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Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate Ⅱ

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 15773

Special Issue Editors

College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Interests: vegetation change; land–atmosphere interactions; model simulation; climate change
Special Issues, Collections and Topics in MDPI journals
Department of Earth Science, University of Gothernburg, 405 30 Gothenburg, Sweden
Interests: climate extreme events; land–atmosphere interaction; climate modeling
Special Issues, Collections and Topics in MDPI journals
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Interests: remote sensing and modeling of the frozen ground and environment; climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Vegetation, as one of the crucial underlying land surfaces, plays an important role in terrestrial ecosystems and the Earth's climate system. Under the impact of climate warming, vegetation exhibits clear diverse responses, such as greening and browning, which have been reported by many remote sensing studies. Vegetation is an important and sensitive indicator of climate and environment evolutions, underscoring the need to better detect and understand vegetation physiological and phenological responses, analyze mechanisms of how changes in land surface properties (e.g. surface albedo and roughness length) are associated with vegetation dynamics, and identify climate and ecological feedbacks of vegetation changes. The recent development of satellite remote sensing and its derived products provide great opportunities to study vegetation dynamics and its feedback to regional and global climate system. Moreover, some of the new generation of climate models, such as CMIP6 Earth system models, which include dynamic vegetation, are state-of-the-art tools for investigating the feedback of vegetation changes.

For this Special Issue, contributions are sought which demonstrate the application of a variety of high-resolution satellite data, global and regional numerical models, and machine learning methods to obtain the fine classification of vegetation, detect vegetation dynamic changes, and examine interactions between vegetation and climate/ecological systems, especially for high-latitude and high-altitude regions. We would like to invite you to contribute to the Special Issue. Submissions are encouraged to cover a wide range of topics, which may include, but are not limited to, the following:

  • Vegetation mapping;
  • Vegetation changes from various remote sensing data sources;
  • Response of vegetation to climate change;
  • Feedback of vegetation change to climate;
  • Dynamic vegetation modeling;
  • Ecological effect of vegetation change.

Dr. Xuejia Wang
Dr. Tinghai Ou
Dr. Wenxin Zhang
Dr. Youhua Ran
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • vegetation type
  • vegetation phenology
  • change detection
  • model simulation
  • response to climate change
  • feedback to climate change

Published Papers (9 papers)

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19 pages, 10404 KiB  
Article
Response of Vegetation Phenology to Climate Change on the Tibetan Plateau Considering Time-Lag and Cumulative Effects
by Xiaohui He, Anqi Liu, Zhihui Tian, Lili Wu and Guangsheng Zhou
Remote Sens. 2024, 16(1), 49; https://doi.org/10.3390/rs16010049 - 21 Dec 2023
Viewed by 660
Abstract
The study of the response of vegetation phenology in the Qinghai Tibet Plateau to various climatic variables is paramount to unveiling the reaction of alpine ecosystems to worldwide climate alterations. Nonetheless, the lagged and cumulative effects of various climatic variables on vegetation phenology [...] Read more.
