[HTML][HTML] Deep learning for urban land use category classification: A review and experimental assessment
Map** the distribution, pattern, and composition of urban land use categories plays a
valuable role in understanding urban environmental dynamics and facilitating sustainable …
valuable role in understanding urban environmental dynamics and facilitating sustainable …
[HTML][HTML] Cross-resolution national-scale land-cover map** based on noisy label learning: A case study of China
The spatial resolution of land cover map** has been increasing with the evolution of Earth
observation technology. However, the higher spatial resolution makes it more laborious to …
observation technology. However, the higher spatial resolution makes it more laborious to …
FROM-GLC Plus: Toward near real-time and multi-resolution land cover map**
Global land cover has undergone extensive and rapid changes as a result of human
activities and climate change. These changes have had a significant impact on biodiversity …
activities and climate change. These changes have had a significant impact on biodiversity …
A coarse-to-fine weakly supervised learning method for green plastic cover segmentation using high-resolution remote sensing images
Green plastic cover (GPC) is a kind of green plastic fine mesh primarily used for covering
construction sites and mitigating large amounts of dust during construction. Accurate GPC …
construction sites and mitigating large amounts of dust during construction. Accurate GPC …
A multi-scale weakly supervised learning method with adaptive online noise correction for high-resolution change detection of built-up areas
Accurate change detection of built-up areas (BAs) fosters a comprehensive understanding of
urban development. The post-classification comparison (PCC) is a widely-used change …
urban development. The post-classification comparison (PCC) is a widely-used change …
Large-scale land cover map** with fine-grained classes via class-aware semi-supervised semantic segmentation
Semi-supervised learning has attracted increasing attention in the large-scale land cover
map** task. However, existing methods overlook the potential to alleviate the class …
map** task. However, existing methods overlook the potential to alleviate the class …
Map** essential urban land use categories (EULUC) using geospatial big data: Progress, challenges, and opportunities
Urban land use information that reflects socio-economic functions and human activities is
critically essential for urban planning, landscape design, environmental management …
critically essential for urban planning, landscape design, environmental management …
Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels
Large-scale high-resolution (HR) land-cover map** is a vital task to survey the Earth's
surface and resolve many challenges facing humanity. However it is still a non-trivial task …
surface and resolve many challenges facing humanity. However it is still a non-trivial task …
Knowledge evolution learning: A cost-free weakly supervised semantic segmentation framework for high-resolution land cover classification
H Cui, G Zhang, Y Chen, X Li, S Hou, H Li, X Ma… - ISPRS Journal of …, 2024 - Elsevier
Despite the success of deep learning in land cover classification, high-resolution (HR) land
cover map** remains challenging due to the time-consuming and labor-intensive process …
cover map** remains challenging due to the time-consuming and labor-intensive process …
[HTML][HTML] Swcare: Switchable learning and connectivity-aware refinement method for multi-city and diverse-scenario road map** using remote sensing images
Accurate and efficient map** of road networks is crucial for evaluating urban
development, transportation accessibility, and environmental impact. However, existing road …
development, transportation accessibility, and environmental impact. However, existing road …