Regional Desertification Research Articles

A New Large-Scale Monitoring Index of Desertification Based on Kernel Normalized Difference Vegetation Index and Feature Space Model

As a new vegetation monitoring index, the KNDVI has certain advantages in characterizing the evolutionary process of regional desertification. However, there are few reports on desertification monitoring based on KNDVI and feature space models. In this study, seven feature parameters, including the kernel normalized difference vegetation index (KNDVI) and Albedo, were introduced to construct different models for desertification remote-sensing monitoring. The optimal desertification remote-sensing monitoring index model was determined with the measured data; then, the spatiotemporal evolution pattern of desertification in Gulang County from 2013 to 2023 was analyzed and revealed. The main conclusions were as follows: (1) Compared with the NDVI and MSAVI, the KNDVI showed more advantages in the characterization of the desertification evolution process. (2) The point–line pattern KNDVI-Albedo remote-sensing index model had the highest monitoring accuracy, reaching 94.93%, while the point–line pattern NDVI-TGSI remote-sensing monitoring index had the lowest accuracy of 54.38%. (3) From 2013 to 2023, the overall desertification situation in Gulang County showed a trend of improvement with a pattern of “firstly aggravation and then alleviation.” Additionally, the gravity center of desertification in Gulang County first shifted to the southeast and then to the northeast, indicating that the northeast’s aggravating rate of desertification was higher than in the southwest during the period. (4) From 2013 to 2023, the area of stable desertification in Gulang County was the largest, followed by the slightly weakened zone, and the most significant transition area was that of extreme desertification to severe desertification. The research results provide important decision support for the precise monitoring and governance of regional desertification.

Analysis of Spatiotemporal Dynamics of Land Desertification in Qilian Mountain National Park Based on Google Earth Engine

Notwithstanding the overall improvement in the ecological condition of the Qilian Mountains, there are localized occurrences of grassland degradation, desertification, and salinization. Moreover, timely and accurate acquisition of desertification information is a fundamental prerequisite for effective monitoring and prevention of desertification. Leveraging the Google Earth Engine (GEE) platform in conjunction with machine learning techniques, this study aims to identify and extract the spatiotemporal dynamics of desertification in the Qilian Mountain National Park (QMNP) and its surroundings (QMNPs) spanning from 1988 to 2023. Results show that based on the random forest algorithm, the multi-index inversion methodology achieves a commendable overall accuracy of 91.9% in desertification extraction. From 1988 to 2023, the gravity center of light desertification shifts southeastward, while centers characterized by moderate, severe, and extremely severe desertification display a westward retreat with fluctuations. The area of sandy land shows an expansion trend in the medium term, but after 2018, desertification in QMNPs reversed. As of 2023, the sandy land area measured 16,897.35 km2, accounting for 18.29% of the total area of QMNPs. The insights garnered from this study provide a valuable reference for regional desertification prevention and control in the future.

Remote sensing dynamic analysis of regional desertification evolution based on geological modelling

Remote sensing dynamic analysis of regional desertification evolution based on geological modelling

Remote sensing dynamic analysis of regional desertification evolution based on geological modelling

Remote sensing dynamic analysis of regional desertification evolution based on geological modelling

The Latest Desertification Process and Its Driving Force in Alxa League from 2000 to 2020

Alxa League of Inner Mongolia Autonomous Region is a concentrated desert distribution area in China, and the latest desertification process and its driving mechanism under the comprehensive influence of the extreme dry climate and intense human activities has attracted much attention. Landsat data, including ETM+ images obtained in 2000, TM images obtained in 2010, and OLI images obtained in 2020, were used to extract three periods of desertification land information using the classification and regression tree (CART) decision tree classification method in Alxa League. The spatio-temporal variation characteristics of desertification land were analyzed by combining the transfer matrix and barycenter migration model; the effects of climate change and human activities on regional desertification evolution were separated and recombined using the multiple regression residual analysis method and by considering the influence of non-zonal factors. The results showed that from 2000 to 2020, the overall area of desertification land in Alxa League was reduced, the desertification degree was alleviated, the desertification trend was reversed, and the desertification degree in the northern part of the region was more serious than in the southern part. The barycenter of the slight, moderate, and severe desertification land migrated to the southeast, whereas the serious desertification land’s barycenter migrated to the northwest in the period of 2000–2010; however, all of them hardly moved from 2010 to 2020. The degree of desertification reversal in the south was more significant than in the north. Regional desertification reversal was mainly influenced by the combination of human activities and climate change, and the area accounted for 61.5%; meanwhile, the localized desertification development was mainly affected by human activities and accounted for 76.8%.

