Spatiotemporal dynamics of grassland aboveground biomass and its driving factors in North China over the past 20 years
J Ge, M Hou, T Liang, Q Feng, X Meng, J Liu… - Science of the Total …, 2022 - Elsevier
Although remote sensing has enabled rapid monitoring of grassland aboveground biomass
(AGB) at a regional scale, it is still a difficult challenge to construct an accurate estimation …
(AGB) at a regional scale, it is still a difficult challenge to construct an accurate estimation …
Available water capacity from a multidisciplinary and multiscale viewpoint. A review
Soil–plant–atmosphere models and certain land surface models usually require information
about the ability of soils to store and release water. Thus, a critical soil parameter for such …
about the ability of soils to store and release water. Thus, a critical soil parameter for such …
[HTML][HTML] Comparing the prediction performance, uncertainty quantification and extrapolation potential of regression kriging and random forest while accounting for soil …
Geostatistics and machine learning have been extensively applied for modelling and
predicting the spatial distribution of continuous soil variables. In addition to providing …
predicting the spatial distribution of continuous soil variables. In addition to providing …
Using machine learning for prediction of saturated hydraulic conductivity and its sensitivity to soil structural perturbations
SN Araya, TA Ghezzehei - Water Resources Research, 2019 - Wiley Online Library
Saturated hydraulic conductivity (Ks) is a fundamental soil property that regulates the fate of
water in soils. Its measurement, however, is cumbersome and instead pedotransfer functions …
water in soils. Its measurement, however, is cumbersome and instead pedotransfer functions …
Prediction of soil water infiltration using multiple linear regression and random forest in a dry flood plain, eastern Iran
Abstract Knowledge of the spatial variation of soil infiltration is necessary for managing
water conservation, salinity, and precision agriculture in drylands. In this study, the spatial …
water conservation, salinity, and precision agriculture in drylands. In this study, the spatial …
[HTML][HTML] Progress in the elaboration of GSM conform DSM products and their functional utilization in Hungary
The GlobalSoilMap initiative significantly inspired the DOSoReMI. hu (Digital, Optimized,
Soil Related Maps and Information in Hungary) project, which was started intentionally for …
Soil Related Maps and Information in Hungary) project, which was started intentionally for …
Machine learning for predicting field soil moisture using soil, crop, and nearby weather station data in the Red River Valley of the North
Precise soil moisture prediction is important for water management and logistics of on-farm
operations. However, soil moisture is affected by various soil, crop, and meteorological …
operations. However, soil moisture is affected by various soil, crop, and meteorological …
In situ observation-constrained global surface soil moisture using random forest model
The inherent biases of different long-term gridded surface soil moisture (SSM) products,
unconstrained by the in situ observations, implies different spatio-temporal patterns. In this …
unconstrained by the in situ observations, implies different spatio-temporal patterns. In this …
Develo** pedotransfer functions using Sentinel-2 satellite spectral indices and Machine learning for estimating the surface soil moisture
A Sedaghat, MS Shahrestani, AA Noroozi… - Journal of …, 2022 - Elsevier
To estimate the surface soil moisture (SM) using a combination of new spectral indices and
methods of Random Forrest (RF) and Multiple Linear Regression (MLR), 11 pedotransfer …
methods of Random Forrest (RF) and Multiple Linear Regression (MLR), 11 pedotransfer …
Incorporating machine learning models and remote sensing to assess the spatial distribution of saturated hydraulic conductivity in a light-textured soil
Saturated soil hydraulic conductivity (K sat) is a key component in hydrogeology and water
management. This study aimed at evaluating popular tree-based machine learning …
management. This study aimed at evaluating popular tree-based machine learning …