scholarly journals Quantitative Analysis of Spectral Response to Soda Saline-AlkaliSoil after Cracking Process: A Laboratory Procedure to Improve Soil Property Estimation

2019 ◽  
Vol 11 (12) ◽  
pp. 1406
Author(s):  
Jianhua Ren ◽  
Xiaojie Li ◽  
Sijia Li ◽  
Honglei Zhu ◽  
Kai Zhao
Keyword(s):  
Soil Properties ◽  
Soil Property ◽  
Spectral Response ◽  
Texture Feature ◽  
Soil Surface ◽  
Soil Samples ◽  
Spectral Measurements ◽  
Spectral Difference ◽  
Property Estimation ◽  
Alkali Soil

Cracking on the surface of soda saline-alkali soil is very common. In most previous studies, spectral prediction models of soil salinity were less accurate since spectral measurements were usually performed on 2 mm soil samples which cannot represent true soil surface condition very well. The objective of our research is to provide a procedure to improve soil property estimation of soda saline-alkali soil based on spectral measurement considering the texture feature of the soil surface with cracks. To achieve this objective, a cracking test was performed with 57 soil samples from Songnen Plain of China, the contrast (CON) texture feature of crack images of soil samples was then extracted from grey level co-occurrence matrix (GLCM). The original reflectance was then measured and the mixed reflectance considering the CON texture feature was also calculated from both the block soil samples (soil blocks separated by crack regions) and the comparison soil samples (soil powders with 2 mm particle size). The results of analysis between spectra and the main soil properties indicate that surface cracks can reduce the overall reflectivity of the soda saline-alkali soil and thus increasing the spectral difference among the block soil samples with different salinity levels. The results also show that both univariate and multivariate linear regression models considering the CON texture feature can greatly improve the prediction accuracy of main soil properties of soda saline-alkali soils, such as Na+, EC and salinity, which also can reduce the intensity of field spectral measurements under natural condition.

scholarly journals USING LEGACY SOIL DATA FOR STANDARDIZING PREDICTIONS OF TOPSOIL CLAY CONTENT OBTAINED FROM VNIR/SWIR HYPERSPECTRAL AIRBORNE IMAGES

2015 ◽  
Vol XL-3/W3 ◽  
pp. 439-444
Author(s):  
C. Gomez ◽  
A. Gholizadeh ◽  
L. Borůvka ◽  
P. Lagacherie
Keyword(s):  
Soil Properties ◽  
Spectral Index ◽  
Near Infrared ◽  
Soil Property ◽  
Clay Content ◽  
Short Wave ◽  
Soil Samples ◽  
Spectral Bands ◽  
Large Sets ◽  
The One

Mapping of topsoil properties using Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery requires large sets of ground measurements for calibrating the models that estimate soil properties. To avoid collecting such expensive data, we proposed a procedure including two steps that involves only legacy soil data that were collected over and?or around the study site: <i>1)</i> estimation of a soil property using a spectral index of the literature and <i>2)</i> standardisation of the estimated soil property using legacy soil data. This approach was tested for mapping clay contents in a Mediterranean region in which VNIR/SWIR AISA-DUAL hyperspectral airborne data were acquired. The spectral index was the one proposed by Levin et al (2007) using the spectral bands at 2209, 2133 and 2225 nm. Two legacy soil databases were tested as inputs of the procedure: the <i>Focused-Legacy</i> database composed of 67 soil samples collected in 2000 over the study area, and the No-Focused-Legacy database composed of 64 soil samples collected between 1973 and 1979 around but outside of the study area. The results were compared with those obtained from 120 soil samples collected over the study area during the hyperspectral airborne data acquisition, which were considered as a reference. <br><br> Our results showed that: <i>1)</i> the spectral index with no further standardisation offered predictions with high accuracy in term of coefficient of correlation <i>r</i> (0.71), but also high <i>bias</i> (&minus;414 g/kg) and <i>SEP</i> (439 g/kg), <i>2)</i> the standardisation using both legacy soil databases allowed an increase of accuracy (<i>r</i> = 0.76) and a reduction of <i>bias</i> and <i>SEP</i> and <i>3)</i> a better standardisation was obtained by using the <i>Focused-Legacy</i> database rather than the <i>No-Focused-Legacy</i> database. Finally, the clay predicted map obtained with standardisation using the <i>Focused-Legacy</i> database showed pedologically-significant soil spatial structures with clear short-scale variations of topsoil clay contents in specific areas. <br><br> This study, associated with the coming availability of a next generation of hyperspectral VNIR/SWIR satellite data for the entire globe, paves the way for inexpensive methods for delivering high resolution soil properties maps.

