Model-Based Integrated Methods for Quantitative Estimation of Soil Salinity from Hyperspectral Remote Sensing Data: A Case Study of Selected South African Soils

Mashimbye, Zama Eric; Cho, Moses Azong; Nell, J. P.; Clercq, Willem de; Niekerk, Adriaan van; Turner, David P.

doi:10.1016/s1002-0160(12)60049-6

Cited by 90 publications

(60 citation statements)

References 31 publications

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“…For soil salinity, the SWIR bands (i.e., Bands 9, 8 and 7) and NIR (i.e., Band 3) had the highest contribution to estimating soil salinity (Figure 4a). These results were consistent with the results of many studies on spectral wavebands and their relationships with soil salinity [26,74,86]. For instance, Farifteh et al [26] reported that the best performing bands for different scales (field, image and experimental) were found in the NIR and SWIR regions of the spectrum.…”

Section: Evaluation Of Aster Datasupporting

confidence: 88%

“…They defined the wavelength at 2257 nm of the raw spectrum as the most effective band for estimating the soil EC for dry soils using a linear predictive model. The reflectance spectra within the NIR and SWIR regions were viewed as the best spectral region for evaluating the EC [26,52,86]. The results of the present study suggest that ASTER data could be sufficiently sensitive to model and map soil salinity in arid and semi-arid environments.…”

Section: Evaluation Of Aster Datamentioning

confidence: 75%

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Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

2015

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Modeling and mapping of soil properties has been identified as key for effective land degradation management and mitigation. The ability to model and map soil properties at sufficient accuracy for a large agriculture area is demonstrated using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Soil samples were collected in the El-Tina Plain, Sinai, Egypt, concurrently with the acquisition of ASTER imagery, and measured for soil electrical conductivity (ECe), clay content and soil organic matter (OM). An ASTER image covering the study area was preprocessed, and two predictive models, multivariate adaptive regression splines (MARS) and the partial least squares regression (PLSR), were constructed based on the ASTER spectra. For all three soil properties, the results of MARS models were better than those of the respective PLSR models, with cross-validation estimated R

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Section: Evaluation Of Aster Datasupporting

confidence: 88%

Section: Evaluation Of Aster Datamentioning

confidence: 75%

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

2015

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“…As mentioned above, the results obtained in this study have significant implications for spatially and temporally continuous management and monitoring of soil C using leaf and canopy spectral features over large spatial domains (e.g., Luo et al 2008, Ben-Dor et al 2009, and Mashimbye et al 2012. These results emphasize the need to integrate vegetation cover in future soil fertility parameter estimations, because vegetation importance in soil erosion, land degradation, and climate change mitigation studies is well documented (Le Roux and Sumner 2013).…”

Section: Implications Of These Results For Terrestrial Systemssupporting

confidence: 57%

Soil carbon estimation from <i>eucalyptus grandis</i> using canopy spectra

Mzinyane¹,

Aardt²,

Gebreslasie³

2015

SA J of Geomatics

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“…Van Zijl and Le Roux 57 also used an expert knowledge approach to create a hydrological soil map in the Kruger National Park. Both Stalz 58 and Mashimbye et al 59 mapped saltaffected soils using remote sensing. Van Zijl 60 developed a digital soil mapping protocol for large areas (1000 -50 000 ha) with no soils data.…”

Section: Resultsmentioning

confidence: 99%

Spatial soil information in South Africa: Situational analysis, limitations and challenges

et al. 2015

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Soil information is vital for a range of purposes; however, soils vary greatly over short distances, making accurate soil data difficult to obtain. Soil surveys were first carried out in the 1920s, and the first national soil map was produced in 1940. Several regional studies were done in the 1960s, with the national Land Type Survey completed in 2002. Subsequently, the transfer of soil data to digital format has allowed a wide range of interpretations, but many data are still not freely available as they are held by a number of different bodies. The need for soil data is rapidly expanding to a range of fields, including health, food security, hydrological modelling and climate change. Fortunately, advances have been made in fields such as digital soil mapping, which enables the soil surveyors to address the need. The South African Soil Science fraternity will have to adapt to the changing environment in order to comply with the growing demands for data. At a recent Soil Information Workshop, soil scientists from government, academia and industry met to concentrate efforts in meeting the current and future soil data needs. The priorities identified included: interdisciplinary collaboration; expansion of the current national soil database with advanced data acquisition, manipulation, interpretation and countrywide dissemination facilities; and policy and human capital development in newly emerging soil science and environmental fields. It is hoped that soil information can play a critical role in the establishment of a national Natural Agricultural Information System.

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Model-Based Integrated Methods for Quantitative Estimation of Soil Salinity from Hyperspectral Remote Sensing Data: A Case Study of Selected South African Soils

Cited by 90 publications

References 31 publications

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

Soil carbon estimation from <i>eucalyptus grandis</i> using canopy spectra

Spatial soil information in South Africa: Situational analysis, limitations and challenges

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