Desertification Assessment Research Articles

Caring of the Fringe? Mediterranean Desertification between Peri-Urban Ecology and Socioeconomics

This commentary debates on the role of multiple socioeconomic drivers of fringe land degradation (including, but not limited to, population and social dynamics, economic polarization, and developmental policies), as a novel contribution to the desertification assessment in Southern European metropolitan regions, a recognized hotspot of desertification at the global scale. Expanding rapidly all over the world, metropolitan regions are a geographical space where land degradation drivers and processes assume typical relationships that require further research supporting dedicated policy strategies. To assure a better comprehension of the environmental-economic nexus at the base of land degradation in peri-urban areas, we provided a classification of relevant socioeconomic and territorial dimensions in both macro-scale and micro-scale degradation processes. We also identified the related (contextual) factors that determine an increased risk of desertification in metropolitan regions. Micro-scale factors, such as agricultural prices and off-farm employment, reflect some potential causes of fringe land degradation, with a mostly local and on-site role. Technological change, agricultural prices, and household income influence land vulnerability, but their impact on fringe land degradation was less investigated and supposed to be quite moderate in most cases. Macro-scale factors such as population density, rural poverty, and environmental policies—being extensively studied on a qualitative base—were taken as important drivers of fringe land degradation, although their impact still remains undefined. Regional disparities in land resource distribution, rural poverty, and unsustainable management of environmental resources like soil and water were indirect consequences of land degradation in peri-urban districts. Based on a comparative review of theoretical and empirical findings, strategies mitigating degradation of fringe land and reducing desertification risk in potentially affected metropolitan regions were finally discussed for the Northern Mediterranean basin and generalized to other socioeconomic contexts.

Development of Desertification Indicators for Desertification Monitoring from Landsat Images Using Python Programming

Nowadays, desertification is one of the most serious environment socioeconomic issues and sand dune advances are a major threat that causes desertification. Wadi El-Rayan is one of the areas facing severe dune migration. Therefore, it's important to monitor desertification and study sand dune migration in this area. Image differencing for the years 2000 (Landsat ETM+) and 2019 (OLI images) and Bi-temporal layer stacking was performed. It was found that image differencing is a superior method to get changes of the study area compared to the visual method (Bi-temporal layer stacking). This research develops a quantitative technique for desertification assessment by developing indicators using Landsat images. Spatial distribution of the movement of sand dunes using some spectral indices (NDVI, BSI, LDI, and LST) was studied and a Python script was developed to calculate these indices. The results show that NDVI and BSI indices are the best indices in the identification and detection of vegetation. It was found that mobile sand dunes on the southern side of the lower Wadi El-Rayan Lake caused filling up of large part of the lower lake. The indices results show that sand movement decreased the size of the lower Wadi El-Rayan Lake and there are reclamation activities in the west of the lower lake. The results show that a good result could be achieved from the developed codes compared to ready-made software (ENVI 5).

Assessment of karst rocky desertification from the local to regional scale based on unmanned aerial vehicle images: A case‐study of Shilin County, Yunnan Province, China

AbstractKarst rocky desertification is a major ecologic and geologic problem in Southwest China that has restricted the sustainable development of society and the economy. Many methods have been used to evaluate rocky desertification based on satellite remote sensing, but the results of these methods are affected by the heterogeneous surroundings of the karst region and the low resolution of sensors. In this study, a new method that combines satellite images and unmanned aerial vehicle (UAV) images was used to quantitatively extract information and evaluate rocky desertification. First, we extracted the bare rock ratio from the local high‐resolution UAV images, and then the regression models were established between the bare rock ratio of UAV images and the band reflectivity and eight rock indices of satellite images to invert the bare rock ratio at the county scale. The results showed that the overall accuracy and F1 of the classification of UAV images was 97% and 90%, respectively. The linear regression model between the reflectivity of the pixels in band 2 of the LANDSAT image and the bare rock ratio extracted from the UAV images was the best (R2 = 0.86). In addition, our method in which rocky desertification was assessed by the inversion model based on UAV images and LANDSAT images was superior to the traditional approach based on vegetation coverage. These results suggested that we can extract information on rocky desertification based on high‐resolution UAV images and assess rocky desertification by the inversion model from the local to regional scale.

