Trouble in Paradise: Natural Disaster Preparation in Jamaica: Looking at Flooding, Landslides and Human Vulnerability

The above poster was made by Mwahaki King for the GIS at Tufts University Poster Exhibition 2016 (GIS@Tufts) and has also been published on the GIS@Tufts website here: 
https://sites.tufts.edu/gis/files/2016/01/King_Mwahaki_MCM1009_2016.pdf

The purpose of the project was to ascertain high risk areas and thus areas prioritisation in Jamaica during natural disasters; specifically landslides, flooding and hurricanes. High risk areas were determined primarily by weak housing infrastructure, access to hospitals and environmental factors such as the slope of the terrain and proximity to rivers.

The maps were made by Mwahaki King using ArcGIS software and the poster itself was produced using Microsoft Publisher.

Data Sources:

GDAM, DIVA-GIS, CARISKA

• GDAM: http://www.gadm.org/
• DIVA-GIS http://www.diva-gis.org/gdata
• CARISKA (N.B. This website is originally in French) http://ckan.c-read.net/fr/organization/cariska

The accompanying paper can be found below, which further outlines Jamaica's environmental background, conclusions, recommendations and limitations of the project.

Mwahaki King

May 2016

B.A. Diplomacy and World Affairs || Occidental College

M.A. Law and Diplomacy ||  The Fletcher School, Tufts University 

Natural Disaster Preparation in Jamaica: Looking at Flooding, Landslides and Human Vulnerability

INTRODUCTION

Jamaica is largely susceptible to hurricanes, with a specific hurricane season running from June 1 – November 30. Even without the development of an actual hurricane there can be severe devastation due to flooding and landslides. “It has been estimated that…some US$15 million are spent annually to repair the landslide damage to roads alone”[1] and for historical and socio-economic reasons, both rural and urban areas have large squatter settlements that are severely impacted by these environmental hazards. The settlements are usually on precarious pieces of land highly susceptible to flooding or landslides; and due to the harsh economic reality of the inhabitants, usually very poorly built structures. 

The nature of squatter settlements in Jamaica is tied to the nation’s history of slavery and the socio-economic climate that followed emancipation and apprenticeship in 1838: As Jimmy Tindigarukayo elucidates in “The Squatter Problem in Jamaica”:

Jamaica has had a long history of squatting, dating as far back as the emancipation period in the 19th century. After the abolition of slavery in 1833, systematic attempts were made by the owners of plantations and the colonial administration in Jamaica to ensure that the newly freed slaves had no easy access to land…The termination of the apprenticeship system in 1838 relieved former slaves of any legal obligation to work for their former masters. This then led to their voluntary exodus from plantations to subsistence agriculture, utilizing small holdings acquired either through purchase or through illegal occupation. The labour shortage on plantations resulting from this mass exodus led to the abandonment of estates by some planters which, in turn, created idle lands. This together with vacant crown land, enticed the landless former slaves to acquire more illegal holdings for both building homes and for subsistence agriculture. Thus a stage was set for what later came to be known as "the squatting problem" in Jamaica. In fact, by 1866 squatting had become institutionalized as a form of land tenure in Jamaica [2].

Furthermore, rural to urban migration, housing shortages, economic hardships, political support [3] and the availability of idle land [4] have only amplified the squatter community presence in the modern era.

According to the Jamaican Ministry of Transport, Works and Housing “one quarter of Jamaica’s population (675,000) live in squatter settlements. Estimates also indicate that one in every three urban dwellers live in squatter settlements. Settlements are characterized by lack of/poor sanitation, inadequate physical infrastructure/poor quality housing, impoverished dwellings, high levels of unemployment and underemployment”[5]

Spatial questions attempting to answer:

• What areas are prone to flooding and do vulnerable populations live in or near these areas?
• What areas are prone to landslides and do vulnerable population live in or near these areas?
• How far are vulnerable populations from hospitals in the case of emergency during either of the disasters outlined above?

Purpose: The goal of the analysis is to establish the High Risk Areas specifically for Vulnerable Populations. 

