ETSITGC, Universidad Politécnica de Madrid, Madrid, Spain.
Sensors (Basel). 2012;12(3):3528-61. doi: 10.3390/s120303528. Epub 2012 Mar 13.
Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth's resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.
土地覆盖物会在各种时间和空间尺度上不断发生变化。这些变化会对人类和自然活动产生重大影响。通过使用不同传感器（如卫星图像、航空照片等）获取的图像来维护一个具有最新发生变化的空间数据库，可以更好地监测地球资源和环境管理。事实证明，使用图像的变化检测 (CD) 技术是一种合适且安全的数据源，可以从中高效地提取更新信息，从而可以对变化进行清查和监测。本文提出了一种用于多分辨率数据集的多源 CD 方法。首先，处理不同的变化指数，然后将不同的阈值算法应用于这些指数的变化/无变化，以便更好地估计这些类别的统计参数，最后将指数集成到一个变化检测多源融合过程中，该过程可以从多个指数组合中生成一个单一的 CD 结果。该方法已应用于具有不同光谱和空间分辨率特性的数据集。然后，通过质量控制分析以及补充图形表示来评估获得的结果。所提出的方法还被证明可以有效地识别出变化检测指数中贡献更高的指数。
