Jingzhe Wang

Biographic Data

ID8842756
NAMEJingzhe Wang
GIVEN NAMESJingzhe
FAMILY NAMEWang
SIGNATUREWANG J
AFFILIATIONSSchool of Artificial Intelligence Shenzhen Polytechnic University Shenzhen China
ORCID0000-0001-8332-7997
VERIFIEDYes
TOTAL WORKS8
TOTAL CITATIONS0
WORKS AS AUTHOR8
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2026
H-INDEX0

  • Application of the Process‐Oriented and Machine Learning Combined Model in Mapping of Soil Organic Carbon of Non‐Waterlogged Mineral Soils at National Scale

    Open AccessKeqiang Wang, Zipeng Zhang et al.ARTICLELand Degradation and Development2026

    Integrating process‐oriented (PO) and machine learning (ML) models is effective for obtaining dynamic spatial information on soil organic carbon (SOC) stocks. However, PO‐ML integration, particularly at large scales, has received insufficient attention. This gap limits our understanding of and predictive capabilities regarding SOC dynamics. To explore the adaptability and effectiveness of PO‐ML integration on a large scale, we constructed a natio…

  • Fractional Order Differentiation Preprocessing Based Fusion of Vis– NIR and pXRF

    Open AccessLiangyi Li, Zipeng Zhang et al.ARTICLELand Degradation and Development2026

    Soil contamination by heavy metals has become a significant issue threatening the ecological security of global agriculture, particularly in arid regions, where accurate monitoring of low‐concentration heavy metals remains a technical challenge. This study proposes a proximal sensing method based on the fusion of visible–near infrared (Vis–NIR) spectroscopy and portable X‐ray fluorescence (pXRF) sensors, aiming to address the limitations of tradi…

  • Hybrid Modeling of Physics and Machine Learning for Soil Moisture Inversion in Arid Regions on Google Earth Engine

    Open AccessXinlei Jiang, Xiangyu Ge et al.ARTICLELand Degradation and Development2026

    Soil moisture content (SMC) is vital for agriculture and water management, but accurate monitoring remains challenging. Current methods rely on standalone physical models (e.g., Water Cloud Model) or machine learning (ML), but physical models lack accuracy in complex environments, while ML lacks physical constraints. We hypothesize that hybrid models can improve SMC estimation. Using 90 soil samples from arid oasis ecosystems, we compared four ap…

  • Unveiling the Dynamic Patterns and Driving Forces of Soil Organic Carbon in Chinese Croplands From 1980 to 2020

    Open AccessJunchen Ai, Zipeng Zhang et al.ARTICLELand Degradation and Development2025

    Soil organic carbon (SOC) in cropland is a critical component of the global carbon cycle, representing the most dynamic segment of the carbon pool, and is vital to addressing both “dual‐carbon” goals and food security challenges. However, the current research on SOC in China's croplands has limitations in timeliness, continuity, and accuracy. This study constructed a machine learning model to assess the spatial–temporal distribution and changes o…

  • Soil Organic Carbon Sequestration Potential, Storage, and Influencing Mechanisms in China

    Open AccessJinhua Cao, Zipeng Zhang et al.ARTICLELand Degradation and Development2025

    The soil organic carbon sequestration potential (SOC sp ) has important implications for the global carbon cycle and responses to climate change. However, there is a dearth of spatial information specifically for China within this field, and our knowledge regarding the factors influencing SOC sp remains somewhat limited. To solve this problem, this study utilized legacy soil data collected in the 1980s (1979–1984s), combined with climatic landsca…

  • The influence of lifestyle habits on levels of depression among rural middle school students in Northeastern China

    Open AccessJunCheng Zhao, Xiaoyin Wang et al.ARTICLEFrontiers in Public Health2024

    Background Depression rates among adolescents have risen dramatically over the past decade. Therefore, preventing depression among adolescents is particularly important. Differences in lifestyle habits may play a role in depression. Purpose This study aimed to explore the influence of living habits on depression levels among rural middle school students in Northeast China and to provide a theoretical basis for developing interventions to reduce d…

  • Soil salinity dynamics in arid oases during irrigated and non‐irrigated seasons

    Open AccessChuanmei Zhu, Jianli Ding et al.ARTICLELand Degradation and Development2023

    Preventing soil salinization is key to the healthy development of agroecosystems in arid regions. Notably, long‐term anthropogenic irrigation accelerates secondary salinity accumulation in arid areas; however, the regional‐scale spatial patterns of soil salinity pre‐ and post‐irrigation season remain unclear. Accordingly, field observations over two periods ( n = 182 samples), along with environmental covariates and the randomForest algorithm, we…

  • Changes in soil organic carbon stocks from 1980‐1990 and 2010‐2020 in the northwest arid zone of China

    Open AccessZipeng Zhang, Jianli Ding et al.ARTICLELand Degradation and Development2022

    Soil is the largest carbon reservoir in terrestrial ecosystems, and thus minor changes in it can dramatically affect atmospheric CO 2 concentrations. In the northwestern arid zone of China, the prediction of soil organic carbon (SOC) changes is often limited by the scarcity of soil samples and the scale and depth of research, which limit the understanding of carbon cycling processes in arid zone terrestrial ecosystems. Therefore, this study produ…