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Examining the spatially varying effects of climatic and environmental pollution factors on the NDVI based on their spatially heterogeneous relationships in Bohai Rim, China

•Slight degradation, but increased vegetation and coverage coexist in the Bohai Rim.•In coastal wetlands slight and severe degradation were observed from 2002 to 2017.•Temperature, Particulate Matter and Precipitation have an intense link with NDVI.•They also have an influence on moderately and thic...

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Published in:Journal of hydrology (Amsterdam) 2023-02, Vol.617, p.128815, Article 128815
Main Authors: Sawut, Rukeya, Li, Ying, Kasimu, Alimujiang, Ablat, Xarapat
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description •Slight degradation, but increased vegetation and coverage coexist in the Bohai Rim.•In coastal wetlands slight and severe degradation were observed from 2002 to 2017.•Temperature, Particulate Matter and Precipitation have an intense link with NDVI.•They also have an influence on moderately and thickly covered vegetated areas. Variations in vegetation patterns can provide a scientific basis for assessing environmental quality and monitoring ecosystem dynamics under environmental pollution and global warming conditions. To evaluate the ecological environment of the Bohai Rim, Theil-Sen trend analysis, the Mann-Kendall (MK) test and the Hurst exponent were applied to analyze the patterns of variation in the vegetation coverage, climate factors (temperature, precipitation, relative humidity) and particulate matter and to assess sustainability in the near future. Fine particulate matter, also known as PM2.5 (PM2.5,μg/m3), refers to atmospheric particles with a diameter of less than or equal to 2.5 μm, also known as respirable particles. These not only lead to a decline in atmospheric visibility but also increase human mortality and respiratory disease rates. Given the spatiotemporal nonstationarity of climate factors and PM2.5, geographically weighted regression (GWR) was applied to confirm the spatially heterogeneous relationship among the vegetation coverage, climate factors and PM2.5. The vegetation coverage in the Bohai Rim was mostly comprised of slightly degraded areas, followed by unchanged areas, improved areas, and severely degraded areas from 2002 to 2017. The slightly degraded area accounted for 30.9 %, while 15.8 % of the area remained at the same level during the period, and 16.8 % improved. Slight degradation was mainly observed on agricultural lands and forests, whereas severely degraded areas were distributed among grasslands and wetlands. Approximately 20.9 % of the improved area, most of which was agricultural lands, forests and grasslands, continued to improve. Seasonal trends indicated that a large proportion of the areas remained unchanged or were slightly degraded from autumn to spring, whereas areas improved from spring to autumn. During the winter, slightly and severely degraded areas continuously expanded. GWR indicated that temperature, PM2.5, and precipitation displayed a significant heterogeneous spatial relationship with the vegetation coverage and had an obvious influence on the medium, high and low vegetation cover areas. When co
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Variations in vegetation patterns can provide a scientific basis for assessing environmental quality and monitoring ecosystem dynamics under environmental pollution and global warming conditions. To evaluate the ecological environment of the Bohai Rim, Theil-Sen trend analysis, the Mann-Kendall (MK) test and the Hurst exponent were applied to analyze the patterns of variation in the vegetation coverage, climate factors (temperature, precipitation, relative humidity) and particulate matter and to assess sustainability in the near future. Fine particulate matter, also known as PM2.5 (PM2.5,μg/m3), refers to atmospheric particles with a diameter of less than or equal to 2.5 μm, also known as respirable particles. These not only lead to a decline in atmospheric visibility but also increase human mortality and respiratory disease rates. Given the spatiotemporal nonstationarity of climate factors and PM2.5, geographically weighted regression (GWR) was applied to confirm the spatially heterogeneous relationship among the vegetation coverage, climate factors and PM2.5. The vegetation coverage in the Bohai Rim was mostly comprised of slightly degraded areas, followed by unchanged areas, improved areas, and severely degraded areas from 2002 to 2017. The slightly degraded area accounted for 30.9 %, while 15.8 % of the area remained at the same level during the period, and 16.8 % improved. Slight degradation was