Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Impervious Surface Area Prediction Using Landsat Satellite Imagery and Open Source GIS Plugin
In India, population growth is rapidly increasing and the rural people are moving to urban areas for improving their socio-economic activity of life. For sustaining the human needs, most of the land use land cover features are migrating to impervious surfaces, which may lead to decreasing the infiltration capacity of the soil and increasing the flood frequency. Land Use Land Cover (LULC) maps are helpful to monitor and predict the impervious surface area using the Remote Sensing techniques. The proposed work aims to simulate the impervious surface area of Jagtial, Telangana, India, in the year 2050. This is accomplished by using Landsat satellite images from the years 2000, 2005, 2010, 2015, and 2020, and applying the Random Forest classification algorithm to generate LULC maps. The maximum tree depth is set at 30, the maximum number of trees is 250, and the maximum number of samples per class is 1000. A land use simulation model, based on Cellular Automata and Markov Chains, is employed to calibrate and optimize the LULC images. The model predicts the LULC map for the years 2020 and 2050, which are validated using existing classified LULC images. The imperviousness index of the LULC classes is used to estimate the impervious surface area of the location. The analysis of the multi-temporal LULC images shows that biophysical and socioeconomic factors have a significant impact on the increase in built-up areas and the decline in water bodies by the year 2050.
Impervious Surface Area Prediction Using Landsat Satellite Imagery and Open Source GIS Plugin
In India, population growth is rapidly increasing and the rural people are moving to urban areas for improving their socio-economic activity of life. For sustaining the human needs, most of the land use land cover features are migrating to impervious surfaces, which may lead to decreasing the infiltration capacity of the soil and increasing the flood frequency. Land Use Land Cover (LULC) maps are helpful to monitor and predict the impervious surface area using the Remote Sensing techniques. The proposed work aims to simulate the impervious surface area of Jagtial, Telangana, India, in the year 2050. This is accomplished by using Landsat satellite images from the years 2000, 2005, 2010, 2015, and 2020, and applying the Random Forest classification algorithm to generate LULC maps. The maximum tree depth is set at 30, the maximum number of trees is 250, and the maximum number of samples per class is 1000. A land use simulation model, based on Cellular Automata and Markov Chains, is employed to calibrate and optimize the LULC images. The model predicts the LULC map for the years 2020 and 2050, which are validated using existing classified LULC images. The imperviousness index of the LULC classes is used to estimate the impervious surface area of the location. The analysis of the multi-temporal LULC images shows that biophysical and socioeconomic factors have a significant impact on the increase in built-up areas and the decline in water bodies by the year 2050.
Impervious Surface Area Prediction Using Landsat Satellite Imagery and Open Source GIS Plugin
Lecture Notes in Civil Engineering
Mesapam, Shashi (Herausgeber:in) / Ohri, Anurag (Herausgeber:in) / Sridhar, Venkataramana (Herausgeber:in) / Tripathi, Nitin Kumar (Herausgeber:in) / Allu, Ayyappa Reddy (Autor:in) / Mesapam, Shashi (Autor:in)
International Virtual Conference on Developments and Applications of Geomatics ; 2022
27.02.2024
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Detection of potential green open space area using landsat 8 satellite imagery
| DOAJ | 2021
| British Library Conference Proceedings | 2007
Impervious Surface Detection from Satellite Imagery with Knowledge-Based Systems and GIS
| British Library Conference Proceedings | 2005