Vegetation cover change detection and assessment in arid environment using multi-temporal remote sensing images and ecosystem management approach

Aly, Anwar A.; Sallam, Abdelazeem Sh.; Al-Wabel, Mohammad I.; Al-Shayaa, Mohammad Shayaa

doi:10.5194/se-7-713-2016

Cited by 46 publications

(23 citation statements)

References 50 publications

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“…Furthermore, both interpolation methods illustrate that the eastern part of AlKharj contains groundwater of higher quality than western part since its EC around 2 dS m -1 . These finding is in agreement with the finding of Aly et al (2016). This study suggest that using the interpolation methods of geostatistical software (GS?…”

Section: Comparing Interpolation Using Gs1 and Gissupporting

confidence: 83%

Geostatistical methods in evaluating spatial variability of groundwater quality in Al-Kharj Region, Saudi Arabia

et al. 2017

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The analyses of 180 groundwater samples of AlKharj, Saudi Arabia, recorded that most groundwaters are unsuitable for drinking uses due to high salinity; however, they can be used for irrigation with some restriction. The electric conductivity of studied groundwater ranged between 1.05 and 10.15 dS m -1 with an average of 3.0 dS m -1 . Nitrate was also found in high concentration in some groundwater. Piper diagrams revealed that the majority of water samples are magnesium-calcium/sulfate-chloride water type. The Gibbs's diagram revealed that the chemical weathering of rock-forming minerals and evaporation are influencing the groundwater chemistry. A kriging method was used for predicting spatial distribution of salinity (EC dS m -1 ) and NO 3 -(mg L -1 ) in Al-Kharj's groundwater using data of 180 different locations. After normalization of data, variogram was drawn, for selecting suitable model for fitness on experimental variogram, less residual sum of squares value was used. Then cross-validation and root mean square error were used to select the best method for interpolation. The kriging method was found suitable methods for groundwater interpolation and management using either GS? or ArcGIS.

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Section: Comparing Interpolation Using Gs1 and Gissupporting

confidence: 83%

Geostatistical methods in evaluating spatial variability of groundwater quality in Al-Kharj Region, Saudi Arabia

et al. 2017

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“…The data collected include the indicator of the grassland condition, the status of SISGC, and climate and socio-economic factors. In the existing literature, the grassland condition has been indicated by vegetation coverage, height, density, biomass production, and density of perennial vegetation (Gu & Li, 2013;Yu & Farrell, 2013;Aly et al, 2016). These indicators are commonly measured using two methods: direct sampling tests undertaken during small-scale fieldwork and estimation over large areas with remote sensing technology (Gu & Li, 2013).…”

Section: Data Collectionmentioning

confidence: 99%

The Impact of Ecological Construction Programs on Grassland Conservation in Inner Mongolia, China

et al. 2017

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A series of Ecological Construction Programs have been initiated to protect the condition of grasslands in China during recent decades. However, grassland degradation is still severe, and conditions have not been restored as intended. This paper aims to empirically examine the effectiveness of these programs for protecting the grassland condition in the extensive pastoral areas of China. We focus on one major program that has been implemented widely on the grasslands, the Subsidy and Incentive System for Grassland Conservation (SISGC). The normalized difference vegetation index, measured with remote sensing technology, is used to quantify the grassland condition between 2001 and 2014. With data from 54 counties in the pastoral areas of Inner Mongolia, we estimate the impact of SISGC on the grassland condition. A fixed effects model is employed to control for livestock production, climate, time trends, and time‐invariant heterogeneity between counties. The model results provide quantitative evidence that the condition of the grasslands has improved significantly because of SISGC; but that the effectiveness of SISGC was offset to some extent by other socio‐economic and climate factors, such as increased producer prices and high temperature. This may explain why the actual grassland degradation has not been prevented as effectively as was expected. In addition, the impact of SISGC was stronger in counties with worse initial grassland condition. Furthermore, the effects of producer prices and climate changes were also more pronounced in these counties. Copyright © 2017 John Wiley & Sons, Ltd.

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“…Similarly, extensive farming practices were converted into much more intensive systems due to heavy machineries in Southern Italy, accelerating the disturbance of semi-natural landforms and reducing native plant species diversity (Shelef et al, 2015). Moreover, drylands may be subjected to soil and water salinization as in Al-Kharj agro-ecosystem in the centre of Saudi Arabia (Aly et al, 2016), where intensive cultivation systems increased land degradation due to irrigation with poor quality water (e.g. saline water).…”

Section: Discussionmentioning

confidence: 99%

Using Landsat Images and Spectral Mixture Analysis to Assess Drivers of 21‐Year LULC Changes in Sudan

2016

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Landsat images acquired in 1987, 1999 and 2008 were selected to evaluate land use and land cover changes in three different ecological zones in the Republic of the Sudan: savannah (North Kordofan), semi‐desert (River Nile) and desert (Northern State). Maps of soil, vegetation and non‐photosynthetic material were built by spectral mixture analysis using endmembers spectra derived from images. Multitemporal comparison techniques were then applied to vegetation and soil maps to estimate the long‐term land degradation/re‐growth dynamics and to emphasize land cover variation over time and in space. Multitemporal comparisons have shown that site‐specific interactions between natural processes, climate variation and human activity played a pivotal role in land use and land cover change. In savannah, human activities strongly affected degradation phenomena. Expansion of villages triggered a change in land use and mismanagement of the natural resources, mainly caused by deforestation to supply wood for domestic uses. The degradation then promoted sand encroachment and dune migration. On average, 48% of the total area was subjected to medium (25–50%) and high (50–75%) land degradation. Differently, climatic constraints drove increasing degradation processes in semi‐desert and desert zones. The phenomenon was particularly severe in the desert zone. In each site, an inversion of the general trend was due to a land use change where forestry or agricultural projects were established, partly sustained in savannah by the positive rainfall trend of the last two decades. Site‐specific strategies that take into account the interactions of the driving factors at local scale are thus necessary to combat land degradation. Copyright © 2016 John Wiley & Sons, Ltd.

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Vegetation cover change detection and assessment in arid environment using multi-temporal remote sensing images and ecosystem management approach

Cited by 46 publications

References 50 publications

Geostatistical methods in evaluating spatial variability of groundwater quality in Al-Kharj Region, Saudi Arabia

Geostatistical methods in evaluating spatial variability of groundwater quality in Al-Kharj Region, Saudi Arabia

The Impact of Ecological Construction Programs on Grassland Conservation in Inner Mongolia, China

Using Landsat Images and Spectral Mixture Analysis to Assess Drivers of 21‐Year LULC Changes in Sudan

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