【摘要】 利用气象卫星 NOAA AVHRR资料 ,反演出农作物生育期内每日和旬度的 N DVI数据 ,分析了 NDVI时间曲线的波动与农作物生长发育阶段及农作物长势的响应规律 ,并以华北冬小麦为例 ,探讨了 N DVI在冬小麦各生育期的积分值与农作物单产之间的相关关系。结果表明 ,利用长时间序列的 N DVI数据 ,结合作物的物候历 ,可以实现作物长势的遥感监测和产量遥感估算。更多还原

【Abstract】 Growing situation monitoring and yield estimation of crops is an important region of agriculture research using remote sensing. Electronic waves reflected or emitted by crops and surface objects passed through atmosphere and reached the surface of sensors onboard satellite. The variation of the waves can be recorded and useful indexes reflecting growing status of crops can be created with proper procession and analysis. Therefore, continuously monitoring of growing status of crops can be carried out successfully. Reflecting values of cropland surface are influenced by many factors including environmental factors (such as solar angle, cloud, aerosol etc.) and inner factors (such as physical condition of leaves, leaf area, geometry structure of canopy, etc.). Giving same environmental factors, variation of emission lights and reflecting values in certain extent indicate growing status, growing season, and physical condition of crops. With the help of meteorological satellite NOAA AVHRR images (one image a day, with 1.1 km ×1.1km spatial resolution) from sowing to harvest, we can find that temporal variation of emission lights and reflecting values have their special characters, which demonstrate the process of the bare soil replaces by green vegetation (crops) step by step. Spectral vegetation indices, which are integrated data of several bands of satellite images, have been widely used in order to derive useful information of canopies, meanwhile, deduce interference of background. There are two absorbing zones in the typical spectrum profile of green vegetation: one is in blue band and another is in red band. In near infrared spectral region, there is a peak of reflectance. These are caused by pigments and inner structure of leaves. The sensors of NOAA AVHRR were just designed to catch these characters: the first band CH 1(0.58～0.68μm)was in the absorbing zone of chlorophyll, and the second band CH 2(0.725～1.1μm)was in the reflecting zone of vegetation. So that the CH 1 and CH 2 are always used together to form vegetation indices. The Normalized Difference Vegetation Index(NDVI)is a case in point. The normalization algorithm of NDVI gives much help to distinguish vegetation with background soil; meanwhile, it deduces the influences of atmosphere and elevation. NDVI is sensitive to the variation of soil. The NDVI of vegetation varies in different land-cover circumstances, it is somewhat large than bare soil in the case of low cover (vegetation covering ratio is smaller than 15%); it increases linearly when vegetation covering ratio increase in the case of middle cover (vegetation covering ratio is between 25% and 80%); and the sensitivity of detecting will decrease when vegetation covering ratio lager than 80%. Daily Normalized Difference Vegetation Index (NDVI) data in every growing season of winter wheat had been retrieved using meteorological satellite NOAA AVHRR images. In order to deduce influences of cloud and atmosphere, NDVI data may be composed using proper algorithm in certain time duration. The most popular method is “decade composing”, which means maximum NDVI of a decade will be selected to represent the NDVI value of this decade. In this study, decade NDVI of Huang Huaihai plain in 1999 were calculated and the NDVI database was established as the foundation of further studies. According to these data, the principle of the variety of NDVI profile in answer to growing situation of winter wheat had been discussed thoroughly. About 60 counties with different yield levels (high, middle, low) were selected as samples. Putting NDVI values of a whole growing season onto the NDVI-Time coordination, dynamic trace profiles of crop growing will be achieved. These profiles indicate variation of NDVI from sowing to harvest. Different types of crops and different growing condition have different types of NDVI profile. It was found that there were three key points on the NDVI profile, which were turning points of growing season of crops: (1) Starting point of growing in spring; (2) Pick point of NDVI profile;更多还原