SATELLITE-BASED AND COMMUNITY-BASED COASTAL RESOURCE MAPS: COMPLEMENTARY OR CONTRADICTORY?

Similar documents
NATIONAL MAPPING EFFORTS: THE PHILIPPINES

Community Participation in Land Governance Through Citywide Community Mapping GLTN Learning Exchange, Bayview Hotel, Manila November 7, 2017

Satellite Remote Sensing for Ocean

Designing Networks of Marine Protected Areas in DFO s Three Atlantic Bioregions

TASMANIAN SEAGRASS COMMUNITIES

TOWARDS CLIMATE-RESILIENT COASTAL MANAGEMENT: OPPORTUNITIES FOR IMPROVED ICZM IN BELIZE

A Baseline Mapping of Aquaculture and Coastal Habitats in Myanmar

Courtesy of John Mitchell

Abstract. Introduction

USE OF RADIOMETRICS IN SOIL SURVEY

IMA s ROLE IN COASTAL AND OCEAN GOVERNANCE IN TRINIDAD AND TOBAGO

Coastal Landuse Change Detection Using Remote Sensing Technique: Case Study in Banten Bay, West Java Island, Indonesia

Rural Pennsylvania: Where Is It Anyway? A Compendium of the Definitions of Rural and Rationale for Their Use

Ecological mapping using satellite imagery: an Abu Dhabi case study Middle East Geospatial Forum 16 th February 2015

Marine Spatial Planning as an important tool for implementing the MSFD

MALDIVES. Regional Expert Workshop On Land Accounting For SDG Monitoring & Reporting (25-27 th Sept 2017) - Fathimath Shanna, Aishath Aniya -

World Oceans Day 2010 Our oceans: opportunities and challenges

Mapping Coastal Change Using LiDAR and Multispectral Imagery

Quick Response Report #126 Hurricane Floyd Flood Mapping Integrating Landsat 7 TM Satellite Imagery and DEM Data

LAND COVER CATEGORY DEFINITION BY IMAGE INVARIANTS FOR AUTOMATED CLASSIFICATION

GEOMATICS. Shaping our world. A company of

HELSINKI COMMISSION Baltic Marine Environment Protection Commission

Overview of Methods. Terrestrial areas that are most important for conservation Conservation

GEOGRAPHIC INFORMATION SYSTEMS Session 8

National Disaster Management Centre (NDMC) Republic of Maldives. Location

Use of Geospatial Data: Philippine Statistics Authority 1

Coastal Viewer Mapping Application:

Virginia Shoreline Mapping Tools

An Environmental Profile of the Island of Jost Van Dyke, British Virgin Islands

Lorna V Inniss, Ph.D SAGE Workshop, New York City

Urban Tree Canopy Assessment Purcellville, Virginia

Module 2.1 Monitoring activity data for forests using remote sensing

Cross-border Maritime Spatial Plan for the Black sea - Romania and Bulgaria project

Summary Description Municipality of Anchorage. Anchorage Coastal Resource Atlas Project

Mapping Maine s Working Waterfront: for Our Heritage and Economy

HCSA Peer Review Report Musim Mas PT. Mentari Pratama (PT. MP)

National Marine Sanctuary Program

Case Study: Ecological Integrity of Grasslands in the Apache Highlands Ecoregion

Martin MENSA, Eli SABLAH, Emmanuel AMAMOO-OTCHERE and Foster MENSAH, Ghana. Key words: Feeder Roads Condition Survey, Database Development

Preliminary Vulnerability Assessment of Coastal Flooding Threats - Taylor County, Florida

Recreation Use and Spatial Distribution of Use by Washington Households on the Outer Coast of Washington

Spatial Accuracy Assessment for Coral Reef Classifications. Supawan Wongprayoon 1 Carlos Antonio Oliveira Vieira 2 Joseph Henry John Leach 3

WELCOME & INTRODUCTION

Understanding and Measuring Urban Expansion

Outline. - Background of coastal and marine conservation - Species distribution modeling (SDM) - Reserve selection analysis. - Results & discussion

