{"title":"基于时序图像和相对香农熵模型的埃塞俄比亚阿达玛城市扩张时空动态","authors":"S. Manikandan","doi":"10.24321/2455.3190.201801","DOIUrl":null,"url":null,"abstract":"Two very important major factors that have driven rapid growth of cities and towns are population growth and large-scale migration. Urban buildup information is required for enormous application for planning land use and management. A challenging task is to extract urban build up areas from moderate-resolution Landsat images due to intra-urban heterogeneity and spectral confusion between other land cover types. In this study, urban area was extracted from Landsat series of thematic mapper (TM) and object land imager (OLI) between 1984 and 2017 of Adama city in Ethiopia. Study chose two indices, Normalized Difference in Built-up Index (NDBI) and Normalized Difference in Vegetation Index (NDVI) to represent three major urban land use classes, i.e., built-up/barren/bare land, open waterbodies, and vegetation. Built-up area has been extracted by taking difference between NDBI and NDVI to remove water and vegetation noises and the resulting image was spectrally segmented to separate built-up areas. Derived index was utilized to plot decade difference of built-up area from 1984 to 2017. In order to compute Shannon entropy value, the study area was divided into 52 equal zones to quantify urban sprawl. The expansion of the built-up area has been revealed as a major change in the area when city area expanded substantially by six times 51.3364 (sq. km) area of 1984 (8.80 sq. km).","PeriodicalId":387744,"journal":{"name":"Journal of Advanced Research in Geo Sciences & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Spatial and Temporal Dynamics of Urban Sprawl Using Multi- temporal Images and Relative Shannon Entropy Model in Adama, Ethiopia\",\"authors\":\"S. Manikandan\",\"doi\":\"10.24321/2455.3190.201801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two very important major factors that have driven rapid growth of cities and towns are population growth and large-scale migration. Urban buildup information is required for enormous application for planning land use and management. A challenging task is to extract urban build up areas from moderate-resolution Landsat images due to intra-urban heterogeneity and spectral confusion between other land cover types. In this study, urban area was extracted from Landsat series of thematic mapper (TM) and object land imager (OLI) between 1984 and 2017 of Adama city in Ethiopia. Study chose two indices, Normalized Difference in Built-up Index (NDBI) and Normalized Difference in Vegetation Index (NDVI) to represent three major urban land use classes, i.e., built-up/barren/bare land, open waterbodies, and vegetation. Built-up area has been extracted by taking difference between NDBI and NDVI to remove water and vegetation noises and the resulting image was spectrally segmented to separate built-up areas. Derived index was utilized to plot decade difference of built-up area from 1984 to 2017. In order to compute Shannon entropy value, the study area was divided into 52 equal zones to quantify urban sprawl. The expansion of the built-up area has been revealed as a major change in the area when city area expanded substantially by six times 51.3364 (sq. km) area of 1984 (8.80 sq. km).\",\"PeriodicalId\":387744,\"journal\":{\"name\":\"Journal of Advanced Research in Geo Sciences & Remote Sensing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Advanced Research in Geo Sciences & Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24321/2455.3190.201801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advanced Research in Geo Sciences & Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24321/2455.3190.201801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatial and Temporal Dynamics of Urban Sprawl Using Multi- temporal Images and Relative Shannon Entropy Model in Adama, Ethiopia
Two very important major factors that have driven rapid growth of cities and towns are population growth and large-scale migration. Urban buildup information is required for enormous application for planning land use and management. A challenging task is to extract urban build up areas from moderate-resolution Landsat images due to intra-urban heterogeneity and spectral confusion between other land cover types. In this study, urban area was extracted from Landsat series of thematic mapper (TM) and object land imager (OLI) between 1984 and 2017 of Adama city in Ethiopia. Study chose two indices, Normalized Difference in Built-up Index (NDBI) and Normalized Difference in Vegetation Index (NDVI) to represent three major urban land use classes, i.e., built-up/barren/bare land, open waterbodies, and vegetation. Built-up area has been extracted by taking difference between NDBI and NDVI to remove water and vegetation noises and the resulting image was spectrally segmented to separate built-up areas. Derived index was utilized to plot decade difference of built-up area from 1984 to 2017. In order to compute Shannon entropy value, the study area was divided into 52 equal zones to quantify urban sprawl. The expansion of the built-up area has been revealed as a major change in the area when city area expanded substantially by six times 51.3364 (sq. km) area of 1984 (8.80 sq. km).