Results 171 to 180 of about 223,998 (212)

Fusion of Multispectral LiDAR and Hyperspectral Imagery

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
This paper presents a technique for the fusion of multispectral LiDAR and hyperspectral data. The proposed method is based on the fusion of the features of multispectral LiDAR and hyperspectral data projected in two different subspaces. First, the spatial features are extracted from both data using morphological filters.
Rasti, B., Ghamisi, P., Gloaguen, R.
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Probability Fusion for Hyperspectral and LiDAR Data

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
In this paper, a new probability fusion strategy is proposed for hyperspectral and LiDAR data classification, which is inspired by the representation residual fusion strategy in our previous work. Unlike the residual fusion strategy utilizes a collaborative representation classifier, the probability fusion strategy deploys a deep residual network (DRN).
Chiru Ge, Qian Du 0001
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Hyperspectral and lidar data integration and classification

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015
Light Detection and Ranging (LiDAR) is a technology used in different topic (mapping, urban land cover, agriculture, forestry, etc.). The great potential of LiDAR data lies in its high accuracy in the measurement of heights. Hyperspectral images, which comprise hundreds of (nearly contiguous) spectral channels, can also have spatial resolution of up to
Maria Angeles Garcia-Sopo, Aurora Cuartero, Pablo García Rodríguez, Antonio J. Plaza   +3 more
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Active hyperspectral LIDAR methods for object classification

2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010
We have studied the fusion of active hyperspectral and range (LIDAR) data to investigate the concept of an active hyperspectral LIDAR and its potential applications in the remote sensing of vegetation. We have built two prototype instruments using the newly developed supercontinuum laser technique providing a continuous spectrum, which has then been ...
Sanna Kaasalainen, Juha Suomalainen, Teemu Hakala, Yuwei Chen 0005, Esa Räikkönen, Eetu Puttonen, Harri Kaartinen   +6 more
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Research on simulating hyperspectral lidar

SPIE Proceedings, 2015
Hyperspectral Lidar using supercontinuum laser as light source, applying spectroscopic technology gets backscattered reflectance of different wavelengths, and can acquire both the geometry and spectral information on the target. In the vegetation detection by using Hyperspectral Lidar, through refusing 3d and spectral data, we can get the physical ...
Feng Li, Jing-guo Zhu, Meng-lin Li, Ru-qing Liu   +3 more
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Hyperspectral and LiDAR Classification With Semisupervised Graph Fusion

IEEE Geoscience and Remote Sensing Letters, 2020
To fuse hyperspectral and Light Detection And Ranging (LiDAR), we propose a semisupervised graph fusion (SSGF) approach. We apply morphological filters to LiDAR and the first few components of hyperspectral data to model the height and spatial information, respectively.
Junshi Xia, Wenzhi Liao, Peijun Du
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Integrated LiDAR and Hyperspectral

2013
Integrating LiDAR data and hyperspectral imagery is an area of active research in remote sensing, inclusive of application for coastal and coral reef mapping. These two technologies can be combined in a number of different ways, and at a number of stages of processing to produce benthic classification maps.
Jennifer M. Wozencraft, Joong Yong Park
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Tree species classification with hyperspectral imaging and lidar

2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016
This paper presents a new method to discriminate between spruce, pine and birch, which are the dominating tree species in Norwegian forests. For this purpose, simultaneously acquired airborne laser scanning (ALS) and hyperspectral data are used. The laser scanning data was used to mask pixels with low or no vegetation in the hyperspectral data.
Øystein Rudjord, Øivind Due Trier
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Predicting year of plantation with hyperspectral and lidar data

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
This paper introduces a methodology for predicting the year of plantation (YOP) from remote sensing data. The application has important implications in forestry management and inventorying. We exploit hyperspectral and LiDAR data in combination with state-of-the-art machine learning classifiers.
Adrià Descals, Luis Alonso 0002, Gustau Camps-Valls   +2 more
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LiDAR-guided analysis of airborne hyperspectral data

2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
This paper describes a new framework to the collection and fusion of multisensor airborne LiDAR and hyperspectral data. We describe a data fusion philosophy that provides a spatially precise positioning of hyperspectral data based on discrete first and last return LiDAR data.
K. Olaf Niemann, Gordon Frazer, Rafael Loos, Fabio Visintini   +3 more
openaire   +1 more source