Comparison of pixel-based and object-based classification methods in detecting land use/land cover dynamics

28th European-Association-of-Remote-Sensing-Laboratories (EARSeL) Symposium and Workshops on Remote Sensing for a Changing Europe -- JUN 02-05, 2008 -- Istanbul Tech Univ, Remote Sensing Div, ITU Maslak Campus, Istanbul, TURKEYWOS: 000342298700024Due to the complex spatial structure of the earth surface, obtaining a detailed and accurate land use/land cover (LULC) classification results with satellite data have still been problematic. The overall goal of this research is to compare the pixel based and object oriented image classification approaches in terms of the overall accuracies and robustness of the final classification product. An Aster image, dated 4/27/2005, with 3 bands from spectral regions of VNIR is used to perform the LULC classification for 16 different LULC classes. Ground truth data are collected from field surveys, available maps and Quickbird images. In pixel-based image analysis, supervised classification is performed by using maximum-likelihood classifier in Erdas 8.7. Object-oriented image analysis is conducted by utilizing Definiens Professional 5.0: The segmentation algorithm does not solely rely on the single pixel value, but also on shape, texture, and pixel spatial continuity. During the implementation, several different sets of parameters were tested for image segmentation, 20 was selected as a scale parameter and nearest neighbor was used as the classifier. At the end, the performance of pixel based and object-oriented classifications are compared based on the accuracy assessment results.European Assoc Remote Sensing Lab

Erosion risk mapping using rusle with GIS: Case study of Büyük Menderes river basin of Turkey

Soil erosion causes loss of soil nutrients, decline in crop yields, and reduction in soil productivity. Moreover, soil moved by erosion carries nutrients, pesticides and other harmful farm chemicals into rivers, streams, and ground water resources. Subsequently, protecting soils from erosion is important to sustain landscapes and human life. Geographic Information Systems (GIS) have emerged as a powerful tool for handling spatial information and interact well with erosion models to provide robust problem solving capabilities useful for effective decision making. Erosion models often require moderate to high amounts of spatial data, which can be effectively handled through GIS. The Universal Soil Loss Equation (USLE), later Revised (RUSLE), is a relatively simple model that has remained one of the most practical methods for estimating soil erosion potential and the effects of different management practices for over 40 years. Coupling GIS and RUSLE has been shown in many cases to be an effective approach for estimating the magnitude of soil loss and identifying spatial locations vulnerable to soil erosion. The objective of this research was to develop a user-friendly GIS-based application that could quickly estimate soil loss in Büyük Menderes, which is a Mediterranean River Basin through the integration of GIS and erosion modelling. RUSLE was chosen to model erosion due to its simplicity, wide acceptance/use, and manageable data requirements. This study emphasizes that spatial information technology including, remote sensing and GIS with RUSLE erosion modelling approach could be utilized in the spatial and quantitative assessment of erosion risk. The study showed that 2% of the basin is subject to very high erosion risk, 11% has high erosion risk, 33% has medium erosion risk. This erosion risk assessment also pointed the hot spot areas of erosion to related authorities to help in their erosion prevention efforts. © 2016 WIT Press

Urban growth pattern of Didim

28th European-Association-of-Remote-Sensing-Laboratories (EARSeL) Symposium and Workshops on Remote Sensing for a Changing Europe -- JUN 02-05, 2008 -- Istanbul Tech Univ, Remote Sensing Div, ITU Maslak Campus, Istanbul, TURKEYWOS: 000342298700023Didim peninsula is the fattest growing urban area in the Aydin province, Turkey. Since 1990, the Town of Didim has changed significantly after discovered by domestic and international tourist. In spite of the recent rapid LULC change, Didim has not been spoiled compared to other big touristic towns of Turkey. Didim has been announced as "Tourism hot spot" in 2000, thus its planning is overseen by the Ministry of Culture and Tourism. Monitoring of the Didim's development is necessary to guide the Ministry in promoting sustainable planning guidelines. The present work aims to determine the characteristics and the amount of urban growth in Didim by using remote sensing and GIS technology. Already rectified Aster (dated 04/27/2005) and Spot 2X (03/02/1994) images were used as well as the population information, aerial photographs, city plans and thematic maps from previous studies. Object oriented classification technique is employed. Some complementary information is extracted from aerials and maps by on-screen digitization. Total of 16 LULC categories are defined. After, putting all information in the GIS database, the pattern of landscape change in Didim is described by using selected landscape metrics. The case study of the Town of Didim offers a good example of the impact of national policies on land use dynamics at local landscape scale. The findings indicate three simultaneous key trends: loss of coniferous forests, the thinning of the maqui vegetation cover, and intensification of urban areas on valuable class II type of soils. Identified trends have significant consequences in terms of the response that ecosystems have given to these anthropogenic landscape alterations. A strategy to promote sustainable land use management should be generated timely manner.European Assoc Remote Sensing Lab