The underestimated role of tectonics in the mid-Late Cretaceous desertification in SE Asia

The relative roles of tectonics and climate change in global and regional desertification are not well constrained. Previous studies have emphasized the role played by climate change as a dominant cause of southeastern (SE) Asia desertification during the mid-Late Cretaceous. The effect of early uplift of the Tibetan Plateau prior to the collision between Eurasia and India on regional desertification remains poorly understood. We present a comprehensive set of provenance data on two aeolian sequences deposited in the Simao Basin and Khorat Plateau desert environments adjacent to southeast Tibet. Our provenance results suggest that the aeolian sandstones of the Pashahe Formation in the Simao Basin were largely recycled from exposed sedimentary rocks of the Songpan-Garze terrane, Southern Qiangtang terranes, and northern Yangtze Block with minor contributions from the magmatic rocks of the Tengchong and Southern Qiangtang terranes. Combined with other evidence, provenance results indicate the source areas started to grow and to be rapidly unroofed and determined the birth of the transcontinental southerly flowing paleo-river, which carried the sand to be stored. In contrast, the Phu Thok aeolian sandstones in the Khorat Plateau were predominantly sourced from the exposed Sibumasu igneous rocks together with recycled detritus in the Sukhothai Arc terrane, which was possibly transported by a local river. Hence, our thesis is that elevated topography caused by the closure of the Bangong-Nujiang Mesotethys profoundly affected the atmospheric circulation and drainage development, leading to mid-Late Cretaceous desertification across SE Asia.

Finding an optimal selection in diversify combating modes for desertification region

The differential game method effectively reflects the multi-agent, long-term, and dynamic characteristics of combating regional desertification. Considering the differences in the levels of economic development level and governance technology between adjacent areas, three desertification-combating modes are proposed for exploratory purposes. The differential game models of the two regions combating desertification areas are constructed as per the certain level of cooperation, ecological subsidy, and technology transfer modes. The optimal combating mode is found by comparing the equilibrium results. The study demonstrates that when cooperation level dominated by the region with higher economic and governance technology levels is lower than the threshold $ \phi^{*}_{u_2} $ and $ \phi^{*}_{1V} $, the technology transfer mode is optimal, and the level of cooperation does not affect the technology transfer fee. However, when cooperation level is higher than the threshold $ \phi^{*}_{u_2} $ and $ \phi^{*}_{1V} $, the ecological subsidy mode is optimal. Meanwhile, as the dominant region further raises the cooperation level, it can drive the non-dominant region to increase the desertification combating input level. The certain level of cooperation mode is the least efficient of the three modes. However, when compared with the situation of completely independent governance by the two regions, the certain level of cooperation mode can relatively improve the efficiency of regional desertification combating.

Morphological changes and dynamic mechanism of blowouts on fixed dunes in the Otingdag sandy land, China

