scholarly journals Tigris Basin Landscapes: Sensitivity of Vegetation Index NDVI to Climate Variability Derived from Observational and Reanalysis Data

2020 ◽  
Vol 24 (7) ◽  
pp. 1-18
Author(s):  
A. S. Alhumaima ◽  
S. M. Abdullaev

AbstractThe primary aim of this work is to study the response of the normalized difference vegetation index (NDVI) of landscapes in the lower Tigris basin to current global and regional climate variability presented, respectively, by the global circulation indices and monthly temperatures and precipitation extracted from five observational/reanalysis datasets. The second task is to find the dataset that best reflects the regional vegetation and climate conditions. Comparison of the Köppen–Trewartha bioclimatic landscapes with the positions of botanical districts, land-cover types, and streamflow estimates led to the conclusion that only two datasets correctly describe regional climatic zones. Therefore, searching for the NDVI response to regional climate variability requires the use of normalized analogs of temperatures and precipitations, as well as the Spearman rank correlation. We found that March/April NDVI, as proxies of the maximum biological productivity of the regional landscapes, are strongly correlated with October–March precipitation derived from three datasets and January–March temperatures derived from one dataset. We discovered the significant impact of autumn–winter El Niño–Southern Oscillation and winter Indian Oceanic dipole states on regional weather (e.g., all five recent severe droughts occurred during strong La Niña events). However, the strength of this impact on the vegetation was clearly linked to the zonal landscape type. By selecting pairs of the temperature/precipitation time series that best correlated with NDVI at a given landscape, we have built a synthetic climate dataset. The landscape approach presented in this work can be used to validate the viability of any dataset when assessing the impacts of climate change and variability on weather-dependent components of Earth’s surface.

2021 ◽  
Vol 30 (1) ◽  
pp. 159-170
Author(s):  
Ali Alhumaima ◽  
Sanjar Abdullaev

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-


2014 ◽  
Vol 11 (5) ◽  
pp. 7685-7719 ◽  
Author(s):  
M. Broich ◽  
A. Huete ◽  
M. G. Tulbure ◽  
X. Ma ◽  
Q. Xin ◽  
...  

Abstract. Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI). We based our analysis on Enhanced Vegetation Index (EVI) data from the MODerate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray–Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in the interior of the continent. The phenological cycle peak magnitude and integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over north-eastern Australia and within the MDB predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of productivity) showed positive anomalies of more than two standard deviations over most of eastern Australia in 2009–2010, which coincided with the transition between the El Niño induced decadal droughts to flooding caused by La Niña. The quantified spatial-temporal variability in phenology across Australia in response to climate variability presented here provides important information for land management and climate change studies and applications.


2019 ◽  
Vol 11 (6) ◽  
pp. 724 ◽  
Author(s):  
Simon Measho ◽  
Baozhang Chen ◽  
Yongyut Trisurat ◽  
Petri Pellikka ◽  
Lifeng Guo ◽  
...  

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.


2019 ◽  
Vol 65 (3-4) ◽  
pp. 119-129
Author(s):  
G. Brabata ◽  
C. Battisti ◽  
R. Carmona ◽  
C.A. Sánchez-Caballero

The Chametla wetland is used by shorebirds as a stopover site during their autumn migration and it is also an important breeding area for several species of waterbirds. The objective of this work was to compare the bird assemblages in Chametla wetland during three sampling periods: 1) 1991–1992; 2) 1997–1998 which was subjected to El Nino Southern Oscillation (ENSO) climate conditions and 3) 2005–2006. Bird communities were characterized in terms of species composition and diversity, using similarity analysis. Bird assemblage composition differed across years and seasons. Seasonal variations in composition and diversity were related to the presence/absence of phenological-characterized species (migratory vs. wintering species). The highest species richness was recorded under the ENSO period (1997–1998). We observed a sharp decrease in shorebird numbers, with evident stress at the assemblage level throughout the entire study period. There seems to be a transition of the bird assemblages from shorebird dominance to a dominance by long-legged wading birds and waterfowl species, which could be related to water level variation and changes in the quality/availability of food in the intertidal zone. The joint pressures of regional climate variation combined with local anthropogenic perturbations may lead to changes in bird assemblage in the Chametla wetland.


