International Journal of Environmental Technology and Management (33 papers in press)

Regular Issues

• Big Data Analytics: Classification and Solution for Soil and Fertilizer System  
  by Raghu Garg, Himanshu Aggarwal 
  Abstract: Soil is one of the most important factors for the growth of plants. It carries various nutrients like water and certain contents of air which are essential for plant nourishment. At times over exposure becomes the root cause for the degradation of an otherwise fertile soil. In present times fertilizers are given the responsibility to maintain the productivity that we yield from the soil. The method prevalent to determine the quality of the soil is known as soil analysis. Soil analysis generates an estimation of the unstructured data through the process of examining the defined soil. The specimens of a wide spectrum of soils are tested in the laboratories in order to develop heaps of agricultural data. During our research work different machine learning algorithm using big data analysis are used to detect the fertilizer recommendation classes through defined soil nutrition composition. The reports are collected from Tata soil testing laboratories for experiment. Stochastic Gradient Descent (SGD) and Artificial Neural Network (ANN) are the classification methods that are compared in this paper. The performance measures inclusive of the accuracy and area under curve (AUC) are exercised to determine efficiency of classification model. Experiments show that the SGD performs a lot better then artificial neural network when it comes to accuracy, AUC and pace. The ANN is outdone by SGD with linear regression. The percentage of overall accuracy and AUC values of SGD are 88% and 86% respectively. The overall accuracy and AUC using ANN is 80% and 79% respectively. The results also reflect that SGD with linear regression are feasible in accurate recognition of the fertilizer recommendation classes.
  Keywords: Agriculture data; Fertilizer recommendations; SGD; Soil reports; artificial neural network; AUC.
  
  
• Waste to Wealth and Health: Bio-recovery and Applications of chitin and its derivatives  
  by Machineni Lakshmi 
  Abstract: The search for new molecules that are useful for human health and ecofriendly has led to the study of molecules derived from plants, animals and microorganisms. Chitin is the second most ubiquitous natural polysaccharide after cellulose on the earth, comprising repeating units of N-acetyl-D-glucosamine. However, because chitin in its natural form has high crystallinity and low solubility, its applications are limited. Modified chitin can be converted into chitooligosaccharides with varied degree of polymerization by either chemical or enzymatic methods. Even though this review has emphasized on the different chitin extraction methods, and their applications, the biological methods discussed in detail could suggest new understanding about nontoxic chitin extraction methods. In addition, an attempt has been made to highlight the recent research on their commercial applications.
  Keywords: Chitin; Chitosan; CHOS; Bio-deproteinization; Bio-demineralization; Biofilm.
  
  
• Investigation and optimisation of turbidity and organic matter removal from surface water by electrocoagulation using response surface methodology  
  by Slimane Bessioud, Abed Mohamed Affoune, Mohamed Lyamine Chelaghmia 
  Abstract: In this research, the response surface methodology (RSM) based on the central composite design (CCD) was applied to assess and optimise the electrocoagulation (EC) process used to remove turbidity and organic matter from surface water. The effects of operating factors on turbidity and organic matter removal were investigated: reaction time, electric current, effective electrode surface area and inter-electrode distance. The potassium permanganate method was used to estimate the organic matter by chemical oxygen demand (CODMn). Analysis of variance showed that the quadratic models developed to assess the responses were found to have high coefficients of determination values of 0.9747 and 0.9851 for turbidity and CODMn removal efficiencies, respectively. The experimental results revealed that 99.08% of turbidity and 85.96% of CODMn were removed at optimal conditions. The results show that the selected operating factors are significant, and RSM effectively optimises turbidity and organic matter removal from surface water by EC process.
  Keywords: electrocoagulation; surface water; turbidity; organic matter; reaction time; electric current; electrode surface area; inter-electrode distance; response surface methodology; central composite design; environmental technology.
  
