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VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity.

Fernández R, Montes H, Salinas C - Sensors (Basel) (2015)

Bottom Line: Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming.The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation.Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations.

View Article: PubMed Central - PubMed

Affiliation: Centre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0.2, La Poveda, Arganda del Rey, Madrid 28500, Spain. roemi.fernandez@car.upm-csic.es.

ABSTRACT
Ground bearing capacity has become a relevant concept for site-specific management that aims to protect soil from the compaction and the rutting produced by the indiscriminate use of agricultural and forestry machines. Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming. In order to alleviate these difficulties, this paper introduces an innovative sensory system based on Visible-Near InfraRed (VIS-NIR), Short-Wave InfraRed (SWIR) and Long-Wave InfraRed (LWIR) imagery and a sequential algorithm that combines a registration procedure, a multi-class SVM classifier, a K-means clustering and a linear regression for estimating the ground bearing capacity. To evaluate the feasibility and capabilities of the presented approach, several experimental tests were carried out in a sandy-loam terrain. The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation. Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations.

No MeSH data available.


Related in: MedlinePlus

Penetrometer utilised during the experimental tests.
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sensors-15-13994-f002: Penetrometer utilised during the experimental tests.

Mentions: It is also important to mention that during the design phase several measurements were carried out not only with the proposed sensory rig, but also with a penetrometer, so that the soil penetration resistance acquired with the penetrometer could be associated with the normalised reflectance value of the SWIR images. The M06.01 penetrometer (Eijkelkamp, Giesbeek, The Netherlands) utilised during these tests for the acquisition of training data is shown in Figure 2. It is composed of a steel rod fitted with a conical tip, a device to monitor the force, and several marks to locate some predefined positions of the cone. The cone has 60° angle, and the basal area is equal to 1 cm2. For each test the cone was pushed into the soil at constant velocity and the penetration resistance was read at certain depths.


VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity.

Fernández R, Montes H, Salinas C - Sensors (Basel) (2015)

Penetrometer utilised during the experimental tests.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507653&req=5

sensors-15-13994-f002: Penetrometer utilised during the experimental tests.
Mentions: It is also important to mention that during the design phase several measurements were carried out not only with the proposed sensory rig, but also with a penetrometer, so that the soil penetration resistance acquired with the penetrometer could be associated with the normalised reflectance value of the SWIR images. The M06.01 penetrometer (Eijkelkamp, Giesbeek, The Netherlands) utilised during these tests for the acquisition of training data is shown in Figure 2. It is composed of a steel rod fitted with a conical tip, a device to monitor the force, and several marks to locate some predefined positions of the cone. The cone has 60° angle, and the basal area is equal to 1 cm2. For each test the cone was pushed into the soil at constant velocity and the penetration resistance was read at certain depths.

Bottom Line: Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming.The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation.Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations.

View Article: PubMed Central - PubMed

Affiliation: Centre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0.2, La Poveda, Arganda del Rey, Madrid 28500, Spain. roemi.fernandez@car.upm-csic.es.

ABSTRACT
Ground bearing capacity has become a relevant concept for site-specific management that aims to protect soil from the compaction and the rutting produced by the indiscriminate use of agricultural and forestry machines. Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming. In order to alleviate these difficulties, this paper introduces an innovative sensory system based on Visible-Near InfraRed (VIS-NIR), Short-Wave InfraRed (SWIR) and Long-Wave InfraRed (LWIR) imagery and a sequential algorithm that combines a registration procedure, a multi-class SVM classifier, a K-means clustering and a linear regression for estimating the ground bearing capacity. To evaluate the feasibility and capabilities of the presented approach, several experimental tests were carried out in a sandy-loam terrain. The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation. Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations.

No MeSH data available.


Related in: MedlinePlus