The study of the response of vegetation phenology in the Qinghai Tibet Plateau to various climatic variables is paramount to unveiling the reaction of alpine ecosystems to worldwide climate alterations. Nonetheless, the lagged and cumulative effects of various climatic variables on vegetation phenology in the Qinghai Tibet Plateau remain unclear. Therefore, based on MODIS NDVI data, we extracted vegetation phenological parameters from 2001 to 2020, including the start of the vegetation growing season (SOS) and the end of the vegetation growing season (EOS), and then analyzed the response mechanisms of vegetation phenology to pre-seasonal air temperature (T), precipitation (P), and daytime and nighttime land surface temperatures (DLST, NLST) in the Qinghai Tibet Plateau on the basis of an investigation of the lag and cumulative effects. The results showed that: (1) the multiyear mean values of the SOS mainly occurred from 120 to 160 days, accounting for 86.17% of the study area, while the multiyear mean values of the EOS were mainly concentrated between 260 and 280 days, accounting for 77.05% of the study area; (2) air temperature (T), precipitation (P), and daytime and nighttime land surface temperatures (DLST, NLST) had different degrees of lagging effects on the SOS and the EOS. Among them, the time lag effect of precipitation on vegetation phenology was more pronounced; (3) different climatic variables had distinct cumulative effects on vegetation phenology. In contrast to the insignificant cumulative effects of temperature and nighttime surface temperature on the SOS and the EOS, the cumulative effects of precipitation and daytime land surface temperature on the SOS were more pronounced than those on the EOS; (4) the SOS and air temperature, precipitation, and NLST were mainly negatively correlated, in which the proportion of the negative correlation between SOS and NLST was up to 68.80%, and SOS and DLST were mainly positively correlated with a positive correlation proportion of 73.27%, EOS and air temperature, precipitation, and NLST were positively correlated with a positive correlation proportion of EOS and precipitation of up to 71.52%, and EOS and DLST were mainly negatively correlated with a negative correlation ratio of 55.87%. Full article
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21 pages, 16094 KiB  
Article
Spatiotemporal Variations of Global Terrestrial Typical Vegetation EVI and Their Responses to Climate Change from 2000 to 2021
by Chenhao Li, Yifan Song, Tianling Qin, Denghua Yan, Xin Zhang, Lin Zhu, Batsuren Dorjsuren and Hira Khalid
Remote Sens. 2023, 15(17), 4245; https://doi.org/10.3390/rs15174245 - 29 Aug 2023
Viewed by 841
Abstract
With the increasing impact of climate change on ecosystems, it is crucial to analyze how changes in precipitation and temperature affect global ecosystems. Therefore, this study aims to investigate the spatiotemporal variation characteristics of the Enhanced Vegetation Index (EVI) in the global forest, [...] Read more.
With the increasing impact of climate change on ecosystems, it is crucial to analyze how changes in precipitation and temperature affect global ecosystems. Therefore, this study aims to investigate the spatiotemporal variation characteristics of the Enhanced Vegetation Index (EVI) in the global forest, grassland, shrubland, and tundra (FGST) from 2000 to 2021. We utilized partial correlation analysis and grey relation analysis to assess the responses of different vegetation types to precipitation, temperature, and extreme water and heat indicators. The result shows that, despite a “warmer and drier” trend in FGST (excluding tundra), global climate change has not adversely affected the ongoing vegetation growth. It presents a favorable implication for global carbon dioxide assimilation. Different vegetation types displayed different sensitivities to changes in precipitation and temperature. Shrubland proved to be the most sensitive, followed by grassland, forest, and tundra. As the impacts of global climate change intensify, it becomes crucial to direct our attention toward dynamics of vegetation types demonstrating heightened sensitivity to fluctuations in precipitation and temperature. Our study indicates that, except for forests, extreme precipitation indicators have a stronger impact on EVI than extreme temperature indicators. Forests and tundra have demonstrated heightened susceptibility to the intensity of extreme climatic events, while grasslands and shrublands have been more sensitive to the duration of such events. Understanding these responses can offer valuable insights for developing targeted strategies for adaptation and preservation. Our study enhances comprehension of the feedback relationship between global climate change and vegetation, offering scientific evidence for global climate change evaluation. Full article
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18 pages, 8635 KiB  
Article
Sensitivity of Vegetation to Climate in Mid-to-High Latitudes of Asia and Future Vegetation Projections
by Jiangfeng Wei, Xiaocong Liu and Botao Zhou
Remote Sens. 2023, 15(10), 2648; https://doi.org/10.3390/rs15102648 - 19 May 2023
Cited by 3 | Viewed by 1828
Abstract
Mid- to high-latitude Asia (MHA) is one of the regions with the strongest warming trend and it is also a region where ecosystems are most sensitive to climate variability. However, how the vegetation in the region will change in the future remains uncertain. [...] Read more.