Thus, given the poverty and weak infrastructure facing squatter communities, as well as the key role they play in the nation’s political framework and the large percentage of the population that they comprise; squatter communities were the vulnerable population at the center of this analysis. The analysis attempts to address the environmental risk posed to these vulnerable communities by flooding and landslides and thus determine the areas of the country that present the highest risk for vulnerable populations. This will provide policy makers and environmental planners such as the Office of Disaster Preparedness, The Ministry of Transport, Works and Housing and National Environment Planning Agency with areas to prioritize when addressing disaster management.

Projection: 

All the maps used in the poster component of this project were done in the following projection:

Coordinate System: NAD_1983_UTM_Zone_18N

Projection: Transverse_Mercator

Linear Unit: Meter

METHODOLOGY

To establish the High Risk Areas specifically for Vulnerable Populations, two elements needed to be addressed: a risk analysis related to landslides and flooding, and a vulnerability analysis related to the population that live in weak infrastructure and their proximity to hospitals in the event of an emergency. Separately, these two models provide important information for policy planning regarding environmental risks and human vulnerability, but addressed together they demonstrate the total high risk areas for vulnerable populations. 

To Address the Weak Infrastructure Population and their Access to Hospitals

First, the Kernal Density Tool was used on the Squatter Housing Layer to create a new layer that would demonstrate the density of squatter communities nationwide. Then, using the Reclassify Tool, the Density layer was reclassified on a scale of 1 to 5, 1 representing a low concentration of communities with weak infrastructure and thus low vulnerability, and 5 representing a high concentration of such communities and thus a high vulnerability.

Similarly, the Kernal Density Tool was used on the Hospitals Layer to develop a new layer that would provide the density of hospitals nationwide and then this layer was re-classed on a scale of 1 – 5. The difference here being that 1 represented a low vulnerability because there were a high concentration of hospitals in that region and 5 represented a highly vulnerable areas due to the low concentration of hospitals. A low concentration of hospitals would make access to difficult to impossible in the event of an emergency. The Euclidean Distance Tool was also run on Hospital Data to determine the relative distance of hospitals.

To determine the Total (Unweighted) Vulnerability of The Weak Infrastructure Population, the reclassified Housing layer and the reclassified Hospital Layers were added into the Raster Calculator.

To Address the Environmental Risks

1. FLOODING

The Euclidean Distance tool was run on the Rivers Layer to create a Distance to Rivers Layer, then reclassified on scale of 1 – 5, from lowest to highest risk. The DEM Elevation Layer was then reclassified on a scale of 1 – 5 from lowest to highest risk. It is important to note that during the reclassification, “Reverse New Values” needed to be used so that the lowest values (-3 meters to 200 meters) would be represented by a 5 demonstrating the extreme risk low elevations pose to increasing the likelihood of flooding. The Reclassified Distance to Rivers layer and the Reclassified Elevation layer were then added into the Raster Calculator to create the Total Risk of Flooding Layer.

2. LANDSLIDES

To determine the risk for landslides the DEM Elevation layer was used once again, but in this instance to obtain the danger posed by steep slopes. According to joint research between The University of the West Indies and the British Department for International Development (DFID), landslides tend to occur on slopes between 10 – 35 degrees, with different types of landslides occurring at varying degrees:

Rock falls occur most frequently where highly fractured rock occurs along road cuts with slopes greater than 30° …Debris falls are common across the area and can occur in weathered bedrock, lithosols and colluvial debris…on slopes of more than 20°…Earth slides are likely to occur on slopes above 10 - 15° [6]

As such slopes found in the analysis to be below 10 degrees were deemed to pose little to no risk in the development of landslides. To get the slope degrees and include them in the environmental risk analysis, the Slope Tool was used. The DEM layer was used as the Input Raster and the Output Measurement was set to DEGREE. The Slope Layer this step created was then reclassified on a scale of 1 – 5 with one being relatively gentle slopes which posed no threat of landslides and 4 and 5 being much steeper slopes which posed significant risk for the development of landslides (between 10 – 36° in this analysis).

3. TOTAL ENVIRONMENTAL RISK

To determine the complete environmental risk that landslides and floods pose, the ‘Total Risk of Flooding” Layer and “Reclassified Slope” Layer were both added in the Raster Calculator.