Economic and Social Council

VISUALIZATION URBAN SPATIAL GROWTH OF DESERT CITIES FROM SATELLITE IMAGERY: A PRELIMINARY STUDY

The Study of Multi-temporal Analysis of Urban Development and Environmental Changes of the City of Abu Dhabi

HOLY CROSS CATHOLIC PRIMARY SCHOOL

MEADOWS PRIMARY SCHOOL and NURSERY GEOGRAPHY POLICY

Marine Spatial Planning: A Tool for Implementing Ecosystem-Based Management

Object Oriented Classification Using High-Resolution Satellite Images for HNV Farmland Identification. Shafique Matin and Stuart Green

The Governance of Land Use

Haida Gwaii Queen Charlotte Islands

15 March 2010 Re: Draft Native Vegetation of the Sydney Metropolitan Catchment Management Authority Area GIS layers and explanatory reports

Characterization of the Nigerian Shoreline using Publicly-Available Satellite Imagery

PACIFIC ISLANDS REGIONAL OCEAN POLICY. A healthy Ocean that sustains the livelihoods and aspirations of Pacific Island communities.

DRRM in the Philippines: DRRM Projects, Geoportals and Socio-Economic Integration

SPECIAL MID-TERM REPORT

Land Cover Classification Over Penang Island, Malaysia Using SPOT Data

MAINTENANCE DREDGE BENTHIC ASSESSMENT SUNSET POINT FARM LLC LONG POINT KEY MONROE COUNTY, FLORIDA. Prepared by:

Resolution XIII.23. Wetlands in the Arctic and sub-arctic

Effects of Rising Sea Levels on Coral Reef and Mangrove Distributions along the Great Barrier Reef in Australia

The Positional and Thematic Accuracy for Analysis of Multi-Temporal Satellite Images on Mangrove Areas

Outline Introduction Objectives Study Area Methodology Result Discussion Conclusion

IMPROVING REMOTE SENSING-DERIVED LAND USE/LAND COVER CLASSIFICATION WITH THE AID OF SPATIAL INFORMATION

The Use of Remote Sensing and GIS in MPA Delineation and Management

MR. George ALEXAKIS, parallel session 3. "Mediterranean Sea Region. laying the conditions. for sustainable growth and jobs"

A TOOLKIT FOR MARINE SPATIAL PLANNING Version: 17 July, 2009

VCS MODULE VMD0018 METHODS TO DETERMINE STRATIFICATION

ENVIRONMENTAL CONSIDERATIONS IN CLUP

Mutah university faculty of Social Sciences The Study plan of the department of Geography 2006/2007

EpiMAN-TB, a decision support system using spatial information for the management of tuberculosis in cattle and deer in New Zealand

A FRAMEWORK FOR CAPACITY BUILDING IN MAPPING COASTAL RESOURCES USING REMOTE SENSING IN THE PHILIPPINES

Natural Resource Management Strategy. Southern Tasmania. Summary. Natural Resource Management Strategy for Southern Tasmania Summary

Regional stakeholders strategy of Donegal County Council

GIS Monroe Geographic Information System March 14, 2018

Economic and Social Council 2 July 2015

Sri Lanka has a coastline of km excluding the shoreline of bays and inlets.

Technical Drafting, Geographic Information Systems and Computer- Based Cartography

NOAA s OCM: Services, tools and collaboration opportunities & Puerto Rico s NE Marine Corridor as a case study

Development of Geospatial Information in Indonesia: Progress & Challenge

INSTITUTE OF TOWN PLANNERS, INDIA TOWN PLANNING EXAMINATION BOARD ASSOCIATESHIP EXAMINATION

China-ASEAN Advanced Academy on Oceans Law and Governance 7-16 November 2016, NISCSS, Haikou

Capturing a Holistic Understanding of a Large Marine Ecosystem The NOAA Gulf of Mexico Data Atlas

Land Administration and Cadastre

Africa Partnership Station: Coastal Processes

Modeling Coastal Change Using GIS Technology

RETA 6422: Mainstreaming Environment for Poverty Reduction Category 2 Subproject

Habitat Mapping using Remote Sensing for Green Infrastructure Planning in Anguilla

