VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity
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 tim...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-06-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/6/13994 |
| _version_ | 1817996516131864576 |
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| author | Roemi Fernández Héctor Montes Carlota Salinas |
| author_facet | Roemi Fernández Héctor Montes Carlota Salinas |
| author_sort | Roemi Fernández |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T02:23:18Z |
| format | Article |
| id | doaj.art-a08ba1ebbaa14403a824b1cf48fbbe52 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T02:23:18Z |
| publishDate | 2015-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a08ba1ebbaa14403a824b1cf48fbbe522022-12-22T02:17:57ZengMDPI AGSensors1424-82202015-06-01156139941401510.3390/s150613994s150613994VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing CapacityRoemi Fernández0Héctor Montes1Carlota Salinas2Centre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0.2, La Poveda, Arganda del Rey, Madrid 28500, SpainCentre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0.2, La Poveda, Arganda del Rey, Madrid 28500, SpainCentre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0.2, La Poveda, Arganda del Rey, Madrid 28500, SpainGround 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.http://www.mdpi.com/1424-8220/15/6/13994ground bearing capacityVIS-NIRLWIRSWIRmultispectralsoil moistureoptical filterspenetrometersoil compaction |
| spellingShingle | Roemi Fernández Héctor Montes Carlota Salinas VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity Sensors ground bearing capacity VIS-NIR LWIR SWIR multispectral soil moisture optical filters penetrometer soil compaction |
| title | VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity |
| title_full | VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity |
| title_fullStr | VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity |
| title_full_unstemmed | VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity |
| title_short | VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity |
| title_sort | vis nir swir and lwir imagery for estimation of ground bearing capacity |
| topic | ground bearing capacity VIS-NIR LWIR SWIR multispectral soil moisture optical filters penetrometer soil compaction |
| url | http://www.mdpi.com/1424-8220/15/6/13994 |
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