Estimation of soil properties at the field scale from satellite data: a comparison between spatial and non-spatial techniques

It is known that field-scale variations in subsurface hydraulic characteristics are influenced, to a large extent, by soil properties. Limited information, however, exists on the sensitivity of hydraulic functions to field-scale variations in soil properties. The sensitivity of 4 soil water retention functions, θ(h), to variations in soil properties and changes in bulk density (ρ) across and within soils along a 500-m transect has been assessed in this study. The θ(h) functions compared are those of van Genuchten, Brooks and Corey, Campbell, and Gardner. Water retention characteristics for 7 soils, each packed to 2 relative ρ, were established for each function. The coefficient of determination, R 2 , for the best fit of water retention ranged from 0·79 to 0· 98 for the Gardner and Campbell functions, from 0· 92 to 0·99 for the Brooks and Corey function, and from 0·83 to 0·99 for the van Genuchten function. Simple linear regression analysis indicated the nonlinear slope parameters of the 4 functions were more strongly correlated with soil properties. However, only the van Genuchten slope parameters were sensitive to changes in ρ. No consistency existed between the sensitivity of the linear parameters of the 4 functions and soil properties, and none were sensitive to changes in ρ. Except for the a parameter in the van Genuchten function, all the parameters in this function can be predicted with satisfactory confidence from soil properties and ρ. The results indicate that, of the 4 functions assessed, the van Genuchten θ(h) function is the most sensitive to field-scale variations in soil properties along a transect in a landscape unit and to changes in ρ.

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A Framework for Global Characterization of Soil Properties Using Repeat Hyperspectral Satellite Data

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2018.2883311 ◽

2019 ◽

Vol 57 (6) ◽

pp. 3308-3323

Author(s):

Debsunder Dutta ◽

Praveen Kumar

Keyword(s):

Soil Properties ◽

Satellite Data

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Evapotranspiration Partitioning at Field Scales Using TSEB and Multi-Satellite Data Fusion in The Middle Reaches of Heihe River Basin, Northwest China

Remote Sensing ◽

10.3390/rs12193223 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3223

Author(s):

Yan Li ◽

Chunlin Huang ◽

William P. Kustas ◽

Hector Nieto ◽

Liang Sun ◽

...

Keyword(s):

Data Fusion ◽

River Basin ◽

Satellite Data ◽

Temporal Dynamics ◽

Surface Flux ◽

Northwest China ◽

Heihe River Basin ◽

Heihe River ◽

Field Scale ◽

Natural Ecosystems

Daily evapotranspiration (ET) and its components of evaporation (E) and transpiration (T) at field scale are often required for improving agricultural water management and maintaining ecosystem health, especially in semiarid and arid regions. In this study, multi-year daily ET, E, and T at a spatial resolution of 100 m in the middle reaches of Heihe River Basin were computed based on an ET partitioning method developed by combing remote sensing-based ET model and multi-satellite data fusion methodology. Evaluations using flux tower measurements over irrigated cropland and natural desert sites indicate that this method can provide reliable estimates of surface flux partitioning and daily ET. Modeled daily ET yielded root mean square error (RMSE) values of 0.85 mm for cropland site and 0.84 mm for desert site, respectively. The E and T partitioning capabilities of this proposed method was further assessed by using ratios E/ET and T/ET derived from isotopic technology at the irrigated cropland site. Results show that apart from early in the growing season when the actual E was reduced by plastic film mulching, the modeled E/ET and T/ET agree well with observations in terms of both magnitude and temporal dynamics. The multi-year seasonal patterns of modeled ET, E, and T at field scale from this ET partitioning method shows reasonable seasonal variation and spatial variability, which can be used for monitoring plant water consumption in both agricultural and natural ecosystems.

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Three-dimensional digital soil mapping of multiple soil properties at a field-scale using regression kriging

Geoderma ◽

10.1016/j.geoderma.2020.114253 ◽

2020 ◽

Vol 366 ◽

pp. 114253 ◽

Cited By ~ 2

Author(s):

Yakun Zhang ◽

Wenjun Ji ◽

Daniel D. Saurette ◽

Tahmid Huq Easher ◽

Hongyi Li ◽

...

Keyword(s):

Soil Properties ◽

Three Dimensional ◽

Soil Mapping ◽

Digital Soil Mapping ◽

Regression Kriging ◽

Field Scale

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Spatial Variability of Grapevine Bud Burst Percentage and Its Association with Soil Properties at Field Scale

PLoS ONE ◽

10.1371/journal.pone.0165738 ◽

2016 ◽

Vol 11 (10) ◽

pp. e0165738 ◽

Cited By ~ 2

Author(s):

Tao Li ◽

Xinmei Hao ◽

Shaozhong Kang

Keyword(s):

Spatial Variability ◽

Soil Properties ◽

Bud Burst ◽

Field Scale

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Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties

Canadian Journal of Soil Science ◽

10.4141/cjss2013-079 ◽

2014 ◽

Vol 94 (2) ◽

pp. 189-208 ◽

Cited By ~ 2

Author(s):

Catherine A. Fox ◽

Charles Tarnocai ◽

Gabriele Broll ◽

Monika Joschko ◽

David Kroetsch ◽

...

Keyword(s):

Soil Properties ◽

Best Management Practices ◽

Management Practices ◽

Dynamic Properties ◽

Experimental Studies ◽

Density Level ◽

Field Scale ◽

Dynamic Soil Properties ◽

Field Form ◽

Fingerprint Code

Fox, C. A., Tarnocai, C., Broll, G., Joschko, M., Kroetsch, D. and Kenney, E. 2014. Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties. Can. J. Soil Sci. 94: 189–208. Taxonomic protocols for A horizon description are limited when detailed monitoring of soil change in dynamic soil properties is required for determining the effectiveness of best management practices, remediation efforts, and assessing subtle impacts on soil properties from environmental and anthropogenic stressors. The A Horizon Framework was designed by consolidating protocols from national and international description systems and expert opinion to optimize descriptive capability through use of additional enhanced lowercase designators. The Framework defines new protocols and syntax resulting in a unique soil fingerprint code. Five levels of enhanced lowercase A horizon designators are defined: Level 1, Soil processes and environmental context; Level 2, Soil structure-bulk density; Level 3, Organic carbon; Level 4, pH and electrical conductivity; and, Level 5, Soil and landscape context (i.e., soil texture, surface conditions, current land use, slope character). An electronic Field Form based on the new Framework syntax automatically records the soil fingerprint code in an enhanced (all Levels included) and a minimum detail mode focused on the key dynamic properties. The soil fingerprint codes become a powerful tool by which to identify trends of soil change and small alterations in the dynamic soil properties. Examples of soil fingerprint codes from selected Canada and Germany long-term experimental studies are presented.

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