scholarly journals Testing Possible Scenario-Based Responses of Vegetation Under Expected Climatic Changes in Khuzestan Province

2021 ◽  
Vol 14 ◽  
pp. 117862212110133
Author(s):  
Hadi Eskandari Damaneh ◽  
Meysam Jafari ◽  
Hamed Eskandari Damaneh ◽  
Marjan Behnia ◽  
Asadollah Khoorani ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kendall Test ◽  
Baseline Period ◽  
System Model ◽  
Future Period ◽  
Khuzestan Province ◽  
Ecosystem Planning ◽  
Slope Estimator ◽  
Precipitation And Temperature

Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.

scholarly journals A New Approach for Land Degradation and Desertification Assessment Using Geospatial Techniques

2017 ◽  
Author(s):  
Masoud Masoudi ◽  
Parviz Jokar ◽  
Biswajeet Pradhan
Keyword(s):  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Evaluation Method ◽  
Low Cost ◽  
United Nations Environment Programme ◽  
Geospatial Techniques ◽  
New Approach ◽  
Khuzestan Province ◽  
Current State

Abstract. Land degradation reduces production of biomass and vegetation cover in every land uses. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of current state of land degradation or desertification is very difficult because this phenomena includes several complex processes. For that reason, there is no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment based on its current state by modifying of FAO1/UNEP2 index and normalized difference vegetation index (NDVI) index in Khuzestan province, placed in the southwestern part of Iran. The proposed evaluation method is easy to understand the degree of destruction due to low cost and save time. Results showed that based on percent of hazard classes in current condition of land degradation, the most widespread and minimum area of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. While results in the desert area of study area showed that severe class is much widespread than other hazard classes, showing environmentally bad situation in the study area. Statistical results indicated that degradation is highest in desert and then rangeland compared to dry cultivation and forest. Also statistical test showed average of degradation amount in the arid region is higher than other climates. It is hoped that this attempt using geospatial techniques will be found applicable for other regions of the world and better planning and management of lands, too. 1 Food and Agriculture Organization 2 United Nations Environment Programme

scholarly journals Declining Effect of Precipitation on the Normalized Difference Vegetation Index of Grasslands in the Inner Mongolian Plateau, 1982–2010

2021 ◽  
Vol 11 (18) ◽  
pp. 8766
Author(s):  
Yanan Li ◽  
Dan Wu ◽  
Liangyan Yang ◽  
Tiancai Zhou
Keyword(s):  
Climate Change ◽  
Inner Mongolia ◽  
Carbon Balance ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Effect Of Temperature ◽  
Mongolian Plateau ◽  
Temperature And Precipitation ◽  
Inner Mongolia Plateau ◽  
Precipitation And Temperature

Grasslands play an irreplaceable role in maintaining carbon balance and stabilizing the entire Earth’s ecosystem. Although the grasslands in Inner Mongolia are sensitive and vulnerable to climate change, a generalized effect of climate change on the grasslands is still unavailable. In this study, we analyzed the effects of annual mean precipitation and annual mean temperature on the normalized difference vegetation index from 1982 to 2010 on the Inner Mongolia Plateau. Our results indicated that the normalized difference vegetation index was mostly affected by precipitation, followed by temperature. Spatially, temperature and precipitation had greater effects on normalized difference vegetation index in dry regions than in wet ones. In time series, the effect of precipitation on normalized difference vegetation index had significantly decreased from 1982 to 2010 (R2 = 0.11, p > 0.05). However, the effect of temperature on normalized difference vegetation index remained stable. The high variation effect of precipitation on normalized difference vegetation index was due to the significant decrease in precipitation from 1980 to 2010. Thus, 35.47% and 0.56% of the dynamic of normalized difference vegetation index from 1982 to 2010 was accounted for by the precipitation and temperature, respectively. Our findings highlighted that grasslands are adaptable to the significant increase in temperature, but are sensitive to the decrease in precipitation on the Inner Mongolia Plateau.

scholarly journals Factors Affecting Long-Term Trends in Global NDVI

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 372 ◽  
Author(s):  
Yujie Yang ◽  
Shijie Wang ◽  
Xiaoyong Bai ◽  
Qiu Tan ◽  
Qin Li ◽  
...  
Keyword(s):  
Central Asia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Pearson Correlation ◽  
Central Africa ◽  
Kendall Test ◽  
Boosted Regression Trees ◽  
Underlying Distribution ◽  
Factors Affecting ◽  
Ecological Conservation

