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https://doi.org/10.5194/essd-2023-87
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_49openalex-snapshot
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-24574-4openalex-snapshot
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
inferredcites →https://doi.org/10.1007/s12524-011-0182-3openalex-snapshot
Exploring the Potential of Object Based Image Analysis for Mapping Urban Land Cover
inferredcites →https://doi.org/10.1016/j.cities.2022.103717openalex-snapshot
Urban growth rates, trajectories, and multi-dimensional disparities in China
inferredcites →https://doi.org/10.1016/j.ecosys.2005.07.002openalex-snapshot
The paradox of China's growing under-urbanization
inferredcites →https://doi.org/10.1016/j.gloplacha.2006.10.002openalex-snapshot
Scenarios of land cover in China
inferredcites →https://doi.org/10.1016/j.habitatint.2014.10.019openalex-snapshot
Construction land expansion and cultivated land protection in urbanizing China: Insights from national land surveys, 1996–2006
inferredcites →https://doi.org/10.1016/j.habitatint.2017.11.009openalex-snapshot
Assessment on the urbanization strategy in China: Achievements, challenges and reflections
inferredcites →https://doi.org/10.1016/j.isprsjprs.2007.07.002openalex-snapshot
Remote sensing research issues of the National Land Use Change Program of China
inferredcites →https://doi.org/10.1016/j.isprsjprs.2014.09.002openalex-snapshot
Global land cover mapping at 30 m resolution: A POK-based operational approach
inferredcites →https://doi.org/10.1016/j.isprsjprs.2016.03.008openalex-snapshot
Optical remotely sensed time series data for land cover classification: A review
inferredcites →https://doi.org/10.1016/j.isprsjprs.2020.03.012openalex-snapshot
Fractional evergreen forest cover mapping by MODIS time-series FEVC-CV methods at sub-pixel scales
inferredcites →https://doi.org/10.1016/j.isprsjprs.2020.06.003openalex-snapshot
A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images
inferredcites →https://doi.org/10.1016/j.isprsjprs.2021.08.024openalex-snapshot
National-scale greenhouse mapping for high spatial resolution remote sensing imagery using a dense object dual-task deep learning framework: A case study of China
inferredcites →https://doi.org/10.1016/j.isprsjprs.2022.04.012openalex-snapshot
A coarse-to-fine weakly supervised learning method for green plastic cover segmentation using high-resolution remote sensing images
inferredcites →https://doi.org/10.1016/j.isprsjprs.2022.07.011openalex-snapshot
Cross-spatiotemporal land-cover classification from VHR remote sensing images with deep learning based domain adaptation
inferredcites →https://doi.org/10.1016/j.protcy.2016.05.231openalex-snapshot
Use of High Resolution Google Earth Satellite Imagery in Landuse Map Preparation for Urban Related Applications
inferredcites →https://doi.org/10.1016/j.rse.2004.06.017openalex-snapshot
Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification
inferredcites →https://doi.org/10.1016/j.rse.2009.08.016openalex-snapshot
MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets
inferredcites →https://doi.org/10.1016/j.rse.2012.10.031openalex-snapshot
Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation
inferredcites →https://doi.org/10.1016/j.rse.2014.02.015openalex-snapshot
Good practices for estimating area and assessing accuracy of land change
inferredcites →https://doi.org/10.1016/j.rse.2015.01.018openalex-snapshot
A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data
inferredcites →https://doi.org/10.1016/j.rse.2018.06.034openalex-snapshot
An object-based convolutional neural network (OCNN) for urban land use classification
inferredcites →https://doi.org/10.1016/j.rse.2018.10.031openalex-snapshot
Intra-annual reflectance composites from Sentinel-2 and Landsat for national-scale crop and land cover mapping
inferredcites →https://doi.org/10.1016/j.rse.2019.04.014openalex-snapshot
Understanding urban landuse from the above and ground perspectives: A deep learning, multimodal solution
inferredcites →https://doi.org/10.1016/j.rse.2019.111563openalex-snapshot
Integrating Google Earth imagery with Landsat data to improve 30-m resolution land cover mapping
inferredcites →https://doi.org/10.1016/j.rse.2020.111838openalex-snapshot
Open-source data-driven urban land-use mapping integrating point-line-polygon semantic objects: A case study of Chinese cities
inferredcites →https://doi.org/10.1016/j.rse.2022.113058openalex-snapshot
Cross-sensor domain adaptation for high spatial resolution urban land-cover mapping: From airborne to spaceborne imagery
inferredcites →https://doi.org/10.1016/j.scib.2019.03.002openalex-snapshot
Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017
inferredcites →https://doi.org/10.1016/j.scib.2019.04.024openalex-snapshot
40-Year (1978–2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing
inferredcites →https://doi.org/10.1016/j.scib.2020.03.003openalex-snapshot
High-resolution urban land-cover mapping and landscape analysis of the 42 major cities in China using ZY-3 satellite images