  
• Maximum power point tracking for grid tied solar fed DTC controlled IM drive using artificial neural network with energy management  
  by S. Senthamizh Selvan 
  Abstract: In the mechanised world, carbon-less emission of energy production is vitalised. Despite varied renewable energy sources available, solar PV seems to be an optimum choice due to its ease of installation and maintenance. Though conventional algorithm exists for extracting maximum power, non-conventional algorithm by soft computing is foreseen for high stability during a sudden change in irradiation and load transients. In this article, artificial neural network-based maximum power point tracking is focused. A comparative analysis is carried out between single layer neural network and multi-layer neural network for varied parameters. The multi-layer neural network is found to be advantageous in the case of neuron’s requirement, implementation complexity and testing MSE. Hence, the trained neural model is implemented in PV-grid fed DTC-IM drive system with various operating conditions. Simulation results are found to satisfactory. Added energy management condition is also validated for various irradiations.
  Keywords: artificial neural network; ANN; single layer feed forward; multi-layer feed forward neural network; maximum power point tracking.
  DOI: 10.1504/IJETM.2023.10053417
   
  

Special Issue on: Application of Remote Sensing and GIS in Environmental Studies II

• Study on monitoring method of pollution range in scenic spots based on two-dimensional threshold method  
  by Yaqi Shi 
  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%.
  Keywords: two dimensional threshold method; tourist attractions; pollution range monitoring; satellite remote sensing data.
  DOI: 10.1504/IJETM.2022.10052222
   
  
• An analysis of change detection in land use land cover area of remotely sensed data using supervised classifier  
  by H.N. Mahendra, S. Mallikarjunaswamy 
  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.
  Keywords: multispectral data; change detection; remote sensing; geographic information system; GIS; land use land cover; LULC; support vector machines; SVM; maximum likelihood classifier; MLC.
  DOI: 10.1504/IJETM.2022.10052058
   
  
• An optimisation method of urban road green space landscape layout based on leapfrog algorithm  
  by Yuanying Li, Linlin Zheng 
  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 8.3s, 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.
  Keywords: leapfrog algorithm; hierarchical single sorting; judgment matrix; analytic hierarchy process; fitness function.
  DOI: 10.1504/IJETM.2022.10052203
   
  
• An ecological health evaluation of tourist attractions based on gradient boosting decision tree  
  by Renzhong Jin 
  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. Design the data collection framework of tourist attractions based on UAV low-altitude remote sensing, construct the ecological health evaluation index system of tourist attractions, and use information entropy and analytic hierarchy process 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%.
  Keywords: UAV low-altitude remote sensing; tourist attractions; ecological health evaluation; information entropy; analytic hierarchy process; gradient boosting decision tree algorithm; support vector machine.
  DOI: 10.1504/IJETM.2022.10052223
   
  
• Location method of garden air pollution source based on gradient lifting regression tree algorithm  
  by Xiang Huang, Liuzhen Li 
  Abstract: In order to improve the location accuracy of garden air pollution sources, this paper proposes a new method of garden air pollution source location based on gradient lifting regression tree algorithm. Firstly, the infrared remote sensing spectrometer is used to collect the air pollution data in the garden. Secondly, the decision tree algorithm is used to construct the regression tree of garden pollution data. The least square regression tree is used as the base learner, and the gradient lifting regression tree is constructed by iterative calculation. Finally, the gradient value of the gradient lifting regression tree is calculated and fitted with the regression tree to obtain the node location of the regression tree, which is the location of the pollution source. The experimental results show that, compared with the traditional location methods, the pollution source location accuracy of this method is higher, which is always maintained at more than 96%.
  Keywords: gradient lifting regression tree algorithm; garden air environment; pollution source location; gradient value.
  DOI: 10.1504/IJETM.2022.10052224
   
  
• The temporal and spatial evolution law of construction land structure in central Yunnan urban agglomeration based on GIS  
  by Lede Niu, Lifang Zhou, Jingzhi Lin, Anlin Li, Yan Zhou 
  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.
  Keywords: geographic information system; construction land structure; central Yunnan urban agglomeration; temporal and spatial evolution law; standard deviation ellipse.
  DOI: 10.1504/IJETM.2022.10052280
   
  

