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Background: Monitoring coastal erosion and flooding in deltaic environment is a major challenge. The uncertainties associated with land based methods and remote sensing approaches affect the levels of accuracy, reliability and usability of the output maps generated. This study monitored flooding and erosion activities in a flood prone fishing community (Fuvemeh) in the Volta Delta in Ghana using Unmanned Aerial Vehicles (UAVs) or drone technology. Results: The study revealed that coastal flooding and coastal erosion have destroyed sources of livelihood and increased risk to life and property in the Volta Delta communities. It was identified that between 2005 and 2017 the shoreline has moved several meters inland (over 100 m along some transects) in some areas, while in other areas about 24,057 m land has been gained (about 80 m along some transects) that can serve as natural fish landing site. It emerged that over 77 houses have been destroyed which resulted in the displacement of over 300 inhabitants between 2005 and 2017. The study estimated that about 37% of the total land area in Fuvemeh has been lost as a result of erosion. Conclusion: Coastal erosion and flooding are major environmental challenges in the Volta delta. Coastal erosion has destroyed natural fish landing sites, which has affected the local fishing business (the main source of livelihood) and increased poverty. Coastal flooding has displaced inhabitants from their homes and increased migration from the Fuvemeh community. Keywords: Volta Delta, Flooding, Drone, Unmanned aerial vehicle (UAV), Coastal Erosion, Coastal monitoring Background environment to detect and measure change in the shore- Delta environment is dynamic, highly vulnerable and chal- line morphology (Appeaning Addo et al. 2008). The re- lenged due to adverse impacts of flooding probably as a re- mote sensing approach includes aerial photographs, sult of relative sea level rise, extreme oceanic wave actions, satellite imagery, airborne light detection and ranging and subsidence or anthropogenic impact such as dam con- technology (LIDAR), and video technique. struction etc. (Ericson et al. 2006;Wong et al. 2014; The land based methods and the remote sensing ap- Appeaning Addo 2015). Variety of methods that differ in proaches have their strengths and weaknesses, which approach, accuracy, cost and duration have been devel- can affect their levels of accuracy, the reliability of the oped to meet the demand for higher accuracy in delta en- output maps generated and their usability. These vironment monitoring (Appeaning Addo et al. 2008). strengths and weaknesses have been discussed exten- These methods can broadly be categorized as in-situ sively in the literature (see Basha et al. 2008; Kussul (physical surveying) method and remote sensing approach. et al. 2008; Matgen et al. 2011;Turner et al., 2016). The physical surveying method has resulted in the Selecting a particular method for monitoring is therefore production of historical maps at varying scales, which influenced by several factors such as the type of feature can be combined with recent information on the delta to be monitored, the accuracy required, availability of funding, type of output desired, the intended use of the * Correspondence: firstname.lastname@example.org results and geographical location (Dolan et al. 1991; Department of Marine and Fisheries Sciences, College of Basic and Applied Klemas 2015). Sciences, University of Ghana, P. O. Box Lg 99, Legon, Accra, Ghana Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 2 of 13 Physical surveying generated historic maps detailed helps in complex coastal environmental disaster moni- the mapped position of physical features influenced by toring (Whitehead and Hugenholtz 2014; Wallace et al. flooding overtime as estimated on site by a land sur- 2012). Datasets produced by drone have high resolution veyor. Such maps provide accurate information for (< 10 cm) (Harwin and Lucieer 2012) and supports the change detection as the surveyor is physically present development of high resolution digital elevation models during the data collection period (Graham et al. 2003; (DEMs) that facilitate change detection and measure- Leatherman et al. 2005). However, the approach tends to ment (Hugenholtz et al. 2013). Drone based monitoring be limited both spatially and temporally due to several of disaster events has significant advantages due to its factors (Morton 1991; Smith and Jackson 1992). The timeliness, event based rapid availability and better qual- method is time consuming, expensive and impractical ity/resolution (Pérez-Alberti and Trenhaile 2015). for long distance mapping (Leatherman et al. 2005). It is Drones are also being used in advocacy to booster com- also associated with human errors that can affect its reli- munity awareness in various environmental hazards, in- ability (Appeaning Addo et al. 2008). Aerial photographs cluding deforestation and bush fires and as a are the most commonly used data source in coastal en- communication tool in stakeholder engagement at vari- vironment monitoring (Moore 2000). In addition to hav- ous levels (Goldberg et al. 2013; Mohammed et al. ing the ability for stereo pair mapping, they also provide 2014). Appeaning Addo (2016) used drone video record- good spatial coverage (Lane et al. 2001). However, tem- ings to communicate erosion dynamics and flood prob- poral coverage is very site specific and the process of ac- lems to policy makers in Ghana (parliamentarian and quiring the near vertical photographs as well as the local authorities), which influenced their perception laborious field preparation can be expensive (Whitehead about these problems (Owens 2016). The use of drone is et al. 2014; Darwin et al. 2013). This short coming af- therefore the best way in data gathering to arm decision fects the repeatability of the monitoring