Detection and modeling of soil salinity variations in arid lands using remote sensing data

Soil salinization is a ubiquitous global problem. The literature supports the integration of remote sensing (RS) techniques and field measurements as effective methods for developing soil salinity prediction models. The objectives of this study were to (i) estimate the level of soil salinity in Abu Dhabi using spectral indices and field measurements and (ii) develop a model for detecting and mapping soil salinity variations in the study area using RS data. We integrated Landsat 8 data with the electrical conductivity measurements of soil samples taken from the study area. Statistical analysis of the integrated data showed that the normalized difference vegetation index and bare soil index showed moderate correlations among the examined indices. The relation between these two indices can contribute to the development of successful soil salinity prediction models. Results show that 31% of the soil in the study area is moderately saline and 46% of the soil is highly saline. The results support that geoinformatic techniques using RS data and technologies constitute an effective tool for detecting soil salinity by modeling and mapping the spatial distribution of saline soils. Furthermore, we observed a low correlation between soil salinity and the nighttime land surface temperature

Drought severity trend analysis based on the Landsat time-series dataset of 1998-2017 in the Iraqi Kurdistan Region

Drought is a natural hazard that significantly impacts economic, agricultural, environmental, and social aspects and is characteristic of Iraq's climate, particularly the Iraqi Kurdistan Region (IKR). For studying the spatiotemporal characteristics of drought severity in the IKR, a time-series of 120 Landsat images (TM, 7 ETM+, and OLI sensors) over twenty years (1998-2017) was assembled. Twenty separate mosaics of six Landsat scenes were used to derive the Vegetation Condition Index (VCI). The VCI index was employed to capture the drought severity in the study area. Results revealed that 1999, 2000, and 2008 were the most severe drought years. The results also indicated that severe droughts increased by 29.1%, 25.0%, and 26.9 through 1999, 2000, and 2008, respectively. Furthermore, a drop in precipitation averages occurred in the two years and significantly reduced the VCI values. Statistical analysis exhibited significant correlations between the VCI and each precipitation, and crop yield was 0.81 and 0.478, respectively. It can be concluded that the IKR experienced severe to extremely severe agricultural droughts, which caused significant reductions in crop yields, particularly in 2000 and 2008

Drought Spatiotemporal Characteristics Based on a Vegetation Condition Index in Erbil, Kurdistan Region, Iraq

Drought is a complex phenomenon that has severe impacts on the environment. Vegetation and its conditions are very sensitive to drought effects. This study aimed to monitor and assess the drought severity and its relationships to some ecological variables in ten districts of Erbil Governorate (Kurdistan Region), Iraq, throughout 20 years (1998-2017). The results revealed that droughts frequently hit Erbil throughout the study period. The Landsat time-series- based on Vegetation Condition Index (VCI) significantly correlated with precipitation, Digital Elevation Model (DEM), and latitude. Extreme VCI-based drought area percentages were recorded in 1999, 2000, 2008, and 2011 by 43.4%, 67.9%, 43.3%, and 40.0%, respectively. The highest crop yield reduction in the study area occurred mainly in 2000, 2008, and 2012 due to low precipitation rates. These results reveal the capability of the VCI for drought characteristics and highlighting relationships with some ecological variables, which provide vital information to the decision-makers, environmental, and economic sectors

Color slices analysis of land use changes due to urbanization in a city environment of Miami Area, South Florida, USA

Land use maps are widely using all over the world for monitoring the usage of lands over a while when urbanization booms. The urban development of the city environment parallelly involves the quick change of landcover in a short time. This work aims to review the land cover changes in Miami which areone of a highly urbanized county in the USA in the twentieth century. The color patterns of land use maps were reviewed with a uniform temporal rate (5 years once) from 2001 to 2016. Based on the color code of the image, land use maps were visually interpreted and it was extended to the Statistical analysis. Unique formulas are derived from the linear statistical model for the changing rate of the land use type in 15 years. Urban built-up gave expeditious increment in land use (9.5%). In the meantime, agricultural land (5.97%) and water (4.21%) decreased at a rapid rate. At the end of the study, the regression model projects the land use change in the year 2021 in Miami Dade County. This study distinctly exhibits how urbanization affects the vegetation cover, water areas, and wetlands, in which land use classes playing a vital role in the ecosystem. This experiment gives a basic understanding of Miami Dade county development and its environmental impact

