Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018

New solar energy facilities on public lands in the deserts of southern California are being monitored long-term to detect environmental impacts. For this purpose, we have developed a framework for detecting changes in vegetation cover region-wide using greenness index data sets from the Moderate Res...

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Main Authors: Justin Nghiem, Christopher Potter, Rebecca Baiman
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Environments
Subjects:
EVI
Online Access:https://www.mdpi.com/2076-3298/6/4/40
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spelling doaj-c98d7bb1372a42e9b7837f3f1037218a2020-11-24T21:44:34ZengMDPI AGEnvironments2076-32982019-03-01644010.3390/environments6040040environments6040040Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018Justin Nghiem0Christopher Potter1Rebecca Baiman2NASA Ames Research Center, Moffett Field, CA 94035, USANASA Ames Research Center, Moffett Field, CA 94035, USANASA Ames Research Center, Moffett Field, CA 94035, USANew solar energy facilities on public lands in the deserts of southern California are being monitored long-term to detect environmental impacts. For this purpose, we have developed a framework for detecting changes in vegetation cover region-wide using greenness index data sets from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. This study focused on three sites, Joshua Tree National Park (JOTR), Mojave National Preserve (MOJA), and a proximal group of solar energy Development Focus Areas (DFAs). Three MODIS vegetation indices (VIs), the normalized difference (NDVI), enhanced (EVI), and soil-adjusted (SAVI), all at 250-m spatial resolution, were evaluated using the Breaks for Additive Season and Trend (BFAST) methodology to estimate significant time series shifts (“breakpoints„) in green vegetation cover, from February 2000 to May 2018. The sample cross-correlation function with local precipitation records and comparison with timing of wildfires near the study sites for breakpoint density (proportion of area with a breakpoint) showed that NDVI had the strongest response and hence greatest sensitivity to these major disturbances compared to EVI and SAVI, supporting its use over the other VIs for subsequent analysis. Time series of NDVI breakpoint change densities for individual solar energy DFAs did not have a consistent vegetation response following construction. Bootstrap-derived 95% confidence intervals show that the DFAs have significantly larger kurtosis and standard deviation in positive NDVI breakpoint distribution than protected National Park System (NPS) sites, but no significant difference appeared in the negative distribution among all sites. The inconsistent postconstruction NDVI signal and the large number of detected breakpoints across all three sites suggested that the largest shifts in greenness are tied to seasonal and total annual precipitation amounts. Further results indicated that existing site-specific conditions are the main control on vegetation response, mostly driven by the history of human disturbances in DFAs. Although the results do not support persistent breakpoints in solar energy DFAs, future work should seek to establish links between statistical significance and physical significance through ground-based studies to provide a more robust interpretation.https://www.mdpi.com/2076-3298/6/4/40MODISNDVIvegetation coverSAVIEVIMojave DesertLower Colorado Desertprecipitation
collection DOAJ
language English
format Article
sources DOAJ
author Justin Nghiem
Christopher Potter
Rebecca Baiman
spellingShingle Justin Nghiem
Christopher Potter
Rebecca Baiman
Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018
Environments
MODIS
NDVI
vegetation cover
SAVI
EVI
Mojave Desert
Lower Colorado Desert
precipitation
author_facet Justin Nghiem
Christopher Potter
Rebecca Baiman
author_sort Justin Nghiem
title Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018
title_short Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018
title_full Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018
title_fullStr Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018
title_full_unstemmed Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018
title_sort detection of vegetation cover change in renewable energy development zones of southern california using modis ndvi time series analysis, 2000 to 2018
publisher MDPI AG
series Environments
issn 2076-3298
publishDate 2019-03-01
description New solar energy facilities on public lands in the deserts of southern California are being monitored long-term to detect environmental impacts. For this purpose, we have developed a framework for detecting changes in vegetation cover region-wide using greenness index data sets from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. This study focused on three sites, Joshua Tree National Park (JOTR), Mojave National Preserve (MOJA), and a proximal group of solar energy Development Focus Areas (DFAs). Three MODIS vegetation indices (VIs), the normalized difference (NDVI), enhanced (EVI), and soil-adjusted (SAVI), all at 250-m spatial resolution, were evaluated using the Breaks for Additive Season and Trend (BFAST) methodology to estimate significant time series shifts (“breakpoints„) in green vegetation cover, from February 2000 to May 2018. The sample cross-correlation function with local precipitation records and comparison with timing of wildfires near the study sites for breakpoint density (proportion of area with a breakpoint) showed that NDVI had the strongest response and hence greatest sensitivity to these major disturbances compared to EVI and SAVI, supporting its use over the other VIs for subsequent analysis. Time series of NDVI breakpoint change densities for individual solar energy DFAs did not have a consistent vegetation response following construction. Bootstrap-derived 95% confidence intervals show that the DFAs have significantly larger kurtosis and standard deviation in positive NDVI breakpoint distribution than protected National Park System (NPS) sites, but no significant difference appeared in the negative distribution among all sites. The inconsistent postconstruction NDVI signal and the large number of detected breakpoints across all three sites suggested that the largest shifts in greenness are tied to seasonal and total annual precipitation amounts. Further results indicated that existing site-specific conditions are the main control on vegetation response, mostly driven by the history of human disturbances in DFAs. Although the results do not support persistent breakpoints in solar energy DFAs, future work should seek to establish links between statistical significance and physical significance through ground-based studies to provide a more robust interpretation.
topic MODIS
NDVI
vegetation cover
SAVI
EVI
Mojave Desert
Lower Colorado Desert
precipitation
url https://www.mdpi.com/2076-3298/6/4/40
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AT christopherpotter detectionofvegetationcoverchangeinrenewableenergydevelopmentzonesofsoutherncaliforniausingmodisndvitimeseriesanalysis2000to2018
AT rebeccabaiman detectionofvegetationcoverchangeinrenewableenergydevelopmentzonesofsoutherncaliforniausingmodisndvitimeseriesanalysis2000to2018
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