NORTHERN AND MID-LATITUDE SOIL DATABASE, VERSION 1

2004 ◽  
Author(s):  
C. TARNOCAI
Keyword(s):  
Soil Database

scholarly journals A Comparative Study of Various Methods of Handling Missing Data in UNSODA

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 727
Author(s):  
Yingpeng Fu ◽  
Hongjian Liao ◽  
Longlong Lv
Keyword(s):  
Missing Data ◽  
Missing Values ◽  
Soil Property ◽  
Particle Density ◽  
Organic Matter Content ◽  
Nonparametric Tests ◽  
Matter Content ◽  
Support Vector ◽  
Soil Database ◽  
Property Data

UNSODA, a free international soil database, is very popular and has been used in many fields. However, missing soil property data have limited the utility of this dataset, especially for data-driven models. Here, three machine learning-based methods, i.e., random forest (RF) regression, support vector (SVR) regression, and artificial neural network (ANN) regression, and two statistics-based methods, i.e., mean and multiple imputation (MI), were used to impute the missing soil property data, including pH, saturated hydraulic conductivity (SHC), organic matter content (OMC), porosity (PO), and particle density (PD). The missing upper depths (DU) and lower depths (DL) for the sampling locations were also imputed. Before imputing the missing values in UNSODA, a missing value simulation was performed and evaluated quantitatively. Next, nonparametric tests and multiple linear regression were performed to qualitatively evaluate the reliability of these five imputation methods. Results showed that RMSEs and MAEs of all features fluctuated within acceptable ranges. RF imputation and MI presented the lowest RMSEs and MAEs; both methods are good at explaining the variability of data. The standard error, coefficient of variance, and standard deviation decreased significantly after imputation, and there were no significant differences before and after imputation. Together, DU, pH, SHC, OMC, PO, and PD explained 91.0%, 63.9%, 88.5%, 59.4%, and 90.2% of the variation in BD using RF, SVR, ANN, mean, and MI, respectively; and this value was 99.8% when missing values were discarded. This study suggests that the RF and MI methods may be better for imputing the missing data in UNSODA.

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.

Evaluating the role of soil physical properties on simulated land-atmosphere interactions over South Africa using coupled atmosphere-hydrological modeling

2021 ◽  
Author(s):  
Zhenyu Zhang ◽  
Patrick Laux ◽  
Joël Arnault ◽  
Jianhui Wei ◽  
Jussi Baade ◽  
...  
Keyword(s):  
South Africa ◽  
Physical Properties ◽  
Land Degradation ◽  
Land Surface ◽  
Soil Physical Properties ◽  
Near Surface ◽  
Soil Database ◽  
Global Soil ◽  
The Impact

<p>Land degradation with its direct impact on vegetation, surface soil layers and land surface albedo, has great relevance with the climate system. Assessing the climatic and ecological effects induced by land degradation requires a precise understanding of the interaction between the land surface and atmosphere. In coupled land-atmosphere modeling, the low boundary conditions impact the thermal and hydraulic exchanges at the land surface, therefore regulates the overlying atmosphere by land-atmosphere feedback processes. However, those land-atmosphere interactions are not convincingly represented in coupled land-atmosphere modeling applications. It is partly due to an approximate representation of hydrological processes in land surface modeling. Another source of uncertainties relates to the generalization of soil physical properties in the modeling system. This study focuses on the role of the prescribed physical properties of soil in high-resolution land surface-atmosphere simulations over South Africa. The model used here is the hydrologically-enhanced Weather Research and Forecasting (WRF-Hydro) model. Four commonly used global soil datasets obtained from UN Food and Agriculture Organization (FAO) soil database, Harmonized World Soil Database (HWSD), Global Soil Dataset for Earth System Model (GSDE), and SoilGrids dataset, are incorporated within the WRF-Hydro experiments for investigating the impact of soil information on land-atmosphere interactions. The simulation results of near-surface temperature, skin temperature, and surface energy fluxes are presented and compared to observational-based reference dataset. It is found that simulated soil moisture is largely influenced by soil texture features, which affects its feedback to the atmosphere.</p>

scholarly journals Synchrotron Radiation X-ray Analyses of Heavy Minerals and Heavy Elements in River Sediments of Kyushu for Constructing a Forensic Soil Database