Special Issue on: Innovative Environmental Technologies and Management

• The numerical simulation of thermal environment of high-rise buildings based on Rosseland radiation model  
  by Yanping Xie, Yabin Wu, Zhi Zhao, Hui-hua Xiong 
  Abstract: Aiming at the problem of thermal environment numerical simulation of buildings, this paper proposes a new research method of thermal environment numerical simulation of high-rise buildings based on Rosseland radiation model. First of all, analyse the wind flow characteristics of the thermal environment around the building to obtain the total heat value. Secondly, the energy conservation law equation, momentum conservation law equation and mass conservation law control equation of hot gas fluid flow are constructed. Finally, Rosseland radiation model is introduced to obtain heat flux and output the numerical simulation results of thermal environment. The results of performance comparison show that the proposed simulation method can get accurate thermal environment simulation results without being affected by seasonal temperature changes.
  Keywords: Rosseland radiation model; high rise building; thermal environment; numerical simulation.
  DOI: 10.1504/IJETM.2023.10053935
   
  
• Spatial planning method of urban landscape architecture distribution pattern based on evolutionary algorithm  
  by Jingjing Feng, Yuxiong Chen 
  Abstract: Aiming at the problems of low planning accuracy and long planning time in the traditional spatial planning method of urban landscape architecture distribution pattern, a spatial planning method of urban landscape architecture distribution pattern based on evolutionary algorithm was proposed. Acquire urban landscape remote sensing image through ETM+ and Landsat TM/OLI images, and use ENVI software to conduct geometric correction, image enhancement and other processing. Acquire spatial data of landscape distribution pattern from urban landscape green space types, patch area size, number and other aspects, use differential evolution algorithm to calculate the fitness value corresponding to the initialised population, extract landscape features, and use mutation operators The optimal solution is obtained through three steps of crossover operator and selection operation, which is the optimal spatial planning strategy. The simulation results show that the proposed method has higher precision and shorter planning time in spatial planning of urban landscape architecture distribution pattern.
  Keywords: evolutionary algorithm; urban landscape architecture; distribution pattern; spatial planning; landscape characteristics.
  DOI: 10.1504/IJETM.2023.10053936
   
  
• A monitoring method of surface vegetation distribution in the Yellow River Basin Based on remote sensing image segmentation  
  by Wei Wang, Xiaoyan Yi 
  Abstract: In order to overcome the problems of low accuracy and long time-consuming of traditional vegetation distribution monitoring methods, a new monitoring method of surface vegetation distribution in the Yellow River Basin based on remote sensing image segmentation is proposed. First, describe the segmentation features of remote sensing images. Secondly, based on the results of feature description, H-minimum transform is used to calculate the segmentation parameters of remote sensing image and complete the segmentation of remote sensing image. Finally, the maximum value synthesis method is used to calculate the surface vegetation coverage. Combined with the normalised vegetation index, the dichotomy model is used to calculate the distribution parameters of surface vegetation, and the distribution monitoring of surface vegetation is completed. The experimental results show that this method can effectively improve the monitoring accuracy and reduce the monitoring time, and the monitoring accuracy reaches more than 93%.
  Keywords: remote sensing image segmentation; the Yellow River Basin; surface vegetation; distribution monitoring.
  DOI: 10.1504/IJETM.2023.10053937
   
  
• Economic security and enterprise management in the conditions of an environmental economy as a basis for sustainable development.  
  by Svitlana Tiutchenko, Maryna Ivanova, Viktoriia Smiesova, Olena Tryfonova, Vasyl Shvets, Alla Dudnyk 
  Abstract: The paper addresses the features of management of enterprises in an environmental economy to ensure their economic security. It has been stated that currently there is a need to define criteria that would improve the procedure for assessing the economic security of enterprises and take into consideration the transition to an environmental economy. The concept of "ensuring the enterprise economic security" is interpreted by the authors as a system of guaranteeing resistance, risk reduction and economic succession of enterprises in the face of today’s challenges and threats and under the conditions of transition to an environmental economy. The existing approaches to integral assessment of the enterprise economic security have been supplemented by the environmental method. The authors have proposed a method for determining a three-component index for assessing the economic security and a matrix of security zones for enterprises.
  Keywords: enterprise management; environmental economy; economic security; decoupling; nature management; sustainable development.
  DOI: 10.1504/IJETM.2023.10054092
   
