SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA)
Uncontrolled land cover changes negatively affect several social, economic, and environmental aspects, so that the impact on the environment is significant both locally and globally. One of the causes of land use change is a factor of human activity involving physical action on land cover, for examp...
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id-itb.:807042024-02-28T12:11:29ZSPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) Siti Aisah Robiansah, Suci Indonesia Theses Land cover, Binary Logistic Regression (BLR), land cover change pattern, cross tabulation, National Road, Provincial Road, Other Road INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/80704 Uncontrolled land cover changes negatively affect several social, economic, and environmental aspects, so that the impact on the environment is significant both locally and globally. One of the causes of land use change is a factor of human activity involving physical action on land cover, for example by the construction of road network. The road network can provide easy access to workplaces as well as educational, health, social and entertainment facilities. To facilitate the management, the road is grouped into various classes. This road grouping is intended to realize legal certainty of road operation in accordance with the authority of the Government and local government. Public roads according to their status are grouped into national roads, provincial roads, district roads, city roads and village roads. Many studies also suggest that road is one of the factors affecting land change. However, no studies have shown which class of roads are more influential on changes in land cover. Therefore, an effort is needed to understand how this land cover change phenomenon occurs. Efforts to understand land cover changes are by modeling. One of the modeling methods that can be used in predicting land cover change is Binary Logistic Regression Model (BLR). Regression is a mathematical method that aims to evaluate the relationship between one dependent variable (response) with one or more independent variables (predictor / explanatory). In this study, the independent variables used are the National Road class, Provincial Road, and Other Roads. The result showed that the model of land cover change with road class factor based on the RLB method has the best accuracy of 34,51%, the road factor only affects about 2.90% of all land cover changes and the more influential road class to the change of cover land is a national road. text |
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Uncontrolled land cover changes negatively affect several social, economic, and environmental aspects, so that the impact on the environment is significant both locally and globally. One of the causes of land use change is a factor of human activity involving physical action on land cover, for example by the construction of road network. The road network can provide easy access to workplaces as well as educational, health, social and entertainment facilities. To facilitate the management, the road is grouped into various classes. This road grouping is intended to realize legal certainty of road operation in accordance with the authority of the Government and local government. Public roads according to their status are grouped into national roads, provincial roads, district roads, city roads and village roads. Many studies also suggest that road is one of the factors affecting land change. However, no studies have shown which class of roads are more influential on changes in land cover. Therefore, an effort is needed to understand how this land cover change phenomenon occurs. Efforts to understand land cover changes are by modeling. One of the modeling methods that can be used in predicting land cover change is Binary Logistic Regression Model (BLR). Regression is a mathematical method that aims to evaluate the relationship between one dependent variable (response) with one or more independent variables (predictor / explanatory). In this study, the independent variables used are the National Road class, Provincial Road, and Other Roads. The result showed that the model of land cover change with road class factor based on the RLB method has the best accuracy of 34,51%, the road factor only affects about 2.90% of all land cover changes and the more influential road class to the change of cover land is a national road. |
format |
Theses |
author |
Siti Aisah Robiansah, Suci |
spellingShingle |
Siti Aisah Robiansah, Suci SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) |
author_facet |
Siti Aisah Robiansah, Suci |
author_sort |
Siti Aisah Robiansah, Suci |
title |
SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) |
title_short |
SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) |
title_full |
SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) |
title_fullStr |
SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) |
title_full_unstemmed |
SPATIAL ANALYSIS INFLUENCE OF ROAD CLASS ON LAND COVER CHANGE WITH BINARY LOGISTIC REGRESSION (CASE STUDY: WEST JAVA) |
title_sort |
spatial analysis influence of road class on land cover change with binary logistic regression (case study: west java) |
url |
https://digilib.itb.ac.id/gdl/view/80704 |
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