Published November 15, 2022
| Version
v1
Dataset
Open
Braila - Phenological Annual Summary Statistics - 2019/2020
Description
Phenological Annual Summary Statistics based on Ecosystem Functional Attribute framework. The result are based on S2 interpolated with a bayesian implementation of Harmonic Model.
Methods
Details of the method can be found in Vicario S, Adamo M, Alcaraz-Segura D, Tarantino C (2019) Bayesian Harmonic Modelling of Sparse and Irregular Satellite Remote Sensing Time Series of Vegetation Indexes: A Story of Clouds and Fires. Remote Sens 12:83 . doi: 10.3390/rs12010083Technical info
The phenology is not a scalar variable but it is an ensamble of sub-variables all based on MCARI2 vegetation index and for each one two statistics are given: expected value (mean) and a mask for all pixel with standard deviation of uncertianities larger than 10% the mean (CVmask) within the general name rule proposed: locality_variable_timestamp.extension variable formed in: Phenology-SubvariableStatistics The subvariables are: mean: mean value across the year - values range between 0-0.5 stdintra: standard deviation of the value across the year - values range between 0-0.05 maxpos: day of the year of the maximum value - values range between 0-0.5 sdinter: standard deviation across years - values range between 0-0.05 The statistics are: mean: Expected value of the subvariable across 100 simulation CVmask: 0-1 mask with value 1 for pixel with less than 10% of standard deviation compared to the mean The timestamp refer to a year or to two yearsFiles
Braila - Phenological AnnuaSummaryStatistics-20192020.zip
Files
(1.2 GB)
| Name | Size | Download all |
|---|---|---|
|
Checksum: md5:276e0a413cd83a561bb40fc43e754e93
PID: http://hdl.handle.net/11304/d2675c99-0f67-4d40-829b-6b2c0b45680a |
1.2 GB | Preview Download |
Additional details
Identifiers
- B2SHARE Legacy Record ID
- 6436f257b9e44c3c81e614e6d68c5083
LTER metadata
- Metadata URL
- https://deims.org/d4854af8-9d9f-42a2-af96-f1ed9cb25712