[HTML][HTML] Hyperspectral and lidar data applied to the urban land cover machine learning and neural-network-based classification: A review
Rapid technological advances in airborne hyperspectral and lidar systems paved the way
for using machine learning algorithms to map urban environments. Both hyperspectral and …
for using machine learning algorithms to map urban environments. Both hyperspectral and …
Radiometric calibration of small-footprint full-waveform airborne laser scanner measurements: Basic physical concepts
W Wagner - ISPRS Journal of Photogrammetry and Remote …, 2010 - Elsevier
Small-footprint (0.2–2 m) airborne laser scanners are lidar instruments originally developed
for topographic map**. While the first airborne laser scanners only allowed determining …
for topographic map**. While the first airborne laser scanners only allowed determining …
Relevance of airborne lidar and multispectral image data for urban scene classification using Random Forests
Airborne lidar systems have become a source for the acquisition of elevation data. They
provide georeferenced, irregularly distributed 3D point clouds of high altimetric accuracy …
provide georeferenced, irregularly distributed 3D point clouds of high altimetric accuracy …
Hyperspectral and LiDAR data fusion using extinction profiles and deep convolutional neural network
This paper proposes a novel framework for the fusion of hyperspectral and light detection
and ranging-derived rasterized data using extinction profiles (EPs) and deep learning. In …
and ranging-derived rasterized data using extinction profiles (EPs) and deep learning. In …
SVM-based classification of segmented airborne LiDAR point clouds in urban areas
J Zhang, X Lin, X Ning - Remote sensing, 2013 - mdpi.com
Object-based point cloud analysis (OBPA) is useful for information extraction from airborne
LiDAR point clouds. An object-based classification method is proposed for classifying the …
LiDAR point clouds. An object-based classification method is proposed for classifying the …
Relevance assessment of full-waveform lidar data for urban area classification
Full-waveform lidar data are increasingly being available. Morphological features can be
retrieved from the echoes composing the waveforms, and are now extensively used for a …
retrieved from the echoes composing the waveforms, and are now extensively used for a …
Hyperspectral and LiDAR data classification using joint CNNs and morphological feature learning
Convolutional neural networks (CNNs) have been extensively utilized for hyperspectral
image (HSI) and light detection and ranging (LiDAR) data classification. However, CNNs …
image (HSI) and light detection and ranging (LiDAR) data classification. However, CNNs …
OPALS–A framework for Airborne Laser Scanning data analysis
A framework for Orientation and Processing of Airborne Laser Scanning point clouds,
OPALS, is presented. It is designed to provide tools for all steps starting from full waveform …
OPALS, is presented. It is designed to provide tools for all steps starting from full waveform …
[HTML][HTML] A comprehensive automated 3D approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds
Three dimensional city models are necessary for supporting numerous management
applications. For the determination of city models for visualization purposes, several …
applications. For the determination of city models for visualization purposes, several …
Contextual segment-based classification of airborne laser scanner data
Classification of point clouds is needed as a first step in the extraction of various types of geo-
information from point clouds. We present a new approach to contextual classification of …
information from point clouds. We present a new approach to contextual classification of …