scholarly journals Response of Natural Vegetation to Climate in Dryland Ecosystems: A Comparative Study between Xinjiang and Arizona

2020 ◽  
Vol 12 (21) ◽  
pp. 3567
Author(s):  
Fang Zhang ◽  
Chenghao Wang ◽  
Zhi-Hua Wang
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Natural Vegetation ◽  
Vegetation Growth ◽  
Climate Change And Variability ◽  
Changing Climate ◽  
Dryland Ecosystems ◽  
Background Climate

As one of the most sensitive areas to climate change, drylands cover ~40% of the Earth’s terrestrial land surface and host more than 38% of the global population. Meanwhile, their response to climate change and variability carries large uncertainties as induced by background climate, topography, and land cover composition; but there is a lack of intercomparison of different dryland ecosystems. In this study, we compare the changing climate and corresponding responses of major natural vegetation cover types in Xinjiang and Arizona, two typical drylands with similar landscapes in Asia and North America. Long-term (2002–2019) quasi-8-day datasets of daily precipitation, daily mean temperature, and Normalized Difference Vegetation Index (NDVI) were constructed based on station observations and remote sensing products. We found that much of Xinjiang experienced warming and wetting trends (although not co-located) over the past 18 years. In contrast, Arizona was dominated by warming with insignificant wetting or drying trends. Significant greening trends were observed in most parts of both study areas, while the increasing rate of NDVI anomalies was relatively higher in Xinjiang, jointly contributed by its colder and drier conditions. Significant degradation of vegetation growth (especially for shrubland) was observed over 18.8% of Arizona due to warming. Our results suggest that responses of similar natural vegetation types under changing climate can be diversified, as controlled by temperature and moisture in areas with different aridity.

scholarly journals Vegetation Dynamic Changes and Their Response to Ecological Engineering in the Sanjiangyuan Region of China

2020 ◽  
Vol 12 (24) ◽  
pp. 4035
Author(s):  
Xiaohui Zhai ◽  
Xiaolei Liang ◽  
Changzhen Yan ◽  
Xuegang Xing ◽  
Haowei Jia ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Positive Impact ◽  
Ecological Engineering ◽  
Scientific Basis ◽  
Vegetation Dynamic ◽  
Vegetation Growth ◽  
The Impact

In recent decades, the vegetation of the Sanjiangyuan region has undergone a series of changes under the influence of climate change, and ecological restoration projects have been implemented. In this paper, we analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the global inventory modeling and mapping studies (GIMMS) and moderate resolution imaging and spectroradiometer (MODIS) datasets during the past 34 years. Specifically, the characteristics of vegetation changes were analyzed according to the stage of implementation of different ecological engineering programs. The results are as follows. (1) The vegetation in 65.6% of the study area exhibited an upward trend, and in 53.0% of the area, it displayed a large increase, which was mainly distributed in the eastern part of the study area. (2) The vegetation NDVI increased to differing degrees during stages of ecological engineering. (3) The NDVI in the western part of the Sanjiangyuan region is mainly affected by temperature, while in the northeastern part, the NDVI is affected more by precipitation. In the southern part, however, vegetation growth is affected neither by temperature nor by precipitation. On the whole region, vegetation growing is more affected by temperature than by precipitation. (4) The impacts of human activities on vegetation change are both positive and negative. In recent years, ecological engineering projects have had a positive impact on vegetation growth. This study can help us to correctly understand the impact of climate change on vegetation growth, so as to provide a scientific basis for the evaluation of regional ecological engineering effectiveness and the formulation of ecological protection policies.

scholarly journals Spatial and Seasonal Patterns in Vegetation Growth-Limiting Factors over Europe

2019 ◽  
Vol 11 (20) ◽  
pp. 2406
Author(s):  
Arnon Karnieli ◽  
Noa Ohana-Levi ◽  
Micha Silver ◽  
Tarin Paz-Kagan ◽  
Natalya Panov ◽  
...  
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Limiting Factors ◽  
Limiting Factor ◽  
Spring Season ◽  
Entire Study ◽  
Vegetation Growth ◽  
Biophysical Indicators ◽  
Positive Correlations