process. makers and local authorities with more accurate picture Satellite imagery approach covers large area and pro- of environmental impacts (STAFF AG 2017). vides detailed spectral information (Boak and Turner A major challenge to the operation of drone in the 2005) as well as very high resolution (< 1 m) satellite coastal environment of delta regions is the presence of data (Ford 2013).Satellites have short revisit time, pro- strong winds (Gonçalves and Henriques 2015). Flights vide multi-spectral data and have the capability for ste- are therefore limited to specific times to reduce the im- reo pair mapping. However, they are affected by cloud pact of strong winds. Other challenges include platform coverage, dust during image acquisition, pixel reso- instability, view angle, data processing tools and short lution and operational cost (Whitehead et al. 2014; flight times due to battery constraints (Elaksher et al. Darwin et al. 2013). 2017). This paper presents the application of drones in LIDAR has the ability to cover hundreds of kilome- flood monitoring in the Volta Delta in Ghana and sets ters of coastal area in a relatively short period and pro- up agenda for further studies in the Volta Delta. The duce extremely dense and accurate elevation drone technology was adopted for this study due to its measurements (Stockdon et al. 2002). It is limited in advantages over the other methods, which will ensure its temporal and spatial availability because of cost repeated flood monitoring activity in the Volta Delta (Boak and Turner 2005). Digital video imaging also has environment. the capability to monitor detailed changes in the Flooding frequency and coastal erosion intensity as a coastal systems (Boak and Turner 2005)and record result of intensive rainfall, oceanographic conditions flooding events in real-time. It also has the ability to (waves, sea level rise and tides) and human activities collect both time-averaged and instantaneous images (watershed management) has increased in frequency (Angnuureng et al. 2016). Thesensorhas afixed loca- and impact in the Volta Delta significantly. Construc- tion and a fixed area of coverage that makes it unsuit- tion of the Akosombo dam on the Volta River has been able for wider coverage monitoring. identified as a major cause of erosion and flooding Recent developments have resulted in the use of problems in the Volta Delta region. Runoff before dam Unmanned Aerial Vehicles (UAVs) also known as drones construction was higher (87.5 mm/yr) and more varied in delta environment monitoring (Mancini et al. 2013; than the post-dam period with value of 73.5 mm/yr. Klemas 2015). This is due to the relatively low cost of (Oguntunde et al. 2006). The dam construction (com- operation that allows for frequent missions, increased pleted in 1965) has resulted in controlled water flow, spatial coverage, no required installation points, rapid which has changed the natural flooding of the area deployment, better quality outputs (Vousdoukas et al. (Corcoran et al. 2007), although periodic high flooding 2011) and as a tool for effective communication. The from the tidal waves persist. The yearly sediment ability of drones to perform missions and acquire data transport before the dam construction was about 7.5 autonomously as well as its maneuverability capacity million m /s (Bollen et al. 2011). Since the Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 3 of 13 construction of the dam, there are no peaks in flow Study area discharge and the sediment transport is reduced to The Volta Delta is located in the eastern coast of 0 0 only a fraction of the original transport (Bollen et al. Ghana within latitudes 5 25′ and 6 20’ North and lon- 0 0 2011). It is estimated that coastal erosion and flood- gitude 0 40′ and 1 10′ East (Fig. 1). The delta is de- ing have destroyed about 5000 houses since the fined as the land below the 5 m contour in the lower 1960s, displaced households, destroyed sources of portion of the Volta river basin within the livelihoods and forced migration within and out of Accra-Ho-Keta Plains (Appeaning Addo et al. 2018). the Delta (Boateng 2009;Karley 2009;Lumor 2015). Nine administrative districts that are responsible for Though riverine flooding occurs and particularly dur- managing resources in the Delta region are located ing the dam spillage, tidal flooding is dominant along wholly or partially in the Volta Delta. The delta is char- the coastline of the Delta. The last reported Dam acterised by a fairly uniform, moderately steep shore- spillage was in November 2010 (Owusu and Waylen face with a gradient of between 1:120 and 1:150 down 2013) which cause flooding in communities along the to 15 m, which is considered as the close-out depth for river. However, tidal flooding in the Delta is on the significant wave-induced sediment movement on this increase as observed by previous reports (Bokpe 2010; coast (Rossi 1989; Anthony 2015). The wave climate in Fagotto 2016). the region consists of swell waves from south-west dir- ection (Angnuureng et al. 2013). The average signifi- cantwaveheightisabout1.4 m(Wellens-Mensah et Application of drone in coastal zone monitoring al. 2002) while the annual maximum are around 2.5 – Several studies have applied the drone technology in 3m (Roest 2018). Some variability in the wave climate coastal environmental monitoring and achieved reliable is present over the year. The highest waves occur from results. The drone technic has been applied in tidal stud- July to August, while the lowest waves occur around ies (Chabot and Bird 2014; Klemas 2015), wave run-up January and February (Roest 2018). The tidal regime is and coastal morphological change modelling studies semi-diurnal with a tidal range of about 1 m (Well- (Casella et al. 2014) as well as bathymetric work ens-Mensah et al. 2002). The tidal currents are weak (Delacourt et al. 2009). Harwin and Lucieer (2012) and their