Diagnosing the evolution trends of vegetation and its drivers is necessary for ecological conservation and restoration. However, it remains unclear what the underlying distribution pattern of these trends and its correlation with some drivers at large spatial-temporal scales. Here we use the normalized difference vegetation index (NDVI) to quantify the activity of vegetation by Theil–Sen median trend analysis and the Mann–Kendall test, Pearson correlation analysis and Boosted regression trees (BRT) model. Results show that about 34% of the global continent area has experienced greening in the grid annual NDVI from 1982 to 2015. The major greening areas were observed in the Sahel, European, India and south China. Only 10% of the global continent land areas were browning, and these were observed in Canada, South America, central Africa and Central Asia. BRT model shows that rainfall is the most important factor affecting vegetation evolution (63.1%), followed by temperature (15%), land cover change (8.6%), population (6.5%), elevation (6.4%) and nightlight (0.4%). It’s about 21% of the world’s continent were affected by rainfall, mainly in arid regions such as central Asia and Australia. The main temperature-affected areas accounted for 36%, located near the equator or in high latitudes.

scholarly journals Assessing Vegetation Decline due to Pollution from Waste Cycle Activities by a Multitemporal Remote-Sensing Approach

2021 ◽  
Author(s):  
Giuseppe Mancino ◽  
Rodolfo Console ◽  
Michele Greco ◽  
Chiara Iacovino ◽  
Maria Lucia Trivigno ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Waste Disposal ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Kendall Test ◽  
Landsat 8 ◽  
Polluted Sites ◽  
Exogenous Factors ◽  
Multitemporal Remote Sensing

The work consisted in identifying possible effects from heavy metals (HMs) pollution due to waste disposal activities in three potentially polluted sites located in Basilicata (Italy), where a release of pollutants with values over the thresholds allowed by the Italian legislation was detected. The potential variations in the physiological efficiency of vegetation have been analyzed through the multitemporal processing of satellite images. In detail, Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images were used to calculate the Normalized Difference Vegetation Index (NDVI) trend over the years. Then, the multitemporal trends were analyzed using the median of Theil-Sen, a non-parametric estimator particularly suitable for the treatment of remote sensing data, being able to minimize the outlier effects due to exogenous factors. Finally, the subsequent application of the Mann-Kendall test on the trends identified by Theil-Sen slope allowed the evaluation of trends significance and, therefore, the areas characterized by the effects of contamination on vegetation. The application of the procedure to the three survey sites led to the exclusion of the presence of significant effects of HMs contamination on the vegetation surrounding the sites during the years of waste disposal activities.

scholarly journals Growing Season Vegetation Dynamics Based on NDVI and the Driving Forces in Nepal during 1982-2015

2020 ◽  
Vol 17 ◽  
pp. 1-22
Author(s):  
Binod Baniya ◽  
Qiuhong Tang ◽  
Madan Koirala ◽  
Kedar Rijal ◽  
Giri Kattel
Keyword(s):  
Vegetation Dynamics ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Pearson Correlation ◽  
Growing Season ◽  
Kendall Test ◽  
Warming Trend ◽  
Shuttle Radar Topography Mission

Monitoring and attributing growing season vegetation dynamics have become crucial for maintaining the structure and function of the ecosystem. The objective of this research was to examine the spatial and temporal vegetation changes and explore their driving forces during growing season in Nepal. It also explored the variation of Normalized Difference Vegetation Index (NDVI) in different altitudes at each 100m interval. The National Oceanic and Atmospheric Administration (NOAA) NDVI, monthly temperature, precipitation and Shuttle Radar Topography Mission (SRTM) 90m Digital Elevation Model (DEM) were used. The linear regression model, Sen’s slope, Mann Kendall test and Pearson correlation between NDVI and climate, i.e., temperature and precipitation were computed. The driving forces were identified based on threshold segmentation method. Our results showed positive intensity of vegetation change. The NDVI has significantly increased at the rate of 0.001yr-1, 0.0005yr-1 and 0.002yr-1 in growing season, spring and autumn but it has insignificantly increased at the rate of 0.0003yr-1 in summer. In the meantime, growing season temperature has significantly increased with an average warming trend of 0.03&deg;Cyr-1 but precipitation decreased at the rate of 2.76 mm yr-1 during 1982-2015. The NDVI increased in 84.20% (53.08% significant) of the area. The correlation between NDVI and temperature was found positive whereas correlation with precipitation was negative. Spatially, 84.05% of the study area found positive correlation between NDVI and temperature with 25.72% significance (p<0.05) which was very less with precipitation. Our results demonstrate that NDVI was strongly correlated with temperature compared with precipitation. Beyond the climate, NDVI changes were also attributed to multi-control environments and ecological restoration in Nepal.  

