Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image
Vegetation has become very important decision-making information in promoting tasks such as urban regeneration, urban planning, environment, and landscaping. In the past, the vegetation index was calculated by combining images of various wavelength regions mainly acquired from the Landsat satellite’...
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| Format: | Article |
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MDPI AG
2022-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/1/515 |
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| author | Geunsang Lee Gyeonggyu Kim Gyeongjo Min Minju Kim Seunghyun Jung Jeewook Hwang Sangho Cho |
| author_facet | Geunsang Lee Gyeonggyu Kim Gyeongjo Min Minju Kim Seunghyun Jung Jeewook Hwang Sangho Cho |
| author_sort | Geunsang Lee |
| collection | DOAJ |
| description | Vegetation has become very important decision-making information in promoting tasks such as urban regeneration, urban planning, environment, and landscaping. In the past, the vegetation index was calculated by combining images of various wavelength regions mainly acquired from the Landsat satellite’s TM or ETM+ sensor. Recently, a technology using UAV-based multispectral images has been developed to obtain more rapid and precise vegetation information. NDVI is a method of calculating the vegetation index by combining the red and near-infrared bands, and is currently the most widely used. In this study, NDVI was calculated using UAV-based multispectral images to classify vegetation. However, among the areas analyzed using NDVI, there was a problem that areas coated with urethane, such as basketball courts and waterproof coating roofs, were classified as vegetation areas. In order to examine these problems, the reflectance of each land cover was investigated using the ASD FieldSpec4 spectrometer. As a result of analyzing the spectrometer measurements, the NDVI values of basketball courts and waterproof coating roofs were similar to those of grass with slightly lower vegetation. To solve this problem, the temperature characteristics of the target site were analyzed using UAV-based thermal infrared images, and vegetation area was analyzed by combining the temperature information with NDVI. To evaluate the accuracy of the vegetation classification technology, 4409 verification points were selected, and kappa coefficients were analyzed for the method using only NDVI and the method using NDVI and thermal infrared images. Compared to the kappa coefficient of 0.830, which was analyzed by applying only NDVI, the kappa coefficient, which was analyzed by combining NDVI and thermal infrared images, was 0.934, which was higher. Therefore, it is very effective to apply a technology that classifies vegetation by combining NDVI and thermal infrared images in urban areas with many urethane-coated land cover such as basketball courts or waterproof coating roofs. |
| first_indexed | 2024-03-11T10:07:49Z |
| format | Article |
| id | doaj.art-62d9973b29a04b929f00b1e11b74352b |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:07:49Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-62d9973b29a04b929f00b1e11b74352b2023-11-16T14:58:06ZengMDPI AGApplied Sciences2076-34172022-12-0113151510.3390/app13010515Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared ImageGeunsang Lee0Gyeonggyu Kim1Gyeongjo Min2Minju Kim3Seunghyun Jung4Jeewook Hwang5Sangho Cho6Department of Cadastre & Civil Engineering, Vision College of Jeonju, Jeonju 54896, Republic of KoreaDepartment of Mineral Resources and Energy Engineering, Jeonbuk National University, Jeonju 54896, Republic of KoreaDepartment of Mineral Resources and Energy Engineering, Jeonbuk National University, Jeonju 54896, Republic of KoreaKorea Institute of Civil Engineering and Building Technology, Gyeonggi-do 10223, Republic of KoreaKorea Institute of Civil Engineering and Building Technology, Gyeonggi-do 10223, Republic of KoreaDepartment of Urban Engineering, Jeonbuk National Unviersity, Jeonju 54896, Republic of KoreaDepartment of Mineral Resources and Energy Engineering, Jeonbuk National University, Jeonju 54896, Republic of KoreaVegetation has become very important decision-making information in promoting tasks such as urban regeneration, urban planning, environment, and landscaping. In the past, the vegetation index was calculated by combining images of various wavelength regions mainly acquired from the Landsat satellite’s TM or ETM+ sensor. Recently, a technology using UAV-based multispectral images has been developed to obtain more rapid and precise vegetation information. NDVI is a method of calculating the vegetation index by combining the red and near-infrared bands, and is currently the most widely used. In this study, NDVI was calculated using UAV-based multispectral images to classify vegetation. However, among the areas analyzed using NDVI, there was a problem that areas coated with urethane, such as basketball courts and waterproof coating roofs, were classified as vegetation areas. In order to examine these problems, the reflectance of each land cover was investigated using the ASD FieldSpec4 spectrometer. As a result of analyzing the spectrometer measurements, the NDVI values of basketball courts and waterproof coating roofs were similar to those of grass with slightly lower vegetation. To solve this problem, the temperature characteristics of the target site were analyzed using UAV-based thermal infrared images, and vegetation area was analyzed by combining the temperature information with NDVI. To evaluate the accuracy of the vegetation classification technology, 4409 verification points were selected, and kappa coefficients were analyzed for the method using only NDVI and the method using NDVI and thermal infrared images. Compared to the kappa coefficient of 0.830, which was analyzed by applying only NDVI, the kappa coefficient, which was analyzed by combining NDVI and thermal infrared images, was 0.934, which was higher. Therefore, it is very effective to apply a technology that classifies vegetation by combining NDVI and thermal infrared images in urban areas with many urethane-coated land cover such as basketball courts or waterproof coating roofs.https://www.mdpi.com/2076-3417/13/1/515vegetation indexUAVmultispectral imagethermal infrared imagespectrometer |
| spellingShingle | Geunsang Lee Gyeonggyu Kim Gyeongjo Min Minju Kim Seunghyun Jung Jeewook Hwang Sangho Cho Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image Applied Sciences vegetation index UAV multispectral image thermal infrared image spectrometer |
| title | Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image |
| title_full | Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image |
| title_fullStr | Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image |
| title_full_unstemmed | Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image |
| title_short | Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image |
| title_sort | vegetation classification in urban areas by combining uav based ndvi and thermal infrared image |
| topic | vegetation index UAV multispectral image thermal infrared image spectrometer |
| url | https://www.mdpi.com/2076-3417/13/1/515 |
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