Abstract
In Africa, the distribution of color steel tile roof (CSTR) can reflect the living standard of residents, and the analysis of its temporal and spatial changes can reflect the local changes in local living conditions. It is helpful to analyze the change of the local economic level. By using the satellite remote sensing image processing method to obtain the temporal and spatial change characteristics of CSTR and to analyze the changes in residents’ living conditions in Munyaka, Eldoret, Kenya, Africa, the model of multifeature decision tree method (DTM) extraction was established. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Building Index (NDBI) were used to remove farmland from the difference of the CSTR. The Normalized Difference Surface Index (NCSI) was constructed, and the texture features were analyzed to eliminate wasteland and bare land, respectively. The research results show that the Kappa coefficient is 0.9223, and the user precision and mapping precision are 97.79% and 91.10%, respectively. At the same time, combined with the Erdoret municipal road project, the changes of CSTR before and after the project in 2016–2020 are studied. Compared the area change of CSTR in 2016–2018 with that in 2018–2020, the annual growth rate before the construction of the municipal road project is about 3.47%. After the completion of the project, the annual growth rate is 7.29%, more than twice the rate before the construction. This method can realize the dynamic monitoring of CSTR, reflect the changes of the residents’ living environment in the region, help analyze the improvement of poverty in Africa, and help understand the changes of African economic conditions.
Funder
Fundamental Research Funds for the Universities of Henan Province, China
National Natural Science Foundation of China
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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