scholarly journals A new approach for land degradation and desertification assessment using geospatial techniques

2018 ◽  
Vol 18 (4) ◽  
pp. 1133-1140 ◽  
Author(s):  
Masoud Masoudi ◽  
Parviz Jokar ◽  
Biswajeet Pradhan
Keyword(s):  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Evaluation Method ◽  
Statistical Tests ◽  
United Nations Environment Programme ◽  
Geospatial Techniques ◽  
New Approach ◽  
Khuzestan Province ◽  
Current State

Abstract. Land degradation reduces the production of biomass and vegetation cover for all forms of land use. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of the current state of land degradation or desertification is very difficult because this phenomenon includes several complex processes. For that reason, no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment, based on its current state by modifying of Food and Agriculture Organization (FAO)–United Nations Environment Programme (UNEP) index and the normalized difference vegetation index (NDVI) index in Khuzestan province, southwestern Iran. Using the proposed evaluation method it is easy to understand the degree of destruction caused by the pursuit of low costs and in order to save time. Results showed that based on the percent of hazard classes in the current condition of land degradation, the most and least widespread areas of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. Results in the desert component of the study area showed that the severe class is much more widespread than the other hazard classes, which could indicate an environmentally dangerous situation. Statistical results indicated that degradation is highest in deserts and rangeland areas compared to dry cultivated areas and forests. Statistical tests also showed that the average degradation amount in the arid region is higher than in other climates. It is hoped that this study's use of geospatial techniques will be found to be applicable in other regions of the world and can also contribute to better planning and management of land.

scholarly journals Spatio-Temporal Patterns of Vegetation in the Yarlung Zangbo River, China during 1998–2014

2019 ◽  
Vol 11 (16) ◽  
pp. 4334 ◽  
Author(s):  
Xiaowan Liu ◽  
Zongxue Xu ◽  
Dingzhi Peng
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Lag Time ◽  
High Elevation ◽  
Vegetation Patterns ◽  
Broadleaf Forest ◽  
Ecological Protection ◽  
Yarlung Zangbo River ◽  
Spatio Temporal ◽  
Precipitation And Temperature

Spatiotemporal vegetation patterns are of great importance for regional development. As one of the largest transnational rivers in China, the Yarlung Zangbo River in the Qinghai-Tibetan Plateau was selected as the study site, and the spatiotemporal patterns of vegetation during 1998–2014 were analyzed using the normalized difference vegetation index (NDVI). The results show that the NDVI increased with decreasing elevation, and the largest value was observed for the broadleaf forest. The lag time of NDVI to precipitation for most of the vegetation units was distinguished as approximately one month. In the region with an elevation of over 5000 m, the NDVI for the alpine vegetation was negatively correlated with the precipitation. Most NDVI variations were due to precipitation and temperature (approximately 75%). These results could provide a reference for ecological protection at a similar high elevation in the future.

scholarly journals The sensitivity of vegetation in the lower Tigris basin landscapes to regional and global climate variability

2021 ◽  
Vol 30 (1) ◽  
pp. 159-170
Author(s):  
Ali Alhumaima ◽  
Sanjar Abdullaev
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Southern Oscillation ◽  
Global Climate ◽  
Standardized Precipitation Index ◽  
Monthly Precipitation ◽  
Anthropogenic Landscapes ◽  
Precipitation And Temperature