Desertification of Iran in the early twenty-first century: assessment using climate and vegetation indices

Remote sensing of specific climatic and biogeographical parameters is an effective means of evaluating the large-scale desertification status of drylands affected by negative human impacts. Here, we identify and analyze desertification trends in Iran for the period 2001–2015 via a combination of three indices for vegetation (NPP—net primary production, NDVI—normalized difference vegetation index, LAI—leaf area index) and two climate indices (LST—land surface temperature, P—precipitation). We combine these indices to identify and map areas of Iran that are susceptible to land degradation. We then apply a simple linear regression method, the Mann–Kendall non-parametric test, and the Theil–Sen estimator to identify long-term temporal and spatial trends within the data. Based on desertification map, we find that 68% of Iran shows a high to very high susceptibility to desertification, representing an area of 1.1 million km2 (excluding 0.42 million km2 classified as unvegetated). Our results highlight the importance of scale in assessments of desertification, and the value of high-resolution data, in particular. Annually, no significant change is evident within any of the five indices, but significant changes (some positive, some negative) become apparent on a seasonal basis. Some observations follow expectations; for instance, NDVI is strongly associated with cooler, wet spring and summer seasons, and milder winters. Others require more explanation; for instance, vegetation appears decoupled from climatic forcing during autumn. Spatially, too, there is much local and regional variation, which is lost when the data are considered only at the largest nationwide scale. We identify a northwest–southeast belt spanning central Iran, which has experienced significant vegetation decline (2001–2015). We tentatively link this belt of land degradation with intensified agriculture in the hinterlands of Iran’s major cities. The spatial and temporal trends identified with the three vegetation and two climate indices afford a cost-effective framework for the prediction and management of future environmental trends in developing regions at risk of desertification.

Assessment of desertification using modified MEDALUS model in the north Nile Delta, Egypt

Understanding spatial patterns of environmentally sensitive areas (ESAs) to desertification is essential for sustainable land use in the drylands. This work is a novel trial for integrating the erosion quality index (EQI) with a modified Mediterranean Desertification and Land Use (MEDALUS) method and factor analysis to define ESAs to desertification. The model was then applied within 8607.13 km2 (860713 ha) in the north Nile Delta of Egypt as a case study. Climate data, satellite imageries, field observations, and samples collected from 105 soil profiles were analyzed to characterize five thematic quality indices of soil, climate, vegetation, management, and erosion. These indices were weighted based on the factor analysis (FA) and superimposed under the GIS environment in a single map using the weighted sum model. The proposed model showed that 72% of the total area was classified as critical-sensitive to desertification where 70% was classified as highly-critical, while 2% as moderately-critical. No significant difference (p < 0.001) was observed between the results of the proposed model and those calculated by the geometric mean algorithm (MEDALUS model) with R2 and root mean square error of 0.88 and 0.11, respectively. The average linear sensitivity analysis showed that using weights derived from the FA could assimilate the results of the proposed model closer to reality rather than equal weights used in the MEDALUS model. The developed model would improve the insight into desertification processes in the studied area, thereby suitable conservation practices would be adopted in time.

Moving toward the north: A country-level classification of land sensitivity to degradation in Czech Republic

Land sensitivity to degradation is a spatially varying attribute of local systems that experience rapid changes in socio-ecological conditions. To answer the increasing demand of quantitative risk assessment of land degradation and desertification - taken as a final stage of land degradation - in non-affected countries, our study estimates land sensitivity to degradation in the Czech Republic at 1:10,000 scale using the Environmental Sensitive Area (ESA) framework. Czech land was classified into four sensitivity levels (‘insensitive’, ‘potentially sensitive’, ‘fragile’, and ‘critical’). ‘Fragile’ and ‘critical’ land concentrated in accessible lowlands with intensive agriculture. Climate and vegetation quality contributed the most to land sensitivity to degradation in the country. Low soil quality and land management quality were causes of land sensitivity in few, sparse agricultural districts. A comparison with Mediterranean and South-Eastern European countries indicates that land sensitivity to degradation in the Czech Republic is only slightly lower than in neighbouring, affected countries (sensu UNCCD, Annex IV), with the same acting drivers (agriculture intensification and urban sprawl). In light of climate change, national and regional policies are required to face with the increase of land sensitivity in ‘formally non-affected’ countries of Central-Eastern Europe, taking stock of the ‘Mediterranean’ experience in assessing and managing land sensitivity to degradation.

