基于遥感技术的水稻抽穗期长势分级监测研究

选择黑龙江省泰来县为试验样区,利用环境减灾卫星数据,结合遥感、地理信息系统和全球定位系统技术手段对水稻种植面积进行监测并分析水稻抽穗期的长势情况。利用地形图,对卫星影像数据进行精校正,结合GPS调查点建立的解译标志,采用人机交互目视解译方法进行水稻面积提取,解译精度在95%以上。最后,根据水稻抽穗期的植被覆盖指数反演的叶面积指数数据信息,进行水稻长势分析与分等定级,结果表明:泰来县水稻抽穗期长势分为3个等级。叶面积指数小于4.2的为水稻长势弱的地域,占水稻总面积的5.53%,在4.2～5.9的为长势正常区域,占水稻总面积的67.80%,大于5.9的为长势旺盛区域,占水稻总面积的26.67%。

Monitoring on Rice Growth in Heading Stage Based on Remote Sensing Technology

Taking Tailai county of Heilongjiang province as the experimental area,using environmental satellite data for disaster reduction,combining with the rice planting area monitoring by remote sensing,geographic information systems and global positioning system techniques,the growing conditions of rice in heading stage was to monitor and analyze.Topographic maps were used to precise correction of satellite image data,combined with the GPS survey points to establish interpretation signs,the use of interactive visual interpretation methods was used to extract rice area,the interpretation accuracy was 95% or more.Finally,according to leaf area index data inversion vegetation cover exponential in rice heading stage,the rice growth was analyzed and classified and graded.The result showed that the rice growth during heading stage in Tailai county was divided into three grades.Leaf area index(LAI) lower than 4.2 weak growth district,which accounting for 5.53% of the whole rice planting area;LAI between 4.2 and 5.9 was divided as normal district,which accounting for 67.80% of the whole rice planting area;LAI more than 5.9 was divided as exuberant district,which accounting for26.67% of the whole rice planting area.