Urbanization and flood risk analysis using geospatial techniques

Raphael Ane Atanga; Vitus Tankpa; Isaiah Acquah

doi:10.1371/journal.pone.0292290

. 2023 Oct 20;18(10):e0292290. doi: 10.1371/journal.pone.0292290

Urbanization and flood risk analysis using geospatial techniques

Raphael Ane Atanga ^1,^*, Vitus Tankpa ², Isaiah Acquah ¹

Editor: Mohammed Sarfaraz Gani Adnan³

PMCID: PMC10588841 PMID: 37862338

Abstract

This research investigates the relationship between urbanization as a land use/land cover change and the increased flood disasters in Accra. Understanding this relationship will provide evidence for urban development planners, policy makers and flood managers to coordinate in responding to the problems effectively. This study maps and analyzes the changes in urbanization from 1991 to 2015. The research reviews the trends of flood events in Greater Accra and analyzes the relationship between the pattern of urbanization and the increase in flood disaster events from 1991 to 2015. The research revealed that there was an increase in urban land use/land cover change of up to 95.51% and 129.14% in the periods 1991–2002 and 2002–2015 respectively. The pattern of urbanization took place in an unplanned style, where physical developments in waterways became high. The findings show that the pattern of flood disasters increased from 1991 to 2015 with evidence showing two years having repeated flood events.

1 Introduction

This study analyses the relationship between urbanization as a land use/land cover change and flood disasters in Accra using geospatial techniques. Land use/land cover changes are major concerns for environment and development planning, especially when the changes have negative impacts on society [1]. Land use/land cover changes can come from natural and human induced processes which can destroy and replace existing land use/land cover surfaces. Existing land use/landcover surfaces as ecosystems, are difficult and expensive to remediate when destroyed. Land use/land cover changes can be influenced by political, economic, demographic and environmental factors [2]. Changes in political decisions and development policies may favour and discourage people from living in urban areas. For instance, where economic and physical development focused more on the provision of infrastructure, services and quality of life in urban areas than rural development, people may be attracted to migrate to urban settings [3]. The migrants would need more houses and urban land spaces which could eat up other land cover surfaces. Economic reasons for changes in land use/land cover follow similar trend of argument where economic activities were predominantly urban, thereby attracting the concentration of people in urban environs. In the 1990s, for example, countries that experienced trade liberalization and structural adjustments policies focused more on urban development which subsequently attracted the working population to cities and towns leading to urbanization [1]. Land use/land cover changes including land degradation, natural disasters and insecurity may drive people to urban areas leading to increase in demand for urban dwellings and environmental changes. Demographic changes as in population increase in rural and urban settings can lead to a need for more land for housing and development which may trigger changes in land cover and land use to urban land surface. Of all developmental activities that bring about land use land cover changes, urbanization is one of the prominent changes that the world has been experiencing over the years that lead to spiral social and environmental challenges [4]. Urbanization is the uncontrolled expansion of urban land uses emanating from development. Urbanization is particularly a problem of developing countries, especially in Africa where the percentage of urban population is less than 50, which means that the continent is rapidly urbanizing [5]. Changes in society that accelerate urbanization may include demographic, economic and technological advancements, leading to the quest to dwell in urban environments.

Impacts of urbanization on environment in developing nations includes modernization and improvement in quality of life but it can also result in environmental problems including degradation of ecosystems, pollution and poor sanitation, solid waste, slum development and increase in flood disaster risk [5–8]. Urbanization and its impacts in Ghana are a serious concern for planners, development practitioners and policy makers alike as major cities including Accra and Kumasi keep expanding uncontrollably over the years. About 50% of the Ghana population is urban dwellers and most recent research shows that this figure will reach 70% by the year 2050 [4]. Factors that explain the reasons for the increase of urban dwellers in Ghana are related to those mentioned modernization, rural urban migration, globalization and environmental factors [9]. Greater Accra is the capital of Ghana with a current population of over 4 million of which over 90% is urban and the total population is expected to exceed 10 million in the next 20 years [4]. The impacts of urbanization have consequences on land use land cover changes, environmental degradation, waste management challenges, conversion water bodies into urban developments and encroachment on waterways resulting increase in flood disaster risk [10]. This is particularly for Accra where urban sprawl is a problem and a major cause of environmental degradation, insanitary conditions, pollution, and annual flood disasters [11]. The rate of urbanization and its related challenges of development keep increasing and require further solutions. Flood disaster risk has been a chronic annual problem in Accra since the 1990s with serious impacts on lives, property and environment [7, 12–14]. The spate of flood problems seems to coincide with the period in which urbanization in Accra started gaining momentum [3, 15]. However, relationship between flood disaster risk and urbanization in Accra is not yet well examined using remote sensing and geographic information systems (GIS).

The development of remote sensing and geographic information systems technologies has brought possibilities to study the spatio-temporal changes of land use land cover that allow researchers to understand in quantitative and qualitative terms, the extent of changes in urbanization and its relationship with other urban environmental problems [15, 16]. Particularly, GIS plays a crucial role in mapping, modeling and spatial analysis of land use land cover changes which includes urbanization and flood disasters [17–19]. [20] reviewed successful application of remote sensing and GIS of all stages in flood disaster risk management (pre-flood, during flood and post-flood event management phases). Several studies about urbanization and flood disaster risk have been conducted in Accra using GIS and remote sensing but none of them has focused on mapping and explaining the relationship between urbanization and flood disasters. [3] indicates that urbanization of Accra makes the city vulnerable to climate change impacts. [7] studied urban planning problems and flood disasters in Accra and concludes on poor urban planning as one reason for flood disasters in the city.

For instance, using GIS [21], modeled flood risk zones in Accra and contended that over 40% is it between high and medium flood risk zones. Other scholars employed GIS and remote sensing techniques to investigate vulnerability of slums in Accra to flooding and environmental degradation using social status, demographics and health as yardsticks [22]. [23] further applied GIS to model and predict the future extent of flood risk in Accra. [24] applied a triangulated irregular network and GIS to analyse reservoirs for flood management in Accra.

