Global geographic and feature space coverage of temperature data in the context of spatio-temporal interpolation
Abstract
This article highlights the results of an assessment of representation and usability of global temperature station data for global spatio-temporal analysis. Datasets from the Global Surface Summary of Day (GSOD) and the European Climate Assessment & Dataset (ECA&D) were merged and consisted of 10,695 global stations for the year 2011. Three aspects of data quality were considered: (a) representation in the geographical domain, (b) representation in the feature space (based on the MaxEnt method), and
Keywords:
GSOD / MaxEnt / MODIS LST / Spatio-temporal analysis / Daily temperature interpolation / Global space-time kriging modelSource:
Spatial Statistics, 2015, 14, 22-38Publisher:
- Elsevier
Projects:
- Studying climate change and its influence on environment: impacts, adaptation and mitigation (RS-43007)
- The role and implementation of the national spatial plan and regional development documents in renewal of strategic research, thinking and governance in Serbia (RS-47014)
- Croatian Science Foundation 2831
- Spatial, environmental, energy and social aspects of developing settlements and climate change - mutual impacts (RS-36035)
DOI: 10.1016/j.spasta.2015.04.005
ISSN: 2211-6753
WoS: 000368912700003
Scopus: 2-s2.0-84947862977
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