  
• Environmental quality of the Oued Larbaa, Morocco: a multivariate approach using physicochemical parameters, indicator bacteria and parasite and floristic monitoring  
  by Nezha Mherzi, Fatima Lamchouri, Abdelouahab Zalaghi, Hamid Toufik 
  Abstract: In this study, a botanical inventory, five physico-chemical parameters, results of bacteriological and parasitological analyses of soil and water during three periods (dry-2017, wet-2018, and dry-2018) on nine stations of Oued Larbaa, were analysed by principal component analysis and ascending hierarchical classification. The interpretation of results using these tools allowed us to understand that acidity and salinity are stress factors for the survival of bacteria because of negative correlations between them; the analysis also showed negative correlations between bacteria and parasites which means the presence of competition, vegetation is negatively affected by temperature and pollution. Ascending hierarchical classification showed that stations having received the same type of discharges meet in the same group, station S8 which receives the leachates of the uncontrolled landfill is alone in a group indicating the unique polluting character of leachate.
  Keywords: principal component analysis; PCA; Oued Lârbaa; water; soil; physicochemical-bacteriological-parasitological parameters; hierarchical ascending classification; HAC; botanical inventory; Morocco.
  DOI: 10.1504/IJETM.2023.10053678
   
  
• A risk detecting and preventing system for hazardous chemicals in energy industry based on knowledge graph  
  by Guanlin Chen, Bangjie Zhu, Lei Zhou, Qi Lu, Wenyong Weng 
  Abstract: In order to improve the ability of hazardous chemicals management and risk prevention and control in the energy industry, combined with the concept of knowledge graph and visualisation related technology, this paper mainly introduces a risk detecting and preventing system for hazardous chemicals (RDPSHC). The system consists of user management, equipment management, visual display, log recording, real-time alarm, knowledge map application and so on. RDPSHC can extract entity relationships from a large number of hazardous chemical data and information, build knowledge graph, and provide corresponding treatment measures for hazardous chemicals according to the displayed visual early warning information such as storage humidity and temperature of hazardous chemicals, so as to make the risk prevention and detection of hazardous chemicals more scientific and efficient, and improve the supervision and prevention ability of hazardous chemicals in the energy industry.
  Keywords: knowledge graph; hazardous chemicals; energy industry; Neo4j; visual display; Vue; Spring Boot.
  DOI: 10.1504/IJETM.2023.10053932
   
  
• A drought monitoring method in the Yellow River basin based on boundary extraction of remote sensing images  
  by Yang Liu, Xiaodong Shi, Ge Zhang, Shaofeng Zhao, Ze Wang 
  Abstract: In order to improve the extraction accuracy of remote sensing image boundary information and improve the fitting degree between drought monitoring results and actual results, this study designed a drought monitoring method in the Yellow River basin based on boundary extraction of remote sensing images. ETM+ Landsat satellite was selected to collect real-time remote sensing images comprehensively. After geometric correction and radiometric correction, edge information is extracted from remote sensing image data. Then the spatial inversion process of remote sensing index and surface temperature characteristics is established, and the drought monitoring level of the Yellow River basin is set after the elevation correction. According to the experiment, the accuracy of the method to extract the image boundary information is always above 91.7%, and the fitting degree between the obtained drought monitoring results and the actual results is always above 0.94, indicating that the method effectively achieves the design expectation.
  Keywords: Yellow River basin; drought conditions; remote sensing monitoring; remote sensing image; boundary extraction.
  DOI: 10.1504/IJETM.2023.10053933
   
  
• Analysis on the spatial dynamic characteristics of land use in the urban agglomeration in central Yunnan based on random forest algorithm  
  by Lede Niu, Jingzhi Lin, Lifang Zhou, Yan Zhou 
  Abstract: In order to improve the accuracy of land use spatial analysis results, this paper takes the urban agglomeration in central Yunnan as an example, and proposes a land use spatial dynamic characteristics analysis method based on random forest algorithm. Use GIS technology to collect and process land remote sensing image data, extract sparse description features of remote sensing image through dictionary learning method, build a random forest classification model, classify land use space and analyse dynamic features. The detailed analysis of land use change in the study area from 2005 to 2020 shows that the cultivated land area in this area has increased by 3,661 km2, the dry land area has increased by 3,704 km2, and the grassland area has decreased by 2,727 km2, with the highest annual change rate of 0.62%.
  Keywords: remote sensing image; land use; spatial dynamic feature; random forest algorithm; sparse description feature.
  DOI: 10.1504/IJETM.2023.10053934
   
