Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability...

Volledige beschrijving

Bibliografische gegevens
Hoofdauteurs:	Midekisa, A, Holl, F, Savory, D, Andrade-Pacheco, R, Gething, P, Bennett, A, Sturrock, H
Formaat:	Journal article
Taal:	English
Gepubliceerd in:	Public Library of Science 2017

Gelijkaardige items

Household electricity access in Africa (2000–2013): Closing information gaps with model-based geostatistics
door: Andrade-Pacheco, R, et al.
Gepubliceerd in: (2019)

Intercalibration and Gaussian process modeling of nighttime lights imagery for measuring urbanization trends in Africa 2000-2013
door: Savory, D, et al.
Gepubliceerd in: (2017)

Bridging the national data gap with Google earth engine and landsat imagery by developing annual land cover for Afghanistan
door: Kabir Uddin, et al.
Gepubliceerd in: (2024-06-01)

Harmonized Landsat and Sentinel-2 Data with Google Earth Engine
door: Elias Fernando Berra, et al.
Gepubliceerd in: (2024-07-01)

Characterization of Landsat-8 and Landsat-9 Reflectivity and NDVI Continuity Based on Google Earth Engine
door: Qing Zhang, et al.
Gepubliceerd in: (2025-01-01)

Synergizing google earth engine and earth observations for potential impact of land use/ land cover on air quality
door: Keval H. Jodhani, et al.
Gepubliceerd in: (2024-06-01)

Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenario forecasting
door: Cecilia Parracciani, et al.
Gepubliceerd in: (2024-12-01)

Integration of generative artificial intelligence and Google Earth Engine for mangrove land cover mapping
door: Jhonnerie Romie, et al.
Gepubliceerd in: (2024-01-01)

Seasonal Dynamics in Land Surface Temperature in Response to Land Use Land Cover Changes Using Google Earth Engine
door: Lei Feng, et al.
Gepubliceerd in: (2024-01-01)

MULTISOURCE AND MULTITEMPORAL LAND COVER MAPPING OF GREATER LUZON ISLAND USING GOOGLE EARTH ENGINE
door: C. G. Candido, et al.
Gepubliceerd in: (2024-04-01)

Continuous Time-Series Land Cover Maps for South Korea using Google Earth Engine
door: Chulhuyn Choi, et al.
Gepubliceerd in: (2023-12-01)

Mapping the Influence of Olympic Games’ Urban Planning on the Land Surface Temperatures: An Estimation Using Landsat Series and Google Earth Engine
door: Joan-Cristian Padró, et al.
Gepubliceerd in: (2024-09-01)

Land Cover Changes Based on Landsat Imagery Interpretation
door: Chairiyah Umi Rahayu, et al.
Gepubliceerd in: (2023-03-01)

Mapping malaria risk in low transmission settings: challenges and opportunities
door: Sturrock, H, et al.
Gepubliceerd in: (2016)

Performance of LANDSAT-5TM data in land-cover classification /
door: 375608 Mikihiro Ioka, et al.
Gepubliceerd in: (1986)

Modeling of land use and land cover changes using google earth engine and machine learning approach: implications for landscape management
door: Weynshet Tesfaye, et al.
Gepubliceerd in: (2024-08-01)

Land use and land cover change in East Java from 2015 to 2021: Use optical imagery and Google Earth engine
door: Mandala Marga, et al.
Gepubliceerd in: (2024-03-01)

Inner Niger Delta Inundation Extent (2010–2022) Based on Landsat Imagery and the Google Earth Engine
door: Benjamin Bonkoungou, et al.
Gepubliceerd in: (2024-05-01)

Spatiotemporal Mapping of Surface Water Using Landsat Images and Spectral Mixture Analysis on Google Earth Engine
door: Yaotong Cai, et al.
Gepubliceerd in: (2024-01-01)

Impact of land use/land cover changes on evapotranspiration and model accuracy using Google Earth engine and classification and regression tree modeling
door: Chaitanya B. Pande, et al.
Gepubliceerd in: (2024-12-01)

