Review of Remote Sensing-Based Methods to Assess Soil Salinity

Ben‐Dor, Eyal; Metternicht, Graciela; Goldshleger, Naftaly; Eshel, Mor; Mirlas, Vladimir; Basson, Uri

doi:10.1201/9781420065039.ch3

Cited by 19 publications

(16 citation statements)

References 45 publications

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“…Metternicht and Zinck (2003, 2009) provide an extensive overview of the indicators and kinds of remotely sensed imagery commonly used for mapping soil and terrain salinization, whereas Ben Dor et al (2009) review the use of airborne and satellite‐borne sensors that have been used for mapping salt‐affected areas.…”

Section: Soil Salinizationmentioning

confidence: 99%

“…Remote sensing-based approaches to map and monitor salinized landscapes should take into consideration (i) the discontinuous way in which salts tend to distribute on the landscape, so that appropriate classifi cation schemes can be developed and (ii) the mineralogy of salt types, as this controls the occurrence of spectral absorption features in specifi c regions of the electromagnetic spectrum and infl uences the appearance of salinity indicators (e.g., salt crust types) at the soil surface (Metternicht and Zinck, 2009). Zinck (2003, 2009) provide an extensive overview of the indicators and kinds of remotely sensed imagery commonly used for mapping soil and terrain salinization, whereas Ben Dor et al (2009) review the use of airborne and satellite-borne sensors that have been used for mapping saltaff ected areas.…”

Section: Soil Salinizationmentioning

confidence: 99%

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Remote Sensing of Land Degradation: Experiences from Latin America and the Caribbean

Metternicht

Zinck²,

Blanco

et al. 2010

J of Env Quality

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Land degradation caused by deforestation, overgrazing, and inappropriate irrigation practices affects about 16% of Latin America and the Caribbean (LAC). This paper addresses issues related to the application of remote sensing technologies for the identification and mapping of land degradation features, with special attention to the LAC region. The contribution of remote sensing to mapping land degradation is analyzed from the compilation of a large set of research papers published between the 1980s and 2009, dealing with water and wind erosion, salinization, and changes of vegetation cover. The analysis undertaken found that Landsat series (MSS, TM, ETM+) are the most commonly used data source (49% of the papers report their use), followed by aerial photographs (39%), and microwave sensing (ERS, JERS-1, Radarsat) (27%). About 43% of the works analyzed use multi-scale, multi-sensor, multi-spectral approaches for mapping degraded areas, with a combination of visual interpretation and advanced image processing techniques. The use of more expensive hyperspectral and/or very high spatial resolution sensors like AVIRIS, Hyperion, SPOT-5, and IKONOS tends to be limited to small surface areas. The key issue of indicators that can directly or indirectly help recognize land degradation features in the visible, infrared, and microwave regions of the electromagnetic spectrum are discussed. Factors considered when selecting indicators for establishing land degradation baselines include, among others, the mapping scale, the spectral characteristics of the sensors, and the time of image acquisition. The validation methods used to assess the accuracy of maps produced with satellite data are discussed as well.

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Section: Soil Salinizationmentioning

confidence: 99%

Section: Soil Salinizationmentioning

confidence: 99%

Remote Sensing of Land Degradation: Experiences from Latin America and the Caribbean

Metternicht

Zinck²,

Blanco

et al. 2010

J of Env Quality

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“…The PLSR model is effective in dealing with strong collinearity between independent variables [39], and has been successfully used in soil salinity retrievals from hyperspectral data [35,36,40]. Moreover, new technologies have been developed, for example, the use of sub-surface-to-surface correlation, frequency domain electromagnetic induction (FDEM) and ground penetrating radar (GPR) [41,42]. However, complicated atmospheric correction and high cost may preclude use of the hyperspectral remote sensing for mapping large-scale soil salinity [37,43].…”

mentioning

confidence: 99%

Soil Salinity Retrieval from Advanced Multi-Spectral Sensor with Partial Least Square Regression

Fan

Liu

Tao³

et al. 2015

Remote Sensing

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Improper use of land resources may result in severe soil salinization. Timely monitoring and early warning of soil salinity is in urgent need for sustainable development. This paper addresses the possibility and potential of Advanced Land Imager (ALI) for mapping soil salinity. In situ field spectra and soil salinity data were collected in the Yellow River Delta, China. Statistical analysis demonstrated the importance of ALI blue and near infrared (NIR) bands for soil salinity. A partial least square regression (PLSR) model was established between soil salinity and ALI-convolved field spectra. The model estimated soil salinity with a R 2 (coefficient of determination), RPD (ratio of prediction to deviation), bias, standard deviation (SD) and root mean square error (RMSE) of 0.749, 3.584, 0.036 g·kg . The model was then applied to atmospherically corrected ALI data. Soil salinity was underestimated for moderately (soil salinity within 2-4 g·kg −1) and highly saline (soil salinity >4 g·kg sensing pixels was probably the major source responsible for the underestimation. Our study demonstrates the effectiveness of PLSR model in retrieving soil salinity from new-generation multi-spectral sensors. This is very valuable for achieving worldwide soil salinity mapping with low cost and considerable accuracy.

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“…A detailed review of non-plant approaches to improving P utilization is that by Cordell et al (2011). We propose some strategies: 1) maximizing recycling of P from biosolids back to farmland, 2) minimize P loss from productive farmland in run-off and soil erosion since these losses can be reduced (cf de Kliein et al 2010), 3) maximize recycling of mineral nutrient containing residues from biofuel production back to the land that produced the plant materials used in the process, 4) use of microorganisms to solubilize P and other strategies to release P from rock and P-fixing soils, 5) improve P fertilizer application strategies (cf Malley et al 2007) to rapidly and economically assess soil fertility above ground (cf Ben-Dor et al 2009), in the root zone (cf Christy 2008) and the crop itself (cf Bowman et al 2007), 6) use of P efficient genotypes, 7) research P capture from ocean sediments, and, 8) locate animal industries closer to the sources of their seed/grain feed.…”

Section: Discussionmentioning

confidence: 99%

The critical role of phosphorus in world production of cereal grains and legume seeds

et al. 2011

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The production of food for the nearly 7 billion people on the earth today requires a large input of phosphorus (P), a non-renewable resource. Over the 14 year period 1995-2008, the global production of dry cereal grains plus legume seeds has not increased per capita and the area farmed to obtain these yields has declined steadily. There is great concern about the availability of food, the rising cost of food and the availability of P to maintain crop yields of key food staples. Known P reserves are finite. We report the rates of change in the area of agricultural land, the production of food staples, the use of fertilizer P and the export of elemental P in the major cereal and legume crops on a per capita basis. We seek to draw attention to the urgent need to utilize world P reserves more wisely so as to delay the impact of dwindling amounts of P and increasing costs of P on world food security. We strongly urge agriculturalists to pursue more P-efficient crop genotypes and land management which reduces losses of P from agricultural ecosystems and we support the engineering of P-recycling schemes which convert the current P-loss system nearer to a closed P-cycle system. Unless these avenues are developed in the immediate future there are likely to be severe consequences for food security in the longer term.

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Review of Remote Sensing-Based Methods to Assess Soil Salinity

Cited by 19 publications

References 45 publications

Remote Sensing of Land Degradation: Experiences from Latin America and the Caribbean

Remote Sensing of Land Degradation: Experiences from Latin America and the Caribbean

Soil Salinity Retrieval from Advanced Multi-Spectral Sensor with Partial Least Square Regression

The critical role of phosphorus in world production of cereal grains and legume seeds

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