Results 1 to 10 of about 2,025 (161)

Remote Nanoscopy with Infrared Elastic Hyperspectral Lidar. [PDF]

Adv Sci (Weinh), 2023
AbstractMonitoring insects of different species to understand the factors affecting their diversity and decline is a major challenge. Laser remote sensing and spectroscopy offer promising novel solutions to this. Coherent scattering from thin wing membranes also known as wing interference patterns (WIPs) have recently been demonstrated to be species ...
Müller L, Li M, Månefjord H, Salvador J, Reistad N, Hernandez J, Kirkeby C, Runemark A, Brydegaard M.   +8 more
europepmc   +6 more sources

Estimating the Biomass of Maize with Hyperspectral and LiDAR Data [PDF]

Remote Sensing, 2016
The accurate estimation of crop biomass during the growing season is very important for crop growth monitoring and yield estimation. The objective of this paper was to explore the potential of hyperspectral and light detection and ranging (LiDAR) data ...
Cheng Wang, Sheng Nie, Xiaohuan Xi, Shezhou Luo, Xiaofeng Sun   +4 more
doaj   +2 more sources

FULL WAVEFORM ACTIVE HYPERSPECTRAL LIDAR [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
We have developed a prototype full waveform hyperspectral LiDAR and investigated its potential for remote sensing applications. Traditionally hyperspectral remote sensing is based on passive measurement of sunlit targets.
T. Hakala, J. Suomalainen, S. Kaasalainen   +2 more
doaj   +3 more sources

Two-channel Hyperspectral LiDAR with a Supercontinuum Laser Source [PDF]

Sensors, 2010
Recent advances in nonlinear fiber optics and compact pulsed lasers have resulted in creation of broadband directional light sources. These supercontinuum laser sources produce directional broadband light using cascaded nonlinear optical interactions in an optical fibre framework.
Juha Hyyppä, Teemu Hakala, Sanna Kaasalainen   +2 more
exaly   +5 more sources

Tree-Species Classification in Subtropical Forests Using Airborne Hyperspectral and LiDAR Data

Remote Sensing, 2017
Accurate classification of tree-species is essential for sustainably managing forest resources and effectively monitoring species diversity. In this study, we used simultaneously acquired hyperspectral and LiDAR data from LiCHy (Hyperspectral, LiDAR and ...
Lin Cao, Xin Shen
exaly   +3 more sources

Nitrogen concentration estimation with hyperspectral LiDAR [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013
Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands require more efficient and accurate methods.
O. Nevalainen, T. Hakala, J. Suomalainen, J. Suomalainen, S. Kaasalainen   +4 more
doaj   +3 more sources

Value of hyperspectral data for wall to wall wetland vegetation mapping in heterogeneous landscapes [PDF]

Scientific Reports
Remote sensing is increasingly employed today for the creation of wall-to-wall vegetation maps of protected areas. The main objective of this study was to evaluate whether it is feasible to develop a remote sensing-based wall-to-wall vegetation map of ...
Anna Jarocińska, Dominik Kopeć, Jan Niedzielko, Anna Halladin-Dąbrowska, Marlena Kycko   +4 more
doaj   +2 more sources

A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration.
A. Roncat, C. Briese, C. Briese, N. Pfeifer   +3 more
doaj   +3 more sources

Hypergraph Convolution Network Classification for Hyperspectral and LiDAR Data. [PDF]

Sensors (Basel)
Conventional remote sensing classification approaches based on single-source data exhibit inherent limitations, driving significant research interest in improved multimodal data fusion techniques. Although deep learning methods based on convolutional neural networks (CNNs), transformers, and graph convolutional networks (GCNs) have demonstrated ...
Wang L, Deng S.
europepmc   +4 more sources

Estimating Aboveground Carbon Stock at the Scale of Individual Trees in Subtropical Forests Using UAV LiDAR and Hyperspectral Data

Remote Sensing, 2021
Accurate estimation of aboveground carbon stock for individual trees is important for evaluating forest carbon sequestration potential and maintaining ecosystem carbon balance.
Haiming Qin, Weiqi Zhou, Yang Yao, Weimin Wang   +3 more
doaj   +1 more source