High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion

Unmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of <i>Suaeda salsa</i> using UAV-based visible-...

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Main Authors: Lin Wang, Xiang Wang, Xiu Su, Shiyong Wen, Xinxin Wang, Qinghui Meng, Lingling Jiang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/13/7423
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author Lin Wang
Xiang Wang
Xiu Su
Shiyong Wen
Xinxin Wang
Qinghui Meng
Lingling Jiang
author_facet Lin Wang
Xiang Wang
Xiu Su
Shiyong Wen
Xinxin Wang
Qinghui Meng
Lingling Jiang
author_sort Lin Wang
collection DOAJ
description Unmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of <i>Suaeda salsa</i> using UAV-based visible-light imagery combined with hue angle inversion modeling. By integrating diffuse reflectance standard plates into the flight protocol, we converted RGB pixel values into reflectance and derived hue angle metrics with enhanced radiometric accuracy. A hue angle cutoff threshold of 249.01° was identified as the optimal cutoff to distinguish <i>Suaeda salsa</i> from the surrounding land cover types with high confidence. To estimate biomass, we developed an exponential inversion model based on hue angle data calibrated through extensive field measurements. The resulting model—Biomass = 3.57639 × 10<sup>−15</sup> × e<sup>0.12201×α</sup>—achieved exceptional performance (<i>R</i><sup>2</sup> = 0.99696; MAPE = 3.616%; RMSE = 0.02183 kg/m<sup>2</sup>), indicating strong predictive accuracy and robustness. This study highlights a cost-effective, non-destructive, and scalable method for the real-time monitoring of coastal vegetation, offering a significant advancement in remote sensing applications for wetland ecosystem management.
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institution Kabale University
issn 2076-3417
language English
publishDate 2025-07-01
publisher MDPI AG
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series Applied Sciences
spelling doaj-art-3b4e88da8c1d4ee8ba5ed87609bc90f52025-08-20T03:28:25ZengMDPI AGApplied Sciences2076-34172025-07-011513742310.3390/app15137423High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle InversionLin Wang0Xiang Wang1Xiu Su2Shiyong Wen3Xinxin Wang4Qinghui Meng5Lingling Jiang6National Marine Environmental Monitoring Center, Dalian 116023, ChinaNational Marine Environmental Monitoring Center, Dalian 116023, ChinaNational Marine Environmental Monitoring Center, Dalian 116023, ChinaNational Marine Environmental Monitoring Center, Dalian 116023, ChinaNational Marine Environmental Monitoring Center, Dalian 116023, ChinaNational Marine Environmental Monitoring Center, Dalian 116023, ChinaCollege of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, ChinaUnmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of <i>Suaeda salsa</i> using UAV-based visible-light imagery combined with hue angle inversion modeling. By integrating diffuse reflectance standard plates into the flight protocol, we converted RGB pixel values into reflectance and derived hue angle metrics with enhanced radiometric accuracy. A hue angle cutoff threshold of 249.01° was identified as the optimal cutoff to distinguish <i>Suaeda salsa</i> from the surrounding land cover types with high confidence. To estimate biomass, we developed an exponential inversion model based on hue angle data calibrated through extensive field measurements. The resulting model—Biomass = 3.57639 × 10<sup>−15</sup> × e<sup>0.12201×α</sup>—achieved exceptional performance (<i>R</i><sup>2</sup> = 0.99696; MAPE = 3.616%; RMSE = 0.02183 kg/m<sup>2</sup>), indicating strong predictive accuracy and robustness. This study highlights a cost-effective, non-destructive, and scalable method for the real-time monitoring of coastal vegetation, offering a significant advancement in remote sensing applications for wetland ecosystem management.https://www.mdpi.com/2076-3417/15/13/7423remote sensing inversion<i>Suaeda salsa</i> biomassUAV imageryhue angle
spellingShingle Lin Wang
Xiang Wang
Xiu Su
Shiyong Wen
Xinxin Wang
Qinghui Meng
Lingling Jiang
High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion
Applied Sciences
remote sensing inversion
<i>Suaeda salsa</i> biomass
UAV imagery
hue angle
title High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion
title_full High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion
title_fullStr High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion
title_full_unstemmed High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion
title_short High-Resolution Mapping and Biomass Estimation of <i>Suaeda salsa</i> in Coastal Wetlands Using UAV Visible-Light Imagery and Hue Angle Inversion
title_sort high resolution mapping and biomass estimation of i suaeda salsa i in coastal wetlands using uav visible light imagery and hue angle inversion
topic remote sensing inversion
<i>Suaeda salsa</i> biomass
UAV imagery
hue angle
url https://www.mdpi.com/2076-3417/15/13/7423
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