Results 1 to 10 of about 1,871 (181)

Factors affecting relative height and ground elevation estimations of GEDI among forest types across the conterminous USA

GIScience and Remote Sensing, 2022
The Global Ecosystem Dynamics Investigation (GEDI), a new spaceborne LiDAR system of the National Aeronautics and Space Administration (NASA), has the potential to revolutionize global measurements of vertical vegetation structure.
Mark Cochrane, Izaya Numata, Andrew Elmore   +2 more
exaly   +2 more sources

The impact of geolocation uncertainty on GEDI tropical forest canopy height estimation and change monitoring

Science of Remote Sensing, 2021
The Global Ecosystem Dynamics Investigation (GEDI) LiDAR provides new spaceborne vegetation canopy structural information including relative canopy height products defined with respect to 25 m diameter footprints. The GEDI geolocation requirement is that
David Roy, John David Armston
exaly   +3 more sources

Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest

Science of Remote Sensing, 2023
The vertical structure of forests provides important parameters for estimating aboveground biomass (AGB) and it can be measured by lidar sensors. The Global Ecosystem Dynamics Investigation (GEDI) full-waveform lidar sensor collects data systematically ...
Xiaoyang Zhang, Jean Ometto, Pedro V C Oliveira   +2 more
exaly   +3 more sources

Intercomparison of the DART model and GEDI simulator for simulating GEDI waveforms in forests

International Journal of Applied Earth Observations and Geoinformation
The launch of GEDI opens a new era of forest structure monitoring using full-waveform LiDAR from space. Simulation of GEDI waveform is of great importance for the algorithm design and forest structure metric estimation.
Ziyang Wang, Jing Liu, Yehua Sheng, Xuebo Yang   +3 more
doaj   +2 more sources

Validation and Error Minimization of Global Ecosystem Dynamics Investigation (GEDI) Relative Height Metrics in the Amazon

Remote Sensing
Global Ecosystem Dynamics Investigation (GEDI) is a relatively new technology for global forest research, acquiring LiDAR measurements of vertical vegetation structure across Earth’s tropical, sub-tropical, and temperate forests. Previous GEDI validation
Patrick Jantz, David W Roberts, Andrew Hansen   +2 more
exaly   +3 more sources

Quality Assessment of Acquired GEDI Waveforms: Case Study over France, Tunisia and French Guiana

Remote Sensing, 2021
The Global Ecosystem Dynamics Investigation (GEDI) full-waveform (FW) LiDAR instrument on board the International Space Station (ISS) has acquired in its first 18 months of operation more than 25 billion shots globally, presenting a unique opportunity ...
Jérôme Riedi, Nicolas Baghdadi, Baghdadi Nicolas   +2 more
exaly   +3 more sources

Accuracy evaluation and effect factor analysis of GEDI aboveground biomass product for temperate forests in the conterminous United States

GIScience and Remote Sensing
The Global Ecosystem Dynamics Investigation (GEDI) is expected to revolutionize the quantification of aboveground carbon at continental scales, through its unprecedented dense vertical observations of vegetation structure.
Duo Jia, Mark Cochrane, Christopher Hakkenberg   +2 more
exaly   +3 more sources

Assessing the Accuracy of GEDI Data for Canopy Height and Aboveground Biomass Estimates in Mediterranean Forests

Remote Sensing, 2021
Global Ecosystem Dynamics Investigation (GEDI) satellite mission is expanding the spatial bounds and temporal resolution of large-scale mapping applications.
Iván Dorado-Roda, Adrián Pascual, Sergio Godinho, Carlos A. Silva, Brigite Botequim, Pablo Rodríguez-Gonzálvez, Eduardo González-Ferreiro, Juan Guerra-Hernández   +7 more
doaj   +1 more source

Entrepreneurship in Africa Through the Eyes of Gedi [PDF]

SSRN Electronic Journal, 2013
Since the 1990s several new indices, including the Index of Economic Freedom, Doing Business and the Global Competitiveness Index, have been created to achieve progress in modernizing the business climates of developed and developing countries alike. These indicators, however, are focused largely on ameliorating burdens for current business, addressing
Zoltán J. Ács, László Szerb, Scott Jackson   +2 more
openaire   +1 more source

GeDi: Generative Discriminator Guided Sequence Generation [PDF]

Findings of the Association for Computational Linguistics: EMNLP 2021, 2021
While large-scale language models (LMs) are able to imitate the distribution of natural language well enough to generate realistic text, it is difficult to control which regions of the distribution they generate. This is especially problematic because datasets used for training large LMs usually contain significant toxicity, hate, bias, and negativity.
Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq R. Joty, Richard Socher, Nazneen Fatema Rajani   +6 more
openaire   +2 more sources