Water and energy are recognized as the most influential climatic vegetation growth-limiting factors. These factors are usually measured from ground meteorological stations. However, since both vary in space, time, and scale, they can be assessed by satellite-derived biophysical indicators. Energy, represented by land surface temperature (LST), is assumed to resemble air temperature; and water availability, related to precipitation, is represented by the normalized difference vegetation index (NDVI). It is hypothesized that positive correlations between LST and NDVI indicate energy-limited conditions, while negative correlations indicate water-limited conditions. The current project aimed to quantify the spatial and seasonal (spring and summer) distributions of LST–NDVI relations over Europe, using long-term (2000–2017) MODIS images. Overlaying the LST–NDVI relations on the European biome map revealed that relations between LST and NDVI were highly diverse among the various biomes and throughout the entire study period (March–August). During the spring season (March–May), 80% of the European domain, across all biomes, showed the dominance of significant positive relations. However, during the summer season (June–August), most of the biomes—except the northern ones—turned to negative correlation. This study demonstrates that the drought/vegetation/stress spectral indices, based on the prevalent hypothesis of an inverse LST–NDVI correlation, are spatially and temporally dependent. These negative correlations are not valid in regions where energy is the limiting factor (e.g., in the drier regions in the southern and eastern extents of the domain) or during specific periods of the year (e.g., the spring season). Consequently, it is essential to re-examine this assumption and restrict applications of such an approach only to areas and periods in which negative correlations are observed. Predicted climate change will lead to an increase in temperature in the coming decades (i.e., increased LST), as well as a complex pattern of precipitation changes (i.e., changes of NDVI). Thus shifts in plant species locations are expected to cause a redistribution of biomes.

scholarly journals Effects of Climate Change on Vegetation Cover in the Oued Lahdar Watershed. Northeastern Morocco

Plants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1624
Author(s):  
Hind Khalis ◽  
Abdelhamid Sadiki ◽  
Fatimazahra Jawhari ◽  
Haytam Mesrar ◽  
Ehab Azab ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Mean Value ◽  
Economic Conditions ◽  
Protective Strategies ◽  
Very High

Episodes of drought that Morocco experienced in the years 1984–1986, 1993–1995, and 1997–2000 had repercussions that were felt many years later and continue to pose serious problems for environmentalists, as some of the affected lands have become practically deserted. These problems acted on the socio-economic conditions and created severe constraints for the development of the country. This work was conducted to study and identify changes that occurred in vegetation cover in the Oued Lahdar watershed (Rif, Morocco) between 1984 and 2017 using Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Landsat TM 5, and Landsat OLI 8. The LST had significantly increased overall from 1984 to 2017, where it moved from a mean value of 29.4 °C in 1984 to 40.4 °C in 2007 and then reduced slightly to 37.9 °C in 2017. The vegetation cover index for the study area indicates that in 1984, fully vegetated areas represented 94.3% before deteriorating to 35.4% in 2007 and recovering in 2017 to 54.3%. While bare soil, which previously constituted 5.7%, reached a very high value of 64.6% in 2007 and then decreased to 47.7%. This study contributes towards society as it provides interesting data about the consequences of climate change in the area studied as well as potential protective strategies to protect vegetation cover.

scholarly journals Assessing the Relationship among the Land Surface Features: A Geographic Information System (GIS) and Remote Sensing (RS) Based Approach for City Area

2021 ◽  
Vol 8 (2) ◽  
pp. 935-952
Author(s):  
Sharmin Siddika ◽  
Md. Nazmul Haque ◽  
Mizbah Ahmed Sresto
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Moisture Index ◽  
Gis And Remote Sensing ◽  
Positive Correlation

Due to climate change and urbanization, it is important to monitor and evaluate the components of the environment. For this reason, ward-22 and ward-27 of the Khulna City Corporation (KCC) area have been selected for the study. This research seeks to identify the existing land use profile and assess the land surface components such as topography, Normalized Difference Buildup Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Salinity Index (NDSI) and Land Surface Temperature (LST) to measure the relationships among the land surface components. The land use land cover map shows that about 59% of ward-22 and 71.5% area of ward-27 are built-up areas. Both of the wards contain little amount of water body, vegetation and open space. Both of the wards have residential land use types with commercial purposes on the periphery. Accordingly, 63.32% and 65% of structures of ward-22 and 27 are pucca. The land surface components reveal that both areas contain lower slopes, less vegetation, less moisture, severe salinity, highly built-up areas, and high land surface temperature. The relationships among the land surface components show that NDVI has a negative relation with LST and NDBI whereas NDVI represents a positive correlation with NDMI. On the other hand, NDBI shows a positive correlation with LST whereas NDMI negatively correlates with LST. NDSI and topography reflect no meaningful relationship between NDBI, NDVI, LST, and NDMI. However, the research findings may be essential to city planners and decision-makers for incorporating better urban management at the micro level concerning climate change.

scholarly journals A Comparative Study for Performance of Five Landsat-based Vegetation Indices: Their Relations to Some Ecological and Terrain Variables

2020 ◽  
Vol 1 (1) ◽  
pp. 20-37
Author(s):  
Ayad Al-Quraishi ◽  
Hawar Razvanchy ◽  
Heman Gaznayee
Keyword(s):  
Aspect Ratio ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Point Of View ◽  
Vegetation Growth ◽  
Spectral Vegetation Indices ◽  
Landsat 7 ◽  
Total Study Area

