Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

In-Season Estimation of Japanese Squash Using High-Spatial-Resolution Time-Series Satellite Imagery.

Sensors (Basel, Switzerland)·2025
Same author

Apparent soil electrical conductivity and gamma-ray spectrometry to map particle size fraction in micro-irrigated citrus orchards in California.

Frontiers in plant science·2025
Same author

Relationships among soil moisture at various depths under diverse climate, land cover and soil texture.

The Science of the total environment·2024
Same author

Electromagnetic sensing and infiltration measurements to evaluate turfgrass salinity and reclamation.

Scientific reports·2022
Same author

Multitemporal satellite imagery analysis for soil organic carbon assessment in an agricultural farm in southeastern Brazil.

The Science of the total environment·2021
Same author

Modeling of xylem vessel occlusion in grapevine.

Tree physiology·2019

Related Experiment Video

Updated: Mar 18, 2026

In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

7.8K

Validation of Sensor-Directed Spatial Simulated Annealing Soil Sampling Strategy.

Elia Scudiero, Scott M Lesch, Dennis L Corwin

    Journal of Environmental Quality
    |July 6, 2016
    PubMed
    Summary

    Spatial simulated annealing and response surface sampling design provide similar accuracy for mapping soil salinity and other properties. This validates spatial simulated annealing for agronomic and environmental soil science applications.

    More Related Videos

    Sampling Soils in a Heterogeneous Research Plot
    07:11

    Sampling Soils in a Heterogeneous Research Plot

    Published on: January 7, 2019

    36.1K
    Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations
    10:30

    Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

    Published on: September 11, 2016

    11.4K

    Related Experiment Videos

    Last Updated: Mar 18, 2026

    In Situ Soil Moisture Sensors in Undisturbed Soils
    08:20

    In Situ Soil Moisture Sensors in Undisturbed Soils

    Published on: November 18, 2022

    7.8K
    Sampling Soils in a Heterogeneous Research Plot
    07:11

    Sampling Soils in a Heterogeneous Research Plot

    Published on: January 7, 2019

    36.1K
    Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations
    10:30

    Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

    Published on: September 11, 2016

    11.4K

    Area of Science:

    • Agronomy
    • Soil Science
    • Environmental Science

    Background:

    • Soil spatial variability significantly impacts agronomic and environmental processes.
    • Mobile sensors offer practical mapping of soil variability, requiring sensor-soil calibration.
    • Linear regression modeling is a viable method for calibrating sensor measurements to soil properties.

    Purpose of the Study:

    • Compare two sampling scheme delineation methods: spatial simulated annealing and response surface sampling design (RSSD).
    • Validate spatial simulated annealing against the established RSSD approach for soil property mapping.
    • Assess the effectiveness of both methods in sensor calibration and spatial coverage.

    Main Methods:

    • Surveyed a 6.8-ha area for soil apparent electrical conductivity (EC).
    • Selected 30 soil sampling locations per strategy using EC-directed spatial simulated annealing and RSSD.
    • Compared sensor calibration to salinity and spatial coverage for nontarget properties.

    Main Results:

    • Linear modeling of EC-salinity calibrations from both schemes yielded salinity maps with similar errors.
    • Maps of nontarget soil properties also showed comparable errors across sampling strategies.
    • Spatial simulated annealing was validated as an effective sampling methodology.

    Conclusions:

    • Spatial simulated annealing is a validated and justified methodology for agronomic and environmental soil science.
    • Both spatial simulated annealing and RSSD offer comparable performance in mapping soil properties.
    • The findings support the use of spatial simulated annealing for efficient and accurate soil mapping.