2021 ◽  
Vol 3 ◽  
Author(s):  
Omar Gutierrez-Cori ◽  
Jhan Carlo Espinoza ◽  
Laurent Z. X. Li ◽  
Sly Wongchuig ◽  
Paola A. Arias ◽  
...  

The southern Amazonia is undergoing a major biophysical transition, involving changes in land use and regional climate. This study provides new insights on the relationship between hydroclimatic variables and vegetation conditions in the upper Madeira Basin (~1 × 106 km2). Vegetative dynamics are characterised using the normalized difference vegetation index (NDVI) while hydroclimatic variability is analysed using satellite-based precipitation, observed river discharge, satellite measurements of terrestrial water storage (TWS) and downward shortwave radiation (DSR). We show that the vegetation in this region varies from energy-limited to water-limited throughout the year. During the peak of the wet season (January-February), rainfall, discharge and TWS are negatively correlated with NDVI in February-April (r = −0.48 to −0.65; p &lt; 0.05). In addition, DSR is positively correlated with NDVI (r = 0.47–0.54; p &lt; 0.05), suggesting that the vegetation is mainly energy-limited during this period. Outside this period, these correlations are positive for rainfall, discharge and TWS (r = 0.55–0.88; p &lt; 0.05), and negative for DSR (r = −0.47 to −0.54; p &lt; 0.05), suggesting that vegetation depends mainly on water availability, particularly during the vegetation dry season (VDS; late June to late October). Accordantly, the total rainfall during the dry season explains around 80% of the VDS NDVI interannual variance. Considering the predominant land cover types, differences in the hydroclimate-NDVI relationship are observed. Evergreen forests (531,350 km2) remain energy-limited during the beginning of the dry season, but they become water-limited at the end of the VDS. In savannas and flooded savannas (162,850 km2), water dependence occurs months before the onset of the VDS. These differences are more evident during extreme drought years (2007, 2010, and 2011), where regional impacts on NDVI were stronger in savannas and flooded savannas (55% of the entire surface of savannas) than in evergreen forests (40%). A spatial analysis reveals that two specific areas do not show significant hydroclimatic-NDVI correlations during the dry season: (i) the eastern flank of the Andes, characterised by very wet conditions, therefore the vegetation is not water-limited, and (ii) recent deforested areas (~42,500 km2) that break the natural response in the hydroclimate-vegetation system. These findings are particularly relevant given the increasing rates of deforestation in this region.


2020 ◽  
Vol 12 (13) ◽  
pp. 2113
Author(s):  
Dan Wanyama ◽  
Nathan J. Moore ◽  
Kyla M. Dahlin

Many developing nations are facing severe food insecurity partly because of their dependence on rainfed agriculture. Climate variability threatens agriculture-based community livelihoods. With booming population growth, agricultural land expands, and natural resource extraction increases, leading to changes in land use and land cover characterized by persistent vegetation greening and browning. This can modify local climate variability due to changing land–atmosphere interactions. Yet, for landscapes with significant interannual variability, such as the Mount Elgon ecosystem in Kenya and Uganda, characterizing these changes is a difficult task and more robust methods have been recommended. The current study combined trend (Mann–Kendall and Sen’s slope) and breakpoint (bfast) analysis methods to comprehensively examine recent vegetation greening and browning in Mount Elgon at multiple time scales. The study used both Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data and attempted to disentangle nature- versus human-driven vegetation greening and browning. Inferences from a 2019 field study were valuable in explaining some of the observed patterns. The results indicate that Mount Elgon vegetation is highly variable with both greening and browning observable at all time scales. Mann–Kendall and Sen’s slope revealed major changes (including deforestation and reforestation), while bfast detected most of the subtle vegetation changes (such as vegetation degradation), especially in the savanna and grasslands in the northeastern parts of Mount Elgon. Precipitation in the area had significantly changed (increased) in the post-2000 era than before, particularly in 2006–2010, thus influencing greening and browning during this period. The greenness–precipitation relationship was weak in other periods. The integration of Mann–Kendall and bfast proved useful in comprehensively characterizing vegetation greenness. Such a comprehensive description of Mount Elgon vegetation dynamics is an important first step to instigate policy changes for simultaneously conserving the environment and improving livelihoods that are dependent on it.


