UAV aerial imaging applications for post-disaster assessment, environmental management and infrastructure development

Ezequiel, Carlos Alphonso F.; Cua, Matthew; Libatique, Nathaniel Joseph C.; Tangonan, Gregory L.; Alampay, Raphael; Labuguen, Rollyn; Favila, C. M.; Honrado, Jaime Luis E.; Canos, Vinni; Devaney, Charles; Loreto, Alan B.; Bacusmo, J. L.; Palma, Benny

doi:10.1109/icuas.2014.6842266

Cited by 152 publications

(96 citation statements)

References 15 publications

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“…They may also provide relevant information that is specific to critical infrastructure, transport systems, aid and reconstruction logistics, government and community buildings, hazard exposure, displaced population, etc. (Ezequiel et al, 2014). Concurrently, the availability of clear and straightforward raster and vector data, integrated with base cartographic contents (transportation, surface hydrology, boundaries, etc.)…”

Section: Discussionmentioning

confidence: 99%

“…The landslide impact extent is usually analysed based on detailed optical images acquired after the event. From these acquisitions, it is possible to derive digital elevation models (DEMs) and orthophotos that allow major changes to be detected in geomorphological figures (Fan et al, 2017;Chang et al, 2018). In this scenario, the use of the mini and micro RPASs is practical for small areas and optimal for landslides that often cover an area that ranges from less than one square kilometres up to few square kilometres.…”

Section: Landslidesmentioning

confidence: 99%

“…Török et al (2018) and Tannant et al (2017) also described in their papers how RPAS DSMs can be used for the evaluation of slope stability using numerical modelling. Fan et al (2017) analysed the geometrical features and provided the disaster assessment of a landslide that occurred on 24 June 2017 in the village of Xinmo in Maoxian County (Sichuan province, south-west China). Aerial images were acquired the day after the event from a UAV (fixed-wing UAV, with a weight less than 10 kg, and flight autonomy up to 4 h), and a DEM was processed, with the purpose to analysed the main landslide geometrical features (front, rear edge elevation, accumulation area, horizontal sliding distance).…”

Section: Landslide Susceptibility and Hazard Assessmentmentioning

confidence: 99%

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Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Giordan

Hayakawa

Nex

et al. 2018

Nat. Hazards Earth Syst. Sci.

145

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Abstract. The number of scientific studies that consider possible applications of remotely piloted aircraft systems (RPASs) for the management of natural hazards effects and the identification of occurred damages strongly increased in the last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of the literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPASs can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes such as landslides or volcanic activities but can also define the effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazards. IntroductionIn the last three decades, the number of natural disasters showed a positive trend with an increase in the number of affected populations. Disasters not only affected the poor and characteristically more vulnerable countries but also those thought to be better protected. The Annual Disaster Statistical Review describes recent impacts of natural disasters on the population and reports 342 naturally triggered disasters in 2016 (Guha-Sapir et al., 2017). This is less than the annual average disaster frequency observed from 2006 to 2015 (376.4 events). However, natural disasters are still responsible for a high number of casualties (8733 death). In the period 2006-2015, the average number of causalities caused annually by natural disasters is 69 827. In 2016, hydrological disasters (177) had the largest share in natural disaster occurrence (51.8 %), followed by meteorological disasters (96; 28.1 %), climatological disasters (38; 11.1 %) and geophysical disasters (31; 9.1 %) (Guha-Sapir et al., 2017). To face these disasters, one of the most important solutions is the use of systems able to provide an adequate level of information for correctly understanding these events and their evolution. In this context, surveying and monitoring natural hazards gained importance. In particular, during the emergency phase it is very important to evaluate and control the phenomenon of evolution, preferably operating in near real time or real time, and consequently, use this information for a better risk assessment scenario. The available acquired data must be processed rapidly to support the emergency services and decision makers.Recently, the use of remote sensing (satellite and airborne platform) in the field of natural hazards and disasters has become common, also supported by the increase in geospatial technologies and the ability to provide and process up-to-date imagery (Joyce et al., 2009;Tarolli, 2014). Remotely sensed data play an integral role in predicting hazard events such as floods and landslides, subsidence events and other ground instabilities. Because of their acquisition mode and capabilPublished by Copern...

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Section: Discussionmentioning

confidence: 99%

Section: Landslidesmentioning

confidence: 99%

Section: Landslide Susceptibility and Hazard Assessmentmentioning

confidence: 99%

See 1 more Smart Citation

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Giordan

Hayakawa

Nex

et al. 2018

Nat. Hazards Earth Syst. Sci.

