Grebby, S, Jordan, C J, and Dijkstra, T. 2015. Risk information services for Disaster Risk Management (DRM) in the Caribbean - Service utility document. British Geological Survey Technical Note, OR/15/061.
Numerous data layers were incorporated into 11 map-based EO information products that were delivered through the implementation of three Services for disaster risk management in the Caribbean region. These Services are summarised in Table 1. Services 1 and 2 deliver key information — including landslide inventories, land use/land cover maps, elevation data and information on rivers and streams — for input to landslide and flood hazard assessments undertaken within the WB-led CHARIM project (van Westen, 2014[1]). Service 3 delivers elevation information for input to flood hazard assessments for Belize, also undertaken within the CHARIM project. More detailed descriptions of the Services and their associated EO information products are provided in the following sub-sections along with associated Service Readiness information published in Jordan & Grebby (2014)[2] and Operational Documentation published in Jordan et al. (2015)[3].
Table 1 Summary of the Services
Service Number
Service Description
Service Coverage
1
Land use/land cover mapping
St. Lucia, Grenada, St. Vincent and the Grenadines
2
Hazard mapping to support landslide risk assessment
St. Lucia and Grenada
3
Digital Elevation Model
Belize
Service 1: Land use/land cover mapping
The objective of Service 1 was to generate land use/land cover maps (including water features and road basic networks) for St. Lucia, Grenada, and St. Vincent and the Grenadines by exploiting recent high-resolution or very high-resolution optical satellite imagery. The mapping was undertaken using a combination of Pleiades (spatial resolution of 0.5 m panchromatic and 2 m multispectral) and RapidEye (5 m) satellite imagery, acquired from the relevant providers through the ESA Third Party Mission (TPM) scheme.
Service 1 demonstrates the ability to produce high-resolution land use/land cover maps remotely from EO data using a largely automated processing method. The primarily benefits of this approach are increased cost and time effectiveness in comparison to traditional field based mapping, and the ability to overcome terrain accessibility issues that commonly restrict field surveys in densely vegetated tropical environments and rugged terrain. The maps delivered by this Service provide a more contemporary snapshot of land cover/land use than the existing maps produced by The Nature Conservancy Mesoamerica and Caribbean Region project (Helmer et al., 2007[4]; 2008[5]), while also providing an order of magnitude increase in spatial resolution (2 m compared to 30 m). More detailed and recent land use/land cover information has been beneficial to the CHARIM project because it was used to better understand the factors controlling landslides and consequently improve the landslide susceptibility modelling. Beyond hazard risk, EO-derived land use/land cover information delivered by this Service has a wide spectrum of uses. For example, such information can be used for planning purposes, asset management and conservation. Given its semi-automated nature, the mapping approach implemented in this Service can be readily applied to monitor change over time.
Prior to delivery, the land use/land cover information products were quality checked and subject to an initial validation (Jordan et al., 2015[3]). Quality checking generally comprised evaluating whether the products satisfied the specified user requirements with regards to the minimum coverage of the areas of interest (AOIs) and thematic accuracy. The thematic accuracy of the land use/land cover maps was determined using the conventional remote sensing approach of deriving confusion matrices (Congalton, 1991[6]). Specifically, the land use/land cover class identities of a sample of validation pixels in the map were compare with their ‘true’ land use/land cover class to compute the overall accuracy (i.e., the percentage of validation pixels correctly classified). The thematic accuracies were then further corroborated with the aid of observations made in the field during a 10-day visit to the region in October 2014. This involved visiting numerous randomly selected locations on the ground to cross-check the actual land use/land cover type with that on the map.
Ahead of delivery, the land use/land cover data was released to the CHARIM project partners at ITC for initial validation. This initial validation involved evaluating the suitability of the define land use/land cover classes for hazard assessment and checking for significant misclassifications or artefacts in the maps.
The EO information products delivered through Service 1 are described in Figures 1–3.
Service 2: Hazard mapping to support landslide risk assessment
The objective of Service 2 was to generate ground-truthed landslide inventories and digital elevation models (DEMs) for St. Lucia and Grenada. The landslide mapping was undertaken using a combination of multi-temporal, pan-sharpened Pleiades (spatial resolution of 0.5 m) and RapidEye (5 m) satellite imagery, acquired from the relevant providers through the ESA TPM scheme. The DEMs were generated using ASTER stereo satellite imagery (30 m) in conjunction with ancillary elevation data (e.g., airborne LiDAR, contour heights, SRTM DEM).
