[HTML][HTML] Advancements and Perspective in the Quantitative Assessment of Soil Salinity Utilizing Remote Sensing and Machine Learning Algorithms: A Review
F Wang, L Han, L Liu, C Bai, J Ao, H Hu, R Li, X Li… - Remote Sensing, 2024 - mdpi.com
Soil salinization is a significant global ecological issue that leads to soil degradation and is
recognized as one of the primary factors hindering the sustainable development of irrigated …
recognized as one of the primary factors hindering the sustainable development of irrigated …
Application of near-infrared spectroscopy to predict chemical properties in clay rich soil: A review
S Park, S Jeon, NH Kwon, M Kwon, JH Shin… - European Journal of …, 2024 - Elsevier
Proximal soil sensing is a highly advanced and rapidly evolving technique for predicting soil
chemical properties. NIR spectroscopy is expected to offer an easier and more cost-effective …
chemical properties. NIR spectroscopy is expected to offer an easier and more cost-effective …
[HTML][HTML] Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean
Soil salinization is a critical global issue for sustainable agriculture, impacting crop yields
and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food …
and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food …
Cyclone vulnerability assessment in the coastal districts of Bangladesh
This research aims to assess the vulnerability to cyclones in the coastal regions of
Bangladesh, employing a comprehensive framework derived from the Intergovernmental …
Bangladesh, employing a comprehensive framework derived from the Intergovernmental …
Future groundwater potential mapping using machine learning algorithms and climate change scenarios in Bangladesh
The aim of the study was to estimate future groundwater potential zones based on machine
learning algorithms and climate change scenarios. Fourteen parameters (ie, curvature …
learning algorithms and climate change scenarios. Fourteen parameters (ie, curvature …
Delineating the drought vulnerability zones in Bangladesh
The research aims to explore the vulnerability of Bangladesh to drought by considering a
comprehensive set of twenty-four factors, classified into four major categories …
comprehensive set of twenty-four factors, classified into four major categories …
Salinity challenges and adaptive strategies in salinization-affected coastal Bangladesh: Implications for agricultural sustainability and water resource management
ML Hossain, J Li - Environmental Research Letters, 2024 - iopscience.iop.org
Salinization has become a rising global concern due to its notable effects on agriculture and
freshwater resources. Coastal region of Bangladesh has been struggling with elevated …
freshwater resources. Coastal region of Bangladesh has been struggling with elevated …
[HTML][HTML] Spatiotemporal Dynamics and Driving Factors of Soil Salinization: A Case Study of the Yutian Oasis, Xinjiang, China
S Li, I Nurmemet, J Seydehmet, X Lv, Y Aili, X Yu - Land, 2024 - mdpi.com
Soil salinization is a critical global environmental issue, exacerbated by climatic and
anthropogenic factors, and posing significant threats to agricultural productivity and …
anthropogenic factors, and posing significant threats to agricultural productivity and …
流域绿洲土壤盐分多模型反演效果评估
龙威夷, 施建飞, 李双媛, 孙金金, 王玉刚 - 干旱区研究, 2024 - azr.xjegi.com
为更好地实现区域土壤盐分的监测和治理, 促进绿洲可持续发展, 本文基于气候, 地形,
植被等相关数据, 结合三工河流域平原绿洲土壤表层盐分调查, 对比评估不同模型(随机森林 …
植被等相关数据, 结合三工河流域平原绿洲土壤表层盐分调查, 对比评估不同模型(随机森林 …
Digital Mapping of Soil Salinity in the Southern Steppe Zone of Russia Based on Artificial Neural Networks and Linear Regression
KO Prokopieva, IV Sobolev - Moscow University Soil Science Bulletin, 2024 - Springer
Remote sensing data are an important source of information for monitoring and mapping
vegetation cover. Machine-learning methods are a modern and powerful tool for data …
vegetation cover. Machine-learning methods are a modern and powerful tool for data …