<p indent="0mm">Blowouts are a major indicator of fixed dune reactivation, and their continuous occurrence and expansion aggravate the process of regional desertification. Therefore, research on the morphological evolution and dynamic processes of blowouts is paramount not only to understanding reactivation processes in stabilized and semistabilized dune fields but also to accurately assessing regional desertification trends. At present, much research has focused on blowouts in coastal dunes and flat grasslands, and little research has focused on the evolution mode of blowouts that have developed on fixed dunes in semiarid inland areas. Moreover, the morphological changes and airflow dynamics of blowouts are usually analyzed separately, and research integrating the two is still insufficient. In this paper, a fixed dune on the southern edge of the Otingdag sandy land was selected as the research object. A high precision real-time kinematic global positioning system (RTK-GPS) and 17 2D ultrasonic anemometers were used to measure the topography and airflow of four blowouts with different morphologies on the fixed dunes, and the multiperiod imaging data and multiyear meteorological data were used to monitor the morphological changes of each type of blowout and the regional meteorological conditions. The goal of this research is to reveal the morphological evolution, erosion-accumulation characteristics and airflow distribution patterns of each type of blowout and to discuss the relationship among the topography of fixed dunes, morphology of various blowouts and airflow variation. The results showed that the length, width and area of each type of blowout continued to increase from 2010 to 2021, and the overall shapes of each type of blowout tend to be oval or trough-shaped. The expansion direction of the blowout shape has a general corresponding relationship with the erosion-accumulation pattern in the deflation basin. The eastern and southeastern edges of the deflation basins are the most severely eroded, and their overall shapes expand from west to east. Relative to the wind direction of the field reference station, the approaching wind direction of the blowouts hardly deflects at the foot of the windward slope of the fixed dune, while it deflects significantly at the middle and top of the fixed dune, and the deflection angle changes with the regional wind direction. Both the blowout shapes and the approaching wind directions determine the airflow pattern within the blowouts. Based on a detailed analysis of both the regional climate and the morphological changes in blowouts, this study considered that the effect of the topography of fixed dunes on regional airflow could be the fundamental reason for the morphological differences in blowouts. The shape of blowouts determines the airflow pattern in the deflation basin, and the change in the wind speed and wind direction in turn affects the erosion-accumulation pattern and finally changes the evolution direction of blowouts. The research results can act as a good supplement for studying blowouts in semiarid inland areas.

Dynamics of blowouts indicating the process of grassland desertification

AbstractSand desertification is a serious ecological and environmental problem in semiarid grassland areas; thus an accurate understanding of its causes and process mechanisms is of significance for grassland desertification control. With the popularization of remote sensing monitoring technology, most research has focused on analyzing the trends of grassland sand patches and their impact on regional desertification, whereas fewer studies have explored the mechanisms of grassland desertification development. This study analyzed the dynamic changes in grassland landscape in the Hulun Buir grassland of China via multiperiod high‐resolution remote sensing images from 1959 to 2020, and examined the morphological changes, erosion patterns, grain size characteristics and sediment compaction of two trough blowouts. Our study noted that under climate change and human activities, grassland desertification is becoming increasingly serious, and its main manifestation is the occurrence and expansion of blowouts. Changes in blowout morphologies indicate that the area of the deflation basin shows a state of continuous growth, whereas the area of the depositional lobe shows fluctuating changes, which could mean that the deflation basin may be a useful indicator of desertification. Based on a detailed analysis of both climate and grassland changes, we believe that human activities determine the occurrence of blowouts, and climatic conditions determine the expansion of blowouts and the desertification degree. The morphological changes of blowouts are related to the removal mode and erosion resistance of the grassland soil, and the rate of removal of the soil limits the rate of blowout expansion.

An Analysis of the Driving Factors of the Desertification in the Desert-Oasis Transition Zone Utilizing the Perspective of the Marx’s Concept of Nature: A Case Study of the Ulan Buh Desert

The Ulan Buh Desert is in an arid and semiarid area in China, which features an exceedingly vulnerable ecological environment and has severe desertification. Based on Marx’s explanations for the human-nature relationship, this research applies the remote sensing data and meteorological and socioeconomic data from 2006 to 2018 to conduct a quantitative analysis of the desertification driving factors in the Ulan Buh Desert by adopting the method called multivariate random forest regressor. The findings of the research suggested that the average model employing a random forest algorithm is found to be 84.20%. The desertification in the Ulan Buh Desert showed a declining trend from 2006 to 2018, and the reversed desertification areas mainly are expanded into the hinterlands of the Ulan Buh Desert and along the Yellow River. While the main driving factor of desertification was found to be related to human activities, which were undertaken based on natural factors, the regional desertification was mainly attributed to human economic activities, population density, and altitude. Thus, lessening the excessive impact of human activities on the desert ecosystem would be crucial to protecting the local desert resources and increasing the ecological capacity of the desert ecological capacity. As a consequence, to reduce pressure on land, expand environment capacity, protect vegetation cover in the region, and lower the probability of triggering desertification, the interaction between human beings and nature should be carefully managed and observed.

