bingxin, ma shao, yang yang, hequn yiwen, lu gao, yanqing wang, xinyao xie, ying wang, xiaofeng
This study was designed to develop a 30 m resolution land cover dataset to improve the performance of regional weather forecasting models in East China. A 10-class land cover mapping scheme was established, reflecting East China’s diverse landscape characteristics and incorporating a new category for plastic greenhouses. Plastic greenhouses are key...
jingyu, li chen, yangbo gu, yu wang, meiying zhao, yanjun
Land use and cover change (LUCC) is directly linked to the sustainability of ecosystems and the long-term well-being of human society. The Helong Region in the Loess Plateau has become one of the areas most severely affected by soil and water erosion in China due to its unique geographical location and ecological environment. The long-term construc...
chavez, segundo g. veneros, jaris rojas-briceño, nilton b. oliva-cruz, manuel guadalupe, grobert a. garcía, ligia
Despite the importance of using digital technologies for resource management, Peru does not record current and estimated processed data on rural agriculture, hindering an effective management process combined with policy. This research analyzes the connotation of spatiotemporal level trends of eight different land cover types in nine rural district...
ajibola, segun cabral, pedro
Recent advancements in deep learning have spurred the development of numerous novel semantic segmentation models for land cover mapping, showcasing exceptional performance in delineating precise boundaries and producing highly accurate land cover maps. However, to date, no systematic literature review has comprehensively examined semantic segmentat...
cao, shuyi tang, yubin yan, enping jiang, jiawei dengkui, mo
High-resolution land cover mapping is crucial in various disciplines but is often hindered by the lack of accurately matched labels. Our study introduces an innovative deep learning methodology for effective land cover mapping, independent of matched labels. The approach comprises three main components: (1) An advanced fully convolutional neural ne...
Liu, Lanfa Tong, Zichen Cai, Zhanchuan Wu, Hao Zhang, Rongchun Le Bris, Arnaud Olteanu-Raimond, Ana-Maria
Land cover mapping is crucial for natural resource assessment, urban planning, and sustainable development. Land cover nomenclature often includes two or three hierarchical levels with tree-like hierarchical structures. This study aims to explore these hierarchical relationships and the potential of hierarchical semantic segmentation for land cover...
mallinis, giorgos verde, natalia siachalou, sofia latinopoulos, dionisis akratos, christos kagalou, ifigenia
The conservation and management of forest areas require knowledge about their extent and attributes on multiple scales. The combination of multiple classifiers has been proposed as an attractive classification approach for improved accuracy and robustness that can efficiently exploit the complementary nature of diverse remote sensing data and the m...
Chandrasekharan, Kiran M. Villholth, Karen G. Kashaigili, J. J. Gebregziabher, Gebrehaweria Mandela, P. J.
Over the past century, the world has experienced an unprecedented surge in population growth, accompanied by a significant increase in economic activity and fuelled by an intensive utilization of natural resources, including water. This phenomenon has brought about profound alterations in land cover and land use patterns across various regions. Kno...
Nguyen, Phuong Minh Luong, Phuong Thi Vantalon, Thibaud Reymondin, Louis Talsma, Tiffany Phan, Trong Van Nguyen Thi, Thuy Thu Bunn, Christian
In an ever-evolving landscape of regulations and commitments to net-zero emission commodity chains, Terra-i+ offers a satellite-based solution for agroforestry supply chain sustainability management. At its core, Terra-i+ functions as an integrated platform to access critical information about the sustainability status of coffee supply chains. With...
Akpoti, Komlavi Dembele, Moctar Forkuor, G. Obuobie, E. Mabhaudhi, Tafadzwanashe Cofie, Olufunke
Although Ghana is a leading global cocoa producer, its production and yield have experienced declines in recent years due to various factors, including long-term climate change such as increasing temperatures and changing rainfall patterns, as well as drought events. With the increasing exposure of cocoa-producing regions to extreme weather events,...
