Výsledky vyhledávání

Spatial and Spatiotemporal Interpolation / Prediction using Ensemble Machine Learning

Autor: Hengl, T., Parente, L., Bonannella, C.

This R tutorial explains step-by-step how to use Ensemble Machine Learning to generate predictions (maps) from 2D, 3D, 2D+T training (point) datasets. We show functionality to do automated benchmarking for spatial/spatiotemporal prediction problems,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fa4539241d39a70d08fe36778e4eba3

Zobrazit plný text záznamu

SoilKsatDB: global compilation of soil saturated hydraulic conductivity measurements for geoscience applications

A total of 13,258 Ksat measurements from 1,908 sites were assembled from the published literature and other sources, standardized, and quality-checked in order to obtain a global database of soil saturated hydraulic conductivity (SoilKsatDB). The Soi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dris___00893::472cf02e6af21580cc5ac9917e9ef57b
https://doi.org/10.5281/zenodo.3752721

Zobrazit plný text záznamu

Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution

Autor: Hengl, Tomislav

Potential distribution of biomes(Potential Natural Vegetation) at 250 m spatial resolution based on theBIOME 6000 data set (8057 modern pollen-based site reconstructions). Predicted at 250 m using Ensemble Machine Learning and relief and climatevaria

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5632857e8c7882e6f27180b5e7e4db7f

Zobrazit plný text záznamu

Basic Soil Data Requirements for Process-Based Crop Models as a Basis for Crop Diversification

Autor: Tengku Adhwa Syaherah Tengku Mohd Suhairi, Ebrahim Jahanshiri, A.S. Karunaratne, Eranga M. Wimalasiri, Lal P. Vidhanarachchi, Sayed Azam-Ali, Hasika Udayangani, R. B. Mapa

Publikováno v: Sustainability, Vol 12, Iss 7781, p 7781 (2020)
Sustainability
Volume 12
Issue 18

Data from global soil databases are increasingly used for crop modelling, but the impact of such data on simulated crop yield has not been not extensively studied. Accurate yield estimation is particularly useful for yield mapping and crop diversific

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5adcb7ddf3b4d346c86f0164914ff123
https://doi.org/10.3390/su12187781

Zobrazit plný text záznamu

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Towards initiating OpenLandMap founded on citizens’ science: The current status of land use features of OpenStreetMap in Europe

Autor: Jamal Jokar Arsanjani, Eric Vaz, Mohamed Bakillah, Peter Mooney

Publikováno v: Repositori Universitat Jaume I
Universitat Jaume I
Aalborg University

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014. Land use invento

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::04b093534da7e2ad545deb815e9a1893

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání