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Low-Cost Unmanned Aerial Multispectral Imagery for Siltation Monitoring in Reservoirs

Authors :
Diogo Olivetti
Henrique Roig
Jean-Michel Martinez
Henrique Borges
Alexandre Ferreira
Raphael Casari
Leandro Salles
Edio Malta
Source :
Remote Sensing, Vol 12, Iss 11, p 1855 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

The recent and continuous development of unmanned aerial vehicles (UAV) and small cameras with different spectral resolutions and imaging systems promotes new remote sensing platforms that can supply ultra-high spatial and temporal resolution, filling the gap between ground-based surveys and orbital sensors. This work aimed to monitor siltation in two large rural and urban reservoirs by recording water color variations within a savanna biome in the central region of Brazil using a low cost and very light unmanned platform. Airborne surveys were conducted using a Parrot Sequoia camera (~0.15 kg) onboard a DJI Phantom 4 UAV (~1.4 kg) during dry and rainy seasons over inlet areas of both reservoirs. Field measurements of total suspended solids (TSS) and water clarity were made jointly with the airborne survey campaigns. Field hyperspectral radiometry data were also collected during two field surveys. Bio-optical models for TSS were tested for all spectral bands of the Sequoia camera. The near-infrared single band was found to perform the best (R2: 0.94; RMSE: 7.8 mg Lāˆ’1) for a 0ā€“180 mg Lāˆ’1 TSS range and was used to produce time series of TSS concentration maps of the study areas. This flexible platform enabled monitoring of the increase of TSS concentration at a ~13 cm spatial resolution in urban and rural drainages in the rainy season. Aerial surveys allowed us to map TSS load fluctuations in a 1 week period during which no satellite images were available due to continuous cloud coverage in the rainy season. This work demonstrates that a low-cost configuration allows dense TSS monitoring at the inlet areas of reservoirs and thus enables mapping of the sources of sediment inputs, supporting the definition of mitigation plans to limit the siltation process.

Details

Language :
English
ISSN :
20724292
Volume :
12
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.2bdff8815341b8a57294b2442bcfc3
Document Type :
article
Full Text :
https://doi.org/10.3390/rs12111855