Xiangyu Ge
Dados Biográficos
| ID | 109203 |
|---|---|
| NOME | Xiangyu Ge |
| PRENOMES | Xiangyu |
| SOBRENOME | Ge |
| ASSINATURA | GE X |
| AFILIAÇÕES | College of Geographical and Remote Sciences Xinjiang University Urumqi China |
| ORCID | 0009-0008-2341-8051 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 18 |
| TOTAL DE CITAÇÕES | 11 |
| TOTAL COMO AUTOR | 18 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2018 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 1 |
Effects of Landscape Pattern on Spatial Distribution of Soil Organic Carbon Content in a Typical Lakeside Oasis
Knowledge of the factors influencing the spatial distribution of farmland soil organic carbon (SOC) content contributes to a better understanding of human impacts on soil, which is crucial for improving soil quality and mitigating climate change. Intensive agricultural production has significantly altered the landscape patterns of oasis farmlands, yet its effects on the spatial distribution of SOC content remain unclear. The study employed Ordina…
Application of the Process‐Oriented and Machine Learning Combined Model in Mapping of Soil Organic Carbon of Non‐Waterlogged Mineral Soils at National Scale
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
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…
Unveiling the Dynamic Patterns and Driving Forces of Soil Organic Carbon in Chinese Croplands From 1980 to 2020
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…
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 …
Soil Organic Carbon Sequestration Potential, Storage, and Influencing Mechanisms in China
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…
Needs Analysis for Business Chinese Education Based on Language Economics
Foreign language education can promote international trade, which, in turn, informs the planning of foreign language education. This study examines how bilateral trade between China and other countries promotes the development of Chinese language education from the perspective of policy planning. The research introduces the structural absorption hypothesis and utilizes trade data alongside indicators to construct regression models. These models a…
Ameliorating saline‐sodic soils
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…
Potential of Hyperspectral Data Combined With Optimal Band Combination Algorithm for Estimating Soil Organic Carbon Content in Lakeside Oasis
Accurate estimation of soil organic carbon (SOC) content is essential for promoting regional sustainable agriculture and improving land quality. Visible and near‐infrared (Vis‐NIR) near‐Earth remote sensing spectroscopy has become an effective alternative to the traditional time‐consuming and costly methods due to its high‐resolution and nondestructive application, but it is vulnerable to the redundancy of spectral information and the overlap bet…
Future changes in soil salinization across Central Asia under CMIP6 forcing scenarios
Soil salinization is a critical environmental and socio‐economic concern with global implications, and its severity is expected to amplify under changing climate. The impact of climate change on salinization in Central Asia is still not fully understood. This study addresses this gap by employing a digital soil mapping (DSM) framework. Cubist, random forest (RF), and quantile regression forests (QRF) are utilized to project variations in soil sur…
Test of the lateral angle method of sex estimation on Anglo‐Saxon and medieval archaeological populations with genetically estimated sex
The lateral angle method of sex estimation is tested on an archaeological population with genetic sex estimates. Casts of the internal auditory canal were made using a quick drying impression material on 90 individuals (76 adults and 14 nonadults) from Anglo‐Saxon and Medieval Cambridgeshire. The anterior and posterior angles of the internal auditory canal were measured, and the relationship of the angle to genetic sex was tested. The posterior a…
Soil salinity estimation
The microwave dielectric constant is a key bridge in establishing the relationship between microwave remote sensing and soil salinity (electrical conductivity, EC). However, the response between microwave dielectric spectrum type, frequency, and soil salinity is still unclear. The purpose of this study is to reveal the dielectric spectrum and frequency range closely related to soil salinity. In this study, 129 surface soil samples were collected,…
The characteristics of local government debt governance
This paper takes 66 local government debt governance policy texts from 2009 to 2019 as sample, and constructs an analysis framework of 'target debt -management measures -mechanism guarantee', derives up with identifying the characteristics of determining local government debt governance in China. The results show as follow: (i) It attaches more importance to the policy design of 'borrowing', 'repayment' and 'management' on local government debt i…
Pathway of Green Development of Yangtze River Economics Belt from the Perspective of Green Technological Innovation and Environmental Regulation
The eco-efficiency of the Yangtze River Economic Belt from 2005 to 2019 has been evaluated by the super-efficiency SBM window model, the results of which are taken as the measurement standard for green development. Next, more attempts have been done to figure out the impacts of green technological innovation on the green development in urban clusters of the Yangtze River Economic Belt by a systematic GMM model, further confirming the moderation e…
Evaluating macroscopic sex estimation methods using genetically sexed archaeological material
OBJECTIVES: In tests on known individuals macroscopic sex estimation has between 70% and 98% accuracy. However, materials used to create and test these methods are overwhelming modern. As sexual dimorphism is dependent on multiple factors, it is unclear whether macroscopic methods have similar success on earlier materials, which differ in lifestyle and nutrition. This research aims to assess the accuracy of commonly used traits by comparing macro…
A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China
Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China's central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their ne…
Evaluating macroscopic sex estimation methods using genetically sexed archaeological material
