Identifying Determinants of Spatiotemporal Disparities in Ecological Quality of Mongolian Plateau

Vegetation quality is crucial for maintaining ecological health, and remote sensing techniques offer precise assessments of vegetation’s environmental quality. Although existing indicators and remote sensing approaches provide extensive spatial coverage, challenges remain in effectively integrating diverse indicators for a comprehensive evaluation. This study introduces a comprehensive ecological quality index (EQI) to assess vegetation quality on the Mongolian Plateau from 2001 to 2020 and to identify the determinants of EQI variations over space and time. We developed the EQI using remotely sensed normalized difference vegetation index (NDVI) data and the net primary productivity (NPP). Our analysis revealed distinct spatial patterns, with high ecological quality concentrated in northern Mongolia and eastern Inner Mongolia. Temporal fluctuations, indicative of ecological shifts, were primarily observed in eastern Mongolia and specific zones of Inner Mongolia. We employed a Geographically Optimal Zones-based Heterogeneity (GOZH) model to analyze the spatial scales and interactions influencing EQI patterns. This study found that precipitation, with an Omega value of 0.770, was the dominant factor affecting the EQI, particularly at spatial scales of 40–50 km. The GOZH model provided deeper insights into the spatial determinants of the EQI compared with previous models, highlighting the importance of climatic variables and their interactions in driving ecological quality. This research enhanced our understanding of vegetation quality dynamics and established a foundation for ecosystem conservation and informed management strategies, emphasizing the critical role of climate, especially precipitation, in shaping ecological landscapes.

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Publication Details

Journal
Remote Sensing
Published
2024-09-12
DOI
https://doi.org/10.3390/rs16183385
Citations
4
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
1.13
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article

Identifying Determinants of Spatiotemporal Disparities in Ecological Quality of Mongolian Plateau

Zhengtong Wang, Yongze Song, Zhengyuan Chai, Zehua Zhang et al.
4 citations
Remote Sensing
Land Use and Ecosystem Services
1.13
article

Identifying Determinants of Spatiotemporal Disparities in Ecological Quality of Mongolian Plateau

Zhengtong Wang, Yongze Song, Zhengyuan Chai, Zehua Zhang, Xueyuan Zhang, Peng Luo, Gang Lin
article en
4 citations

Abstract

Vegetation quality is crucial for maintaining ecological health, and remote sensing techniques offer precise assessments of vegetation’s environmental quality. Although existing indicators and remote sensing approaches provide extensive spatial coverage, challenges remain in effectively integrating diverse indicators for a comprehensive evaluation. This study introduces a comprehensive ecological quality index (EQI) to assess vegetation quality on the Mongolian Plateau from 2001 to 2020 and to identify the determinants of EQI variations over space and time. We developed the EQI using remotely sensed normalized difference vegetation index (NDVI) data and the net primary productivity (NPP). Our analysis revealed distinct spatial patterns, with high ecological quality concentrated in northern Mongolia and eastern Inner Mongolia. Temporal fluctuations, indicative of ecological shifts, were primarily observed in eastern Mongolia and specific zones of Inner Mongolia. We employed a Geographically Optimal Zones-based Heterogeneity (GOZH) model to analyze the spatial scales and interactions influencing EQI patterns. This study found that precipitation, with an Omega value of 0.770, was the dominant factor affecting the EQI, particularly at spatial scales of 40–50 km. The GOZH model provided deeper insights into the spatial determinants of the EQI compared with previous models, highlighting the importance of climatic variables and their interactions in driving ecological quality. This research enhanced our understanding of vegetation quality dynamics and established a foundation for ecosystem conservation and informed management strategies, emphasizing the critical role of climate, especially precipitation, in shaping ecological landscapes.

Remote SensingVol. 16(18)
Curtin University (AU), China University of Geosciences (Beijing) (CN), Inner Mongolia University of Science and Technology (CN), Technical University of Munich (DE), Lanzhou University (CN)
Life in Land
Openalex Percentile: Top 23%
Land Use and Ecosystem Services
1.13
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