Using Boosted Regression Trees and Remotely Sensed Data to Drive Decision-Making

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Open Journal of Statistics

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"Using Boosted Regression Trees and Remotely Sensed Data to Drive Decision-Making"
written by Brigitte Colin, Samuel Clifford, Paul Wu, Samuel Rathmanner, Kerrie Mengersen,
published by Open Journal of Statistics, Vol.7 No.5, 2017

has been cited by the following article(s):

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[15]	Using Machine Learning to Predict the Risk of Human-Elephant Conflict in the Nepal-India Transboundary Region
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[16]	Smart Environment Monitoring Models Using Cloud‐Based Data Analytics: A Comprehensive Study
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[17]	Patterns and drivers of rodent abundance across a South African multi-use landscape
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[18]	Environmental drivers of reef manta ray (Mobula alfredi) visitation patterns to key aggregation habitats in the Maldives
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[19]	Identifying predictors of international fisheries conflict
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[20]	Fine‐scale oceanographic drivers of reef manta ray (Mobula alfredi) visitation patterns at a feeding aggregation site
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[21]	Large-scale High-resolution Coastal Mangrove Forests Mapping across West Africa with Machine Learning Ensemble and Satellite Big Data
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[22]	Application of machine learning algorithms and their ensemble for landslide susceptibility mapping
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[23]	ABİDE 2016 fen başarısının yordanmasında MARS ve BRT veri madenciliği yöntemlerinin karşılaştırılması
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[24]	Remote islands are vulnerable to non-indigenous species: Utilization of data analytics to investigate potential modes of introduction and pest interceptions
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[25]	Reef manta rays, Mobula afredi, of the Chagos Archipelago: Habitat use and the effectiveness of the region's marine protected area
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[26]	Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach
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[27]	Serum proteomic analysis of melanoma patients with immunohistochemical profiling of primary melanomas and cultured cells: Pilot study
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[28]	Data-Driven Decision Making in Precision Agriculture: The Rise of Big Data in Agricultural Systems
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[29]	Performance indicators in football: The im-portance of actual performance for the market value of football players
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[30]	portance of actual performance for the market value of football players
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[33]	Influence of Spatial Aggregation on Prediction Accuracy of Green Vegetation Using Boosted Regression Trees
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[34]	Eğitim ve Bilim

[1]	Remote Sensing of Soils 2024 DOI:10.1016/B978-0-443-18773-5.00011-9

[2]	Unveiling spatial variations of high forest live biomass carbon stocks of Gabon using advanced remote sensing techniques Environmental Research Letters, 2024 DOI:10.1088/1748-9326/ad5572

[3]	Heat stress resilience assessment of urban form from physical space dimension: A case study of Guangdong-Hong Kong-Macao Greater Bay Area Urban Climate, 2024 DOI:10.1016/j.uclim.2024.101905

[4]	Integrating indicator-based and event-based surveillance data for risk mapping of West Nile virus, Europe, 2006 to 2021 Eurosurveillance, 2024 DOI:10.2807/1560-7917.ES.2024.29.44.2400084

[5]	Heat stress resilience assessment of urban form from physical space dimension: A case study of Guangdong-Hong Kong-Macao Greater Bay Area Urban Climate, 2024 DOI:10.1016/j.uclim.2024.101905

[6]	A flexible data‐driven approach to co‐producing drought vulnerability assessments Ecosphere, 2024 DOI:10.1002/ecs2.70040

[7]	Modeling climate‐driven range shifts in populations of two bird species limited by habitat independent of climate Ecosphere, 2023 DOI:10.1002/ecs2.4408

[8]	Contrasting determinants of land surface temperature in three megacities: Implications to cool tropical metropolitan regions Sustainable Cities and Society, 2023 DOI:10.1016/j.scs.2023.104505

[9]	Diversity of global fisheries governance: Types and contexts Fish and Fisheries, 2023 DOI:10.1111/faf.12713

[10]	Modeling climate‐driven range shifts in populations of two bird species limited by habitat independent of climate Ecosphere, 2023 DOI:10.1002/ecs2.4408

[11]	Comparison of Machine Learning Algorithms for Prediction of Total Assets 2023 International Conference On Cyber Management And Engineering (CyMaEn), 2023 DOI:10.1109/CyMaEn57228.2023.10051085

[12]	Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China Forest Ecosystems, 2023 DOI:10.1016/j.fecs.2023.100101

