Drone based Mapping and Identification of Young Spruce Stand for Semiautonomous Cleaning
| Autor: | Arto Visala, Heikki Hyyti, Issouf Ouattara |
|---|---|
| Přispěvatelé: | National Land Survey of Finland, Maanmittauslaitos |
| Rok vydání: | 2020 |
| Předmět: |
Forest inventory
Watershed 010504 meteorology & atmospheric sciences Computer science autonomous vehicle Forest management forestry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies convolutional neural network Terrain 02 engineering and technology Vegetation 15. Life on land 01 natural sciences Convolutional neural network Drone Control and Systems Engineering individual tree identification unmanned aerial vehicle RGB color model mapping 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | IFAC-PapersOnLine. 53:15777-15783 |
| ISSN: | 2405-8963 |
| Popis: | We propose a novel method to locate spruces in a young stand with a low cost unmanned aerial vehicle. The method has three stages: 1) the forest area is mapped and a digital surface model and terrain models are generated, 2) the locations of trees are found from a canopy height model using local maximum and watershed algorithms, and 3) these locations are used in a convolution neural network architecture to detect young spruces. Our result for detecting young spruce trees among other vegetation using only color images from a single RGB camera were promising. The proposed method is able to achieve a detection accuracy of more than 91%. As low cost unmanned aerial vehicles with color cameras are versatile today, the proposed work is enabling low cost forest inventory for automating forest management. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|