Using Remote Sensing Techniques for Appraisal of Irrigated Soil Salinity

被引:0
|
作者
Abbas, A. [1 ]
Khan, S. [1 ]
机构
[1] CSIRO Land & Water, Wagga Wagga, NSW 2678, Australia
关键词
Irrigation; remote sending; soil salinity; spatial analysis; waterlogging;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Waterlogging and salinization are the twin evils of the irrigated agriculture in arid and semi-arid areas, which reduce the productivity of agricultural lands adversely. Managing salinity so as to minimize its environmental impact is a prerequisite for the long-term sustainability of irrigated agriculture. It necessitates establishing fast monitoring systems that facilitate taking actions. Remote sensing appears to offer several advantages over the conventional ground methods used to map and monitor soil salinity. This paper describes an integrated approach to assess soil salinity using remotely sensed data. This encompasses spatial analysis of ground truth and satellite data. The study area is located in the District of Faisalabad in Pakistan. The ground truth data of soil salinity from selected sampling points is tied to the corresponding pixels from the satellite image bands. Remotely sensed data based salinity indices (band combinations) and principal components using principal component analysis (PCA) are developed to find out the occurrence pattern of the salinization. Out of the six salinity indices developed, the following proved to be the most promising when compared with ground truth data. Salinity Index = (B-2 x B-3)/B-1 Where; B-1, B-2 and B-3 are bands of the satellite, IRS-1B LISS-II, in spectral range of band 1 (0.45-0.52 mu m), band 2 (0.52-0.59 mu m) and band 3 (0.62-0.68 mu m) respectively. Regression methods were applied to find the best correlation between salinity data and corresponding pixels on the satellite images. The resulting images were categorized into three distinct classes of saline soils; slightly saline, moderately saline and strongly saline. Using supervised maximum likelihood classification, the images were classified with an overall accuracy of more than 90%. Based on the classified results, saline soils covered 8.7%, 14.2% and 6.6% of the image area in 1991, 1994 and 1997 respectively. The relationship between salt affected soils, waterlogged soils and groundwater quality revealed that 60 to 70% of the salt-affected soils occurred in the zone of shallow water table within 200 cm from ground surface, which is indicative of waterlogged situation. The groundwater in the saline areas is also of hazardous quality, which restricts plant growth except high salt-tolerant crops. [GRAPHICS] Figure A shows the probability density of salt-affected soils with intensity ranging from zero to unity. "Zero" indicated normal soils and above zero to unity represented intensity of salt-affected soils. Using satellite data, the principal component analysis (PCA) and the salinity indices are found to be promising techniques for assessment of saline soils. In the scenario of water scarcity (restricted irrigation supplies in supply channels) due to persistent drought, the reuse of poor quality ground water for irrigation and the failure of tile drainage system in the area are likely to disturb the water ecosystem resulting in increased risks of further environmental land degradation.
引用
收藏
页码:2632 / 2638
页数:7
相关论文
共 50 条
  • [1] Characterizing soil salinity in irrigated agriculture using a remote sensing approach
    Abbas, Akhtar
    Khan, Shahbaz
    Hussain, Nisar
    Hanjra, Munir A.
    Akbar, Saud
    PHYSICS AND CHEMISTRY OF THE EARTH, 2013, 55-57 : 43 - 52
  • [2] Calculation of land subsidence and changes in soil moisture and salinity using remote sensing techniques
    Mohammad Roohi
    Mehdi Faeli
    Maryam Irani
    Ehsan Shamsaei
    Environmental Earth Sciences, 2021, 80
  • [3] Calculation of land subsidence and changes in soil moisture and salinity using remote sensing techniques
    Roohi, Mohammad
    Faeli, Mehdi
    Irani, Maryam
    Shamsaei, Ehsan
    ENVIRONMENTAL EARTH SCIENCES, 2021, 80 (12)
  • [4] Soil salinity mapping using remote sensing and GIS
    Gad, Mahmoud Mohamed El-Sayed
    Mohamed, Mostafa H.A.
    Mohamed, Mervat Refaat
    Geomatica, 2022, 75 (04) : 295 - 309
  • [5] Soil salinity assessment of a natural pasture using remote sensing techniques in central Anatolia, Turkey
    Kilic, Orhan Mete
    Budak, Mesut
    Gunal, Elif
    Acir, Nurullah
    Halbac-Cotoara-Zamfir, Rares
    Alfarraj, Saleh
    Ansari, Mohammad Javed
    PLOS ONE, 2022, 17 (04):
  • [6] Evaluation of Different Soil Salinity Indices Using Remote Sensing Techniques in Siwa Oasis, Egypt
    Salem, Omnia H.
    Jia, Zhonghua
    AGRONOMY-BASEL, 2024, 14 (04):
  • [7] Soil Salinity Sampling Strategy Using Spatial Modeling Techniques, Remote Sensing, and Field Data
    Eldeiry, Ahmed A.
    Garcia, Luis A.
    Reich, Robin M.
    JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING, 2008, 134 (06) : 768 - 777
  • [8] Identification of irrigated olive growing farms using remote sensing techniques
    Kefi M.
    Pham T.D.
    Kashiwagi K.
    Yoshino K.
    Euro-Mediterranean Journal for Environmental Integration, 2016, 1 (1)
  • [9] Inversion of Soil Salinity in the Irrigated Region along the Southern Bank of the Yellow River Using UAV Multispectral Remote Sensing
    Wang, Yuxuan
    Qu, Zhongyi
    Yang, Wei
    Chen, Xi
    Qiao, Tian
    AGRONOMY-BASEL, 2024, 14 (03):
  • [10] Evaluation of Different Soil Salinity Mapping Using Remote Sensing Techniques in Arid Ecosystems, Saudi Arabia
    Elhag, Mohamed
    JOURNAL OF SENSORS, 2016, 2016