[9] examine the spatio-temporal land use land cover change patterns that occurred in Accra between 1985 and 2010 using remote sensing and GIS techniques. [25] suggest that risk of flooding to settlements in Accra will keep increasing the next years. The most recent study by [4] suggests that urbanization keeps increasing at the expense of other land use land cover surfaces and this could reach about 70% in the year 2025.

The existing urban planning policies and flood risk management measures in Accra have been unsuccessful in stopping urbanization and floods in Greater Accra [26]. The Town and Country Planning department exists with a history of land use planning policies and measures for responding to urbanization and floods but have not been successful yet [7]. The main flood management interventions in Accra include structural and non-structural measures. The structural measures are engineering approaches, mainly channelization which focuses construction and maintenance of drains to convey storm waters to sea. These are physical structures with an objective prevent and control flood hazards and vulnerabilities. The Korle Lagoon Restoration Project (KLERP) and the Accra Sanitary and Storm Drainage Alleviation Project 2013 (the Conti Project) are examples of structural flood management interventions.

The non-structural measures are policies and programmes with an objective to save lives and property through flood preparedness, emergency response, recovery and mitigation measures. Institutions such as NADMO, Ghana Meteorological Agency, security agencies and non-state organizations play various roles in flood management of the study site. The flood preparedness measures include public education on safety measures as well as eviction and relocation of settlements on waterways [27]. During flood events, early warning of floods for safety and evacuation further support to minimize flood impacts. There are also relief interventions and clean-up exercises after flood events to minimize post-flood impacts. These measures together with flood mitigation interventions exist but the menace of floods keeps increasing.

Seemingly, flooding is a big problem in Accra and there is a knowledge gap about the relationship between changes in urbanization and flood disasters from Remote sensing and GIS analysis. Remote sensing and GIS can show temporal and spatial changes in urbanization to enhance quantitative and qualitative understanding of the changes and the relationship with flood disaster risks in Accra. This study seeks to map and analyze the changes in urbanization for the periods of 1991 to 2015 (1991–2002 and 2002–2015) and the relationship of these changes with increase in flood disasters in Accra within the period. Establishing this relationship would help to map and understand the relationship between urbanization and flood disaster risk in the city to inform urban planning and development in the future.

This research has three specific research objectives. The first objective is to map and analyze the trends of urbanization as a land use land type in Greater Accra for the periods of 1991–2002 and 2002–2015 using geospatial techniques. The second objective is to map flood risk zones, identify the flood disaster events between 1990 and 2015 and analyze the trends of flood disaster risk in Greater Accra. The third objective is to analyze the relationship between the pattern of urbanization and the increase in flood disaster events from 1990 to 2015. The aim of this research is to contribute to research, policy and practical management of urbanization and flood disaster risk in the study site and other areas with similar conditions.

2 Materials and methods

2.1 Description of the study area

The Greater Accra Region of Ghana was chosen for the research due to its increasing urbanization and chronic annual flood disasters in recent years. [3] provided extensive mapping and analysis of uncontrolled urbanization in Accra. Accra in the Metropolitan Assembly (AMA) is the capital of the Greater Accra Region and the capital city of Ghana. It is the centre of development and the headquarters of international organizations that link Ghana to rest of the world.

Accra is between Latitude 5º 40’N and between Longitude 00º 34’W and Longitude 00º 29’E (Fig 1). The region has about 780 cubic millimeters of average annual rainfall with temperature fairly stable from 24.7°C in August to 28°C in March with an annual average of 26.8°C. Located along the Gulf Guinea Coast, the northern part of Accra is bordered by the Akwampim ranges with Tema Municipal Assembly bordering eastern part. The topography of Accra is undulating with generally lowland dissected by 7 drainage basins. Namely, Chemu, Osu, Songo Mokwe, Lafa, Sakumo, Densu, Kpeshie and Korle basins. The Korle basin experiences high runoff resulting in frequent flood disasters. The region lies within -40 meters below and 400 meters above sea level. The surroundings of the drainage basins in low lying areas experience floods. The flood prone communities are located in very high to medium flood risk zones. Studies have established that these communities regularly had flood events leading to disasters [3, 21].

2.2 Data sources

The main data for this study were Landsat images and flood disaster statistics. A spatial resolution of 30m Landsat satellite surface reflectance images of 1991, 2002 and 2015 were acquired from the United States Geological Survey (USGS) Earth Explorer site (https://glovis.usgs.gov). These images were extracted to assess temporal and spatial changes in the study area. Landsat TM, ETM+ and Landsat 8 images were considered (see Table 1) due to their high resolutions which would enable changes of urban areas from other land use/land cover surfaces to be detected. These periods were chosen because the negative impacts of urbanization in Accra such as flood disasters became serious from the 1990s and these impacts are a major challenge for developers and other stakeholders in the area. Furthermore, existing literature already indicates that the land area of Accra built up in periods before the year 2015 [7]. Additionally, the readily availability of data for flood data disasters in the study site for the period is also the reason for choosing those periods. Data on flood risk zones and flood disaster events were obtained from secondary sources and Ghana’s National Disaster Management Organization (NADMO) archives.

Table 1. Characteristics of the satellite images used for the investigation.

Acquisition Date	Path/Row	Landsat	Sensor	Spatial Resolution	Number of Bands
10/01/1991	193/056	Landsat 4	TM	30m	7
26/12/2002	193/056	Landsat 7	ETM+	30m	9
06/12/2015	193/056	Landsat 8	OLI-TIRS	30m	11

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Source: Fieldwork, 2020

2.3 Pre-process of Landsat images

Top-of-atmosphere (TOA) calibration was used to convert the Digital Number (DN) values to reflectance in order to minimize the radiometric differences caused by disparities in TM and Landsat 8 sensors as a result of sensor-target-illumination. Geometrically, the images were corrected and calibrated to reflectance by means of information provided in the image metadata. Atmospherically calibrated images were mosaicked and clipped to the extent of the study area boundary.