Geography Policy. Introduction

Urban Climate Resilience

Marine Spatial Data for Marine Spatial Planning. Ocean Leadership 2010 Public Policy Forum

KNOWLEDGE-BASED CLASSIFICATION OF LAND COVER FOR THE QUALITY ASSESSEMENT OF GIS DATABASE. Israel -

A Case Study of Using Remote Sensing Data and GIS for Land Management; Catalca Region

THE IMPACT OF EL NIÑO AND LA NIÑA ON SOUTHEAST ASIA

1. Introduction. S.S. Patil 1, Sachidananda 1, U.B. Angadi 2, and D.K. Prabhuraj 3

System of Environmental-Economic Accounting. Advancing the SEEA Experimental Ecosystem Accounting. Extent Account (Levels 1 and 2)

CHAPTER 4 HIGH LEVEL SPATIAL DEVELOPMENT FRAMEWORK (SDF) Page 95

Spatial Data Availability Energizes Florida s Citizens

Transcription:

SATELLITE-BASED AND COMMUNITY-BASED COASTAL RESOURCE MAPS: COMPLEMENTARY OR CONTRADICTORY? Randy John N. Vinluan and Paolo C. Campo Department of Geodetic Engineering University of the Philippines, Diliman 1101 Metro Manila, The Philippines Fax: (63 2) 9208924; E-mail: rjnv@up.edu.ph KEY WORDS: Coastal management, Coastal resource, Community-based approach, Mapping, Remote sensing ABSTRACT. Participatory coastal resource assessment, or PCRA, is a coastal management approach that involves the coastal community in the appraisal of natural resources found within its coastal zone. One strategic activity in this approach is the community-based mapping of its coastal resources. In community-based mapping, the leaders and ordinary residents of several communities, which make up the coastal municipality or city, work together to produce coastal habitat maps of their respective communities, relying on local knowledge and technical assistance from other people or groups. However, their lack of training in mapping becomes evident in the output e.g., shapes and sizes of habitat patches are grossly in error, extent of a habitat patch is wrongly delineated, etc. In contrast, a satellite-based coastal resource map is typically produced by field experts. The accuracy of the map is dependent on the extent and comprehensiveness of ground validation, and experience in image interpretation, among others. The map-making process receives little input from community residents, who are theoretically the most knowledgeable of the area to be mapped. Therefore, satellite-based and community-based coastal habitat maps are, more often than not, not in agreement. This does not imply, however, that one map is accurate while the other map is not. Instead, the paper shows that one map may be enhanced by the other. Using as an example the case for one municipality fronting Davao Gulf, the paper discusses how a more accurate map may be produced from integrating the results of community-based mapping to a classified Landsat 7 ETM+ image of the area. 1. INTRODUCTION The Philippine coastal zones are under tremendous stress. Fish catch is declining, coral reefs are battered, mangroves are under threat, pollution levels are rising, and growing coastal communities are experiencing increasing poverty (Courtney and White, 2000). Thus, the need for an integrated approach to the management of the Philippine coastal zones--which effectively addresses the social, economic, physical, natural and other factors causing these problems--cannot be overemphasized. One of the key elements in an integrated coastal zone management approach is the continuing process of scientific data collection on coastal resources. This involves the collection of baseline information and development of a coastal environmental profile to lay the basis for the coastal management plan. In much of the Philippines' experience in coastal management, coastal communities are engaged to participate in this critical activity. The reasons for involving the community in this and other coastal management activities are plenty (Zeitlin-Hale, 1996), but local wisdom and knowledge and community participation seem to be two of the most compelling. This activity, commonly referred to as participatory coastal resource assessment (PCRA), focuses on resource assessment from the point of view of local users of coastal resources and integrates local wisdom and knowledge with the technical expertise of other people or groups, such as non-governmental organizations, universities, research institutions, and local government staff, who are also involved in planning and management (Walters et al., 1998). One of the major outputs of such activity is a coastal resource map, which shows the occurrence, distribution and use of, and access to resources and associated habitats within the economic and cultural domain of the community. This map is essential in planning and implementing coastal management activities. With this type of map, one is able, among other things, to represent and then analyze the extent and condition of coastal resources and habitats, prepare a coastal use plan, optimize coastal space for infrastructure development and interventions, localize coastal problems, and identify various coastal issues and conflicts. The same map may be produced scientifically by field experts through the use of satellite remote sensing and related mapping techniques. Through the combined use of data collected from ground validation activities, experience in visual interpretation, the collection of secondary information, and the application of various image processing methods, a coastal resource map may be produced. The literature is replete with cases of the use of remote sensing for mapping coastal resources (e.g., Clark et al., 1997; Chauvaud et al., 1998) with varying degrees

