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There is growing global consensus that assessments of land degradation be conducted at regional or smaller scales. Working at this scale allows for locally relevant environmental and land use conditions to be incorporated into the assessment methodology. In this paper, a recently developed regional approach to assessing land degradation in the Hardeveld bioregion of the Succulent Karoo is applied to the Little Karoo region of this biome. The methodology uses fuzzy classification statistical techniques to combine field data with multiple Sentinel-2A and Landsat vegetation indices, as well as regionally modelled soil variables. The resultant habitat condition archetype map values show strong correlation with field observations of perennial plant and bare soil cover in 96 ground-truthed plots. The archetype map indicates that heavily degraded hotspots of high bare ground cover occur throughout the project region, although there is an overall lower average habitat condition in the western half of the Little Karoo. The mean habitat condition archetype value for the entire project area is 0.54 (standard deviation = 0.13), on a continuous scale where 0 and 1 represent the most degraded and pristine extremes, respectively. Random forest regression analysis of various environmental covariates of degradation indicates a strong relationship between habitat condition and topographic as well as rainfall variables, although the limited accuracy of modelled livestock data may obscure the negative impacts of overgrazing. The 30 m resolution habitat condition archetype map builds upon previous degradation research in the Little Karoo and has the potential to inform future conservation, restoration, and rangeland management decisions. The methodology was successfully transferred to a new region and provides an opportunity to improve reporting on the extent of land degradation across South Africa. • Effective transfer of methodology for regional scale assessment of degradation. • Western Little Karoo has lower habitat condition score than the eastern part. • Topography, rainfall, and land use history influence habitat condition score. • 30 × 30 m habitat condition map can inform sustainable land management decisions. [ABSTRACT FROM AUTHOR]

Trees in agroforestry parklands influence crops both through competitive and facilitative mechanism, but the effects are challenging to disentangle due to the complexity of the system with high variability in tree cover structure and species diversity and crop combinations. Focusing on a landscape in central Burkina Faso dominated by Vitellaria paradoxa and Parkia biglobosa , this paper examines how tree cover influences crop yield at landscape scale using satellite data and spatial statistics. Our analysis is based on data from 2017 to 2018 with differences in rainfall to assess the stability in identified relationships. Our findings showed that tree canopy cover and tree density inside the fields tended to decrease crop yield because of competition, but also that these variables when considering the surrounding landscape exerted an opposite effect because of their buffering effects. The explanatory variables representing soil properties did have limited effects on crop yield in this study. These patterns were consistent during the two years of monitoring. Overall, our results suggest that farmers in this area might manage the tree cover in a way that optimizes sustainable yields as canopy cover and tree density in most parklands is below the limits identified here where competition outweight the facilitative effects. • We studied causes of crop yield variability in parklands at landscape scale. • Satellite remote sensing and field data was used in spatial statistics. • Trees in agricultural fields tend to reduce crop yield through resource competition. • Surrounding trees had positive influence on crop yield via buffering effects. • Fewer large trees have more positive influence on crop yield than many small ones. [ABSTRACT FROM AUTHOR]

Abstract This paper calls attention to the presence of countless ancient paths on the basalt-covered surfaces characteristic of harra landscapes in north-eastern Jordan. These paths have developed over the course of at least the last two millennia, and potentially prior to that, by trafficking of nomadic peoples and animals. These paths facilitated movements through terrains that were otherwise difficult to traverse. Paths can be recognised on high-resolution satellite imagery, which allows for systematic documentation and the reconstruction of potential routes through the landscape. The identification and mapping of these paths is important for better understanding mobility patterns of nomadic peoples who inhabited these desert landscapes in antiquity. Highlights • Ancient paths were identified on harra surfaces in northeastern Jordan. • Paths can be systematically mapped using high resolution satellite imagery. • Paths developed as a result of trafficking of people and animals. • Paths were used to traverse the landscape at least for the last 2000 years. • Routes relate to nomadic exploitation of the environment on a local scale. [ABSTRACT FROM AUTHOR]

