DOI: 10.5281/zenodo.2373797
title: Planetary Surface Features Change Detection Dataset

description: <strong>Summary</strong> This dataset contains bi-temporal images pairs with associated labels of <em>change </em>or <em>no-change</em> describing whether there was a change in surface features between the two images acquired over the same location at two different times. This dataset contains images from four different instruments orbiting three different planets, each of which contains four representations of the bi-temporal image pair: composite grayscale, absolute difference, signed difference, and autoencoder bottleneck representations (described in detail in [1]). We also include the grayscale image tiles these representational datasets were created from. All datasets contain 100x100 images tiles that were cropped from larger images. We describe each below. <strong>Contents</strong> <strong>hirise_rsl.zip</strong> : all subdirectories contain <em>change </em>and <em>no-change </em>examples represented as composite grayscale, absolute difference, signed difference, and autoencoder bottleneck from a before and after HiRISE image of recurring slope lineae on Mars<em>. </em>Subdirectory names are garni_XXXXXX_YYYYYY where Garni is the name of the crater on Mars shown in the images, XXXXXX is the HiRISE image ID of the before image, and YYYYYY is the HiRISE image ID of the after image. The "*_lcn" ending on some directories indicates that local contrast normalization was applied. The "*_gs_illum" and "*_gs_slope" directories contain composite grayscale representation with a third band that contains the difference between illumination (illum) and slope values at the same locations. Images with line endings _vflip, _hflip, _rot90, _rot180, and _rot270 were the result of vertical flips, horizontal flips, 90-deg rotations, 180-deg rotations, and 270-deg rotations of the image with the corresponding prefix. <strong>ctx_impacts.zip</strong> : all subdirectories contain <em>change </em>and <em>no-change </em>examples represented as composite grayscale, absolute difference, signed difference, and autoencoder bottleneck from a before and after CTX image of meteorite impacts on Mars. The prefix in each image name corresponds to the image pair described in the Appendix in [1]. <strong>lroc_impacts.zip </strong>: all subdirectories contain <em>change </em>and <em>no-change </em>examples represented as composite grayscale, absolute difference, signed difference, and autoencoder bottleneck from a before and after LROC image of meteorite and spacecraft landing impacts on the Moon. Filenames correspond to pair names provided in the Appendix in [1]. <strong>planet_misc.zip</strong> : all subdirectories contain <em>change </em>and <em>no-change </em>examples represented as composite grayscale, absolute difference, signed difference, and autoencoder bottleneck from a before and after PlanetScope image of miscellaneous processes on Earth. Filenames correspond to pair names provided in the Appendix in [1]. <strong>*_before_after_grayscale.zip</strong> : before and after grayscale tiles used to create image representations in above directories (indicated with _before and _after suffix in filenames). Images that contain "_0_" in the filename have the label <em>no-change </em>and images with "_1_" in the filename have the label <em>change</em>. [1] Kerner et al. (2019) Deep Learning Methods Toward Generalized Change Detection on Planetary Surfaces. In review at <em>Journal of Selected Topics in Earth Observations and Remote Sensing</em>. <strong>Attribution</strong> If you use this dataset in your own work, please cite this DOI: 10.5281/zenodo.2373798 as well as the paper below: Kerner, H. R., Wagstaff, K. L., Bue, B. D., Gray, P. C., Bell, J. F., & Amor, H. B. (2019). Toward generalized change detection on planetary surfaces with convolutional autoencoders and transfer learning. <em>IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</em>, <em>12</em>(10), 3900-3918.