of successes. However, normally, this particular map-making process receives quite little input from community residents, who are theoretically the most knowledgeable of the area to be mapped. Therefore, satellite-based and community-based coastal resource maps are, more often than not, not in agreement. These disagreements are manifested as differences in shapes, sizes, and lengths of patches, and errors in the positions of such patches, among others. This disagreement does not imply, however, that one map is more accurate and useful than the other map. The paper attempts to answer the question of whether satellite-based and community-based coastal resource maps are indeed contradictory or complementary. This paper posits the latter. We show that one map may be enhanced by the other. Using as an example the case for one municipality fronting Davao Gulf, the paper discusses how a more accurate and useful map may be produced from integrating the results of community-based mapping to a classified Landsat 7 ETM+ image of the area. The paper also discusses the role of coordination (among participating agencies), cooperation (among field experts and community residents), awareness (of coastal environmental issues), and advocacy in coastal management, in general, and mapping, in particular. 2. METHODS 2.1 PCRA Community-based mapping is a fairly straightforward process. Each municipality or city designates an officer from the Municipal or City Agriculturist s Office to facilitate the coastal resource assessment activity in the different communities (called barangays) that make up the coastal municipality or city. The municipal or city officer normally provides a base map over which the community residents sketches various types of information such as habitats, resources, water uses, environmental issues, and other features. The base map, normally plotted at a scale of 1:100,000 for lower-class municipalities, shows political boundaries and features such as landmarks, shorelines, and roads. Being typically prepared from topographic maps produced by the national mapping agency, this allows for comparison with existing maps produced by mapping experts. Different methods are employed in depicting map elements on the base map. For example, a habitat is expressed as a patch of varying colors. Living resources such as sea mammals or fish are tagged as Arabic numerals placed over locations where these resources are reported to exist. After some initial mapping has been conducted, the PCRA map is refined by undertaking field visits. Being a group exercise, peer pressure and group consultation often lead to a better understanding of the map-making process and consequently, to a more accurate location of map elements. Also, years of experience in fishing and farming, or even living in the community, help in the identification of features that are not distinct in aerial photographs (from which most topographic maps are derived) and satellite images. These procedures were implemented by the residents of the coastal municipality of Banaybanay in Davao Oriental, situated in southern Mindanao on the eastern side of Davao Gulf. This was undertaken during the first quarter of 2001. 2.2 Analysis of satellite images A Landsat 7 ETM+ image of Davao Gulf and adjoining cities and municipalities (path = 112, row = 55), acquired on 26 May 2000 was used in the study (see figure 1). Routine preprocessing procedures, including geometric correction and radiometric calibration, were applied to the image. Ground-truth data were collected during site visits conducted in May 2001 by mapping and fishery experts from the University of the Philippines and the Bureau of Fisheries and Aquatic Resources respectively. The boatman served as their only field guide. The study area was limited to the region bounded by a three-kilometer buffer zone offshore and a variable distance inland. After this mask had been applied, the scene was plotted at a scale of 1:100,000 and visually interpreted for coastal land uses and habitats. Multispectral classification of the image using the maximum likelihood algorithm was then performed. 2.3 Integration of information from the two maps Only a qualitative assessment of accuracy of the two maps--satellite-based and community-based--was performed. This was done by a visual correlation approach. Observations are made on the two maps regarding the shape, size and length of coastal resource patches, the location of these patches, and the correspondence of their identities, i.e.

