Jinjie Wang
Biographic Data
| ID | 4020480 |
|---|---|
| NAME | Jinjie Wang |
| GIVEN NAMES | Jinjie |
| FAMILY NAME | Wang |
| SIGNATURE | WANG J |
| AFFILIATIONS | College of Geography and Remote Sensing Sciences Xinjiang University Urumqi China |
| ORCID | 0000-0003-2700-6501 |
| VERIFIED | Yes |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 9 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Assessing Natural Resource Carrying Capacity in Xinjiang Using Remote Sensing: Spatiotemporal Patterns and Implications for Future Land Use
Xinjiang has undergone rapid oasis expansion, leading to significant changes in land use and, consequently, to unsustainable issues regarding natural resources. Most studies on natural resource carrying capacity (NRCC) focus on single resource elements and rarely examine patterns at the pixel scale. Although remote sensing technologies and cloud platforms offer significant advantages in NRCC assessment, this potential remains underutilized. Meanw…
Fractional Order Differentiation Preprocessing Based Fusion of Vis– NIR and pXRF: A New Strategy for Precise Monitoring of Low Concentration Heavy Metals in Arid Agricultural Soils
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…
Unveiling the Advantages of UV −Vis/ NIR − pXRF Data Fusion for Precise Estimation of Soil Heavy Metals in Farmland
Heavy metal contamination in agricultural soils threatens ecosystem stability and food safety. Rapid and accurate estimation of arsenic (As), cadmium (Cd), and lead (Pb) is therefore essential for environmental protection and soil remediation. Near‐field sensing technologies provide a fast and cost‐efficient alternative to laboratory analysis, yet single‐spectrum approaches often suffer from limited information coverage and reduced prediction acc…
Hybrid Modeling of Physics and Machine Learning for Soil Moisture Inversion in Arid Regions on Google Earth Engine
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…
Tobacco contract farming and poverty reduction: Zimbabwe evidence and China lessons
Assessing Surface Water Hydrological Connectivity and Spatiotemporal Evolution in Xinjiang (2000–2020)
Assessing hydrological connectivity is crucial for maintaining the health and integrity of wetland and river‐lake ecosystems in arid regions as it plays a key role in watershed ecological balance and sustainable development. We utilized the Joint Research Center's global surface water dataset. We combined these data with connectivity indices and circuit theory to analyze the hydrological connectivity and spatiotemporal evolution of surface water …
Ameliorating saline‐sodic soils: A global meta‐analysis of field studies on the influence of exogenous amendments on crop yield
As the demand for food continues to rise, soil salinization and sodification pose an increasingly pressing challenge. Currently, there is a knowledge gap regarding how to effectively improve saline‐sodic soils to support sustainable agricultural production, especially the lack of systematic analysis on the effects of different amendments at a global scale. To address this gap, this study aims to explore the feasibility of using exogenous amendmen…
Soil salinity dynamics in arid oases during irrigated and non‐irrigated seasons
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…
Implementation Process of General Land-Use Planning and Its Adjustment—A Case Study of Rongchang District in Chongqing, China
General land-use planning has a critical role and a guiding significance for economic and regional social development. To increase the ability of planning to cope with regional economic changes in an orderly manner and to defend the legal status of the planning guidance role, this article takes Rongchang District as a case study. This study combines GIS spatial analysis to select speed indicators, the center of gravity offset theory, and the spat…
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Implementation Process of General Land-Use Planning and Its Adjustment—A Case Study of Rongchang District in Chongqing, China
General land-use planning has a critical role and a guiding significance for economic and regional social development. To increase the ability of planning to cope with regional economic changes in an orderly manner and to defend the legal status of the planning guidance role, this article takes Rongchang District as a case study. This study combines GIS spatial analysis to select speed indicators, the center of gravity offset theory, and the spat…
Soil salinity dynamics in arid oases during irrigated and non‐irrigated seasons
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…
Ameliorating saline‐sodic soils: A global meta‐analysis of field studies on the influence of exogenous amendments on crop yield
As the demand for food continues to rise, soil salinization and sodification pose an increasingly pressing challenge. Currently, there is a knowledge gap regarding how to effectively improve saline‐sodic soils to support sustainable agricultural production, especially the lack of systematic analysis on the effects of different amendments at a global scale. To address this gap, this study aims to explore the feasibility of using exogenous amendmen…
Assessing Surface Water Hydrological Connectivity and Spatiotemporal Evolution in Xinjiang (2000–2020)
Assessing hydrological connectivity is crucial for maintaining the health and integrity of wetland and river‐lake ecosystems in arid regions as it plays a key role in watershed ecological balance and sustainable development. We utilized the Joint Research Center's global surface water dataset. We combined these data with connectivity indices and circuit theory to analyze the hydrological connectivity and spatiotemporal evolution of surface water …
Assessing Natural Resource Carrying Capacity in Xinjiang Using Remote Sensing: Spatiotemporal Patterns and Implications for Future Land Use
Xinjiang has undergone rapid oasis expansion, leading to significant changes in land use and, consequently, to unsustainable issues regarding natural resources. Most studies on natural resource carrying capacity (NRCC) focus on single resource elements and rarely examine patterns at the pixel scale. Although remote sensing technologies and cloud platforms offer significant advantages in NRCC assessment, this potential remains underutilized. Meanw…
Fractional Order Differentiation Preprocessing Based Fusion of Vis– NIR and pXRF: A New Strategy for Precise Monitoring of Low Concentration Heavy Metals in Arid Agricultural Soils
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…
Unveiling the Advantages of UV −Vis/ NIR − pXRF Data Fusion for Precise Estimation of Soil Heavy Metals in Farmland
Heavy metal contamination in agricultural soils threatens ecosystem stability and food safety. Rapid and accurate estimation of arsenic (As), cadmium (Cd), and lead (Pb) is therefore essential for environmental protection and soil remediation. Near‐field sensing technologies provide a fast and cost‐efficient alternative to laboratory analysis, yet single‐spectrum approaches often suffer from limited information coverage and reduced prediction acc…
Hybrid Modeling of Physics and Machine Learning for Soil Moisture Inversion in Arid Regions on Google Earth Engine
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…
Tobacco contract farming and poverty reduction: Zimbabwe evidence and China lessons
Arid (4 works) · Soil Geostatistics and Mapping (4 works) · Soil water (4 works) · Environmental Science (3 works) · Soil and Unsaturated Flow (3 works) · Agriculture (2 works) · Agronomy (2 works) · Biology (2 works) · China (2 works) · Data pre-processing (2 works)