、黄熟期等水稻生长关键期的稻田生态系统运行状态进行监测评价。结果表明,2006年长江下游平原稻田生态系统总体运行状态较好,孕穗期和抽穗开花期表现正常,其中安徽最好,健康程度高于正常水平,江苏部分地区在黄熟期健康程度较差。结合2006年各地区的稻谷产出水平,这一监测评价方法能客观地反映长江下游平原稻田生态系统总体运行趋势,可为有关部门采取相应政策措施,以确保稻田生产稳定发展,提供重要的科学依据。

Paddy rice ecosystem is a fanning system composed of paddy, animals, microbes and environmental factors in specific period of time and place, with features of temporal and spatial dynamics. Since paddy rice is a main grain crop to feed above half of population in China, the performance of paddy rice ecosystem is highly concerned to yield level of paddy and food supply safety in China. Therefore, monitoring the performance of paddy rice ecosystem is very important to obtain the required information for evaluation of ecosystem health. In the study we intend to develop an approach to monitor the ecosystem performance spatially and dynamically in a regional scale using MODIS remote sensing data and GIS spatial mapping. On the basis of key factors governing the paddy rice ecosystem, we accordingly develop the following three indicators for the evaluation： Crop Growth Index （CGI）, Environmental Index （El）, and Plant Insect and Disease Index （PIDI）. Then, we integrated the three indicators into a model with different weight coefficients to calculate Ecosystem Health Degree Comprehensive Index （EHDCI） to evaluate the performance and functioning of paddy rice ecosystem in a regional scale. CGI indicates the health status of paddy rice calculated from the normalizing Enhanced Vegetation Index （EVI） retrieved from MODIS data. El is estimated from Temperature Index （TI） and Precipitation Index （PI） indicating heat and water stress on the rice field. PIDI reflects the damage brought by insects and diseases, which can be estimated using the information obtained from governmental websites. Applying the approach to Lower Yangtze River Basin, we monitor and evaluate the performance of paddy rice ecosystem in various stages of rice growing period in 2006. The results indicated that the performance of the eeosystem was generally very encouraging. During booting stage and heading and blooming stage, the health level was the highest in Anhui province, which is the main paddy rice producer in the region. During stage of yellow ripeness, Jiangsu province had lowest level of performance. Yield level of paddy rice in 2006 confirms that the applicability of the proposed approach for a rapid evaluation and monitoring of agricultural ecosystem performance in Lower Yangtze River Basin. As a result, the new approach could supply scientific basis for relevant departments taking policies and measures to make sure stable development of paddy yield.