This study investigates the lower Tigris basin’s the normalized difference vegetation index (NDVI) sensitivity in 2000–2016 to regional climate variability reflected by the monthly precipitation and temperature time series of seven global datasets as well as to four global circulation indices. To examine the effect of climate variability on the different ecosystems, the study area has been classified into 10 smaller natural and anthropogenic landscapes based on landforms and land cover patterns. The preliminary analysis showed that the maximum biological productivity reflected by the NDVI of March and April has the highest correlation (0.5–0.8) to the same cumulative amounts of October–March period total precipitation and January–March period mean temperatures according to all datasets. In addition, this article showed there is a correlation between landscapes’ NDVI and global modulation represented by the September–February state of El Nińo-Southern Oscillation (ENSO) (0.55–0.70) and December state of the dipole mode index (DMI) (0.35–0.72). The significant differences in the original precipitation and temperature levels according to the different datasets have urged the use of normalized time series: z-score of temperatures and analogous six-months the standardized precipitation index (SPI). However, the multiple correlation analysis showed that using ERA-

scholarly journals Influences of Climate Change and Human Activities on NDVI Changes in China

2021 ◽  
Vol 13 (21) ◽  
pp. 4326
Author(s):  
Yu Liu ◽  
Jiyang Tian ◽  
Ronghua Liu ◽  
Liuqian Ding
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kendall Test ◽  
Dynamic Monitoring ◽  
Scientific Management ◽  
Liaohe River ◽  
Continental Basin ◽  
The Impact

The spatiotemporal evolution of vegetation and its influencing factors can be used to explore the relationships among vegetation, climate change, and human activities, which are of great importance for guiding scientific management of regional ecological environments. In recent years, remote sensing technology has been widely used in dynamic monitoring of vegetation. In this study, the normalized difference vegetation index (NDVI) and standardized precipitation‒evapotranspiration index (SPEI) from 1998 to 2017 were used to study the spatiotemporal variation of NDVI in China. The influences of climate change and human activities on NDVI variation were investigated based on the Mann–Kendall test, correlation analysis, and other methods. The results show that the growth rate of NDVI in China was 0.003 year−1. Regions with improved and degraded vegetation accounted for 71.02% and 22.97% of the national territorial area, respectively. The SPEI decreased in 60.08% of the area and exhibited an insignificant drought trend overall. Human activities affected the vegetation cover in the directions of both destruction and restoration. As the elevation and slope increased, the correlation between NDVI and SPEI gradually increased, whereas the impact of human activities on vegetation decreased. Further studies should focus on vegetation changes in the Continental Basin, Southwest Rivers, and Liaohe River Basin.

scholarly journals Modeling NDVI Using Joint Entropy Method considering Hydro-Meteorological Driving Factors in the Middle Reaches of Hei River Basin

2017 ◽  
Author(s):  
Zhang Gengxi ◽  
Xiaoling Su ◽  
Vijay P. Singh ◽  
Olusola O. Ayantobo
Keyword(s):  
River Basin ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Entropy Method ◽  
Joint Entropy ◽  
Terrestrial Vegetation ◽  
Ecosystem Monitoring ◽  
Vegetation Growth ◽  
Region I ◽  
Precipitation And Temperature

Terrestrial vegetation dynamics are closely influenced by a multitude of factors. This study investigated the relationships between vegetation patterns and their main influencing factors. The joint entropy method was employed to evaluate the dependence between normalized difference vegetation index (NDVI) and coupled variables in the middle reaches of Hei River basin. Based on the spatial distribution of mutual information, the whole study area was divided into five sub-regions. In each sub-region, nested statistical models were applied to model the NDVI on the grid and regional scales, respectively. Results showed that the annual average NDVI increased with a rate of 0.005/a in recent 11 years. In the desert regions, the NDVI increased significantly with an increase in precipitation and temperature, and high accuracy of retrieving NDVI model was obtained by coupling precipitation and temperature, especially in sub-region I. In the oasis regions, groundwater was also an important factor driving vegetation growth, and the rise of groundwater level contributed to the growth of vegetation. However, the relationship was weaker in artificial oasis regions (sub-region III and sub-region V) due to the influence of human activities, such as irrigation. The overall correlation coefficient between the observed NDVI and modeled NDVI was observed to be 0.97. Outcomes of this study are suitable for ecosystem monitoring, especially under the realm of climate change. Further studies are necessary and should consider more factors, such as runoff and irrigation.

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