Classification of wetland vegetation using aerial photographs by captive balloon cameras and aero NIR color video image, Kushiro northern wetland in Japan

Abstract

The final goal is to develop an algorithm of satellite remote sensing for classification of specific vegetation patterns in wetland using balloon photograph interpretation and aerial Near Infrared (NIR) color video images. We focused on the following definite objectives. (1) Making vegetation maps by mosaic balloon photos with high resolution and discussing about the efficiency for the classification of wetland vegetation in Kushiro wetland, located in the eastern part of Hokkaido, Japan , (2) Investigation on applicability of the balloon mosaic photos as the training data for classification of aerial NIR color video images with low resolution, (3) Classification of wetland vegetation using aerial visible and NIR color video images taken from nadir angle and 45 degree zenith angle. We extracted training data for classification of wetland vegetation on NIR color video sequence image from aerial balloon photographs taken by two captive balloons at low altitude and we got higher accuracy classification: two vegetation types in low-moor, three types in transition-moor, and five types in high-moor. NIR color video sequence image is one of the most promising tools for wetland monitoring because it has fine resolution and NIR band that is sensitive to vegetation. In consequence of this research, it concluded that availability of the high resolution training data such as balloon mosaic photos were useful to classify NIR color video images or wetland vegetation in wide range.