PNV - Probability distribution for Abies alba

Open data API in a single place

Provided by The GeoHarmonizer project consortium

Get early access to PNV - Probability distribution for Abies alba API!

Let us know and we will figure it out for you.

Dataset information

Country of origin
Updated
Created
Available languages
English
Keywords
Vegetation, geoharvester, Europe, Geoharmonizer, geodata
Quality scoring
100

Dataset description

Overview: Potential Natural Vegetation (PNV): potential probability of occurrence for the Silver fir from 2018 to 2020 Traceability (lineage): This is an original dataset produced with a machine learning framework which used a combination of point datasets and raster datasets as inputs. Point dataset is a harmonized collection of tree occurrence data, comprising observations from National Forest Inventories (EU-Forest), GBIF and LUCAS. The complete dataset is available on Zenodo. Raster datasets used as input are: monthly time series air and surface temperature and precipitation from a reprocessed version of the Copernicus ERA5 dataset; long term averages of bioclimatic variables from CHELSA; elevation, slope and other elevation-derived metrics and long term monthly averages snow probability. For a more comprehensive list refer to Bonannella et al. (2022) (in review, preprint available at: https://doi.org/10.21203/rs.3.rs-1252972/v1). Scientific methodology: Probability and uncertainty maps were the output of a spatiotemporal ensemble machine learning framework based on stacked regularization. Three base models (random forest, gradient boosted trees and generalized linear models) were first trained on the input dataset and their predictions were used to train an additional model (logistic regression) which provided the final predictions. More details on the whole workflow are available in the listed publication. Usability: Probability maps are particularly useful when compared with existing products of potential distribution of species or when combined with maps of realized distribution: gaps in potential and realized distribution can be identified and used as information for future programs of tree planting or forest restoration. Uncertainty quantification: Uncertainty is quantified by taking the standard deviation of the probabilities predicted by the three components of the spatiotemporal ensemble model. Data validation approaches: Distribution maps were validated using a spatial 5-fold cross validation following the workflow detailed in the listed publication. Completeness: The raster files perfectly cover the entire Geo-harmonizer region as defined by the landmask raster dataset available here. Consistency: Areas which are outside of the calibration area of the point dataset (Iceland, Norway) usually have high uncertainty values. This is not only a problem of extrapolation but also of poor representation in the feature space available to the model of the conditions that are present in this countries. Positional accuracy: The rasters have a spatial resolution of 30m. Temporal accuracy: The maps cover the period 2018 - 2020 Thematic accuracy: Both probability and uncertainty maps contain values from 0 to 100: in the case of probability maps, they indicate the probability of occurrence of a single individual of the target species, while uncertainty maps indicate the standard deviation of the ensemble model.
Build on reliable and scalable technology
Revolgy LogoAmazon Web Services LogoGoogle Cloud Logo
FAQ

Frequently Asked Questions

Some basic informations about API Store ®.

Operation and development of APIs are currently fully funded by company Apitalks and its usage is for free.
Yes, you can.
All important information such as time of last update, license and other information are in response of each API call.
In case of major update that would not be compatible with previous version of API, we keep for 30 days both versions so you will have enough time to transfer to new version. We will inform you about the changes in advance by e-mail.

Didn't find the API you need?

Let us know and we will figure it out for you.

API Store provides access to European Open Data via scalable and reliable REST API interface.
Copyright © 2024. Made with ♥ by Apitalks