Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the 1990s

Stow, Douglas A.; Daeschner, Scott; Hope, Allen; Douglas, David C.; Petersen, A. K.; Myneni, Ranga B.; Zhou, Liming; Oechel, W. C.

doi:10.1080/0143116021000020144

Cited by 244 publications

(144 citation statements)

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“…The seasonal integrated vegetation index is widely used in vegetation change studies [19] as an annual index that indicates the status of vegetation growth for a whole year. In our study, we calculated growing season integrated enhanced vegetation index (GSIEVI) values to analyze the trends in vegetation change.…”

Section: Remotely Sensed Vegetation Index Data Processingmentioning

confidence: 99%

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

2018

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Abstract:The Qinghai-Tibet (QT) Plateau Engineering Corridor is located in the hinterland of the QT Plateau, which is highly sensitive to global climate change. Climate change causes permafrost degradation, which subsequently affects vegetation growth. This study focused on the vegetation dynamics and their relationships with climate change and human activities in the region surrounding the QT Plateau Engineering Corridor. The vegetation changes were inferred by applying trend analysis, the Mann-Kendall trend test and abrupt change analysis. Six key regions, each containing 40 nested quadrats that ranged in size from 500 × 500 m to 20 × 20 km, were selected to determine the spatial scales of the impacts from different factors. Cumulative growing season integrated enhanced vegetation index (CGSIEVI) values were calculated for each of the nested quadrats of different sizes to indicate the overall vegetation state over the entire year at different spatial scales. The impacts from human activities, a sudden increase in precipitation and permafrost degradation were quantified at different spatial scales using the CGSIEVI values and meteorological data based on the double mass curve method. Three conclusions were derived. First, the vegetation displayed a significant increasing trend over 23.6% of the study area. The areas displaying increases were mainly distributed in the Hoh Xil. Of the area where the vegetation displayed a significant decreasing trend, 72.4% was made up of alpine meadows. Second, more vegetation, especially the alpine meadows, has begun to degenerate or experience more rapid degradation since 2007 due to permafrost degradation and overgrazing. Finally, an active layer depth of 3 m to 3.2 m represents a limiting depth for alpine meadows.

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Section: Remotely Sensed Vegetation Index Data Processingmentioning

confidence: 99%

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

2018

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“…The slope of the linear regression was employed as an index to fit the trend in the vegetation dynamics for every pixel using the least squares method for a given study period, which can comprehensively reflect the spatiotemporal variation characteristics of vegetation coverage [32,33]. The slope is calculated as follows:…”

Section: Analysis Of Trends In Vegetation Dynamicsmentioning

confidence: 99%

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

Liu

Zhu

et al. 2015

Remote Sensing

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Abstract:In recent decades, the monitoring of vegetation dynamics has become crucial because of its important role in terrestrial ecosystems. In this study, a satellite-derived normalized difference vegetation index (NDVI) was combined with climate factors to explore the spatiotemporal patterns of vegetation change during the growing season, as well as their driving forces in China from 2001 to 2012. Our results showed that the growing season NDVI increased continuously during 2001-2012, with a linear trend of 1.4%/10 years (p < 0.01). The NDVI in north China mainly exhibited an increasing spatial trend, but this trend was generally decreasing in south China. The vegetation dynamics were mainly at a moderate intensity level in both the increasing and decreasing areas. The significantly increasing trend in the NDVI for arid and semi-arid areas of northwest China was attributed mainly to an increasing trend in the NDVI during the spring, whereas that for the north and northeast of China was due to an increasing trend in the NDVI during the summer and autumn. Different vegetation types exhibited great variation in their trends, where the grassforb community had the highest linear trend of 2%/10 years (p < 0.05), followed by meadow, and needle-leaf forest with the lowest increasing trend, i.e., a linear trend of 0.3%/10 years. OPEN ACCESSRemote Sens. 2015, 7 15518Our results also suggested that the cumulative precipitation during the growing season had a dominant effect on the vegetation dynamics compared with temperature for all six vegetation types. In addition, the response of different vegetation types to climate variability exhibited considerable differences. In terms of anthropological activity, our statistical analyses showed that there was a strong correlation between the cumulative afforestation area and NDVI during the study period, especially in a pilot region for ecological restoration, thereby suggesting the important role of ecological restoration programs in ecological recovery throughout China in the last decade.

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“…Linear regression analysis was used to simulate NDVI/WY/NPP change trends at the pixel level or over the whole regional level [4,55,56]. The equation is as follows:…”

Section: Change Trendsmentioning

confidence: 99%

Ecosystem Services and Ecological Restoration in the Northern Shaanxi Loess Plateau, China, in Relation to Climate Fluctuation and Investments in Natural Capital

et al. 2017

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Accurately identifying the spatiotemporal variations and driving factors of ecosystem services (ES) in ecological restoration is important for ecosystem management and the sustainability of nature conservation strategies. As the Green for Grain project proceeds, food provision, water regulation and climate regulation services in the Northern Shaanxi Loess Plateau (NSLP) are changing and have caused broad attention. In this study, the dynamic pattern of the normalized differential vegetation index (NDVI) and the main drivers of grain production (GP), water yield (WY) and net primary production (NPP) in the NSLP from 2000-2013 are identified by incorporating multiple data and methods, in order to provide a better understanding of how and why ES change during ecological restoration. WY was simulated by hydrological modeling, and NPP was estimated with the Carnegie Ames Stanford Approach (CASA) model. The results show that vegetation restoration continued from 2000-2013, but fluctuated because of the comprehensive influence of climate and human activity. GP and NPP both exhibited significantly increasing trends, while changes in WY occurred in two stages: decline (2000)(2001)(2002)(2003)(2004)(2005)(2006) and growth (2007)(2008)(2009)(2010)(2011)(2012)(2013). Spatially, significantly increasing trends in NPP and WY were detected in 52.73% and 24.76% of the region, respectively, in areas that correspond with the Green for Grain project and high precipitation growth. Correlation and partial correlation analyses show that there were different dominant factors (i.e., natural vs. anthropogenic) driving ES change in the NSLP from 2000-2013. The change in WY was mainly driven by precipitation, while the improvements in GP and NPP can be attributed to investments in natural capital (i.e., chemical fertilizer, agricultural machinery power and afforestation). We also found that vegetation restoration can produce positive effects on NPP, but negative effects on WY by using response analyses of WY or NPP change to NDVI change, demonstrating that additional research on the role of water in vegetation restoration is needed. Our results provide support for ES management and the sustainable development of ecological restoration in the NSLP.

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Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the 1990s

Cited by 244 publications

References 0 publications

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

Ecosystem Services and Ecological Restoration in the Northern Shaanxi Loess Plateau, China, in Relation to Climate Fluctuation and Investments in Natural Capital

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