Mid- to high-latitude Asia (MHA) is one of the regions with the strongest warming trend and it is also a region where ecosystems are most sensitive to climate variability. However, how the vegetation in the region will change in the future remains uncertain. Using observation-based Leaf Area Index (LAI) and meteorological data and the multiple regression method, this study analyzes the response of vegetation in the MHA to climate elements during 1982–2020. Then, machine learning prediction models based on the Random Forest (RF) and Extreme Random Tree (ERT) algorithms are built and validated. Based on the calibrated meteorological fields from 17 Coupled Model Intercomparison Project Phase 6 (CMIP6) models under intermediate (SSP2-4.5) and high (SSP5-8.5) emission scenarios and the machine learning models, the LAI over the MHA in 2021–2100 is projected. The historical long-term increasing trends of LAI in the MHA since 1982 are found to be mainly caused by the increasing near-surface air temperature, while the interannual variations of LAI are also greatly affected by precipitation and surface downward solar radiation, especially in summer. The LAI over most of the MHA shows a significant increasing trend in the future, except over some dry areas, and the increasing trends are stronger under the SSP5-8.5 scenario than under the SSP2-4.5 scenario. Full article
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20 pages, 9703 KiB  
Article
Temporal and Spatial Change in Vegetation and Its Interaction with Climate Change in Argentina from 1982 to 2015
by Qi Long, Fei Wang, Wenyan Ge, Feng Jiao, Jianqiao Han, Hao Chen, Fidel Alejandro Roig, Elena María Abraham, Mengxia Xie and Lu Cai
Remote Sens. 2023, 15(7), 1926; https://doi.org/10.3390/rs15071926 - 03 Apr 2023
Cited by 2 | Viewed by 2952
Abstract
Studying vegetation change and its interaction with climate change is essential for regional ecological protection. Previous studies have demonstrated the impact of climate change on regional vegetation in South America; however, studies addressing the fragile ecological environment in Argentina are limited. Therefore, we [...] Read more.
Studying vegetation change and its interaction with climate change is essential for regional ecological protection. Previous studies have demonstrated the impact of climate change on regional vegetation in South America; however, studies addressing the fragile ecological environment in Argentina are limited. Therefore, we assessed the vegetation dynamics and their climatic feedback in five administrative regions of Argentina, using correlation analysis and multiple regression analysis methods. The Normalized Difference Vegetation Index 3rd generation (NDVI3g) from Global Inventory Monitoring and Modeling Studies (GIMMS) and climatic data from the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) were processed. The NDVI of the 1982–2015 period in Argentina showed a downward trend, varying from −1.75 to 0.69/decade. The NDVI in Northeast Argentina (NEA), Northwest Argentina (NWA), Pampas, and Patagonia significantly decreased. Precipitation was negatively correlated with the NDVI in western Patagonia, whereas temperature and solar radiation were positively correlated with the NDVI. Extreme precipitation and drought were essential causes of vegetation loss in Patagonia. The temperature (73.09%), precipitation (64.02%), and solar radiation (73.27%) in Pampas, Cuyo, NEA, and NWA were positively correlated with the NDVI. However, deforestation and farming and pastoral activities have caused vegetation destruction in Pampas, NEA, and NWA. Environmental protection policies and deforestation regulations should be introduced to protect the ecological environment. The results of this study clarify the reasons for the vegetation change in Argentina and provide a theoretical reference for dealing with climate change. Full article
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19 pages, 4221 KiB  
Article
Land Surface Greening and CO2 Fertilization More than Offset the Gross Carbon Sequestration Decline Caused by Land Cover Change and the Enhanced Vapour Pressure Deficit in Europe
by Qiaoli Wu, Xinyao Wang, Shaoyuan Chen, Li Wang and Jie Jiang
Remote Sens. 2023, 15(5), 1372; https://doi.org/10.3390/rs15051372 - 28 Feb 2023
Cited by 1 | Viewed by 1392
Abstract
Satellite observations have revealed strong land surface “greening” (i.e., increases in vegetation greenness or leaf area index (LAI)) in the Northern Hemisphere over the past few decades. European terrestrial ecosystems are a greening hotspot, but how they respond to land surface greening, climate [...] Read more.