Service 2 demonstrates the ability to utilise very-high resolution, multi-temporal optical satellite imagery for landslide inventory mapping. Implementation of this Service has led to the delivery of annual landslide inventories for St. Lucia for the period 2010–2014 and a single inventory for Grenada (also covering the same period). Mapping landslides remotely from satellite imagery is again far more time and cost effective than traditional field-based mapping, and it provides a means of readily accessing the inhospitable terrain in which landslides typically occur. The very-high resolution Pleiades satellite imagery offers advantages over satellite imagery with a more moderate spatial resolution (e.g., Landsat) because it enables small landslides (<100 m2) to be mapped in detail. Furthermore, the very-high resolution imagery provides sufficient detail to allow the generation of geomorphological maps that can be attributed with information such as the likely nature of deformation and a timeline of event progression. This Service also provides a practical means of monitoring landslide activity on an annual basis, which helps gain a better understanding of the landscape response to trigger events (e.g., hurricanes). Information on trigger event response, spatial distribution, magnitude-frequency, type of movement that can be obtained through this Service is very valuable for the development of landslide susceptibility maps and landslide risk assessments. Accordingly, the landslide inventories delivered in Service 2 comprised crucial information that was input to the landslide susceptibility modelling under the CHARIM project. Service 2 also delivered accurate national-scale 30 m DEMs generated from optical satellite imagery. This Service therefore demonstrates a cheaper, alternative approach to generating DEMs at this scale over large areas in comparison to ground-based GPS or airborne LiDAR surveys. The DEMs and derived information (e.g., slope, relief) are essential to both the landslide and flood risk assessments undertaken within the CHARIM project. The generation of 1 m DEMs was planned, but issues acquiring cloud-free Pleiades stereo satellite imagery during the Atlantic hurricane season meant that this could not be completed within the timeframe.
The landslide inventories were ground-truthed prior to delivery, by visiting the locations of potential landslides identified on the satellite imagery during a 10-day field trip to the region. Subsequently, the inventories were updated to remove any false positives that were confirmed during ground-truthing. The DEMs were validated by computing their vertical accuracies using GPS control points (St. Lucia) and high-resolution airborne LiDAR data (Grenada).
The EO information products delivered through Service 2 are described in Figures 4–9.
The objective of Service 3 was to deliver a national-scale DEM for Belize and as a demonstration, a high-precision DEM (for an area 100 km2) to support risk/hazard mapping. The national-scale 30 m DEM was generated using ASTER stereo imagery, while a higher resolution 20 m DEM covering 40% of the country was derived using SPOT-5 stereo satellite imagery. Pleaides tri-stereo (also refer to as triplet) satellite imagery, obtained through the ESA TPM scheme, was used to generate the high-precision 1 m DEM demonstration product.
This Service demonstrates the ability to generate both national and local-scale DEMs from optical satellite imagery with different spatial resolutions. In the absence of any other suitable elevation data, the 20 m and 30 m DEMs can be used as the basis for modelling flood risk at national-scale across Belize as part of the CHARIM project. Moreover, the precise DEM demonstration product derived from the very-high resolution Pleiades tri-stereo imagery can be used to more accurately model flood risk on a local-scale. With the ability to generate contemporary elevation data with a similar quality to airborne LiDAR, this approach represents a viable alternative to DEM production when airborne surveys are too costly or logistically challenging. Beyond flood risk modelling, high resolution DEMs such as this are important for infrastructure planning and resource management.
The DEMs delivered by this Service were quality checked for data gaps and artefacts, and rectified where necessary. In the absence of ancillary GPS or other control data, the national-scale 30 m DEM was validated using the higher resolution 20 m SPOT-derived DEM acquired from Airbus Defence & Space. The DEM was validated by computing the vertical accuracy using a subset of 32 000 randomly chosen elevation values from the 20 m DEM.
Due to issues acquiring cloud-free Pleiades tri-stereo satellite imagery during the Atlantic hurricane season, it was not possible to generate the 100 km2 high precision DEM until relatively recently. For this reason — in addition to the lack of any suitable GPS or other control data — it has only been possible to undertake a preliminary validation of the high precision DEM to date. As for the national-scale DEM, this involved computing the vertical accuracy using 32 000 randomly chosen elevation values from the 20 m DEM.