inferredcites →https://doi.org/10.1016/j.scitotenv.2016.07.078openalex-snapshot
Land-use/land-cover change and ecosystem service provision in China
inferredcites →https://doi.org/10.1016/s0264-2751(02)00039-2openalex-snapshot
The growth and structural change of Chinese cities: a contextual and geographic analysis
inferredcites →https://doi.org/10.1016/s0264-8377(03)00007-3openalex-snapshot
China's land resources and land-use change: insights from the 1996 land survey
inferredcites →https://doi.org/10.1080/014311600210191openalex-snapshot
Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data
inferredcites →https://doi.org/10.1080/01431160412331291297openalex-snapshot
GLC2000: a new approach to global land cover mapping from Earth observation data
inferredcites →https://doi.org/10.1080/01431161.2012.748992openalex-snapshot
Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data
inferredcites →https://doi.org/10.1080/01431161.2014.930202openalex-snapshot
Towards a common validation sample set for global land-cover mapping
inferredcites →https://doi.org/10.1080/15481603.2020.1724707openalex-snapshot
Large-scale urban functional zone mapping by integrating remote sensing images and open social data
inferredcites →https://doi.org/10.1080/17538947.2015.1031716openalex-snapshot
Horizontal accuracy assessment of very high resolution Google Earth images in the city of Rome, Italy
inferredcites →https://doi.org/10.1109/cvprw.2017.199openalex-snapshot
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps
inferredcites →https://doi.org/10.1109/igarss46834.2022.9884345openalex-snapshot
Multi-Stage Pseudo-Label Iteration Framework for Semi-Supervised Land-Cover Mapping
inferredcites →https://doi.org/10.1109/igarss47720.2021.9553120openalex-snapshot
Change Cross-Detection Based on Label Improvements and Multi-Model Fusion for Multi-Temporal Remote Sensing Images
inferredcites →https://doi.org/10.1109/igarss47720.2021.9553499openalex-snapshot
Global land use / land cover with Sentinel 2 and deep learning
inferredcites →https://doi.org/10.1109/jstars.2010.2084072openalex-snapshot
Monitoring Urban Sprawl Using Remote Sensing and GIS Techniques of a Fast Growing Urban Centre, India
inferredcites →https://doi.org/10.1109/jstars.2013.2262767openalex-snapshot
Coffee Crop's Biomass and Carbon Stock Estimation With Usage of High Resolution Satellites Images
inferredcites →https://doi.org/10.1109/jstars.2022.3144318openalex-snapshot
The Outcome of the 2021 IEEE GRSS Data Fusion Contest—Track MSD: Multitemporal Semantic Change Detection
inferredcites →https://doi.org/10.1109/tsmc.1979.4310076openalex-snapshot
A Threshold Selection Method from Gray-Level Histograms
inferredcites →https://doi.org/10.1109/wacv56688.2023.00619openalex-snapshot
OpenEarthMap: A Benchmark Dataset for Global High-Resolution Land Cover Mapping
inferredcites →https://doi.org/10.3390/rs12121909openalex-snapshot
US EPA EnviroAtlas Meter-Scale Urban Land Cover (MULC): 1-m Pixel Land Cover Class Definitions and Guidance
inferredcites →https://doi.org/10.3390/rs8040271openalex-snapshot
Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods
inferredcites →https://doi.org/10.48550/arxiv.2110.08733openalex-snapshot
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
inferredcites →https://doi.org/10.5194/essd-14-1359-2022openalex-snapshot
High-resolution spatial-distribution maps of road transport exhaust emissions in Chile, 1990–2020
inferredcites →https://doi.org/10.5194/essd-15-113-2023openalex-snapshot
MDAS: a new multimodal benchmark dataset for remote sensing
inferredcites →https://doi.org/10.5281/zenodo.7707461openalex-snapshot
SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (Central of China)
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4660440openalex-extracted
Multifaceted Spectral Feature Interaction Effects Enhance Remote Sensing Inversion of Chlorophyll in Cadmium-Stressed Rice
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Cooking emissions dominated the high-resolution spatial variations of ultrafine particles (PM0.1) in a Chinese megacity
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Seasonal analysis of land surface temperature using local climate zones in peak forest basin topography: A case study of Guilin
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Seasonal variation in vegetation cooling effect and its driving factors in a subtropical megacity
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Prioritizing 30% community tree volume ratio: Effects of community, street, and park greenspace exposure metrics on predicting older adults’ mental health
inferred← citeshttps://doi.org/10.1016/j.ecolind.2023.111424openalex-snapshot
A systematic review of studies involving canopy layer urban heat island: Monitoring and associated factors
inferred← citeshttps://doi.org/10.1016/j.ecolind.2025.113722openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ecolind.2025.113901openalex-snapshot
Integrating ecosystem services: a new indicator for evaluating net carbon sink efficiency of urban green spaces and its influencing factors
