摘要
卫星遥感可以为农作物的精准管理提供必要、及时并具有空间连续性的信息 ,但高成本一直是限制该项技术在农业上深入发展的主要障碍。利用价格相对较为低廉的 TM卫星影像作为信息源来评价其对估测小区域内作物产量空间变异并为规划管理单元提供必要信息的可行性做了初步的研究 ,结果表明 ,利用 TM图像所获得的植被指数能较好地反映小麦各生育时期的基本特点。两种植被指数 (NDVI及 RVI)都表现出一定程度的空间变异 ,而且都以小麦抽穗后期的变异程度为最大 ,而且 ,小麦生长发育的三个重要时期 (分蘖期、抽穗期及拔节期 )的两种植被指数之间具有极显著的相关关系 ,两个试验地块小麦 1 1月 8日的归一化植被指数都与产量表现出了良好的相关关系。另外 ,两种植被指数在表现作物千粒重和亩穗数等产量指标信息方面 ,也有一定的效果。
The intention of site specific management is to optimize grower inputs on areas much smaller than the entire field. These areas may be as small as a few square meters in size. To manage a field on such a scale, data would have to be collected on a similar or smaller scale. To collect the data by hand would be very time consuming, labor intensive and destructive. In recent years, as an important component of site specific soil management in precision agriculture, remote sensing developed greatly. Satellite remote sensing is a promising technique, which could provide the essential, real time and spatially continuous crop information for site specific crop management. Specially, recent advances in the spatial, spectral and temporal resolution of remote sensing as well as potential positive changes in availability of remotely sensed data may make it a profitable tool for more farmers. However, higher cost still hinders its widespread application in agriculture production. In this paper, TM remote sensing image with relatively low cost was studied for the feasibility as a important information resource for evaluating crop yield variability and designing the management unit of soil nutrients. The results showed that Vegetation Index (VI) could reflect the wheat characteristics of each growth stage. Two VI (NDVI and RVI) showed greater spatial variability in accordance with the wheat yield in the field and the largest spatial variability occurred in the late growth period of wheat. NDVI and RVI of three important growth stages of wheat (heading, stooling and jointing stages) were significantly correlated and the significant correlation between wheat yield and NDVI on Nov.18 (stooling stage) was found. Moreover, NDVI and RVI could supply important information on some yield parameters, such as 1000 kernel weight and spike number. This research was preliminary and some other detailed studies would be needed in future.
出处
《遥感技术与应用》
CSCD
2001年第1期23-27,共5页
Remote Sensing Technology and Application
关键词
精准农业
变量变异
TM遥感
植被指数
冬小麦产量
Precision agriculture, Yield variability, TM remote sensing, Vegetation index
