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ResultsMetadata11 th International Symposium for GIS and Computer Cartography for Coastal Zones ManagementDetailed metadata was missing from many of the biodiversity data layers, including source of information, date,and method of collection or a description of the data. For example, the layer “Critical habitat sites of green, leatherbackand hawksbill turtles in the Coral Triangle”, used in a number of regional reports and in connectivity analysisof biodiversity, created by the Ministry of Forestry & WWF Indonesia, was lacking information on data collection,dates and methodology.Multiple layersFour sources of data for coral reefs were compared: United Nation Environment Program and World ConservationMonitoring Center (UNEP–WCMC) Global Distribution of Coral Reefs (2010); World Resource Institute(WRI) from the 2008 Reefs@Risk Revisited report; Global Coral Reef Monitoring Network (GCRMN); Status ofcoral reefs of the world by Wilkinson (2008) and UNEP-WCMC World Atlas of Coral Reefs by Spalding et al.(2001).The analysis of the total area of coral reefs within each country of the Coral Triangle revealed a discrepancy betweenthe two most recent data sources (Table 1). The area from WRI was approximately twice the area fromUNEP-WCMC.Table 1. Comparison of the area of coral reef (in km 2 ) calculated by several sources for the six countries of the Coral Triangle.UNEP - WCMC (2010)Global Distribution ofCoral ReefsWRI (2011) Reefs@RiskRevisitedWilkinson, C. (2008) Statusof coral reefs of the world.GCRMN.Spalding M.D. et al. (2001)World Atlas of Coral Reefs.UNEP-WCMC.Indonesia Malaysia PNG PhilippinesSolomonIslandsTimor-Leste19,805 1,687 7,126 11,852 2,802 3539,538 2,935 14,535 22,484 6,743 14650,875 4,006 NA 25,819 5,750 NA51,020 3,600 13,840 25,060 5,750 NAA closer look into the two datasets helps to understand the difference in area of coral reef cover. Both data setshave similar sources: the UNEP-WCMC data consists of vector spatial data, 85% of which was obtained from theMillennium Coral Reef Mapping Project (mapped at 30 m resolution using Landsat images), and from various othersources. The WRI data also relies mainly on the Millennium Coral Reef Mapping Project and completes it withother various sources as well. However, to standardize the data for the Reefs at Risk Revisited project, WRI convertedall their data to a 500 m grid in raster format. This procedure almost doubles the total area of coral cover, asoriginal small patches of coral reef are converted to grid cells of a 0.25 km 2 in size. The reef data was converted to500 m grids to represent the reef slopes and deeper reefs typically undetectable from satellite remote sensing.Digitization errorDigitization errors were found in both mangrove and coral reef datasets.Four sources of data for mangroves were compared: Spalding et al. (2010) World Atlas of Mangroves; Giri et al.(2011) Status and Distribution of Mangrove Forests of the World using Earth Observation Satellite data; UNEP-WCMC (1997) The Global Distribution of Mangroves and FAO (2007) The World's Mangroves 1980–2005.The analysis of the total area of mangroves within each country of the Coral Triangle revealed a discrepancyamong all the data and some specific differences between the two most recent references.A closer look at the GIS layers of the World Atlas of Mangroves showed that most of Malaysia’s mangrove hadtwo copies of extremely similar polygons which were overlaid and most likely caused the error in calculation. The36
11 th International Symposium for GIS and Computer Cartography for Coastal Zones Managementsmall differences between the other five areas were due to the use of different sources: Spalding et al. (2010) usedvarious sources while Giri et al. (2011) based their data on Landsat 30 m resolution imagery.Outdated and misclassified dataData from the World Database on Protected Areas (WDPA) was compared to the compilation of MPAs by theCoral Triangle team which went directly to the source, working with government agencies to create and update theirMPA database. WDPA seemed to have many MPAs which either never officially existed or no longer existed.Figure 1. Comparison of MPAs in Sabah, Malaysia from WDPA (line) and CT Atlas compilation MPAs (solid). Some of theMPAs in the WDPA are mostly terrestrial.By further comparing WDPA’s MPAs and CT Atlas’ MPAs, it was clear that some of the discrepancy in areacame from the different definitions of MPAs. WDPA’s MPAs are Protected Areas (PAs) that have a marine component.This results in classifying PAs that are mostly terrestrial but with a beach or mangrove as an MPA, while theintent of the protection is only terrestrial (Figure 1). In Malaysia, entire islands are considered MPAs when only thewaters around the island are protected and none of the land is regulated, including mangroves, overestimating thetotal extent of protected areas.For a high quality MPA layer, further information would be needed to complete the current layer, including zoninginformation and management effectiveness.Lack of user guidanceThe Reefs@Risk Revisited data, as well as most of the oceanographic and climatology data (that was only brieflychecked during this process), are all high quality data. However, we found that it was often misused with countriescombining data that had been converted to grids with data that were not, resulting in gross miscalculation of areas.Although Reefs@Risk Revisited is an excellent product there is no warning on how to use the data in combinationwith other layers, and this could lead to inexperienced managers or GIS users misusing it.DiscussionCompiling several data layers is useful, and often necessary to present data at a regional scale, but is hamperedwhen metadata records are incomplete. The example given of the “Critical Turtle Habitat” is a typical situationwhere although the data looks complete and is used in government reports and other authoritative publications, theactual quality of the data is poor due to the lack of information. The consequence is that the public, stakeholders,managers, and donors are led to believe that the data exists and that it can be used for spatial planning or resourcemanagement. However the features represented on a map may, in fact, be from a low quality source, out of date, orinconsistent.The proliferation of errors in one data set is compounded when used with other imperfect data sets. For example,one of the most common issues the CT Atlas has found is the calculation of coral reefs protected by MPAs. If thecountries use an MPA layer that overestimates the area of MPAs in the country (WDPA) with a coral reef layer thatis represented with a 500 m grid (Reefs@Risk Revisited), the area of coral reef protected by MPAs will be greatlyoverestimated. In Table 1, the coral reef area from Reefs@Risk Revisited is twice that calculated using UNEP-WCMC data. This could result in a government reaching the erroneous conclusion that they have achieved their goal37
Page 1 and 2: CoastGIS Conference 2013: Monitorin
Page 3 and 4: Sponsors
Page 5 and 6: Steering Committee Secretariat main
Page 7 and 8: Santos Basin, BrazilA.F. Romero, R.
Page 9 and 10: Coastline development and associate
Page 11 and 12: Visual resource management system f
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11 th International Symposium for G
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Developing and testing approaches f
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A dynamic GIS as an efficient tool
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GIS spatio-temporal modeling of hum
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ResultsCollected data11 th Internat
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The use of GIS and geospatial techn
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Ocean Radar for Monitoring of the C
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Geophysical investigations of marin
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A semi-supervised learning framewor
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Simulation of maritime paths taking
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COINAtlantic: Sharing through open
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Implementation of the marine data i
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Perspectives11 th International Sym
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Tools and best practices for coasta
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Washington Coastal Atlas: creating
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Long-term continuous observations o
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Comparing endmember extraction meth
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Integration of scientific data as a
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Conclusions11 th International Symp
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