This paper addresses the land cover classification task for remote sensing images by deep self-taught learning. Our selftaught learning approach learns suitable feature representations of the input data using sparse representation and undercomplete dictionary learning. We propose a deep learning framework which extracts representations in multiple layers and use the output of the deepest layer ...

North Hebei province lies in the ecotone from agriculture to animal husbandry and forest and is eco-fragile transitional region. Serous land degradation, especially grassland degradation occurs in this area, because of overgrazing and over-reclamation. There are also many disasters, such as drought, dust storm, forest fire, and so on. This area has characteristics of ecological degradation and ...

Indicators based on territorial information, both spatial and temporal are widely used in many areas to promote and monitor sustainable development. Different databases can be used as well as different approaches to interpret these databases into a range of indicators. In this paper we present a series of theoretical landscape indices based on multispectral data from satellite Landsat 7 TM of A...

Forty-year calibrated record of earth-reflected radiance from Landsat: A review" (2012). a b s t r a c t a r t i c l e i n f o Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily pictur...

Recently, in classification of multispectral remote resensing image by using back-propagation neural network (BPNN), all bands of image must be used for training and classing. Disadvantage of the mentioned method not only requires more time for training and classing but also more complexity. In this paper, to decrease the mentioned disadvantage, principal component analysis (PCA) is applied to ...

Merging of different data sets is often used in digital image processing to improve the visual and analytical quality of the data. The analyst may need to merge different types of data. In this process, different data such as satellite imagery from the same sensor but with different resolution, satellite imagery from different sensors with varying resolution, digitized aerial photography and sa...