Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134334
Zhen Li
{"title":"An evaluation method of urban green space landscape spatial structure based on entropy weight method","authors":"Zhen Li","doi":"10.1504/ijetm.2023.134334","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134334","url":null,"abstract":"","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135053864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134324
Yaqi Shi
In order to overcome the problem of low accuracy of monitoring threshold extraction and pollution range monitoring in traditional pollution range monitoring methods, a new pollution range monitoring method of scenic spots based on two-dimensional threshold method is proposed in this paper. Firstly, collect satellite remote sensing data of the pollution range of scenic spots. Secondly, based on the collected data, the two-dimensional threshold method is used to extract the pollution range change threshold of scenic spots. Finally, according to the threshold extraction results, the weight coefficient of pollution range change is calculated, and the pollution range monitoring function is constructed. The output result of the function is the final monitoring result. The experimental results show that compared with the traditional pollution range monitoring method, this method can accurately monitor the pollution range of scenic spots, and the monitoring accuracy is always maintained at more than 94%.
{"title":"Study on monitoring method of pollution range in scenic spots based on two-dimensional threshold method","authors":"Yaqi Shi","doi":"10.1504/ijetm.2023.134324","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134324","url":null,"abstract":"In order to overcome the problem of low accuracy of monitoring threshold extraction and pollution range monitoring in traditional pollution range monitoring methods, a new pollution range monitoring method of scenic spots based on two-dimensional threshold method is proposed in this paper. Firstly, collect satellite remote sensing data of the pollution range of scenic spots. Secondly, based on the collected data, the two-dimensional threshold method is used to extract the pollution range change threshold of scenic spots. Finally, according to the threshold extraction results, the weight coefficient of pollution range change is calculated, and the pollution range monitoring function is constructed. The output result of the function is the final monitoring result. The experimental results show that compared with the traditional pollution range monitoring method, this method can accurately monitor the pollution range of scenic spots, and the monitoring accuracy is always maintained at more than 94%.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135057177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134333
Jing Yang
{"title":"The simulation of ecological spatial pattern evolution of tourist attractions based on remote sensing data","authors":"Jing Yang","doi":"10.1504/ijetm.2023.134333","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134333","url":null,"abstract":"","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134322
H.N. Mahendra, S. Mallikarjunaswamy
In the present work, change detection in land use and land cover (LULC) area of Chikkamagaluru district were assessed using remote sensing data and supervised classifier. Chikkamagaluru district is known for the green cover; therefore an analysis of the land use land cover of the district is the main objective of this work. The change detection of an entire Chikkamagaluru district has been carried out for the period between 2017 and 2021 by using Sentinel-2 multispectral remote sensing data. Supervised classification-based support vector machines (SVM) have been applied to assess the LULC of the study area. An experimental result shows the positive changes in vegetation cover, water bodies, and negative changes observed in bare ground and rangeland. Overall classification accuracy of the SVM was estimated to be 86.30% for 2017 and 85.36% for 2021. The performance of SVM is also compared with the other supervised classifiers such as neural networks, maximum likelihood classifier (MLC), minimum-distance-to-means, and Mahalanobis distance. The comparison results show that SVMs provide better classification results as compared to other supervised classifiers.
{"title":"An analysis of change detection in land use land cover area of remotely sensed data using supervised classifier","authors":"H.N. Mahendra, S. Mallikarjunaswamy","doi":"10.1504/ijetm.2023.134322","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134322","url":null,"abstract":"In the present work, change detection in land use and land cover (LULC) area of Chikkamagaluru district were assessed using remote sensing data and supervised classifier. Chikkamagaluru district is known for the green cover; therefore an analysis of the land use land cover of the district is the main objective of this work. The change detection of an entire Chikkamagaluru district has been carried out for the period between 2017 and 2021 by using Sentinel-2 multispectral remote sensing data. Supervised classification-based support vector machines (SVM) have been applied to assess the LULC of the study area. An experimental result shows the positive changes in vegetation cover, water bodies, and negative changes observed in bare ground and rangeland. Overall classification accuracy of the SVM was estimated to be 86.30% for 2017 and 85.36% for 2021. The performance of SVM is also compared with the other supervised classifiers such as neural networks, maximum likelihood classifier (MLC), minimum-distance-to-means, and Mahalanobis distance. The comparison results show that SVMs provide better classification results as compared to other supervised classifiers.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134326
Xiang Huang, uzhen Li
{"title":"Location method of garden air pollution source based on gradient lifting regression tree algorithm","authors":"Xiang Huang, uzhen Li","doi":"10.1504/ijetm.2023.134326","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134326","url":null,"abstract":"","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.127339
Jiong Li
In order to solve the problem of poor accuracy of traditional ecological vulnerability assessment methods, an ecological vulnerability assessment method of scenic spots based on entropy weight TOPSIS model is proposed. Firstly, it analyses the natural environment and conditions of the scenic spot, determines the ecological vulnerability evaluation index of the scenic spot, and constructs the evaluation index system through spatial principal component analysis. Then, the evaluation indexes are standardised and graded according to the ecological vulnerability index of scenic spots. Finally, the weight of ecological vulnerability index is calculated by using entropy weight TOPSIS model, and the ecological vulnerability index is determined. After building the ecological vulnerability assessment model of scenic spots, input the ecological vulnerability indicators into the model and output the assessment results. The results show that the accuracy of this method is as high as 0.98.