Scarcity of in situ vegetation data inhibits research and natural resource management in the Sudano-Sahelian zone (SSZ). Satellite and aerial remote sensing (RS) constitute key technologies for improving the availability of vegetation data, and consequently the preconditions for scientific analysis and monitoring. The aim of this paper was to investigate how the hands-on application of RS for vegetation analysis has developed in the SSZ by reviewing the scientific literature published between 1975 and 2014. The paper assesses the usages and the users of RS by focusing on four aspects of the material (268 peer-reviewed articles), including publication details (time of publication, scientific discipline of journals and author nationality), geographic information (location of study areas and spatial scale of research), data usage (application of RS systems and procedures for accuracy assessments), and research topic (scientific objective of the research). Three key results were obtained: i) the application of RS to analyze vegetation in the SSZ has increased consistently since 1977 and it seems to become adopted by a growing number of scientific disciplines; ii) the contribution of African authors is low, potentially signalling a need for an increased transfer of knowledge and technology from developed countries; iii) RS has primarily been used to analyze changes in vegetation productivity and broad vegetation types, whereas its use for studying interactions between vegetation and environmental factors has been relatively low. This calls for stronger collaborative RS research that enables the mapping of additional vegetation variables of high relevance for the environmental problems facing the SSZ. Remotely sensed vegetation data are needed at spatial scales that suits the requirements of both research and natural resource management in order to further enhance the usefulness of this technology. [ABSTRACT FROM AUTHOR]

Abstract: Riparian evapotranspiration (ET) is a major component of the surface and subsurface water balance for many semiarid watersheds. Measurement or model-based estimates of ET are often made on a local scale, but spatially distributed estimates are needed to determine ET over catchments. In this paper, we document the ET that was quantified over 3 years using eddy covariance for three riparian ecosystems along the Upper San Pedro River of southeastern Arizona, USA, and we use a water balance equation to determine annual groundwater use. Riparian evapotranspiration and groundwater use for the watershed were then determined by using a calibrated, empirical model that uses 16-day, 250–1000m remote-sensing products for the years of 2001–2005. The inputs for the model were derived entirely from the NASA MODIS sensor and consisted of the Enhanced Vegetation Index and land surface temperature. The scaling model was validated using subsets of the entire dataset (omitting different sites or years) and its capable performance for well-watered sites (MAD=0.32mmday−1, R 2=0.93) gave us confidence in using it to determine ET over the watershed. Three years of eddy covariance data for the riparian sites reveal that ET and groundwater use increased as woody plant density increased. Groundwater use was less variable at the woodland site, which had the greatest density of phreatophytes. Annual riparian groundwater use within the watershed was nearly constant over the study period despite an on-going drought. For the San Pedro alone, the amounts determined in this paper are within the range of most recently reported values that were derived using an entirely different approach. However, because of our larger estimates for groundwater use for the main tributary of the San Pedro, the watershed totals were higher. The approach presented here can provide riparian ET and groundwater use amounts that reflect real natural variability in phreatophyte withdrawals and improve the accuracy of a watershed''s water budget. [Copyright &y& Elsevier]

This paper presents the results of a multi-scale investigation of environmental change in the Old Peanut Basin of Senegal throughout the 20th century. Based on historical accounts, ethnographies, aerial photos, satellite images, field and household surveys as well as various participatory research activities with farmers in selected villages, the study attempts to make explicit layered scales of analysis, both temporally and spatially. It shows that, despite some general trends of resource degradation in the Old Peanut Basin, local farming systems have embarked on different pathways of change to adapt to their evolving environment. It also illustrates that high diversity with respect to soil fertility management exists at the farm and household level. Finally, the paper proposes a farmer-oriented approach to carbon sequestration in order to integrate recommended technical options more efficiently into the complex and dynamic livelihoods of smallholders in dryland environments. This approach includes pathway-specific land use and management options at the level of farming systems and, at the level of individual households, a basket of possible practices from which farmers can choose depending on their multiple needs, capacities, and adaptive strategies to cope with risk and uncertainty. [Copyright &y& Elsevier]

Soil erosion and desertification are the main problems faced by the Bou-Hedma National Park in South-Tunisia. Restoration of the original woodland cover, particularly by afforestation and reforestation with Acacia tortilis ssp. raddiana , has been recognized as efficient to combat further degradation of the environment in this protected area. In order to study effects of woodland restoration and future trends in Bou-Hedma, it is essential to accurately assess its current situation. This paper addresses a monotemporal assessment of the population structure of A . tortilis . An extensive field inventory was performed to provide deeper insight into the dendrometric characteristics of this keystone species. Next, a spatially explicit and repeatable method is developed to model key tree attributes like crown diameter, volume and tree height from which the structural composition of the A . tortilis population in the Bou Hedma National Park is derived. This method involves analysis of a very high resolution (VHR) GeoEye-1 image within an OBIA (Object-based Image Analysis) framework. The remote sensing (RS) results show that the population of A . tortilis is typified by an irregular population structure and confirm the findings of Noumi and Chaieb (2012) suggesting regressive population dynamics. The RS approach demonstrates potential for monitoring purposes in this particular setting of an arid environment. [ABSTRACT FROM AUTHOR]

