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Using Machine Learning Algorithms to Predict Groundwater Levels in Indonesian Tropical Peatlands

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Peat–water interrelationships in a tropical peatland ecosystem in Southeast Asia
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inferredcites →https://doi.org/10.1016/j.geoderma.2019.04.001openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.scitotenv.2019.134199openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.scitotenv.2020.137988openalex-snapshot
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inferredcites →https://doi.org/10.1038/s41561-021-00785-2openalex-snapshot
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inferredcites →https://doi.org/10.1080/02626667.2018.1554940openalex-snapshot
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inferredcites →https://doi.org/10.1088/1748-9326/ac2011openalex-snapshot
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inferredcites →https://doi.org/10.1088/issn.1755-1315openalex-snapshot
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Variable carbon losses from recurrent fires in drained tropical peatlands
inferredcites →https://doi.org/10.1111/gwat.12464openalex-snapshot
Applied Groundwater Modeling—Simulation of Flow and Advective Transport
inferredcites →https://doi.org/10.1111/j.1365-2486.2010.02279.xopenalex-snapshot
Global and regional importance of the tropical peatland carbon pool
inferredcites →https://doi.org/10.1111/rec.13097openalex-snapshot
Defining ecological restoration of peatlands in Central Kalimantan, Indonesia
inferredcites →https://doi.org/10.1111/sjtg.12319openalex-snapshot
Beyond slash‐and‐burn: The roles of human activities, altered hydrology and fuels in peat fires in Central Kalimantan, Indonesia
inferredcites →https://doi.org/10.1177/1536867x20909688openalex-snapshot
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inferredcites →https://doi.org/10.15623/ijret.2015.0423022openalex-snapshot
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inferredcites →https://doi.org/10.3390/a13110300openalex-snapshot
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inferredcites →https://doi.org/10.3390/rs11141655openalex-snapshot
GNSS-R Soil Moisture Retrieval Based on a XGboost Machine Learning Aided Method: Performance and Validation
inferredcites →https://doi.org/10.3390/rs12010005openalex-snapshot
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inferredcites →https://doi.org/10.3390/rs13020196openalex-snapshot
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A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles
inferredcites →https://doi.org/10.3390/s21134408openalex-snapshot
Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments
inferredcites →https://doi.org/10.5194/acp-16-11711-2016openalex-snapshot
Field measurements of trace gases and aerosols emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Niño
inferredcites →https://doi.org/10.5194/acp-18-2585-2018openalex-snapshot
Chemical characterization of fine particulate matter emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Niño
inferredcites →https://doi.org/10.5194/acp-22-10173-2022openalex-snapshot
Tropical peat fire emissions: 2019 field measurements in Sumatra and Borneo and synthesis with previous studies
inferredcites →https://doi.org/10.5194/bg-12-6707-2015openalex-snapshot
Landscape-scale changes in forest canopy structure across a partially logged tropical peat swamp
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Subsidence and carbon loss in drained tropical peatlands
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Accelerating the XGBoost algorithm using GPU computing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Unravelling Climate Dynamics
inferred← citeshttps://doi.org/10.5194/bg-20-2099-2023openalex-snapshot
A process-based model for quantifying the effects of canal blocking on water table and CO 2 emissions in tropical peatlands
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