Deep-Learning-Based Classification for DTM Extraction from ALS Point Cloud
نویسندگان
چکیده
منابع مشابه
Deep-Learning-Based Classification for DTM Extraction from ALS Point Cloud
Airborne laser scanning (ALS) point cloud data are suitable for digital terrain model (DTM) extraction given its high accuracy in elevation. Existing filtering algorithms that eliminate non-ground points mostly depend on terrain feature assumptions or representations; these assumptions result in errors when the scene is complex. This paper proposes a new method for ground point extraction based...
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This paper presents an automated and effective framework for classifying airborne laser scanning (ALS) point clouds. The framework is composed of four stages: (i) step-wise point cloud segmentation, (ii) feature extraction, (iii) Random Forests (RF) based feature selection and classification, and (iv) post-processing. First, a step-wise point cloud segmentation method is proposed to extract thr...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2016
ISSN: 2072-4292
DOI: 10.3390/rs8090730