Observation Instance

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    "ob_id": 27346,
    "uuid": "275dd9bd0a9f42ff8b226c542b16a772",
    "title": "Weighing trees with lasers project: terrestrial laser scanner data; Peru Madre De Dios Tambopata National Reserve (Plot TAM-05),  May 2017",
    "abstract": "This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations which, have been re-surveyed at different times. This plot site was situated in Peru Madre De Dios Tambopata National Reserve. The plot site had the following geographical features; Moisture type: Moist, Elevation: Lowland, Edaphic Type: Terra Firme, Composition Mixed Forrest , Substrate Geology: Pre-Holocence, Forrestry: Old-growth.\r\n\r\nThe project scanned all trees in the  permanent sample plot (PSP) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total).  The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents, or whether they differ significantly, and require continental level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB (Above Ground Biomass) from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI (Global Ecosystem Dynamics Investigation Lidar) missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data including: UAVs (unmanned aerial vehicle) for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.",
    "keywords": "Terrestrial Laser Scanner, data; Peru Madre De Dios Tambopata National Reserve , Moisture type: Moist, Elevation: Lowland, Edaphic Type: Terra Firme, Composition Mixed Forrest , Substrate Geology: Pre-Holocence, Forrestry: Old-growth",
    "publicationState": "published",
    "dataPublishedTime": "2025-06-16T10:37:24",
    "doiPublishedTime": null,
    "updateFrequency": "",
    "status": "completed",
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        "volume": 57084831882,
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    "dataLineage": "Provided by Andrew Burt UCL to  CEDA for publication",
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    "language": "English",
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