IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Template

José M. Bioucas‐Dias, Antonio Plaza, Nicolas Dobigeon et al. · 1 Apr 2012

Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras. Imaging spectrometers are therefore often referred to as hyperspectral cameras (HSCs). Higher spectral resolution enables material identification via spectroscopic analysis, which facilitates countless applications that require identifying materials in scenarios…

Yushi Chen, Zhouhan Lin, Xing Zhao et al. · 1 Jun 2014

Classification is one of the most popular topics in hyperspectral remote sensing. In the last two decades, a huge number of methods were proposed to deal with the hyperspectral data classification problem. However, most of them do not hierarchically extract deep features. In this paper, the concept of deep learning is introduced into hyperspectral data…

Patrick Helber, Benjamin Bischke, Andreas Dengel et al. · 14 Jun 2019

In this paper, we present a patch-based land use and land cover classification approach using Sentinel-2 satellite images. The Sentinel-2 satellite images are openly and freely accessible, and are provided in the earth observation program Copernicus. We present a novel dataset, based on these images that covers 13 spectral bands and is comprised of ten…

Yushi Chen, Xing Zhao, Xiuping Jia · 23 Jan 2015

Hyperspectral data classification is a hot topic in remote sensing community. In recent years, significant effort has been focused on this issue. However, most of the methods extract the features of original data in a shallow manner. In this paper, we introduce a deep learning approach into hyperspectral image classification. A new feature extraction (FE)…

Meisam Amani, Arsalan Ghorbanian, Seyed Ali Ahmadi et al. · 1 Jan 2020

Remote sensing (RS) systems have been collecting massive volumes of datasets for decades, managing and analyzing of which are not practical using common software packages and desktop computing resources. In this regard, Google has developed a cloud computing platform, called Google Earth Engine (GEE), to effectively address the challenges of big data analysis. In particular,…