2.4 Classification and accuracy assessment

Hybrid approach to image classification was used to classify the images with the aid of GIS software and ERDAS imagine. This involves conducting unsupervised classification first by defining signature files and fixing the number of classes to undertake preliminary interpretation. The main benefit of employing the unsupervised classification is the identification of distinct spectral classes for the images. It was then followed by supervised classification techniques by using the maximum likelihood classification algorithm, where a comparison of the spectral properties of each pixel were made to a set of representative pixels, which are known as training data or sample specified by the user. The training samples were collected using the researcher’s personal knowledge and experience of the study area, as well as Google Earth and topographic maps. In all, the satellite images were classified into various classes of urban, grassland, water, bareland, forest, agriculture and shrublands (Table 2). These classes were identified and grouped in this study based on the USGS Land use/land cover classification scheme developed by [28]. However, the classification system was fairly improved to suit the study area.

Table 2. Description of land use/land cover types.

Land use/land cover categories	Description
Urban	Mixed urban areas, Residential areas, Industrial and Commercial units, Transportation facilities
Grassland	Mixed grassland with few scattered tree
Water,	Lakes, Rivers, Streams, Canals, Reservoirs, Estuaries, Bays, Forested wetlands, Aquaculture facilities
Bareland,	Beaches, Sandy areas, Exposed rocks, River banks, Quarries and gravel pits, transitional areas
Agriculture	Pasture, cropland, orchards and fallow land
Shrubland	Herbaceous vegetation, Shrub and bush areas,
Forest	Evergreen forest land, Mixed forest land, Deciduous forest land, Forest reserves

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Source: Fieldwork, 2020

Confusion matrix was used to assess the accuracy of the classified images. This includes the omission error, commission error and kappa statistic. Ground-truth data obtained from GPS field surveys, Landsat images, existing maps and Google earth images were used as reference data. A minimum of sixty samples for each class was taken based on the rule-of-thumb theory recommended by [29].

The post-classification change detection technique was adopted to quantify, identify, and describe the differences in the land use maps produced. This technique is capable of generating a complex matrix of change and also minimizing the effects of sensor and atmospheric differences between two dates by using classified images [30].

2.5 Land use/land cover change detection

Change detection is the procedure of distinguishing the differences in the settings of both natural and man-made features on earth at different periods [31, 32]. Several approaches can attain change detection analysis by detecting and measuring differences in the image acquired at different time points over the same area. In this study, change detection was attained through transition matrices. This was achieved through “subtraction” of any two classified images via a pixel-by-pixel comparison. This generates a matrix with diagonal representing area statistics of categories that have not changed between the time points compared. The non-diagonal cells represent the dynamics transition between the initial period and the final period.

2.6 Flood risk mapping

Data on topography, hydrology, land use and historical flood events are used to map flood risk. To ensure consistency, the collected data was cleaned and formatted. ArcGIS Pro was used to analyze the clean data and identify areas of potential flood risk. This entails creating digital elevation models, calculating flow accumulation and direction, and identifying areas of potential flooding based on historical flood events and land use/land cover of the study area. The analyzed data was then used to perform a risk assessment to determine the level of flood risk in different zones within the study area. The assessment considered the study area’s topography, hydrology, and land use/land cover. Finally, a flood risk map was created using ArcGIS Pro. This consists of creating a base map, overlaying the analyzed data, and symbolizing the data to show the levels of flood risk.

3 Results and discussion

3.1 Spatial distribution of land use/land cover of the study area

Based on the classification of the satellite image data of the three periods in the study area, the spatial distribution map of land use/land cover in different time points was generated (Fig 2). Statistics on land use/land cover types in the corresponding years (Table 3) were also produced to analyze the quantitative and spatial characteristics of land use changes.

Table 3. Summary of land use/land cover type structure of the study area.

Land use type		1991	2002	2015
Water	Area(km²)	185.974	203.914	236.865
Water	Proportion (%)	5.09	5.6	6.51
Urban	Area(km²)	403.51	788.894	1807.69
Urban	Proportion (%)	11.09	21.68	49.67
Grassland	Area(km²)	1887.72	1475.81	497.312
Grassland	Proportion (%)	51.9	40.55	13.67
Bare land	Area(km²)	32.5791	90.022	169.179
Bare land	Proportion (%)	0.9	2.47	4.65
Shrubland	Area(km²)	868.95	887.063	773.807
Shrubland	Proportion (%)	23.87	24.37	21.26
Forest	Area(km²)	11.680	63.684	31.086
Forest	Proportion (%)	0.32	1.75	0.85
Agric	Area(km²)	248.846	129.872	123.33
Agric	Proportion (%)	6.84	3.57	3.39

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Source: Fieldwork, 2020

Fig 2 shows that the main land use/land cover classes were grassland, shrubland and urban. Grassland was the largest land cover, mainly distributed in the south western, central, nothern and north eastern plains of the study area in 1991. The area of grassland accounts for over 50% of the total area of the study area, but keep on decreasing gradually from about 51% in 1991 to 13% in 2015. This shows a decrease of more than hundred percent, and significant decline in the area of grassland. This can be to the rapid expansion of urban areas at the expense of grassland and agriculture areas. The urban area is mainly distributed within the southern, south west, along the central to south eastern, towards the northern part of the study area. From 1991 to 2015 urban area has increased significantly more than hundred percent, which can be attributed to population increase and the need for accomodation by the rapidly growing population in the study area. Though shrubland cover is second and larger than urban, forest, water and agric (agriculture) classes, urban area in 1991 stands as the third largest land use type in the study area. From Fig 1, it also is obvious that, in 2002, grassland occupies the largest area although it has reduced in coverage relative to 1991. The urban class has increased extremely to more than hundred percent from 1991 to 2002 and this can be explained by the possible factors of urbanization mentioned earlier. Also, drastic changes in the land use types were observed in 2015. Apparently, the urban class has increased to be the largest land surface and has eaten up most of the grassland, agriculture land and forest cover surface of the study area. The forest land cover has reduced to be the smallest land cover of the region and water land cover seems to be increasing. This is similar to the assertion of [4] that the urban area has increased, and it is projected to increase to over 50% between 2015 and 2025.