Biogeomorphology of nebkhas in the Mu Us dune field, north-central China: Chronological and morphological results

Nebkhas, also known as nebkha dunes or coppice dunes, are a unique biogeomorphological aeolian landform that is common in arid and semi-arid regions. They are often regarded as a signal of regional desertification and could be potential dust sources due to their relatively large content of fine sediments, but they also serve as “fertile islands” that enhance biodiversity at a micro-habitat. How the interactions between plant growth and aeolian sand deposition affect the formation and development of nebkhas has not been well documented, though. In this study, the chronology and morphological features of nebkhas in the Mu Us dune field, north-central China were studied using radionuclide (137Cs) dating and unmanned aerial vehicle (UAV) photogrammetric survey. The results show that the nebkhas are mainly distributed around lake basins and dry river valleys with relatively flat topography. Most nebkhas have heights around 0.5–1.5 m, and according to a new integrated age-height model, they mostly formed in the last fifty years. Widespread nebkha growth over that time is interpreted as a response to both desiccation of lake beds and river valleys and a pronounced decline in strong wind frequency. The regular rounded shape of the nebkhas in the study area may reflect the growth form of prostrate, extensively branched Nitraria tangutorum, the dominant formative shrub, and response to the low-energy wind environment. A nebkha's height and horizontal length increase synchronously in the early stage of the development, while the increase in horizontal length and projected area accelerates when the dunes become larger. Feedbacks involving both aeolian sand transport and shrub growth can explain a decline in growth rate with increasing height and an apparent height limit of about 4 m. This study also implies that nebkhas are important biogeomorphological features demonstrating how biotic and abiotic interactions can shape landforms and influence ecological functioning in arid and semi-arid environments.

Mapping groundwater-dependent ecosystems in arid Central Asia: Implications for controlling regional land degradation

Groundwater-dependent ecosystems (GDEs) exist all over the world, especially in water-limited regions. To achieve better water management, it is necessary to map and identify GDEs. Central Asia (CA) is one of the most arid regions in the mid-latitudes and one of the major regions with shallow groundwater tables. However, the role of groundwater in the impacts of climate change and regional anthropogenic activities on environmental risks, especially regional desertification, is inadequately understood due to the limited available research on GDEs. In the present study, a remote sensing-based method was used for mapping GDEs in regional CA, and three means—overlay analysis, correlation analysis, and the water balance method—were adopted to validate the accuracy of the mapping outcomes. Our results indicated that: 1) GDEs were concentrated around large lakes and in central Kazakhstan (between 46°N and 50°N latitudes), and areas “Very Likely” and “Likely” to be GDEs accounted for 36.89%, and 28.85% of the total natural vegetation areas, respectively; 2) at the watershed scale, the Sarysu Basin had the largest proportion (94.02% of the area) of potential GDEs while the Ysyk-Kol Basin had the lowest proportion (17.84%); 3) all the three validation methods indicated a good performance for our GDE mapping results. We concluded that the remote sensing-based GDE identification method can be considered a potential approach for mapping GDEs regionally. Better recognition of relationships among groundwater availability, ecosystem health and groundwater management policies should be developed by conducting further studies, to protect GDEs and to prevent regional land degradation.

Spatiotemporal changes of land desertification sensitivity in northwest China from 2000 to 2017

