A spectral soil quality index (SSQI) for characterizing soil function in areas of changed land use

Paz‐Kagan, Tarin; Shachak, Moshe; Zaady, Eli; Karnieli, Arnon

doi:10.1016/j.geoderma.2014.04.003

Cited by 86 publications

(49 citation statements)

References 76 publications

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“…The sensitivity bands that were identified by the VIP for the different soil properties and SQI values are presented in Table 7. These bands are in agreement with those that were previously found in other studies [14,31,70]. Figures 6 and 7 shows scatterplots of correlations between soil spectroscopy and laboratory-measured soil values, for the Migda site and Schä fertal site, respectively.…”

Section: Soil Properties and Soil Qualitysupporting

confidence: 90%

“…Spectroscopy is a reliable tool for assessing soil properties; however, it is site-specific and related to the soil function and structure. Previous studies have shown the ability of spectroscopy to predict several soil properties, such as texture, SOM, AWC, NH4, NO3, EC, and pH, with different prediction levels [15,25,31,66]. These differences are probably associated with the energy of the absorbance and reflectance of molecular bonds in the NIR region due to the combination of C-H, N-H, C-O, C-N and O-H groups (chromophores) [77][78][79], minerals, water, and nutrients.…”

Section: Predictability Of Indicators and Indicesmentioning

confidence: 99%

“…They found that laboratory analyses for several physical, biological, and chemical soil properties could be replaced with a spectral analysis for SQ scores. The use of reflectance spectroscopy for the multidimensional assessment of the impact of land-use change on SQ for three land uses (afforestation, traditional grazing, and agro-pastoral) was presented by Paz-Kagan et al [31]. Their study evaluated the spectral predictability of 14 SQ indicators along with an integrated spectral soil quality index (SSQI).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mapping the Spectral Soil Quality Index (SSQI) Using Airborne Imaging Spectroscopy

et al. 2015

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Soil quality (SQ) assessment has numerous applications for managing sustainable soil function. Airborne imaging spectroscopy (IS) is an advanced tool for studying natural and artificial materials, in general, and soil properties, in particular. The primary goal of this research was to prove and demonstrate the ability of IS to evaluate soil properties and quality across anthropogenically induced land-use changes. This aim was fulfilled by developing and implementing a spectral soil quality index (SSQI) using IS obtained by a laboratory and field spectrometer (point scale) as well as by airborne hyperspectral imaging (local scale), in two experimental sites located in Israel and Germany. In this regard, 13 soil physical, biological, and chemical properties and their derived soil quality index (SQI) were measured. Several mathematical/statistical procedures, consisting of a series of operations, including a principal component analysis OPEN ACCESSRemote Sens. 2015, 7 15749(PCA), a partial least squares-regression (PLS-R), and a partial least squares-discriminate analysis (PLS-DA), were used. Correlations between the laboratory spectral values and the calculated SQI coefficient of determination (R 2 ) and ratio of performance to deviation (RPD) were R 2 = 0.84; RPD = 2.43 and R 2 = 0.78; RPD = 2.10 in the Israeli and the German study sites, respectively. The PLS-DA model that was used to develop the SSQI showed high classification accuracy in both sites (from laboratory, field, and imaging spectroscopy). The correlations between the SSQI and the SQI were R 2 = 0.71 and R 2 = 0.7, in the Israeli and the German study sites, respectively. It is concluded that soil quality can be effectively monitored using the spectral-spatial information provided by the IS technology. IS-based classification of soils can provide the basis for a spatially explicit and quantitative approach for monitoring SQ and function at a local scale.

