Land cover change detection by using remote sensing: A case study of Zlatibor (Serbia)

Abstract

Change detection is a process of detecting differences with the objects or phenomena which are observed in the different time intervals. In this study different methods of analyzing satellite images are presented, with the aim to identify changes in land cover in a certain period of time (1985 -2013). The area observed in this study is the region of mountain Zlatibor (Serbia) with its surroundings. The methods represented in this study are vegetation indices differencing, Supervised classification and Object based classification. These methods gave different results in term of land cover area, and it is generally concluded that supervised classification gave the most accurate results with the images of medium spatial resolution. The results of this study can be used for urban and environmental planning. All information lead to conclusion that the surface under the forests is reduced for about 4% (or about 1000 ha) while the built up area has doubled (grown about 600 ha) during the examined period. The results also highlights the importance of change detection techniques in land cover for the areas that are developing rapidly, such as Zlatibor study area.

Analysis of vegetation from satellite images correlated to the bird species presence and the state of health of the ecosystems of Bucharest during the period from 1991 to 2006

“…Accurate remote sensing techniques have been widely used in locating and mapping urban vegetation: Light Detection And Ranging -LiDAR (Holmgren, et al, 2008;Kim, Muller, 2011;Bellakaou, et al, 2016;Dogon-Yaro, et al, 2016;Näsi, et al, 2016;Scaunas, Merciu, 2016), satellite imagery (Bino, et al, 2008;Mcfarland, et al, 2012;Mészáros, et al, 2014;Jovanović, et al, 2015;Agrawal, et al, 2016;Burchfield, et al, 2016;Milanović, et al, 2016).…”

“…Remote sensing techniques present several advantages: speed of the measurements, efficiency, high resolution of the recording, acquisition of an important number of data in a digital archive, integration of all information from a certain area, an important tool for monitoring environmental conditions facilitating investigation and intervention, 3D images of a certain area, the support of collecting a set of relevant data and their integration into an easily accessible system for public use, and environmental control and management (Mcfarland, et al, 2012;Jovanović, et al, 2015;Milanović, et al, 2016).…”

“…Also, the Normalized Difference Vegetation Index (NDVI) was calculated as a ratio between the difference and the sum between the infrared and red reflectance areas of the electromagnetic radiation (Mcfarland et al, 2012;Jovanović et al, 2015;Burchfield et al, 2016):…”

Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

“…The pixel cue metrics can include human visual attributes, such as color/tone, texture, and site/situation, and also visually undetectable information, such as spectral transforms or vegetation indices. Higher/lower probability values are assigned to those pixels whose values are similar/different from the training samples [59][60][61]. Subsequently, the feature probability layer (ranging between 0 and 1) is outputted, with each pixel value representing the probability of being the object of interest [62].…”

Analysis of Land Use Land Cover Change Detection of Bostanlik District, Uzbekistan

“…RS platforms continuously capture the Earth's surface and decision makers can easily apply satellite imagery to monitor dynamics of change. LULC change analysis using RS techniques gives an opportunity to obtain results with low costs, less time consumption and good accuracy, and geographical information systems (GIS) allow updating results whenever new data is available [14,15]. Utilization of open source data is a good choice to improve the skills in RS and GIS tools, in particular for scientists from less-developed countries.…”