Identifying, recording and monitoring land cover change on the Earth's surface is a complex procedure. Spatio-temporal modelling is an effective approach to simplifying and simulating the process. Existing spatio-temporal modelling methods are typically based on either, an overlay of multi-temporal land cover maps, or temporal trend analysis of spatial pattern indices. Consequently, an understanding of the spatial dynamics of any changes is either fragmental in the former case, or invisible in the latter case, due to the lack of adequate geographical location information. In the arid zone of western China, a widely accepted belief is that rapid farmland expansion and the subsequent abandonment of the farms, or their mis-management, would lead to soil salinisation and desertification. In order to better understand the spatio-temporal pattern of farmland change, this paper proposes an integrated approach that combines the two methods of pixel-based trajectory analysis and class-level spatial pattern metrics. Multi-temporal remote sensing images were collected beginning in 1994, a year that captured the initial effects of the period of rapid farmland expansion. Historical change trajectories were established for each pixel and categorized according to change types ( i.e . expanding or shrinking). The spatial dynamics of farmland change can then be illustrated by mapping the change trajectory classes. Spatial patterns of farmland change were quantified by employing distribution-related landscape metrics, such as indices of interspersion (IJI), connectivity (COHESION) and isolation (ENN), to analyse farmland development models of the two river basins in the study area. Shape indices, including overall shape (nLSI) and edge shape (FRAC), were applied to appraise the structural stability of the farmlands over time. Results indicate that, over the past two decades, the area subject to farmland expansion was significantly larger than that experiencing farmland abandonment. The relatively rapid expansion of farmland exhibited a concentrated pattern, and generally followed a layer-based development model. The study showed that the proposed research method effectively visualized and quantified the spatio-temporal dynamics of farmland change. [ABSTRACT FROM AUTHOR]

The paper examines the role of mountain runoff in the seasonal growth of oasis vegetation in the hyper-arid region of northwest China. Central to this examination is the development of a simple hydrologic model that relates hydrologic inflows and outflows estimated from remote sensing data (e.g., evapotranspiration, precipitation, snow accumulation, and snowmelt) to the calculation of runoff over a ten-year period (2000–2009). Modeled runoff is shown to reproduce the seasonal trends in hydrometric data fairly well, yielding R 2 's of 0.75 and 0.66 for stations in the upper reaches of the Shiyang and Hei River systems. Greater than 90% of the runoff from the Qilian Mountains to the oases occurs during the May–September period. Considerable discrepancy between modeled and observed runoff exists in the lower reaches of the rivers, where significant amounts of river water (>45%) are routinely extracted for cropland irrigation. Along the river systems, where water extraction and inflow of glacial meltwater are minor, model calculations replicate observed water yields much more closely. Analysis of seasonal trends in the contribution of snowmelt and rainfall to the return flow, reveals snowmelt as having the greatest influence in initiating the oasis growing period during the March-to-May period of each year. [ABSTRACT FROM AUTHOR]

A significant part of the world's largest river basins are located in areas of arid and semi-arid climate, such as the Amu Darya, Jordan, Murray-Darling, Yellow River, and Aksu-Tarim river basin. These river basins are experiencing water scarcity resulting in conflicts between upstream and downstream, conflicts between water users, and degradation of the natural ecosystems. Therefore, in many river basins, including the Aksu-Tarim river basin, water quota systems have been established, in order to allocate water under scarcity. The Aksu-Tarim river basin (NW China) has developed into one of the most important cotton production areas worldwide. In this paper, we aim at assessing the water consumption through irrigated agriculture, mainly cotton, and natural vegetation in the Aksu-Tarim river basin against the background of this water quota system. Firstly, we map the evapotranspiration (ET a ) as water consumption of irrigated agriculture and natural vegetation in the Aksu-Tarim river basin. Secondly, we calculate water balances and relate them to the water quota system. We employed the remote sensing method Simplified Surface Energy Balance Index (S-SEBI), in order to map ET a based on MODIS satellite images for the growing seasons 2009, 2010, and 2011. Thereby, the MODIS products 8-day land surface temperature (MOD11A2), 16-day albedo (MCD43A3), and 16-day NDVI (MOD13A1) were used. The ET a of cotton ranges from 884 to 1198 mm. The ET a of the natural vegetation of a total coverage ranges from 715 in 2009 to 960 mm in 2011, clearly following the annual runoff of the Aksu and Tarim River. The water balance of the Aksu-Tarim river basin is −3.25 to −3.73 km 3 , 0.1–0.53 km 3 , and −3.55 to −4.12 km 3 in 2009, 2010, and 2011, respectively. The water quotas along the Aksu River and the upper reaches of the Tarim are exceeded by water consumption, while the quotas along the middle and lower reaches are not met. Considerable amounts of groundwater, including fossil groundwater, are exploited for irrigation along the Aksu and Tarim River, which must be regarded as exploitation of a non-renewable resource. [ABSTRACT FROM AUTHOR]