3.2 Nature, extent and rate of land/use change

The statistics revealed that, in 1991, the main land-cover was grassland and shrubland, occupying about 51.9% and 23.9% of the total area respectively. The results further indicate that the third major land cover was urban area with 11.1% of the total land use/land cover of the study site. Agriculture area occupied 6.9% as at 1991, while water, bare land and forest occupies 5.1%, 0.9% and 0.3% of the total land use/land cover area respectively. It was observed that urban areas in the region have drastically expanded, mainly at the expense of grassland and agriculture areas. Forest areas, grassland and agriculture in the region had the greatest loss, while shrubland and water bodies showed very little change between 1991 and 2015. During 2002, different distributions of the land use/land cover classes were identified compared to 1991. Urban area increased from 1991 to 2002 to cover 21.7% of the total land use/land cover area. The analysis also indicated that urban areas had significantly increased, expanding from 11.1% in 1991 to 21.7% in 2002. This finding agrees with [4]. This percentage increase means that urban covered approximately 788.894km² of the region in 2002 Between the same time period, grassland and agriculture area reduced to 40.6% and 3.6% respectively. Table 4 shows the land-use percentage and area changes for the two study periods. Urban areas continued to massively expand and became the main land use type in the region in 2015. Thus, it covered almost half of the total land use/land cover of the study area, amounting to 49.7% (1807.69km²) in the year. Grassland reduced extremely within the same time period, occupying only 13.7% of the study area in 2015. Fig 3 shows the percentage coverage of the land-use types for the years 1991, 2002 and 2015. Table 4 also presents the land-use percentage and area changes for the two study periods. The study observed a drastic continued increased in urban areas, by 95.51% and 129.14% in the periods 1991–2002 and 2002–2015 respectively.

Table 4. Land-use percentage change and rate of change during the two study periods.

Percentage change (%)			Annual rate of change		Area change (km sq.)
LULC types	1991–2002	2002–2015	1991–2002	2002–2015	1991–2002	2002–2015
Water	9.65	16.16	0.88	1.24	17.94	32.95
Urban	95.51	129.14	8.68	9.93	385.38	1018.80
Grassland	-21.82	-66.30	-1.98	-5.1	-411.91	-978.50
Bareland	176.32	87.93	16.03	6.76	57.44	79.16
Shrubland	2.08	-12.77	0.19	-0.98	18.11	-113.26
Forest	445.23	-51.19	40.48	-3.94	52.00	-32.60
Agric	-47.81	-5.04	-4.35	-0.39	-118.97	-6.54

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Source: Fieldwork, 2020

3.3 Change detection analysis

Change detection statistics were performed to obtain the land use/land cover changes for each of the intervals: 1991–2002 and 2002–2015. The results are shown in Tables 5 and 6. Table 5 indicates that, out of the 1887.72 km² that was grassland in 1991, 995.69 km² was still grassland area in 1991 and the rest converted to urban and shrubland. The reduction in grassland during the period 1991–2002 was mainly due to the expansion of urban area and shrubland. Grassland area was converted into urban area of about 283.92 km² accounting for about 15% of the grassland area in 1991. Urban has gained from the area of shrubland of about 149.03km² representing about 17% of the shrubland in 1991. The main land use types converted into urban area during the period were grassland, shrubland and agriculture. Similarly, from 2002 to 2015, grassland, shrubland and agriculture areas continued to be converted into urban area as shown in Table 6.

Table 5. Change detection matrix of land use in the study area from 1991 to 2002, unit (km²).

	Water	Urban	Grassland	Bareland	Shrubland	Forest	Agric	Total 2002
Water	118.96	2.50	41.32	3.99	30.64	2.85	3.66	203.91
Urban	34.57	276.15	283.92	9.60	149.03	0.63	35.00	788.89
Grassland	14.50	54.64	995.69	8.36	307.29	3.25	92.10	1475.81
Bareland	8.79	18.32	30.09	4.41	22.21	0.03	6.17	90.02
Shrubland	6.76	43.92	471.11	5.77	280.96	0.76	77.78	887.06
Forest	0.51	0.43	39.58	0.05	12.88	3.95	6.28	63.68
Agric	1.89	7.56	26.00	0.41	65.95	0.21	27.86	129.87
Total 1991	185.97	403.51	1887.72	32.58	868.95	11.68	248.85	3639.26

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Source: Fieldwork, 2020

Table 6. Change detection matrix of land use in the study area from 2002 to 2015, unit (km²).

	Water	Urban	Grassland	Bareland	Shrubland	Forest	Agric	Total 2015
Water	143.84	37.32	17.64	5.72	28.51	0.93	2.89	236.86
Urban	13.09	656.02	636.94	59.06	369.12	11.79	61.66	1807.69
Grassland	21.52	9.94	334.50	2.38	88.81	23.35	16.81	497.31
Bareland	0.71	38.57	66.56	6.60	49.74	0.82	6.19	169.18
Shrubland	11.16	46.69	344.04	15.83	315.65	7.33	33.12	773.81
Forest	4.81	0.05	10.61	0.04	3.44	10.17	1.96	31.09
Agric	8.77	0.32	65.51	0.40	31.79	9.30	7.24	123.33
Total 2002	203.91	788.89	1475.81	90.02	887.06	63.68	129.87	3639.26

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Source: Fieldwork, 2020

3.4 Flood risk zones within the study area

Based on the topography, hydrology, land use/land cover and historical flood events of the study area, the flood risk zones of the area and the levels of risk were generated (Fig 4).

3.5 The trends of urbanization and frequency of flood disaster events in the study areas

The land use/land cover change analysis shows that urban areas keep increasing at the expense of forest and grassland which cause flooding in the area. For instance, urban areas increased from 11.1% in 1991 to 21.7% in 2002. This is about double in urban expansion within a period of 10 years. Whereas grassland was reduced by 11.4%, there was insignificant increment of 1.3% in forest land cover of the area during the same period. Besides, from 2002 to 2015, grassland, shrubland and agricultural lands continue to urban areas (Table 6). Coupled with these changes and unplanned development of physical structures which encroach on waterways, the risk of flooding in Accra is increased when there is rainstorm. Studies such as [3, 7, 33] confirmed issues of urbanization and floods as major urban problems in Greater Accra.