Spectral vegetation indices and their relations to some ecological and terrain variables in the Iraqi Kurdistan Region (IKR) is the main objective of this study. A mosaic of two Landsat-7 ETM+ images was utilized to produce five spectral vegetation indices, and Terra ASTER Digital Elevation Model (DEM) dataset were employed. The Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Optimized Soil Adjusted Vegetation Index (OSAVI), Tasseled Cap Greenness, Land Surface Temperature (LST) were utilized for this study. The results of the current study revealed that MSAVI2 is more reliable and accurate in depicting the vegetation presence in the IKR, which is occupied 34.7% of the total study area in 2014. In terms of terrain variables, all vegetation indices responded to variation of aspect ratio variation. It was found that the densest vegetation exists between 180 to 350°. Mainly, in the South (157.5°-202.5°), Southwest (202.5°-247.5°), West (247.5°-292.5°), Northwest (292.5°-337.5°), and North (337.5°-360°). In contrast, from the aspect ratio point of view, vegetation cover growth was in its maximum status in the shaded side of the mountains, more than the sunny side. Additionally, the adequate slope for vegetation growth in the mountainous lands is 9-17%. Statistically, the LST appeared negative relations with vegetation indices and elevation

scholarly journals Assessment of Vegetation Dynamics and Ecosystem Resilience in the Context of Climate Change and Drought in the Horn of Africa

2021 ◽  
Vol 13 (9) ◽  
pp. 1668
Author(s):  
Simon Measho ◽  
Baozhang Chen ◽  
Petri Pellikka ◽  
Lifeng Guo ◽  
Huifang Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Severe Drought ◽  
Ecosystem Resilience ◽  
Horn Of Africa ◽  
Drought Conditions ◽  
Agroecological Zones ◽  
Ecosystem Water Use Efficiency

Understanding the response of vegetation and ecosystem resilience to climate variability and drought conditions is essential for ecosystem planning and management. In this study, we assessed the vegetation changes and ecosystem resilience in the Horn of Africa (HOA) since 2000 and detected their drivers based mainly on analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS) products. We found that the annual and seasonal trends of NDVI (Normalized Difference Vegetation Index) generally increased during the last two decades over the Horn of Africa particularly in western parts of Ethiopia and Kenya. The weakest annual and seasonal NDVI trends were observed over the grassland cover and tropical arid agroecological zones. The NDVI variation negatively correlated with Land Surface Temperature (LST) and positively correlated with precipitation at a significant level (p < 0.05) account for 683,197 km2 and 533,385 km2 area, respectively. The ecosystem Water Use Efficiency (eWUE) showed overall increasing trends with larger values for the grassland biome. The precipitation had the most significant effect on eWUE variation compared to LST and annual SPEI (Standardized Evapotranspiration Index). There were about 54.9% of HOA resilient to drought disturbance, whereas 32.6% was completely not-resilient. The ecosystems in the humid agroecological zones, the cropland, and wetland were slightly not-resilient to severe drought conditions in the region. This study provides useful information for policy makers regarding ecosystem and dryland management in the context of climate change at both national and regional levels.

Climate-forced changes of bio-productivity of Belorussian terrestrial ecosystems

2019 ◽  
pp. 77-88
Author(s):  
S. A. Lysenko
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Terrestrial Ecosystems ◽  
Vegetation Period ◽  
Climatic Trend ◽  
Vegetation Growth ◽  
Current Century ◽  
The Impact

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.

scholarly journals A Fused Variable by Night Light Images and MODIS Products for Improving Urban Built-Up Area Extraction

Technologies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 40
Author(s):  
Guang Yang ◽  
Yuntao Ma ◽  
Jiaqi Hu
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Extraction Methods ◽  
Average Error ◽  
Geographic Coordinate System ◽  
Optimal Thresholds ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Spatial Locations

The boundary of urban built-up areas is the baseline data of a city. Rapid and accurate monitoring of urban built-up areas is the prerequisite for the boundary control and the layout of urban spaces. In recent years, the night light satellite sensors have been employed in urban built-up area extraction. However, the existing extraction methods have not fully considered the properties that directly reflect the urban built-up areas, like the land surface temperature. This research first converted multi-source data into a uniform projection, geographic coordinate system and resampling size. Then, a fused variable that integrated the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night light images, the Moderate-resolution Imaging Spectroradiometer (MODIS) surface temperature product and the normalized difference vegetation index (NDVI) product was designed to extract the built-up areas. The fusion results showed that the values of the proposed index presented a sharper gradient within a smaller spatial range, compared with the only night light images. The extraction results were tested in both the area sizes and the spatial locations. The proposed index performed better in both accuracies (average error rate 1.10%) and visual perspective. We further discussed the regularity of the optimal thresholds in the final boundary determination. The optimal thresholds of the proposed index were more stable in different cases on the premise of higher accuracies.

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