Assessing NDVI Spatial Pattern as Related to Irrigation and Soil Salinity Management in Al-Hassa Oasis, Saudi Arabia

Aldakheel, Yousef

doi:10.1007/s12524-010-0057-z

Cited by 69 publications

(32 citation statements)

References 17 publications

(18 reference statements)

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“…Different salinity indices were developed to detect and map soil salinity such as Normalized Difference Salinity Index (NDSI) and Salinity Index (SI). Soil salinity can be detected directly from remotely sensed data through salt features that are visible on soil surface, such as bare soil with white salt crusts on the surface (Matinfar, 2013) or indirectly from indicators such as the presence of halophytic plant, the performance level of salt-tolerant crops (Alhammadi and Glenn, 2008;Iqbal, 2011;Aldakheel, 2011).…”

Section: Introductionmentioning

confidence: 99%

Change Detection of Land Cover and Salt Affected Soils at Siwa Oasis, Egypt

2017

Alexandria Science Exchange Journal: An International Quarterly

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Constant and accurate change detection of land cover/land use features is highly significant to interpret the correlation between human activities and natural phenomena in order to make better decisions and for investigating the processes and patterns of landscape changes over time and the impact of these changes on sustainable development. Soil salinization is a major problem affecting productivity of irrigated lands. Managing salinity to minimize environmental impact is a prerequisite for sustainable irrigated agriculture. The current study aims at detecting, classifying and mapping the current status for land cover types, salt affected soils and their changes in quantity that have taken place in Siwa Oasis during the period from 1987 to 2017, based on satellite imagery data, GIS facilities, statistical analysis, ground truth and laboratory analysis.An approach of multi-temporal mid resolution satellite images of TM 1987, and OLI 8 2017 combined with visual interpretation, supervised classification and new remote sensing indices namely NDVI to enhance accuracy of land cover classification was used. The study employed normal image classification, and developing model from ECe vs NDSI to produce maps for salt affected soils during the period under study.Results showed that the study area has different land cover / land use units; i.e. Salt marches, Sabkha, Cropland, Grassland, Bare Land, Urban, Lakes, Sand dunes, and Hills. During the study period, a very severe land cover change has taken place as a result of mismanagement of land resources. Change detection at the study area explains the rapid increase of saline lakes and salt marshes, and the consequent hazards to the cultivated lands, roads and archeological sites and urban areas over the last three decades. These changes in land cover led to land degradation and water logging in many parts of the study area. In 1987, very slightly saline soil area was the largest in extent 34.1% of the total area whereas strongly saline, slightly saline and moderately saline soils covered 27.0%, 17.4% and 17.1%, respectively, of the total area. In 2017, strongly saline area increased as compared to 1987 and contributed for 39.1% of the total area, while very slightly, slightly saline and, moderately saline areas represented 18.9% and 13.2% and 14.9% respectively of the total area. Most of the salt affected areas were on shallow water table.The results indicate that long-term irrigation activities would affect agricultural potentiality of the area in the future. RS, GIS, NDVI and NDSI tools are efficient and feasible for detecting land cover/land use and salt affected areas from satellite images.

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Section: Introductionmentioning

confidence: 99%

Change Detection of Land Cover and Salt Affected Soils at Siwa Oasis, Egypt

2017

Alexandria Science Exchange Journal: An International Quarterly

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“…Concern for human health has limited its use in commercial food production but in regions experiencing significant water stress, wastewater can contribute approximately 20% of the total irrigation water used [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

“…The relative humidity of the air is generally high for arid systems, often reaching 90% in summer [6,26]. The average daily soil temperature in the AlHassa eastern oasis typically ranges from 16.4 to 37.9 °C at 20 cm depth and 17.1 to 37.6 °C at 30 cm with an average of 30 °C (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Substrate Influences Temperature Sensitivity of Dissolved Organic Carbon (DOC) and Nitrogen (DON) Mineralization in Arid Agricultural Soils

2018

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Abstract:The bioavailability of nitrogen (N) in soil relies on the progressive breakdown of necromass protein to peptide and amino acid components and conversion to inorganic N forms. We understand the fluxes and pathways of the N cycle downstream from amino acids, but our understanding of the factors controlling peptide and amino acid mineralization, particularly in arid soils, is lacking. We investigated the influence of temperature on the rate of dissolved organic carbon (DOC) and nitrogen (DON) cycling in three agricultural soils from Saudi Arabia. Although the physical and chemical properties of the soils differed markedly, phospholipid fatty acid (PLFA) analysis revealed they had similar topsoil and subsoil microbial communities. Soils behaved similarly in terms of the rate of substrate use, microbial C-use efficiency, and response to temperature. Substrate mineralization rate increased with temperature with more C being allocated to microbial catabolic rather than anabolic processes. Our results show that climate change is likely to lead to changes in soil organic matter turnover and shift C allocation patterns within the soil microbial community. This is expected to reduce soil quality and exacerbate nutrient losses. Management strategies are required to promote the retention of organic matter in these soils.

