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DETERMINATION OF LAND COVER/LAND USE USING SPOT 7 DATA WITH SUPERVISED CLASSIFICATION METHODS [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
Land use/ land cover (LULC) classification is a key research field in remote sensing. With recent developments of high-spatial-resolution sensors, Earth-observation technology offers a viable solution for land use/land cover identification and management
F. Bektas Balcik, A. Karakacan Kuzucu
doaj   +1 more source

Land cover classification using multi-temporal MERIS vegetation indices [PDF]

, 2007
The spectral, spatial, and temporal resolutions of Envisat's Medium Resolution Imaging Spectrometer (MERIS) data are attractive for regional- to global-scale land cover mapping.
A. Mathur, Baret F., Benedetti R., Clark R. N., Clevers J. G. P. W., G. M. Foody, Gaston G. G., Gobron N., Halldorsson G. H., J. Dash, J. W. Chipman, Lillesand T. M., Mather P. M., P. J. Curran, Peterson D. L., Richardson A. L., Smith G. M., Smith P. M., T. M. Lillesand, Wilkinson G. G.   +19 more
core   +1 more source

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, Bulent Ayhan, Bence Budavari, Yan Lu, Daniel Perez, Jiang Li, Sergio Bernabe, Antonio Plaza   +7 more
doaj   +1 more source

Large-scale Land Cover Classification in GaoFen-2 Satellite Imagery

, 2018
Many significant applications need land cover information of remote sensing images that are acquired from different areas and times, such as change detection and disaster monitoring.
Lu, Qikai, Tong, Xin-Yi, Xia, Gui-Song, Zhang, Liangpei   +3 more
core   +1 more source

Comparative analysis of support vector machine, maximum likelihood and neural network classification on multispectral remote sensing data [PDF]

, 2018
Land cover classification is an essential process in many remote sensing applications. Classification based on supervised methods have been preferred by many due to its practicality, accuracy and objectivity compared to unsupervised methods. Nevertheless,
Abdullah, Mohd Mawardy, Ahmad, Asmala, Mohd Hashim, Ummi Kalsom, Mohd, Othman, Rasib, Abd Wahid, Sakidin, Hamzah, Sufahani, Suliadi Firdaus   +6 more
core   +1 more source

Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes

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, Jan Verbesselt, Martin Herold, Nandin-Erdene Tsendbazar, Giovanni Sabatino, Giancarlo Rivolta   +5 more
doaj   +1 more source

Land Cover Change Image Analysis for Assateague Island National Seashore Following Hurricane Sandy [PDF]

, 2015
The assessment of storm damages is critically important if resource managers are to understand the impacts of weather pattern changes and sea level rise on their lands and develop management strategies to mitigate its effects. This study was performed to
Congalton, Russell G., Grybas, Heather
core   +2 more sources

Transformation of a Classified Image from Pixel Clutter to Land Cover Map Using Geometric Generalization and Thematic Self-Enrichment

Geomatics
Land 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, Eva Solbjørg Flo Heggem, Linda Aune-Lundberg, Agata Hościło, Adam Waśniewski   +4 more
doaj   +1 more source

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
doaj   +1 more source

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
doaj   +1 more source