Assessing the impact of fractional vegetation cover on urban thermal environment: A case study of Hangzhou, China

M Zhang, S Tan, C Zhang, S Han, S Zou… - Sustainable Cities and …, 2023 - Elsevier
The large-scale urbanization has changed the surface characteristics of cities, seriously
affected the urban heat balance, and worsened the urban thermal environment. The …

Rolling bearing fault diagnosis based on WGWOA-VMD-SVM

J Zhou, M Xiao, Y Niu, G Ji - Sensors, 2022 - mdpi.com
A rolling bearing fault diagnosis method based on whale gray wolf optimization algorithm-
variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was …

How can agricultural water production be promoted? A review on machine learning for irrigation

H Gao, L Zhangzhong, W Zheng, G Chen - Journal of Cleaner Production, 2023 - Elsevier
Abstract The Food and Agriculture Organization (FAO) indicated that irrigation technology is
the key to improving food security. However, the current restricted agricultural water and …

TPE-CatBoost: An adaptive model for soil moisture spatial estimation in the main maize-producing areas of China with multiple environment covariates

J Yu, W Zheng, L Xu, F Meng, J Li, L Zhangzhong - Journal of Hydrology, 2022 - Elsevier
Maize is one of the major crops in China. The soil water content (SWC) in the root zone of
maize is a critical indicator that guides agricultural production decisions and can affect …

A Review of Root Zone Soil Moisture Estimation Methods Based on Remote Sensing

M Li, H Sun, R Zhao - Remote Sensing, 2023 - mdpi.com
Root zone soil moisture (RZSM) controls vegetation transpiration and hydraulic distribution
processes and plays a key role in energy and water exchange between land surface and …

Modelling soil moisture using climate data and normalized difference vegetation index based on nine algorithms in alpine grasslands

S Wang, G Fu - Frontiers in Environmental Science, 2023 - frontiersin.org
Soil moisture (SM) is closely correlated with ecosystem structure and function. Examining
whether climate data (temperature, precipitation and radiation) and the normalized …

Computer vision and machine learning for smart farming and agriculture practices

K Kalinaki, W Shafik, TJL Gutu… - Artificial intelligence tools …, 2023 - igi-global.com
The advent of cutting-edge techniques such as Computer Vision (CV) and Artificial
Intelligence (AI) have sparked a revolution in the agricultural industry, with applications …

[HTML][HTML] Explainable artificial intelligence reveals environmental constraints in seagrass distribution

B He, Y Zhao, W Mao - Ecological Indicators, 2022 - Elsevier
Seagrass is a globally vital marine resource that plays an essential global role in combating
climate change, protecting coastlines, ensuring food security, and enriching biodiversity …

Application of hyperspectral technology combined with bat algorithm-AdaBoost model in field soil nutrient prediction

H Wang, L Zhang, J Zhao, X Hu, X Ma - Ieee Access, 2022 - ieeexplore.ieee.org
This paper proposes a hyperspectral soil nutrient estimation method based on the bat
algorithm (BA)-AdaBoost model. The spectral reflectance, the first derivative of the …

[HTML][HTML] Inversion of large-scale citrus soil moisture using multi-temporal Sentinel-1 and Landsat-8 data

Z Wu, N Cui, W Zhang, D Gong, C Liu, Q Liu… - Agricultural Water …, 2024 - Elsevier
Soil moisture is a significant variable in agricultural study and precision irrigation decision-
making. It determines the soil water availability for plants, directly influencing plant growth …