{"title":"Evaluation method of ecological vulnerability of scenic spots based on entropy weight TOPSIS model","authors":"Jiong Li","doi":"10.1504/ijetm.2023.127339","DOIUrl":"https://doi.org/10.1504/ijetm.2023.127339","url":null,"abstract":"In order to solve the problem of poor accuracy of traditional ecological vulnerability assessment methods, an ecological vulnerability assessment method of scenic spots based on entropy weight TOPSIS model is proposed. Firstly, it analyses the natural environment and conditions of the scenic spot, determines the ecological vulnerability evaluation index of the scenic spot, and constructs the evaluation index system through spatial principal component analysis. Then, the evaluation indexes are standardised and graded according to the ecological vulnerability index of scenic spots. Finally, the weight of ecological vulnerability index is calculated by using entropy weight TOPSIS model, and the ecological vulnerability index is determined. After building the ecological vulnerability assessment model of scenic spots, input the ecological vulnerability indicators into the model and output the assessment results. The results show that the accuracy of this method is as high as 0.98.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136229296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134325
Renzhong Jin
In order to overcome many problems existing in traditional evaluation methods, such as the low accuracy of the evaluation of ecological health of tourist attractions, an ecological health evaluation method of tourist attractions based on gradient boosting decision tree was proposed. The data collection framework of tourist attractions based on UAV low-altitude remote sensing is designed, the ecological health evaluation index system of tourist attractions is constructed, and information entropy and analytic hierarchy process were used to determine the combination weight. The gradient boosting decision tree algorithm is used to calculate the ecological health of tourist attractions, and multiple support vector machines are used to construct multi-classifiers to achieve ecological health evaluation. The experimental results show that the average data acquisition time of the method in this paper is 0.76 s, the error rate of the index weight calculation is between -1% and 2%, and the average evaluation accuracy rate is 97.2%.
{"title":"An ecological health evaluation of tourist attractions based on gradient boosting decision tree","authors":"Renzhong Jin","doi":"10.1504/ijetm.2023.134325","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134325","url":null,"abstract":"In order to overcome many problems existing in traditional evaluation methods, such as the low accuracy of the evaluation of ecological health of tourist attractions, an ecological health evaluation method of tourist attractions based on gradient boosting decision tree was proposed. The data collection framework of tourist attractions based on UAV low-altitude remote sensing is designed, the ecological health evaluation index system of tourist attractions is constructed, and information entropy and analytic hierarchy process were used to determine the combination weight. The gradient boosting decision tree algorithm is used to calculate the ecological health of tourist attractions, and multiple support vector machines are used to construct multi-classifiers to achieve ecological health evaluation. The experimental results show that the average data acquisition time of the method in this paper is 0.76 s, the error rate of the index weight calculation is between -1% and 2%, and the average evaluation accuracy rate is 97.2%.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134328
Lede Niu, Lifang Zhou, Jingzhi Lin, Anlin Li, Yan Zhou
In order to reduce the pressure of urban construction land demand and improve the level of urban land use, this paper studies the temporal and spatial evolution of the construction land structure in the central Yunnan urban agglomeration. Firstly, ArcGIS 10.3 software was used to extract the construction land quantity of the urban agglomeration in central Yunnan, and then the standard deviation ellipse, standard distance and gravity centre migration model were used to analyse its spatial characteristics. Experiments show that the northeast direction is the most prominent direction of construction land expansion in the central Yunnan urban agglomeration, while the southeast direction shows a relatively weakening trend.
