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
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | December 31, 2022 |
| Published in Issue | Year 2022 |
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