2016 ◽  
Vol 65 (2) ◽  
pp. 93-98 ◽  
Author(s):  
Junko HIROKAWA ◽  
Issei MAEDA ◽  
Shunsuke FURUYA ◽  
Yoshinari ABE ◽  
Keiichi OSAKA ◽  
...  
Keyword(s):  
Synchrotron Radiation ◽  
River Sediments ◽  
Heavy Elements ◽  
Heavy Minerals ◽  
X Ray ◽  
Soil Database

scholarly journals Applicability of laser diffraction analyses in soil physics practice

2016 ◽  
Vol 5 (1-2) ◽  
pp. 32-37
Author(s):  
András Makó ◽  
József Szabó ◽  
Zsófia Bakacsi ◽  
Sándor Koós ◽  
Gabriella Hauk ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Laser Diffraction ◽  
Soil Samples ◽  
Soil Types ◽  
Diffraction Measurement ◽  
Boundary Values ◽  
Soil Physics ◽  
Soil Database ◽  
First Results

In this research we present the first results how can be used laser diffraction measurement in soil physics practice. The main goals are understanding differences of particle size distribution (PSD) measurments, developing converting methods of PSD data of different determinations. In order to realization of this survey a representative soil database of Hungarian soil types was built up. We compared PSDs of 157 soil samples measured with sieve-pipette method (SPM) and laser diffractometer technique (Malvern Mastersizer 2000) (LDM). Soil textural classes were also determined using the USDA texture triangle. We used the clay/silt fraction boundary values (clay < 0.0066 mm; silt: 0.0066 - 0.05 mm) introduced for the LDM data in order to take them comparable to PSD data determined by the SPM: We got higher similarities of clay and silt fractions of the modified size boundary values. For the used dataset correspondence of texture classes derived from SPM and LDM PSD data, however is not higher than 60%.

scholarly journals Online Fertilizer Recommendation System (OFRS): A Step Towards Precision Agriculture And Optimized Fertilizer Usage By Smallholder Farmers In Bangladesh

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
M. A. Hossain ◽  
M. N. A. Siddique
Keyword(s):  
Precision Agriculture ◽  
Recommendation System ◽  
Smallholder Farmers ◽  
Fertilizer Application ◽  
Soil Test ◽  
Total Production ◽  
Soil Database ◽  
Fertilizer Recommendation ◽  
Fertilizer Recommendations ◽  
Input Cost

The recent progression and Green Revolution (approx. between the 1990s-2010s) in agriculture of Bangladesh resulted in an increase of total production despite yield-gap to ensure food security. But agriculture in Bangladesh is still backed-up by higher use of inputs (agrochemicals-fertilizers, pesticides; modern varieties, irrigation etc.) and inversion tillage. This conventional agrochemical-based smallholder agriculture may lead to soil and environmental degradation, soil acidification, and a decline in soil fertility. Therefore, it is significant to optimize input application in intensive agriculture, especially fertilizers. This paper introduces the potential online facilities of generating online fertilizer recommendations for smallholder farmers in Bangladesh to ensure proper usage of fertilizers and enable sustainable agricultural production. We also highlighted how the usage of fertilizers increased with an increase in total production over time. But the sustainability of production in the years to come still remain challenging. With the aim of sustainable crop production, reduction in the misuse of fertilizers and reduction of input cost by optimizing the present pattern of excessive fertilizer application, the Soil Resource Development Institute (SRDI) provides location-specific fertilizer recommendation through both the manual and soil test based interpretation of plant nutrients: soil database in Upzazila Nirdeshika and static laboratory soil analysis. Recently, SRDI developed web-based software named Online Fertilizer Recommendation System (OFRS). The system is capable of generating location-specific fertilizer recommendations for selected crops by analyzing the national soil database developed by this governmental institute. The software requires farmer field location, respective soil and land type, and crop type and variety information to generate crop-specific instant fertilizer recommendation. It was observed that by using fertilizer according to the recommended dose calculated on the basis of soil test values, farmers could harvest approx. 7-22% higher yield of different crops over usual farmers practice. If this system can be popularized and disseminated by effective agricultural extension, this would immensely contribute to the promotion of precision agriculture, input cost reduction and it would certainly enable us to optimize fertilizer application by the smallholder farmers in Bangladesh.

Use of a large world soil database for modeling the global soil distribution

2007 ◽  
Vol 40 (9) ◽  
pp. 928-933 ◽  
Author(s):  
J. M. Gray ◽  
G. S. Humphreys ◽  
J. A. Deckers
Keyword(s):  
Soil Database ◽  
Global Soil ◽  
Soil Distribution
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