Advances in Land–Ocean Heat Fluxes Using Remote Sensing

Advanced remote sensing technology has provided spatially distributed variables for estimating land–ocean heat fluxes, allowing for practical applications in drought monitoring, water resources management, and climate assessment. This Special Issue includes several research studies using state-of-the-art algorithms for estimating downward longwave radiation, surface net radiation, latent heat flux, columnar atmospheric water vapor, fractional vegetation cover, and grassland aboveground biomass. This Special Issue intends to help scientists involved in global change research and practices better comprehend the strengths and disadvantages of the application of remote sensing for monitoring surface energy, water, and carbon budgets. The studies published in this Special Issue can be applied by natural resource management communities to enhance the characterization and assessment of land–ocean biophysical variables, as well as for more accurately partitioning heat flux into soil and vegetation based on the existing and forthcoming remote sensing data

A Geospatial Approach for Analysis of Drought Impacts on Vegetation Cover and Land Surface Temperature in the Kurdistan Region of Iraq

Drought is a common event in Iraq’s climate, and the country has severely suffered from drought episodes in the last two decades. The Kurdistan Region of Iraq (KRI) is geographically situated in the semi-arid zone in Iraq, whose water resources have been limited in the last decades and mostly shared with other neighboring countries. To analyze drought impacts on the vegetation cover and the land surface temperature in the KRI for a span of 20 years from 1998 to 2017, remote sensing (RS) and Geographical Information Systems (GIS) have been adopted in this study. For this study, 120 Landsat satellite images were downloaded and utilized, whereas six images covering the entire study area were used for each year of the study period. The Normalized Difference Vegetation Index (NDVI) and Land Surfaces Temperature Index (LST) were applied to produce multi-temporal classified drought maps. Changes in the area and values of the classified NDVI and LST were calculated and mapped. Mann–Kendall and Sen’s Slope statistical tests were used to assess the variability of drought indices variation in 60 locations in the study area. The results revealed increases in severity and frequency of drought over the study period, particularly in the years 2000 and 2008, which were characterized by an increase in land surface temperatures, a decrease in vegetation area cover, and a lack of precipitation averages. Climate conditions affect the increase/decrease of the vegetated cover area, and geographical variability is also one factor that significantly influences the distribution of vegetation. It can be concluded that the southeast and southwestern parts of the KRI were subjected to the most severe droughts over the past 20 years

Drought Severity and Frequency Analysis Aided by Spectral and Meteorological Indices in the Kurdistan Region of Iraq

In the past two decades, severe drought has been a recurrent problem in Iraq due in part to climate change. Additionally, the catastrophic drop in the discharge of the Tigris and Euphrates rivers and their tributaries has aggravated the drought situation in Iraq, which was formerly one of the most water-rich nations in the Middle East. The Kurdistan Region of Iraq (KRI) also has catastrophic drought conditions. This study analyzed a Landsat time-series dataset from 1998 to 2021 to determine the drought severity status in the KRI. The Modified Soil-Adjusted Vegetation Index (MSAVI2) and Normalized Difference Water Index (NDWI) were used as spectral-based drought indices to evaluate the severity of the drought and study the changes in vegetative cover, water bodies, and precipitation. The Standardized Precipitation Index (SPI) and the Spatial Coefficient of Variation (CV) were used as meteorologically based drought indices. According to this study, the study area had precipitation deficits and severe droughts in 2000, 2008, 2012, and 2021. The MSAVI2 results indicated that the vegetative cover decreased by 36.4%, 39.8%, and 46.3% in 2000, 2008, and 2012, respectively. The SPI’s results indicated that the KRI experienced droughts in 1999, 2000, 2008, 2009, 2012, and 2021, while the southeastern part of the KRI was most affected by drought in 2008. In 2012, the KRI’s western and southern parts were also considerably affected by drought. Furthermore, Lake Dukan (LD), which lost 63.9% of its surface area in 1999, experienced the most remarkable shrinkage among water bodies. Analysis of the geographic distribution of the CV of annual precipitation indicated that the northeastern parts, which get much more precipitation, had less spatial rainfall variability and more uniform distribution throughout the year than other areas. Moreover, the southwest parts exhibited a higher fluctuation in annual spatial variation. There was a statistically significant positive correlation between MSAVI2, SPI, NDWI, and agricultural yield-based vegetation cover. The results also revealed that low precipitation rates are always associated with declining crop yields and LD shrinkage. These findings may be concluded to provide policymakers in the KRI with a scientific foundation for agricultural preservation and drought mitigation