Sensitivity assessment is useful for monitoring land desertification. Research into how to prevent and control desertification is also important. In the arid region of northwest China, desertification is becoming worse and is a serious problem that affects local sustainable development. Based on remote-sensing and geographic information system technology, this study establishes a “soil-terrain-hydrology-climate-vegetation” desertification sensitivity comprehensive evaluation system to reflect the spatiotemporal changes of land desertification, and proposes a spatial distance model to calculate a desertification sensitivity index. The spatiotemporal change characteristics of land desertification sensitivity in northwest China are quantitatively assessed from 2000 to 2017. Moreover, the main driving factors are analyzed using the geographical detector method. The results show the following. (1) Terrain, soil, climate, vegetation and hydrology affect and restrict each other, and constitute the background conditions of the distributions and changes of sensitivity to desertification in northwest China. (2) Desertification sensitivity generally displays a low distribution characteristic on the periphery of the area and a high one in the interior. The low-sensitivity regions are mainly in the five major mountain ranges (Altai Mountains, Tianshan Mountains, Kunlun Mountains, Altun Mountains and Qilian Mountains), while the high-sensitivity regions are mainly in regions such as the Junggar Basin, the Tarim Basin and the Inner Mongolia Plateau, as well as the Taklimakan Desert, Badain Jaran Desert and Tengger Desert. The spatial distribution of desertification sensitivity is obviously regional, and the high- and low-sensitivity regions have clear boundaries and a concentrated distribution. (3) With regard to spatiotemporal evolution, changes in desertification sensitivity since 2000 have been predominantly stable, and the overall sensitivity has displayed a slowly decreasing trend, indicating that potential desertification regions are decreasing annually and that some achievements have been made in the control of regional desertification. (4) Soil and climate play a direct role in the driving factors of desertification in northwest China, and these have been found to be the most important influential factors. Vegetation is the most active and basic factor in changing the sensitivity. In addition, topography and hydrology play a role in restricting desertification changes. Socio-economic factors are the most rapid factors affecting regional desertification sensitivity, and their impacts tend to be gradually increasing. In general, desertification has been effectively controlled in northwest China, and positive results have been achieved in such control. However, against the backdrop of intensified global climate change, increasingly prominent human activities and new normals of socio-economic development, the monitoring, assessment and control of desertification in China still have a long way to go.

Early-Warning System for Desertification Based on Climatic and Hydrologic Criteria

The United Nations’ convention on desertification encourages the participating countries to introduce criteria for developing Early-Warning Systems (EWS) in order to monitor and assess desertification. The objective of the present study was to establish an EWS for desertification assessment in Kashan plain, Iran, using the methodology of practical and general applicability. Designing EWS requires a model to identify the influential criteria and areas vulnerable to desertification. The Kashan Plain’s EWS relies on the Iranian Model for Desertification Potential Assessment (IMDPA) to establish desertification thresholds and generate desertification maps with Geographic Information Systems (GIS). The EWS of Kashan plain was designed to calculate hydrologic (groundwater level and electric conductivity of groundwater indices) and climatic (precipitation, Transeau aridity, and drought indices) criteria and assess the degree of regional desertification. Afterwards, the desertification intensity maps of criteria and indices were produced and overlapped. The EWS was developed in areas most bound to be threatened by desertification. EWS quantifies desertification data and thresholds to issue desertification assessments and warnings for management purposes. In the next step, Client–Server program was designed based on an algorithm defined by Java programming language and implemented as a data collection, analysis, and response management system. Whenever the thresholds exceed the defined limits, warning messages can be sent via SMS or internet to relevant system managers for appropriate action.

Unraveling the impacts of droughts and agricultural intensification on the Altiplano water resources

During the last decades, agriculture has drastically increased over the South American Andean Plateau (Altiplano), resulting in extensive changes in land cover from native vegetation to essentially Quinoa crop. Along with climatic variability, these land use changes appear as a catalyst in worsening the already existing drought events and water scarcity processes. Hence, understanding their relative contributions to the regional desertification process is crucial for sustainable water-use adaptation, but also is quite ambiguous because of water resource data scarcity over the Altiplano. Therefore, in the present study, an attempt to measure the impact of severe droughts and agricultural intensification on the water resources has been made using remote sensing datasets. The first step was dedicated to the validation of newly released CHIRPS v.2 precipitation and GLEAM v.3 potential evapotranspiration products by comparing their estimates with the results obtained from gauges data. Then, the Standardized Precipitation Index (SPI) was used to describe past hydro-meteorological drought events in terms of their spatial extent, duration, intensity and their impacts on the regional water resources. Finally, the dynamic trends in the spatial extent of the Quinoa crop and the meteorological conditions derived from CHIRPS v.2 and GLEAM v.3 were compared with the Vegetation Condition Index (VCI) and the Total Water Storage (TWS) derived from AVHRR and GRACE data respectively, to observe the respective influence of agriculture and climate variability on the regional hydrological system. A significant increase in Quinoa crop extent is observed from 2001 which corresponds to a significant decrease in regional VCI and TWS. Based on this trend, agriculture appears as a contributing factor in the water scarcity process over the Altiplano. The outcomes of this study will contribute to local decision making for a better water management and hydro-meteorological monitoring system.

