基于数字相机、ASTER和MODIS影像综合测量植被盖度

DETERMINING VEGETATION COVER BASED ON FIELD DATA AND MULTI-SCALE REMOTELY SENSED DATA

选择我国北方温带典型草原作为研究对象,基于Bottom-up方法,采用地表实测和多尺度遥感综合测量的方法,建立基于地表实测与多尺度遥感数据综合测量的两阶段植被盖度经验模型。此外,还将该模型与常用的亚像元分解模型相比较,结果表明:1)两阶段经验模型可以较好地实现将地面数据扩展到中尺度空间范围,从而完成数据空间尺度的转换,提高大区域草地植被盖度的测量精度;2)MODIS遥感影像数据,结合地面数据和ASTER遥感影像数据可以较好地在区域范围内对北方典型草原的植被盖度进行估测;3)目前常用的亚像元分解模型,应用于中空间分辨率的MODIS影像,估测北方温度典型草原植被盖度的精度不够理想。

Aims There are problems with estimating vegetation cover using remotely sensed data. Many models have been developed by regression of field data and remotely sensed data, but this simple scale transformation often results in large errors. Our objective was to combine field data and multi-scale remotely sensed data to estimate vegetation cover for a typical temperate steppe of North China. Methods Within our research area, we selected 49 sample fields from areas with high, medimn and low vegetation cover and sampled each using 1 m plots nested within larger plots. We vertically photographed each 1 m sample plot with a digital camera positioned at 2 m height. We estimated vegetation cover in each image. Using these data and data obtained through ASTER and MODIS images, we developed a two-stage experiential model of vegetation cover based on the bottom-up method. Important findings We accurately estimated vegetation cover of typical temperate steppe of North China at a regional scale based on our two-stage model using field data and ASTER and MODIS images. Using a series of MODIS images, it would be possible to estimate vegetation cover of typical steppe across China.