Application of the Random Forest Classifier to Map Irrigated Areas Using Google Earth Engine
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Application of the Random Forest Classifier to Map Irrigated Areas Using Google Earth Engine
Authors
Keywords
-
Journal
Remote Sensing
Volume 13, Issue 5, Pages 876
Publisher
MDPI AG
Online
2021-02-26
DOI
10.3390/rs13050876
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Irrigation of World Agricultural Lands: Evolution through the Millennia
- (2020) Andreas N. Angelakιs et al. Water
- Determination of the Normalized Difference Vegetation Index (NDVI) with Top-of-Canopy (TOC) Reflectance from a KOMPSAT-3A Image Using Orfeo ToolBox (OTB) Extension
- (2020) Kiwon Lee et al. ISPRS International Journal of Geo-Information
- CHIRPS: Explaining random forest classification
- (2020) Julian Hatwell et al. ARTIFICIAL INTELLIGENCE REVIEW
- An integrative analytical model for the water-energy-food nexus: South Africa case study
- (2020) Luxon Nhamo et al. ENVIRONMENTAL SCIENCE & POLICY
- Prospects of Improving Agricultural and Water Productivity through Unmanned Aerial Vehicles
- (2020) Luxon Nhamo et al. Agriculture-Basel
- Nexus planning as a pathway towards sustainable environmental and human health post Covid-19
- (2020) Luxon Nhamo et al. ENVIRONMENTAL RESEARCH
- Does environmental data increase the accuracy of land use and land cover classification?
- (2020) Leiliane Bozzi Zeferino et al. International Journal of Applied Earth Observation and Geoinformation
- Climate Change Impacts on Water and Agriculture Sectors in Southern Africa: Threats and Opportunities for Sustainable Development
- (2020) Charles Nhemachena et al. Water
- Comparing different classification algorithms for monitoring mangrove cover changes in southern Iran
- (2019) Neda Bihamta Toosi et al. Global Ecology and Conservation
- Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data
- (2019) Abdulhakim Mohamed Abdi GIScience & Remote Sensing
- Recent advances and applications of machine learning in solid-state materials science
- (2019) Jonathan Schmidt et al. npj Computational Materials
- An assessment of groundwater use in irrigated agriculture using multi-spectral remote sensing
- (2019) Luxon Nhamo et al. PHYSICS AND CHEMISTRY OF THE EARTH
- Rainfall variability and its effects on growing period and grain yield for rainfed lowland rice under transplanting system in Northeast Thailand
- (2019) Sukanya Sujariya et al. PLANT PRODUCTION SCIENCE
- Climate response of rainfed versus irrigated farms: the bias of farm heterogeneity in irrigation
- (2018) Janka Vanschoenwinkel et al. CLIMATIC CHANGE
- Large-scale prerain vegetation green-up across Africa
- (2018) Tracy Adole et al. GLOBAL CHANGE BIOLOGY
- Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory
- (2018) Tedros Berhane et al. Remote Sensing
- Improving the Accuracy of Remotely Sensed Irrigated Areas Using Post-Classification Enhancement Through UAV Capability
- (2018) Luxon Nhamo et al. Remote Sensing
- The Water-Energy-Food Nexus: Climate Risks and Opportunities in Southern Africa
- (2018) Luxon Nhamo et al. Water
- Land-cover mapping using Random Forest classification and incorporating NDVI time-series and texture: a case study of central Shandong
- (2018) Yuhao Jin et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform
- (2018) Pardhasaradhi Teluguntla et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Challenges and opportunities for revitalising smallholder irrigation schemes in South Africa
- (2018) M Fanadzo et al. WATER SA
- Climate Change Adaptation through the Water-Energy-Food Nexus in Southern Africa
- (2018) Sylvester Mpandeli et al. International Journal of Environmental Research and Public Health
- Prospects for Improving Irrigated Agriculture in Southern Africa: Linking Water, Energy and Food
- (2018) Tafadzwanashe Mabhaudhi et al. Water
- Learning from the Ancient Maya: Exploring the Impact of Drought on Population Dynamics
- (2018) Linda Kuil et al. ECOLOGICAL ECONOMICS
- Google Earth Engine: Planetary-scale geospatial analysis for everyone
- (2017) Noel Gorelick et al. REMOTE SENSING OF ENVIRONMENT
- Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches
- (2017) Amit Kumar Basukala et al. European Journal of Remote Sensing
- Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine
- (2017) Jun Xiong et al. Remote Sensing
- Improving Water Sustainability and Food Security through Increased Crop Water Productivity in Malawi
- (2016) Luxon Nhamo et al. Water
- Feeding the world into the future – food and nutrition security: the role of food science and technology†
- (2016) Jenny (Jingxin) Tian et al. Frontiers in Life Science
- Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015
- (2016) Anukesh Krishnankutty Ambika et al. Scientific Data
- Water management: Current and future challenges and research directions
- (2015) William J. Cosgrove et al. WATER RESOURCES RESEARCH
- Water Scarcity and Future Challenges for Food Production
- (2015) Noemi Mancosu et al. Water
- Smallholder irrigation schemes in South Africa: A review of knowledge generated by the Water Research Commission
- (2011) W Van Averbeke et al. WATER SA
- MIRCA2000-Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling
- (2010) Felix T. Portmann et al. GLOBAL BIOGEOCHEMICAL CYCLES
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started