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Next-Generation Conservation Monitoring: Leveraging Cloud Computing and Machine Learning for Early Warning Systems in Meteoritic Lake Ecosystems
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Atmospheric, radiative, and hydrologic effects of future land use and land cover changes: A global and multimodel climate picture
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Al-Based Remoted Sensing Model for Sustainable Landcover Mapping and Monitoring in Smart City Context
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A Novel Agricultural Remote Sensing Drought Index (ARSDI) for high-resolution drought assessment in Africa using Sentinel and Landsat data
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Land use and land cover changes in Morocco: trends, research gaps, and perspectives
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Remote sensing inversion and prediction of land use land cover in the middle reaches of the Yangtze River basin, China
inferredcites →https://doi.org/10.1007/s11356-023-25875-zopenalex-snapshot
Assessing the link between land use/land cover changes and land surface temperature in Himalayan urban center, Srinagar
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Satellite Remote Sensing: Sensors, Applications and Techniques
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Evaluation of hydrological impacts of land use/land cover changes of Holota Watershed, Upper Awash Sub-basin, Ethiopia
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Land-cover and land-use change in a Mediterranean landscape: A spatial analysis of driving forces integrating biophysical and human factors
inferredcites →https://doi.org/10.1016/j.gltp.2021.01.002openalex-snapshot
Development of classification system for LULC using remote sensing and GIS
inferredcites →https://doi.org/10.1016/j.gsf.2015.07.003openalex-snapshot
Machine learning in geosciences and remote sensing
inferredcites →https://doi.org/10.1016/j.isprsjprs.2012.04.001openalex-snapshot
Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points
inferredcites →https://doi.org/10.1016/j.isprsjprs.2016.01.011openalex-snapshot
Random forest in remote sensing: A review of applications and future directions
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Land use transitions: Socio-ecological feedback versus socio-economic change
inferredcites →https://doi.org/10.1016/j.landusepol.2013.03.013openalex-snapshot
Key issues of land use in China and implications for policy making
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Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring
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Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects
inferredcites →https://doi.org/10.1063/5.0117111openalex-snapshot
Using Landsat to track land use and land cover (LULC) change from 1970 to 2020 in Mayang watershed, East Jawa
inferredcites →https://doi.org/10.1080/01431160903131000openalex-snapshot
Sampling designs for accuracy assessment of land cover
inferredcites →https://doi.org/10.1080/01431161.2018.1433343openalex-snapshot
Implementation of machine-learning classification in remote sensing: an applied review
inferredcites →https://doi.org/10.1080/09640568.2021.2001317openalex-snapshot
Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine
inferredcites →https://doi.org/10.1080/09669580903298531openalex-snapshot
Residents' perceptions of the environmental impacts of tourism in the Lake Bosomtwe Basin, Ghana
inferredcites →https://doi.org/10.1080/10106049.2019.1629647openalex-snapshot
Land use/land cover in view of earth observation: data sources, input dimensions, and classifiers—a review of the state of the art
inferredcites →https://doi.org/10.1109/igarss.2016.7730346openalex-snapshot
Comparing supervised algorithms in Land Use and Land Cover classification of a Landsat time-series
inferredcites →https://doi.org/10.1109/jstars.2020.3021052openalex-snapshot
Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review
inferredcites →https://doi.org/10.1126/science.1244693openalex-snapshot
High-Resolution Global Maps of 21st-Century Forest Cover Change
inferredcites →https://doi.org/10.1201/9781315139470openalex-snapshot
Classification And Regression Trees
inferredcites →https://doi.org/10.1201/9781420090741openalex-snapshot
Classification Methods for Remotely Sensed Data
inferredcites →https://doi.org/10.13031/aim.202401426openalex-snapshot
Drone Remote Sensing and Evapotranspiration Modeling for Intercropping and Irrigation strategies Study
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Hessian Fly Infestation Assessment with Stress Indicator based on Multispectral Imaging and Machine Learning Techniques
inferredcites →https://doi.org/10.1371/journal.pone.0184926openalex-snapshot
Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing
inferredcites →https://doi.org/10.14358/pers.69.3.289openalex-snapshot
Sampling Method and Sample Placement
inferredcites →https://doi.org/10.21105/joss.02305openalex-snapshot
geemap: A Python package for interactive mapping with Google Earth Engine
inferredcites →https://doi.org/10.3390/rs15010106openalex-snapshot
Mapping and Predicting Land Cover Changes of Small and Medium Size Cities in Alabama Using Machine Learning Techniques
inferredcites →https://doi.org/10.3390/rs17020200openalex-snapshot
Review on the Application of Remote Sensing Data and Machine Learning to the Estimation of Anthropogenic Heat Emissions
inferredcites →https://doi.org/10.3390/su13073590openalex-snapshot
Use of GIS and Remote Sensing Data to Understand the Impacts of Land Use/Land Cover Changes (LULCC) on Snow Leopard (Panthera uncia) Habitat in Pakistan
inferredcites →https://doi.org/10.3390/su15031858openalex-snapshot
Mapping LULC Dynamics and Its Potential Implication on Forest Cover in Malam Jabba Region with Landsat Time Series Imagery and Random Forest Classification
inferredcites →https://doi.org/10.46488/nept.2023.v22i01.019openalex-snapshot
Evapotranspiration Over the Indian Region: Implications of Climate Change and Land Use/Land Cover Change
inferredcites →https://doi.org/10.58496/bjiot/2025/001openalex-snapshot
Leveraging the Internet of Things, Remote Sensing, and Artificial Intelligence for Sustainable Forest Management
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