Spatial evapotranspiration, rainfall and land use data in water accounting–Part 1: Review of the accuracy of the remote sensing data

P Karimi, WGM Bastiaanssen - Hydrology and Earth System …, 2015 - hess.copernicus.org
The scarcity of water encourages scientists to develop new analytical tools to enhance water
resource management. Water accounting and distributed hydrological models are examples …

Application of GIS-based data driven random forest and maximum entropy models for groundwater potential map**: a case study at Mehran Region, Iran

O Rahmati, HR Pourghasemi, AM Melesse - Catena, 2016 - Elsevier
Groundwater is considered as the most important natural resources in arid and semi-arid
regions. In this study, the application of random forest (RF) and maximum entropy (ME) …

Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an …

V Rodriguez-Galiano, MP Mendes… - Science of the Total …, 2014 - Elsevier
Watershed management decisions need robust methods, which allow an accurate predictive
modeling of pollutant occurrences. Random Forest (RF) is a powerful machine learning data …

Accuracy improvements to pixel-based and object-based lulc classification with auxiliary datasets from Google Earth engine

L Qu, Z Chen, M Li, J Zhi, H Wang - Remote Sensing, 2021 - mdpi.com
The monitoring and assessment of land use/land cover (LULC) change over large areas are
significantly important in numerous research areas, such as natural resource protection …

Comparison of gradient boosted decision trees and random forest for groundwater potential map** in Dholpur (Rajasthan), India

S Sachdeva, B Kumar - Stochastic Environmental Research and Risk …, 2021 - Springer
In the drought prone district of Dholpur in Rajasthan, India, groundwater is a lifeline for its
inhabitants. With population explosion and rapid urbanization, the groundwater is being …

[HTML][HTML] Auxiliary datasets improve accuracy of object-based land use/land cover classification in heterogeneous savanna landscapes

P Hurskainen, H Adhikari, M Siljander… - Remote sensing of …, 2019 - Elsevier
Classifying land use/land cover (LULC) with sufficient accuracy in heterogeneous
landscapes is challenging using only satellite imagery. To improve classification accuracy …

Predictive modelling of gold potential with the integration of multisource information based on random forest: a case study on the Rodalquilar area, Southern Spain

VF Rodriguez-Galiano, M Chica-Olmo… - International Journal …, 2014 - Taylor & Francis
Mineral exploration activities require robust predictive models that result in accurate
map** of the probability that mineral deposits can be found at a certain location. Random …

Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review

C Zhang, K Wang, Y Yue, X Qi, M Zhang - Sensors, 2023 - mdpi.com
Ecosystem conditions at the regional level are critical factors for environmental
management, public awareness, and land use decision making. Regional ecosystem …

Evaluating the impacts of land use/land cover changes across topography against land surface temperature in Cameron Highlands

D How ** Aik, MH Ismail, FM Muharam, MA Alias - PloS one, 2021 - journals.plos.org
The Cameron Highlands has experienced multiple land encroachment activities and
repeated deforestation, leading to extensive land-use and land-cover change (LULCC) …

Evaluation of different machine learning methods for land cover map** of a Mediterranean area using multi-seasonal Landsat images and Digital Terrain Models

VF Rodriguez-Galiano… - International Journal of …, 2014 - Taylor & Francis
Land cover monitoring using digital Earth data requires robust classification methods that
allow the accurate map** of complex land cover categories. This paper discusses the …