Table 7 shows the trajectory of flood events from 1990 to 2015 in the study area. The results show that 8 and 11 flood events occurred in the periods of 1991 to 2002 and 2002 to 2015 respectively. It is clear in the two periods that there is reoccurrence of flood events for the period of 2002 to 2015 and annual flood incidence is also consistent from 2007 up to 2015 whereas the period 1991 to 2002 does not have this consistency in the flood events. In 2011 and 2014 for instance, flood events reoccurred twice in each year. The patterns of increase in reoccurrence of floods seem to correlate with the sharp increase in urban areas culminating in reduction in grassland and forest cover of the 2002 to 2015 period. Other factors such as increase in rainfall and sea level rise contribute to flood risk in Accra [34]. However, literature further contends that flood risk in the study site has increased in recent years as a result of unregulated urbanization [3]. Notwithstanding this, rainfall records since 1960 till date have not increased and could not be a major factor for flood disaster risk [21, 33]. [3] further show that urbanization has increased upward since the 2000s and encroachment on waterways has been repeatedly reported as a reason for increase in flood disaster risk Accra [7, 34].

Table 7. Historical records of floods since 1955 and frequency of flood events between 1991 to 2002 and 2002 to 2015.

1990–2002 Period	2003–2015 Period
Flood events	Flood events
27 Nov. 1990	26-Mar 2007
15 July 1991	03-June 2007
18 Nov 1993	18-May 2008
5–6 June 1994	19 June 2009
04-July 1995	5 May 2010
13 June 1997	24-Feb 2011
28-June 2001	01-Nov 2011
09 June 2002	31-May 2013
	06-June 2014
	04-July 2014
	03-Jun 2015
Total: 8 flood events	Total: 11 flood events

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Sources: NADMO Disaster Reports.

This researched revealed that earlier studies have already mapped the flood risk zones in Accra as the centre of the study. [21] mapped out flood risk zones in the city of Accra using GIS and confirmed that medium to high flood risk zones constituted to about 40% of flood zones. However, our studies showed that urbanization has increased beyond those zones that were marked by those studies conducted earlier, and the frequency of flood occurrence has also increased. This correspondence means that more areas have been urbanized in an unplanned manner and more areas have become vulnerable to flood hazards thereby increasing the risk of flooding in the study site. Analysis of our research shows that the epicentre of flooding in the study area is the AMA which previous studies on flood risk revealed that urbanization with its consequences of encroachment on waterways results in the increase in flood occurrence [7]. From our analysis and with increase in urban expansion beyond the AMA, it can be envisaged that encroachment on waterways through unplanned development has increased and this suggests a positive correlation with the corresponding increase in frequency of flood occurrence in the study site.

4 Conclusions, limitations and recommendations

The findings revealed that the trend of urbanization increased in the Greater Accra Region for period of 1991 to 2015 and this corresponds with the increase in the frequency of flood events. The study mapped and analyzed urbanization of land use/land cover change in Accra for the periods of 1991–2002 and 2002–2015, using geospatial analytical techniques. Of the various land use land cover classes that were mapped and analyzed, it can be deduced that urban land cover area did not cover a large area in 1991 but it increased to become the largest land use/land cover surface of the study site in the year 2015. Out of historical flood events since 1955, between 1991 and 2015, flood disaster events were identified which indicated an increased in the pattern of flood occurrence in the study site. The analysis of the relationship between the pattern of urbanization and frequency of flood disaster events in the study area between 1991 and 2015 suggests that there is both an increase in urban land surface and the frequency of flood events. It was also observed that the pattern of urbanization in the study site took place in an unplanned style, where physical developments in waterways became high. This unplanned expansion in urban development resulted in encroachment on waterways and flood risk zone areas. The findings therefore suggest that the increase in urbanization corresponds with the increase in the frequency of flood disaster events in the study area from 1991 to 2015.

The main limitations of this study include the following. Due to this limitation, it is clear how much percentage is rate of urban land use land cover change. A future research should take up a a comprehensive quantitative analysis of these two processes of urbanization and flood disaster risk management can be considered in future studies using remote sensing and GIS. For urban planning and development policy, it is recommended that urbanization and flood disaster risk are a major environmental problem of the study site and need to be tackled. It is recommended land use policy decision makers should ensure that developers and stakeholders abide by the land use policies and regulations of the study area. This will ensure the growing expansion of urban areas can be minimized to reduce flood disaster risk in the study area.

Supporting information

S1 File. Description of supplementary material file.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

Acknowledgments

We acknowledge Centre for Remote Sensing and Geographic Information Services, University of Ghana, Legon for providing us information for this research.

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0292290.r001

Decision Letter 0

Mohammed Sarfaraz Gani Adnan

21 Jun 2023

PONE-D-23-15951“URBANIZATION AND FLOOD RISK ANALYSIS USING GEOSPATIAL TECHNIQUESPLOS ONE

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Reviewer #1: Partly

Reviewer #2: Partly

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #2: Yes

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Reviewer #1: This manuscript presented Urbanization and Flood Risk Analysis using Geospatial Techniques. The overall quality of this paper is worthy of publication. The authors could reply to general and scientific issues and revise their papers accordingly.

1. Is the author’s focus on urban/pluvial flood here? In the current version, it is pretty tricky to understand the type of flood. I’d suggest stressing this in the revision.

2. The abstract is not well written. Please emphasize the following contents: background, objectives, methods, results, and concluding remarks.

3. Research questions were not correctly indicated. What are the problems solved by the authors in their existing investigation? Please stress it. See these papers for your reference:

https://link.springer.com/article/10.1007/s11069-022-05357-0

https://www.sciencedirect.com/science/article/pii/S1674987122000780

4. The choice of the model should be justified.

5. Why does the scientific community cite this work? There is nothing observed regarding the new contribution of the findings other than selecting the case study.

6. Literature review is poorly done. The latest work on flood modeling should be well justified. Therefore, the literature review needs to be well-expanded.