To answer the original and overarching purpose of this analysis i.e. what are the high risk areas for vulnerable populations; the “Total Vulnerability of the Weak Infrastructure Population” Layer needed to be added with the “Total Environmental Risk” Layer, using the Raster Calculator. The scores that resulted from this calculation, from lowest to highest would demonstrate the areas of Jamaica that posed the least and the most risk to the nation’s most vulnerable citizens.

The table below was used to outline the necessary factors for analysis: 

Factors	1 Very Low Risk	2 Low Risk	3 Moderate Risk	4 High Risk	5 Very High Risk
Distance to Rivers	> 25 miles	15 - 25 miles	5 - 15 miles	1 - 3 miles	< 1 mile
Slope Degree	0 - 2 degrees	2 - 5 degrees	5 - 10 degrees	10 - 20 degrees	20 - 36 degrees
Elevation	> 1000 m	750 - 1000 m	500 -750 m	200 - 500 m	< 200 m
Distance to Hospitals	< 0.5 miles	0.5 - 1 mile	1 - 3 miles	4 - 10 miles	> 10 miles
Number of Hospitals	> 0.0742	0.0556 - 0.0742	0.03712 - 0.0556	0.01856 - 0.03712	0 - 0.01856
Number of Squatter Communities	< 0.1548	0.1548 - 0.3097	0.3097 - 0.4645	0.4645 - 0.6194	0.6194 - 0.7743

RESULTS & DISCUSSION

Human Vulnerability:

The vulnerability score was calculated based on the Reclassified Housing and Reclassified Hospital layers. As the layers had been reclassified on a scale of 1 – 5, the vulnerability score was produced with a range of 3 – 15. Three represented the least vulnerable and 15 represented the most vulnerable communities. The vulnerability increased due to a lack of hospitals further up the scale.

Environmental Risk:

The flooding risk score was calculated using the Reclassified River Layer and the Reclassified DEM Elevation Layer. As the layers had been reclassified on a scale of 1 – 5, the vulnerability score was produced with a range of 2 – 10. A new “Total Flooding Risk” Layer was created. Then this “Total Flooding Risk” Layer and the “Reclassified DEM Slope” Layer were added to the Raster Calculator to determine the Total Environmental Risk from both flooding and landslides. The DEM Slope had been reclassified on a scale of 1 – 5, so the scores for the “Total Environmental Risk” range from 3 – 15.

The final “High Risk Areas for Vulnerable Populations” Map was based on a raster calculation of “Total Human Vulnerability” and “Total Environmental Risk”. This produced a score of 6 – 30 with 6 providing the least risk and 30, the most.  

PARISH	RISK LEVEL
Manchester, Kingston, St. Ann, St. Catherine	Low
Trelawny, Clarendon, Hanover, St. Andrew	Moderate
Westmoreland, St. James, St. Mary	High
St. Thomas, Portland	Very High Priority/Critical

The analysis showed that squatter communities in the parish of Manchester were the least at risk. While the communities are in a mountainous region, the steepness of the slope is actually rather small (between 0 – 9°) and as noted before landslides in Jamaica generally occur on slopes beginning at 10°. Additionally, there are more hospitals available in Manchester available to the surrounding communities than in Eastern parishes of Portland, St. Thomas or St. Mary. Thus, providing the Manchester communities with greater safety in the event of an emergency. There are also far fewer rivers in Manchester than in the Eastern region of the island, thus providing fewer potential sources of flooding. 

While highly populated, the squatter communities in the capital Kingston, and neighboring St. Andrew are at a lower risk because of their closer proximity to hospitals and the relative flatness of the terrain. While a few settlements in St Andrew are located in mountainous areas, the majority of the Kingston and St. Andrew settlements are located in or around the Liguanea Plain beneath the mountains. Thus, several of the issues in those communities, while highly important, are man-made rather than natural hazards which come from the high density of the impoverished population, weak infrastructure and poor sanitation; such as crime and water borne diseases. Concerning environmental issues, greater attention needs to be paid to impoverished rural squatter communities, as will be discussed further in the Conclusion and future recommendations.

