基于多源遥感数据的甘蔗霜冻监测评估

利用Landsat 8 OLI遥感数据提取云南耿马县甘蔗集中种植区,结合中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)历史数据和野外调查数据制定甘蔗霜冻分级指标,通过多时相甘蔗归一化植被指数(normalized difference vegetation index,NDVI)变化差异对2013年底耿马县甘蔗霜冻进行灾后监测评估。结果表明:利用Landsat 8较高分辨率及光谱可分性强的优势,结合非监督分类、监督分类以及归一化植被指数阈值剔除法可迅速有效地提取甘蔗集中种植区。甘蔗全生育期MODIS NDVI变化曲线表明,正常年份12月甘蔗NDVI平均下降0.03±0.01,结合野外调查制定的分级指标可对甘蔗霜冻进行有效评估,评估结果在空间分布上与实况相符合,面积统计结果误差小于6%。

Monitoring Sugarcane Frost Injury Using Multi-sources Remote Sensing Images

Landsat8 OLT remote sensing data is utilized to extract sugarcane planting area of Gengma county in Yunnan province. Sugarcane frost classification indexes are developed using MODIS historical series combined with field investigations. Then, frost disaster happened in the end of 2013 are evaluated with multi-phases images by using NDVI difference method. The results show that: Landsat 8 OLI provides an excellent resource to sugarcane classification with its higher resolution and subtle spectrum. Sugarcane distinction becomes more efficiency with the incorporation of non-supervised classification and supervised classification and vegetation index threshold method. MODIS NDVI change curve of sugarcane during the whole stages shows that the normal year drop value of sugarcane NDVI is 0.03±0.01 in December. Combined with field investigation, classification index is made for sugarcane frost evaluation. Remote sensing valuation result is high consistent with the actual survey and its error is less than 6%.