Biological Soil Crusts (BSCs) are critical components of desert ecosystems worldwide. While all BSCs significantly modify the surfaces they occupy, the manner in which they affect their environment depends on the composition of the microphytic community. The aim of this paper is to study the hyperspectral thermal emissivity signatures of BSCs in order to identify and characterize them in a sand dune environment. The research was conducted in the northwestern Negev dunes. Measurements of several types of BSCs and bare soil were obtained using ground hyperspectral thermal sensors. We present an ability to spectrally separate different types of BSCs from bare sand, and to rank them according to successional development. Based on this ability, we created a spectral index for the discrimination of sand and BSCs of different types and applied it to multispectral remote sensing thermal images. This newly acquired ability to map different BSC types, using remote sensing, may lead to future applications of habitat and ecological function spatial mapping. We also demonstrate how a fusion of reflective and thermal data can be used to map different land-cover features in a sand dune environment. Our proposed thermal index not only discriminates sand and BSCs, but also enhances the signal from limestone pebbles more than other indices, based on reflective data. Unlike remote sensing in the reflective spectral region, thermal remote sensing is unconstrained by solar illumination. High resolution emissivity signatures of land cover are unaffected by environmental variables, as opposed to land-surface temperature that depends on the time of day and the season. [ABSTRACT FROM AUTHOR]

Desertification in Kazakhstan affects the country's environment, agriculture and animal husbandry. It is critical to quickly and accurately identify the locations of desertification land and grasp the main causes of desertification in different states in Kazakhstan. This paper builds a new technical framework for desertification identification. Through a comprehensive analysis of desertification sensitivity, long-term trends and stability of net primary productivity (NPP), the authors determined the spatial distribution of land desertification in Kazakhstan and further analyzed the possible driving factors of desertification. The results showed that (1) approximately 76.1% of Kazakhstan land is considered desertification sensitive areas with moderate and higher sensitivity; (2) the area of desertification land in Kazakhstan is approximately 1.04 × 105 km2, accounting for 3.8% of the total land area, which is mainly distributed across seven states in western, northwestern and southwestern Kazakhstan; and (3) in the four main desertification states (West Kazakhstan, Aktobe, Mangystau and Atyrau), the climate warming and drying trends are significant. Large-scale and intensive human activities in agriculture and animal husbandry in the two main desertification regions in northern Kazakhstan have promoted land desertification to some extent. Targeted agricultural and industrial regulatory actions should be taken to prevent and control land desertification. The desertification mapping technical framework established in this paper can be used in other parts of the world. The conclusions about the driving factors have reference value for the government authorities of the states of Kazakhstan. • The a new technical framework for desertification identification was constructed. • Approximately 76.1% of Kazakhstan land is considered desertification sensitive areas with moderate and higher sensitivity. • Area of desertification land in Kazakhstan is approximately 1.04 × 105 km2, accounting for 3.8% of the total land area. • The desertification mapping technical framework established can be used in other parts of the world. [ABSTRACT FROM AUTHOR]

Abstract: This review is concerned with the aeolian geomorphology of the Namib Sand Sea, part of the Namib Desert in Namibia, south-west Africa, concentrating in particular on studies made over the past 50 years. The paper covers: sand sea organisation and dune patterns; and the dynamics of individual dunes. It demonstrates that studies in the Namib Sand Sea have been important to a much wider understanding of the geomorphological development of global sand seas. [Copyright &y& Elsevier]

