Results 11 to 20 of about 2,046 (182)

Parameter Simulation and Design of an Airborne Hyperspectral Imaging LiDAR System

Remote Sensing, 2021
With continuous technological development, the future development trend of LiDAR in the field of remote sensing and mapping is to obtain the elevation and spectral information of ground targets simultaneously.
Liyong Qian, Decheng Wu, Dong Liu, Shalei Song, Shuo Shi, Wei Gong, Le Wang   +6 more
doaj   +1 more source

Identification of tree species based on the fusion of UAV hyperspectral image and LiDAR data in a coniferous and broad-leaved mixed forest in Northeast China

Frontiers in Plant Science, 2022
Rapid and accurate identification of tree species via remote sensing technology has become one of the important means for forest inventory. This paper is to develop an accurate tree species identification framework that integrates unmanned airborne ...
Hao Zhong, Wenshu Lin, Haoran Liu, Nan Ma, Kangkang Liu, Rongzhen Cao, Tiantian Wang, Zhengzhao Ren   +7 more
doaj   +1 more source

Estimation of the fraction of absorbed photosynthetically active radiation (fPAR) in maize canopies using LiDAR data and hyperspectral imagery. [PDF]

PLoS ONE, 2018
Accurate estimation of the fraction of absorbed photosynthetically active radiation (fPAR) for maize canopies are important for maize growth monitoring and yield estimation.
Haiming Qin, Cheng Wang, Kaiguang Zhao, Xiaohuan Xi   +3 more
doaj   +1 more source

Hyperspectral and Lidar Data Applied to the Urban Land Cover Machine Learning and Neural-Network-Based Classification: A Review

Remote Sensing, 2021
Rapid technological advances in airborne hyperspectral and lidar systems paved the way for using machine learning algorithms to map urban environments.
Agnieszka Kuras, Maximilian Brell, Jonathan Rizzi, Ingunn Burud   +3 more
doaj   +1 more source

CLASSIFIER FUSION OF HYPERSPECTRAL AND LIDAR REMOTE SENSING DATA FOR IMPROVEMENT OF LAND COVER CLASSIFCATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013
The interest in the joint use of remote sensing data from multiple sensors has been remarkably increased for classification applications. This is because a combined use is supposed to improve the results of classification tasks compared to single-data ...
B. Bigdeli, F. Samadzadegan, P. Reinartz
doaj   +1 more source

Lidar-Driven Spatial Regularization for Hyperspectral Unmixing [PDF]

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Only a few research works consider LiDAR data while conducting hyperspectral image unmixing. However, the digital surface model derived from LiDAR can provide meaningful information, in particular when spatially regularizing the inverse problem underlain by spectral unmixing.
Uezato, Tatsumi, Fauvel, Mathieu, Dobigeon, Nicolas   +2 more
openaire   +3 more sources

SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages.
Y. Pang, Z. Li
doaj   +1 more source

A Novel Dual-Encoder Model for Hyperspectral and LiDAR Joint Classification via Contrastive Learning

Remote Sensing, 2023
Deep-learning-based multi-sensor hyperspectral image classification algorithms can automatically acquire the advanced features of multiple sensor images, enabling the classification model to better characterize the data and improve the classification ...
Haibin Wu, Shiyu Dai, Chengyang Liu, Aili Wang, Yuji Iwahori   +4 more
doaj   +1 more source

Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data

GIScience & Remote Sensing, 2023
Recent growth in unmanned aerial vehicle (UAV) technology have promoted the detailed mapping of individual tree species. However, the in-depth mining and comprehending of the significance of features derived from high-resolution UAV data for tree species
Ying Quan, Mingze Li, Yuanshuo Hao, Jianyang Liu, Bin Wang   +4 more
doaj   +1 more source

Hyperspectral Point Cloud Projection for the Semantic Segmentation of Multimodal Hyperspectral and Lidar Data with Point Convolution-Based Deep Fusion Neural Networks

Applied Sciences, 2023
The fusion of dissimilar data modalities in neural networks presents a significant challenge, particularly in the case of multimodal hyperspectral and lidar data.
Kevin T. Decker, Brett J. Borghetti
doaj   +1 more source