Results 1 to 10 of about 15,050 (225)

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.
Andrew Elmore
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 P Roy, John David Armston
exaly   +3 more sources

Identifikasi Barcode Tumbuhan Gedi Merah (Abelmoschus Manihot L. Medik) Dan Gedi Hijau (Abelmoschus Moschatus) Berdasarkan Gen MatK [PDF]

Jurnal MIPA, 2014
Gedi (Abelmoschus L.) merupakan tumbuhan tropis. Tumbuhan ini memilki efek farmakologis. Masyarakat Minahasa mengkonsumsi daun gedi yang direbus tanpa diberi bumbu sebagai obat tradisional untuk menurunkan kadar kolesterol, antihipertensi dan ...
Fattah, Y. R. (Yusuf), Kamu, V. S. (Vanda), Momuat, L. I. (Lidya), Runtuwene, M. R. (Max)   +3 more
core   +4 more sources

A live cell biosensor protocol for high-resolution screening of therapy-resistant cancer cells. [PDF]

PLoS ONE
The Genetically Encoded Death Indicator (GEDI) is a ratiometric, dual-fluorescence biosensor that enables real-time detection of cell death through calcium influx.
Viral D Oza, Colin S Williams, Jessica S Blackburn   +2 more
doaj   +2 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

Entrepreneurship in Africa through the Eyes of GEDI [PDF]

SSRN Electronic Journal, 2013
Since the 1990s, several new indices like the Index of Economic Freedom, Doing Business, Global Competitiveness Index, have been created to achieving real progress in modernizing the business climates of developed and developing countries alike.
Acs, Zoltan, J, Jackson, Scott, Szerb, Laszlo   +2 more
core   +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, Cangjiao Wang, Christopher R. Hakkenberg, Izaya Numata, Andrew J. Elmore, Mark A. Cochrane   +5 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

Accuracy Assessment and Impact Factor Analysis of GEDI Leaf Area Index Product in Temperate Forest

Remote Sensing, 2023
The leaf area index (LAI) is a vital parameter for quantifying the material and energy exchange between terrestrial ecosystems and the atmosphere. The Global Ecosystem Dynamics Investigation (GEDI), with its mission to produce a near-global map of forest
Cangjiao Wang, Duo Jia, Shaogang Lei, Izaya Numata, Luo Tian   +4 more
doaj   +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.
Krause, Ben, Gotmare, Akhilesh Deepak, McCann, Bryan, Keskar, Nitish Shirish, Joty, Shafiq, Socher, Richard, Rajani, Nazneen Fatema   +6 more
openaire   +2 more sources