Abstract: Carbon stocks and carbon accumulation in the earth''s drylands have gained increasing attention. The winter-cold deserts of Middle Asia, i.e. in Kazakhstan, Uzbekistan, and Turkmenistan, cover an area of 2.5 million km2. Within these deserts, the two Saxaul species White Saxaul (Haloxylon persicum Bunge ex Boiss. & Buhse) and Black Saxaul (Haloxylon aphyllum (Minkw.) Iljin) are dominant woody species with a potential distribution area of about 500,000 km2. From the 1950s until today, the Saxaul vegetation has been degraded through logging and over-grazing. In this paper, we estimate the current and potential living above ground and below ground biomass of the Saxaul vegetation and its carbon stock. The living above ground biomass ranges between 1.5 t/ha and 3 t/ha. The potential carbon stocks above ground and below ground amount to 29.4–52.1 million t and 22–81.4 million t, respectively. Today, only 11%–28% of the potential biomass and carbon stock have remained. The carbon stock of the Saxaul vegetation is low compared to other ecosystems of the earth, but restoration and conservation of Saxaul vegetation is one way to sequester carbon through vegetation for Uzbekistan and Turkmenistan, which do not have much other woody vegetation. [Copyright &y& Elsevier]

Abstract: In arid Southwest Arabia spatio-temporal patterning of land and water resources substantially shaped the lives and livelihoods of ancient peoples. This paper examines mid Holocene human subsistence and hydrology along the Wadi Sana drainage, including increased aridity, an associated shift from alluvial aggradation to incision, and its role the appearance of irrigation strategies that supplemented herding economies. Geospatial analyses indicate that (rather than solely the result of increased aridity) the onset of incision along middle Wadi Sana was most plausibly a function of heightened inter and intra-annual precipitation variability. [Copyright &y& Elsevier]

Abstract: Many of the complex issues worldwide regarding environmental management and sustainable develo-pment require integrating the social and natural sciences. Nevertheless, while theoretical discussions have been increasingly developed, operative issues are still major barriers to integrated social–ecological analysis. The aim of this paper was to assess regional forage production in semi-arid rangelands as a key feature in social-ecological analysis, by using human organizational units (i.e. counties). We used these state-administrative units to explore demographic and farming indicators in order to address socio-productive implications of different regional forage production dynamics. We studied the forage spatial and temporal dynamics in two different large ecological regions: Monte and Patagonia, under a single administrative unit (i.e. province). Since forage production estimations in arid rangelands are not trivial, we tested two different methods. We found that inter-annual variability in forage production explained the main differences between regions. At a regional level, zones with higher temporal variability in forage production registered less rural residents and farm numbers, but inverse situations were registered at sub-regional scales. We found a non-linear relationship between forage production variability and rural population density. We proposed differentiated policy recommendations regarding rangeland management and animal husbandry, considering both the social and ecological contexts. [Copyright &y& Elsevier]

Abstract: As in most semiarid regions, the main source of freshwater in SE Spain is its aquifers, and their exploitation has enabled the development of highly profitable irrigated agriculture and tourism industries. The application of sustainable water management plans requires aquifer recharge to be quantified and its spatial pattern evaluated. This paper gives a comprehensive review of various recharge studies in mountainous carbonated aquifers, the most important groundwater reservoirs in SE Spain. Quantification of potential recharge rates and their spatial variability are illustrated using satellite-based modeling and tracer techniques. Actual recharge figures from the application of a lumped model based on water table fluctuations are also presented. Potential recharge relative to actual recharge is around 1 in small aquifers and flat areas and may increase up to 1.3 in heterogeneous mountainous aquifers with deep water levels due to losses of recharge in transit in the vadose zone. The complex interaction between climate, geology, aquifer geometry, topography, soil properties and the degree of karstification prevents the systematization of any particular technique to quantify potential recharge. The use of water table fluctuation methods for actual recharge evaluation requires daily time steps to compute unnoticed small recharge events. Therefore, the monitoring of environmental variables and the use of complementary techniques for comparison are recommended. Despite their importance for the correct assessment of recharge in the region, uncertainty analyses are still scarce, and the natural variability of recharge is unknown in most cases. Effort is required to improve the spatial and temporal characterization of recharge through the integration of interdisciplinary sciences. [Copyright &y& Elsevier]