  
• Changes and variability of rainfall amounts and extreme indices in Gedeo Zone, Southern Ethiopia  
  by Yimer Mohammed, Asnake Yimam, Abiyot Legesse 
  Abstract: This study made detailed analysis of variability and trends of rainfall in Gedeo Zone, Southern Ethiopia using climate data tool. Its variability was examined by coefficient of variation, precipitation concentration index, and standardised rainfall anomalies whereas trends were evaluated using Mann-Kendall trend test and Sens slope estimator. The finding indicated that rainfall variability was high during MarchMay and September-November which resulted in extended periods of driest years. Insignificant decreasing trends of rainfall amount at annual and seasonal (MarchMay) timescales were observed. However, most extreme events showed varying trends across studied stations. For example, all rainfall extreme indices showed decreasing trends in Yirgachefe and Kochere and significant increasing trends at Bule. Since climatic variability and trends have been changing in short distances, this type of local level study is thought important to take up to date and appropriate decisions on the management of agriculture, water, and flood risks.
  Keywords: extreme indices; Gedeo; Mann-Kendall; trend; variability; Ethiopia.
  DOI: 10.1504/IJETM.2023.10053938
   
  

Special Issue on: Environmental Change Management with Advanced Technologies

• An assessment of built-up cover using geospatial techniques - a case study on Mysuru district, Karnataka state, India  
  by H.N. Mahendra, S. Mallikarjunaswamy, Sudalayandi Rama Subramoniam 
  Abstract: The cities in any developing countries are the main backbone for the economic growth of the country. In recent days, developing countries faces major issues such as increases in urbanisation and population. An assessment of built-up area plays an important role during the regional planning and infrastructure development of the city. Mysuru has a unique place in the world due to its culture, green cover, and pleasant weather. The present study assess the decade changes in a built-up area of Mysuru district, Karnataka state, India using multispectral remotely sensed data of 2009 and 2019. Change detection of an entire Mysuru district has been carried out with respect to the built-up area of cities and taluks. An experimental result shows that 4.66% of built-up cover in 2009 was increased to 6.56% in 2019. These results show that the built-up cover of the Mysuru district increased by 1.9% over the decade. Overall classification was estimated to be 88.7% for 2009 and 85.4% for 2019.
  Keywords: remote sensing; multispectral data; maximum likelihood classifier; MLC; built-up cover; change detection; geographic information system; GIS.
  DOI: 10.1504/IJETM.2022.10048734
   
  
• Microplastic hazard, management, remediation, and control strategies: a review  
  by Nafiaah Naqash, Shaista Manzoor, Rahul Singh 
  Abstract: Understanding microplastic distribution within natural systems and its ecological impact is a worldwide concern. Here, we review the distribution and impact of microplastic across aquatic and terrestrial habitats including humans. In comparison with marine, freshwater environments have reported limited studies. Whereas, studies indicating microplastic contamination of terrestrial systems are very few. Therefore, comprehensive assessment of microplastic pollution is essential for effective management and control. Further, improving techniques and expanding microplastic research are needed to highlight intense research requirements in the future. Improper management of plastic has been observed to increase overall plastic contamination in recent years. Successful implementation of proper management is crucial for preventing the hazardous effects of microplastic pollution. Inexpensive recycling procedures and biodegradation of polymers are being implemented for the efficient recovery of plastic waste. Such remediation needs to be focused in detail to control the adverse consequences related to the improper discarding of plastic waste.
  Keywords: microplastic pollution; environmental impact; health risks; waste management; reduction; terrestrial system; human health; consequences; remediation; control.
  DOI: 10.1504/IJETM.2022.10049175
   
