Urban change detection for multispectral earth observation using convolutional neural networks
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing …, 2018•ieeexplore.ieee.org
The Copernicus Sentinel-2 program now provides multispectral images at a global scale
with a high revisit rate. In this paper we explore the usage of convolutional neural networks
for urban change detection using such multispectral images. We first present the new
change detection dataset that was used for training the proposed networks, which will be
openly available to serve as a benchmark. The Onera Satellite Change Detection (OSCD)
dataset is composed of pairs of multispectral aerial images, and the changes were manually …
with a high revisit rate. In this paper we explore the usage of convolutional neural networks
for urban change detection using such multispectral images. We first present the new
change detection dataset that was used for training the proposed networks, which will be
openly available to serve as a benchmark. The Onera Satellite Change Detection (OSCD)
dataset is composed of pairs of multispectral aerial images, and the changes were manually …
The Copernicus Sentinel-2 program now provides multispectral images at a global scale with a high revisit rate. In this paper we explore the usage of convolutional neural networks for urban change detection using such multispectral images. We first present the new change detection dataset that was used for training the proposed networks, which will be openly available to serve as a benchmark. The Onera Satellite Change Detection (OSCD) dataset is composed of pairs of multispectral aerial images, and the changes were manually annotated at pixel level. We then propose two architectures to detect changes, Siamese and Early Fusion, and compare the impact of using different numbers of spectral channels as inputs. These architectures are trained from scratch using the provided dataset.
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