Abstract: Many researchers have used time-series analysis of remotely sensed images to gain understanding of the dynamics of loss of vegetation cover in drylands. However, complex interactions between vegetation and climate still mask the potential of remote sensing signals to detect human-induced loss of vegetation cover. This paper presents mixed-effect modelling method for time-series NDVI-rainfall relationship to account for the complex interaction between vegetation and climate. Mixed-effects method is a form of statistical modelling that can simultaneously model environmental relationships for a population and for different groups within the population. In this study, it was used to model the NDVI-rainfall relationship in Somalia and for different vegetation types in the country. Its time-series application removed the interaction between vegetation and rainfall and identified areas experiencing human-induced loss of vegetation cover in the country. On average, it gave an accurate relationship between rainfall and NDVI (r 2 >60%) and detected areas with human-induced loss of vegetation cover (kappa=75%). Although the potential of mixed-effects was shown using vegetation types, other factors such as soil types and land use can also be included in the method to improve accuracy of time-series NDVI images in detecting human-induced loss of vegetation cover in the drylands. [Copyright &y& Elsevier]

Abstract: In extra-Andean Patagonia, wet meadows contrast with the prevailing arid steppes, and present a gradient of water availability from the periphery to the center. The objectives of this paper are to describe the spatial and temporal variation of aerial net primary production (ANPP) of Patagonian meadows, and to obtain a model for the relationship between the normalized difference vegetation index (NDVI) and ANPP. We determined ANPP in four regionally scattered meadows during 3–5 years and in three positions of the gradient of water availability. In one meadow, we correlated ANPP with NDVI during 2 years. Annual ANPP was 2–3 times larger in the center than in the periphery, and also varied 2–3 fold among the four meadows. The interannual variation of ANPP was high and similar across meadows and zones. ANPP was closely correlated with NDVI through a linear model. Within the growing season, the central zone had a more extended period of high NDVI into the summer than the peripheral and the intermediate zones. We conclude that (1) the local variation of ANPP across the gradient of water availability is strong and must be taken into account for management, and (2) the highly variable ANPP may be monitored by remote sensing. [Copyright &y& Elsevier]

Abstract: This paper describes evaluation of forest stand density combining satellite imagery with forest inventory data set. The degree of canopy cover is described in terms of fractional vegetation cover (FVC) obtained by a linear mixture model applied on multi-spectral IKONOS image and canopy cover (CC). CC was calculated from field measurements of crown width of 646 standing trees sited within 72 circular (200m2) plots. A comparison between CC and FVC shows that the former can be accurately represented by the latter linking in-situ measured forest characteristics with surface reflectance measured by a satellite. Stand density expressed as an absolute term (number of trees per unit area) showed high and significant positive correlation to FVC (R 2 =0.96) and to relative density measure (Crown Competition Factor; R 2 =0.89). In order to show the applicability of the presented approach for managerial practices, a map of the spatial distribution of stand density within the forest was produced using the above-mentioned correlations. Its quality was verified against an independent data set of ground measurements. The correlation between field- and map-based number of trees per unit area was found to be satisfactory (R 2 =0.4; p <0.05), even though a slight lack of sensitivity was evident for low-density stands. [Copyright &y& Elsevier]

Abstract: This paper analyses the role of climatic aridity on the spatial differences of vegetation activity and its inter-annual variability in a semi-arid region of the North East of the Iberian Peninsula. The vegetation activity was quantified by means of a monthly Normalized Difference Vegetation Index (NDVI) database from NOAA–AVHRR satellite images (1987–2000) at 1km2 of spatial resolution. Coefficients of variation (CoV) from temporal NDVI series were also calculated. The greater temporal variability of NDVI was recorded in areas with low vegetation cover (steppe and dry farming lands), whereas the lowest temporal variability of NDVI was recorded in the irrigated lands and forests located in the most humid areas. There is a strong and negative relationship between the CoV and the NDVI distribution, but we recorded important differences among land uses. Using maps of annual precipitation and temperature obtained by means of a regression-based method, we studied the influence of aridity on spatial patterns of NDVI and CoV values. The results show the high influence of aridity on the spatial distribution of vegetation activity in the Middle Ebro Valley. Aridity causes a general decrease of NDVI and an increase of CoV. Nevertheless, non-linear relationships between aridity and NDVI and CoV were recorded for the whole of the study area and for the different land uses. The relationships between aridity and vegetation patterns in the semi-arid region studied are discussed in depth. [Copyright &y& Elsevier]