if a patch in one map is identified as the same in the other map. Any observed differences are noted and subsequently translated onto the satellite-based map using one's best judgement. 3. RESULTS Assigning the Landsat bands 4, 3, 2 to red, green and blue respectively, we find that vegetated areas appear in red tones, built-up areas in blue-green tones, coral reefs in blue to light blue tones, and mangroves in red tones (please refer to figure 1a). Fishponds also appear distinctly in the image as regular patches of dark and light green. It is context which distinguishes fishponds and mangroves from other coastal resources and habitats which exhibit,more or less, similar spectral responses. Interestingly, bagnets a fishing implement appear as dark green patches in several locations along the coast. Figure 1b shows the PCRA map for the municipality under study produced by the community residents. The coastal habitats and resources within the municipality that have been identified are sandy beach, seagrass beds, coral reefs, mangroves, and fishponds and fish cages. Water uses mostly fishing-related such as fish sanctuary, fish shelter, fish corrals and bagnets, are also indicated in the map. Figure 1c, on the other hand, is the generalized classified Landsat image of the area. About 93 percent of the training pixels (n = 8,975) have been correctly classified to one of six classes, namely coral reefs, mangroves, fishponds, marine zone, terrestrial zone, and bagnets (see table 1). However, immediately noticeable are the misclassification of mangrove pixels to terrestrial zone pixels, and of marine zone pixels to coral reef pixels. The former is due to spectral confusion between mangroves and other types of vegetation. The latter is due to spectral confusion between coral reefs and shallow water. Submerged seagrass beds are difficult to detect from the image. Some categories in the PCRA map are not identifiable from the image. Table 1. Error matrix from the classification of the Landsat 7 ETM+ image of the study area. CR MN MZ TZ BN FP Total CR 638 0 9 2 0 13 662 MN 0 534 0 170 3 2 709 MZ 0 0 3296 3 0 0 3299 TZ 0 137 0 2553 3 170 2863 BN 0 1 0 3 306 22 332 FP 22 9 0 39 4 1036 1110 Total 660 681 3305 2770 316 1243 8975 Notes: CR = coral reefs, MN = mangroves, MZ = marine zone, TZ = terrestrial zone, BN = bagnets, FP = fishponds. Overall accuracy = 93.18 percent. While similar in some respects, several disagreements between the PCRA and satellite-based maps may be observed. These disagreements, as well as the possibility for improving the satellite-based map based on PCRA inputs, are discussed in the following section. 4. DISCUSSION One difference in the two maps is in the shape of the coastal resource and habitat patches. For example, labeled A at the center of figures 1b and 1c is a stationary bagnet. It is rectangular in shape in the community-based map while irregular in the satellite-based map. Another difference in the two maps is in the size of the patches. Labeled B near the top of figures 1b and 1c is a coral reef patch. While similar in length, the coral reefs in the satellitebased image are represented as being wider in extent. Another difference is in the location of the patches. Labeled C at the left side of figures 1b and 1c is another coral reef patch, the location of which grossly differs in the two maps. Another type of differences in the map is miscorrespondence of patches. Examples are those marked D and E near the bottom of figures 1b and 1c. Seagrass in the community-based map is misidentified as a coral reef patch ( D ) while the terrestrial zone in the community-based map is misidentified as either mangrove or fishpond patches ( E ). Nevertheless, despite these differences, a potential exists for improving the satellite-based maps using information derived from community-based maps. Shapes, sizes, lengths, and locations of patches may be reliably obtained from classified satellite imagery. However, information on the identity of patches may be more reliably obtained from community-based maps because of the high reliability and validity that may be attached to local wisdom, knowledge and experience. A better map may be produced by integrating the best features from the two maps. For

