Detection of the Mineral Presence and Its Effects on Different Tree Species Using Drone Photogrammetry and Remote Sensing Methods

Abstract

It is expected that the vegetation, especially the tree roots, will be affected by the underground mines that may be discovered and have different spectral characteristics. In particular, it is possible for forest areas to be more frequent and stronger by being fed from metallic mines that are mineralized in a long process underground. For this purpose, the study was carried out in a mining area with a licensed gold and copper mineralization located in the west of Amasya province borders. Drone Photogrammetry has been studied to clearly classify the trees in the forest with dense and steep geography in the region. The spectral anomaly of tree species was investigated by using the ASTER satellite image with high spectral resolution of the region. With remote sensing methods such as SAVI, NDVI and supervised classification, satellite images were enriched to reach potential ore-intensive areas. The slope analysis was performed by creating a digital terrain model for the region, which geography is very rough and steep, and it was examined by considering tree height values from different angles. Tree species classified by the Spectral Correlation Mapping method were also evaluated together with their spectral signatures.

Keywords

• Remote sensing
• Drone photogrammetry
• GIS