Discrimination of crown closure of forest ecosystems using different remotely sensed data: a case study of Kızılcasu planning unit

Discrimination of crown closure of forest ecosystems using different remotely sensed data: a case study of Kızılcasu planning unit

The objective of this study was to estimate crown closure using different satellite images, Landsat TM and QuickBird. As reference data, forest cover type map were used in the study, and two different methods were used to determine the crown closure. First, to classify crown closures from satellite images, a supervised classification method was used. Second, the linear mixture modeling (LMM) fuzzy classification method was used to determine the stand crown closure. Landsat TM and QuickBird data were used in this frame. The training dataset was derived from a fine spatial resolution land cover classification of QuickBird imagery. This classification was combined to estimate the percentage crown closure in Landsat TM spatial resolution. The research also focused on classifying and mapping the crown closure classes with the spatial analysis functions of geographical information systems (GIS). The results showed that the QuickBird image had the highest classification accuracies compared to the spatial analyses results of Landsat TM and fuzzy classification.

The objective of this study was to estimate crown closure using different satellite images, Landsat TM and QuickBird. As reference data, forest cover type map were used in the study, and two different methods were used to determine the crown closure. First, to classify crown closures from satellite images, a supervised classification method was used. Second, the linear mixture modeling (LMM) fuzzy classification method was used to determine the stand crown closure. Landsat TM and QuickBird data were used in this frame. The training dataset was derived from a fine spatial resolution land cover classification of QuickBird imagery. This classification was combined to estimate the percentage crown closure in Landsat TM spatial resolution. The research also focused on classifying and mapping the crown closure classes with the spatial analysis functions of geographical information systems (GIS). The results showed that the QuickBird image had the highest classification accuracies compared to the spatial analyses results of Landsat TM and fuzzy classification.