example, information on the location of seagrass beds in the PCRA map, which is absent in the satellite-based map, may be transferred to the other map. Also, other coastal resources or habitats shown in PCRA maps, but not easily detectable in satellite imagery, may also be depicted in the improved map. Figure 2 is an enhanced coastal resource map produced by integrating information from the two maps. Many problems in the integration of the two maps may be avoided by maintaining quality throughout the mapmaking process. In most instances, to do so not only requires strictly following mechanical procedures in mapping but also seeing to it that the social dimensions of mapping are adequately addressed. One such dimension is coordination among agencies or entities that have a stake or a significant role to play in coastal resource mapping. The community-based and satellite-based maps were produced by two different groups at two different times, but for the same national project. It would have been great savings of time, energy, and money had the production of the two maps been coordinated. Another important social dimension in mapping is cooperation among field experts and community residents. This paper has shown that local wisdom and knowledge are invaluable as far as map-making is concerned. Cooperation cuts on time for, and consequently, on costs for fieldwork. More importantly, it gives the community residents a deep sense of involvement in the process and, somehow, a sense of ownership over the output map. Awareness of coastal environmental issues is another important social dimension of mapping coastal resources and habitats. For example, knowing that coral reefs are essential in supporting marine life could encourage community residents to continually seek out this habitat, add the location of significant coral reef patches to their mental map of their coastal zone, and find ways to protect them. The fisherfolk of Banaybanay instinctively know where their coral reef regions are and they deliberately avoid passing their boats to those regions or, if it is not at all possible, they naturally slow down to avoid causing damage. Finally, community residents and field experts must adopt a "management" attitude towards coastal resources, or an advocacy for coastal management. This attitude attaches importance to mapping because of the significant role that it plays in making policies and decisions related to coastal management. 5. CONCLUSIONS The study sought to answer the question of whether satellite-based and community-based maps were complementary or contradictory. While disagreements between the two types of maps exist, it has been shown that they play more of a complementary role, in that one map may be improved by the other. The study took two coastal resource maps one prepared by community residents and the other prepared by field and remote sensing experts and observed differences between the two. These differences were mainly on the shape, size, length, location, and identity of the different elements on the map. The differences notwithstanding, a better map was produced by integrating the best features from the two maps, although this was done using the mapping experts' best judgement. An accurate and reliable map must be one of the goals of coastal management from the very start. To this end, the social dimensions of mapping, namely coordination (among participating agencies), cooperation (among field experts and community residents), awareness (of coastal environmental issues), and advocacy in coastal management, play a crucial role. 6. ACKNOWLEDGEMENTS The authors wish to acknowledge the funding support of the Fisheries Resource Management Project of the Bureau of Fisheries and Aquatic Resources and the technical support of the staff of the Remote Sensing Image Analysis Laboratory of the University of the Philippines. REFERENCES Chauvaud, S., C. Bouchon and R. Manière, 1998. Remote sensing techniques adapted to high resolution mapping of tropical coastal marine ecosystems (coral reefs, seagrass beds and mangrove). International Journal of Remote Sensing 19, pp. 3625-3639. Clark, C.D., H.T. Ripley, E.P. Green, A.J. Edwards and P.J. Mumby, 1997. Mapping and measurement of tropical coastal environments with hyperspectral and high spatial resolution data. International Journal of Remote Sensing 18, pp. 237-242. Courtney, C.A. and A.T. White, 2000. Integrated coastal management in the Philippines: Testing new paradigms. Coastal Management 28(1), pp. 39-53. Walters, J.S., J. Maragos, S. Siar and A.T. White, 1998. Participatory Coastal Resource Assessment: A Handbook for Community Workers and Coastal Resource Managers. Coastal Resource Management Project, Cebu City. Zeitlin-Hale, L., 1996. Involving communities in coastal management. In: Proceedings of the Coast to Coast 96 Conference, edited by Harvey, N.C., University of Adelaide, Adelaide.

B B C C A A E E D D Figure 1. 1:180,000-scale plots of: (a) the Landsat 7 ETM+ image of Banaybanay, Davao Oriental in southern Philippines acquired on 26 May 2000 (RGB=432); (b) the PCRA map for the same municipality produced by the residents of the coastal municipality (see figure 2 for legend); and (c) the generalized classified Landsat 7 ETM+ image of the municipality (see figure 2 for legend).

Figure 2. A 1:100,000-scale coastal resource map of Banaybanay, Davao Oriental integrating results from the satellite-based and community-based maps.