Impact of Land Use and Land Cover (LULC) Changes on Carbon Stocks and Economic Implications in Calabria Using Google Earth Engine (GEE)
door: Yasir Hassan Khachoo, et al.
Gepubliceerd in: (2024-09-01)

Exploring the Dynamics of Land Surface Temperature in Jordan’s Local Climate Zones: A Comprehensive Assessment through Landsat Entire Archive and Google Earth Engine
door: Khaled Hazaymeh, et al.
Gepubliceerd in: (2024-03-01)

Utilizing Landsat 8 OLI for land cover classification in plantations area
door: S N Anua, et al.
Gepubliceerd in: (2022)

Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation
door: Chaitanya Baliram Pande, et al.
Gepubliceerd in: (2024-04-01)

Marine and human habitat mapping for the Coral Triangle Initiative region of Sabah using Landsat and Google Earth imagery
door: Hossain, Mohammad Shawkat, et al.
Gepubliceerd in: (2016)

Calibration of volumetric soil moisture using Landsat-8 and Sentinel-2 satellite imagery by Google Earth Engine
door: José Rodolfo Quintana-Molina, et al.
Gepubliceerd in: (2023-07-01)

Surface water monitoring from 1984 to 2021 based on Landsat time-series images and Google Earth Engine
door: Bingxue Zhao, et al.
Gepubliceerd in: (2024-09-01)

Hacking Google Maps and Google Earth /
door: 326804 Brown, Martin C.
Gepubliceerd in: (2006)

Accuracy Assessment of Land Use Land Cover Classification Using Machine Learning Classifiers in Google Earth Engine; A Case Study of Jammu District
door: S. Khan, et al.
Gepubliceerd in: (2024-10-01)

Analyzing Land Use/Land Cover Changes Using Google Earth Engine and Random Forest Algorithm and Their Implications to the Management of Land Degradation in the Upper Tekeze Basin, Ethiopia
door: Alemu Eshetu Fentaw, et al.
Gepubliceerd in: (2024-01-01)

Impacts of Land Cover Changes on Land Surface Temperature using Landsat Imagery with the Supervised Classification Method
door: Astrid Damayanti, et al.
Gepubliceerd in: (2023-04-01)

Google earth for dummies /
door: Crowder, David A
Gepubliceerd in: (2007)

Continental-scale mapping of soil pH with SAR-optical fusion based on long-term earth observation data in google earth engine
door: Yajun Geng, et al.
Gepubliceerd in: (2024-08-01)

Spatiotemporal analysis of land cover change, projection, and fragmentation: an application of Google earth engine and machine learning approach on Baraitali forest, Bangladesh
door: Saddam Hossen, et al.
Gepubliceerd in: (2024-05-01)

Dynamic Geo-Visualization of Urban Land Subsidence and Land Cover Data Using PS-InSAR and Google Earth Engine (GEE) for Spatial Planning Assessment
door: Joko Widodo, et al.
Gepubliceerd in: (2024-12-01)

Spatiotemporal land use land cover (LULC) change analysis of urban narrow river using Google Earth Engine and Machine learning algorithms in Monterrey, Mexico
door: K. D. Rodríguez González, et al.
Gepubliceerd in: (2024-11-01)

Exploring Google Earth Engine, Machine Learning, and GIS for Land Use Land Cover Change Detection in the Federal Capital Territory, Abuja, between 2014 and 2023
door: Akus Okoduwa, et al.
Gepubliceerd in: (2024-06-01)

Mapping and Quantification of Land Area and Cover Types with Landsat in Carey Island, Selangor, Malaysia
door: Jusoff, Kamaruzaman, et al.
Gepubliceerd in: (2009)

Pendeteksian Kekeringan Lahan menggunakan Citra Landsat pada Platform Google Earth Engine untuk Keperluan Mitigasi Kebakaran Lahan
door: HARY NUGROHO, et al.
Gepubliceerd in: (2024-12-01)

Agroforestry mapping using multi temporal hybrid CNN+LSTM framework with landsat 8 satellite imagery and google earth engine
door: Jenila Vincent M, et al.
Gepubliceerd in: (2024-01-01)