{"title":"The temporal and spatial evolution law of construction land structure in central Yunnan urban agglomeration based on GIS","authors":"Lede Niu, Lifang Zhou, Jingzhi Lin, Anlin Li, Yan Zhou","doi":"10.1504/ijetm.2023.134328","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134328","url":null,"abstract":"In order to reduce the pressure of urban construction land demand and improve the level of urban land use, this paper studies the temporal and spatial evolution of the construction land structure in the central Yunnan urban agglomeration. Firstly, ArcGIS 10.3 software was used to extract the construction land quantity of the urban agglomeration in central Yunnan, and then the standard deviation ellipse, standard distance and gravity centre migration model were used to analyse its spatial characteristics. Experiments show that the northeast direction is the most prominent direction of construction land expansion in the central Yunnan urban agglomeration, while the southeast direction shows a relatively weakening trend.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijetm.2023.134323
Yuanying Li, Linlin Zheng
To improve the effect of green space landscape layout optimisation and shorten the time-consuming of view layout optimisation, this paper proposes an urban road green space landscape layout optimisation method based on leapfrog algorithm. Firstly, GIS is used to collect road landscape layout data. Then, the index weight is calculated by analytic hierarchy process. The frog-leaping algorithm is used to construct the fitness objective function and solve the fitness value. Finally, the fitness values are sorted from good to bad to judge whether the current output optimal value is the global optimal value, and the final landscape layout optimisation scheme is obtained. The experimental results show that the green space landscape layout optimisation time of this method is only 8.3 s, and the rationality of landscape layout is as high as 99.02%, which shows that this method can have a good effect of road green space landscape layout optimisation.
{"title":"An optimisation method of urban road green space landscape layout based on leapfrog algorithm","authors":"Yuanying Li, Linlin Zheng","doi":"10.1504/ijetm.2023.134323","DOIUrl":"https://doi.org/10.1504/ijetm.2023.134323","url":null,"abstract":"To improve the effect of green space landscape layout optimisation and shorten the time-consuming of view layout optimisation, this paper proposes an urban road green space landscape layout optimisation method based on leapfrog algorithm. Firstly, GIS is used to collect road landscape layout data. Then, the index weight is calculated by analytic hierarchy process. The frog-leaping algorithm is used to construct the fitness objective function and solve the fitness value. Finally, the fitness values are sorted from good to bad to judge whether the current output optimal value is the global optimal value, and the final landscape layout optimisation scheme is obtained. The experimental results show that the green space landscape layout optimisation time of this method is only 8.3 s, and the rationality of landscape layout is as high as 99.02%, which shows that this method can have a good effect of road green space landscape layout optimisation.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-12DOI: 10.1504/ijetm.2021.10040302
Lu Zhang, Zhihui Tang, Sulu Zhu, Yuankai Song
Although the construction of water conservancy projects has promoted economic development, it has also caused great damage to the social environment to a certain extent. Research on water conservancy project construction is of great significance for promoting sustainable development. This article first deeply studied the relationship between water conservancy project construction and environmental protection, then put forward constructive opinions on how to plan water conservancy project construction scientifically and rationally, and finally carried out simulation experiments using examples. The experimental results show that the method proposed in this article can effectively reduce the environmental impact of water conservancy project construction and promote economic growth.
{"title":"Strategic relationship between water conservancy project construction and environmentally sustainable development","authors":"Lu Zhang, Zhihui Tang, Sulu Zhu, Yuankai Song","doi":"10.1504/ijetm.2021.10040302","DOIUrl":"https://doi.org/10.1504/ijetm.2021.10040302","url":null,"abstract":"Although the construction of water conservancy projects has promoted economic development, it has also caused great damage to the social environment to a certain extent. Research on water conservancy project construction is of great significance for promoting sustainable development. This article first deeply studied the relationship between water conservancy project construction and environmental protection, then put forward constructive opinions on how to plan water conservancy project construction scientifically and rationally, and finally carried out simulation experiments using examples. The experimental results show that the method proposed in this article can effectively reduce the environmental impact of water conservancy project construction and promote economic growth.","PeriodicalId":13984,"journal":{"name":"International Journal of Environmental Technology and Management","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45377452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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