Cigdem Goksel

Forecasting land-cover growth using remotely sensed data: a case study of the Igneada protection area in Turkey

Human activities in many parts of the world have greatly affected natural areas. Therefore, monitoring and forecasting of land-cover changes are important components for sustainable utilization, conservation, and development of these areas. This research has been conducted on Igneada, a legally protected area on the northwest coast of Turkey, which is famous for its unique, mangrove forests. The main focus of this study was to apply a land use and cover model that could quantitatively and graphically present the changes and its impacts on Igneada landscapes in the future. In this study, a Markov chain-based, stochastic Markov model and cellular automata Markov model were used. These models were calibrated using a time series of developed areas derived from Landsat Thematic Mapper (TM) imagery between 1990 and 2010 that also projected future growth to 2030. The results showed that CA Markov yielded reliable information better than St. Markov model. The findings displayed constant but overall slight increase of settlement and forest cover, and slight decrease of agricultural lands. However, even the slightest unsustainable change can put a significant pressure on the sensitive ecosystems of Igneada. Therefore, the management of the protected area should not only focus on the landscape composition but also pay attention to landscape configuration.

Use of GIS in epidemiology: a case study in Istanbul.

In this study, the procedure of using GIS for tracking the distribution of measles in a district of Istanbul was performed. The aim of the study is to present the available questionnaire data, which were collected during the measles epidemic, by means of maps. The designed maps show the relation and the distribution of individual cases on time and spatiality. A database is designed according to the questionnaires. Geo-spatial distribution of measles cases was analyzed. The obtained results were discussed and presented.

Comparing Spatial Interpolation Methods for Mapping Meteorological Data in Turkey

Determining the potentials of the renewable energy sources provides realistic assumptions on useful utilization of the energy. Wind speed and solar radiation are the main meteorological data used in order to estimate renewable energy potential. Stated data is considered as point source data since it is collected at meteorological stations. However, meteorological data can only be significant when it is represented by surfaces. Spatial interpolation methods help to convert point source data into raster surfaces by estimating the missing values for the areas where data is not collected. Besides the purpose, the total number of data points, their location, and their distribution within the study area affect the accuracy of interpolation. This study aims to determine optimum spatial interpolation method for mapping meteorological data in northern part of Turkey. In this context, inverse distance weighted (IDW), kriging, radial basis, and natural neighbor interpolation methods were chosen to interpolate wind speed and solar radiation measurements in selected study area. The cross-validation technique was used to determine most efficient interpolation method. Additionally, accuracy of each interpolation method were compared by calculating the root-mean-square errors (RMSE). The results prove that the number of control points affects the accuracy of the interpolation. The second degree IDW (IDW2) interpolation method performs the best among the others. Thus, IDW2 was used for mapping meteorological data in northern Turkey.

GIS based spatial pattern analysis: Children with Hepatitis A in Turkey

ABSTRACT This study aimed to provide an insight into the geographic distribution of Hepatitis A incidence considering their temporal distribution, spatial patterns, hot spots and clusters identification in three different age‐group (0–4, 5–9 and 10–14) in Turkey. Province based tabular data, including monthly numbers of Hepatitis A cases in children, and the populations from 2001 to 2011 were used as the basic input of the study. Time series maps were created using Geographic Information Systems (GIS) to introduce the temporal changes in the morbidity rates of Hepatitis A. The spatial variation of Hepatitis A was measured using Morans I at the global level and the local indicators of spatial associations (LISAs) Morans I and Getis‐Ord Gi *(d) in order to identify influential locations through clusters and hot spots detection of Hepatitis A cases. The morbidity rates in children under the age of 5 were found significantly lower than the other age‐groups, whereas the age‐group 5–9 revealed the highest morbidity rates in the study area. The morbidity of Hepatitis A was detected very high for the years 2001, and 2005–2007. The identification of the highly vulnerable provinces was conducted using local Morans I and local Getis‐Ord Gi *(d). The majority of clusters and hot spots were detected to be agglomerated in the Eastern Mediterranean and South‐Eastern Anatolian Regions and Ceyhan, Asi and Southeast part of Firat‐Dicle river basins in Turkey. HighlightsAge‐group 5–9 reveals the highest morbidity rates.Hepatitis A morbidity reaches the highest in 2001, and between 2005 and 2007.Clusters mostly appear in the South‐Eastern regions of Turkey.Hepatitis A is significant in Ceyhan, Asi and Southeast of Firat‐Dicle basins.

The use of remote sensing and geographic information systems for the evaluation of river basins: a case study for Turkey, Marmara River Basin and Istanbul.

The aim of this study was to determine sensitive river basins and specific areas that urgently need planning activities for sustainable resource and environmental management. In this context, a combination of remote sensing (RS) and geographic information systems (GIS) were employed. For that purpose, a comprehensive overview of the current situation of Turkish river basins in terms of existing spatial data was provided and all tabular data gathered from the national authorities on regional basis was assessed in combination with the geometric data of Turkish river basins in a GIS environment. Considering the GIS studies that covered all 26 Turkish basins, the Marmara River Basin was selected as the model sensitive region and was studied in more detail by using 2000 dated Landsat 7 ETM mosaic satellite image. Results of this comprehensive study indicated that Istanbul, which is located in the basin under study and the largest metropolitan of Turkey, was determined as the most populated and urbanized area of the region. Istanbul was further examined to determine the expansion of urban areas over a time period of 16 years using Landsat images dated 1984, 1992 and 2000. Finally, interpretations were done by combining the demographic and statistical data on urban wastewater treatment plants to present the prevailing situation of the water treatment facilities in Istanbul. Our study not only delineated the importance of applying environmental policies correctly for the efficient installation and operation of urban wastewater treatment plants in Istanbul but also demonstrated that effective urban wastewater management is a nationwide problem in Turkey.

Prediction of Lagoons' Natural Conditions Using Satellite Data and GIS

Abstract In this study, monitoring and management of coastlines were emphasized and usage of remotely sensed data and GIS has been proposed as alternative solution to conventional studies. An example of using satellite data for depth measurement in shallow areas is given. Past morphological and hydrodynamic structures were obtained by means of Remote Sensing technique and obtained data have been transferred to GIS. Results extracted from these measurements were compared with the bathymetric map and visualized by means of GIS. Our proposal is to use remotely sensed data combined with GIS in the cases where the data obtained via ground measurements have been inadequate. It has been shown that the integrated approach can be used satisfactorily in order to predict the possible effects of a river induced parameters such as turbidity on the coasts, because the suspended material in the water can be used as the tracer material in interpretation of remotely sensed data.