Liberia's coastal erosion vulnerability and LULC change analysis: Post-civil war and Ebola epidemic

Awange, Joseph; Saleem, Ashty; Konneh, S.S.; Gonçalves, Rodrigo Mikosz; Kiema, John; Hu, K.X.

doi:10.1016/j.apgeog.2018.10.007

Cited by 17 publications

(13 citation statements)

References 35 publications

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“…Use of modern remote sensing data sources, e.g., Landsat and ASTER, and GIS analysis, therefore, provide efficient alternative platforms that allows efficient analysis of regions with limited accessibility to be carried out in a sufficient manner (see e.g., Gonçalves and Awange, 2017;Jayson-Quashigah et al, 2013;Yu et al, 2011). These have been demonstrated in studies of coastline monitoring that employ multi-temporal satellite images and Geo-Information System modelling techniques, e.g., in Ghana (Appeaning Addo et al, 2008; Jayson- Quashigah et al, 2013), Bangladesh (Hussain et al, 2014), Thailand (Tochamnanvita and Muttitanon, 2014), Iran (Alesheikh et al, 2007), India (Misra and Balaji, 2015;Poornima and Chinthaparthi, 2014;Rawat and Kumar, 2015), Korea (Shin and Kim, 2015), Egypt (Abd El-Kawy et al, 2011;El-Hattab, 2016), Portugal (Pardo-Pascual et al, 2012), China (Zhang et al, 2013) and more recently for Liberia in Awange et al (2018). The uses of traditional medium spatial resolution satellite imagery, e.g., Landsat-8 (30 m) is very powerful data for mapping landscape elements at regional scales.…”

Section: Tablementioning

confidence: 99%

“…The availability of Sentinel-2 data with 10 m spatial resolution and 5 days revisit, is expected to improve the mapping accuracy by this new platform in the field of remote sensing (Parrish, 2012;Topouzelis et al, 2016). Since its launch in 2015, Sentinel-2 products have been used, e.g., to map spruce and pine areas in Germany (Immitzer et al, 2018), for land use land cover (LULC) change analysis (Gašparović, 2018;Goldblatt et al, 2018), and its potential for coastal erosion studies acknowledged, e.g., by Awange et al (2018), Castillo et al (2017), Hagenaars et al (2018), and Sagar et al (2018). The study conducted by Santos and Gonçalves (2014) used Landsat 8 data and Sentinel-2 for testing many applications i.e., LULC, shoreline delineation, and forest mapping.…”

Section: Tablementioning

confidence: 99%

“…The novelty of this present contribution, therefore, is that it extends on the work of Hagenaars et al (2018) by providing the first test of the applicability of manually digitised coastline from Sentinel-2 products to monitor coastline movements over data deficient regions, thereby providing high accurate spatio-temporal mapping than previously achieved using freely available remotely sensed Landsat products. The advantages of using manually digitised imagery include, e.g., avoiding misclassification (see Awange et al, 2019;Awange et al, 2018;Dewan et al, 2017). This becomes important for inaccessible regions where obtaining in-situ data for validating automated imageries is impossible as is the case for Somalia.…”

Section: Tablementioning

confidence: 99%

“…The Liberian coastal zone of about 559 km in length is home to about 58% of the Liberian population (Nicholls and Cazenave, 2010;USAID, 2012). Geographical features along Liberia's coastline include lagoons, sandbars and mangrove swamps (Awange et al, 2018). The topography of Liberia in general is largely flat with the highest point being the top of Mount Wuteve, 1380 m above mean sea level (Awange et al, 2018).…”

Section: Case Study Areasmentioning

confidence: 99%

“…Constant monitoring of coastlines is thus paramount for a sustainable use of its resources. The importance of coastline monitoring is highlighted, e.g., by Li et al (1998), Di et al (2003), Veloso-Gomes et al (2008), Awange et al (2018) and Gonçalves and Awange (2017) who opine that coastline mapping is critical for safe navigation, coastal resource management, coastal environmental protection, integrated coastal zone management (ICZM, i.e., management of coastal resources to meet the needs of the coastal population in a sustainable way, see e.g., Post and Lundin, 1996), and sustainable coastal development and planning; and is therefore a critical Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

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Coastline shift analysis in data deficient regions: Exploiting the high spatio-temporal resolution Sentinel-2 products

Saleem

Awange

2019

CATENA

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In most developing countries, coastline shift monitoring using in-situ (ground-based) data faces challenges due, e.g., to data unreliability, inconsistency, deficiency, inaccessibility or incompleteness. Even where practically applicable, the traditional "boots on the ground" methods are labour intensive and expensive, thus imposing burden on poor countries struggling to meet other urgent pressing daily needs, i.e., food and medicine. Remote sensing (RS) techniques provide a more efficient and effective way of collecting data for coastline shift analysis. However, moderate spatio-temporal resolution RS products such as the widely used Landsat products (30 m and 16 days) may be insufficient where high accuracy is desired. In 2015, Sentinel-2 Multi-Spectral Instrument (MSI) remotely sensed products with higher spatio-temporal resolution (10 m and 5 days) and high spectral resolution (13 bands), which promises to improve coastline movement monitoring to high accuracy, was launched. Using two war-impacted countries (Liberia and Somalia) as case studies of regions with data deficiency or of poor quality, for the period 2015-2018, this contribution aims at (i) assessing the suitability of the new freely available high spatio-temporal Sentinel-2 products to monitor coastline shift, (ii) assessing the possibility of filling the missing Sentinel-2 gaps with Landsat 8 panchromatic band (15 m) products to provide alternative data source for mapping of coastline movements where Sentinel-2 data is unusable, e.g., due to cloud cover, and (iii), undertake a comparative analysis between Sentinel-2 (10 m), Landsat panchromatic (15 m), and Landsat multi-spectral (30 m). The results of the evaluation indicate 23% (on average) improvement gained by using Sentinel-2 compared to the traditional Landsat 30 m resolution data (i.e., 32% for Liberia and 14% for Somalia). A comparison of 100 check points from Google Earth Pro (i.e., surrogate in-situ reference data) show 91% agreement for Liberia and 85% for Somalia, indicating the potential of using Sentinel-2 data for future coastal shift studies, particularly for the data deficient regions. The results of comparative studies for Sentinel-2, Landsat panchromatic (PAN), and Landsat multi-spectral (MS) show that the percentages of Sentinel-2 and Landsat PAN that falls within 10 m threshold is much higher than Landsat MS by 35% and 26%, respectively, and for the 2016-2017 period, they provide more detailed mapping of the Liberian coastline compared to Landsat MS (30 m). Finally, panchromatic Landsat data with 15 m resolution are found to be capable of filling the missing Sentinel-2 gaps, i.e., where cloud cover hampers its usability.

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