The importance of spatial accuracy in characterizing stand types using remotely sensed data
This study assessed the potential use of Landsat 7 ETM+ (15 and 30 m spatial resolutions) images to estimate forest stand attributes such as development stages, crown closure and stand types. The study evaluates the performance of spatial and image classification accuracies between Landsat images (15 and 30 m spatial resolutions) and the forest cover type map (FCTM) with the spatial analysis functions of Geographical Information System (GIS). As a base study, the stand parameters were determined by forest cover type generated with high spatial accuracy of infrared color aerial photography interpretation. The study compared the performance of classification accuracies of satellite images into the forest cover type map (FCTM). The result shows that crown closure was the most successfully classified stand parameters with a 0.92 kappa statistic value and 94.2% overall accuracy assessments in 30 m resolution Landsat 7 image and 0.94 and 95.8% in 15 m resolution Landsat image, respectively. The results indicate that 15 m resolution Landsat 7 image can lead to more accurate mapping of stand type with development stages and crown closures, than 30 m resolution Landsat image according to classification accuracy. However, spatial accuracy was lower than classification accuracy in both images. Spatial analysis clearly showed that the spatial accuracy might be more important than the image accuracy in classification of satellite images to determine forest cover types. This study reveals the differences between image accuracy and spatial accuracy of stand parameters in both Landsat images. The differences were quite significant and should be taken into consideration in forest inventory and land use planning.
Key words: Image fusion, Landsat, spatial analysis, stand parameters.