Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring
Sensing distance and speed have crucial effects on the data of active and passive sensors, providing valuable information relevant to crop growth monitoring and environmental conditions. The objective of this study was to evaluate the effects of sensing speed and sensor height on the variation in pr...
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MDPI AG
2025-02-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/15/3/618 |
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| author | Md Rejaul Karim Md Asrakul Haque Shahriar Ahmed Md Nasim Reza Kyung-Do Lee Yeong Ho Kang Sun-Ok Chung |
| author_facet | Md Rejaul Karim Md Asrakul Haque Shahriar Ahmed Md Nasim Reza Kyung-Do Lee Yeong Ho Kang Sun-Ok Chung |
| author_sort | Md Rejaul Karim |
| collection | DOAJ |
| description | Sensing distance and speed have crucial effects on the data of active and passive sensors, providing valuable information relevant to crop growth monitoring and environmental conditions. The objective of this study was to evaluate the effects of sensing speed and sensor height on the variation in proximal canopy reflectance data to improve rice vegetation monitoring. Data were collected from a rice field using active and passive sensors with calibration procedures including downwelling light sensor (DLS) calibration, field of view (FOV) alignment, and radiometric calibration, which were conducted per official guidelines. The data were collected at six sensor heights (30–130 cm) and speeds (0–0.5 ms<sup>–1</sup>). Analyses, including peak signal-to-noise ratio (PSNR) and normalized difference vegetation index (NDVI) calculations and statistical assessments, were conducted to explore the impacts of these parameters on reflectance data variation. PSNR analysis was performed on passive sensor image data to evaluate image data variation under varying data collection conditions. Statistical analysis was conducted to assess the effects of sensor speed and height on the NDVI derived from active and passive sensor data. The PSNR analysis confirmed that there were significant impacts on data variation for passive sensors, with the NIR and G bands showing higher noise sensitivity at increased speeds. The NDVI analysis showed consistent patterns at sensor heights of 70–110 cm and sensing speeds of 0–0.3 ms<sup>–1</sup>. Increased sensing speeds (0.4–0.5 ms<sup>–1</sup>) introduced motion-related variability, while lower heights (30–50 cm) heightened ground interference. An analysis of variance (ANOVA) indicated significant individual effects of speed and height on four spectral bands, red (R), green (G), blue (B), and near-infrared (NIR), in the passive sensor images, with non-significant interaction effects observed on the red edge (RE) band. The analysis revealed that sensing speed and sensor height influence NDVI reliability, with the configurations of 70–110 cm height and 0.1–0.3 ms<sup>–1</sup> speed ensuring the stability of NDVI measurements. This study notes the importance of optimizing sensor height and sensing speed for precise vegetation index calculations during field data acquisition for agricultural crop monitoring. |
| format | Article |
| id | doaj-art-a5ae44915cab4eeeb44eea1f565bfe37 |
| institution | OA Journals |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-02-01 |
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| series | Agronomy |
| spelling | doaj-art-a5ae44915cab4eeeb44eea1f565bfe372025-08-20T02:11:17ZengMDPI AGAgronomy2073-43952025-02-0115361810.3390/agronomy15030618Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation MonitoringMd Rejaul Karim0Md Asrakul Haque1Shahriar Ahmed2Md Nasim Reza3Kyung-Do Lee4Yeong Ho Kang5Sun-Ok Chung6Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of KoreaNational Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54875, Republic of KoreaJeollabuk-do Agriculture Research and Extension Services, Iksan 54591, Republic of KoreaDepartment of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of KoreaSensing distance and speed have crucial effects on the data of active and passive sensors, providing valuable information relevant to crop growth monitoring and environmental conditions. The objective of this study was to evaluate the effects of sensing speed and sensor height on the variation in proximal canopy reflectance data to improve rice vegetation monitoring. Data were collected from a rice field using active and passive sensors with calibration procedures including downwelling light sensor (DLS) calibration, field of view (FOV) alignment, and radiometric calibration, which were conducted per official guidelines. The data were collected at six sensor heights (30–130 cm) and speeds (0–0.5 ms<sup>–1</sup>). Analyses, including peak signal-to-noise ratio (PSNR) and normalized difference vegetation index (NDVI) calculations and statistical assessments, were conducted to explore the impacts of these parameters on reflectance data variation. PSNR analysis was performed on passive sensor image data to evaluate image data variation under varying data collection conditions. Statistical analysis was conducted to assess the effects of sensor speed and height on the NDVI derived from active and passive sensor data. The PSNR analysis confirmed that there were significant impacts on data variation for passive sensors, with the NIR and G bands showing higher noise sensitivity at increased speeds. The NDVI analysis showed consistent patterns at sensor heights of 70–110 cm and sensing speeds of 0–0.3 ms<sup>–1</sup>. Increased sensing speeds (0.4–0.5 ms<sup>–1</sup>) introduced motion-related variability, while lower heights (30–50 cm) heightened ground interference. An analysis of variance (ANOVA) indicated significant individual effects of speed and height on four spectral bands, red (R), green (G), blue (B), and near-infrared (NIR), in the passive sensor images, with non-significant interaction effects observed on the red edge (RE) band. The analysis revealed that sensing speed and sensor height influence NDVI reliability, with the configurations of 70–110 cm height and 0.1–0.3 ms<sup>–1</sup> speed ensuring the stability of NDVI measurements. This study notes the importance of optimizing sensor height and sensing speed for precise vegetation index calculations during field data acquisition for agricultural crop monitoring.https://www.mdpi.com/2073-4395/15/3/618precision agriculturecanopy sensorspatial resolutionradiometric calibrationNDVI |
| spellingShingle | Md Rejaul Karim Md Asrakul Haque Shahriar Ahmed Md Nasim Reza Kyung-Do Lee Yeong Ho Kang Sun-Ok Chung Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring Agronomy precision agriculture canopy sensor spatial resolution radiometric calibration NDVI |
| title | Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring |
| title_full | Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring |
| title_fullStr | Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring |
| title_full_unstemmed | Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring |
| title_short | Effects of Sensor Speed and Height on Proximal Canopy Reflectance Data Variation for Rice Vegetation Monitoring |
| title_sort | effects of sensor speed and height on proximal canopy reflectance data variation for rice vegetation monitoring |
| topic | precision agriculture canopy sensor spatial resolution radiometric calibration NDVI |
| url | https://www.mdpi.com/2073-4395/15/3/618 |
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