New approaches: Use of assisted natural succession in revegetation of inhabited arid drylands as alternative to large‑scale aforestation

It is a great concept to let nature do the work of revegetation, however in semi-arid and arid regions the process of natural succession, if it occurs at all, typically requires many years of undisturbed development until an increase in bio�mass becomes measurable, hence it rather is applied to remote, sparsely populated regions and may be underrated as a measure to restore native vegetation, particularly in inhabited arid areas. What are the factors that make arid successional processes successful, how to expedite, and how to enable their use for the ecological revegetation of densely populated drylands? We review restoration methods that combine the planting of shelterbelt compartments with successional revegetation of the internal area, protected from wind and drought. Various measures of assisted natural succession can be applied to greatly accelerate the revegetation, including soil tillage, amendment with organic matter and the inoculation with cyanobacteria or lichens to form biocrusts. The aim is to initiate the development of native, water-saving savanna with biodiversity, resilience and adaptability to climate change. A narrow twin shelterbelt module could facilitate the use of natural succession within inhabited and peri-urban areas, also serving as protective greenbelt for cities. A pilot is planned in a peri-urban area of Northern Iraq, with a successional area of 125–150 m between shelterbelts. Land-use of agriculture, gardening and recreation can be integrated within the successional area, which also generates engage�ment of residents in the maintenance work. Planting of shelterbelts is required on 10–25% (not 100%) of the restoration area, therefore the use of assisted succession within protective compartments is expected to have both, ecological and economic advantages over large-scale aforestation

Sahel Afforestation and Simulated Risks of Heatwaves and Flooding Versus Ecological Revegetation That Combines Planting and Succession

Studies simulating the large-scale afforestation of the African Sahel constantly find warning signals of increased risk of extreme temperatures and heatwaves resulting from changes in albedo and latent heat flow. We review the affore�station measures underlying three simulation studies, together with a restora�tion model in which compartments are formed by greenbelts to enable suc�cession of savanna vegetation, protected from hot wind and drought. Savan�na-like vegetation (around 20% woody plants) will show bright reflective sur�face and drying of leaves during dry season rather than constant green color, with very different impact on albedo and temperatures. We derive that the simulated risks of extreme heat and flooding from rain will strongly depend on species, shape and density of the new vegetation. Ecological restoration concepts are expected to mitigate or prevent such restoration related climatic risks. Compact afforestation of the Sahel does not appear to be necessary or feasible. A restoration model based on compartmentalization and the pro�tected succession of diverse, climatically adaptable vegetation could also be used in populated drylands, as a sustainable and temperature balancing solu�tion to desertificatio

Modelling habitat suitability for the breeding Egyptian Vulture (Neophron percnopterus) in the Kurdistan region of Iraq

The Egyptian Vulture (Neophron percnopterus) is an endangered species with a globally declining population. Information on the current habitat distribution and potential suitable habitat for this ecologically important species will provide invaluable insight into conservation planning and the species’ future status as climate changes. This is specifically important for areas where there are little or no reported data on the status of the Egyptian Vulture. We used 13 years nest-site records (n = 69) together with relevant environmental variables to understand the known distribution and predict potential habitat distribution of the Egyptian Vulture in the Kurdistan Region of Iraq. A machine learning model, maximum entropy, was used to generate various model options, from which the best model was selected based on the Akaike information criterion (AICc) statistical indicators. The model showed reasonably good discriminative ability using both True Skill Statistics TSS = 0.722 and Area under the Curve (AUC) = 0.825 metrics. The Egyptian Vultures in Iraq mainly breed in territories at elevations between 1000 and 3300 m above sea level. This suggests that the species shows preference to areas distant from human settlements likely due to decreased disturbance and that the species may rely on alternative/complementary food sources (e.g. wild goat and boar). The total area of the study site is approximately 51,069 km2, out of which around 25% (12,767 km2) is predicted as suitable breeding habitat for the Egyptian Vulture. The output of this study provides useful baseline information for conservation actions and plans