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Harvard Forest Data Archive
R Code and Images for Developing a Spatial Concordance Coefficient at Harvard Forest 2010Related Publications
- Lead: Ronny Vallejos, Aaron Ellison, Andrew Richardson
- Investigators: Javier Pérez
- Contact: Aaron Ellison
- Start date: 2010
- End date: 2010
- Status: completed
- Location: Prospect Hill Tract (Harvard Forest)
- Latitude: +42.53 to +42.55
- Longitude: -72.20 to -72.17
- Elevation: 280 to 420 meter
- Taxa: Pinus strobus (white pine), Quercus rubra (red oak)
- Release date: 2019
- EML file: knb-lter-hfr.322.1
- DOI: digital object identifier
- Related links:
- PhenoCam Images and Canopy Phenology at Harvard Forest since 2008
- Canopy Phenology and Greenness Indices at 13 Sites across North America 2003-2012
- Study type: short-term measurement, modeling
- Research topic: ecological informatics and modelling
- LTER core area: primary production
- Keywords: canopies, imagery, phenology, spatial variability
Concordance correlation coefficients have been developed in a variety of different contexts. This problem has been widely addressed in a non-spatial context, but here we consider a coefficient that for a fixed spatial lag allows the comparison of two spatial sequences (e.g., images). We define a spatial concordance coefficient for second-order stationary processes.
The proposed spatial concordance coefficient was explored for the bivariate Mat\'ern and Wendland covariance functions. The asymptotic normality of a sample version of the spatial concordance coefficient for an increasing domain sampling framework was established for the Wendland covariance function. Finally, we developed a local approach for estimating the concordance that uses local spatial models on non-overlapping windows.
As an illustrative example, we applied this methodology to two similar images of a deciduous forest canopy at Harvard Forest. The images were recorded with different cameras but similar fields-of-view and within minutes of each other. Our analysis showed that the local approach helped to explain a percentage of the non-spatial concordance and to learn about the decaying of it as a function of the spatial lag.
This dataset is released to the public under Creative Commons license CC BY (Attribution). Please keep the designated contact person informed of any plans to use the dataset. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the dataset must include proper acknowledgement.
Vallejos R, Ellison A, Richardson A. 2019. R Code and Images for Developing a Spatial Concordance Coefficient at Harvard Forest 2010. Harvard Forest Data Archive: HF322.
hf322-01: R code
- Compression: none
- Format: R code
- Type: R code
hf322-02: canopy images
- Compression: zip
- Format: zip
- Type: zip