2020 ◽  
Vol 12 (18) ◽  
pp. 2970
Author(s):  
Anna C. Talucci ◽  
Elena Forbath ◽  
Heather Kropp ◽  
Heather D. Alexander ◽  
Jennie DeMarco ◽  
...  

The ability to monitor post-fire ecological responses and associated vegetation cover change is crucial to understanding how boreal forests respond to wildfire under changing climate conditions. Uncrewed aerial vehicles (UAVs) offer an affordable means of monitoring post-fire vegetation recovery for boreal ecosystems where field campaigns are spatially limited, and available satellite data are reduced by short growing seasons and frequent cloud cover. UAV data could be particularly useful across data-limited regions like the Cajander larch (Larix cajanderi Mayr.) forests of northeastern Siberia that are susceptible to amplified climate warming. Cajander larch forests require fire for regeneration but are also slow to accumulate biomass post-fire; thus, tall shrubs and other understory vegetation including grasses, mosses, and lichens dominate for several decades post-fire. Here we aim to evaluate the ability of two vegetation indices, one based on the visible spectrum (GCC; Green Chromatic Coordinate) and one using multispectral data (NDVI; Normalized Difference Vegetation Index), to predict field-based vegetation measures collected across post-fire landscapes of high-latitude Cajander larch forests. GCC and NDVI showed stronger linkages with each other at coarser spatial resolutions e.g., pixel aggregated means with 3-m, 5-m and 10-m radii compared to finer resolutions (e.g., 1-m or less). NDVI was a stronger predictor of aboveground carbon biomass and tree basal area than GCC. NDVI showed a stronger decline with increasing distance from the unburned edge into the burned forest. Our results show NDVI tended to be a stronger predictor of some field-based measures and while GCC showed similar relationships with the data, it was generally a weaker predictor of field-based measures for this region. Our findings show distinguishable edge effects and differentiation between burned and unburned forests several decades post-fire, which corresponds to the relatively slow accumulation of biomass for this ecosystem post-fire. These findings show the utility of UAV data for NDVI in this region as a tool for quantifying and monitoring the post-fire vegetation dynamics in Cajander larch forests.


2019 ◽  
Vol 49 (5) ◽  
pp. 423-433 ◽  
Author(s):  
E. Bumann ◽  
T. Awada ◽  
B. Wardlow ◽  
M. Hayes ◽  
J. Okalebo ◽  
...  

Remnant populations of Betula papyrifera Marshall have persisted in the Great Plains after the Wisconsin Glaciation along the Niobrara River Valley, Nebraska. Population health has declined in recent years, which has been hypothesized to be due to climate change. We used dendrochronological techniques to assess the response of B. papyrifera to microclimate (1950–2014) and the normalized difference vegetation index (NDVI) derived from satellite imagery (Landsat 5 TM (1985–2011) and MODIS (2000–2014)) as a proxy for population health. Growing-season streamflow and precipitation were positively correlated with raw and standardized tree-ring widths and basal area increment increase. Increasing winter and spring temperatures were unfavorable for tree growth, while increasing summer temperatures were favorable in the absence of drought. The strongest predictor for standardized tree rings was the Palmer Drought Severity Index, suggesting that B. papyrifera is highly responsive to a combination of temperature and water availability. The NDVI from the vegetation community was positively correlated with standardized tree-ring growth, indicating the potential of these techniques to be used as a proxy for ex situ monitoring of B. papyrifera. These results aid in forecasting the dynamics of the species in the face of climate variability and change in both remnant populations and across its current distribution in northern latitudes of North America.


2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Melku Dagnachew ◽  
Asfaw Kebede ◽  
Awdenegest Moges ◽  
Adane Abebe

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen’s slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (RNDVI-RF = 0.189, P≤0.001) and annual (RNDVI-RF = 0.637, P≤0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes.


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