scholarly journals Comparative Analysis of the Spectral Response to Soil Salinity of Saline-Sodic Soils under Different Surface Conditions

2018 ◽  
Vol 15 (12) ◽  
pp. 2721 ◽  
Author(s):  
Jianhua Ren ◽  
Kai Zhao ◽  
Xiangwen Wu ◽  
Xingming Zheng ◽  
Xiaojie Li
Keyword(s):  
Soil Properties ◽  
Soil Salinity ◽  
Prediction Models ◽  
Spectral Response ◽  
Total Concentration ◽  
Salt Content ◽  
Size Fraction ◽  
Soil Samples ◽  
Sodic Soils ◽  
Cracked Soil

Desiccation cracking is a very common surface soil phenomenon of saline-sodic land. The objective of this study was to investigate the effects of salt content on the spectral reflectance of soil with and without desiccation cracks. To achieve our objective, a cracking test was performed using 17 soil samples. Following the tests, crack parameters were extracted, and correlation analysis was then performed between crack parameters and four soil properties: Na+, salinity (total concentration of ions), pH, and electric conductivity (EC). In order to select the optimum spectral measurement method and develop prediction models, spectral response to different soil properties were compared between the cracked soil samples and the comparative soil samples composed of the 2 mm particle size fraction processed by traditional methods. The results indicate that soil salinity dominated cracking propagation with a positive correlation. Since area and volume scattering are closer to what occurs in the field, a greater spectral response to soil properties was found for cracked soil samples relative to the comparative soil samples in the near-infrared and shortwave-infrared regions. The R2 of optimal linear prediction models based on the cracked soil samples were 0.74, 0.67, 0.58, and 0.67 for Na+, salinity, pH, and EC, respectively.

scholarly journals Ecotone Dynamics and Stability from Soil Scientific Point of View

Diversity ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 53 ◽  
Author(s):  
Theodore Marfo ◽  
Rahul Datta ◽  
Shamina Pathan ◽  
Valerie Vranová
Keyword(s):  
Soil Properties ◽  
Soil Surface ◽  
Forest Stand ◽  
Soil Samples ◽  
Point Of View ◽  
Soil Reaction ◽  
Forest Region ◽  
Vegetation Structures ◽  
Air Capacity ◽  
Water Holding

Transitional areas between two or more different biomes—ecotones—are clearly visible due to the sudden changes in vegetation structures and patterns. However, much is still unknown about the crucial soil factors that control such vegetational changes across ecotones and how different soil properties vary across ecotones. In this study, we try to understand the spatial variation in soil properties across a clearly defined ecotone from a forest stand to meadow field at the Training Forest Enterprise (T.F.E), Masaryk Forest Křtiny, Czechia. Thirteen sampling sites were selected: six in the forest region, six in the meadow and one in the ecotone zone between forest and meadow. Soil samples were taken at 5 cm below the soil surface once every month from April to November. All the collected soil samples were examined for minimal air capacity, actual and potential soil reaction and maximum capillary water. The results showed a pattern of soil acidity decreasing from the forest stand towards the meadow field but that increased sharply at the ecotone zone. The water holding capacity showed a decreasing trend approaching the ecotone zone from the meadow region and markedly decreased from the meadow site closest to the ecotone zone. The minimum air capacity showed an increasing trend from the forest region but suddenly declined at the ecotone region.

Quantifying the uncertainty in the prediction of soil properties from soil-spectra using local and regional spectral libraries

2020 ◽  
Author(s):  
Timo Breure ◽  
Alice Milne ◽  
Richard Webster ◽  
Stephan M. Haefele ◽  
Jacqueline A. Hannam ◽  
...  
Keyword(s):  
Soil Properties ◽  
Reference Values ◽  
Fixed Effects ◽  
Linear Mixed Model ◽  
Size Fraction ◽  
Soil Samples ◽  
Spectral Measurements ◽  
Total N ◽  
Wet Chemistry ◽  
Spectral Libraries