  
• The impact modelling of urban and rural land planning and development on the ecological environment around the city  
  by Fang Yan, Wentao Lei, Ling Li 
  Abstract: In order to effectively explore the impact of urban and rural land planning and development on the environment, improve the research accuracy and environmental quality, and summarise the impact of urban and rural land planning and development on the periphery of the city. According to the results of impact analysis, the information of urban and rural land development intensity and the information of ecological environment around the city are counted. The global scheduling method is used to calculate the contribution of promoting factors, so as to construct the impact research model. The urban and rural land development intensity information and ecological environment information are input into the model, and the output of the model is the impact research result. The experimental results show that the accuracy of ecological environmental impact analysis around the city remains above 90% after the application of this method.
  Keywords: urban; rural land; ecological environment; influence model; planning and development degree; ecological environment security.
  DOI: 10.1504/IJETM.2022.10049176
   
  
• Air quality monitoring of landscape architecture based on multi-sensor fusion  
  by Xiang Huang, Liangjie Li 
  Abstract: In order to overcome the problems of low accuracy and poor real-time performance of traditional methods, a new air quality monitoring of landscape architecture based on multi-sensor fusion is proposed. Build a sensor acquisition device based on ZigBee network to collect PM2.5 concentration, PM10 concentration, carbon monoxide concentration, ozone concentration, sulphur dioxide concentration, nitrogen dioxide concentration and other indicators, eliminate the interference value, and use Bayes algorithm to fuse the multi-sensor data. R-type cluster analysis is used to calculate the correlation between the collection indexes, based on which a comprehensive evaluation model of air quality is constructed. The processed collection results are substituted into the model to obtain the comprehensive evaluation results of air quality. Combined with the evaluation results, it is necessary to realise the air quality monitoring of landscape architecture. The test results show that this method has high monitoring accuracy and good real-time performance.
  Keywords: multi-sensor information; landscape architecture; air quality monitoring; Bayes algorithm; R-type cluster analysis.
  DOI: 10.1504/IJETM.2022.10049177
   
  
• Method for monitoring regional environmental temperature change data based on 5G internet of things technology  
  by Qiong-Pei Wang 
  Abstract: In view of the inconsistency between the temperature data monitoring results and the actual results and the low monitoring efficiency, a regional environmental temperature change data monitoring method based on 5G internet of things technology is proposed. Using 5G internet of things technology to build a real-time data acquisition platform to complete data acquisition; With the help of the logic structure of the input gate, input the collected data, set the data threshold, determine the continuity between the data through the forgetting gate, and use the digital filtering method to suppress the interference factors and complete the preprocessing. The fuzzy control algorithm is used to control the temperature change data, construct the fuzzy subset of the temperature change data, introduce the fuzzy theory to construct the monitoring model, and realise the design of the monitoring method. The results show that the monitoring time of this method is less than 5.5 s.
  Keywords: 5G internet of things technology; temperature change; data monitoring; fuzzy control algorithm; inertial filtering; fitting property.
  DOI: 10.1504/IJETM.2022.10049178
   
  
• Comprehensive evaluation of landscape architecture environment quality based on multi-source remote sensing technology  
  by Yuanying Li 
  Abstract: In order to overcome the problems of low accuracy of information collection and large error of comprehensive evaluation of environmental quality in traditional methods, a comprehensive evaluation of landscape architecture environment quality based on multi-source remote sensing technology was proposed. Multi-source remote sensing images were collected, and the remote sensing images were registered by radiometric correction and geometric correction methods, and environmental information of landscape architecture was collected. According to the collected information, the comprehensive evaluation index system of landscape environment quality was established, the weight distribution of each evaluation index was determined by fuzzy comprehensive evaluation model and single index membership function, and the comprehensive evaluation model of landscape environment quality was built according to the evaluation index weight to achieve the comprehensive evaluation of environmental quality. Experimental results show that the accuracy of this method varies from 93% to 97%, and the average evaluation error is 3.51.
  Keywords: multi-source remote sensing technology; landscape architecture; environmental quality; comprehensive evaluation; radiation correction; geometric correction; fuzzy comprehensive evaluation model.
  DOI: 10.1504/IJETM.2022.10049179
   
