Validation and refinement of cropland data layer using a spatial-temporal decision tree algorithm

L Lin, L Di, C Zhang, L Guo, Y Di, H Li, A Yang - Scientific Data, 2022 - nature.com
Abstract Space-based crop identification and acreage estimation have played a significant
role in agricultural studies in recent years, due to the development of Remote Sensing …

Multi-branch deep learning framework for land scene classification in satellite imagery

SD Khan, S Basalamah - Remote Sensing, 2023 - mdpi.com
Land scene classification in satellite imagery has a wide range of applications in remote
surveillance, environment monitoring, remote scene analysis, Earth observations and urban …

Measuring Urban Poverty Spatial by Remote Sensing and Social Sensing Data: A Fine-Scale Empirical Study from Zhengzhou

K Wang, L Zhang, M Cai, L Liu, H Wu, Z Peng - Remote Sensing, 2023 - mdpi.com
Urban poverty is a major obstacle to the healthy development of urbanization. Identifying
and mapping urban poverty is of great significance to sustainable urban development …

Grid-Scale Poverty Assessment by Integrating High-Resolution Nighttime Light and Spatial Big Data—A Case Study in the Pearl River Delta

M Li, J Lin, Z Ji, K Chen, J Liu - Remote Sensing, 2023 - mdpi.com
Poverty is a social issue of global concern. Although socioeconomic indicators can easily
reflect poverty status, the coarse statistical scales and poor timeliness have limited their …

[HTML][HTML] Modeling urban redevelopment: A novel approach using time-series remote sensing data and machine learning

L Lin, L Di, C Zhang, L Guo, H Zhao, D Islam… - Geography and …, 2024 - Elsevier
Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban
studies and decision-makers to foster sustainable urban development. Traditional mapping …

Mapping property redevelopment via GeoAI: Integrating computer vision and socioenvironmental patterns and processes

C Liu, W Song - Cities, 2024 - Elsevier
Abstract Domain knowledge of social and environmental sciences is generally derived from
less structured small data and/or small models. The integration of deep learning with …

Spatially granular poverty index (SGPI) for urban poverty mapping in Jakarta metropolitan area (JMA): a remote sensing satellite imageries and geospatial big data …

NA Utami, AW Wijayanto, S Pramana… - Earth Science Informatics, 2023 - Springer
Accurate and comprehensive urban poverty monitoring is undoubtedly essential to support
the urban poverty alleviation targets in many developing countries. The currently available …

Assessment of Urban Neighbourhoods' Vulnerability through an Integrated Vulnerability Index (IVI): Evidence from Barcelona, Spain

G Piasek, I Fernández Aragón, J Shershneva… - Social Sciences, 2022 - mdpi.com
Urban inequality, specifically in vulnerable areas, has been a study topic from the earliest
days of sociology to the present. This study's objective is to discuss the scope and limitation …

Group-Privacy Threats for Geodata in the Humanitarian Context

BK Masinde, CM Gevaert, MH Nagenborg… - … International Journal of …, 2023 - mdpi.com
The role of geodata technologies in humanitarian action is arguably indispensable in
determining when, where, and who needs aid before, during, and after a disaster. However …

Despite being distinguished as the 2020 European Green Capital, Lisbon has lost public green areas over the previous decade

JR de Almeida, GBM Alves, RO Nunes, T Dias - Sustainability, 2022 - mdpi.com
With the objective of assessing Lisbon's environmental improvement and sustainable
development, we measured the changes in Lisbon's vegetation cover over the 2010–2020 …