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“…irrigation scheduling (e.g. Hunsaker et al 2007, Aldakheel 2011, soil salinity management (e.g. Li et al 2014), yield prediction (e.g.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Soil Moisture on the Reflectance Spectra Correlations in Beech and Sessile Oak Foliage/ Talajnedvesség hatása bükk és kocsánytalan tölgy lombozat reflexiós spektrumainak korrelációira.

Eredics¹,

Németh²,

Rákosa³

et al. 2015

Acta Silvatica Et Lignaria Hungarica

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-Reflectance intensities of foliage are mostly due to biomaterials synthesised by plants. Adaptation to the continuously changing environment requires the regulated alteration of metabolic processes, which also influences the UV-VIS (Ultraviolet-Visible) and IR (Infra Red) spectra of leaves. For the calculation of various Vegetation Indices (VIs), e.g. NDVI (Normalized Difference Vegetation Index), the common practice is to use the reflectance spectrum of the whole foliage and when individual leaves of the same plant are sampled, an average VI is derived. On the contrary, our method exploits the small differences between individual leaves of the same plant, making use of the similar distributions of measured reflectance values. Using particular wavelength pairs, linear regressions of reflectance intensities have been investigated. The parameters of these regressions (slope and intercept) have been compared to the temporal variations of the environmental factors, such as temperature, vapour pressure deficit and soil moisture. By assessing the sensitivity of the regression coefficient (slope) to the changing environment, wavelength pairs can be selected whose sensitivity change reflects the effect of soil moisture deficit on the plant. Based on the state-dependent correlations of the reflectance spectra of plant foliage, a new concept is presented that is capable of indicating the level of environmental stress, e.g. drought stress. drought stress / state-dependent correlation / UV-VIS and IR spectrometryKivonat -Talajnedvesség hatása bükk és kocsánytalan tölgy lombozat reflexiós spektrumainak korrelációira. A lombozat reflexiós intenzitásainak változását elsősorban a növény által előállított anyagok okozzák. A folyamatosan változó környezethez való alkalmazkodás megköveteli az anyagcsere-folyamatok szabályozott megváltoztatását, ami befolyásolja a levelek reflexiós spektrumát is az UV, látható és közeli infravörös tartományban. Különböző Vegetációs Indexek (VI) számításánál, mint pl. NDVI (Normalized Difference Vegetation Index), az általános gyakorlat szerint a teljes lombozat reflexiós spektrumát használják, vagy ha ugyanazon növény különböző leveleit mintázták, akkor egy átlagos VI-t származtatnak. Ezzel szemben módszerünk éppen a növény egyes levelei közötti kis különbségeket hasznosítja, kihasználva a mért reflexiós értékek hasonló eloszlását. Bizonyos hullámhosszpárokat kiválasztva, a mért reflexiós intenzitások lineáris regresszióit vizsgáltuk. A regressziós paramétereket (meredekség és tengelymetszet) összehasonlítottuk a környezeti hatások időbeli változásával, mint pl. hőmérséklet, légköri telítési hiány és talajnedvesség. A regressziós paraméter (meredekség) érzékenységének vizsgálatával olyan hullámhosszpárokat lehet *

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Assessing NDVI Spatial Pattern as Related to Irrigation and Soil Salinity Management in Al-Hassa Oasis, Saudi Arabia

Cited by 69 publications

References 17 publications

Change Detection of Land Cover and Salt Affected Soils at Siwa Oasis, Egypt

Change Detection of Land Cover and Salt Affected Soils at Siwa Oasis, Egypt

Substrate Influences Temperature Sensitivity of Dissolved Organic Carbon (DOC) and Nitrogen (DON) Mineralization in Arid Agricultural Soils

The Effect of Soil Moisture on the Reflectance Spectra Correlations in Beech and Sessile Oak Foliage/ Talajnedvesség hatása bükk és kocsánytalan tölgy lombozat reflexiós spektrumainak korrelációira.

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