The EO information products delivered through Service 2 are described in Figures 10–12.
The EO products and Services delivered by this project address the issue of disaster risk management in the Caribbean region. Specifically, the Services deliver data products that are fundamental in helping to improve understanding of the risk posed by natural (geo-) hazards that frequently affect each country (Jordan et al., 2015[3]) (Table 2). These data feed directly in to the WB-funded CHARIM project to enable flood and landslide hazard mapping to be undertaken. Dissemination of the Services via the CHARIM project will ultimately help to increase awareness of the capabilities of EO, and strengthen the capacity of regional and national governments to generate flood and landslide hazard information and subsequent application to disaster risk reduction.
Table 1 Hazard characteristics for the four countries (source: CDEMA, and Jordan et al., 2015, modified from van Westen, 2014)
Belize
St. Lucia
St. Vincent and the Grenadines
Grenada
Coastline
386 km
158 km
84 km
121 km
Terrain
Flat, swampy coastal plain; low mountains in south. Max. elevation 1 160 m
Volcanic and mountainous with some broad, fertile valleys. Max. elevation: 950 m
Volcanic, mountainous. Max. elevation: 1 234 m
Volcanic in origin with central mountains. Max elevation: 840 m
Natural hazards
Frequent, devastating hurricanes (June to November) and coastal flooding (especially in south).
Hurricanes and volcanic activity, debris flows, flash floods.
Hurricanes; Soufriere volcano on the island of Saint Vincent is a constant threat. Flash floods and landslides
Lies on edge of hurricane belt; hurricane season lasts from June to November. Flash floods and landslides.
Hazard characteristics
Hurricanes and tropical storms are the principal hazards, causing severe losses from wind damage and flooding due to storm surge and heavy rainfall. Hurricanes Keith (2000), and Iris (2001) caused some of the worst damage ever, reaching 45% (US$280 million) and 25% of GDP, respectively.
St. Lucia’s mountainous topography coupled with its volcanic geology means that it experiences landslides, particularly in the aftermath of heavy rains. Much of the island’s housing is distributed along steep slopes and poorly engineered and constructed housing is particularly at risk.
Additionally, the island periodically experiences earthquakes of generally lower magnitudes. Also storm surge and flash floods are among the other risks regularly faced by the island.
Landslides, particularly on the larger islands, are a significant hazard and the risk is increased during the seasonal rains. Coastal flooding is a major concern particularly relating to storm surge and high wave action. The Grenadines are more susceptible to drought. The active volcano La Soufriere, located on the north end of St. Vincent is another risk factor, posing threats from shallow earthquake and eruption events. Since 1900, St. Vincent has been hit by 8 named storms, the strongest being Hurricane Allen (Category 4), which passed between St. Lucia and St. Vincent in 1980. The 1939 eruption of the volcano Kick‐‘em‐Jenny located some 100 km reports South of Grenada, generated a 2‐meter high tsunami.
The country was heavily affected by Hurricane Ivan in 2004, and Hurricane Emily in 2005. There are two active volcanoes in Grenada, Mount St. Catherine in the centre of the island and the submarine volcano kick‐‘em‐Jenny is located 8 km north of the island and has led to tsunami in the past. Flood risk in Grenada is largely associated with storm surge in low lying coastal areas. Flash flooding from mountain streams coupled with storm surge events are the primary causes of flood events and effects are generally limited to communities located in the coastal margins along stream passages. Landslides are a common event in Grenada, with much of the impact experienced along the roadway network.
The initial user requirements were determined by WB and the WB CHARIM project, and then used to define the Services in the SOW. In some cases, these initial requirements were been refined slightly following subsequent discussions with the WB team (i.e., the WB TTL and CHARIM project) and BGS-stakeholder discussions in workshops held in the Caribbean and in the Netherlands (Jordan et al., 2015[3]). Overall, the Services are designed to support flood/landslide hazard mapping by providing essential data that is currently missing or inadequate due to limitations with the current practices. Specifically, the primary requirement is information on land cover/land use, water bodies (e.g., streams, rivers, lakes), landslides and elevation (i.e., DEMs). Acceptance of the Services by the users is therefore dependent on successfully demonstrating the capability to deliver EO products that provide information on these elements that is currently missing, or new information that represents a significant improvement over what already exists (e.g., in terms of accuracy, detail, time period). Further acceptance by the local users could also be dependent on them recognising the benefit of the EO products in applications beyond disaster risk management.