OBJECTIVES: In tests on known individuals macroscopic sex estimation has between 70% and 98% accuracy. However, materials used to create and test these methods are overwhelming modern. As sexual dimorphism is dependent on multiple factors, it is unclear whether macroscopic methods have similar success on earlier materials, which differ in lifestyle and nutrition. This research aims to assess the accuracy of commonly used traits by comparing macro…
A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China
Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China's central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their ne…
Evaluating macroscopic sex estimation methods using genetically sexed archaeological material
OBJECTIVES: In tests on known individuals macroscopic sex estimation has between 70% and 98% accuracy. However, materials used to create and test these methods are overwhelming modern. As sexual dimorphism is dependent on multiple factors, it is unclear whether macroscopic methods have similar success on earlier materials, which differ in lifestyle and nutrition. This research aims to assess the accuracy of commonly used traits by comparing macro…
Pathway of Green Development of Yangtze River Economics Belt from the Perspective of Green Technological Innovation and Environmental Regulation
The eco-efficiency of the Yangtze River Economic Belt from 2005 to 2019 has been evaluated by the super-efficiency SBM window model, the results of which are taken as the measurement standard for green development. Next, more attempts have been done to figure out the impacts of green technological innovation on the green development in urban clusters of the Yangtze River Economic Belt by a systematic GMM model, further confirming the moderation e…
The characteristics of local government debt governance
This paper takes 66 local government debt governance policy texts from 2009 to 2019 as sample, and constructs an analysis framework of 'target debt -management measures -mechanism guarantee', derives up with identifying the characteristics of determining local government debt governance in China. The results show as follow: (i) It attaches more importance to the policy design of 'borrowing', 'repayment' and 'management' on local government debt i…
Soil salinity estimation
The microwave dielectric constant is a key bridge in establishing the relationship between microwave remote sensing and soil salinity (electrical conductivity, EC). However, the response between microwave dielectric spectrum type, frequency, and soil salinity is still unclear. The purpose of this study is to reveal the dielectric spectrum and frequency range closely related to soil salinity. In this study, 129 surface soil samples were collected,…
Ameliorating saline‐sodic soils
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…
Potential of Hyperspectral Data Combined With Optimal Band Combination Algorithm for Estimating Soil Organic Carbon Content in Lakeside Oasis
Accurate estimation of soil organic carbon (SOC) content is essential for promoting regional sustainable agriculture and improving land quality. Visible and near‐infrared (Vis‐NIR) near‐Earth remote sensing spectroscopy has become an effective alternative to the traditional time‐consuming and costly methods due to its high‐resolution and nondestructive application, but it is vulnerable to the redundancy of spectral information and the overlap bet…
Future changes in soil salinization across Central Asia under CMIP6 forcing scenarios
Soil salinization is a critical environmental and socio‐economic concern with global implications, and its severity is expected to amplify under changing climate. The impact of climate change on salinization in Central Asia is still not fully understood. This study addresses this gap by employing a digital soil mapping (DSM) framework. Cubist, random forest (RF), and quantile regression forests (QRF) are utilized to project variations in soil sur…
Test of the lateral angle method of sex estimation on Anglo‐Saxon and medieval archaeological populations with genetically estimated sex
The lateral angle method of sex estimation is tested on an archaeological population with genetic sex estimates. Casts of the internal auditory canal were made using a quick drying impression material on 90 individuals (76 adults and 14 nonadults) from Anglo‐Saxon and Medieval Cambridgeshire. The anterior and posterior angles of the internal auditory canal were measured, and the relationship of the angle to genetic sex was tested. The posterior a…
Unveiling the Dynamic Patterns and Driving Forces of Soil Organic Carbon in Chinese Croplands From 1980 to 2020
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…
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 …
Soil Organic Carbon Sequestration Potential, Storage, and Influencing Mechanisms in China
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…
Needs Analysis for Business Chinese Education Based on Language Economics
Foreign language education can promote international trade, which, in turn, informs the planning of foreign language education. This study examines how bilateral trade between China and other countries promotes the development of Chinese language education from the perspective of policy planning. The research introduces the structural absorption hypothesis and utilizes trade data alongside indicators to construct regression models. These models a…
Effects of Landscape Pattern on Spatial Distribution of Soil Organic Carbon Content in a Typical Lakeside Oasis
Knowledge of the factors influencing the spatial distribution of farmland soil organic carbon (SOC) content contributes to a better understanding of human impacts on soil, which is crucial for improving soil quality and mitigating climate change. Intensive agricultural production has significantly altered the landscape patterns of oasis farmlands, yet its effects on the spatial distribution of SOC content remain unclear. The study employed Ordina…
Application of the Process‐Oriented and Machine Learning Combined Model in Mapping of Soil Organic Carbon of Non‐Waterlogged Mineral Soils at National Scale
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
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…
Environmental Science (10 obras) · Soil water (10 obras) · Geology (7 obras) · Soil Geostatistics and Mapping (7 obras) · Soil Science (7 obras) · Geography (6 obras) · Soil carbon (5 obras) · Computer Science (4 obras) · Earth science (4 obras) · Geochemistry and Geologic Mapping (4 obras)