AUTOMATIC TREE-CROWN DETECTION IN CHALLENGING SCENARIOS
Abstract
In this paper, a new procedure for individual tree detection and modeling is presented. The input of this procedure consists of a normalized
digital surface model NDSM, and a possibly error-prone classification result. The procedure is modular so that the functionality,
the advantages and the disadvantages for every single module will be explained. The most important technical contributions of the
paper are: Employing watershed transformation combined with classification results, applying hotspots detectors for identifying treetops
in groups of trees, and correcting NDSM by detecting and geometric reconstruction of small anomalies, such as earth walls. Two
minor contributions are made up by a detailed literature research on available methods for individual tree detection and estimation of
tree-crowns for clearly identified trees in order to reduce arbitrariness by assigning trees to one of the few types in the output model.
Keywords
Engineering (General). Civil engineering (General)
Technology
Literature (General)
environmental effects of industries and plants
renewable energy sources
environmental sciences
economics as a science
language and literature
applied optics. photonics
sociology (general)
communication. mass media
special aspects of education
advertising
Citation
ID:
86038
References
Blockchain Verification
Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
86038
Unique Identifier:
10ea04e586311910796f174f6c0e8e2a
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
Creates 1,000,000 NFT tokens for this article
Token Features:
- ERC-1155 Standard NFT
- 1 Million Supply per Article
- Transferable via MetaMask
- Permanent Blockchain Record
Scan with Saymatik Web3.0 Wallet