A new approach for land degradation and desertification assessment using geospatial techniques

Masoudi, Masoud; Jokar, Parviz; Pradhan, Biswajeet

doi:10.5194/nhess-18-1133-2018

Cited by 46 publications

(23 citation statements)

References 21 publications

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“…Recent studies have also shown that with the help of the integrated use of GIS and RS analyses of both temporal and spatial dynamics of land-cover changes caused by drying surface water bodies become possible, [46] analyzing potential changes occurring among land cover features and develop the baseline maps of desertification or land-cover [6,16,44]. Concerning these studies, RS implies either satellite images or aerial photography to perform a trend analysis for future scenarios and create trend maps showing the possible changes in land cover condition over a certain period [27].…”

Section: Methodsmentioning

confidence: 99%

Land cover-adjusted index for the former Aral Sea using Landsat images

et al. 2021

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The Aral Sea was the fourth largest inland lake on the globe until 1960, with a surface area of about 68,000 km2. Mainly, the huge irrigation projects in many parts of its transboundary catchment were responsible for the catastrophic desiccation and ecological crises of the Aral Sea after second part of 20th century. Ecological crisis surrounding the Aral Sea (lake) regions is one of the critical environmental problems of Central Asia. As a result, monitoring of desertification processes and determining the aerosol concentration in the atmosphere are highly relevant for any attempts to mitigate environmental changes in the Aral Sea basin. Remote sensing is the most appropriate method for studying desertification and dust storms as it easily covers large areas with a high spatial and temporal resolution. Satellite images provide detailed multispectral information about the earth’s surface features, which proves invaluable for the characterization of vegetation, soil, water, and landforms at different scales. Vegetation cover, biomass, and soil properties were analyzed with remote sensing methods (NDVI, SDVI). It is emphasized that vegetation indices have little sensitivity at low leaf area which is common to all desert ecosystems.

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Section: Methodsmentioning

confidence: 99%

Land cover-adjusted index for the former Aral Sea using Landsat images

et al. 2021

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“…LD has been defined as … any decrease in the land potential through one or combination of several processes, including water erosion, wind, and vegetation degradation, which are affected by potential human and natural factors (Prăvălie, Savulescu, Patrich, Dumitrascu, & Bandoc, 2017; UNEP, 1994). LD not only has more prevalence in arid and semiarid areas (Masoudi, Jokar, & Pradhan, 2018) but also has many undesirable effects on healthy adjacent areas, especially in the developing countries (Hazbavi, Kalehhouei, & Khalili Moghadam, 2020; Hazbavi, Sadeghi, Gholamalifard, & Davudirad, 2020).…”

Section: Introductionmentioning

confidence: 99%

Land degradation assessment in the dust hotspot of Southeastern Ahvaz, Iran

Poornazari¹,

Khalilimoghadam²,

Hazbavi

et al. 2020

Land Degrad Dev

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The present study was conducted to assess the land degradation (LD) in the largest source area for dust storms in Southeastern Ahvaz (SEA) using a Modified Mediterranean Desertification and Land‐use (MMEDALUS) method (a modification of the MEDALUS method). The LD of the dust hotspot of SEA was evaluated using the soil quality index (SQI), climate quality index (CQI), vegetation quality index (VQI), and management quality index (MQI). The study indicators and final land degradation index (LDI) index were classified into four groups of low (100–120), moderate (121–135), severe (136–153), and very severe (more than 153). The results showed that the SQI, CQI, VQI, and land management quality index (MQI), respectively were 151 ± 6, 167 ± 5, 175 ± 12, and 168 ± 18 for the whole dust hotspot of SEA. The results revealed that the SQI and VQI had the minimum and maximum effect on LD assessment, respectively. The integration of study indices and indicators and their effectiveness for LD assessment showed that the study dust hotspot was rated at a mean of 165 ± 7 in the very severe degraded class based on our MMEDALUS assessment. Whereas, only about 18% of the study area scored in the severe class, and other parts are classified in the very severe class. Based on the field surveys of the dust hotspot and the results of the MMEDALUS method, suitable strategies for revitalizing the dust hotspot of SEA, were proposed using homogeneous land‐components such as the construction of windbreaks using indigenous species of the area, forestry, planting, water spreading, wetting, protection, and grazing management.

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“…In the world about 6 million ha of agriculture land becomes unproductive due to soil degradation processes (Asio et al, 2009). Land degradation decreases land capability and causes deterioration in soil productivity (FAO/UNEP, 1978;Berry, 2003;Bai et al, 2008;Pierre, 2010;El Baroudy, 2011;Gessesew, 2017 andMasoudi et al, 2018). Eswaran et al (2001) stated that about 1360 million ha of land on the worldwide are moderately to severely degrade.…”

Section: Introductionmentioning

confidence: 99%

“…Impacts of soil degradation on ecological function ultimately affect on quality of life (El Baroudy, 2011;Masoudi, 2014;Vu et al, 2014;El-Baroudy, 2015;Masoudi and Amiri, 2015;Rashed, 2016 andSadeghi et al 2017). Land degradation assessment is difficult because it includes several complex processes (Safriel, 2007;Bai etal., 2008;Jankava et al, 2017 andMasoudi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Land Degradation Risk in El-minufiya Governorate, Egypt

Rashed

2019

Journal of Soil Sciences and Agricultural Engineering

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El-Minufiya Governorate represents the traditional agriculture in the Nile Delta of Egypt and includes old cultivated and newly reclaimed soils; it represents an area of 217160 ha. GIS and remote sensing are integrated to determine the risk of soil degradation in the studied area. Fifteen soil profiles have been described and collected samples. There were two landscapes: flood plain and aeolian plain. The main landforms are levees (L), overflow mantles (O), overflow basins (B1), decantation basins (B2), recent river terraces (R1 high, R2 moderate and R3 low), turtle backs (T) and sand sheets (S). Compaction (C), water logging (W), Salinization (S) and alkalinization (A), are the main degradation hazards in the studied area and the rate of hazards was low to very high. Soils affected by very high hazard of salinity represented 16.70%, of the total area. The very high hazard of compaction was present in 35.15% of the total area as a result of human activities, inadequate soil management, and using heavy machinery. Soils affected by a high hazard of salinity, compaction and water logging represented 14.66%, 3.60% and 20.50% of the total area, respectively. Moderate hazard of salinity, sodicity, compaction and water logging represented 36.50%, 33.70%, 34.00% and 79.50% of the total area, respectively. A simple model was used to estimate land degradation risk, based on an equation by FAO/UNEP model. A portion of 39.60% of area has a very high chemical degradation and low physical degradation risk in L, B2, R1 and R2 mapping units. The area of low chemical degradation and moderate physical degradation class is 17.00% of study area in T and S mapping units. The area of low physical and chemical degradation is 32.80% of study area in O, B1 and R3. Changes of land use/land cover classes during 1987 to 2018 indicate urban sprawl. Most of soils in the study area showed several categories of land use/land cover change due to agriculture activities and urban growth.

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A new approach for land degradation and desertification assessment using geospatial techniques

Cited by 46 publications

References 21 publications

Land cover-adjusted index for the former Aral Sea using Landsat images

Land cover-adjusted index for the former Aral Sea using Landsat images

Land degradation assessment in the dust hotspot of Southeastern Ahvaz, Iran

Assessment of Land Degradation Risk in El-minufiya Governorate, Egypt

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