Prediction of the Impact of Land Usage Changes on Water Pollution in Public Space Planning with Machine Learning

• Published in: Mathematical problems in engineering 2022-05, Vol.2022, p.1-9
• Main Authors: Lei, Baojie, Myung-Soo, Kim, Nurjahan
• Format: Article
• Language: English
• Subjects: Consumption; Decision making; Environmental impact; Hydrology; Land use; Land use management; Machine learning; Mathematical problems; Natural resources; Pollutants; Public spaces; Rainy season; Regression analysis; Soft computing; Surface water; Urban areas; Urban environments; Water area; Water pollution; Water quality
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2022/6276909

In urban public space planning, changes in land use, structure, and construction impact the urban environment to a certain degree. Land usage changes the urban surface water environment by impacting it through numerous ways. This paper studies about prediction of land use changes on surface water pollution in public space planning. This paper analyzes the characteristics of land use changes in public space planning from the quantitative characteristics of land use types, land use structure characteristics, and land usage degree in different years. The protection of natural resources is important, and water is one of the most important natural resources consumed by human beings. The environmental changes impacting these natural resources are to be studied to preserve the natural resources. The prediction of over-consumption of natural resources using soft computing techniques can certainly provide a solution for appropriate decision making. The prediction of relationship between land use changes and surface water pollution is required. In order to achieve this, the regression analysis on land use changes of different spatial scales with four surface water pollution indicators in the dry and wet seasons is performed to obtain the regression of each water pollution indicator. According to the determination coefficient, the determination coefficient of the model uses the comprehensive pollution index method to predict the impact of land use changes on surface water pollution. The experimental results show that the prediction accuracy of the proposed method is high and it is helpful in studying the impact of land use change on surface water pollution. It can help in decision making on consumption of natural resources to preserve the natural resources for next generations.