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Section: Soil Properties and Soil Qualitysupporting

confidence: 90%

Section: Predictability Of Indicators and Indicesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping the Spectral Soil Quality Index (SSQI) Using Airborne Imaging Spectroscopy

et al. 2015

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“…For example, there are specific soil quality indicators for the intensively managed soils of the Indo-Gangetic Plains [30] that will differ from those for tropical Alfisols in semi-arid regions [31][32][33][34]. A spectral soil quality index based on application of reflectance spectroscopy has also been proposed as a diagnostic tool to assess soil quality [35]. This technique can provide a characterization of physical, chemical and biological attributes that can be merged together to indicate how well a soil is functioning for a specific use [36][37][38][39].…”

Section: Soil Quality Indexmentioning

confidence: 99%

Restoring Soil Quality to Mitigate Soil Degradation

2015

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Abstract:Feeding the world population, 7.3 billion in 2015 and projected to increase to 9.5 billion by 2050, necessitates an increase in agricultural production of ~70% between 2005 and 2050. Soil degradation, characterized by decline in quality and decrease in ecosystem goods and services, is a major constraint to achieving the required increase in agricultural production. Soil is a non-renewable resource on human time scales with its vulnerability to degradation depending on complex interactions between processes, factors and causes occurring at a range of spatial and temporal scales. Among the major soil degradation processes are accelerated erosion, depletion of the soil organic carbon (SOC) pool and loss in biodiversity, loss of soil fertility and elemental imbalance, acidification and salinization. Soil degradation trends can be reversed by conversion to a restorative land use and adoption of recommended management practices. The strategy is to minimize soil erosion, create positive SOC and N budgets, enhance activity and species diversity of soil biota (micro, meso, and macro), and improve structural stability and pore geometry. Improving soil quality (i.e., increasing SOC pool, improving soil structure, enhancing soil fertility) can reduce risks of soil degradation (physical, chemical, biological and ecological) while improving the environment. Increasing the SOC pool to above the critical level (10 to 15 g/kg) is essential to set-in-motion the restorative trends. Site-specific techniques of restoring soil quality include conservation agriculture, integrated nutrient management, continuous vegetative cover such as residue mulch and cover cropping, and controlled grazing at appropriate stocking rates. The strategy is to produce "more from less" by reducing losses and increasing soil, water, and nutrient use efficiency.

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“…Fertility group comprises the following soil indicators: pH 1:2, EC, OM, Ninor, Pava, CEC, texture and exchangeable fraction of Na, K, Ca, Mg, Fe, Mn, Zn and Cu. Salinity group is comprised by pHsat (saturated paste method), EC, % Sat, [24]. Once the correlated variables were found, a Principal Components Analysis (PCA) was developed.…”

Section: Discussionmentioning

confidence: 99%

Robust Soil Quality Index for Tropical Soils Influenced by Agricultural Activities

Rangel‐Peraza¹,

Padilla-Gasca²,

López-Corrales³

et al. 2017

JACEN

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The knowledge of the soil quality plays a vital role in the agricultural sector. Despite its importance, there is scarce scientific information concerning this regard. The objective of this research is to develop a methodology to identify and select the most appropriate indicators of Soil Quality Index (SQI) in a region with high agricultural activity. For its conformation, a descriptive statistical analysis and a Pearson correlation matrix were performed and the indicators that showed greater variation were identified using a Principal Components Analysis (PCA). A sensitivity analysis was carried out and the most sensible soil indicators of SQI were identified. This statistical procedure was also used to specify the weights of the indicators in SQI. The variables resulting from the multiparametric statistical analysis were pH, organic matter, sodium, calcium, iron, zinc, cation exchange capacity and electrical conductivity. The robustness of the SQI obtained in this study was demonstrated through simulations carried out by the numerical optimization through simplex method. The Soil Quality Index range obtained (0.54 -0.75) locates Culiacan Valley soils as moderate/high quality.

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A spectral soil quality index (SSQI) for characterizing soil function in areas of changed land use

Cited by 86 publications

References 76 publications

Mapping the Spectral Soil Quality Index (SSQI) Using Airborne Imaging Spectroscopy

Mapping the Spectral Soil Quality Index (SSQI) Using Airborne Imaging Spectroscopy

Restoring Soil Quality to Mitigate Soil Degradation

Robust Soil Quality Index for Tropical Soils Influenced by Agricultural Activities

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