impact on the shoreline morphology is lim- assessed the accuracy of drone by comparing the results ited (Wellens-Mensah et al. 2002). Although the envir- with differential GPS and total station surveys. The onment is microtidal, a study by Angnuureng et al. study concluded that drone has high accuracy in coastal (2016) identified that short term evolution of the monitoring. Vousdoukas et al. (2011) compared the re- shoreline is affected by tidal cycles from neap to sults of drone generated high quality time average im- spring. Presently, the sea level is rising at a rate of ages with images from satellite and video system, and about 3.1 mm/yr. (Sagoe-Addy and Appeaning Addo concluded that drone has advantages over satellite and 2013). The sea level is predicted to continue rising in video system since it allows increased spatial coverage conformity to the global trend (Armah et al. 2005). and a more favorable vantage point, as well as portability The basic winds along the study area are southwest and rapid deployment. monsoon. It blows from the south-west direction Drone technique was used to acquire images of Aguda (210°-240°) from the sea to land at about 45° angle to and Cabedelo in Portugal with ground resolution better the coast and it is approximately in the same direction than 5 cm and processed to achieve digital surface with the waves (Angnuureng et al. 2013). During the models with vertical accuracy ranging from 3.5 cm to Harmattan season (December–February) winds 5 cm (Gonçalves and Henriques 2015). The accuracy occasionally blow from the northwest. The monthly achieved out matched the accuracies obtained from average wind speed ranges between 1.7 and 2.6 m/s previous conventional aerial photography method (Angnuureng et al. 2013). (Gonçalves and Henriques 2015). According to Klemas Several studies have identified the Volta Delta as (2015), digital elevation model (DEM) products from coastal erosion and flooding hotspot (Boateng 2012; drones satisfy the resolutions mostly required for coastal Jayson-Quashigah et al. 2013; Appeaning Addo 2015). environment applications. in another study, Mancini et One community that suffered huge destruction of prop- al. (2013) compared data from drone point cloud, terres- erties and displacement of households as a result of trial laser scanner (TLS) and Global Navigation Satellite coastal flooding and erosion is Fuvemeh, a fishing com- System (GNSS) survey and concluded that the results munity with over 1,500 inhabitants (see Fig. 1). The compare favourably (see also Chikhradze et al. 2015; problems associated with the flooding incidents in the Hackney and Clayton 2015). These studies have revealed community require scientifically measured and reliable drones extensive work flow and confirmed its accuracy information to aid in effective management and develop- as a tool for delta environment monitoring. ing a resilient community. Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 4 of 13 Fig. 1 Map of the Volta Delta Region in Ghana showing the administration districts, the 5 m contour and Fuvemeh (adapted and modified from Appeaning Addo et al. 2018) Methods region from 1986 to 2015. The recorded number of Rainfall data was obtained from Ghana Meteorological people displaced and buildings collapsed by flooding Agency (GMet) in Accra. Data on impact of flooding on were between the periods 2008 and 2014. people and buildings in the Keta environ within the Orthophoto map of 2005 (0.5 m ground resolution) and Volta Delta region was obtained from the Ghana satellite imagery of 2014 (1.0 m ground resolution) were National Disaster Management Organisation (NADMO) obtained from the Survey and Mapping Division in Ghana in Keta. The data were used to analyse the rainfall trend and Digital Globe Foundation respectively for the Fuve- in the region, frequency of human displacement and meh community. A DJI Phantom 3 drone was used to building collapsing as a result of flooding in the delta re- obtain aerial photographs (0.06 m ground resolution) of gion. The rainfall data included recorded rainfall ob- Fuvemeh community in February 2016 with repeated tained from rain gauge station in Akatsi in the delta surveys in August 2016 and June 2017. Appeaning Addo Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 5 of 13 et al. (2008) validated the 2005 orthophoto map and con- varying intensity, which displaced over 2,000 people and cluded that the map is accurate and reliable. The ortho- destroyed about 306 buildings (Fig. 2). photo map was therefore adopted as reference and used It can be seen from Fig. 2 that between 2008 and 2014, to validate the satellite imageries and the drone aerial pho- several people were displaced by flooding event and sig- tographs by checking the positional accuracies of selected nificant number of houses were also destroyed. The high- features (5 buildings). The coordinates of the features on est number of displaced people (685) occurred in 2011, the satellite imageries and the drone pictures matched while the lowest number occurred in 2013. The highest their conjugate coordinates on the orthophoto maps. This number of houses (90) were destroyed in 2008 and the gave confidence in using the data for the study. lowest number of houses (5) were lost in 2013. The high The shoreline positions, represented by the High destruction of houses in 2008 can be attributed to storm Water Line (HWL) as proxy were mapped and appended surge which flooded the coastal zone in the delta region in GIS environment to detect and measure change (Ghanaweb 2008) and flooding from rainfall. The severe within the period under study. The Digital Shoreline flood experienced in 2011 was due to heavy rains that Analysis System (DSAS) software developed by Thieler caused rivers to overflow their banks (Duodu 2011). Ana- et al. (2017) was used to analyse the shoreline changing lysis of the rain gauge recorded data is presented in