Convolutional neural networks for global human settlements map** from Sentinel-2 satellite imagery

C Corbane, V Syrris, F Sabo, P Politis… - Neural Computing and …, 2021 - Springer
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 …

[HTML][HTML] NDVI threshold-based urban green space map** from sentinel-2A at the local governmental area (LGA) level of Victoria, Australia

J Aryal, C Sitaula, S Aryal - Land, 2022 - mdpi.com
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 …

[HTML][HTML] An alternative approach for map** burn scars using Landsat imagery, Google Earth Engine, and Deep Learning in the Brazilian Savanna

VLS Arruda, VJ Piontekowski, A Alencar… - Remote Sensing …, 2021 - Elsevier
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 …

Dilated-ResUnet: A novel deep learning architecture for building extraction from medium resolution multi-spectral satellite imagery

M Dixit, K Chaurasia, VK Mishra - Expert Systems with Applications, 2021 - Elsevier
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 …

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 …

Weakly-supervised domain adaptation for built-up region segmentation in aerial and satellite imagery

J Iqbal, M Ali - ISPRS Journal of Photogrammetry and Remote …, 2020 - Elsevier
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 …

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

M Wahbi, I El Bakali, B Ez-zahouani, R Azmi… - Remote Sensing …, 2023 - Elsevier
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 …

F2BFE: development of feature-based building footprint extraction by remote sensing data and GEE

H Farhadi, H Ebadi, A Kiani - International Journal of Remote …, 2023 - Taylor & Francis
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 …

Extracting built-up areas from Sentinel-1 imagery using land-cover classification and texture analysis

IH Holobâcă, K Ivan, M Alexe - International Journal of Remote …, 2019 - Taylor & Francis
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 …

Hierarchical classification of Sentinel 2-a images for land use and land cover map** and its use for the CORINE system

DÇ Demirkan, A Koz… - Journal of applied remote …, 2020 - spiedigitallibrary.org
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 …