Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery
Accurate information on the spatial distribution of weeds is the key to effective site-specific weed management and the efficient and sustainable use of weed control measures. This work focuses on the early detection of johnsongrass, common cocklebur and velvetleaf present in a corn field using high...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/13/2/528 |
| _version_ | 1797622887265337344 |
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| author | María Pilar Martín Bernarda Ponce Pilar Echavarría José Dorado Cesar Fernández-Quintanilla |
| author_facet | María Pilar Martín Bernarda Ponce Pilar Echavarría José Dorado Cesar Fernández-Quintanilla |
| author_sort | María Pilar Martín |
| collection | DOAJ |
| description | Accurate information on the spatial distribution of weeds is the key to effective site-specific weed management and the efficient and sustainable use of weed control measures. This work focuses on the early detection of johnsongrass, common cocklebur and velvetleaf present in a corn field using high resolution airborne hyperspectral imagery acquired when corn plants were in a four to six leaf growth stage. Following the appropriate radiometric and geometric corrections, two supervised classification techniques, such as spectral angle mapper (SAM) and spectral mixture analysis (SMA) were applied. Two different procedures were compared for endmember selections: field spectral measurements and automatic methods to identify pure pixels in the image. Maps for both, overall weeds and for each of the three weed species, were obtained with the different classification methods and endmember sources. The best results were achieved by defining the endmembers through spectral information collected with a field spectroradiometer. Overall accuracies ranged between 60% and 80% using SAM for maps that do not differentiate the weed species while it decreased to 52% when the three weed species were individually classified. In this case, the SMA classification technique clearly improved the SAM results. The proposed methodology shows it to be a promising prospect to be applicable to low cost images acquired by the new generation of hyperspectral sensors onboard unmanned aerial vehicles (UAVs). |
| first_indexed | 2024-03-11T09:16:40Z |
| format | Article |
| id | doaj.art-1acca80da60847a7b9b7a13e64bee9de |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-11T09:16:40Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-1acca80da60847a7b9b7a13e64bee9de2023-11-16T18:35:57ZengMDPI AGAgronomy2073-43952023-02-0113252810.3390/agronomy13020528Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral ImageryMaría Pilar Martín0Bernarda Ponce1Pilar Echavarría2José Dorado3Cesar Fernández-Quintanilla4Environmental Remote Sensing and Spectroscopy Laboratory (SpecLab), IEGD, Spanish National Research Council (CSIC), Albasanz 27-28, 28037 Madrid, SpainEnvironmental Remote Sensing and Spectroscopy Laboratory (SpecLab), IEGD, Spanish National Research Council (CSIC), Albasanz 27-28, 28037 Madrid, SpainEnvironmental Remote Sensing and Spectroscopy Laboratory (SpecLab), IEGD, Spanish National Research Council (CSIC), Albasanz 27-28, 28037 Madrid, SpainInstitute of Agricultural Sciences (ICA), Spanish National Research Council (CSIC), Serrano 115B, 28006 Madrid, SpainInstitute of Agricultural Sciences (ICA), Spanish National Research Council (CSIC), Serrano 115B, 28006 Madrid, SpainAccurate information on the spatial distribution of weeds is the key to effective site-specific weed management and the efficient and sustainable use of weed control measures. This work focuses on the early detection of johnsongrass, common cocklebur and velvetleaf present in a corn field using high resolution airborne hyperspectral imagery acquired when corn plants were in a four to six leaf growth stage. Following the appropriate radiometric and geometric corrections, two supervised classification techniques, such as spectral angle mapper (SAM) and spectral mixture analysis (SMA) were applied. Two different procedures were compared for endmember selections: field spectral measurements and automatic methods to identify pure pixels in the image. Maps for both, overall weeds and for each of the three weed species, were obtained with the different classification methods and endmember sources. The best results were achieved by defining the endmembers through spectral information collected with a field spectroradiometer. Overall accuracies ranged between 60% and 80% using SAM for maps that do not differentiate the weed species while it decreased to 52% when the three weed species were individually classified. In this case, the SMA classification technique clearly improved the SAM results. The proposed methodology shows it to be a promising prospect to be applicable to low cost images acquired by the new generation of hyperspectral sensors onboard unmanned aerial vehicles (UAVs).https://www.mdpi.com/2073-4395/13/2/528site-specific weed managementmaizeairborne hyperspectral imagesfield spectroscopyspectral angle mapper (SAM)spectral mixture analysis (SMA) |
| spellingShingle | María Pilar Martín Bernarda Ponce Pilar Echavarría José Dorado Cesar Fernández-Quintanilla Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery Agronomy site-specific weed management maize airborne hyperspectral images field spectroscopy spectral angle mapper (SAM) spectral mixture analysis (SMA) |
| title | Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery |
| title_full | Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery |
| title_fullStr | Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery |
| title_full_unstemmed | Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery |
| title_short | Early-Season Mapping of Johnsongrass (<i>Sorghum halepense</i>), Common Cocklebur (<i>Xanthium strumarium</i>) and Velvetleaf (<i>Abutilon theophrasti</i>) in Corn Fields Using Airborne Hyperspectral Imagery |
| title_sort | early season mapping of johnsongrass i sorghum halepense i common cocklebur i xanthium strumarium i and velvetleaf i abutilon theophrasti i in corn fields using airborne hyperspectral imagery |
| topic | site-specific weed management maize airborne hyperspectral images field spectroscopy spectral angle mapper (SAM) spectral mixture analysis (SMA) |
| url | https://www.mdpi.com/2073-4395/13/2/528 |
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