Improved Accuracy of Riparian Zone Mapping Using Near Ground Unmanned Aerial Vehicle and Photogrammetry Method
| Autor: | Fan-Rui Meng, Paul A. Arp, Kang Liang, Joan Grau, Bonnie Robertson, Jae Ogilvie, Sheng Li |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Agricultural watershed
Channel network LiDAR 010504 meteorology & atmospheric sciences UAV Science 0208 environmental biotechnology 02 engineering and technology 01 natural sciences riparian zone mapping Digital elevation model 0105 earth and related environmental sciences Remote sensing Riparian zone geography geography.geographical_feature_category VDTCN DEM 020801 environmental engineering Photogrammetry Lidar General Earth and Planetary Sciences Environmental science Precision agriculture Digital surface |
| Zdroj: | Remote Sensing; Volume 13; Issue 10; Pages: 1997 Remote Sensing, Vol 13, Iss 1997, p 1997 (2021) |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs13101997 |
| Popis: | In agriculture-dominant watersheds, riparian ecosystems provide a wide array of benefits such as reducing soil erosion, filtering chemical compounds, and retaining sediments. Traditionally, the boundaries of riparian zones could be estimated from Digital Elevation Models (DEMs) or field surveys. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to map the boundaries of riparian zones. We first obtained the 3D digital surface model with a UAV. We applied the Vertical Distance to Channel Network (VDTCN) as a classifier to delineate the boundaries of the riparian area in an agricultural watershed. The same method was also used with a low-resolution DEM obtained with traditional photogrammetry and two more LiDAR-derived DEMs, and the results of different methods were compared. Results indicated that higher resolution UAV-derived DEM achieved a high agreement with the field-measured riparian zone. The accuracy achieved (Kappa Coefficient, KC = 63%) with the UAV-derived DEM was comparable with high-resolution LiDAR-derived DEMs and significantly higher than the prediction accuracy based on traditional low-resolution DEMs obtained with high altitude aerial photos (KC = 25%). We also found that the presence of a dense herbaceous layer on the ground could cause errors in riparian zone delineation with VDTCN for both low altitude UAV and LiDAR data. Nevertheless, the study indicated that using the VDTCN as a classifier combined with a UAV-derived DEM is a suitable approach for mapping riparian zones and can be used for precision agriculture and environmental protection over agricultural landscapes. |
| Databáze: | OpenAIRE |
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