Cargando…

Mapping of Land Cover with Optical Images, Supervised Algorithms, and Google Earth Engine

Crops and ecosystems constantly change, and risks are derived from heavy rains, hurricanes, droughts, human activities, climate change, etc. This has caused additional damages with economic and social impacts. Natural phenomena have caused the loss of crop areas, which endangers food security, destr...

Descripción completa

Detalles Bibliográficos
Autores principales:	Pech-May, Fernando, Aquino-Santos, Raúl, Rios-Toledo, German, Posadas-Durán, Juan Pablo Francisco
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268769/ https://www.ncbi.nlm.nih.gov/pubmed/35808225 http://dx.doi.org/10.3390/s22134729

Ejemplares similares

Mapping and monitoring land use land cover dynamics employing Google Earth Engine and machine learning algorithms on Chattogram, Bangladesh
por: Biswas, Jayanta, et al.
Publicado: (2023)

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing
por: Midekisa, Alemayehu, et al.
Publicado: (2017)

Mapping, intensities and future prediction of land use/land cover dynamics using google earth engine and CA- artificial neural network model
por: Osman, Maysoon A. A., et al.
Publicado: (2023)

Mapping and spatiotemporal dynamics of land-use and land-cover change based on the Google Earth Engine cloud platform from Landsat imagery: A case study of Zhoushan Island, China
por: Chen, Chao, et al.
Publicado: (2023)

Using Google Maps and Google Earth
por: Miller, Michael
Publicado: (2011)

Mapping cover crop species in southeastern Michigan using Sentinel-2 satellite data and Google Earth Engine
por: Wang, Xuewei, et al.
Publicado: (2023)

Land Cover Change in the Central Region of the Lower Yangtze River Based on Landsat Imagery and the Google Earth Engine: A Case Study in Nanjing, China
por: Zhang, Dong-Dong, et al.
Publicado: (2020)

Detection of changes in literary writing style using N-grams as style markers and supervised machine learning
por: Ríos-Toledo, Germán, et al.
Publicado: (2022)

Time-series analyses of land surface temperature changes with Google Earth Engine in a mountainous region
por: Rodrigues de Almeida, Cátia, et al.
Publicado: (2023)

Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine
por: Roy, Bishal, et al.
Publicado: (2022)

Google Earth Forensics
por: Harrington, Michael
Publicado: (2014)

Land Use Change and Climate Variation in the Three Gorges Reservoir Catchment from 2000 to 2015 Based on the Google Earth Engine
por: Hao, Binfei, et al.
Publicado: (2019)

Identifying driving factors of urban land expansion using Google Earth Engine and machine-learning approaches in Mentougou District, China
por: Cheng, Lin-Lin, et al.
Publicado: (2022)

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine
por: Goyal, Manish Kumar, et al.
Publicado: (2023)

Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform
por: Aghababaei, Masoumeh, et al.
Publicado: (2021)

A supervised land cover classification of a western Kenya lowland endemic for human malaria: associations of land cover with larval Anopheles habitats
por: Mutuku, FM, et al.
Publicado: (2009)

Effect of Seasonal Land Surface Temperature Variation on COVID-19 Infection Rate: A Google Earth Engine-Based Remote Sensing Approach
por: Nafiz Rahaman, Sk., et al.
Publicado: (2022)

Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression
por: Salinero-Delgado, Matías, et al.
Publicado: (2021)

Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine
por: Pericak, Andrew A., et al.
Publicado: (2018)

Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine
por: Pipia, Luca, et al.
Publicado: (2021)

Leveraging big data for public health: Mapping malaria vector suitability in Malawi with Google Earth Engine
por: Frake, April N., et al.
Publicado: (2020)

Neuen Teilchenbeschleuniger in Google Earth betrachten
Publicado: (2008)

Fish Farms at Sea: The Ground Truth from Google Earth
por: Trujillo, Pablo, et al.
Publicado: (2012)

Virtual microscopy with Google-Earth: a step in the way for compatibility
por: Alfaro, Luis, et al.
Publicado: (2013)

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine
por: Reyes-Muñoz, Pablo, et al.
Publicado: (2022)

Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data
por: Estévez, José, et al.
Publicado: (2022)

Leveraging Google Earth Engine for Drought Assessment using Global Soil Moisture Data
por: Sazib, Nazmus, et al.
Publicado: (2018)

Measuring sidewalk distances using Google Earth
por: Janssen, Ian, et al.
Publicado: (2012)

Flood inundation mapping- Kerala 2018; Harnessing the power of SAR, automatic threshold detection method and Google Earth Engine
por: Tiwari, Varun, et al.
Publicado: (2020)

Google Earth Engine for concurrent flood monitoring in the lower basin of Indo-Gangetic-Brahmaputra plains
por: Lal, Preet, et al.
Publicado: (2020)

Accurate extraction of surface water in complex environment based on Google Earth Engine and Sentinel-2
por: Li, Jianfeng, et al.
Publicado: (2021)

A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features
por: Brandolini, Filippo, et al.
Publicado: (2021)

A national-scale assessment of land use change in peatlands between 1989 and 2020 using Landsat data and Google Earth Engine—a case study of Ireland
por: Habib, Wahaj, et al.
Publicado: (2023)

Was There Land on the Early Earth?
por: Korenaga, Jun
Publicado: (2021)

Malaria Exposure in Ann Township, Myanmar, as a Function of Land Cover and Land Use: Combining Satellite Earth Observations and Field Surveys
por: Hoffman‐Hall, Amanda, et al.
Publicado: (2020)

Web GIS in practice III: creating a simple interactive map of England's Strategic Health Authorities using Google Maps API, Google Earth KML, and MSN Virtual Earth Map Control
por: Boulos, Maged N Kamel
Publicado: (2005)

Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use classification
por: Hong, Danfeng, et al.
Publicado: (2019)

Screen shot of Google earth focused on CERN Map of the Meyrin diversion works
Publicado: (2007)

Novel Google Maps and Google Earth application for chemical industry disaster risk assessment during complex emergencies in Eastern Ukraine
por: Gan, Rick Kye, et al.
Publicado: (2023)

Salt marsh monitoring along the mid-Atlantic coast by Google Earth Engine enabled time series
por: Campbell, Anthony Daniel, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_6haikj86og0khcbugr4pog76p8