Land-use land-cover classification by machine learning classifiers for satellite observations—A review

S Talukdar, P Singha, S Mahato, S Pal, YA Liou… - Remote sensing, 2020 - mdpi.com
Rapid and uncontrolled population growth along with economic and industrial development,
especially in developing countries during the late twentieth and early twenty-first centuries …

Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine

J Adrian, V Sagan, M Maimaitijiang - ISPRS Journal of Photogrammetry and …, 2021 - Elsevier
Accurate crop type mapping provides numerous benefits for a deeper understanding of food
systems and yield prediction. Ever-increasing big data, easy access to high-resolution …

A comparative assessment of machine-learning techniques for land use and land cover classification of the Brazilian tropical savanna using ALOS-2/PALSAR-2 …

FF Camargo, EE Sano, CM Almeida, JC Mura… - Remote Sensing, 2019 - mdpi.com
This study proposes a workflow for land use and land cover (LULC) classification of
Advanced Land Observing Satellite-2 (ALOS-2) Phased Array type L-band Synthetic …

Refugee camp monitoring and environmental change assessment of Kutupalong, Bangladesh, based on radar imagery of Sentinel-1 and ALOS-2

A Braun, F Fakhri, V Hochschild - Remote Sensing, 2019 - mdpi.com
Approximately one million refugees of the Rohingya minority population in Myanmar
crossed the border to Bangladesh on 25 August 2017, seeking shelter from systematic …

[HTML][HTML] Refugees, traditional energy consumption, environmental pollution, and deforestation: Fourier BARDL method

ME Bildirici, RA Castanho, G Couto, SY Genç - Energy strategy reviews, 2023 - Elsevier
After 2010, refugees through the World peaked at the highest level since WW II. Most of this
increment was realized between 2011 and 2015 years in the effect of the Syrian conflict and …

Multi-sensor mapping of honey bee habitats and fragmentation in agro-ecological landscapes in Eastern Kenya

P Ochungo, R Veldtman, EM Abdel-Rahman… - Geocarto …, 2021 - Taylor & Francis
Extensive land transformation leads to habitat loss, which directly affects and fragments
species habitats. Such land transformations can adversely affect fodder availability for bees …

Google Earth Engine for Advanced Land Cover Analysis from Landsat‐8 Data with Spectral and Topographic Insights

A Abdollahi, B Pradhan, A Alamri, CW Lee - Journal of Sensors, 2023 - Wiley Online Library
The primary goal of this research is to see how effective cloud‐based computing services
such as Google Earth Engine (GEE) platform are at classifying multitemporal satellite …

[HTML][HTML] Vegetation phenology patterns in semi-arid savannah woodlands of Gonarezhou National Park, Southeastern Zimbabwe

T Murwendo, A Murwira, M Masocha - International Journal of Geoheritage …, 2023 - Elsevier
Vegetation phenology (VP) patterns of semi-arid savannah woodlands ecosystems are
essential for sustainable management and conservation since they are indicators of the …

Radar satellite imagery for humanitarian response. Bridging the gap between technology and application

A Braun - 2019 - tobias-lib.ub.uni-tuebingen.de
This work deals with radar satellite imagery and its potential to assist of humanitarian
operations. As the number of displaced people annually increases, both hosting countries …

Analysis of rural areas of Ukraine on the basis of ESA WorldCover 2020.

O Skydan, P Pyvovar, P Topolnytskyi, T Prysiazhna - 2022 - cabidigitallibrary.org
At present, GIS technologies penetrate various spheres of socio-economic life of humankind.
In this paper, based on GIS technologies, the main classes of the land cover of Ukraine were …