This paper presents some preliminary results using Landsat and Worldview images for change detection. The studied area had some significant changes such as construction of buildings between May 2014 and October 2015. We investigated several simple, practical, and effective approaches to change detection. For Landsat images, we first performed pansharpening to enhance the resolution to 15 meters. We then performed a chronochrome covariance equalization between two images. The residual between the two equalized images was then analyzed using several simple algorithms such as direct subtraction and global Reed-Xiaoli (GRX) detector. Experimental results using actual Landsat images clearly demonstrated that the proposed methods are effective. For Worldview images, we used pansharpened images with only four bands for change detection. The performance of the aforementioned algorithms is comparable to that of a commercial package developed by Digital Globe.
Ground object detection is important for many civilian applications. Counting the number of cars in parking lots can provide very useful information to shop owners. Tent detection and counting can help humanitarian agencies to assess and plan logistics to help refugees. In this paper, we present some preliminary results on ground object detection using high resolution Worldview images. Our approach is a simple and semi-automated approach. A user first needs to manually select some object signatures from a given image and builds a signature library. Then we use spectral angle mapper (SAM) to automatically search for objects. Finally, all the objects are counted for statistical data collection. We have applied our approach to tent detection for a refugee camp near the Syrian-Jordan border. Both multispectral Worldview images with eight bands at 2 m resolution and pansharpened images with four bands at 0.5 m resolution were used. Moreover, synthetic hyperspectral (HS) images derived from the above multispectral (MS) images were also used for object detection. Receiver operating characteristics (ROC) curves as well as detection maps were used in all of our studies.
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