Change in NDVI of forest ecosystems in Northern Caucasus as a function of topography and climate

Shary, P. A.; Sharaya, L. S.

doi:10.1134/s1995425514070099

Cited by 10 publications

(3 citation statements)

References 11 publications

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“…In addition, the results of relevant studies vary due to the complexities of the regions and vegetation characteristics [23,[25][26][27]. Most studies have focused on single ecosystems, such as forests [28], grasslands [29,30], croplands [31], and wetlands [32]. Other studies have focused on the entire study area without consideration of different land coverages [33,34].…”

Section: Introductionmentioning

confidence: 99%

Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

et al. 2019

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China is experiencing substantial land-use and land-cover change (LUCC), especially in coastal regions, and these changes have caused many ecological problems. This study selected a typical region of Jiangsu Province and completed a comprehensive and detailed spatial-temporal analysis regarding LUCC and the driving forces. The results show that the rate of land-use change has been accelerating, with land-use experiencing the most substantial changes from 2005 to 2010 for most land-use types and the period from 2010 to 2015 showing a reversed changing trend. Built-up land that occupies cropland was the main characteristic of land-use type change. Southern Jiangsu and the coastline region presented more obvious land-use changes. Social-economic development was the main factor driving increased built-up land expansion and cropland reduction. In addition, land-use policy can significantly affect land-use type changes. For land-cover changes, the normalized difference vegetation index (NDVI) for the land area without land-use type changes increased by 0.005 per year overall. Areas with increasing trends accounted for 82.43% of the total area. Both precipitation and temperature displayed more areas that were positively correlated with NDVI, especially for temperature. Temperature correlated more strongly with NDVI change than precipitation for most vegetation types. Our study can be used as a reference for land-use managers to ensure sustainable and ecological land-use and coastal management.

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Section: Introductionmentioning

confidence: 99%

Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

et al. 2019

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“…At present, to investigate the factors that influence changes in vegetation cover, many researchers analyze the responses of dynamic vegetation changes to temperature and rainfall variations. A few scholars (Pearson et al 2013;Gottfried et al 2012;Liu et al 2013) have also analyzed topographic factors as major influences on changes in vegetation cover and ecological environment (Shary and Sharaya 2014;Cai et al 2014). Overall, the dynamic changes in vegetation are the product of the interactions among many factors; however, few studies have examined the dynamic changes in the vegetation cover according to a comprehensive set of climatic and terrain factors.…”

Section: Introductionmentioning

confidence: 99%

Multi-perspective analysis of vegetation cover changes and driving factors of long time series based on climate and terrain data in Hanjiang River Basin, China

2018

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The Hanjiang River Basin is the source area of the Middle Route Project of the South-to-North Water Diversion Project, and the vegetation coverage in this basin directly affects the quality of the ecological environment. This study is based on long time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data synthesized over 16 days from 2000 to 2016 in the Hanjiang River Basin. Major climatic data (temperature and rainfall) and topographic data (elevation, slope, and aspect) are employed to analyze the driving forces of NDVI changes. The results demonstrate the following: for the 2000-2016 period, the average annual NDVI is 0.823, with a change trend of 0.025 year −1. The overall NDVI upstream is higher than that downstream. The average annual value of NDVI upstream is 0.844, with a change trend of 0.036 year −1 , and that of downstream is 0.799, with a change trend of 0.022 year −1. The spatial distribution of NDVI was significantly increased in the area around the upstream section of the river and near the Danjiangkou Reservoir, and the distribution of NDVI around the central city was significantly reduced. The NDVI was positively correlated with temperature and rainfall, and the impacts differed among different regions. At elevations below 2000 m, the NDVI shows an increasing trend with increasing elevation, and at elevations exceeding 2000 m, the NDVI is negatively correlated with elevation. Slope is positively correlated with the NDVI. The influence of aspect on the NDVI was small.

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“…High (GRNDVI level: 1.75-2.00) and remarkable vegetation growth (GRNDVI level: 2.00-4.00) had the high proportion in 2016 and 2018, accounting for 37.96% (12.103 km 2 ), and 29.96% (9.552 km 2 ), respectively. Some factors, such as climate, soil, and topography, are critical to the changes for the inter-annual vegetation growth [42][43][44]. The area of bare land increased from 0.414 km 2 in 2011 to 6.236 km 2 in 2018 and the area of bare land had been basically expanding.…”

Section: Inter-annual Vegetation Growth Results and Cross-validationmentioning

confidence: 99%

Monitoring and Evaluating Restoration Vegetation Status in Mine Region Using Remote Sensing Data: Case Study in Inner Mongolia, China

et al. 2021

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The ecological restoration of mining areas is very important, and repeated field surveys are inefficient in large-scale vegetation monitoring. The coal mining industry is currently facing the challenge of the lack of appropriate methods for monitoring restoration processes. This study used an open pit coal mine in Dongsheng District, Inner Mongolia, China as an example, and used the 2011–2018 Landsat TM/ETM+ and OLI images to monitor and evaluate vegetation restoration activity of the coal mine. The average value of the monthly maximum value of vegetation index in the growing season was selected as the basic indicator for studying vegetation and bare soil changes. The growth root normalized differential vegetation index (GRNDVI) and GRNDVI anomaly method indicated that the constructed land type change factor was used to study the growth of mine vegetation and change of the range of bare land in the entire mining region. We found that westward mining activities started from 2012, and vegetation was restored in the eastern original mining region from 2013. The restoration vegetation areas from 2015 to 2016 and from 2017 to 2018 were larger than those in the other restoration years. Moreover, areas of expanded bare land from 2011 to 2012, and from 2017 to 2018 were larger than those in the other expansion years. The restoration vegetation growth changes were compared with those of the natural vegetation growth. Results showed that the restoration vegetation growth trend was considerably similar with that of the natural vegetation. Inter-annual restoration effects were analyzed by constructing the effect of the area-average factor and using vegetation growth data. Accordingly, the restoration vegetation effects were best in 2014 and 2016. Comprehensive restoration effect was analyzed using the weighted evaluation method to obtain the overall restoration effects of the coal mine. Results showed that the comprehensive restoration effect is inclined to the inferior growth state. This study conducted a preliminary evaluation of mine restoration vegetation, thereby providing a promising way for the future monitoring and evaluation of such processes.

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Change in NDVI of forest ecosystems in Northern Caucasus as a function of topography and climate

Cited by 10 publications

References 11 publications

Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

Multi-perspective analysis of vegetation cover changes and driving factors of long time series based on climate and terrain data in Hanjiang River Basin, China

Monitoring and Evaluating Restoration Vegetation Status in Mine Region Using Remote Sensing Data: Case Study in Inner Mongolia, China

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