{"title":"利用指数从landsat TM影像提取建成区和植被特征:以坦桑尼亚达累斯萨拉姆和基萨拉维城郊地区为例","authors":"F. Mwakapuja, E. Liwa, J. Kashaigili","doi":"10.5923/J.IJAF.20130307.04","DOIUrl":null,"url":null,"abstract":"Abstrac t This paper address the use of Indices Co mbination with Supervision Classification methods to extract urban built-up areas, vegetation and water features fro m Landsat Thematic Mapper (TM7) imagery covering Dar es Salaam and Kisarawe peri-urban areas. The study uses three indices; Normalized Difference Bu ilt-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI), and Soil Adjusted Vegetation Index (SA VI) to reduce the seven bands Landsat TM7 image into three thematic-oriented bands. Data correlation, spectral confusion and redundancy between original mu ltispectral bands were significantly reduced upon application of the techniques. As a result, the spectral signatures of the three urban land-use classes are mo re distinguishable in the new co mposite image than in the original seven-band image since the spectral clusters of the classes are well separated. Through a supervised classification on the newly formed image, the urban built-up areas, vegetation and water features were finally extracted effect ively; with the accuracy of 82.05 percent attained. The results show that the technique is effective and reliable and can be considered for use in other areas with similar characteristics.","PeriodicalId":13804,"journal":{"name":"International Journal of Agriculture and Forestry","volume":"61 1","pages":"273-283"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Usage of indices for extraction of built-up areas and vegetation features from landsat TM image: a case of Dar es Salaam and Kisarawe peri-urban areas, Tanzania\",\"authors\":\"F. Mwakapuja, E. Liwa, J. Kashaigili\",\"doi\":\"10.5923/J.IJAF.20130307.04\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstrac t This paper address the use of Indices Co mbination with Supervision Classification methods to extract urban built-up areas, vegetation and water features fro m Landsat Thematic Mapper (TM7) imagery covering Dar es Salaam and Kisarawe peri-urban areas. The study uses three indices; Normalized Difference Bu ilt-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI), and Soil Adjusted Vegetation Index (SA VI) to reduce the seven bands Landsat TM7 image into three thematic-oriented bands. Data correlation, spectral confusion and redundancy between original mu ltispectral bands were significantly reduced upon application of the techniques. As a result, the spectral signatures of the three urban land-use classes are mo re distinguishable in the new co mposite image than in the original seven-band image since the spectral clusters of the classes are well separated. Through a supervised classification on the newly formed image, the urban built-up areas, vegetation and water features were finally extracted effect ively; with the accuracy of 82.05 percent attained. The results show that the technique is effective and reliable and can be considered for use in other areas with similar characteristics.\",\"PeriodicalId\":13804,\"journal\":{\"name\":\"International Journal of Agriculture and Forestry\",\"volume\":\"61 1\",\"pages\":\"273-283\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Agriculture and Forestry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5923/J.IJAF.20130307.04\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Agriculture and Forestry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5923/J.IJAF.20130307.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Usage of indices for extraction of built-up areas and vegetation features from landsat TM image: a case of Dar es Salaam and Kisarawe peri-urban areas, Tanzania
Abstrac t This paper address the use of Indices Co mbination with Supervision Classification methods to extract urban built-up areas, vegetation and water features fro m Landsat Thematic Mapper (TM7) imagery covering Dar es Salaam and Kisarawe peri-urban areas. The study uses three indices; Normalized Difference Bu ilt-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI), and Soil Adjusted Vegetation Index (SA VI) to reduce the seven bands Landsat TM7 image into three thematic-oriented bands. Data correlation, spectral confusion and redundancy between original mu ltispectral bands were significantly reduced upon application of the techniques. As a result, the spectral signatures of the three urban land-use classes are mo re distinguishable in the new co mposite image than in the original seven-band image since the spectral clusters of the classes are well separated. Through a supervised classification on the newly formed image, the urban built-up areas, vegetation and water features were finally extracted effect ively; with the accuracy of 82.05 percent attained. The results show that the technique is effective and reliable and can be considered for use in other areas with similar characteristics.