7. The selection of the study area and data used in this paper need more justification. Like, Landsat 4 TM data has scale line errors in many cases. If the author faced the same issue, how did they solve it?

8. “To ensure consistency, the collected data was cleaned and formatted.” How? Need justification.

9. Have the authors experimented with additional classification schemes for constructing a flood risk map? Currently, they assigned the five classes map. Have they assessed the impact of using additional classes? If so, do the spatial distribution of the different classes in the flood risk map and the derived results change significantly?

10. The authors should also clearly explain how they classified their flood risk map into five groups. Changing the limits of the zones can alter the entire result of their study, so a justification is needed.

11. Finally, the authors should enhance the discussion section by discussing: (i) the implications of their findings in the context of the current trend (and necessity) to evaluate flood hazards and secondary effects of a specific phenomenon. (ii) can the approach of the present paper have practical usage for planners, and how can their findings be communicated? In other words, the authors should emphasize the added value of their paper in the context of the topic.

Reviewer #2: The research focuses on the analysis of urbanization and flood risk in the Greater Accra Region of Ghana. The study aims to map and analyze the trends of urbanization, identify flood risk zones, and analyze the relationship between urbanization patterns and flood disaster events from 1990 to 2015. The research also aims to contribute to the understanding of urbanization and flood disaster risk in the study area and similar regions. It emphasizes the importance of effective urban planning, land use policies, and regulations to minimize the expansion of urban areas and reduce flood disaster risk. I enjoyed reading the paper. However, I have some comments for further improvement of the paper. I suggest major revision

**********

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Reviewer #1: Yes: Dr. Md. Mahfuzur Rahman

Reviewer #2: No

**********

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Attachment

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Click here for additional data file.^{(58KB, pdf)}

PLoS One. 2023 Oct 20;18(10):e0292290. doi: 10.1371/journal.pone.0292290.r002

Author response to Decision Letter 0

2 Sep 2023

Reviewer #1’s comments:

This manuscript presented Urbanization and Flood Risk Analysis using Geospatial Techniques. The overall quality of this paper is worthy of publication. The authors could reply to general and scientific issues and revise their papers accordingly.

1. Is the author’s focus on urban/pluvial flood here? In the current version, it is pretty tricky to understand the type of flood. I’d suggest stressing this in the revision.

2. The abstract is not well written. Please emphasize the following contents: background, objectives, methods, results, and concluding remarks.

3. Research questions were not correctly indicated. What are the problems solved by the authors in their existing investigation? Please stress it. See these papers for your reference:

https://link.springer.com/article/10.1007/s11069-022-05357-0

https://www.sciencedirect.com/science/article/pii/S1674987122000780

4. The choice of the model should be justified.

5. Why does the scientific community cite this work? There is nothing observed regarding the new contribution of the findings other than selecting the case study.

6. Literature review is poorly done. The latest work on flood modeling should be well justified. Therefore, the literature review needs to be well-expanded.

8. “To ensure consistency, the collected data was cleaned and formatted.” How? Need justification.

Reviewer #2 comments:

The research focuses on the analysis of urbanization and flood risk in the Greater Accra Region of Ghana. The study aims to map and analyze the trends of urbanization, identify flood risk zones, and analyze the relationship between urbanization patterns and flood disaster events from 1990 to 2015. The research also aims to contribute to the understanding of urbanization and flood disaster risk in the study area and similar regions. It emphasizes the importance of effective urban planning, land use policies, and regulations to minimize the expansion of urban areas and reduce flood disaster risk. I enjoyed reading the paper. However, I have some comments for further improvement of the paper. I suggest major revision

RESPONSE: Thank you very much for all the valuable comments by the reviewer

Response to Reviewer #1’s comments:

1. Is the author’s focus on urban/pluvial flood here? In the current version, it is pretty tricky to understand the type of flood. I’d suggest stressing this in the revision.

RESPONSE:

Flash floods are the common major problem in the Greater Accra, influenced by severe localized storms and that is the focus of this research.

2. The abstract is not well written. Please emphasize the following contents: background, objectives, methods, results, and concluding remarks.

RESPONSE:

Contemporarily, flood disasters are a critical global problem. More especially, urban floods are a developmental problem for metropolitan areas in the global south and the flood disasters in Accra are illustrative case. However, literature on geospatial analysis of the relationship between urbanization and flood disasters in Accra appears unclear. Data on flood disasters and urbanization were obtained from existing sources and analyzed using geospatial techniques. The main data for this study were Landsat images and flood disaster statistics. Three cloud-free spatial resolution of 30m Landsat satellite surface reflectance images of 1991, 2002 and 2015 were acquired from the United States Geological Survey (USGS) Earth Explorer.

3. Research questions were not correctly indicated. What are the problems solved by the authors in their existing investigation? Please stress it. See these papers for your reference:

https://link.springer.com/article/10.1007/s11069-022-05357-0

https://www.sciencedirect.com/science/article/pii/S1674987122000780

Response: The main focused on addressing the specific research objectives (see lines 169 -176).

This research has three specific research objectives. The first objective is to map and analyze the trends of urbanization as a land use land type in Greater Accra for the periods of 1991 -2002 and 2002 – 2015 using geospatial techniques. The second objective is to map flood risk zones, identify the flood disaster events between 1990 and 2015 and analyze the trends of flood disaster risk in Greater Accra. The third objective is to analyze the relationship between the pattern of urbanization and the increase in flood disaster events from 1990 to 2015. The aim of this research is to contribute to research, policy and practical management of urbanization and flood disaster risk in the study site and other areas with similar conditions.

4. The choice of the model should be justified.

RESPONSE: Myriad of studies investigated the menace of flooding in Accra without specific emphasis on the relationship between urbanization and flood disasters using geospatial techniques. Research about such relationship is useful to inform disaster risk managers and urban development planners for better flood disaster risk reduction. Seemingly, the literature indicates flooding as a big problem in Greater Accra as well as its causes, impacts and management challenges (Karley, 2009; Rain et al., 2011; Jha et al., 2012; Amoako and Boamah, 2015; Douglas, 2017). The literature further attributes the floods in Accra to the impacts of climate change (Rain et al., 2011). The flooding Accra is typically pluvial flooding caused by localized rains, poor and inadequate drainage, physical development on waters among others (Karley, 2009; Okyere et al., 2013). Studies applied remote sensing and GIS techniques to investigate the issue of flooding in Accra but did not specifically focus the flood disaster risk and urbanization relationships (Nyarko, 2002; Konadu and Fosu, 2009; Jankowska et al., 2011; Owusu et al., 2013; Yeboah et al., 2017).