Fig. 3, trends along equally spaced perpendicular transects which shows the annual rainfall distribution pattern and along the coast. The transect intervals were set at 50 m the general trend in Akatsi as per the linear trend line. It to enable more areas to be covered in the rates of can be seen that between 1986 and 2015 the area recorded change estimation. The average rates of erosion were substantial amount of rainfall that resulted in flooding in statistically estimated using the end point rate of change some areas. The graph in Fig. 3 shows that 1986 to 1995 method (EPR). The EPR was adopted because it is the had mean rainfall value of 780.76 mm, from 1996 to 2015 most commonly used method to compute shoreline rate the rainfall value was 960.17 mm and then from 2006 to of change (Genz et al. 2007). The method is simple and 2015 the mean rainfall average was 818.67 mm. There was requires only two shoreline positions to obtain a rate of increasing trend from the first decade to the second dec- change. It calculates the rate of change by dividing the ade of 1996 to 2005 and the trend decreased from the sec- distance of shoreline movement by the time elapsed be- ond decade of 1996 to 2005 and the third decade of 2006 tween the earliest and the latest measurement, which to 2015. The general trend indicates increasing rainfall can be the oldest and the most recent shoreline posi- pattern in the delta region. Comparing Figs. 3 and 4 from tions (Crowell et al. 2005). 2008 and 2014, which falls within the 3rd decade, the dec- adal trend reduced similar to the significant reduced building destruction and displaced people, inferring re- Results duced flooding events. Analysis of data obtained from NADMO revealed that Analysis of the shoreline change using the 2005 ortho- several areas in the delta region are experiencing flood- photos and 2017 drone images shows that the shoreline ing problems. In all, 28 flooding events were recorded at has moved inland several meters (about 100 m in some Fig. 2 The number of people affected and buildings destroyed in Keta area between 2008 and 2014 (Data source: NADMO office) Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 6 of 13 Fig. 3 Annual Rainfall (distribution) in Akatsi with the general and decadal trend lines (Data source GMet) instances) along some perpendicular transects, while Figure 7 shows the remains of the school building in along some transects land has been gained (about 80 m May 2016 (A) and June 2016 (B) respectively. in some instance) as can be seen in Fig. 4. Figure 8 shows drone image of the flooding event in the The shoreline migration trend analysis also revealed that community captured on 9th February 2016. The energetic out of a total area of about 375,229 m ,about wave action, which were larger than the usual waves in 138,118.239 m of it has been lost as a result of erosion, the area, was aided by high tides and the prevailing rela- which represent about 37% of the total land area. A total tively low topography, which is below 2 m above sea level of about 77 houses have been destroyed by erosion be- (Boateng 2009) to break closer to the community and thus tween 2005 and 2017, which is about 42% of the total flood the Fuvemeh community. Figure 9 shows the devas- houses in the Fuvemeh community. The destruction of tating effect of the flood water on dwellings places (build- the houses have resulted in the displacement of over 300 ing labelled A) and sources of livelihood (labelled B). inhabitants in the Fuvemeh community. Figure 5 shows The swash of the waves deposit debris onto the houses that have been lost between 2005 and 2017. Strong beaches, while the strong backwash carries proper- erosion as result of natural processes (e.g. sea level rise, ties of the inhabitants into the sea. The inhabitants storm surge, energetic swell waves, subsidence, etc.) and have to salvage their properties and carry them to anthropogenic activities (dam construction, sand mining, safe places (Fig. 10). Occupants of such flooded over harvesting of mangroves, etc.) has damaged proper- houses abandon the buildings and either stay with ties and destroyed the environment. It has also destroyed friends in safer areas or leave the community to natural fish landing sites, which has affected the local fish- other places as there is no government intervention. ing business (the main source of livelihood) and rendered Some of the affected households remove the roofing some of the inhabitants’ jobless (Boateng 2012). sheets of their buildings to put up new buildings in Figure 6 shows part of the community in August 2013 less vulnerable areas. from satellite imagery and the same area as captured by the drone in February 2016. The portion labelled A is the Discussions location of the only school in the community on both the Analysis of the rainfall data revealed that the general August 2013 and February 2016 imageries. Comparing the pattern in the rainfall variability shows an increasing two imageries in Fig. 6, it can be seen that the position of trend, which results in flooding and erosion. According the school from the shoreline has changed. The portion to Allotey et al. (2008), the soil is often flooded during labelled B on the satellite imagery shows part of the the wet season. Other factors that cause flooding along community in August 2013 which is now flooded on the the coast in Fuvemeh and the Volta Delta include the February 2016 image. The lagoon on the August 2013 occasional overflow of the Volta River when the spill- image is also lost on the February 2016 image. ways of Bagre and Akosombo dams are opened amid Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 7 of 13 Fig. 4 Overlay of 2005 shoreline position on 2017 drone image showing land lost inland along transects heavy rains (Biney 2010; Boateng 2012), strong energetic vegetated areas to fish farms have reduced the natural wave activities from the sea (Oteng-Ababio et al. 2011), protection they offer and thus rendered the environment occasional storm surge which has increased in frequency vulnerable. and intensity in recent times (Gakpo 2016), increasing Analysis of the NADMO data shows the impact of relative sea level rise as a result of climate change, pos- flooding on the environment and the people. Flood- sible increased subsidence due to ground water extrac- ing therefore has serious socioeconomic implication tion for irrigation and to a lesser extent tidal actions. for the Fuvemeh community. The destruction of the Although the rate of subsidence has not been measured, school in the community will have huge implications it is expected to probably be between 1 and 2 mm/yr. on formal education delivery in the area. It emerged based on other deltas (Syvitski 2008; Appeaning Addo et from informal discussions with members of the com- al. 2018). The rising sea level coupled with the relatively munity that the destruction of the school building deep nearshore bathymetry (Jayson-Quashigah et al. has increased the difficulty in assessing education fa- 2013; Sagoe-Addy and Appeaning Addo 2013) enables cilities as the displaced school children now have to the strong waves to break closer to the shoreline. Any travel to nearby communities to attend school. The sudden increase in wind intensity may result in a surge, school building, according to some members of the which will further push the breaking waves more inland community interviewed during the study, is used as a to flood the low lying areas. Over harvesting of man- placeof refugeduring flood eventinthe community groves for domestic use and converting mangrove and the surrounding villages in the past. The collapse Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 8 of 13 Fig. 5 Overlay of 2017 shoreline position on 2005 orthophoto showing houses lost to erosion in Fuvemeh Fig. 6 Satellite and drone images of Fuvemeh in 2013 and 2016 showing location of the school building (a) and the area eroded (b) Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 9 of 13 Fig. 7 State of the school building in May 2016 (a) and June 2016 (b) of the school building will affect rescuing effort of structures in Ada(theup-drift sideofFuvemeh)and NADMO during such disasters. The situation has the reduced sediment discharge from the Volta River also forced some of the inhabitants to migrate from (Boateng 2012) has affected the sediment regime in the community to nearby communities, while others the area. The defense structures are made up of have moved from the delta region to other parts of groynes, which traps sediment and thereby starve the the country and beyond (Mumuni et al. 2017). De- down-drift side of sediment as observed by Angnuur- struction of natural fish landing sites by erosion has eng et al. (2013) in Keta. The action of the groynes collapsed the small scale fishing industry and in- further enhances the impact of the reduced sediment creased poverty in the community. This is expected discharge from the Volta River which has resulted in to have a huge impact on the protein intake of the the observed morphological changes. inhabitants in the community and the surrounding communities as well the food security in the country. Conclusions The changes in the shoreline migration trend being Coastal flooding and erosion are major issues in experienced in the study area are due to several fac- Fuvemeh and the entire Volta Delta. Their impact has tors such as energetic wave action, storm surge, dam intensified as a result of increased rainfall that results constructed on the Volta River in Akosombo, the low in rivers overflowing their banks; increased oceano- topography of the beach system and sea level rise graphic conditions such as frequent storm surge ac- (Sagoe-Addy and Appeaning Addo 2013, Giardino et tivities, energetic swell waves, tidal activities and sea al. 2018). The construction of coastal defense level rise that impact vulnerable communities like Fig. 8 Violent sea waves approaching the Fuvemeh community on 9th February 2016 Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 10 of 13 Fig. 9 Flooding in Fuvemeh affecting buildings (A) and fishing canoe (B) Fuvemeh; upstream water catchment management increased migration in the vulnerable areas (affected such as construction of Akosombo dam on the Volta social and cultural dynamics in the Fuvemeh commu- River which has influenced the sediment budget re- nity). The problems will increase in future under gime in delta system as well as the nearshore; over- changing climatic conditions. There is therefore the harvesting of mangroves that has destroyed the need to develop a sustainable adaptation approach to natural defence the vegetation provides and thereby effectively manage the situation and increase the re- opened the area to intense wave and tidal attacks; silience of the inhabitants. Although the government and sand mining for construction that has further af- has adopted building hard engineering structures to fected the sediment budget regime. Coastal erosion manage erosion and flooding, not all the areas experi- and flooding in Fuvemeh have collapsed buildings encing such hazards can be managed using this ap- (about 42% of the total houses); displaced inhabitants proach. It is suggested that relocating the Fuvemeh (about 300 inhabitants); destroyed sources of liveli- community to a more secured place will be more ap- hood (about 37% of Fuvemeh land, mainly natural propriate and cost effective. Alternatively, a soft en- fish landing sites along the coast, has been eroded gineering approach such as beach nourishment can be and this has affected the local fishing business); and adopted to augment the sediment shortage in the Fig. 10 Families carrying an outboard motor from a flooded house Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 11 of 13 area. The study has further demonstrated the Angnuureng, B.D., K. Appeaning Addo, and G. Wiafe. 