{"title":"基于Landsat 7影像的森林类型纹理分类","authors":"O. Butusov","doi":"10.2747/0749-3878.40.2.91","DOIUrl":null,"url":null,"abstract":"A method was developed for using textural, brightness, and spectral indices for the classification of forest valuation tracts on the basis of space imagery. The textural characteristics were determined by applying a discrete wavelet transform and with use of a textural matrix, on the basis of which the following textural indices were determined: energy, standard deviation, inertia, entropy, homogeneity factor, cluster shade (asymmetry), cluster prominence, and cluster correlation information measure. An unsupervised classification of valuation tracts was made for a space image of a test area within the Bulun forested sector of the Zhigansk forest management area registered by the Landsat 7 satellite. The use of textural indices alone for classification purposes proved to be inadequate. Satisfactory results were obtained only with the joint use of both textural and brightness spectral indices.","PeriodicalId":405012,"journal":{"name":"Mapping Sciences and Remote Sensing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Textural Classification of Forest Types from Landsat 7 Imagery\",\"authors\":\"O. Butusov\",\"doi\":\"10.2747/0749-3878.40.2.91\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method was developed for using textural, brightness, and spectral indices for the classification of forest valuation tracts on the basis of space imagery. The textural characteristics were determined by applying a discrete wavelet transform and with use of a textural matrix, on the basis of which the following textural indices were determined: energy, standard deviation, inertia, entropy, homogeneity factor, cluster shade (asymmetry), cluster prominence, and cluster correlation information measure. An unsupervised classification of valuation tracts was made for a space image of a test area within the Bulun forested sector of the Zhigansk forest management area registered by the Landsat 7 satellite. The use of textural indices alone for classification purposes proved to be inadequate. Satisfactory results were obtained only with the joint use of both textural and brightness spectral indices.\",\"PeriodicalId\":405012,\"journal\":{\"name\":\"Mapping Sciences and Remote Sensing\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mapping Sciences and Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2747/0749-3878.40.2.91\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mapping Sciences and Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2747/0749-3878.40.2.91","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Textural Classification of Forest Types from Landsat 7 Imagery
A method was developed for using textural, brightness, and spectral indices for the classification of forest valuation tracts on the basis of space imagery. The textural characteristics were determined by applying a discrete wavelet transform and with use of a textural matrix, on the basis of which the following textural indices were determined: energy, standard deviation, inertia, entropy, homogeneity factor, cluster shade (asymmetry), cluster prominence, and cluster correlation information measure. An unsupervised classification of valuation tracts was made for a space image of a test area within the Bulun forested sector of the Zhigansk forest management area registered by the Landsat 7 satellite. The use of textural indices alone for classification purposes proved to be inadequate. Satisfactory results were obtained only with the joint use of both textural and brightness spectral indices.