  
• An ecological environment impact assessment of municipal solid waste based on grey prediction model  
  by Xuefei Ma 
  Abstract: Aiming at the problem of low accuracy in the impact assessment of urban waste on ecological environment, a method of urban waste ecological environment impact assessment based on grey prediction model is proposed. Determine the pollution type of urban waste, and extract the important pollution data of urban waste with the help of the calculation of comprehensive water quality identification index; The total ranking of pollution data is determined by the square root method, the judgement matrix is set to calculate the weight of pollution data, and the urban waste ecological environment pollution index system is constructed; With the help of grey prediction model, the positive correlation between urban waste and ecological environment is determined, and the urban waste ecological environment impact assessment algorithm is designed to complete the impact assessment. The results show that the evaluation accuracy can be effectively improved by using the evaluation method in this paper.
  Keywords: grey prediction model; city waste; ecological environment; comprehensive water quality identification index; autoregressive integral moving average model.
  DOI: 10.1504/IJETM.2022.10049180
   
  
• A prediction method of soil environmental pollutants in landscape architecture planning based on data clustering  
  by Shengli Xu 
  Abstract: Aiming at the problem of low prediction accuracy in the prediction of soil environmental pollutants in landscape architecture, a prediction method of soil environmental pollutants in landscape architecture planning based on data clustering is designed. Firstly, through the soil pollution evaluation standard in landscape architecture planning, the pollution index system is constructed to obtain the pollution index data; Then, the consistency pre-processing of the obtained pollution index data is carried out, and the data features are extracted with the help of regionalised variables and variogram; Finally, according to the feature extraction results, the pollution weight is determined by Nemero index, and the pollution grade is divided by data clustering method. According to the pollution trend, the prediction model of pollutant soil pollution degree is constructed to complete the prediction. The results show that the proposed method can effectively improve the prediction accuracy of soil pollution.
  Keywords: data clustering; landscape architecture; soil environmental pollutants; similarity matrix.
  DOI: 10.1504/IJETM.2022.10049181
   
  
• Detection algorithm of abnormal characteristics of urban domestic water quality based on K-means clustering  
  by Xiaoying Huang 
  Abstract: In order to solve the problem of low detection accuracy in water quality anomaly detection, an urban domestic water quality anomaly detection algorithm based on K-means clustering is proposed. Firstly, by constructing the water quality feature extraction system and calculating the pollutant content by fluorescence method, the water quality feature extraction and pollutant content determination are completed. Then, normalise and normalise the data, and introduce root mean square error to remove redundancy and complete the preprocessing. Finally, taking the pH value, ammonia nitrogen, oxygen consumption, chromaticity and turbidity of urban domestic water quality as abnormal values, the trust degree and data cluster distance between data are calculated through K-means clustering, and the abnormal characteristic detection model of urban domestic water quality is constructed to complete the detection. The results show that the proposed method has high accuracy in detecting the abnormal characteristics of urban domestic water quality.
  Keywords: K-means clustering; urban domestic water; abnormal characteristics of water quality; DBN model; degree of trust; cluster distance.
  DOI: 10.1504/IJETM.2022.10049264
   
  
• Study on landscape pattern gradient of garden urban green space under ecological guidance  
  by Yan Xiao 
  Abstract: In order to improve the calculation accuracy of landscape pattern gradient, the landscape pattern gradient of garden urban green space is studied under the guidance of ecology. Firstly, it expounds the important role of landscape pattern gradient research under the ecological guidance, as well as the connotation of garden urban green space landscape development under the ecological guidance. Secondly, the gradient characterisation parameters of landscape pattern are calculated, including green space landscape area percentage, number of regional patches, regional maximum patch index, landscape shape index, average patch area, aggregation index, patch density, separation degree, diversity index and evenness index. Finally, set the horizontal and vertical coordinates of the grid, carry out grid processing, and complete the gradient calculation of landscape pattern. The experimental results show that this method can obtain accurate gradient characterisation parameters of landscape pattern, which is conducive to the development of landscape pattern.
  Keywords: ecological orientation; garden urban; green landscape; pattern gradient.
  DOI: 10.1504/IJETM.2022.10049265
   