&lt;p&gt;Spectral measurements are increasingly used to predict soil properties. Libraries of soil spectra are built and statistical models are used to relate the spectra to wet chemistry measurements. These relationships can then be used to predict the properties of new samples. An important&amp;#160; consideration is the uncertainty associated with the prediction. Often to reduce this error calibration is done at field level. This is time and resource intensive, however, and there is scope to use existing spectral libraries. Our aim was to quantify the uncertainty in the prediction of soil properties from spectral measurements using a local library and compare this to predictions made using a regional library. &amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;To investigate this, we considered two case study fields in the Cambridgeshire fens (UK) that were planted with lettuce. These fields contain complex soils which are a combination of peat with underlying alluvial and marine silts that became elevated features in the landscape due to peat oxidation and shrinkage. These elevated features are captured by a 2 m x 2 m LiDAR raster used in our study (UK Environment Agency). We took a total 467 soil samples across the fields and made spectral measurements (near- and mid-infrared). A subset of the soil samples underwent wet chemistry analysis for available pH, P, K, total N and soil particle size fraction. For the regional library we use soil the National Soil Inventory spectral database and its respective wet chemistry reference values.&lt;/p&gt;&lt;p&gt;We used partial least squares to regress the soil spectra for the local and regional spectral libraries against the wet chemistry reference values. These two models were then used to predict the soil properties for both fields. We then mapped the variation in each soil property and the associated uncertainty by kriging. &amp;#160;The variation in some of the soil variables was clearly affected by elevation and there were signs of spatial trend and so we used universal kriging to map the soil properties. To reduce bias, we used residual maximum likelihood estimation (REML) to estimate the variogram by fitting a linear mixed model with the trend accounted for as fixed effects. &amp;#160;We compared these different maps to assess how the calibration regression from local and regional spectral libraries translates itself in uncertainty of kriged maps for five different soil properties within each field.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Soil Surface Reflectance as a Tool to Estimate Water Infiltration Rate from UAV Platforms

2020 ◽  
Author(s):  
Nicolas Francos ◽  
Eyal Ben Dor ◽  
Nunzio Romano ◽  
Paolo Nasta ◽  
Briggita Szabó ◽  
...  
Keyword(s):  
Soil Properties ◽  
Precision Agriculture ◽  
Soil Surface ◽  
Infiltration Rate ◽  
Soil Survey ◽  
Water Infiltration ◽  
Surface Reflectance ◽  
Spectral Measurements ◽  
Laboratory Conditions ◽  
Spectral Libraries

&lt;p&gt;Soil is an essential component in the environment and is vital for food security. It provides ecosystem services, filters water, supplies nutrients to plants, provides us with food, stores carbon, regulates greenhouse gases emissions and it affects our climate. Traditional soil survey methodologies are complicated, expensive, and time-consuming. Visible and infrared spectroscopy can effectively characterize soil properties. Spectral measurements are rapid, precise and inexpensive. The spectra contain information about soil properties, which comprises minerals, organic compounds, and water. Today, several Soil Spectral Libraries (SSLs) are being created worldwide because these datasets have a notable potential to be used as training datasets for machine learning methods that will benefit precision agriculture activity for better management of food production. Nonetheless, as SSL's are created under laboratory conditions it is not clear if it can be used to infer field conditions in situ and/or from the sky. Thus, study the relationship between RS, field spectroscopy and the laboratory measurements of soil is very important. Accordingly, this study postulates that traditional SSLs don't simulate the real spectral signatures in the field that both, satellite and airborne sensors measure as well, because they are affected by factors that are not an integral part of the soil, such as: moisture, litter, human and animal activity, plow, grass, dung, waste, etc&amp;#8230; However, under laboratory conditions, these factors are usually removed for the preparation of SSLs. Thus, given the several SSLs available, it is necessary to evaluate the protocols that were used in these SSLs. The objective of this study is to evaluate the gap between field and laboratory spectral measurements through the analysis of the performance of spectral based models. This procedure combined two soil spectral libraries that contain 114 samples that were measured in the laboratory as well as in the field. The nature of the dataset is varied, because these samples were collected from six different fields in three countries of the Mediterranean basin: Israel, Greece and Italy. Moreover, 63 samples are mainly sandy and 51 are mainly clayey. In order to obtain optimal spectral measurements in the field, we used a new optical apparatus that simulates the sun's radiation. Next, we generated PLSR models to estimate one of the most important hydrological parameters namely &amp;#8220;infiltration rate&amp;#8221; that control the runoff stage, soil erosion and water storage in the soil profile. This property is strongly affected by the surface characteristics. Finally, the field based spectral model was adapted to an UAV hyperspectral sensor in order to estimate the infiltration rate from the sky. The results were successfully validated in field, and we concluded that for the estimation of the infiltration rate, SSLs must be created using surface reflectance in field because laboratory protocols can be detrimental for the performance of the dataset in question.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties

2014 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Set Foong Ng ◽  
Pei Eng Ch’ng ◽  
Yee Ming Chew ◽  
Kok Shien Ng
Keyword(s):  
Soil Properties ◽  
Lagrange Multipliers ◽  
Unbiased Estimator ◽  
Soil Property ◽  
Minimum Variance ◽  
Distance Method ◽  
True Value ◽  
A Site ◽  
Method Of Lagrange Multipliers ◽  
Inverse Distance

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

scholarly journals Research trends of microplastics in the soil environment: Comprehensive screening of effects

2021 ◽  
Author(s):  
Shin Woong Kim ◽  
Matthias C. Rillig
Keyword(s):  
Soil Properties ◽  
Additional Data ◽  
Soil Property ◽  
Dry Weight ◽  
Current Data ◽  
Soil Biota ◽  
Soil Parameters ◽  
Soil Environment ◽  
Soil System ◽  
Sensitivity Distribution

AbstractWe collated and synthesized previous studies that reported the impacts of microplastics on soil parameters. The data were classified and integrated to screen for the proportion of significant effects, then we suggest several directions to alleviate the current data limitation in future experiments. We compiled 106 datasets capturing significant effects, which were analyzed in detail. We found that polyethylene and pellets (or powders) were the most frequently used microplastic composition and shape for soil experiments. The significant effects mainly occurred in broad size ranges (0.1–1 mm) at test concentrations of 0.1%–10% based on soil dry weight. Polyvinyl chloride and film induced significant effects at lower concentrations compared to other compositions and shapes, respectively. We adopted a species sensitivity distribution (SSD) and soil property effect distribution (SPED) method using available data from soil biota, and for soil properties and enzymes deemed relevant for microplastic management. The predicted-no-effect-concentration (PNEC)-like values needed to protect 95% of soil biota and soil properties was estimated to be between 520 and 655 mg kg−1. This study was the first to screen microplastic levels with a view toward protecting the soil system. Our results should be regularly updated (e.g., quarterly) with additional data as they become available.

scholarly journals A Comparison, Validation, and Evaluation of the S-world Global Soil Property Database

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 544
Author(s):  
Jetse J. Stoorvogel ◽  
Vera L. Mulder
Keyword(s):  
Comparative Analysis ◽  
Soil Properties ◽  
Soil Property ◽  
Evaluation Criteria ◽  
Clay Content ◽  
Soil Database ◽  
Global Environmental ◽  
Global Soil ◽  
Mean Square Difference ◽  
Methodological Evaluation

Despite the increased usage of global soil property maps, a proper review of the maps rarely takes place. This study aims to explore the options for such a review with an application for the S-World global soil property database. Global soil organic carbon (SOC) and clay content maps from S-World were studied at two spatial resolutions in three steps. First, a comparative analysis with an ensemble of seven datasets derived from five other global soil databases was done. Second, a validation of S-World was done with independent soil observations from the WoSIS soil profile database. Third, a methodological evaluation of S-world took place by looking at the variation of soil properties per soil type and short distance variability. In the comparative analysis, S-World and the ensemble of other maps show similar spatial patterns. However, the ensemble locally shows large discrepancies (e.g., in boreal regions where typically SOC contents are high and the sampling density is low). Overall, the results show that S-World is not deviating strongly from the model ensemble (91% of the area falls within a 1.5% SOC range in the topsoil). The validation with the WoSIS database showed that S-World was able to capture a large part of the variation (with, e.g., a root mean square difference of 1.7% for SOC in the topsoil and a mean difference of 1.2%). Finally, the methodological evaluation revealed that estimates of the ranges of soil properties for the different soil types can be improved by using the larger WoSIS database. It is concluded that the review through the comparison, validation, and evaluation provides a good overview of the strengths and the weaknesses of S-World. The three approaches to review the database each provide specific insights regarding the quality of the database. Specific evaluation criteria for an application will determine whether S-World is a suitable soil database for use in global environmental studies.

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