FUZZY INTEGRATED DESERTIFICATION VULNERABILITY MODEL

Abstract. Desertification and Land Degradation have constantly affected the global environment over the years. Land degradation is a reduction or loss of productivity over land due to natural processes, climate change and human activities. It involves complex set of processes, which interacts over space to decrease in land productivity. In the present study, regional desertification vulnerability assessment was carried out for Bhavnagar district of Gujarat, India. A vulnerability is a basic concept which explains the flaw in any structure of a system. A vulnerability may also refer to any type of shortcoming in systems, sub system parameters or processes, or in anything that leads the system to be exposed to a threat. Fuzzy Logic (FL) method combined with remote sensing (RS) and geographic information system (GIS) techniques has several advantages for assessing vulnerability. Technically FL combines the intricate classical analytic hierarchy process and grey clustering method for estimation of coefficients. Climate, soil, vegetation and land use play a significant role in desertification of any area, hence, in this work, several indices have been generated. However, man’s intervention leads to significant changes in the environment, making socio-economic factor as a major input to assess vulnerability for desertification. Thus in this study FL has been integrated with both natural and socioeconomic factors for understanding the vulnerability to desertification in Bhavnagar region.

Climate-Related Limitations on Photosynthesis and Drought-Resistance Strategies of Ziziphus spina-christi

Current climatic changes are subjecting plants to increasing amounts of abiotic stress and intensifying desertification in many regions. The identification of tree species that can survive extremely limited water conditions may assist in limiting regional desertification processes and mitigating the greenhouse effect. Ziziphus spina-christi is a thermophilic tree from Sudan that is highly tolerant of heat and drought. In recent years, this tree has become more abundant in the Mediterranean region. In order to predict how a warm and dry climate influences the successful establishment of this species, we compared the seasonal photosynthesis of Z. spina-christi trees growing in a Mediterranean climate and a semi-arid climate. At each site, we measured the seasonal changes in gas exchange, chlorophyll fluorescence and stem water potential (Ψstem). We quantitatively compared the seasonality of factors that limit photosynthesis: stomatal conductance (gs), mesophyll conductance (gm) and maximal capacity for Rubisco carboxylation (Vcmax). Our results revealed differences in the seasonality of the trees’ photosynthetic capacities, as well as different drought avoidance and tolerance strategies at the two different sites. Trees grown at the Mediterranean-climate site exhibited high photosynthetic activity during winter-spring and summer, but significantly less photosynthetic activity during the fall drought. During periods of drought, the overall limitation of photosynthesis was mostly due to strong stomatal regulation. Trees in the Mediterranean sites compensate for their lower gs with a larger gm and high Vcmax. In contrast, at the semi-arid site, peak photosynthesis was observed in the spring and fall. The reduced photosynthesis during the summer drought and the period of low temperatures during the winter were associated with greater reduction in gm, as compared to gs, and increased investment in photoprotective mechanisms (NPQ and photorespiration). Relatively low midday Ψstem was observed at both sites during the driest period (>-2.2 MPa), revealing that this species employs drought-avoidance strategies. Our results demonstrate how Z. spina-christi could be an attractive tree for afforestation programs in semi-arid areas and how climate change may give it an ecological advantage that may lead to its becoming more widely distributed across this region in future decades.

