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Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA

Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can be achieved using the Normalized Difference Vegetation Index (NDVI), an indicator of greenness. However, distinguishing gradual shifts in NDVI (e.g., climate related-changes) versus direct and rapid chan...

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Autores principales: Nash, Maliha S., Wickham, James, Christensen, Jay, Wade, Timothy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261326/
https://www.ncbi.nlm.nih.gov/pubmed/30505570
http://dx.doi.org/10.3390/rs9030295
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author Nash, Maliha S.
Wickham, James
Christensen, Jay
Wade, Timothy
author_facet Nash, Maliha S.
Wickham, James
Christensen, Jay
Wade, Timothy
author_sort Nash, Maliha S.
collection PubMed
description Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can be achieved using the Normalized Difference Vegetation Index (NDVI), an indicator of greenness. However, distinguishing gradual shifts in NDVI (e.g., climate related-changes) versus direct and rapid changes (e.g., fire, land development) is challenging as changes can be confounded by time-dependent patterns, and variation associated with climatic factors. In the present study, we leveraged a method that we previously developed for a pilot study to address these confounding factors by evaluating NDVI change using autoregression techniques that compare results from univariate (NDVI vs. time) and multivariate analyses (NDVI vs. time and climatic factors) for 7,660,636 1 km × 1 km pixels comprising the 48 contiguous states of the USA, over a 25-year period (1989–2013). NDVI changed significantly for 48% of the nation over the 25-year period in the univariate analyses where most significant trends (85%) indicated an increase in greenness over time. By including climatic factors in the multivariate analyses of NDVI over time, the detection of significant NDVI trends increased to 53% (an increase of 5%). Comparisons of univariate and multivariate analyses for each pixel showed that less than 4% of the pixels had a significant NDVI trend attributable to gradual climatic changes while the remainder of pixels with a significant NDVI trend indicated that changes were due to direct factors. While most NDVI changes were attributable to direct factors like wildfires, drought or flooding of agriculture, and tree mortality associated with insect infestation, these conditions may be indirectly influenced by changes in climatic factors.
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spelling pubmed-62613262018-11-28 Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA Nash, Maliha S. Wickham, James Christensen, Jay Wade, Timothy Remote Sens (Basel) Article Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can be achieved using the Normalized Difference Vegetation Index (NDVI), an indicator of greenness. However, distinguishing gradual shifts in NDVI (e.g., climate related-changes) versus direct and rapid changes (e.g., fire, land development) is challenging as changes can be confounded by time-dependent patterns, and variation associated with climatic factors. In the present study, we leveraged a method that we previously developed for a pilot study to address these confounding factors by evaluating NDVI change using autoregression techniques that compare results from univariate (NDVI vs. time) and multivariate analyses (NDVI vs. time and climatic factors) for 7,660,636 1 km × 1 km pixels comprising the 48 contiguous states of the USA, over a 25-year period (1989–2013). NDVI changed significantly for 48% of the nation over the 25-year period in the univariate analyses where most significant trends (85%) indicated an increase in greenness over time. By including climatic factors in the multivariate analyses of NDVI over time, the detection of significant NDVI trends increased to 53% (an increase of 5%). Comparisons of univariate and multivariate analyses for each pixel showed that less than 4% of the pixels had a significant NDVI trend attributable to gradual climatic changes while the remainder of pixels with a significant NDVI trend indicated that changes were due to direct factors. While most NDVI changes were attributable to direct factors like wildfires, drought or flooding of agriculture, and tree mortality associated with insect infestation, these conditions may be indirectly influenced by changes in climatic factors. 2017 /pmc/articles/PMC6261326/ /pubmed/30505570 http://dx.doi.org/10.3390/rs9030295 Text en Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nash, Maliha S.
Wickham, James
Christensen, Jay
Wade, Timothy
Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA
title Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA
title_full Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA
title_fullStr Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA
title_full_unstemmed Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA
title_short Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA
title_sort changes in landscape greenness and climatic factors over 25 years (1989–2013) in the usa
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261326/
https://www.ncbi.nlm.nih.gov/pubmed/30505570
http://dx.doi.org/10.3390/rs9030295
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