Assessment of Deforestation and Desertification Induced Impacts on Ecosystem Services in Eritrea

Assessment of Deforestation and Desertification Induced Impacts on Ecosystem Services in Eritrea

Archetypal temporal dynamics of arid and semi-arid rangelands

The way in which temporal dynamics structure ecological systems under the influence of a changing environment has long interested ecologists. Tackling the hierarchical structure of complex temporal patterns is a necessary step towards a more complete description of the fundamental nature of temporal dynamics in ecosystems. In pursuance of this task, remote sensing data provide valuable information to classify and describe functional features of ecosystems across scales. To approach the temporal complexity of ecosystems, we proposed a stepwise procedure based on combinations of big data techniques and time series analyses applied to data series of the Normalized Difference Vegetation Index (NDVI). The aim was to classify the temporal patterns and identify the differences in temporal dynamics of vegetation, by means of the frequency-domain and time-frequency domain components of a 20-year period of NDVI time series, respectively. In addition, we analysed the influence of climate in the temporal dynamics of vegetation. In particular, we applied archetype analysis to fast Fourier transform coefficients, using pixels as analytical units and frequencies as variables, of a large study area from North Patagonia, Argentina. Then, the most representative pixels for each archetype were used to analyse the explained variance by climatic predictor variables (temperature and precipitation) using a multiplicative model, whereas NDVI temporal dynamics was also described by means of time-frequency domain components with wavelet analysis, respectively. Six archetypes of temporal dynamics of arid and semi-arid rangelands were identified, as well as the main patterns of their distinctive frequencies through time and spatial location, respectively. The differences in temporal dynamics among archetypes were partly associated with climate and spatial features such as topography. The procedure was sensitive to capturing these temporal patterns, even those with a low data representation or noisy series while synthesizing information for an easy interpretation. Results are discussed in the light of future opportunities to combine this kind of information with other sources of information, aiming at the development of reliable land degradation and desertification assessment and monitoring tools.

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.

Assessment and Spatial Analysis of Sensitivity to Desertification in Wadi El Natrun, Northwestern Egypt using MEDLAUS model

Land degradation is a global environmental issue, given the various negative impact on socio-economic and ecological implications. It leads to reduced production capacity in addition to soil erosion, physical /chemical /biological /economic land deterioration, and long-term loss (or degradation) of vegetation. When a severe deterioration in drought areas called the process of desertification i.e. arid, dry sub-humid and semi-arid areas. Desertification processes reduces the productivity of the soil and as a result effect on food stocks. The main objective of this study is integrating remote sensing data and a geographic information system (GIS) to evaluate the environmental sensitivity for desertification in Wadi El Natrun, Egypt based on the Mediterranean Desertification and Land Use (MEDALUS) approach. The collected soil data; from description of represented soil profiles and analysis of soil samples, in addition to climate, plant cover, and management data were considered for assessing the sensitivity of desertification. The obtained results showed that 10.4 % of Wadi El Natrun area is considered severe sensitivity to desertification as a result of alkalinity and salinity, while the moderately sensitive area occupies approximately 10.93 % of the study area. The low sensitive one exhibits 76.3 %. This area is described by high soil quality because of the study area is one of the new development areas which were not affected by the factors of desertification. It can be concluded that the desert extension of El-Beheira Governorate (i.e. Wadi El Rayan) is one of the areas that possess valuable land resources which should be considered for future land reclamation projects. Similar international studies are recommended to be achieved with the use of multi-criteria GIS modeling (i.e. MEDALUS) which considered all relevant factors in the form of thematic layers for easier implementation and assessments. Present study represents one of the initial attempts to use the MEDALUS model for desertification assessment in the desert extension of El-Beheira Governorate.