Abstract: Mapping soil salinity is difficult due to its large spatial and temporal variability. Remote sensing is widely used to lower survey costs, but existing studies usually analyze bare soils and make little reference to the halophytic plants and their role as salinity indicators. This paper aims to correlate soil characteristics (electric conductivity in saturation extract (ECe) and sodium absorption ratio (SAR) with the spectral response of plant species and bare soils, integrating an algorithm to allow multi-scale mapping using remote sensors. Ground radiance was measured on different plant species and bare soils. A Combined Spectral Response Index (COSRI) was calculated for bare soils and vegetation by adjusting the normalized difference vegetation index (NDVI). ECe and SAR were determined in surface soil samples. Correlation coefficients between COSRI and soil salinity were obtained and a model was adjusted to predict soil salinity. Landsat-ETM and airborne digital images were used to calculate raster maps of COSRI, and ECe and SAR were estimated using adjusted models. Correlation between COSRI and ECe and SAR was of −0.885 and −0.857, respectively. Variance accounted for by exponential models for ECe and SAR was of 82.6% and 75.1%, respectively. It may be concluded that the method is an easy, low-cost procedure to map salt-affected areas. [Copyright &y& Elsevier]

Abstract: Grassland degradation has become a serious environmental problem in China due to climate variability and human disturbances in the arid and semi-arid areas. Establishing grassland protection areas (GPAs) is regarded as an effective measure to protect grassland. This paper presents a new method to support the local government''s effort in zoning of GPAs. It integrates a cellular automata (CA) model with geographical information system (GIS) and remote sensing. The proposed method includes two major steps: 1. to extract “seed points” of candidate GPAs using remote sensing techniques and GIS; 2. to simulate the zoning of GPAs using a CA model. The performance of the proposed method is evaluated using a case study in Xilingol steppe grassland in Inner Mongolia Autonomous Region of China. The results show that the integrated approach can rapidly find candidate GPAs that satisfy the zoning requirement. It has demonstrated that the proposed method of grassland protection zoning provides valuable decision support tools for government and planning agencies. [Copyright &y& Elsevier]

The Israel–Egypt border region composed of longitudinal sand dunes is a very unique arid environmental ecosystem in the world: the Israeli side with much more vegetation cover has notably higher land surface temperature (LST) during daytime than the Egyptian side where bare sand prevails. In order to understand this thermal anomaly and its scientific significance in the arid environmental ecosystem development, a series of intensive research activities have been conducted in the past several years, including remote sensing analysis and meteorological modeling. In the paper, we present part of the series studies on the issue: the ground temperature measurement and emissivity determination. The region is mainly composed of four basic surface patterns: biogenic crust, bare sand, vegetation and playa (physical crust). Our hypothesis to occurrence of the thermal anomaly is that it is the direct result of the different surface composition structures and ground emissivities on both sides. Results from our ground temperature measurements during 1997–1998 validate the hypothesis of a significant LST difference existing among the main surface patterns of the region. Biogenic crust covering 72% on the Israeli side and only about 12% on the Egyptian side has an average kinetic surface temperature of above 3°C higher than bare sand. Emissivity of the two most important surface patterns also presents a significant difference. Biogenic crust has an average emissivity ranging from 0.9671 at low temperature to 0.9725 at high temperature. Bare sand occupying above 80% of the surface on the Egyptian side and only about 7% on the Israeli side has an average emissivity between 0.9435 and 0.9543. On the basis of the ground temperature measurements, we use the estimated surface cover percentage to factor the emissivity for a simple simulation of average LST on both sides, which results in an outcome that strongly support the explanation of the thermal anomaly in the border region. Since biogenic crust that covers most surface of the region plays important functions in arid ecosystem development and is common in several deserts such as north Africa and central Australia, our documentation of its surface temperature change and determination of its emissivity, which have not been seen in the literature, will provide valuable scientific basis for other studies on arid environmental ecosystems. [Copyright &y& Elsevier]

Detailed soil maps are required for land evaluation and subsequent comprehensive land-use planning of the Jordanian arid to semi-arid area. The purity and the details of a suitability map are improved when a detailed soil map is used to produce it. This paper investigates the use of Landsat TM images and topographic data to assist in differentiating areas which represent soil-mapping units, at a detailed level. A 3-D view of Landsat TM image data using an air photo-derived DEM proved the best method to assist in this differentiation. Overlaying the soil observation points enhances this view, and provides a tool to validate the delineation. Further research is needed to investigate the interactive use of air photo or satellite image-derived DEMs and satellite data, with more focus on-site-specific planning and field verification of the technique. [Copyright &y& Elsevier]