Service 1 provides comprehensive information on the main land use/land cover types, surface water bodies, basic road network and building footprints for St. Lucia, Grenada and St. Vincent and the Grenadines. Overall, the delivered EO products meet the requirements outlined in the SOW, and provide enhanced information that is considerably more detailed and up-to-date than already exists (Table 3). Although this can be implemented as an entirely stand-alone Service for land use/land cover mapping from optical satellite imagery, some aspects were augmented using ancillary baseline information (e.g., existing land use/land cover maps) in order to produce more accurate and consistent data for input to the risk assessment undertaken within the CHARIM project.
Service 2 delivered detailed landslides inventories and national-scale DEMs for St. Lucia and Grenada. The EO products fully meet the requirements, additionally providing yearly landslide inventories for St. Lucia. Although existing landslide inventories are available (see Table 3), the inventories delivered by Service 2 better capture the state of recent activity. Similarly, elevation data also exists, but is outdated, has a low spatial resolution or provides only partial coverage of the countries. Service 2 addresses this by generating DEMs with full coverage and the desired spatial resolution. The landslide inventory mapping aspect of this Service is stand-alone, as it was undertaken using information derived from the optical satellite imagery. However, as defined in the SOW, the mapping was ground-truthed using in-situ field observations. The generation of DEMs from optical satellite imagery can be implemented as a stand-alone process, but in this case was augmented with the existing elevation data to maximise the accuracy of the data for use in subsequent risk assessments.
Service 3 provides a national-scale DEM for Belize, in addition to a higher resolution regional DEM and a local-scale high-precision DEM. In contrast to Service 2, this Service is implemented as a stand-alone service for generating DEMs solely from optical satellite imagery. The resulting DEMs provide more accurate and higher resolution elevation information than currently available, therefore permitting enhanced flood risk modelling at national and local scale.
The EO information products delivered by the three Services are fundamental in assessing the flood and/or landslide risk in the four countries. However, these products must be used in conjunction with additional information (e.g., geology, soils, rainfall data) in order to robustly assess risk. Although beyond the scope of this project, optical satellite imagery and other types of EO data (e.g., radar) can be used to provide much of this additional information.
Current practices
There is a range of skills and experience amongst the local users, ranging from little or no use of geospatial data, to complex use and understanding (e.g., research-driven activities at the University of West Indies). Table 3 lists the geospatial information currently being utilised by WB and local users through a variety of risk/hazard-related projects and initiatives in the Caribbean region. In general, flood and landslide hazard assessments to date have relied upon making the best use of any existing relevant geospatial data. However, much of this data is incomplete, generalised or somewhat outdated — with the historical data likely to have been produced through conventional means such as field surveys. Table 3 also highlights how the current project has utilised EO satellite data to help overcome limitations associated with the current practices and the availability of essential information.
In Grenada, risk mapping and GIS capability is managed predominantly by the Ministry for Agriculture, but progress is limited and digital data is relatively scarce. A vulnerability assessment of school buildings as shelters in the event of natural hazards has been completed (http://www.oas.org/CDMP/document/schools/vulnasst/gre.htm), but this did not consider landslides. Nonetheless, flooding due to torrential rain was considered, with the vulnerability assessment based on very generalised topographical and land use/land cover information gained through local field surveys. To date, a comprehensive multi-hazard map has not been prepared. The WB is implementing a Disaster Vulnerability Reduction Programme, in which Component 2 (Disaster and Climate Risk Reduction) focusses of new construction and rehabilitation of existing infrastructure in order to reduce their vulnerability to natural hazards and climate change. Included within the activities are consultancy services to undertake soil investigation mitigation measures for landslip sites in several sites. In 2006, a landslide hazard map was produced by the Caribbean Development Bank/Caribbean Disaster Emergency Response Agency. This involved producing a landslide inventory based on limited field work confined locations accessible from the road network. This inventory was used in conjunction with a DEM-derivatives derived from a contour map and low quality (i.e., outdated and generalised) soil and geology maps (see Table 3) to model landslide susceptibility. Recently, an enhanced airborne LiDAR DEM has become available, but this does not provide full national coverage. A national flood hazard assessment was also undertaken by the Caribbean Development Bank in 2006, but this did not involve rigorous hydrologic/hydraulic analysis and its reliability will be hindered by the use of outdated and generalised input data (e.g., land use/land cover, soil map) that was likely mapped through field surveys.
