Machine learning algorithms for urban land use planning: A review

V Chaturvedi, WT de Vries - Urban Science, 2021 - mdpi.com
Urbanization is persistent globally and has increasingly significant spatial and
environmental consequences. It is especially challenging in developing countries due to the …

Mapping essential urban land use categories (EULUC) using geospatial big data: Progress, challenges, and opportunities

B Chen, B Xu, P Gong - Big Earth Data, 2021 - Taylor & Francis
Urban land use information that reflects socio-economic functions and human activities is
critically essential for urban planning, landscape design, environmental management …

Integrating aerial and street view images for urban land use classification

R Cao, J Zhu, W Tu, Q Li, J Cao, B Liu, Q Zhang, G Qiu - Remote Sensing, 2018 - mdpi.com
Urban land use is key to rational urban planning and management. Traditional land use
classification methods rely heavily on domain experts, which is both expensive and …

Integration of convolutional neural networks and object-based post-classification refinement for land use and land cover mapping with optical and SAR data

S Liu, Z Qi, X Li, AGO Yeh - Remote Sensing, 2019 - mdpi.com
Object-based image analysis (OBIA) has been widely used for land use and land cover
(LULC) mapping using optical and synthetic aperture radar (SAR) images because it can …

Google earth engine for informal settlement mapping: a random forest classification using spectral and textural information

D Matarira, O Mutanga, M Naidu - Remote Sensing, 2022 - mdpi.com
Accurate and reliable informal settlement maps are fundamental decision-making tools for
planning, and for expediting informed management of cities. However, extraction of spatial …

Model fusion for building type classification from aerial and street view images

EJ Hoffmann, Y Wang, M Werner, J Kang, XX Zhu - Remote Sensing, 2019 - mdpi.com
This article addresses the question of mapping building functions jointly using both aerial
and street view images via deep learning techniques. One of the central challenges here is …

Large-area, high spatial resolution land cover mapping using random forests, GEOBIA, and NAIP orthophotography: Findings and recommendations

AE Maxwell, MP Strager, TA Warner, CA Ramezan… - Remote Sensing, 2019 - mdpi.com
Despite the need for quality land cover information, large-area, high spatial resolution land
cover mapping has proven to be a difficult task for a variety of reasons including large data …

Large-area, 1964 land cover classifications of Corona spy satellite imagery for the Caucasus Mountains

A Rizayeva, MD Nita, VC Radeloff - Remote Sensing of Environment, 2023 - Elsevier
Historical land use strongly influences current landscapes and ecosystems making maps of
historical land cover an important reference point. However, the earliest satellite-based land …

Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China

Y Hu, Y Zhang - Scientific reports, 2020 - nature.com
Ecological land is a type of land that has considerable ecological value. Understanding the
evolution of urban ecological land in Zhuhai, China, holds great significance for revealing …

Simulating large-scale urban land-use patterns and dynamics using the U-Net deep learning architecture

J Wang, M Hadjikakou, RJ Hewitt, BA Bryan - Computers, Environment and …, 2022 - Elsevier
Accurate predictions of land-use change are important for supporting planning. Cellular
automata (CA) models are widely used to simulate real-world urban land-use change but …