Xinxin Guo

Dr. Xinxin Guo


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 April 2020 in Sustainability
Verified
Journal Article
Open access
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XGXinxin Guo
Xinxin Guo
QFQiang Fu
Qiang Fu
YHYanhong Hang
Yanhong Hang
HLHe Lu
He Lu
FGFengjie Gao
Fengjie Gao
JSJingbo Si
Jingbo Si
Soil moisture, as a crucial factor in the eco-hydrological process, is of great importance for food production, land management in response to water and soil loss, geomorphic processes, and environmental protection. Understanding the spatial variability of soil moisture induced by different land use types and topographic features is conducive to advancing the adjustment of the land use structure and preventing soil erosion on the hillslopes in the black soil (Mollisols) area of Northeast China. Classical statistical methods and Canonical Correspondence Analysis were used to analyze the spatial heterogeneity of soil moisture at 0–20, 20–40, and 40–60 cm on slopes, to identify the main controlling factors and their relative contributions. The results suggested that: the average soil moisture content followed a decreasing order of grassland > shrubland > soybean land > maize land > adzuki bean (Vigna angularis) land > forestland; the profile soil moisture content (SMC) patterns could be divided into four types, related to the comprehensive influence of vegetation types, root system characteristics, and topographic attributes; the spatial variability of soil moisture was strongly influenced by slope gradient, followed by land use types and elevation and slope position, while slope aspect had the least impact; and finally, land use type had a greater impact on the deep layer than the surface layer, while on the contrary, the influence of the topographic attributes on the deep layer was smaller than on the surface layer. Land use types and topographical elements work together on the soil moisture variability and vertical patterns at differing depths. This study provides an insight into policy making of land resource management and can be used in the modeling of hydrological processes.

28 July 2024 in Land
Verified
Journal Article
Open access
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XGXinxin Guo
Xinxin Guo
YYYang Yang
Yang Yang
YZYi Zhang
Yi Zhang
Mohsen KalantariMohsen Kalantari
Mohsen Kalantari
JSJiali Sun
Jiali Sun
Guoming DUGuoming DU
Guoming DU
For the main grain-producing areas worldwide that balance multi-tasks of grain production, ecological protection, and economic development, quantitatively revealing the correlation between human activity intensity (HAI) and ecosystem service value (ESV) is conducive to formulating adapted ecological protection policies and promoting the coordinated development of the regional economy, society, and ecosystem. In this paper, we took the Songnen Plain of China as an example, employed a modified Equivalent Factor Method (integrating socio-economic data, the normalized difference vegetation index (NDVI), and land use data), and the HAI Assessment Model (based on the data of land use, night-time light, and population spatial distribution) to measure the ESV and HAI in the Songnen Plain of China for the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020. We further applied the standard deviational ellipse method, the coupled coordination degree model, and the bivariate spatial autocorrelation models to reveal the spatiotemporal dynamics and correlation characteristics of ESV and HAI. The results showed the following: (1) Temporally, the ESV declined from 950.96 billion yuan in 1990 to 836.31 billion yuan in 2015, and then increased to 864.60 billion yuan in 2020, with the total loss attributed to the significant decline in the ESV of the natural ecosystem. Spatially, the ESV in the western and northeastern regions was relatively high, with a significant increase in the northeast. (2) HAI showed an upward trend from 1990 to 2020, while the high HAI levels gradually shrank after reaching the peak in 2000. Low HAI levels were mainly distributed in the northeast and southwest, aligning with the ecological space, while high HAI levels were distributed in the middle and southeast. (3) The interaction between ESV and HAI was marked by a negative correlation, transitioning from conflict to coordination. The spatial pattern of HAI and ESV showed H (HAI)-L (ESV) and L-H clustering, with H-H and L-L scattered distributions. This study contributes to providing a framework, methods, and suggestions for the sustainable planning and utilization of land and ecological protection in order to offer scientific references for the Songnen Plain, other major grain-producing areas, and related studies.

20 November 2025 in Land
Verified
Journal Article
Open access
PDF file
XGXinxin Guo
Xinxin Guo
YLYunfeng Liu
Yunfeng Liu
YLYuanyuan Liu
Yuanyuan Liu
TMTongtong Ma
Tongtong Ma
YCYajun Cai
Yajun Cai
SYShengtao Yang
Shengtao Yang
Clarifying the spatiotemporal evolution pattern of cultivated land use system resilience (CLUSR) in major grain-producing areas and identifying the key obstacles constraining its enhancement is of great significance for promoting the sustainable development of cultivated land use systems and ensuring regional food security. Taking the Songnen Plain, a typical major grain-producing area in China, as the study area, we constructed a CLUSR evaluation index system based on the “Resources–Utilization–Production–Ecology” (RUPE) framework and analyzed the spatiotemporal dynamics of CLUSR. Furthermore, we identified the primary factors impeding CLUSR enhancement. The results were as follows: (1) From 2005 to 2020, CLUSR values in the Songnen Plain ranged from 0.3353 to 0.4256, indicating a moderately low level overall but showing an upward trend. Across subsystems, the mean resilience scores followed the order ESR (0.121) > RER (0.114) > GPSR (0.090) > CLUR (0.055). (2) Spatially, CLUSR exhibited a distinct “high in the east and low in the west” pattern, with significant growth in the northwestern region. High–High clusters were primarily concentrated in the southeastern part of the study area, while Low–Low clusters exhibited a divergent spatial pattern. (3) From an indicator perspective, agricultural output value per unit of cultivated area, water coverage degree, agricultural labor input, agricultural mechanization level, cultivated land area, per capita yield of grain, and agricultural capital investment were identified as the dominant obstacles to CLUSR improvement. From a subsystem perspective, grain production stability and cultivated land use subsystems were the primary factors limiting CLUSR improvement in the Songnen Plain. (4) At the county level, obstacle factors were classified into three types: single, dual, and multiple obstacles. Nearly half of the counties were facing multiple constraints simultaneously. This study provides theoretical and practical implications for the formulation of cultivated land use policies in the Songnen Plain and other major grain-producing areas worldwide, thereby contributing to the sustainable utilization of cultivated land.