Table 3 Geospatial information sources currently used by WB teams and local users. The EO information delivered by the Services are highlighed in green (Jordan et al., 2015[3])
Geospatial information
Grenada
St. Vincent and the Grenadines
St. Lucia
Belize
DEM
10m raster DEM (source unknown) and partial LiDAR coverage
5 m raster DEM (higher parts are not covered). There are LiDAR data, but the format is incorrect so they cannot be analysed
50m raster maps and contours with 2.5 m intervals
ASTER (30 m) and SRTM (90 m). Higher resolution DEM urgently required for flood risk modelling.
30 m DEM, full coverage
30 m DEM, full coverage
National DEM at 30 m, 40% of territory at 20 m and 100 km2 at 1 m
Land use/land cover
USDA 30 m raster map from Landsat data from ca.2000.
Polygon map exists with 11 land use classes (ca.2000)
1:50 000 raster maps. Vegetation information is in vector format
Not applicable
Derived from 2 m satellite data
Derived from 2 m satellite data
Derived from 2 m satellite data
Landslide inventory and hazard map
1988: OAS study for selected towns. 2006: CDB/CDERA limited landslide inventory, not available digitally
Landslide footprints are available from 1987, but there is no detailed information.
Inventory for 1987 (USDA) and 2006 (CDB/CDERA). 2010 inventory produced from satellite imagery
Not applicable
Landslide inventory at 1:20 000
Landslide inventory at 1:20 000 with key areas (<50%) at 1:10 000
Elements-at-risk
Non-attributed building footprints
Not available
Building footprints available for country — occupancy/structural type unavailable
Not available
Building footprints captured on 2 m land use/land cover map
Building footprints captured on 2 m land use/land cover map
Building footprints captured on 2 m land use/land cover map
Geological map
A very general one is available, made by USGS
A very general one is available, made by USGS
Vector map is available
Not applicable
Soil map
A 1959 soils report exists, but map not available
General soil map from USAID from 1990
Vector map is available
General map has been scanned by ITC
Discharge data
Continuous stream flow data do not exist
None available
None available
None available
Geotechnical data
None available to date
None available
None available
Not applicable
Rainfall data
50 stations, non-continuous data available from Land Use Division, Ministry of Agriculture, Lands, Forestry & Fisheries
None obtained thus far, but rainfall stations do exist
Hourly rainfall data for 24 stations
Missing
Socio-economic data
Missing
Missing
Missing
Missing
In St. Vincent and the Grenadines, progress in preparation of hazard maps is also limited. To date, risk mapping has largely focussed on volcanic risks and some coastal vulnerability analyses. A landslide inventory and susceptibility map exists (produced in 1987), but this was based on generalised and somewhat outdated input data (e.g., geology, elevation, land use/land cover) and therefore will not accurately reflect the current state. Similarly, past flood hazard assessments have been hindered by coarse DEMs derived from contour maps. In recent years higher resolution elevation data (e.g., airborne LiDAR) has become available from an unknown source, although the data is currently in a format that is usable. Basic GIS-ready maps of roads, contours, rivers, coastlines, agricultural & urban land use have been prepared — primarily available through the Ministry of Planning and the National Emergency Management Organisation (NEMO). The WB is implementing a Regional Disaster Vulnerability Reduction Programme. Components include identification and creation of required baseline data for hazard assessment; development of institutional systems for the collection, sharing and management of geospatial data among national agencies and with regional institutions; training and education in applications integrating geospatial data systems, hazard and risk assessment to support decision making within various sectors and mainstream the use of these tools as a standard practice in development planning.