2013. Impact of sea defense structures on downdrift coasts: The case of Keta in Ghana. Academia Journal effectiveness of using the drone technology in moni- of Environmental Science 1 (6): 104–121. toring flood and erosion in a delta community. The Angnuureng, D.B., R. Almar, K. Appeaning Addo, N. Senechal, B. Castelle, S.W. technology can therefore be applied in the fields of Laryea, and G. Wiafe. 2016. Video observation of waves and shoreline change on the microtidal Jamestown Beach in Ghana. In Proceedings of the 14th natural hazards, disaster response and high resolution International Coastal Symposium (Sydney, Australia). Journal of Coastal terrain analysis. Research, Special Issue, No. 75, pp. 1022–1026, ed. A. Vila-Concejo, E. Bruce, D. M. Kennedy, and R.J. McCarroll, 0749–0208. Coconut Creek (Florida): ISSN. Abbreviations Appeaning Addo, K. 2015. Assessment of the Volta Delta shoreline change. DEM: Digital Elevation Model; DSAS: Digital Shoreline Analysis System; Journal of Coastal Zone Management. 18: 408. https://doi.org/10.4172/jczm. EPR: End Point; GMet: Ghana Meteorological Agency; GNSS: Global Navigation Satellite System; GPS: Global Position System; HWL: High Water Appeaning Addo K (2016) Drone footage of community flooding and coastal Line; LIDAR: Light Detection and Ranging; NADMO: Ghana National Disaster erosion in the Volta Delta. The DECCMA project. http://www.deccma.com/ Management Organisation; RTK: Real-Time Kinematic; TLS: Terrestrial Laser deccma/projects_database/features/?action=story&id=82 accessed 20/11/2017. Scanner; UAV: Unmanned Aerial Vehicles Appeaning Addo, K., R.J. Nicholls, S.N.A. Codjoe, and A. Mumuni. 2018. A biophysical and socio-economic review of the Volta Delta, Ghana. Journal of Acknowledgements Coastal Research. https://doi.org/10.2112/JCOASTRES-D-17-00129.1. This study was carried out under the Collaborative Adaptation Research Appeaning Addo, K., M. Walkden, and J.P. Mills. 2008. Detection, measurement Initiative in Africa and Asia (CARIAA), with financial support from the UK and prediction of shoreline recession in Accra, Ghana. ISPRS Journal of Government’s Department for International Development (DFiD) and the Photogrammetry and Remote Sensing. 63 (5): 543–558. International Development Research Centre (IDRC), Canada. The views Armah, A.K., G. Wiafe, and D.G. Kpelle. 2005. Sea-level rise and coastal. Biodiversity expressed in this paper are those of the authors and do not necessarily in West Africa: A case study from Ghana. In Climate change and Africa, ed. P. represent those of DFiD and IDRC or its Board of Governors. S. Low, 204–217. Cambridge: University press. Basha, E.A., S. Ravela, and D. Rus. 2008. Model-based monitoring for early warning Funding flood detection. In: Proceedings of the 6th ACM conference on embedded Funding for this work was provided by the International Development network sensor systems (pp. 295-308). Chicago: ACM. Research Centre (IDRC), Canada and the UK Government’s Department for Biney, C. 2010. Connectivities and linkages within the Volta Basin. The Global International Development (DFiD) as part of the Collaborative Adaptation Dimensions of Change in River Basins 91. Research Initiative in Africa and Asia (CARIAA). Boak, E.H., and I.L. Turner. 2005. Shoreline definition and detection: A review. Journal of Coastal Research 21 (4): 688–703. Availability of data and materials Boateng I (2009) Development of integrated shoreline management planning: A The data will be available at http://188.8.131.52/geonetwork case study of Keta, Ghana. In: Proceedings of the Federation of International Surveyors Working Week 2009-surveyors key role in accelerated Authors’ contributions development, TS 4E, Eilat, Israel, 3–8 May. KAA; he designed the field work, supervised the work, developed the layout Boateng, I. 2012. An assessment of the physical impacts of sea-level rise and of the paper, contributed in writing the manuscript. PNJQ; he took part in coastal adaptation: A case study of the eastern coast of Ghana. Climatic the field data collection, analysed the rates of change, contributed to writing Change 114 (2): 273–293. the manuscript. Samuel NAC; he contributed to writing the manuscript, Bokpe SJ (2010) HELP!...Azizanya is drowning. Retrieved march 1, 2018, From reviewed the manuscript. FM; she analysed the rainfall data, contributed to http://sethbnews09.blogspot.com/2010/08/helpazizanya-is-drowning-friday- writing the manuscript. All authors read and approved the final manuscript. august.html Bollen, M., K. Trouw, F. Lerouge, V. Gruwez, A. Bolle, B. Hoffman, and P. Mercelis. Ethics approval and consent to participate 2011. Design of a Coastal Protection Scheme for Ada at the Volta-River mouth (Ghana). Coastal Engineering Proceedings 1 (32): 36. N/A Casella, E., A. Rovere, A. Pedroncini, L. Mucerino, M. Casella, L.A. Cusati, M. Vacchi, M. Ferrari, and M. Firpo. 2014. Study of wave run-up using numerical models Consent for publication and low-altitude aerial photogrammetry: A tool for coastal management. All the co-authors consented for the publication. Estuarine, Coastal and Shelf Science 149: 160–167. Chabot, D., and D.M. Bird. 2014. Small unamnned aircraft: Precise and convenient new Competing interests tools for surveying wetlands. Journal of Unmanned Vehicle Systems 1: 15–24. The authors declare that they have no competing interests. Chikhradze, N., R. Henriques, M. Elashvili, G. Kirkitadze, Z. Janelidze, N. Bolashvili, and G. Lominadze. 2015. Close range photogrammetry in the survey of the coastal area Geoecological conditions (on the example of Portugal). Earth 4 Publisher’sNote (5–1): 35–40. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Corcoran, E., C. Ravilious, and M. Skuja. 2007. Mangroves of western and central Africa (No. 26). Chicago: UNEP/Earthprint. Author details Crowell, M., S.P. Leatherman, and B. Douglas. 