5. Why does the scientific community cite this work? There is nothing observed regarding the new contribution of the findings other than selecting the case study.

RESPONSE: Contemporarily, flood disasters are a critical global problem. More especially, floods are a developmental problem for urban regions in the global south and the flood disasters in the Greater Accra in Ghana are an illustrative case. However, literature on geospatial analysis of the relationship between urbanization and flood disasters in the Greater Accra appears unclear. The aim of this research will to contribute to research, policy and practical management of urbanization and flood disaster risk in the study site and other areas with similar conditions. Understanding the relationship between urbanization as a land use/land cover change and the occurrence of flood disasters in Great Accra would provide evidence for urban development planners, policy makers and flood managers to coordinate for effective response to the menace of urbanization and flood disaster risk. This research will further to literature and academic discussion in the areas of geospatial analysis, urban flood disaster risk management and urban geography in general.

6. Literature review is poorly done. The latest work on flood modeling should be well justified. Therefore, the literature review needs to be well-expanded.

RESPONSE: Seemingly, the literature indicates flooding as a big problem in Greater Accra as well as its causes, impacts and management challenges (Karley, 2009; Rain et al., 2011; Jha et al., 2012; Amoako and Boamah, 2015; Douglas, 2017). The literature further attributes the floods in Accra to the impacts of climate change (Rain et al., 2011). The flooding Accra is typically pluvial flooding caused by localized rains, poor and inadequate drainage, physical development on waters among others (Karley, 2009; Okyere et al., 2013). Studies applied remote sensing and GIS techniques to investigate the issue of flooding in Accra but did not specifically focused the flood disaster risk and urbanization relationships (Nyarko, 2002; Konadu and Fosu, 2009; Jankowska et al., 2011; Owusu et al., 2013; Yeboah et al., 2017). Asumadu-Sarkodie, Owusu and Rufangura (2015) analyzed the causes of flood in Accra and the suitable structural measures for mitigating flood impacts. The floods usual from emanated several hours of localized rainfall. The authors further revealed that an integrated flood risk management approach to dealing with flood impacts. The monthly precipitation in Accra was projected increase from 160 mm in 1991-2010 to 200 mm in 2011-2020. Ullah et al. (2022) further argued that an effective multi-hazard risk mitigation strategy would require spatiotemporal analysis individual hazards and their interactions using geospatial techniques. The authors proposed a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks. Nkonu et al. (2023) used GIS-based model for flood vulnerability analysis in the Accra Metropolitan Area. The analysis revealed that areas with high flood vulnerability increased between 2007 and 2020, and the high flood vulnerability zones are largely located in the south-central and south-western regions. Ackom, Adjei and Odai (2020) assessed the extent and trends of changes in the urban environment of Odaw River Basin from 1991 to 2016 in Accra, which revealed changes in rates of land degradation during the period with over 200% upsurge in settlement. Sajjad, Lu, Aslam, and Ahmad (2023) applied geospatial techniques to model flood extent as well as flood duration in District Dera Ghazi Khan, Pakistan. The results showed that the flood lasted for nearly 5 weeks in the study area. Results enabled identification of inundated areas to allow for emergency responses to newly flooded areas.

RESPONSE: The study area was selected for the research due to its increasing urbanization and protracted annual flood disasters in recent years. The main data for this study were Landsat images and flood disaster statistics. Three cloud-free spatial resolution of 30m Landsat satellite surface reflectance images of 1991, 2002 and 2015 were acquired from the United States Geological Survey (USGS) Earth Explorer site (HTTP:\\\\glovis.usgs.gov). These images were extracted to assess temporal and spatial changes in the study area. Landsat TM, ETM+ and Landsat 8 images were considered due to their high resolutions which would enable changes of urban areas from other land use/land cover surfaces to be detected. These periods were chosen because the negative impacts of urbanization in Accra such as flood disasters became serious from the 1990s and these impacts are a major challenge for developers and other stakeholders in the area. Due to the cloud-free imagery that were carefully selected and downloaded for the investigation, the analysist did not encounter the issue of scale line errors in any of the images.

8. “To ensure consistency, the collected data was cleaned and formatted.” How? Need justification.

RESPONSE: Data on topography, hydrology, land use and historical flood events are used to map flood risk. To ensure consistency, the collected data were cleaned and formatted using the Hexagon Erdas Imagine software version 15. The techniques used in Erdas Imagine to clean and format the satellite images includes Radiometric corrections which are crucial for removing the atmospheric effects and sensor errors that can result in inconsistent brightness levels in satellite images. These radiometric corrections such as histogram matching, contrast stretching, and gamma correction enhance image details and ensure consistency in radiometric values (Xu & Lenhardt, 2020). Moreover, Geometric corrections were employed to correct distortions and align images accurately with the Earth's surface. Further, the data was georeferenced, and resampled to correct geometric errors caused by sensor orientation, terrain elevation, or projection issues (Hagos et al., 2022). This ensures that images are accurately aligned and can be overlayed with other geographic datasets. Notwithstanding, the Noise and Haze Removal/reduction was also employed using the Erdas Imagine software to filter or remove noise and clouds while preserving image details. These filter help improves the visual quality of satellite images and reducing distractions caused by noise

RESPONSE: The authors considered several scenarios regarding the categorization or the choice of the five classes for the flood risk map, even though it is the most appropriate and widely used classification scheme. Thus, when more than five classes were used, the result did not change significantly. It kept on giving the same output and results.