145

View full text Add to dashboard Cite

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“…In the context of disaster management, high-resolution photos and videos taken by UAVs can help in the development of strategies for dealing with emergencies (Ezequiel et al, 2014;Erdelj and Natalizio, 2016). Another UAV "eye", namely, topographic data obtained by SfM photogrammetry, can also be informative, particularly if acquired immediately after the occurrence of a disaster.…”

Section: Recording Of Landforms With Low Preservation Potential By Usmentioning

confidence: 99%

Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

Izumida

Uchiyama

Sugai

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10 −1 m -including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works -were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300-500 m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.

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“…Techniques for collecting remote sensing data are becoming more feasible due to the emergence of new carrier platforms and imaging sensors such as unmanned aerial vehicles (UAVs) and lightweight hyperspectral cameras. UAVs are being increasingly employed in fields such as agriculture, environmental monitoring, topographic cartography, military reconnaissance, geological prospecting, grassland monitoring and urban planning [8][9][10][11][12][13]. UAVs are becoming a competitive platform for remote sensing-based precision agriculture because they can be easily and cost-effectively deployed to acquire geospatial data with high temporal and spatial resolutions [14].…”

Section: Introductionmentioning

confidence: 99%

The DOM Generation and Precise Radiometric Calibration of a UAV-Mounted Miniature Snapshot Hyperspectral Imager

Yang

Wang

et al. 2017

Remote Sensing

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Abstract:Hyperspectral remote sensing is used in precision agriculture to remotely and quickly acquire crop phenotype information. This paper describes the generation of a digital orthophoto map (DOM) and radiometric calibration for images taken by a miniaturized snapshot hyperspectral camera mounted on a lightweight unmanned aerial vehicle (UAV). The snapshot camera is a relatively new type of hyperspectral sensor that can acquire an image cube with one spectral and two spatial dimensions at one exposure. The images acquired by the hyperspectral snapshot camera need to be mosaicked together to produce a DOM and radiometrically calibrated before analysis. However, the spatial resolution of hyperspectral cubes is too low to mosaic the images together. Furthermore, there are no systematic radiometric calibration methods or procedures for snapshot hyperspectral images acquired from low-altitude carrier platforms. In this study, we obtained hyperspectral imagery using a snapshot hyperspectral sensor mounted on a UAV. We quantitatively evaluated the radiometric response linearity (RRL) and radiometric response variation (RRV) and proposed a method to correct the RRV effect. We then introduced a method to interpolate position and orientation system (POS) information and generate a DOM with low spatial resolution and a digital elevation model (DEM) using a 3D mesh model built from panchromatic images with high spatial resolution. The relative horizontal geometric precision of the DOM was validated by comparison with a DOM generated from a digital RGB camera. A surface crop model (CSM) was produced from the DEM, and crop height for 48 sampling plots was extracted and compared with the corresponding field-measured crop height to verify the relative precision of the DEM. Finally, we applied two absolute radiometric calibration methods to the generated DOM and verified their accuracy via comparison with spectra measured with an ASD Field Spec Pro spectrometer (Analytical Spectral Devices, Boulder, CO, USA). The DOM had high relative horizontal accuracy, and compared with the digital camera-derived DOM, spatial differences were below 0.05 m (RMSE = 0.035). The determination coefficient for a regression between DEM-derived and field-measured crop height was 0.680. The radiometric precision was 5% for bands between 500 and 945 nm, and the reflectance curve in the infrared spectral region did not decrease as in previous research. The pixel and data sizes for the DOM corresponding to a field area of approximately 85 m × 34 m were small (0.67 m and approximately 13.1 megabytes, respectively), which is convenient for data transmission, preprocessing and analysis. The proposed Remote Sens. 2017, 9, 642; doi:10.3390/rs9070642 www.mdpi.com/journal/remotesensing Remote Sens. 2017, 9, 642 2 of 21 method for radiometric calibration and DOM generation from hyperspectral cubes can be used to yield hyperspectral imagery products for various applications, particularly precision agriculture.

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UAV aerial imaging applications for post-disaster assessment, environmental management and infrastructure development

Cited by 152 publications

References 15 publications

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

The DOM Generation and Precise Radiometric Calibration of a UAV-Mounted Miniature Snapshot Hyperspectral Imager

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