2005. Erosion: Historical Analysis Department of Marine and Fisheries Sciences, College of Basic and Applied and Forecasting. In Encyclopedia of Coastal Science, Encyclopedia of Earth Sciences, University of Ghana, P. O. Box Lg 99, Legon, Accra, Ghana. Sciences Series, ed. M.L. Schwartz, 428–432. the Netherlands: Springer. Regional Institute for Population Studies, College of Humanities, University Darwin, N., N.F.A. Hamid, W.S. Udin, and N.A.B. Mohd. 2013. Light weight rotary- of Ghana, P. O. Box LG 96, Legon, Ghana. Ghana Meteorological Agency, P. wing UAV for large scale mapping applications. Asia geospatial forum,24–26. O. Box Lg 87, Legon, Accra, Ghana. Kuala Lumpur, Malaysia: September. Delacourt, C., P. Allemand, M. Jaud, P. Grandjean, A. Deschamps, J. Ammann, V. Received: 9 May 2018 Accepted: 3 October 2018 Cuq, and S. Suanez. 2009. DRELIO: An unmanned helicopter for imaging coastal areas, SI 56. In Proceedings of the 10th international coastal symposium, 1489–1493. References Dolan, R., M.S. Fenster, and S.J. Holme. 1991. Temporal Analysis of Shoreline Allotey, D.F.K., R.D. Asiamah, C.D. Dedzoe, and A.L. Nyamekye. 2008. Physico- Recession and Accretion. Journal of Coastal Research 7 (3): 723–744. chemical properties of three salt-affected soils in the lower Volta Basin and Duodu F (2011) Volta region submerged. General news, modern Ghana. https:// management strategies for their sustainable utilization. West African journal www.modernghana.com/news/342077/volta-region-submerged.html of applied ecology 12(1):1–14. accessed 5/9/2018. Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 12 of 13 Elaksher, A.F., S. Bhandari, C.A. Carreon-Limones, and R. Lauf. 2017. Potential of topography: The structure from motion approach on coastal environments. UAV lidar systems for geospatial mapping. In Lidar Remote Sensing for Remote Sensing 5 (12): 6880–6898. Environmental Monitoring 2017 (Vol. 10406, p. 104060L). International Society Matgen, P., R. Hostache, G. Schumann, L. Pfister, L. Hoffmann, and H.H.G. Savenije. for Optics and Photonics. 2011. Towards an automated SAR-based flood monitoring system: Lessons Ericson, J.P., C.J. Vörösmarty, S.L. Dingman, L.G. Ward, and M. Meybeck. 2006. learned from two case studies. Physics and Chemistry of the Earth, Parts A/B/C Effective Sea-level rise and deltas: Causes of change and human dimension 36 (7): 241–252. implications. Global and Planetary Change 50 (1): 63–82. Mohammed, F., A. Idries, N. Mohamed, J. Al-Jaroodi, and I. Jawhar. 2014. UAVs for smart cities: Opportunities and challenges. In Unmanned Aircraft Systems Fagotto M (2016) West Africa Is Being Swallowed by the Sea: Encroaching waters off the coast of Togo, Ghana, Mauritania, and others are destroying homes, (ICUAS), 2014 International Conference IEEE, 267–273. schools, fish, and a way of life. Retrieved March 1, 2018, from http:// Moore, L.J. 2000. Shoreline mapping techniques. Journal of Coastal Research 16 foreignpolicy.com/2016/10/21/west-africa-is-being-swallowed-by-the-sea- (1): 111–124. climate-change-ghana-benin/ Morton, R.A. 1991. Accurate shoreline mapping: Past, present and future. In Ford, M. 2013. Shoreline changes interpreted from multi-temporal aerial Coastal sediment’91, edited by Kraus, 997–1010. New York: N. C. photographs and high resolution satellite images: Wotje atoll, Marshall Mumuni, A., Y. Atiglo, C. Addoquaye-Tagoe, and S. Codjoe. 2017. Descriptive Islands. Remote Sensing of Environment 135: 130–140. statistics from sending area survey data - Volta Delta. Royal Senchi, Ghana: Gakpo JO (2016) Climate refugees: Life in Ghana’s fast vanishing lands - 2. Joy news. Ghana. DECCMA consortium workshop. | http://www.myjoyonline.com/opinion/2016/October-25th/climate-refugees- Oguntunde, P., J. Friesen, N. van de Giesen, and H.H.G. Savenije. 2006. life-in-ghanas-fast-vanishing-lands-2.php assessed on 6th November 2016. Hydroclimatology of the Volta River basin in West Africa: Trends and Genz, A.S., C.H. Fletcher, R.A. Dunn, L.N. Frazer, J. John, and J.J. Rooney. 2007. The variability from 1901 to 2002. Physics and Chemistry of the Earth 31: predictive accuracy of shoreline change rate methods and Alongshore Beach 1180–1188. variation on Maui, Hawaii. Journal of Coastal Research 23 (1): 87–105. Oteng-Ababio, M., K. Owusu, and K. Appeaning Addo. 2011. The vulnerable state Ghanaweb (2008) Relief for communities hit by tidal waves. https://www. of the Ghana coast: The case of Faana-Bortianor. Jàmbá: Journal of Disaster ghanaweb.com/GhanaHomePage/NewsArchive/Relief-for-communities-hit- Risk Studies 3 (2): 429–442. by-tidal-waves-150323 Accessed 5/9/2018. Owens B (2016) Drones on the Delta: In Ghana’s Volta River Delta, the Giardino, A., R. Schrijvershof, C.M. Nederhoff, H. de Vroeg, C. Brière, P.K. Tonnon, remotely-operated aerial vehicles are going where researchers can’tto and J. Schellekens. 2018. A quantitative assessment of human interventions help study coastal erosion, flooding and migration.http://idrc. and climate change on the west African sediment budget. Ocean & Coastal canadiangeographic.ca/education/docs/ghana-drones-delta-workbook.pdf Management 156: 249–265. (Accessed 10/08/2017). Goldberg D, Corcoran M, Picard RG (2013) Remotely piloted aircraft systems and Owusu, K., and P. Waylen. 2013. The changing rainy season climatology of mid- journalism: Opportunities and challenges of drones in news gathering. Ghana. Theoretical and Applied Climatology. 112 (3): 419–430. https://doi.org/ 10.1007/s00704-012-0736-5. Gonçalves, J.A., and R. Henriques. 2015. UAV photogrammetry for topographic monitoring of coastal areas. ISPRS Journal of Photogrammetry and Remote Pérez-Alberti, A., and A.S. Trenhaile. 2015. An initial evaluation of drone-based Sensing 104: 101–111. monitoring of boulder beaches in Galicia, north-western Spain. Earth Surface Graham, D.M., J.C. Sault, and J. Bailey. 