Satellite observations have revealed strong land surface “greening” (i.e., increases in vegetation greenness or leaf area index (LAI)) in the Northern Hemisphere over the past few decades. European terrestrial ecosystems are a greening hotspot, but how they respond to land surface greening, climate change, CO2 fertilization, land use and land cover change (LULCC) and other factors is unclear. Here, we assessed how these interacting factors might be combined to alter terrestrial gross primary production (GPP) throughout Europe during the period of 2001 to 2016 using a process-based Farquhar GPP model (i.e., FGM). We found a more productive European terrestrial ecosystem and most of the GPP enhancement in Europe was explained by increases in LAI (62%) and atmospheric CO2 concentration (29%). Spatially, the spatial signature of the LAI and GPP trends both suggested widespread (72–73% of the vegetated area) greening phenomena across Europe, among which 23.7% and 13.3% were statistically significant (p < 0.05). The interannual trend of GPP estimated by the FGM (0.55% yr−1) was reasonable compared with other GPP products (0.47% yr−1 to 0.92% yr−1) and the observed LAI increasing rate (0.62% yr−1). FGM factorial simulations suggested that land surface greening (+35.5 Pg C yr−2, p < 0.01), CO2 fertilization (+16.9 Pg C yr−2, p < 0.01), temperature warming (+3.7 Pg C yr−2, p < 0.05), and enhanced downwards solar radiation (+1.2 Pg C yr−2, p > 0.05) contributed to the GPP enhancement, while the enhanced vapour pressure deficit (−5.6 Tg C yr−2, p < 0.01) had significant negative impacts on GPP, especially in 2006 and 2012, when extreme droughts struck south-eastern Europe. Meanwhile, approximately 1.8% of the total area of Europe experienced LULCC from 2001 to 2016 and LULCC exerted a small but significant (−1.3 Tg C yr−2, p < 0.01) impact on GPP due to decreases in the total number of vegetated pixels (−159 pixels yr−1). Although the LULCC effect was negative, the largest increase occurred in forested land (+0.9% of total area). In addition, the increasing trends for the annual mean LAI (0.01 m2 m−2 yr−1, p < 0.001) and total GPP (22.2 Tg C yr−2, p < 0.001) of forests were more significant and higher than those of other vegetation types, suggesting that European forests may continue to play important roles in combating climate change in the future with long-lasting carbon storage potential. These results provide the first systematic quantitative analysis of the driving force of enhanced gross carbon assimilation by European ecosystems by considering variations in leaf physiological traits with environmental adaptations. Full article
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20 pages, 13215 KiB  
Article
Impacts of Extreme Climates on Vegetation at Middle-to-High Latitudes in Asia
by Yuchen Wei, Miao Yu, Jiangfeng Wei and Botao Zhou
Remote Sens. 2023, 15(5), 1251; https://doi.org/10.3390/rs15051251 - 24 Feb 2023
Cited by 6 | Viewed by 2472
Abstract
In this study, we investigated the synchronous responses of vegetation to extreme temperatures and/or precipitation at middle-to-high latitudes in Asia using semi-monthly observations of the GIMMS and GLASS leaf area index (LAI) from 1982 to 2016. The extreme vegetation and climate states were [...] Read more.
