Eco-Environment Evaluation of Grassland Based on Remote Sensing Ecological Index:  A Case in Hulunbuir Area, China

Hui, Jiawei; Bai, Zhaoguang; Ye, Baoying

doi:10.4236/jcc.2021.96012

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…and effectiveness of the ecological index for the assessment of ecological quality. This finding is in line with the research by (Hui et al 2021), which states that the ecological index has a significant positive correlation with ecological quality.…”

Section: Capabilities and Performance Of The Ecological Index Integra...supporting

confidence: 92%

Assessment Of Remote Sensing Approach For Urban Ecological Quality Evaluation In Pekanbaru City, Riau Province Indonesia

Giofandi,

Syahzaqi,

Sekarjati

et al. 2024

GES

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There are obstacles in estimating environmental dynamics behind its convenience, beginning with the development of effective policies for sustainable urban development. The objectives of this research were to comprehend the ability and performance of ecological indices integration and to identify the spatial distribution of changes from 2018 to 2021 in Pekanbaru City, Riau province, Indonesia. This study employed remote sensing data to create ecological parameters including the build-up index, vegetation index, soil index, and moisture index, as well as principal component analysis to generate ecological index integration. The findings indicate a correlation of over 90% among these parameters from 2018 to 2021. Overall, there has been a significant decrease in the ecological quality index’s high-quality categories, such as good and excellent, covering a total of 19.6% over 127 km². Conversely, the poor ecological quality category increased to 2.2%, encompassing an area of 15 km², up from the initial 21.2% covering 122 km². Additionally, the fair and moderate categories also experienced increases of 4% and 13.4%, respectively, reaching 28 km² and 84 km². The study area’s ecological quality is largely affected by increased anthropogenic activities, leading to a drastic decrease in the presence of ecological quality in the good and excellent categories. The importance of spatial planning is emphasized to incorporate aspects of ecological assessment rather than solely focusing on increasing economic activity. This outcome can be used to respond to the concept of sustainable development by caring for the ecological environment, particularly in urban areas, and mitigating ecological damage.

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Section: Capabilities and Performance Of The Ecological Index Integra...supporting

confidence: 92%

Assessment Of Remote Sensing Approach For Urban Ecological Quality Evaluation In Pekanbaru City, Riau Province Indonesia

Giofandi,

Syahzaqi,

Sekarjati

et al. 2024

GES

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“…Fan et al [ 33 ] comprehensively assessed the quality of the eco-environment in the eastern coastal areas of China by constructing RSEIs. Other researchers have also evaluated RSEI remote sensing indices in different regions such as typical basins, comprehensive land consolidation areas, and grasslands [ 34 , 35 , 36 ].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Zhang

Feng

Zhang

et al. 2022

IJERPH

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Using the Google Earth Engine (GEE) platform, Moderate-resolution image spectroradiometer (MODIS) data of the Weihe River Basin from 2001 to 2021 were acquired, four ecological indicators, namely, greenness, wetness, heat, and dryness, were extracted, and the remote sensing ecological index (RSEI) was constructed through principal component analysis. In addition, the geographic detectors and a multi-scale geographic weighted regression model (MGWR) were used to identify the main driving factors of RSEI changes and capture the differences in spatial changes from different perspectives using multiple indicators. The results show that (1) the quality of the eco-environment in the Weihe River basin improved as a whole from 2001 to 2021, and the RSEI increased from 0.376 to 0.414. In terms of the RSEI grade, the medium RSEI and high RSEI areas increased significantly and the growth rate increased significantly, reaching 26.42% and 27.70%, respectively. (2) Spatially, the quality of the eco-environment in the Weihe River Basin exhibited a spatial distribution pattern that was high in the south and low in the north, among which the quality of the eco-environment in the Weihe River Basin in northern Shaanxi and northwestern Ningxia and Gansu was relatively low. In addition, during the study period, the RSEI of the Qinling Mountains in the southern part of the Weihe River Basin and the Jinghe River and Luohe River areas improved significantly. The urban area on the Guanzhong Plain in the Weihe River Basin experienced rapid economic growth, and urban expansion led to a significant decrease in the quality of the eco-environment. (3) The eco-environment quality in the Weihe River Basin is the result of the interaction of natural, anthropogenic, and landscape pattern factors. All of the interactions between the influencing factors had a stronger influence than those of the individual factors. There were significant differences between the individual drivers and the spatial variation in RSEI, suggesting that different factors dominate the variation in RSEI in different regions, and zonal management is crucial to achieving sustainable management of RSEI. The study shows that to improve the eco-environment quality of the Weihe River Basin, it is necessary to further strengthen ecological protection projects, reasonably allocate landscape elements, and strengthen the resistance and resilience of the ecosystem.

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“…RSEI is a composite index based on Remote Sensing data and principal component analysis (PCA). It includes four indicatorsgreenness, wetness, heat, and dryness, which are related to physiological factors of climate and land surface that are perceived by humans and are closely linked to the Environment Ecological [23]. Besides, applying principal component analysis (PCA) helps eliminate subjective human analysis factors in determining weights for data [24].…”

Section: Remote Sensing Ecological Index Estimationmentioning

confidence: 99%

Environmental Quality Monitoring Using Remote Sensing Ecological Index (RSEI) in Can Tho City, Vietnam.

Diep,

Nguyen,

Hieu

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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The significance of green spaces and ecological priorities in urban areas–two major concepts and advancements in Vietnam's recent urban growth, particularly in Can Tho City–is addressed by urban planning. An ecological assessment necessitates participating in urban planning and the eco-environment protection system. This study evaluated the change in the ecological quality of Can Tho City in the period 2015 - 2020 by approaching remote sensing indicators and statistical methods. Using Landsat 8 OLI satellite data from 2015 to 2020, four indicators were calculated in this study: heat (LST), dryness (NDBSI), wetness (WET), and greenness (NDVI). These indices were then applied using the Principal Component Analysis (PCA) method to estimate the Remote Sensing Ecological Index (RSEI). According to the data, the RSEI mean was 3.66 in 2015 and 3.60 in 2020. In 2015, areas with good and very good ecological quality (EQ) accounted for 88.78% of the total natural area; by 2020, it was 84.75%. The areas with low quality increased from 1.97% in 2015 to 3.49% in 2020. This indicates a decreasing trend in ecological quality within the area. The declining trend in urban ecological quality (UEQ) at Can Tho City between 2015 and 2020 can be objectively reflected by the RSEI and the shifting proportions of the ecological level. The results of RSEI provide fundamental data on the ecological quality of the urban environment to support policymakers, managers, and authorities in implementing and developing sustainable approaches to urban ecological conservation and environmental quality preservation.

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Eco-Environment Evaluation of Grassland Based on Remote Sensing Ecological Index: A Case in Hulunbuir Area, China

Cited by 7 publications

References 23 publications

Assessment Of Remote Sensing Approach For Urban Ecological Quality Evaluation In Pekanbaru City, Riau Province Indonesia

Assessment Of Remote Sensing Approach For Urban Ecological Quality Evaluation In Pekanbaru City, Riau Province Indonesia

Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Environmental Quality Monitoring Using Remote Sensing Ecological Index (RSEI) in Can Tho City, Vietnam.

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