Croplands are decreasing due to the expansion of urban areas into rural communities and to some extent due to sand accumulations. Increases in population numbers, new development, in addition to the accumulation of sa...Croplands are decreasing due to the expansion of urban areas into rural communities and to some extent due to sand accumulations. Increases in population numbers, new development, in addition to the accumulation of sand and soil salinity are the major driving force leading to abandonment and shrinking of cropland. The aim of this study was to investigate and assess to what extent agricultural lands are affected by urban development in the Al Hassa oasis, Eastern region in Saudi Arabia by employing Landsat time series data of years 1988, 2000 and 2017 as the main source of information. A set of ground truth, control points (GCPs) was also used besides population census data. Unsupervised classifications approach, Normalized Difference Vegetation Index (NDVI) and change detection methods were used here. Urban area during 2000-2017 exhibits much higher increase compared to 1988-2000, while the arable lands declined to −3.4% in 1988-2000 and increased to 22% during 2000-2017. The data analysis results provided new accurate numerical information supported by a graphical representation in regard to the decrease and increase in urban and agricultural lands. Therefore the findings of this study should be considered by decision maker for improving and development the agriculture activities in rural and urban communities.展开更多
With poor irrigation water quality,cultivation difficulties are certainly expected to rise.This will cause a severe reduction in crops yield unless a strong strategy is followed to control and sustain high yielding ca...With poor irrigation water quality,cultivation difficulties are certainly expected to rise.This will cause a severe reduction in crops yield unless a strong strategy is followed to control and sustain high yielding capacity under particular circumstances.Water salinity presented in the form of water electrical conductivity(EC),has been presented in this study as one of the parameters that significantly participated in decreasing the quality of irrigation water in Al-Hassa oasis at Kingdom of Saudi Arabia.The sharing factors in quantifying water EC and its distribution spacewise has been examined by applying the frequency ratio(FR)technique(spatial autocorrelation)between salinity status and water measured elements,specifically,chlorine(Cl^(-)),sodium(Na^(+)),calcium(Ca^(2+)),potassium(K^(+))and magnesium(Mg^(2+)).A threshold salinity value of(EC≥2.0 dS/m)was identified as a break-line for classifying the well-water sources that non-valid for irrigating vegetables grown in the area.A statistical correlation among the examined parameters and EC was conducted using the statistical package for social sciences(SPSS),and compared to the applied FR technique.A dosage of Cl^(-) in irrigation water was observed to be the most significant candidate that raised EC,proved by an R^(2) of 63%.However,the FR technique has shown the validity in analyzing the spatial distribution of water measured variables;in addition to nominating the variable that had the higher association portion,which was assessed to be Na^(+),followed by Cl^(-) with prediction rates of 4.22 and 3.22,respectively.展开更多
文摘Croplands are decreasing due to the expansion of urban areas into rural communities and to some extent due to sand accumulations. Increases in population numbers, new development, in addition to the accumulation of sand and soil salinity are the major driving force leading to abandonment and shrinking of cropland. The aim of this study was to investigate and assess to what extent agricultural lands are affected by urban development in the Al Hassa oasis, Eastern region in Saudi Arabia by employing Landsat time series data of years 1988, 2000 and 2017 as the main source of information. A set of ground truth, control points (GCPs) was also used besides population census data. Unsupervised classifications approach, Normalized Difference Vegetation Index (NDVI) and change detection methods were used here. Urban area during 2000-2017 exhibits much higher increase compared to 1988-2000, while the arable lands declined to −3.4% in 1988-2000 and increased to 22% during 2000-2017. The data analysis results provided new accurate numerical information supported by a graphical representation in regard to the decrease and increase in urban and agricultural lands. Therefore the findings of this study should be considered by decision maker for improving and development the agriculture activities in rural and urban communities.
基金This research was financially supported by the Deanship of Scientific Research at King Faisal University under Nasher Track(Grant No.186240).
文摘With poor irrigation water quality,cultivation difficulties are certainly expected to rise.This will cause a severe reduction in crops yield unless a strong strategy is followed to control and sustain high yielding capacity under particular circumstances.Water salinity presented in the form of water electrical conductivity(EC),has been presented in this study as one of the parameters that significantly participated in decreasing the quality of irrigation water in Al-Hassa oasis at Kingdom of Saudi Arabia.The sharing factors in quantifying water EC and its distribution spacewise has been examined by applying the frequency ratio(FR)technique(spatial autocorrelation)between salinity status and water measured elements,specifically,chlorine(Cl^(-)),sodium(Na^(+)),calcium(Ca^(2+)),potassium(K^(+))and magnesium(Mg^(2+)).A threshold salinity value of(EC≥2.0 dS/m)was identified as a break-line for classifying the well-water sources that non-valid for irrigating vegetables grown in the area.A statistical correlation among the examined parameters and EC was conducted using the statistical package for social sciences(SPSS),and compared to the applied FR technique.A dosage of Cl^(-) in irrigation water was observed to be the most significant candidate that raised EC,proved by an R^(2) of 63%.However,the FR technique has shown the validity in analyzing the spatial distribution of water measured variables;in addition to nominating the variable that had the higher association portion,which was assessed to be Na^(+),followed by Cl^(-) with prediction rates of 4.22 and 3.22,respectively.
