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Convolutional neural networks for global human settlements map** from Sentinel-2 satellite imagery
Spatially consistent and up-to-date maps of human settlements are crucial for addressing
policies related to urbanization and sustainability, especially in the era of an increasingly …
policies related to urbanization and sustainability, especially in the era of an increasingly …
[HTML][HTML] NDVI threshold-based urban green space map** from sentinel-2A at the local governmental area (LGA) level of Victoria, Australia
Obtaining accurate, precise and timely spatial information on the distribution and dynamics
of urban green space is crucial in understanding livability of the cities and urban dwellers …
of urban green space is crucial in understanding livability of the cities and urban dwellers …
[HTML][HTML] An alternative approach for map** burn scars using Landsat imagery, Google Earth Engine, and Deep Learning in the Brazilian Savanna
Abstract The Cerrado biome in Brazil is characterized by a mosaic of vegetation types
similar to African savanna and has one of the highest levels of biodiversity in the world …
similar to African savanna and has one of the highest levels of biodiversity in the world …
Dilated-ResUnet: A novel deep learning architecture for building extraction from medium resolution multi-spectral satellite imagery
In today's world, satellite images are being utilized for the identification of built-up area,
urban planning, disaster management, insurance & tax assessment in an area, and many …
urban planning, disaster management, insurance & tax assessment in an area, and many …
Detecting and assessing the spatio-temporal land use land cover changes of Bahrain Island during 1986–2020 using remote sensing and GIS
SS Aljenaid, GR Kadhem, MF AlKhuzaei… - Earth Systems and …, 2022 - Springer
Abstract The Kingdom of Bahrain has experienced accelerated development growth since
the 1980s. These rapid land demands increased the pressure on the country area to rebuild …
the 1980s. These rapid land demands increased the pressure on the country area to rebuild …
Weakly-supervised domain adaptation for built-up region segmentation in aerial and satellite imagery
This paper proposes a novel domain adaptation algorithm to handle the challenges posed
by the satellite and aerial imagery, and demonstrates its effectiveness on the built-up region …
by the satellite and aerial imagery, and demonstrates its effectiveness on the built-up region …
A deep learning classification approach using high spatial satellite images for detection of built-up areas in rural zones: Case study of Souss-Massa region-Morocco
The buildings in the rural areas of Morocco exist in various shapes and sizes. They are
randomly distributed and are generally constructed of primary materials such as clay, wood …
randomly distributed and are generally constructed of primary materials such as clay, wood …
F2BFE: development of feature-based building footprint extraction by remote sensing data and GEE
Monitoring the spatiotemporal dynamics of building footprints (BF) is necessary for
understanding urbanization growth. It is a difficult task to extract residential sites, mainly BF …
understanding urbanization growth. It is a difficult task to extract residential sites, mainly BF …
Extracting built-up areas from Sentinel-1 imagery using land-cover classification and texture analysis
Urban areas are continuously expanding, against the background of accelerating
urbanization, while their correct detection might be useful in a wide range of applications in …
urbanization, while their correct detection might be useful in a wide range of applications in …
Hierarchical classification of Sentinel 2-a images for land use and land cover map** and its use for the CORINE system
The aim of this study is to investigate the potential of the Sentinel-2 satellite for land use and
land cover (LULC) map**. The commonly known supervised classification algorithms …
land cover (LULC) map**. The commonly known supervised classification algorithms …