Large scale cartography and analyses of man-induced transformation in an urban area using satellite imagery with very high resolution

A methodology for cartography and assessment of the degree of man-induced transformation on an urban territory based on extraction of thematic information from very high resolution multi spectral Quickbird image is presented in the present paper. The proposed methodology includes 10 work stages and it has been examined on a highly fragmented urban territory (including forested and agricultural lands) of the Gniliane district, city of Novi Iskar, municipality of Sofia, Bulgaria. A land cover classification scheme for the studied area was created and 11 land cover classes are established for the classification second level, depending on the differences in their spectral reflectance. Three levels for automatic identification of the land cover classes on the multi spectral image were applied in ERDAS Imagine: 1) Unsupervised classification; 2) Supervised classification with non-parametric rule of parallelepiped and a parametric rule of maximum likelihood; and 3) Fuzzy convolution filter. A large scale land use map is composed on the base of land cover classification as the land cover classes have been transformed to 7 land use categories depending on the possibilities for recovery of the anthropogenic changes on the environment. A rank of man-induced transformation, which values vary from 1 to 10, has been assigned to each category. A large scale assessment map of man-induced transformation is created. The calculated local index of the man-induced transformation in the study area is 466.96 and the highest relative shares in its formation have the categories permanent crop fields, build-up land for residential and industrial purposes, and the forest territories. This index for the study area is slightly higher than the calculated average index for the overall territory of Bulgaria (448.1). The methodology developed proposes an opportunity for quick and objective extraction of thematic information from multi spectral images in order to assess the man-induced transformations of the environment. This allows to take the right decisions in planning, and to conduct a regional policy which ensures a sustainable development of the environment.