mainly observed on agricultural lands and forests, whereas severely degraded areas were distributed among grasslands and wetlands. Approximately 20.9 % of the improved area, most of which was agricultural lands, forests and grasslands, continued to improve. Seasonal trends indicated that a large proportion of the areas remained unchanged or were slightly degraded from autumn to spring, whereas areas improved from spring to autumn. During the winter, slightly and severely degraded areas continuously expanded. GWR indicated that temperature, PM2.5, and precipitation displayed a significant heterogeneous spatial relationship with the vegetation coverage and had an obvious influence on the medium, high and low vegetation cover areas. When considering the joint influence of climate factors and PM2.5 on the vegetation coverage, the model accuracy was not high for the high and medium vegetation cover areas. In the Bohai region, human activities significantly affect coastal areas. 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Variations in vegetation patterns can provide a scientific basis for assessing environmental quality and monitoring ecosystem dynamics under environmental pollution and global warming conditions. To evaluate the ecological environment of the Bohai Rim, Theil-Sen trend analysis, the Mann-Kendall (MK) test and the Hurst exponent were applied to analyze the patterns of variation in the vegetation coverage, climate factors (temperature, precipitation, relative humidity) and particulate matter and to assess sustainability in the near future. Fine particulate matter, also known as PM2.5 (PM2.5,μg/m3), refers to atmospheric particles with a diameter of less than or equal to 2.5 μm, also known as respirable particles. These not only lead to a decline in atmospheric visibility but also increase human mortality and respiratory disease rates. Given the spatiotemporal nonstationarity of climate factors and PM2.5, geographically weighted regression (GWR) was applied to confirm the spatially heterogeneous relationship among the vegetation coverage, climate factors and PM2.5. The vegetation coverage in the Bohai Rim was mostly comprised of slightly degraded areas, followed by unchanged areas, improved areas, and severely degraded areas from 2002 to 2017. The slightly degraded area accounted for 30.9 %, while 15.8 % of the area remained at the same level during the period, and 16.8 % improved. Slight degradation was mainly observed on agricultural lands and forests, whereas severely degraded areas were distributed among grasslands and wetlands. Approximately 20.9 % of the improved area, most of which was agricultural lands, forests and grasslands, continued to improve. Seasonal trends indicated that a large proportion of the areas remained unchanged or were slightly degraded from autumn to spring, whereas areas improved from spring to autumn. During the winter, slightly and severely degraded areas continuously expanded. GWR indicated that temperature, PM2.5, and precipitation displayed a significant heterogeneous spatial relationship with the vegetation coverage and had an obvious influence on the medium, high and low vegetation cover areas. When considering the joint influence of climate factors and PM2.5 on the vegetation coverage, the model accuracy was not high for the high and medium vegetation cover areas. In the Bohai region, human activities significantly affect coastal areas. These results can support sustainable coastal ecosystem management, relevant management measures and ecological development plans.</description><subject>Bohai region</subject><subject>Climate factors</subject><subject>Geographically weighted regression (GWR model)</subject><subject>Particulate matter (PM2.5)</subject><subject>Spatiotemporal heterogeneity</subject><subject>Theil-Sen+Mann-Kendall analysis (heil–Sen+MK analysis)</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkM9KAzEQxoMoWKuPIOQB3Jpk_-YkWqsWioKo15BNZrtZ0qQka7Hv5EO6tT14cy4D8818M_ND6JKSCSW0uO4mXbvVwdsJI4xNKKsqmh-hEa1KnrCSlMdoRAYloQXPTtFZjB0ZIk2zEfqefcmVccYtcd8CjmvZG2ntFm9k2O6q0DSg-oh9g5U1q0FWWDqNwW1M8G4FrpcWr721n73xDjdS9T4M_e7X8Pn-Y45rGUEfKib8WdJCD8EvwYH_jDiAlTuP2Jp1xMbhO99Kg1_N6gpPW-PkOTpppI1wcchj9P4we5s-JYuXx_n0dpGolPA-UVJJUIzWnORlUdS8Al7XlOUk1QzSWvOMVbxmRFcZFBnJGdUZJ0VFpKqgydIxyve-KvgYAzRiHYbXw1ZQInbIRScOyMUOudgjH-Zu9nMwHLcxEERUBpwCbcIAUWhv_nH4Aby_kYA</recordid><startdate>202302</startdate><enddate>202302</enddate><creator>Sawut, Rukeya</creator><creator>Li, Ying</creator><creator>Kasimu, Alimujiang</creator><creator>Ablat, Xarapat</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>202302</creationdate><title>Examining the spatially varying effects of climatic and environmental pollution factors on the NDVI based on their spatially heterogeneous