The impact of misregistration on change detection
The impact of misregistration on change detection
复制标题
DOI：
10.1109/36.175340
复制
发表时间：
1992-09
期刊：
影响因子：
--
通讯作者：
J. Townshend;C. Justice;C. Gurney;J. McManus
中科院分区：
文献类型：
--
作者：
J. Townshend;C. Justice;C. Gurney;J. McManus
利用空间退化的Landsat MSS图像，以归一化植被指数（NDVI）模拟图像为研究对象，评估了误配对土地覆盖变化检测的影响。对7个地区的单日期图像进行了误配，并分析了差异的统计特性。在地表没有任何实际变化的情况下，即使是亚像元错配，错配的后果也非常明显。然后，不同时期的成对图像被错配。对于四个密集覆盖的区域，由半方差测量的NDVI实际差异的50%以上的误差仅由一个像素的错配引起。为了实现仅10%的误差，需要0.2像素或更小的配准精度。对于三个半干旱气候的稀疏植被地区，0.5到1.0像素的配准精度足以实现10%或更小的误差。结果表明，为了可靠地监测全球变化，需要高水平的登记。>
The impact of misregistration on the detection of changes in land cover has been evaluated using spatially degraded Landsat MSS images, focusing on simulated images of the normalized difference vegetation index (NDVI). Single-date images from seven areas were misregistered against themselves, and the statistical properties of the differences were analyzed. In the absence of any actual changes to the land surface, the consequences of misregistration were very marked even for subpixel misregistrations. Pairs of images from different time periods were then misregistered. For four densely covered areas, an error equivalent to greater than 50% of the actual differences in the NDVI, as measured by the semivariance, was induced by a misregistration of only one pixel. To achieve an error of only 10%, registration accuracies of 0.2 pixels or less are required. For three more sparsely vegetated areas with semiarid climates, a registration accuracy of between 0.5 and 1.0 pixel was sufficient to achieve an error of 10% or less. The results indicate that high levels of registration are needed for reliable monitoring of global change. >