2003. National Ocean Service Shoreline - Processes and Landforms 40 (1): 105–111 Pix4D, (2013). Pix4D Mapper Pro: past, Present, and Future. Journal of Coastal Research SI (38): 14–32. http://pix4d.com/pix4dmapper-pro/. Hackney, C., and A. Clayton. 2015. Unmanned Aerial Vehicles (UAVs) and Their Roest LWM (2018) The coastal system of the Volta Delta, Ghana: Strategies and Application in Geomorphic Mapping. Geomorphological Techniques. In opportunities for development. TU Delft Delta Infrastructures and Mobility Bristish Society for Geomporlogy, ed. L. Lucy Clarke and J. Nield, 6. Initiative (DIMI). Harwin, S., and A. Lucieer. 2012. Assessing the accuracy of georeferenced point Rossi, G. 1989. L’e’rosion du littoral dans le Golfe du Be ´nin: un exemple de clouds produced via multi-view stereopsis from unmanned aerial vehicle perturbation d’un e’quilibre morphodynamique. Zeitschrift fu¨r (UAV) imagery. Remote Sensing 4 (6): 1573–1599. Geomorphologie NF Suppl Band 73: 139–165. Hugenholtz, C.H., K. Whitehead, O.W. Brown, T.E. Barchyn, B.J. Moorman, A. Sagoe-Addy, K., and K. Appeaning Addo. 2013. Effect of predicted sea level rise LeClair, K. Riddell, and T. Hamilton. 2013. Geomorphological mapping with a on tourism facilities along Ghana’s Accra coast. Journal of Coastal Conservation and Management. 17 (1): 155–166. https://doi.org/10.1007/ small unmanned aircraft system (sUAS): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model. s11852-012-0227-y. Geomorphology 194: 16–24. Smith, A.W.S., and L.A. Jackson. 1992. The variability in width of the Visible Beach. Jayson-Quashigah, P.-N., K. Appeaning Addo, and K.S. Kodzo. 2013. Medium Shore and Beach 60 (2): 7–14. resolution satellite imagery as a tool for monitoring shoreline change. Case STAFF AG (2017) Wilderness society to use drones to raise awareness of study of the eastern coast of Ghana. Journal of Coastal Research 65: 551–516. deforestation. Australian geographic. http://www.australiangeographic.com. Karley, N.K. 2009. Flooding and physical planning in urban areas in West Africa: au/news/2017/01/wilderness-society-to-use-drones-to-raise-awareness-of- Situational analysis of Accra, Ghana. Theoretical and Empirical Researches in deforestation (Accessed 15/01/2018). Urban Management 13: 25. Stockdon, H.F., A.H. Sallenger, H.J. List, and R.A. Holman. 2002. Estimation of shoreline position and change using airborne topographic lidar data. Journal Klemas, V.V. 2015. Coastal and environmental remote sensing from of Coastal Research 18 (3): 502–513. unmanned aerial vehicles: An overview. Journal of Coastal Research 31 (5): 1260–1267. Syvitski, J.P. 2008. Deltas at risk. Sustainability science 3 (1): 23–32 Journal of Kussul, N., A., Shelestov, S., Skakun, and O. Kravchenko. 2008. Data assimilation sustainable development; 9(3); 2016. ISSN 1913-9063 E-ISSN 1913-907. technique for flood monitoring and prediction. International Journal Thieler ER, Himmelstoss EA, Zichichi JL, Ergul A (2017) Digital Shoreline Analysis "Information Theories & Applications" 15(2008):76–83. System (DSAS) version 4.0—An ArcGIS extension for calculating shoreline Lane, S.N., J.H. Chandler, and K. Porfiri. 2001. Monitoring river channel and flume change (ver. 4.4, July 2017): U.S. Geological Survey Open-File Report 2008 1278, surfaces with digital photogrammetry. Journal of Hydraulic Engineering 127 https://pubs.er.usgs.gov/publication/ofr20081278 (Accessed 12/12/2017). (10): 871–877. Turner, I.L., M.D. Harley, and C.D. Drummond. 2016. UAVs for coastal surveying. Leatherman, S.P., D. Whitman, and K. Zhang. 2005. Airborne Laser Terrain Coastal Engineering Volume 114: 19–24. Mapping and Light Detection and Ranging. In Encyclopedia of Coastal Vousdoukas, M.I., G. Pennucci, R.A. Holman, and D.C. Conley. 2011. A semi- Science. Encyclopedia of Earth Sciences Series, ed. M.L. Schwartz, 21–23. the automatic technique for Rapid Environmental Assessment in the coastal Netherlands: Springer. zone using Small Unmanned Aerial Vehicles (SUAV). Journal of Coastal Research SI 64: 1755–1759 (Proceedings of the 11th International Coastal Lumor, M. 2015. Estimation of Streamflow and Fluvial Sediment Loads in the Symposium), Szczecin, Poland. White Volta Basin under Future Climate Change. In 2015 AGU Fall Meeting. Agu.Catalyst (2015). Catalyst quick take: Women in male-dominated industries Wallace, L., A. Lucieer, C. Watson, and D. Turner. 2012. Development of a UAV-LiDAR and occupations in U.S. and Canada, 2015. New York: Catalyst. system with application to Forest inventory. Remote Sensing 4: 1519–1543. Mancini, F., M. Dubbini, M. Gattelli, F., Stecchi, S., Fabbri, and G. Gabbianelli. 2013. Wellens-Mensah, J., A.K. Armah, D.S. Amlalo, and K. Tetteh. 2002. Ghana National Using unmanned aerial vehicles (UAV) for high-resolution reconstruction of Report Phase 1: Integrated problem analysis. GEF MSP sub-Saharan Africa Appeaning Addo et al. Geoenvironmental Disasters (2018) 5:17 Page 13 of 13 project (GF/6010-0016): Development and protection of the coastal and marine environment in sub-Saharan Africa. Accra. Whitehead, K., and C.H. Hugenholtz. 2014. Remote sensing of the environment with small unmannned aircraft systems (UASs), part 1: A review of progress and challenges. Journal of unmanned Vehicle Systems 2: 69–85. Whitehead, K., C.H. Hugenholtz, S. Myshak, O. Brown, A. LeClair, A. Tamminga, T.E. Barchyn, B. Moorman, and B. Eaton. 2014. Remote sensing of the environment with small unmanned aircraft systems (UASs), part 2: Scientific and commercial applications1. Journal of Unmanned Vehicle Systems 02 (03): 86–102. Wong, P.P., I.J. Losada, J.-P. Gattuso, J. Hinkel, A. Khattabi, McInnes KL, Y. Saito, and A. Sallenger. 2014. Coastal systems and low-lying areas. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, ed. C.B. Field, V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P. R. Mastrandrea, and L.L. White, 361–409. Cambridge and New York, NY: Cambridge University Press.
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