[13]	Contrasting determinants of land surface temperature in three megacities: Implications to cool tropical metropolitan regions Sustainable Cities and Society, 2023 DOI:10.1016/j.scs.2023.104505

[14]	Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China Forest Ecosystems, 2023 DOI:10.1016/j.fecs.2023.100101

[15]	Iron-rich Metal-poor Stars and the Astrophysics of Thermonuclear Events Observationally Classified as Type Ia Supernovae. I. Establishing the Connection The Astronomical Journal, 2023 DOI:10.3847/1538-3881/ace68c

[16]	The importance of expert selection when identifying threatened ecosystems Conservation Biology, 2023 DOI:10.1111/cobi.14151

[17]	Density, Kinematic Viscosity and Cetane Number Prediction of Biofuel Feedstocks from Fatty Acid Compositions 2022 International Conference on Futuristic Technologies (INCOFT), 2022 DOI:10.1109/INCOFT55651.2022.10094421

[18]	Spatial-Temporal Variations and Driving Factors of Soil Organic Carbon Stocks in Topsoils of Forest Ecosystems of Northeast China SSRN Electronic Journal , 2022 DOI:10.2139/ssrn.4129089

[19]	Driving Forces of Forest Expansion Dynamics across the Iberian Peninsula (1987–2017): A Spatio-Temporal Transect Forests, 2022 DOI:10.3390/f13030475

[20]	Evaluation of the metabolomic profile through 1H-NMR spectroscopy in ewes affected by postpartum hyperketonemia Scientific Reports, 2022 DOI:10.1038/s41598-022-20371-9

[21]	Diversity of global fisheries governance: Types and contexts Fish and Fisheries, 2022 DOI:10.1111/faf.12713

[22]	Density, Kinematic Viscosity and Cetane Number Prediction of Biofuel Feedstocks from Fatty Acid Compositions 2022 International Conference on Futuristic Technologies (INCOFT), 2022 DOI:10.1109/INCOFT55651.2022.10094421

[23]	Driving Forces of Forest Expansion Dynamics across the Iberian Peninsula (1987–2017): A Spatio-Temporal Transect Forests, 2022 DOI:10.3390/f13030475

[24]	Fine‐scale oceanographic drivers of reef manta ray (Mobula alfredi) visitation patterns at a feeding aggregation site Ecology and Evolution, 2021 DOI:10.1002/ece3.7357

[25]	Patterns and Drivers of Rodent Abundance across a South African Multi-Use Landscape Animals, 2021 DOI:10.3390/ani11092618

[26]	Understanding and Reducing Landslide Disaster Risk ICL Contribution to Landslide Disaster Risk Reduction, 2021 DOI:10.1007/978-3-030-60227-7_25

[27]	Large-Scale High-Resolution Coastal Mangrove Forests Mapping Across West Africa With Machine Learning Ensemble and Satellite Big Data Frontiers in Earth Science, 2021 DOI:10.3389/feart.2020.560933

[28]	Fine‐scale oceanographic drivers of reef manta ray ( Mobula alfredi ) visitation patterns at a feeding aggregation site Ecology and Evolution, 2021 DOI:10.1002/ece3.7357

[29]	Identifying predictors of international fisheries conflict Fish and Fisheries, 2021 DOI:10.1111/faf.12554

[30]	Environmental drivers of reef manta ray (Mobula alfredi) visitation patterns to key aggregation habitats in the Maldives PLOS ONE, 2021 DOI:10.1371/journal.pone.0252470

[31]	Machine Learning Approach for Cloud Data Analytics in IoT 2021 DOI:10.1002/9781119785873.ch10

[32]	Patterns and Drivers of Rodent Abundance across a South African Multi-Use Landscape Animals, 2021 DOI:10.3390/ani11092618

[33]	Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach Sensors, 2019 DOI:10.3390/s19020361

[34]	Data-Driven Decision Making in Precision Agriculture: The Rise of Big Data in Agricultural Systems Journal of Agricultural & Food Information, 2019 DOI:10.1080/10496505.2019.1638264

[35]	Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach Sensors, 2019 DOI:10.3390/s19020361

[36]	Influence of Spatial Aggregation on Prediction Accuracy of Green Vegetation Using Boosted Regression Trees Remote Sensing, 2018 DOI:10.3390/rs10081260

[37]	Influence of Spatial Aggregation on Prediction Accuracy of Green Vegetation Using Boosted Regression Trees Remote Sensing, 2018 DOI:10.3390/rs10081260

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