In St. Lucia, landslide inventories were produced in 1987 and 2006 through field reconnaissance. However, fieldwork was confined to areas accessible from the roadside and so the inventories do not provide an accurate reflection of the spatial distribution of landslide activity. Subsequently, the Caribbean Development Bank/Caribbean Disaster Emergency Response Agency produced a landslide susceptibility map from the 2006 inventory, but this was again based on low quality (i.e., outdated and generalised) soil and geology maps and elevation data. A 2010 landslide inventory is available, although this appears to have been generated through automated classification of bare ground on satellite imagery. Accordingly, the inventory contains many false-positive landslides owing to a lack of expert knowledge and interpretation. A landslide hazard map was produced in 2012, but this predominantly relates to debris flows and there is also some concern about the source and integrity of much of the input data. A national flood hazard assessment was also undertaken by the Caribbean Development Bank in 2006, but this did not involve rigorous hydrologic/hydraulic analysis and its accuracy will be hampered by outdated and generalised input data. The WB is implementing a Disaster Vulnerability Reduction Programme. Component 2 (Technical Assistance, Regional Collaboration Platforms for Hazard and Risk Evaluation, Geospatial Data Management, and Applications for Improved Decision-Making) would finance: a series of capacity-building, knowledge-building and technical assistance interventions at the national and regional levels to support disaster risk management and climate change adaptation. There are specific areas that have been identified and proposed as high priorities for intervention. At the national level, activities would include, inter alia: i) enhancement of national hydro-meteorological monitoring networks; ii) development of an integrated watershed management plan for flood mitigation; iii) technical assistance for the establishment of maintenance monitoring systems for bridges and public buildings that would integrate natural hazards and extreme events considerations; iv) establishment of geo-spatial data sharing and management platform and related training activities; and v) climate change adaptation public education and awareness campaigns. The GeoNode platform for Saint Lucia is accessible here: http://sling.gosl.gov.lc.
In Belize, a multi-hazard risk study was undertaken in 1999 for several districts as part of a support activity for NEMO. This study focusses on landslides, volcanic and storm hazards amongst others. This assessment appears to have been based largely on historical data, local reports of the occurrence of such events and basic GIS data. Although a nationwide flood hazard map based on hydrological modelling does not appear to exist, several local- or regional studies have focussed on the susceptibility of the road network flood and coastal flooding. Nevertheless, flood hazard mapping in Belize is hindered by the absence of a detailed and accurate DEM. Previous studies were restricted to using a coarse DEM generated from a 1:50 000-scale contour map with 20 m contour intervals. Belize is participating in the Central American Probabilistic Risk Assessment (CAPRA) platform, but the initiative remains modest in Belize.
Scope of assessment
Successful acceptance of the Services/EO information products by WB and the local users was assessed with respect to the four attributes of a sustainable service, i.e., whether they are useful, available, reliable and affordable. These success criteria are summarised below and in Appendix A: Guideline questions for EO information product/service assessment. The goal was to obtain factual information (and quantitative information where possible) relating to each of these attributes.
Useful: This attribute determines whether the EO Services/information products can be used to improve the user’s operations (with a measurable benefit). Generally, this is assessed by considering aspects such as whether the Services provide information that is better that what already exists, new information that did not previously exist, and does this permit new analysis and work that was not previously possible. It is also important to consider whether the new information is easy to use/understand and is fit for the intended purpose, and what additional EO-based information the users would like to have access to in the future.
Available: Overall, this attribute assesses the spatial and temporal coverage provided by the EO Services/products. It determines whether the EO information products can be generated in a reasonable amount of time and made available to users as and when required, and whether the data provides sufficient coverage of the areas of interest. The compatibility of the data with historical information also needs considering, as does the ability of the Service to continue producing consistent information in the future. The Service Provider (BGS) is better placed than the users to assess most aspects of this particular attribute.
Reliable: This assesses whether the EO products meet the requirements and/or expectations of the users. It involves determining the level of confidence that the users have in the information products with respect to the approach used to generate them, their accuracy, quality and validation process.
Affordable: This attribute involves comparing the performance, content and quality of the EO products with existing information from conventional sources to determine whether the additional benefits offered by the Services justify the costs. It also asks users to consider whether the procurement of EO-based information products could help to reduce their overall expenditure on projects.
World bank team roles
The Service assessment was undertaken by the WB team (Fernand Ramirez (TTL), and Dr Melanie Kappes) in connection to the EU-funded CHARIM project together with the University of Twente ITC, The Netherlands and the local users. The CHARIM project was the primary user of the Services and EO information products delivered by this project. The WB TTL provided approval for the EO information products to be delivered to the various users. Contact between BGS and the Caribbean stakeholders (via CHARIM workshops and training courses) further helped to ensure that the Services were fit-for-purpose in the view of the end-users. The WB TTL and the CHARIM project team were the primary conduits for the Services and also acted as independent assessors for the suitability of the delivered EO products for input to flood and landslide hazard mapping. This comprised assessing whether the products meet the requirements as defined in the SOW, particularly with respect to spatial and temporal coverage, thematic accuracy and information content (e.g., preferred land use/land cover classes, landslide attributes). Close contact with the CHARIM team has been maintained throughout the project to help ensure that the EO Services satisfied the requirements and to try to incorporate any necessary refinements to the specification following subsequent discussions and feedback.