inferred← citeshttps://doi.org/10.1016/j.ecolind.2025.114204openalex-snapshot
Distinct dominant factors of spatially heterogenous urban tree cooling identified in cities across China
inferred← citeshttps://doi.org/10.1016/j.enpol.2024.114368openalex-snapshot
Estimating electrical distribution network length and capital investment needs from real-world topologies and land cover data
inferred← citeshttps://doi.org/10.1016/j.envint.2024.109044openalex-snapshot
Interannual variability and spatial diversification of global urban tree cooling effects
inferred← citeshttps://doi.org/10.1016/j.envres.2023.117475openalex-snapshot
Urban green, blue spaces and their joint effect are associated with lower risk of emotional and behavior problem in children and adolescents, a large population-based study in Guangzhou, China
inferred← citeshttps://doi.org/10.1016/j.envres.2024.118520openalex-snapshot
The greener the living environment, the better the health? Examining the effects of multiple green exposure metrics on physical activity and health among young students
inferred← citeshttps://doi.org/10.1016/j.inffus.2024.102505openalex-snapshot
STFDiff: Remote sensing image spatiotemporal fusion with diffusion models
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2023.11.014openalex-snapshot
A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing
inferred← citeshttps://doi.org/10.1016/j.jum.2025.05.003openalex-snapshot
Identification and planning response to inefficient urban and rural construction land use under the concept of relative performance
inferred← citeshttps://doi.org/10.1016/j.landurbplan.2025.105373openalex-snapshot
Social and ecological factors on the perception of cultural ecosystem services and disservices: Insights from Shanghai, China
inferred← citeshttps://doi.org/10.1016/j.rse.2024.114190openalex-snapshot
Learning spectral-indices-fused deep models for time-series land use and land cover mapping in cloud-prone areas: The case of Pearl River Delta
inferred← citeshttps://doi.org/10.1016/j.rse.2024.114242openalex-snapshot
Building up a data engine for global urban mapping
inferred← citeshttps://doi.org/10.1016/j.scs.2024.105277openalex-snapshot
Prevalent underestimation of tree cooling efficiency attributed to urban intrinsic heterogeneity
inferred← citeshttps://doi.org/10.1016/j.scs.2025.106254openalex-snapshot
Unraveling the effects of extreme heat conditions on urban heat environment: Insights from local climate zones and integrated temperature data
inferred← citeshttps://doi.org/10.1016/j.scs.2025.106467openalex-snapshot
Urban park green spaces and their potential in regulating urban heat Island (UHI) effects in urban-rural gradient in Shanghai, China
inferred← citeshttps://doi.org/10.1016/j.tranpol.2025.03.022openalex-snapshot
Multifunctional development patterns and driving mechanisms of high-speed rail station areas in the Yangtze River Delta, China
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A detection of street trees and green space: Understanding contribution of urban trees to climate change mitigation
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Assessment of ecological and landscape services in urban green spaces in South China Karst
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Mapping Road Surface Type of Kenya Using OpenStreetMap and High-resolution Google Satellite Imagery
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Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets
inferred← citeshttps://doi.org/10.1038/s41597-024-03990-xopenalex-snapshot
A 30-m annual grassland dataset from 1991 to 2020 for Inner Mongolia, China
inferred← citeshttps://doi.org/10.1038/s41597-025-06373-yopenalex-snapshot
A 1.5 m resolution land cover map of Southern China created with Superpixel U-Net
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Enhancing daily streamflow simulation using the coupled SWAT-BiLSTM approach for climate change impact assessment in Hai-River Basin
inferred← citeshttps://doi.org/10.1038/s41598-023-44531-7openalex-snapshot
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Spatially-informed interpolation for reconstructing lake area time series using semantic neighborhood correlation
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Landslide susceptibility assessment in Tongguan District Anhui China using information value and certainty factor models
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Global inequities in population exposure to urban greenspaces increased amidst tree and nontree vegetation cover expansion
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A novel deep learning model for extracting arable land from high-resolution remote sensing images in hilly areas: a case study in the Sichuan Basin of Southwest China
inferred← citeshttps://doi.org/10.1080/17538947.2023.2301673openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/17538947.2024.2353110openalex-snapshot
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SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data
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