黑河流域叶面积指数（LAI）空间尺度转换

为有机地整合利用不同分辨率遥感数据获取的陆面过程以及其他相关的环境变量,尺度问题越来越受到人们的重视.选取黑河张掖绿洲区为实验研究区,利用ETM 影像反演的LAI通过升尺度转换到900m分辨率,对LAI尺度转换过程中引起的误差进行了定量分析,尝试提出一种新的基于NDVI像元分解的更有效的升尺度转换方法.研究发现非线性的升尺度算法引起的误差不超过 10.5%,且误差大小与地表异质性程度正相关,而地表异质性是导致LAI尺度转化误差的主要原因,严重时可能造成 45%的偏差,但纯像元LAI的计算不受尺度影响.提出的基于NDVI像元分解的LAI升尺度转换算法,分两步考虑了地表异质性问题,很好的实现了研究区30m空间精度 LAI向900m的尺度转换,该方法应用于干旱、半干旱的中国西北黑河流域NASA 发布的MODIS LAI产品校正,取得了良好效果.

Spatial scale transferring study on Leaf Area Index derived from remotely sensed data in the Heihe River Basin, China

In order to effectively integrate various land-surface processes and environmental variables retrieved by different spatial resolution remotely sensed data, scaling issues induced by transferring for one resolution data to another have drawn more and more attentions. Taking the Zhangye Oasis in the Heihe River Basin of northwestern China as a study site, using the LAI map derived from the Landsat ETM+ image and NASA published MODIS LAI product for the same day of the region, an experimental study for up scaling the 30m spatial resolution LAI to 900m was conducted to quantitatively analyzes the error transforms in the process of LAI up scaling with the final goal of establishing a new and much effective up scaling scheme in terms of NDVI pixel decomposing techniques. It was found that less than 10.5% errors were caused by the non-linearity of algorithms utilized in LAI up scaling, and its value is highly positively correlated with the terrain heterogeneities, terrain heterogeneity is the predominate causing for the errors introduced in LAI scale transferring. The maximum error caused by terrain heterogeneity can reach to about 45%, but no error can be caused for the pure pixel LAI scale transferring. A new algorithm for LAI up scaling, based on above mentioned analyses, in terms of pixel decomposing techniques of NDVI accounting for terrain heterogeneity in two key procedures, was developed for the up scaling of 30 m LAI to 900 m with fairly satisfied resolution. This algorithm was used to correct NASA published MODIS LAI product and excellent results were obtained, which was back up with the fact that the corrected MODIS LAI product well consistent with the high spatial resolution LAI map of the study region.