relationships in Bohai Rim, China</title><author>Sawut, Rukeya ; Li, Ying ; Kasimu, Alimujiang ; Ablat, Xarapat</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c309t-cacaec21b905766b98e9bb12503d2e3bd94289b20d84e640521d490680ac8ef43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Bohai region</topic><topic>Climate factors</topic><topic>Geographically weighted regression (GWR model)</topic><topic>Particulate matter (PM2.5)</topic><topic>Spatiotemporal heterogeneity</topic><topic>Theil-Sen+Mann-Kendall analysis (heil–Sen+MK analysis)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sawut, Rukeya</creatorcontrib><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Kasimu, Alimujiang</creatorcontrib><creatorcontrib>Ablat, Xarapat</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sawut, Rukeya</au><au>Li, Ying</au><au>Kasimu, Alimujiang</au><au>Ablat, Xarapat</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Examining the spatially varying effects of climatic and environmental pollution factors on the NDVI based on their spatially heterogeneous relationships in Bohai Rim, China</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2023-02</date><risdate>2023</risdate><volume>617</volume><spage>128815</spage><pages>128815-</pages><artnum>128815</artnum><issn>0022-1694</issn><eissn>1879-2707</eissn><abstract>•Slight degradation, but increased vegetation and coverage coexist in the Bohai Rim.•In coastal wetlands slight and severe degradation were observed from 2002 to 2017.•Temperature, Particulate Matter and Precipitation have an intense link with NDVI.•They also have an influence on moderately and thickly covered vegetated areas. Variations in vegetation patterns can provide a scientific basis for assessing environmental quality and monitoring ecosystem dynamics under environmental pollution and global warming conditions. To evaluate the ecological environment of the Bohai Rim, Theil-Sen trend analysis, the Mann-Kendall (MK) test and the Hurst exponent were applied to analyze the patterns of variation in the vegetation coverage, climate factors (temperature, precipitation, relative humidity) and particulate matter and to assess sustainability in the near future. Fine particulate matter, also known as PM2.5 (PM2.5,μg/m3), refers to atmospheric particles with a diameter of less than or equal to 2.5 μm, also known as respirable particles. These not only lead to a decline in atmospheric visibility but also increase human mortality and respiratory disease rates. Given the spatiotemporal nonstationarity of climate factors and PM2.5, geographically weighted regression (GWR) was applied to confirm the spatially heterogeneous relationship among the vegetation coverage, climate factors and PM2.5. The vegetation coverage in the Bohai Rim was mostly comprised of slightly degraded areas, followed by unchanged areas, improved areas, and severely degraded areas from 2002 to 2017. The slightly degraded area accounted for 30.9 %, while 15.8 % of the area remained at the same level during the period, and 16.8 % improved. Slight degradation was mainly observed on agricultural lands and forests, whereas severely degraded areas were distributed among grasslands and wetlands. Approximately 20.9 % of the improved area, most of which was agricultural lands, forests and grasslands, continued to improve. Seasonal trends indicated that a large proportion of the areas remained unchanged or were slightly degraded from autumn to spring, whereas areas improved from spring to autumn. During the winter, slightly and severely degraded areas continuously expanded. GWR indicated that temperature, PM2.5, and precipitation displayed a significant heterogeneous spatial relationship with the vegetation coverage and had an obvious influence on the medium, high and low vegetation cover areas. When considering the joint influence of climate factors and PM2.5 on the vegetation coverage, the model accuracy was not high for the high and medium vegetation cover areas. In the Bohai region, human activities significantly affect coastal areas. These results can support sustainable coastal ecosystem management, relevant management measures and ecological development plans.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2022.128815</doi></addata></record>
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subjects Bohai region
Climate factors
Geographically weighted regression (GWR model)
Particulate matter (PM2.5)
Spatiotemporal heterogeneity
Theil-Sen+Mann-Kendall analysis (heil–Sen+MK analysis)
title Examining the spatially varying effects of climatic and environmental pollution factors on the NDVI based on their spatially heterogeneous relationships in Bohai Rim, China
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