DESERTIFICATION ASSESSMENT USING MEDALUS MODEL IN UPPER LAMCHIENGKRAI WATERSHED, THAILAND

Abstract. Desertification is a global environmental problem. It affects harmful on economic, social and environmental that ultimately effects on quality of human life. Thailand is the 174th member of the UNCCD, according to the Thailand report of desertification by LDD (2004). It was found that the area of degraded land or desertification land in Thailand was 33.57 million hectares which were agricultural soil problem. Soil erosion and soil salinity are major problems for agricultural soil in Thailand. Thus, to prevent and fix such problems, assessment and evaluation of soil properties are essential. Lamchiengkrai watershed in Nakhon Ratchasima province presents soil salinity exposure area which is a major problem in the Northeast region of Thailand. This study aims to access a new approach for assessing the extent and the risk of desertification land by MEDALUS model based on geoinformatics technology in upper Lamchiengkrai watershed, Nakhon Ratchasima province. MEDALUS model is the factors of desertification assessment. Four groups of factors were examined, including vegetation (fire risk, erosion protection, and drought resistance), climatic (rainfall and rainfall erosivity), soil (soil texture, electrical conductivity, organic matter, soil depth, drainage, and slope), and human activity factor (land use and soil erosion). The results of the study indicated that 67.25% of the area was classified as high risk, 30.54% was classified as moderate risk and 2.22% was classified as low risk to desertification land. In addition, the factors affected on the high-risk area were climate and vegetation factors. Moderate risk area was influenced by the human activity factor and soil factors.

Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors

Land degradation reflected by vegetation is a commonly used practice to monitor desertification. To retrieve important information for ecosystem management accurate assessment of desertification is necessary. The major factors that drive vegetation dynamics in arid and semi-arid regions are climate and anthropogenic activities. Progression of desertification is expected to exacerbate under future climate change scenarios, through precipitation variability, increased drought frequency and persistence of dry conditions. This study examined spatiotemporal vegetation dynamics in arid regions of Sindh, Pakistan, using annual and growing season Normalized Difference Vegetation Index (NDVI) data from 2000 to 2017, and explored the climatic and anthropogenic effects on vegetation. Results showed an overall upward trend (annual 86.71% and growing season 82.7%) and partial downward trend (annual 13.28% and growing season 17.3%) in the study area. NDVI showed the highest significant increase in cropland region during annual, whereas during growing season the highest significant increase was observed in savannas. Overall high consistency in future vegetation trends in arid regions of Sindh province is observed. Stable and steady development region (annual 48.45% and growing 42.80%) dominates the future vegetation trends. Based on the Hurst exponent and vegetation dynamics of the past, improvement in vegetation cover is predicted for a large area (annual 44.49% and growing 30.77%), and a small area is predicted to have decline in vegetation activity (annual 0.09% and growing 3.04%). Results revealed that vegetation growth in the study area is a combined result of climatic and anthropogenic factors; however, in the future multi-controls are expected to have a slightly larger impact on annual positive development than climate whereas positive development in growing season is more likely to continue in future under the control of climate variability.

Featured Cover

The cover image is based on the Research Article Updating the MEDALUS-ESA Framework for Worldwide Land Degradation and Desertification Assessment by Agostino Ferrara et al., https://doi.org/10.1002/ldr.3559.

Desertification–Scientific Versus Political Realities

Desertification is defined as land degradation occurring in the global drylands. It is one of the global problems targeted under the Sustainable Development Goals (SDG 15). The aim of this article is to review the history of desertification and to evaluate the scientific evidence for desertification spread and severity. First quantitative estimates of the global extent and severity of desertification were dramatic and resulted in the establishment of the UN Convention to Combat Desertification (UNCCD) in 1994. UNCCD’s task is to mitigate the negative impacts of desertification in drylands. Since the late 1990s, science has become increasingly critical towards the role of desertification in sustainable land use and food production. Many of the dramatic global assessments of desertification in the 1970s and 1980s were heavily criticized by scientists working in drylands. The used methodologies and the lack of ground-based evidence gave rise to critical reflections on desertification. Some even called desertification a myth. Later desertification assessments relied on remote sensing imagery and mapped vegetation changes in drylands. No examples of large areas completely degraded were found in the scientific literature. In science, desertification is now perceived as a local feature that certainly exists but is not as devastating as was earlier believed. However, the policy arena continues to stress the severity of the problem. Claims that millions of hectares of once productive land are annually lost due to desertification are regularly made. This highlights the disconnection between science and policy, and there is an urgent need for better dialogue in order to achieve SDG 15.

