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Title: Landscape Characterization and Representativeness Analysis for Understanding Sampling Network Coverage

Sampling networks rarely conform to spatial and temporal ideals, often comprised of network sampling points which are unevenly distributed and located in less than ideal locations due to access constraints, budget limitations, or political conflict. Quantifying the global, regional, and temporal representativeness of these networks by quantifying the coverage of network infrastructure highlights the capabilities and limitations of the data collected, facilitates upscaling and downscaling for modeling purposes, and improves the planning efforts for future infrastructure investment under current conditions and future modeled scenarios. The work presented here utilizes multivariate spatiotemporal clustering analysis and representativeness analysis for quantitative landscape characterization and assessment of the Fluxnet, RAINFOR, and ForestGEO networks. Results include ecoregions that highlight patterns of bioclimatic, topographic, and edaphic variables and quantitative representativeness maps of individual and combined networks.
Authors:
; ; ;
Publication Date:
OSTI Identifier:
1148699
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Dataset
Data Type:
Numeric Data
Research Org:
Climate Change Science Institute (CCSI), Oak Ridge National Laboratory (ORNL), Oak Rdige, TN (US)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Contributing Orgs:
PNL, BNL,ANL,ORNL
Country of Publication:
United States
Availability:
ORNL
Language:
English
Subject:
54 Environmental Sciences; CCSI; climate datasets; Landscape Characterization; Representativeness Analysis; ORNL