  
• Prediction method of dust pollutant diffusion range in building demolition based on Euclidean distance transformation  
  by Yunfeng Zhao, Yuya Wang, Feng Qiu 
  Abstract: Aiming at the problem of low prediction accuracy in the prediction of pollutant diffusion range, a prediction method of dust pollutant diffusion range in building demolition based on Euclidean distance transformation is proposed. The Euclidean distance field outside the collection object is established by Euclidean distance transformation, and the parameters of dust pollutants in building demolition are extracted; According to the atmospheric stability and the position of the boundary layer, the Gaussian model is used to simulate the diffusion trend of fugitive dust pollutants, the prediction model is established with the help of cellular automata model, the parameters are input into the prediction model, and the output result is the prediction result to realise the prediction. The results show that the prediction accuracy of the proposed method is high.
  Keywords: Euclidean distance transformation; building demolition; dust pollution; diffusion range prediction; cellular automata model.
  DOI: 10.1504/IJETM.2022.10049274
   
  
• Urban garden spatial environment layout method based on random forest  
  by Zhixue Wu, Zhiying Wu 
  Abstract: In order to solve the problems of low layout accuracy and long cost in urban garden spatial environment layout, an urban garden spatial environment layout method based on random forest is designed. Firstly, the multi vision camera is used to collect the spatial environment image of urban garden, the spatial environment coordinates are transformed by rigid body, and the non classical receptive field suppression method is used to remove the interference in the features; Then, with the help of analytic hierarchy process, the hierarchical model of configuration index rating is constructed, the layout index system is determined according to the model, and the constraints of judgment matrix are set. Finally, the layout model is constructed with the help of random forest algorithm, and the final input layout model data is determined to complete the layout. The experimental results show that the layout accuracy of the proposed method is high.
  Keywords: random forest: urban garden space; layout method; rigid body transformation; analytic hierarchy process.
  DOI: 10.1504/IJETM.2022.10049275
   
  
• An evaluation of rural ecological environment carrying capacity under rural land commercial development  
  by Jing Jin 
  Abstract: In order to improve the accuracy and efficiency of rural eco-environmental carrying capacity assessment, this paper proposes a new rural eco-environmental carrying capacity assessment method under rural land commercialisation development based on combined weighting method. Firstly, the weighted average method is used to calculate the rural surface runoff coefficient covering the whole area and determine the soil erodibility factor. Secondly, realise the weighting of rural ecological environment carrying capacity principal component analysis (PCA), calculate the subjective weight of each evaluation index by analytic hierarchy process, and establish a multi-level evaluation index system. Combined PCA weighting and subjective weighting to form combined weighting. Finally, the objective function of maximising the carrying capacity of rural ecological environment resources is constructed to realise the evaluation of carrying capacity. The experimental results show that the evaluation accuracy of this method is as high as 99.68%; and the evaluation time is short.
  Keywords: analytic hierarchy process; empowerment PCA; subjective weight value; weighted superposition; distance weight method; combined weighting method.
  DOI: 10.1504/IJETM.2022.10049276
   
  
• Quantitative evaluation of water pollution degree based on comprehensive biomarker response index method  
  by Wenwen Wu, Shu Hu 
  Abstract: In order to improve the accuracy of water pollution degree evaluation results, a quantitative evaluation method of water pollution degree based on comprehensive biomarker response index method is proposed. Firstly, the research water area is selected, and the sampling and monitoring location is arranged in combination with the actual situation. Secondly, carry out biomarker analysis and water sample pollutant analysis. The collected data include the content data of SOD, CAT, TBARS, GSH, GSSG, GST, GPx, AChE and MTs in gills and viscera of crucian carp, as well as the content data of Pb, As, Cd, Cu and Hg heavy metals in water samples. Finally, the comprehensive marker response index is calculated for the quantitative evaluation of water pollution degree. The experimental results show that compared with the traditional evaluation methods, this method can get more accurate evaluation results, and the evaluation accuracy is always maintained at more than 90%.
  Keywords: comprehensive biomarker response index method; pollution of waters; pollution degree; quantitative evaluation.
  DOI: 10.1504/IJETM.2023.10051289