CONCLUSION 

Limitations:

It must be said that Jamaica data was exceedingly difficult to obtain. I was able to get population data, squatter community data, administrative data and some environmental data. Regarding the environment, I was able to utilize water and elevation data. However, I was not able to acquire soil data which would have given greater depth and complexity to the both the landslide and flooding analyses as different soil types can increase or decrease the likelihood of these disasters. Furthermore, while there are certainly economically vulnerable populations outside of squatter settlements, specific household income data was unavailable. This made it impossible to expand the analysis of economically vulnerable populations in this project, beyond the squatter communities. 

Recommendations:

To provide areas of prioritization for policy makers, The Zonal Statistics Tool was applied to the final “High Risk Areas for Vulnerable Populations” Layer to determine the average risk score per Jamaican parish. This demonstrated the necessity to prioritize government funding and resources in the rural parishes of Portland and St. Thomas as areas of highest concern. While these parishes have fewer squatter communities than Kingston or St. Andrew, the urban centers of the nation; the squatter communities in Portland and St. Thomas are far more vulnerable because they have little to no access to hospitals while living in areas that are extremely susceptible to both flooding and landslides due to the mountainous terrain and proximity to rivers. The government must focus on prioritizing the construction of hospitals in these areas, as both parishes only have one hospital each, compared to 14 in Kingston and St. Andrew.

DATA SOURCES

GDAM, DIVA-GIS, CARISKA

• GDAM: http://www.gadm.org/
• DIVA-GIS http://www.diva-gis.org/gdata
• CARISKA (N.B. This website is originally in French) http://ckan.c-read.net/fr/organization/cariska

REFERENCES:

Hall, Desmond. “Squatting in Jamaica: An Overview” Department of Sociology, Psychology & Social Work University of the West Indies, Mona Campus.

 << https://www.scribd.com/doc/89728192/Squatting-in-Jamaica >>

Tindigarukayo, Jimmy. “The Squatter Problem in Jamaica”. Social and Economic Studies 51.4 (2002): 95–125. Retrieved from << http://www.jstor.org/stable/27865304 >>

Northmore K J, Ahmed R, O’Connor E A, Greenbaum D,  McDonald A J W, Jordan C J, Marchant A P, and Marsh S H. “Landslide Hazard Mapping: Jamaica Case Study” British /Geological Survey, Department for International Development DFID, University of the West Indies. Technical Report WC/00/10 Overseas Geology Series, DFID Project No. R6839. << http://www.bgs.ac.uk/research/international/dfid-kar/WC00010_col.pdf >> 

FOOTNOTES:

1. Northmore K J, Ahmed R, O’Connor E A, Greenbaum D, McDonald A J W, Jordan C J, Marchant A P, and Marsh S H. “Landslide Hazard Mapping: Jamaica Case Study” British Geological Survey, Department for International Development DFID, University of the West Indies. p.4 

2. Tindigarukayo, Jimmy. “The Squatter Problem in Jamaica”. Social and Economic Studies pp.99 - 100

3. “Because squatters are many and concentrated in some specific areas, they have increasingly become attractive to the two major political parties in Jamaica. As a survival strategy, almost every squatter settlement in Jamaica has had to declare its political allegiance to either the Jamaica Labour Party (JLP) or the Peoples' National Party (PNP), especially during elections. And to ensure continued loyalties, party leaders have often supported and enhanced the activities their respective squatter clientele” Tindigarukayo, Jimmy. “The Squatter Problem in Jamaica”. Social and Economic Studies pp. 101 - 102

4. Tindigarukayo, Jimmy. “The Squatter Problem in Jamaica”. Social and Economic Studies pp. 101 - 102

5. Hall, Desmond. “Squatting in Jamaica: An Overview” Department of Sociology, Psychology & Social Work << https://www.scribd.com/doc/89728192/Squatting-in-Jamaica >> 

6. Northmore K J, Ahmed R, O’Connor E A, Greenbaum D, McDonald A J W, Jordan C J, Marchant A P, and Marsh S H. “Landslide Hazard Mapping: Jamaica Case Study” British Geological Survey, Department for International Development DFID, University of the West Indies. pp 14 -18