In this study, we investigated the synchronous responses of vegetation to extreme temperatures and/or precipitation at middle-to-high latitudes in Asia using semi-monthly observations of the GIMMS and GLASS leaf area index (LAI) from 1982 to 2016. The extreme vegetation and climate states were specified using standard anomalies of the annual cycle with removed variables. The results show that the area with the maximum or minimum LAI increased or decreased in correspondence with global warming. Both the GIMMS and GLASS LAI mostly reached their maximum in spring and autumn. The GIMMS LAI mostly reached its minimum in summer, while the GLASS LAI mostly reached its minimum in late spring or late summer. The GIMMS and GLASS datasets were generally consistent regarding the vegetation responses to extreme temperatures and precipitation, especially in the areas covered by trees. Extreme cold and/or wet conditions inhibited forest growth in the area south of 60 °N, particularly from October to November. Extreme hot and/or dry conditions promoted forest growth, particularly in the central and northern parts of Siberia from August to September. However, in some arid areas of Central Asia and the Mongolian Highlands, which are mostly covered by sparse vegetation and grasses, low temperature extremes and/or strong precipitation promoted vegetation growth, while high temperature extremes and/or low precipitation had adverse effects on vegetation growth. This was more apparent in the GIMMS LAI than it was in the GLASS LAI, since the GIMMS dataset supplied more values representing extreme states of vegetation. The compound extreme of hot-and-dry and cold-and-wet climates were more frequent than the combination of cold and dry climates and hot-and-wet climates were. The overall positive response of the vegetation was superior to the negative response. The results of this study suggest that a continuous increase in vegetation density and coverage will occur over the boreal region in the future if the warming trend persists. The consequent climate feedback in this area on the regional and global scales should be afforded more attention. Full article
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20 pages, 5420 KiB  
Article
Vegetation Change and Eco-Environmental Quality Evaluation in the Loess Plateau of China from 2000 to 2020
by Shifeng Chen, Qifei Zhang, Yaning Chen, Honghua Zhou, Yanyun Xiang, Zhihui Liu and Yifeng Hou
Remote Sens. 2023, 15(2), 424; https://doi.org/10.3390/rs15020424 - 10 Jan 2023
Cited by 15 | Viewed by 2052
Abstract
Vegetation change and ecological quality of the Loess Plateau (LP) are directly related to ecological protection and high-quality development of the Yellow River Basin. Based on LP ecological zoning and multisource remote sensing data, we analyzed vegetation change and its relationship with climate, [...] Read more.
Vegetation change and ecological quality of the Loess Plateau (LP) are directly related to ecological protection and high-quality development of the Yellow River Basin. Based on LP ecological zoning and multisource remote sensing data, we analyzed vegetation change and its relationship with climate, terrestrial water storage (TWS), and land use/cover change from 2000 to 2020, using the normalized difference vegetation index (NDVI), fraction of vegetation cover (FVC), and net primary productivity (NPP). And ecological environmental quality was evaluated based on the remote sensing ecological index (RSEI). The results showed that the spatial distribution pattern of NDVI, FVC and NPP decreased from southeast to northwest in the LP as a whole. Vegetation in the LP recovered significantly, and NDVI, FVC, and NPP showed significant increases of 35.66%, 34%, and 54.69%, respectively. The average NDVI and FVC in the earth–rocky mountainous region and river valley plain region (Area D) were the highest, but the growth rate was the slowest. The average NDVI, FVC, and growth rates in the loess hilly and gully regions (Area B) were slightly higher than those in the loess sorghum gully region (Area A). The average NDVI, FVC, and NPP in the sandy land and agricultural irrigation regions (Area C) were the lowest but showed significant increase. RSEI in most LP areas changed from poor to medium, increasing by 43.45%. Precipitation is the basic factor affecting vegetation cover pattern, with the increase (40.79 mm/10a) promoting vegetation restoration in the LP. Vegetation restoration lost much TWS (−0.6 mm/month), and Area D had the highest average NDVI, FVC, and NPP but the largest TWS loss. Anthropogenic land use/cover change (LUCC) (decrease in cultivated land and unused land; increase in forest, grassland, and construction land) is the primary factor affecting LP vegetation change. This study provides a scientific reference for further vegetation restoration in the LP. Full article
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21 pages, 5735 KiB  
Article
Ecological Policies Dominated the Ecological Restoration over the Core Regions of Kubuqi Desert in Recent Decades
by Min Ren, Wenjiang Chen and Haibo Wang
Remote Sens. 2022, 14(20), 5243; https://doi.org/10.3390/rs14205243 - 20 Oct 2022
Cited by 2 | Viewed by 1480
Abstract
Climate change and human activities significantly affected environmental changes in drylands. However, the relative roles remain unclear regarding these factors’ effects on environment changes in drylands. Herein, we analyzed vegetation change trends using remote-sensing datasets to determine the interactions of vegetation, climate, and [...] Read more.