An assessment and local perception of sand deposits induced desertification in Sokoto State, Nigeria

Sokoto State is one of the states in Nigeria that are prone to desertification. This study attempts to identify and delimit areas affected by desertification in the three northernmost Local Government Areas of Sokoto State, namely: Illela, Gada and Tangaza. Field study was carried out to verify the incident and occurrence of desertification and the menace of sand deposition. A simple random sampling method with questionnaire, combined with Focused Group Discussions and Key Informant Interviews was used to derive the local knowledge about sand transport and deposition, and, its socio-environmental impacts. The Digital Elevation Model of Tangaza, Gada, and Illela Local Government Areas for the year 2008 and 2014 were derived from ASTER images. The result indicated that the Gidan Kaura hill grew by about 30 m within the six-year period. This agreed with an overwhelming belief by 95% of the respondents that the area continues to suffer from sandstorms and sand deposition. This was visibly confirmed by the presence of sand dunes in most of the areas visited in the three local government areas. Normalized Difference Vegetation Index derived from Landsat images of the year 2013 and 2018 gave further insight into the current vegetation conditions. Key words: Northern Nigeria, desertification, sustainability, geospatial analyses, environmental impacts.

Updating the MEDALUS‐ESA Framework for Worldwide Land Degradation and Desertification Assessment

AbstractThe environmentally sensitive area (ESA) methodology (originally proposed in the framework of MEDALUS–Mediterranean Desertification and Land Use—a series of international cooperation research projects funded by the European Union) is used worldwide to identify 'sensitive areas' that are potentially threatened by land degradation and desertification (LDD). The distinctive outcome of this approach is a multidimensional index (the ESA index) composed of partial indicators of climate, soil, vegetation, and management quality that are derived from the elaboration of 15 elementary variables. In this study, we propose (a) a major update of the ESA methodology, as presented in the MEDALUS project, for global LDD assessment, (b) a global map of ESAs to LDD, and (c) a global environmentally critical factors map. The results of the updated ESA framework confirm the efficiency and applicability of the ESA methodology in different worldwide areas, allowing for the harmonization of regional/country level studies and applications, and the more efficient use of global level datasets. In this study, we provide examples for analysis of LDD patterns and processes at a global level, as well as for identification of the main risk factors over time and space. Global‐ESA and global‐environmentally critical factors maps also support regional‐scale knowledge on LDD processes and sustainable land management practices for LDD mitigation. High‐resolution illustrative maps and other information are available on a dedicated website (http://web.unibas.it/global-esa/).

Desertification assessment of the territory of Atyrau region

The article assesses the dynamics of desertification based on changes in the area of moving sands in the territories of the villages Issatay, Zineden, Maykomgen, Miyaly Zhaskairat over the past 17 years based on the processed data of remote sensing satellite images. It should be noted that the research area is located almost on the border of the semi-desert and desert zones, which within Kazakhstan occupy 57.7% of the territory. Ecosystems of these arid territories are very vulnerable to impacts, especially in modern conditions of climate change, reduction of water resources and active anthropogenic development. It should be noted that land degradation has a serious socio-economic impact on the standard of living and health of the population, especially on socially vulnerable sections of the rural population.

Quantitative mapping of desertification risk using the modified MEDALUS model: a case study in the Mazayejan Plain, Southwest Iran

This paper presents the Modified MEDALUS (MMEDALUS) approach, a quantitative assessment of desertification, in the case study area located in the Southern part of Iran. Six main factors of desertification including: soil, climate, plant cover, management, erosion state and ground water situation were considered for the model approach. Then several sub-factors determining the quality of each main factor were quantified according to their quality and weighted on a scale between 1.0 and 2.0. We used a Geographic Information System (GIS) software to analyze and prepare the spatial distribution of the factor layers. Subsequently, the final desertification hazard map was prepared by combining the different MEDALUS factors in Arc GIS 10.3 in order to define the final hazard classes on the basis of hazard scores based on the geometric mean of the main factors. The MEDALUS and MMEDALUS models show the "Desertification Potential" that in turn was validated with the current state of desertification observed in the field. The results show that the applied MMEDALUS approach yield significantly better results than the MEDALUS model in the study area. The results also show that the areas under severe and very severe hazard are the most extensive classes in the desertification map. Thus, we illustrate that most of the study area is sensitive to desertification. However, we highlight that management, climate and water table qualities were the most important indicators affecting the desertification processes, while soil quality seems to play a minor role in our study area.

Assessment of Karst rocky desertification based on MODIS: Exemplified by Guizhou Province

Assessment of Karst rocky desertification based on MODIS: Exemplified by Guizhou Province

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.