Results 31 to 40 of about 4,767,349 (290)
Remote Sensing, 2021 The Qilian Mountains (QLM) are an important ecological barrier in western China. High-precision land cover data products are the basic data for accurately detecting and evaluating the ecological service functions of the QLM.
Yanpeng Yang +4 more
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Deep Learning for Land Cover Classification Using Only a Few Bands
Remote Sensing, 2020 There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information and
Chiman Kwan +7 more
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Land use/land cover classification for Göktürk-2 satellite
2016 24th Signal Processing and Communication Application Conference (SIU), 2016 In this study, land-use/land-cover method for Gokturk-2 satellite was developed. Moreover, the developed method can be adapted to any satellite. The aim is to classify pixels in images captured by Gokturk-2 into four basic categories (soil, green areas, water bodies, and others), and to form a persistent mathematical model for this purpose.
Ilker Gurcan +2 more
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Spectral Characteristics of the Dynamic World Land Cover Classification
Remote Sensing, 2023 The Dynamic World product is a discrete land cover classification of Sentinel 2 reflectance imagery that is global in extent, retrospective to 2015, and updated continuously in near real time. The classifier is trained on a stratified random sample of 20,000 hand-labeled 5 × 5 km Sentinel 2 tiles spanning 14 biomes globally. Since the training data are
Christopher Small 0002, Daniel J. Sousa
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Land Cover Image Classification
CoRRLand Cover (LC) image classification has become increasingly significant in understanding environmental changes, urban planning, and disaster management. However, traditional LC methods are often labor-intensive and prone to human error. This paper explores state-of-the-art deep learning models for enhanced accuracy and efficiency in LC analysis.
Antonio Rangel +3 more
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Remote Sensing, 2016 Satellite based land cover classification for Africa’s semi-arid ecosystems is hampered commonly by heterogeneous landscapes with mixed vegetation and small scale land use.
Johannes Eberenz +5 more
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GeomaticsLand cover maps are frequently produced via the classification of satellite imagery. There is a need for a practicable and automated approach for the generalization of these land cover classification results into scalable, digital maps while minimizing ...
Geir-Harald Strand +4 more
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SENTINEL-1 IMAGE CLASSIFICATION FOR CITY EXTRACTION BASED ON THE SUPPORT VECTOR MACHINE AND RANDOM FOREST ALGORITHMS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Environmental change monitoring in earth sciences needs land use land cover change (LULCC) modeling to investigate the impact of climate change phenomena such as droughts and floods on earth surface land cover.
A. Jamali, A. Abdul Rahman
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ADVANCED CLASSIFICATION OF OPTICAL AND SAR IMAGES FOR URBAN LAND COVER MAPPING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 The aim of this research is to classify urban land cover types using an advanced classification method. As the input bands to the classification, the features derived from Landsat 8 and Sentinel 1A SAR data sets are used.
D. Amarsaikhan
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Land Cover Heterogeneity Effects on Sub-Pixel and Per-Pixel Classifications
ISPRS International Journal of Geo-Information, 2014 Per-pixel and sub-pixel are two common classification methods in land cover studies. The characteristics of a landscape, particularly the land cover itself, can affect the accuracies of both methods.
Trung V. Tran +2 more
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