This thesis presents a way to generate a Digital Terrain Model (dtm) from a Digital Surface Model (dsm) and multi spectral images (including the Near Infrared (nir) color band). An Artificial Neural Network (ann) is used to pre-classify the dsm and multi spectral images. This in turn is used to filter the dsm to a dtm. The use of an ann as a classifier provided good results. Additionally, the addition of the nir color band resulted in an improvement of the accuracy of the classifier. Using the classifier, a dtm was easily extracted without removing natural edges or height variations in the forests and cities. These challenges are handled with great satisfaction as compared to earlier methods.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-133337 |
Date | January 2016 |
Creators | Tapper, Gustav |
Publisher | Linköpings universitet, Datorseende |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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