RESPONSE: Creating a flood risk map requires an effective classification scheme that accurately represents the different levels of flood risk (Osman & Das, 2023). A good classification scheme should be easy to understand, based on reliable data sources, and allow for detailed analysis and decision-making (Farhadi & Mohammad, 2021). To accurately depict the flood risk levels in an area, flood risk maps are divided into different classes based on the likelihood and severity of flooding. The five classes that are commonly used in flood risk mapping are Very High, High, Moderate, Low, and Very Low (Farhadi & Mohammad, 2021). These classifications were based on the probability of flooding, the potential severity of damage from flooding, and the vulnerability of the area to flood hazards. This distinct classification increases accuracy, multiple perspectives, improved communication, accessibility, and flexibility in flood risk management. The classifications also encourages a standardization of communication between policymakers and the community, streamlines flood risk mitigation and adaptation strategies (Weday et al., 2023). For example, areas that are likely to experience frequent flooding events, such as those near rivers or in low-lying coastal regions, are typically classified as Very High or High risk. These areas are likely to experience severe damage during flood events and require significant resources to mitigate risk. Moderate risk areas, on the other hand, are those that are less likely to experience frequent flooding events but may still be vulnerable to severe flooding (Osman & Das, 2023). These areas may be located near smaller streams or rivers, or in areas with high soil saturation or poor drainage. While the likelihood of flooding is lower in these areas, property damage and public safety are still a concern. Low and Very Low risk areas are those that are typically located at higher elevations or further from rivers, streams, or coastlines. These areas are less vulnerable to flooding, but still be affected by flash floods or severe storms. Scholars argue that the use of five classes for flood risk map provides greater precision in identifying the level of flood risk in different areas (Nkwunonwo et al., 2020, Weday et al., 2023). This allows for more effective planning and implementation of mitigation and adaptation strategies. Moreover, the five classes offer multiple perspectives of the level of flood risk in different areas. This helps policymakers understand the severity and complexity of flooding, which is essential for developing efficient responses. Also, it provides a standardized communication tool for stakeholders. This helps them to understand and interpret the flood risk map, leading to a more coordinated and effective response to floods. Further, the five classes allow for a simplified version of the flood risk map that is easily accessible to different stakeholders. This makes it easier for them to understand and interpret the information provided as they do not need any technical knowledge. Additionally, Xu and Lenhardt (2020) noted that use of five classes offers flexibility in the classification of flood risk depending on specific variables such as location, severity, and frequency of flood events. It also allows for the inclusion of other factors that could influence flood risk such as infrastructure and natural barriers (Nkwunonwo et al., 2020)

RESPONSE: The implications of this research findings in the context of the current trend would help evaluate flood hazards and secondary effects of a specific phenomenon. The increase in urban land use/land cover change from 95.51% in the period 1991-2002 to 129.14% in the period of 2002-2015 shows the level of urban physical development is high. This means that urban development has eaten up other land uses/land covers which if not critically monitored, even essential vegetation land cover land use could be replaced with buildings and urban development. It is the build space in the Greater Accra region. The pattern of urbanization is unplanned and very high, where physical developments in waterways are common and interfere with flow water in waterways The pattern of flood disasters increased from 1991 to 2015 with evidence showing two years having repeated flood events. This means implies a positive upward increase in flooding and urbanization in the study site. Thus, if quick action is not taken swiftly, a continues increase uncontrolled urban development can translate reduction in urban vegetation, physical development on waterways and other land covers. Urban planners, developers, policy makers and local communities need to make conscious efforts to deal with unregulated urbanization. The findings of this research will be disseminated through online platforms, presentations and discussed at academic and non-academic seminars.

Reviewer #2’s comments:

RESPONSE: Many thanks for the comments. We have revised the manuscript per your comments.

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PLoS One. doi: 10.1371/journal.pone.0292290.r003

Decision Letter 1

Mohammed Sarfaraz Gani Adnan

18 Sep 2023

“URBANIZATION AND FLOOD RISK ANALYSIS USING GEOSPATIAL TECHNIQUES

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PLoS One. doi: 10.1371/journal.pone.0292290.r004

Acceptance letter

Mohammed Sarfaraz Gani Adnan

6 Oct 2023

PONE-D-23-15951R1

“URBANIZATION AND FLOOD RISK ANALYSIS USING GEOSPATIAL TECHNIQUES

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PERMALINK

Urbanization and flood risk analysis using geospatial techniques

Raphael Ane Atanga

Vitus Tankpa

Isaiah Acquah

Roles

Abstract

1 Introduction

2 Materials and methods

2.1 Description of the study area

Fig 1. Location of study area.

2.2 Data sources

Table 1. Characteristics of the satellite images used for the investigation.

2.3 Pre-process of Landsat images

2.4 Classification and accuracy assessment

Table 2. Description of land use/land cover types.

2.5 Land use/land cover change detection

2.6 Flood risk mapping

3 Results and discussion

3.1 Spatial distribution of land use/land cover of the study area

Fig 2. Land use/land cover distribution in three time points.

Table 3. Summary of land use/land cover type structure of the study area.

3.2 Nature, extent and rate of land/use change

Table 4. Land-use percentage change and rate of change during the two study periods.

Fig 3. Land-use type percentage coverage for 1991, 2002, and 2015.

3.3 Change detection analysis

Table 5. Change detection matrix of land use in the study area from 1991 to 2002, unit (km2).

Table 6. Change detection matrix of land use in the study area from 2002 to 2015, unit (km2).

3.4 Flood risk zones within the study area

Fig 4. Flood risk zones and levels of the area.

3.5 The trends of urbanization and frequency of flood disaster events in the study areas

Table 7. Historical records of floods since 1955 and frequency of flood events between 1991 to 2002 and 2002 to 2015.

4 Conclusions, limitations and recommendations

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Mohammed Sarfaraz Gani Adnan

Roles

Author response to Decision Letter 0

Decision Letter 1

Mohammed Sarfaraz Gani Adnan

Roles

Acceptance letter

Mohammed Sarfaraz Gani Adnan

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Table 5. Change detection matrix of land use in the study area from 1991 to 2002, unit (km²).

Table 6. Change detection matrix of land use in the study area from 2002 to 2015, unit (km²).