This paper is a first attempt to compute the total water needs of an agricultural plain with remote sensing and ground data in Iran. The cropping areas were mapped with Sentinels-2 images, based on NDVI profiles classification. This model was validated and 85% of the areas were correctly classified. Second, the crop water needs were computed using PYSEBAL and Landsat-8 images. Crop evapotranspiration (ET season) and Irrigation Requirements (IR season) were calculated for each crop and then validated by comparing IR collected in the field from farmers with computed IR PYSEBAL on 5 plots. IR PYSEBAL underestimated the reality with an average of 10% while the overestimation average was 17%. The second validation was the comparison of Daily ET from FAO-56 method and Daily ET PYSEBAL showed a RMSE of 0.67 mm/day and MAE of 0.52 mm/day, which assesses the accuracy of PYSEBAL. ET season varies according to weather parameters in the plain and IR season , according to different irrigation practices. The most water demanding crops were identified: rice (IR: 1427 mm) and corn (669). The total water balance of Marvdasht was negative in 2018 with 0.2859 km3 of extracted groundwater for irrigation for only 0.098 km3 of available water for aquifers recharge. • This study assessed the water balance of a semi-arid agricultural plain. • Retrieved water use by farmers from PYSEBAL was accurate. • Crop areas classification with Sentinel-2 images through NDVI profiles was accurate. • PYSEBAL Land Surface Temperature influences ET variability more than Radiation. • The water balance of Marvdasht plain was negative. [ABSTRACT FROM AUTHOR]

In this paper, a new approach for mapping polygenic depressions colonised by vegetation is presented. These spatially periodic vegetation patterns situated in the arid areas of North Africa are known locally as "Dayas". The mapping of these structures is an important component in monitoring their evolution which can be regarded as an indicator of socio-environmental conditions. For this purpose, a method based on satellite image analysis is proposed. First, Landsat Thematic Mapper image inspection is performed to highlight the vegetation spots using the Normalized Difference Vegetation Index (NDVI). Then, a Differential Morphological Profile (DMP) which includes both spectral and morphological information, is built for each NDVI pixel. We adapt the F-Score technique combined with the SVM classifier, to select and classify the most effective DMP images in order to extract the Daya's signature. Using feature selection, overall classification accuracy reached 97.8% with a kappa value of 95.61 but also reduced the dimension of the DMP vector. Dayas' morphological and vegetation characteristics are related to their degree of evolution. Furthermore, we categorise categorise the 170 extracted Dayas into three classes according to their size. On the resulting map, each class corresponds to a specific morphological and vegetation evolution stage. • The established methodology allows Dayas identifying in semi-arid areas. • Differential Morphological Profile is a powerful tool for spots vegetation mapping. • Size-based classification of Dayas enables a chronological distribution. • F-Score combined with SVM for feature selection improves classification accuracies. [ABSTRACT FROM AUTHOR]

In arid and semi-arid regions, unregulated land use changes as a result of poor planning, and the expansion of agricultural and livestock activities increase the risk of desertification and other potentially severe environmental impacts. Several consequences of improper land management practices are soil deterioration and erosion, which may be intensified by meteorological events. This paper presents a historical evaluation of the temporal and spatial evolution of soil deterioration in the southern Chihuahuan Desert in Mexico. A multi-temporal analysis of the study area during the 1995–2016 period was carried out using satellite data (Landsat series). Two seasons were analyzed to determine the influence of external events such as rainfall and wind: dry and rainy. The identification of soil conditions was based on the Brightness Index (BI) considering the complete satellite data set. The soil conditions were classified into five categories according to their reflectance values: highly deteriorated, deteriorated, in the process of being deteriorated, in good condition and other (clouds, water, non-soil). The change detection maps clearly show a growing trend wherein areas of deteriorated and eroded soil increase over time. Agriculture and strong winds are the two main factors involved in the soil deterioration process of the study region. • Deficient agricultural practices and strong winds precursors to desertification. • Spatial-temporal identification of deteriorated soil in arid/semi-arid zones. • Spectral analysis based method for categorization of soil conditions. • Comparative analysis of sensitivity in rainy and dry seasons. [ABSTRACT FROM AUTHOR]