It was agreed at the outset of the eoworld2 project that direct contact between BGS and the local users would be limited, and primarily directed via the WB and ITC, in order to avoid confusion with the ongoing CHARIM project. However, dedicated Service Readiness Review and Service Utility Review meetings with the local users planned for Washington DC did not take place and were subsumed into a workshop in the Caribbean. The reduced contacts made it a challenge to fully understand the needs and expectations of the Services, and for the local users to undertake a thorough assessment of the delivered EO information products. BGS participated in a CHARIM workshop in the Caribbean in September 2014, which provided a brief opportunity to present some preliminary EO products to the CHARIM project team local users and subsequently gain feedback relating to their requirements of the products. In March 2015, BGS also participated in the CHARIM training workshop at ITC (in The Netherlands) on ‘The use of geo-data for landslide and flood hazard and risk assessment’. This presented the primary opportunity to provide the local users with hands-on training of working with the EO products and to have them assessed with respect to their requirements and the criteria outlined in the previous sub-section. The training was delivered as a combination of lectures — highlighting how the products were made and validated — and practical sessions that enabled the participants to evaluate the data and compare it with any existing data. The local users that attended the CHARIM workshop in the Netherlands from the relevant countries are listed in Table 4.
Table 4 Participants of the CHARIM workshop and EO product assessment
Country
Name
Affiliation
Belize
Mrs Gina Young
Ministry of Natural Resources and Agriculture
Belize
Mr Irving Thimbriel
Ministry of Works and Transport
Grenada
Mr Fabian Purcell
Ministry of Communication, Works, Physical Development, Public Utilities, ICT and Community Development
Grenada
Mr Jason Williams
Ministry of Communication, Works, Physical Development, Public Utilities, ICT and Community Development
St. Lucia
Mrs Karen Augustin
Ministry of Physical Development, Housing and Urban Renewal
St. Lucia
Mrs Renate McKie
Ministry of Infrastructure, Port Services and Transport
St. Lucia
Mr Mervin Engeliste
Watershed Management Authority
St. Vincent and the Grenadines
Mr Desmond Shallow
Ministry of Housing, Informal Human Settlements, Lands & Surveys and Physical Planning
St. Vincent and the Grenadines
Mr Andy Baptiste
Ministry of Transport, Works, Urban Development and Local Government
References
↑van Westen, C J. (2014). Preliminary Assessment Report: CHARIM Caribbean Handbook on Risk Information management. ITC, University of Twente.
↑Jordan, C J, and Grebby, S. (2014) Risk Information Services for Disaster Risk management (DRM) in the Caribbean: Service Readiness Document. British Geological Survey Open Report, OR/14/064. 31pp. http://nora.nerc.ac.uk/511674/
↑ Jump up to: 3.03.13.23.33.4Jordan, C J, Grebby, S, Dijkstra, T, Dashwood, C, and Cigna, F. (2015) Risk Information Services for Disaster Risk management (DRM) in the Caribbean: Operational Documentation. British Geological Survey Open Report, OR/15/001. 31pp. http://nora.nerc.ac.uk/511672/
↑Helmer, E H, Schill, S, Pedreror, D H, Kennaway, T, Cushing, W M, Coan, M J, Wood, E C, Ruzycki, T, and Tieszen, L L. (2007). Forest formation and land cover map series-Caribbean Islands. U.S. Geological Survey/Earth Resources Observation and Science (EROS), Land Cover Applications and Global Change, International Land Cover and Biodiversity, Caribbean Land Cover Analyses.
↑Helmer, E H, Kennaway, T A, Pedreros, D H, Clark, M L, Marcano-Vega, H, Tieszen, L L, Ruzycki, T R, Schill, S R, and Carrington, C M. (2008). Land cover and forest formation distribution for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from Decision Trees classification of cloud-cleared satellite imagery. Caribbean Journal of Science, 44, 175–189.
↑Congalton, R G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35–46.