Climate change and human activities significantly affected environmental changes in drylands. However, the relative roles remain unclear regarding these factors’ effects on environment changes in drylands. Herein, we analyzed vegetation change trends using remote-sensing datasets to determine the interactions of vegetation, climate, and anthropogenic activities in an arid region of China, Kubuqi Desert. Our study showed that 67.64% of the pixels of fractional vegetation coverage (FVC) increased in 2020 in comparison with those of 1986. The FVC exhibited a significant greening trend (0.0011/yr, p < 0.05) in 1986–2020 as a whole. This greening trend revealed two distinct periods separated by a turning point in 2001. There was no clear trend of FVC before 2001, and then there was a dramatically greening trend since 2001 in most regions of the study area. The increasing rate (0.0036/yr) in the later period was three times higher than the entire period. The accelerated increasing trend was due to the variable compound effects of climate and human activities. The correlation between FVC and precipitation was mainly positive, which outweighs the significantly negative correlation between vegetation and temperature. However, both climatic factors cannot well explain the trends of vegetation dynamics, implying a possible role for human activities. Generally, climate change and anthropogenic activities contributed 42.15% and 57.85% to the overall vegetation variations in 1986–2020. Specifically, the relative role of the two factors was vastly different in two distinct periods. Climate change led the dominant roles (58.68%) in the vegetation variations in 1986–2001, while anthropogenic activities dominated (86.79%) in driving vegetation recovery in the period after 2001. Due to the massive ecological conservation programs such as the Grain for Green Project launched in 2001, substantial deserts have been transformed into grasslands and forests. This analysis highlights the ecological policies largely responsible for vegetation restoration and provides references for ecological protection and sustainable development in eco-fragile ecosystems. Full article
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20 pages, 6711 KiB  
Technical Note
Landscape Ecological Risk Assessment and Analysis of Influencing Factors in Selenga River Basin
by Wangping Li, Qingrun Lin, Junming Hao, Xiaodong Wu, Zhaoye Zhou, Peiqing Lou and Yadong Liu
Remote Sens. 2023, 15(17), 4262; https://doi.org/10.3390/rs15174262 - 30 Aug 2023
Cited by 2 | Viewed by 946
Abstract
Land degradation under the influence of global warming and ecological environmental destruction due to poor land management is the main challenge facing the Mongolian Plateau, and its future ecological risk change trends and drivers are also unclear. Therefore, to address the context relevant [...] Read more.
Land degradation under the influence of global warming and ecological environmental destruction due to poor land management is the main challenge facing the Mongolian Plateau, and its future ecological risk change trends and drivers are also unclear. Therefore, to address the context relevant to this challenge, planning based on measured information from land use patterns is required. Based on land use and land cover (LULC), this study evaluates the landscape ecological risk (LER) of the Selenga River Basin by calculating the landscape pattern index. The spatiotemporal pattern and influencing factors of landscape ecological risk in the Selenga River Basin from 1990 to 2040 were analyzed. According to the results of LULC analysis, forest and grassland were the primary land use types in the Selenga River Basin. The built area, forest, and cropland showed an increasing trend, while the grassland area showed a fluctuating decreasing trend. From 1990 to 2010, the comprehensive land use dynamic degree showed a trend of rising first and then falling, specifically from 0.13% in 1990 to 0.29% in 2010, and will drop to 0.06% by 2040, indicating that the range of land use change is becoming more and more stable. The landscape ecological risk assessment shows a distribution pattern of “low at the edge and high in the middle”. The landscape ecological risk index (LER) first increases and then decreases, with the peak value in 2010 (0.085). By calculating the spatial aggregation of LER and the partial correlation with climate, we found that the Moran’s I index showed an “anti-V”-shaped change trend from 1990 to 2040, and the average landscape ecological risk presents positive spatial correlation, primarily with high-value aggregation, and peaked in 2010. Precipitation had a negative correlation with landscape ecological risk controlling for temperature, while there was a positive relationship between temperature and landscape ecological risk under the influence of controlling precipitation. This study provides a scientific basis for LULC planning in the Selenga River Basin, and is of great significance for maintaining the ecological security of the Mongolian Plateau. Full article
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