Interactive effects of wind speed, vegetation coverage and soil moisture in controlling wind erosion in a temperate desert steppe, Inner Mongolia of China

The rapid desertification of grasslands in Inner Mongolia of China poses a significant ecological threaten to northern China. The combined effects of anthropogenic disturbances (e.g., overgrazing) and biophysical processes (e.g., soil erosion) have led to vegetation degradation and the consequent acceleration of regional desertification. Thus, mitigating the accelerated wind erosion, a cause and effect of grassland desertification, is critical for the sustainable management of grasslands. Here, a combination of mobile wind tunnel experiments and wind erosion model was used to explore the effects of different levels of vegetation coverage, soil moisture and wind speed on wind erosion at different positions of a slope inside an enclosed desert steppe in the Xilamuren grassland of Inner Mongolia. The results indicated a significant spatial difference in wind erosion intensities depending on the vegetation coverage, with a strong decreasing trend from the top to the base of the slope. Increasing vegetation coverage resulted in a rapid decrease in wind erosion as explained by a power function correlation. Vegetation coverage was found to be a dominant control on wind erosion by increasing the surface roughness and by lowering the threshold wind velocity for erosion. The critical vegetation coverage required for effectively controlling wind erosion was found to be higher than 60%. Further, the wind erosion rates were negatively correlated with surface soil moisture and the mass flux in aeolian sand transport increased with increasing wind speed. We developed a mathematical model of wind erosion based on the results of an orthogonal array design. The results from the model simulation indicated that the standardized regression coefficients of the main effects of the three factors (vegetation coverage, soil moisture and wind speed) on the mass flux in aeolian sand transport were in the following order: wind speed>vegetation coverage>soil moisture. These three factors had different levels of interactive effects on the mass flux in aeolian sand transport. Our results will improve the understanding of the interactive effects of wind speed, vegetation coverage and soil moisture in controlling wind erosion in desert steppes, and will be helpful for the design of desertification control programs in future.

Role of Climate Variability and Human Activity on Poopó Lake Droughts between 1990 and 2015 Assessed Using Remote Sensing Data

In 2015, an emergency state was declared in Bolivia when Poopó Lake dried up. Climate variability and the increasing need for water are potential factors responsible for this situation. Because field data are missing over the region, no statements are possible about the influence of mentioned factors. This study is a preliminary step toward the understanding of Poopó Lake drought using remote sensing data. First, atmospheric corrections for Landsat (FLAASH and L8SR), seven satellite derived indexes for extracting water bodies, MOD16 evapotranspiration, PERSIANN-CDR and MSWEP rainfall products potentiality were assessed. Then, the fluctuations of Poopó Lake extent over the last 26 years are presented for the first time jointly, with the mean regional annual rainfall. Three main droughts are highlighted between 1990 and 2015: two are associated with negative annual rainfall anomalies in 1994 and 1995 and one associated with positive annual rainfall anomaly in 2015. This suggests that other factors than rainfall influenced the recent disappearance of the lake. The regional evapotranspiration increased by 12.8% between 2000 and 2014. Evapotranspiration increase is not homogeneous over the watershed but limited over the main agriculture regions. Agriculture activity is one of the major factors contributing to the regional desertification and recent disappearance of Poopó Lake.

The application of satellite-based model and bi-stable ecosystem balance concept to monitor desertification in arid lands, a case study of Sinai Peninsula

Desertification is responsible for depleting natural resources in arid lands, which is globally happening in an alarming rate. It is considered as the major environmental threat that affects about 40% of the world dry lands, which are populated by approximately one billion humans. In this paper the main objective is to discuss the recent and past research in monitoring and assessing desertification and land degradation using remote sensing technology and data. Recently, the Bi-stable ecosystem balance becomes a promising framework theory to detect the spatial extent of prime land degradation in arid and semi-arid environments; it is also a potential methodology to recognize the difference between the natural variability and instantaneous/non-instantaneous desertification symptoms in dry lands. The satellite-based models are the future tools for monitoring very precisely desertification development, MODerate resolution Imaging Spectroradiometer (MODIS) satellite images are becoming the best datasets for building regional desertification monitoring algorithms because of its temporal scales (8–16 days). The MODIS Based Disturbance Index (MBDI) algorithm provide accurate information at six different study sites in Sinai Peninsula and showed the seasonal and yearly changes. This application can be used for monitoring decades of desertification development in North Africa, South Europe, and the Middle East, and can be linked to several fields such as agriculture sustainability, environmental conservations, rural development, and economics.