Comparison of Atmospheric Correction Methods in Mapping Timber Volume with Multitemporal Landsat Images in Kainuu, Finland

Using remote sensing to monitor large forest areas usually requires large field datasets. The need for extensive data collection can be reduced through interpretation of several images simultaneously. This study focused evaluating the accuracy and functionality of stand volume models in overlapping multi-temporal images that could form large areas covering a mosaic of scenes. Various atmospheric correction methods were tested to generalize field information outside the coverage of single images. A dataset consisting of three