Ecological Environment Evaluation of Forest Ecosystem Nature Reserves Using an Unweighted Cloud Model

Xiang, Mengshi; Lin, Xiaonan; Yang, Xuesong; Zhang, Shanghong

doi:10.3390/w12071905

Cited by 8 publications

(5 citation statements)

References 18 publications

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“…Scientific and objective evaluation of ecological environment quality is particularly important, which can provide a strong scientific basis for monitoring, protecting and governing the ecological environment [1][2][3] . A variety of ecological environment assessment methods have been used to monitor and assess the current state and changes in the quality of the ecological environment, among which the establishment of models such as hierarchical analysis and "pressure-state-response" (PSR) have problems such as subjectivity, difficulty in collecting indicator data, and limited coverage 4,5 . In recent years, with the continuous development of satellite remote sensing technology and the accumulation of massive data, it has been widely used in ecological environment quality analysis and assessment due to its many advantages such as speed, timeliness, objectivity and wide spatial coverage 6 .…”

Section: Rsei-based Monitoring Of Ecological Quality and Analysis Of ...mentioning

confidence: 99%

RSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin

Ge,

Qian,

Zhang

et al. 2024

Preprint

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The Daling River basin is an important ecological functional area in the western region of Liaoning, and the monitoring of the ecological environment quality and the analysis of the factors in the basin are of great significance for the protection of the ecological environment and the improvement of the quality of the economy. In this paper, based on the three periods of remote sensing images in 1995, 2010 and 2020 as the basic data, we use platforms and technical means such as RS and GIS to decipher and extract the land use information of the three periods, establish the transfer matrix of land use types, and collect the data to extract the corresponding four remote sensing indices of NDVI, LST, WET and NDBSI, and construct the remote sensing eco-index of Daling River Basin (RSEI) model. Based on the land use change, combined with the trend of remote sensing ecological index (RSEI) of Daling River Basin, so as to achieve the purpose of rapid and efficient dynamic monitoring of ecological quality of Daling River Basin from 1995 to 2020. The geodetector model was applied to systematically evaluate the drivers of ecological quality in the basin, providing a scientific basis for the implementation of further ecological environmental protection measures.

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Section: Rsei-based Monitoring Of Ecological Quality and Analysis Of ...mentioning

confidence: 99%

RSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin

Ge,

Qian,

Zhang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Scientific and objective evaluation of ecological environment quality is particularly important, which can provide a strong scientific basis for monitoring, protecting and governing the ecological environment 1 – 3 . A variety of ecological environment assessment methods have been used to monitor and assess the current state and changes in the quality of the ecological environment, among which the establishment of models such as hierarchical analysis and "pressure-state-response" (PSR) have problems such as subjectivity, difficulty in collecting indicator data, and limited coverage 4 , 5 . In recent years, with the continuous development of satellite remote sensing technology and the accumulation of massive data, it has been widely used in ecological environment quality analysis and assessment due to its many advantages such as speed, timeliness, objectivity and wide spatial coverage 6 .…”

Section: Introductionmentioning

confidence: 99%

IRSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin

Ge,

Qian,

Zhang

et al. 2024

Sci Rep

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The Daling River Basin is an important ecological functional area in the western region of Liaoning with outstanding environmental problems. The monitoring of ecological and environmental quality in the basin and the analysis of driving factors are of great importance for the protection of the ecological environment and the improvement of economic quality. In this paper, the three periods of Landsat remote sensing images in 1995, 2010 and 2020 are used as the basic data, and platforms and technical means such as RS and GIS are used to decipher and extract the three periods of land use information, and to construct the land use type transfer matrix. The remote sensing ecological index (RSEI) was improved, and the principal component analysis method was applied to construct the improved remote sensing ecological index (IRSEI) model based on the greenness (NDVI), moisture (WET), heat (LST) and new dryness (N-NDBSI), so as to realize the dynamic monitoring of ecological and environmental quality in the study area. Based on the land use change, combined with the trend of improved remote sensing ecological index (IRSEI) of Daling River Basin, thus achieving the purpose of rapid and efficient dynamic monitoring of ecological quality of Daling River Basin from 1995 to 2020. A geoprobe model was then used to systematically assess the drivers of ecological quality in the catchment. The results show that the improved remote sensing ecological index (IRSEI) can efficiently and accurately obtain the spatial distribution pattern and temporal variation trend of IRSEI in the study area, which is more in line with the characteristics of indicators in this study area. The IRSEI in the study area showed an increasing trend from 1995 to 2020, from 0.4794 to 0.5615, and the proportion of benign ecological classes increased year by year during the period. Among the evaluation indicators, NDVI and N-NDBSI are the main factors affecting the environmental and ecological quality of the Daling River Basin, and the increase of vegetation cover, climate regulation and human activities have obvious promoting effects on the improvement of the ecological environment of the Daling River Basin. This study provides a scientific theoretical basis for the implementation of further ecological environmental protection measures.

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“…According to the consensus on the ecological environment in previous studies and the characteristics of the study area. Literature [18] established a quantitative evaluation index system for the comprehensive ecological environment of forest ecosystem nature reserve based on water, air, soil and biological environment, constructed a weightless cloud model, and provided a weightless evaluation mechanism. The results showed that the results of this study can provide theoretical support for the evaluation of forest ecosystem nature reserves and general evaluation when the weight is difficult to determine or uncertain.…”

Section: Introductionmentioning

confidence: 99%

Development of ecological management system for planted forest based on ELM deep learning algorithm

Wang¹

2023

3C Empresa

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Plantations play a central and lever role in maintaining the ecological balance of the earth, maintaining the overall function of the terrestrial ecosystem, and promoting the coordinated development of economic society and ecological construction. In order to strengthen the ecological management of plantation forests and improve the ecological level of forest region, the C/S framework is taken as the basic structure, and the programming mode of business model-user interface controller is used, on J2EE platform. The ecological management system of a planted forest is constructed by the evaluation module, the principal component comprehensive analysis module of ecological function value and the demand prediction module of planted forest based on extreme learning machine and deep learning algorithm, and runs under the support of windows system, oracle 15G and above database software. The indexes and factors affecting the ecological function of plantation forests were evaluated and analyzed, and the final management decision was given by the prediction module. The results showed that the plant density significantly affected plant biomass, organic carbon storage, water content and nutrient accumulation, and the comprehensive evaluation indexes of four ecological functions increased from 32.69, 31.84, 33.71 and 35.46 to 86.18, 89.46, 89.83 and 88.76, respectively. Although the degree of influence of the system on lemon strip plants, herbaceous plants, surface litter and soil varies, it still has good feasibility, effectiveness and practicality, and can assist the scientific ecological management of artificial plantation forests.

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Ecological Environment Evaluation of Forest Ecosystem Nature Reserves Using an Unweighted Cloud Model

Cited by 8 publications

References 18 publications

RSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin

RSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin

IRSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin

Development of ecological management system for planted forest based on ELM deep learning algorithm

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