Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion-Reference-Cited by-同舟云学术

Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion

Published:2012-09 Issue: Volume:124 Page:454-465
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Asner Gregory P.,Knapp David E.,Boardman Joseph,Green Robert O.,Kennedy-Bowdoin Ty,Eastwood Michael,Martin Roberta E.,Anderson Christopher,Field Christopher B.

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference75 articles.

1. Tropical forest carbon assessment: Integrating satellite and airborne mapping approaches;Asner;Environmental Research Letters,2009

2. Carnegie Airborne Observatory: In-flight fusion of hyperspectral imaging and waveform light detection and ranging (LiDAR) for three-dimensional studies of ecosystems;Asner;Journal of Applied Remote Sensing,2007

3. Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR;Asner;Remote Sensing of Environment,2008

4. Combined effects of climate and land-use change on the future of humid tropical forests;Asner;Conservation Letters,2010

5. A biogeophysical approach for automated SWIR unmixing of soils and vegetation;Asner;Remote Sensing of Environment,2000

Cited by 275 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On-orbit calibration and performance of the EMIT imaging spectrometer;Remote Sensing of Environment;2024-03

2. Earth observation applications for urban mapping and monitoring: research prospects, opportunities and challenges;Earth Observation in Urban Monitoring;2024

3. A general methodology for the quantification of crop canopy nitrogen across diverse species using airborne imaging spectroscopy;Remote Sensing of Environment;2023-12

4. Measuring Carbon Dioxide Emissions From Liquefied Natural Gas (LNG) Terminals With Imaging Spectroscopy;Geophysical Research Letters;2023-11-30

5. Semantic segmentation of methane plumes with hyperspectral machine learning models;Scientific Reports;2023-11-17