利用地形、土壤和作物信息辅助提高东北漫岗地数字高程模型精度的新方法

马雨阳,官海翔,杨昊轩,邵帅,邵逸群,刘焕军

A New Method to Improve the Accuracy of Digital Elevation Model in Northeast China by Using Terrain, Soil and Crop Information

MA YuYang,GUAN HaiXiang,YANG HaoXuan,SHAO Shuai,SHAO YiQun,LIU HuanJun

表2 改进SRTM的预选变量

Table 2 Improved the preselected variables of SRTM

变量 Variable 描述 Description 数据源 Source 归一化植被指数 NDVI (NIR-RED)/(NIR+RED) SPOT-6 绿度 TCG -0.2848×B2-0.2435×B3-0.5436×B4+0.7243×B8+0.0840×B11-0.1800×B12 Sentinel-2A 亮度 TCB 0.3037×B2+0.2793×B3+0.4743×B4+0.2285×B8+0.5082×B11+0.1863×B12 Sentinel-2A 湿度TCW 0.1509×B2+0.1973×B3+0.3279×B4+0.3406×B8+0.7112×B11+0.4572×B12 Sentinel-2A 归一化湿度指数NDMI (B3-B11)/(B3+B11) Sentinel-2A 潜在太阳辐射 PSR 根据地形和仰视半球视域范围算法得到 According to the terrain and looking up hemisphere field of view algorithm SRTM SRTM 通过航天飞机雷达地形测绘任务获得的30 m高分辨率的地形数据 30 m high-resolution terrain data obtained through SRTM SRTM