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.

Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices.

For the past 60 years, Istanbul has been experiencing an accelerated urban expansion. This urban expansion is leading to the replacement of natural surfaces by various artificial materials. This situation has a critical impact on the environment due to the alteration of heat energy balance.

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.

Defining temporal spatial patterns of mega city Istanbul to see the impacts of increasing population.

Rapid land use change has taken place over the last few decades in Istanbul. As most of the metropolitan areas, Istanbul faces increasing problems connected to increasing population and urbanisation. In this study, temporal changes of Istanbul's land use/cover were defined using remotely sensed data and post classification change detection method.