Results 11 to 20 of about 686,669 (305)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 In this study, the effectiveness of several convolutional neural network architectures (AlbuNet-34/FCN/DeepLabV3+/U-Net/U-Net++) for water and flood mapping using Sentinel-1 amplitude data is compared to ...
Max Bereczky +4 more
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Quantifying Slumness with Remote Sensing Data [PDF]
SSRN Electronic Journal, 2013 The presence of slums in a city is an indicator of poverty and its proper delimitation is a matter of interest for researchers and policy makers. Socio-economic data from surveys and censuses are the primary source of information to identify and quantify slumness within a city or a town. One problem of using survey data for quantifying slumness is that
Duque, Juan C. +3 more
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HYPERSPECTRAL DATA CLASSIFICATION USING FACTOR GRAPHS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use.
A. Makarau +3 more
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Remote Sensing, 2022 Nationwide and consistent information on agricultural land use forms an important basis for sustainable land management maintaining food security, (agro)biodiversity, and soil fertility, especially as German agriculture has shown high vulnerability to ...
Sarah Asam +5 more
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Earth Observation Based Monitoring of Forests in Germany: A Review
Remote Sensing, 2020 Forests in Germany cover around 11.4 million hectares and, thus, a share of 32% of Germany’s surface area. Therefore, forests shape the character of the country’s cultural landscape. Germany’s forests fulfil a variety of functions for nature and society,
Stefanie Holzwarth +9 more
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Remote Sensing, 2023 Remote sensing image composites are crucial for a wide range of remote sensing applications, such as multi-decadal time series analysis. The Advanced Very High Resolution Radiometer (AVHRR) instrument has provided daily data since the early 1980s at a ...
Sarah Asam +5 more
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Deep learning in remote sensing: a review [PDF]
, 2017 Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
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Remote Sensing, 2022 The Paraguayan Chaco is one of the most rapidly deforested areas in Latin America, mainly due to cattle ranching. Continuously forested windbreaks between agricultural areas and forest patches within these areas are mandatory to minimise the impact that ...
Jennifer Kriese +5 more
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Optimal transport for data fusion in remote sensing [PDF]
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016 One of the main objective of data fusion is the integration of several acquisition of the same physical object, in order to build a new consistent representation that embeds all the information from the different modalities. In this paper, we propose the use of optimal transport theory as a powerful mean of establishing correspondences between the ...
Courty, Nicolas +3 more
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CLASSIFICATION ACCURACY INCREASE USING MULTISENSOR DATA FUSION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging.
A. Makarau, G. Palubinskas, P. Reinartz
doaj +1 more source