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Hybrid Spectral Unmixing in Land-Cover Classification
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019Identifying land-cover and specifically the type of the material that constitutes building roofs in urban areas provides important reference information for later procedures including semantic labeling, bridge masking, and 3D reconstruction. In this paper, we present a hybrid unmixing-based classification framework that integrates both class-wise ...
Razieh Kaviani Baghbaderani +4 more
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Polarimetric signatures and classification of tropical land covers
2009 IEEE International Geoscience and Remote Sensing Symposium, 2009Polarimetric signatures for different tropical land covers were extracted from RADARSAT-2 data. Subsequently, the data were classified. The objective of this work was to assess the potential of RADARSAT-2 polarimetric C band data on land cover mapping. RADARSAT-2 data were acquired over Tapajos National Forest, a tropical forest reserve in Brazil, and ...
Tatiana Mora Kuplich +3 more
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Differences of image classification techniques for land use and land cover classification
2015 IEEE 11th International Colloquium on Signal Processing & Its Applications (CSPA), 2015Land use and land cover classification of remotely sensed data is an important research and commonly used in remote sensing application. In this study, the different types of classification techniques were used by using satellite image of some part of Selangor, Malaysia.
Nur Anis Mahmon +2 more
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2019
Land-cover classification is an important application area of satellite remote sensing. However, deriving thematic map from satellite imagery through classification approaches is not a straightforward task, especially from high-resolution satellite imagery.
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Land-cover classification is an important application area of satellite remote sensing. However, deriving thematic map from satellite imagery through classification approaches is not a straightforward task, especially from high-resolution satellite imagery.
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Land Cover Classification Using Ensemble Techniques
2019This paper aims at a Land cover classification of compact polarimetric RISAT-1 data using pixel-based and patch-based input to an ensemble model. In the pixel-based approach, Support Vector Machine (SVM), Multi-Layer Perceptron (MLP) and Random Forest (RF) are ensembled to shape a single voting classifier using the soft voting and majority voting ...
Hemani Parikh +2 more
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Planet-Scale Land Cover Classification with FPGAs
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018AI for Earth puts Microsoft's cloud and AI tools in the hands of those working to solve global environmental challenges. Land cover mapping is part of Microsoft's AI for Earth program, which was created in order to fundamentally change the way that society monitors, models, and ultimately manages Earth's natural resources.
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The development of Superspectral approaches for the improvement of land cover classification
IEEE Transactions on Geoscience and Remote Sensing, 2004This paper develops a critical review of the hyperspectral splitting of the solar reflected radiation acquired by hyperspectral imaging sensors. The bandwidth used in the range from 2.0-2.5 /spl mu/m by many hyperspectral sensors sometimes is too narrow for land cover classification. In fact, hyperspectral imagers often suffer from low signal-to-noise (
GIANINETTO, MARCO +1 more
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Land Use/Land Cover Classification Systems
2009The final objective of a geomatics process concerning Earth observation is the production of thematic maps. How to obtain thematic results is described in Chapter 8. With the use of informatics instruments, the possibilities to produce thematic maps are extensive. The problem is the quality and the assessment of the reliability of these maps. Few rules
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Land Cover and Land Use: Classification and Change Analysis
2004Despite its international designation as a hotspot of biodiversity and tropical deforestation (Achard et al. 1988), the micro-scale land-cover mapping of southern Yucatán peninsular region remains surprisingly incomplete, hindering various kinds of research, including that proposed in the SYPR project.
Rinku Roy Chowdhury, Laura C. Schneider
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Land Cover/Land Use Classification of Urban Areas
International Journal of Pattern Recognition and Artificial Intelligence, 1998This paper proposes a method for remote sensing based land cover/land use classification of urban areas. The method consists of the following four main stages: feature extraction, feature coding, feature selection and classification. In the feature extraction stage, statistical, textural and Gabor features are computed within local image windows of ...
Jukka Heikkonen, Aristide Varfis
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