6533b883fe1ef96bd12dddc5
RESEARCH PRODUCT
Data for: Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations
Fernando Camachosubject
Remote SensingAlgorithm Development for Remote SensingInterdisciplinary sciencesOtherRemote Sensing in Agriculturedescription
This dataset encompasses a large number (> 700) of in-situ observations over elemantary sampling units (about 20m2) of LAI (effective and actual), fAPAR and fraction of vegetation cover (fCover) collected over a network of agricultural sites during the ImagineS project (http://fp7-imagines.eu/) in the period 2013-2016. The ground dataset was collected with digital hemispherical photography (DHP), LAI2200, and AccuPAR devices following well stablished protocols in agreement with CEOS LPV good practices. The ground data is complemented with concomitant Landsat-8/OLI observations, the sun zenith angle at the acquisition and the NDVI. This results in a unique database to calibrate and validate algorithms for retrieval of biophysical variables over crops. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE
year | journal | country | edition | language |
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2021-04-25 |