[HTML][HTML] Air pollution prediction using machine learning techniques–an approach to replace existing monitoring stations with virtual monitoring stations

A Samad, S Garuda, U Vogt, B Yang - Atmospheric Environment, 2023 - Elsevier
Air pollution in the modern world is a matter of grave concern. Due to rapid expansion in
commercial social, and economic aspects, the pollutant concentrations in different parts of …

Comparison of bagging, boosting and stacking algorithms for surface soil moisture mapping using optical-thermal-microwave remote sensing synergies

B Das, P Rathore, D Roy, D Chakraborty, RS Jatav… - Catena, 2022 - Elsevier
Soil moisture information is key to irrigation water management, drought monitoring, and
yield prediction. It plays a vital role in the water cycle and energy budget between the earth's …

Global sea surface salinity via the synergistic use of SMAP satellite and HYCOM data based on machine learning

E Jang, YJ Kim, J Im, YG Park, T Sung - Remote sensing of environment, 2022 - Elsevier
Sea surface salinity (SSS) provides information on the variability of ocean dynamics (global
water cycle and ocean circulation) and air-sea interactions, thereby contributing to the …

Applications of chemical fingerprints and machine learning in plant ecology: Recent progress and future perspectives

C Zhong, L Li, YZ Wang - Microchemical Journal, 2024 - Elsevier
With the rapid development of chromatography, spectroscopy and other detection
techniques, chemical fingerprinting has become a powerful tool for ecology research. The …

Retrieving soil moisture from grape growing areas using multi-feature and stacking-based ensemble learning modeling

S Tao, X Zhang, R Feng, W Qi, Y Wang… - … and Electronics in …, 2023 - Elsevier
Soil moisture (SM) is an essential parameter for crop growth and development, and temporal
and spatial variation in SM in agricultural fields varies by crop type due to corresponding …

[HTML][HTML] Integrative modeling of heterogeneous soil salinity using sparse ground samples and remote sensing images

L Wang, P Hu, H Zheng, Y Liu, X Cao, O Hellwich, T Liu… - Geoderma, 2023 - Elsevier
Soil salinization is a major environmental risk caused by natural or human activities
especially in arid and semi-arid regions. Machine learning for rapidly monitoring large-scale …

A framework for estimating all-weather fine resolution soil moisture from the integration of physics-based and machine learning-based algorithms

P Leng, Z Yang, QY Yan, GF Shang, X Zhang… - … and Electronics in …, 2023 - Elsevier
Due to the effects of radio frequency interference and the limitations of algorithms under
specific conditions, most of the currently available microwave-based soil moisture (SM) …

Mapping population distribution based on XGBoost using multisource data

X Zhao, N Xia, Y Xu, X Huang… - IEEE Journal of Selected …, 2021 - ieeexplore.ieee.org
Mapping fine-scale distribution of the population is essential to the study of human activities,
where more reliable open-access big data could be excavated with the help of machine …

Near-surface soil moisture characterization in mississippi's highway slopes using machine learning methods and UAV-captured infrared and optical images

R Salunke, M Nobahar, OE Alzeghoul, S Khan… - Remote Sensing, 2023 - mdpi.com
Near-surface soil moisture content variation is a major factor in the frequent shallow slope
failures observed on Mississippi's highway slopes built on expansive clay. Soil moisture …

Estimation of soil moisture using multi-source remote sensing and machine learning algorithms in farming land of Northern China

Q Liu, Z Wu, N Cui, X Jin, S Zhu, S Jiang, L Zhao… - Remote Sensing, 2023 - mdpi.com
Soil moisture is a key parameter for the circulation of water and energy exchange between
surface and the atmosphere, playing an important role in hydrology, agriculture, and …