A GIS-based modeling of environmental health risks in populated areas of Port-au-prince, Haiti
par Myrtho Joseph
University of Arizona - Master in Natural Resources Information System 1987
IN POPULATED AREAS OF PORT-AU-PRINCE, HAITI
A Thesis submitted to the Faculty of the
SCHOOL OF NATURAL RESSOURCES
In Partial Fulfillment of the Requirements
For the Degree of
MASTER OF SCIENCE
WITH A MAJOR IN RENEWABLE NATURAL RESOURCES STUDIES
In the Graduate College
THE UNIVERSITY OF ARIZONA
STATEMENT BY AUTHOR
This thesis has been submitted in partial fulfillment of requirements for an advanced degree at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library.
Brief quotations from this thesis are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the head of the major department or the Dean of the Graduate College when in his or her judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained from the author.
APPROVAL BY THESIS COMMITTEE
This thesis has been approved on the date shown below:
D. Phillip Guertin Date
Associate Professor of Watershed Management
Craig Wissler Date
Assistant Professor Landscape Studies
Gary Christopherson Date
Director, Center for Applied Spatial Analysis
Without any doubt the success of a study like this relies on a well-thought methodology, an excellent design, a good theoretical background, reliable data and tools, and a sound analysis. However, without the support of people who are expert in specific domains, this study would be more challenging and might not be made possible. A popular and wise biblical verse says: «People die for lacking knowledge». I would not physically die without access to some precious information released by many of those who helped, but I would be dying slowly with impatience, discouragement, sense of defeat, lack of inspiration, and frustration.
I want to take advantage of this occasion to thanks D. Phil Guertin who has been my advisor not only for the thesis but during the complete course of my studies at the School of Natural Resources. His support has gone beyond academics, and covered a large range of assistance that is not possible to list without missing some. I am more than certain Dr Guertin will continue to guide me even after the completion of my master's study. I want to express my gratitude to Dr Christopherson who opened the CASA Lab for me during the tedious digitization process and had provided me profitable guidance for the generation of Port-au-Prince's DEM. My appreciation goes to Wissler for sporadic but precious intervention when I was struggling with some ArcMap processes. Mickey Reed was irreplaceable for specific advice and access to fine-point tools and processes. Thanks to all the Advanced Resource Technology's staff for unconditional support and flexibility. I am grateful to Kareen Thermil, who granted me access to some precious information and data, and Juvenel Joseph, my brother who did any necessary arrangement to facilitate acquisition of much of the data needed and available from Haiti. I want to thank either the group of Haitian professionals and students who accepted to participate in the EOW survey. Finally, the best for last, I want to thank my wife who accepted heartedly to sacrifice our time and invest it in the accomplishment of the thesis. Her devotion and support were priceless for the completion of my study.
This thesis is dedicated to my mother who would not have the opportunity to witness the fulfillment of my dream; to my wife whose unconditional support helped me to be at the same time a father, a spouse, and a fulltime master's student; finally to my country which unfortunately is the inspiration of this topic.
TABLE OF CONTENTS
AHP: Analytical Hierarchy Process
ARIs: Acute Respiratory Infections
BMRC: Bureau of Meteorology Research Center
CDERA: Caribbean Disaster Emergency Response Agency
DDI: Disaster Deficit Index
DRI: Disaster Risk Index
ECVH: Enquête sur les Conditions de Vie en Haiti
EHR : Environmental Health Risks
EMMUS II: Enquête de Mortalité, Morbidité et Utilisation de Services 1994
EMMUS III : Enquête de Mortalité, Morbidité et Utilisation de Services 2000
EOW: Expert Opinion Survey
EPA: Environment Protection Agency
ESRI: Environmental System Research Institute
GDP: Gross Domestic Product
IDB: InterAmerican Development Bank
IDEA: Instituto de Estudios Ambientales
IDW: Inverse Distance Weighting
IHSI: Institut Haitien de Statistiques et d'Informatique
LDI: Local Disaster Index
MCE : Multi-Criteria Evaluation
PAHO : Panamerican Health Organization
SDE: Section D'Enumeration
SEI: Stockholm Environment Institute
SMCRS: Service Metropolitain pour la Collecte des Residus Solides
UNDP: United Nations Development program
UNDRO: United Nations Disaster Relief Organization
UNEP: United Nations Environment Program
UNISDR: International Strategy for Disaster Reduction
UTSIG/CNIGS: Unite de Teledetection et de Systeme d'Information Geographique/ Centre National de l`Information Geo-Spatiale
VIP's: Very Important Points
WHO: World Health Organization
WLC: Weighted Linear Combination
YTV: Helsinki Metropolitan Area Council
In Port-au-Prince, Haiti's capital, the increasing occurrence and casualties from landslides and floods during the last few years has focused interest toward these natural disasters. The high pressure of human settlements associated with urban migration constitutes the main trigger of these deadly events by increasing the sensitivity of the environment as well as people's vulnerability. Long term impacts of environmental degradation on health related to human settlements have not received as much attention as natural disasters. The inconspicuous nature of environmental health hazards and their related consequences may have diverted stakeholders and people's attention from them. Health hazards derived from the environment are believed to be of a greater spatial extent, cause more losses than any other hazards, and concern more than two-third of the population within the study area. The objective of this study was to identify areas where such health hazards exist and assess neighborhoods' vulnerability to these hazards using a GIS modeling approach that offers the capability of superimposing multiple parameters. Nine factors were combined with different weighting schemes including an Expert Opinion survey. Moreover, several classification techniques were tested and compared in the final process of determining the four risk levels. Finally, a sensitivity analysis was performed to assess the responsiveness of the model to changes induced in the model's parameters.
Though this study was conducted in a context of poor data availability, the results suggest that about 41% of the entire area was subjected to high risk. Pollution originated from water bodies, traffic and waste were found as the most critical, while housing density, which is simultaneously a risk and a vulnerability factor represented the main trigger of many risks encountered. This study called for a deeper investigation of the state of pollution in Port-au-Prince by taking direct field measurement in order to validate the findings. In addition, it reveals the needs for a synergistic effort of governmental and non-governmental institutions to produce and make available spatial data at fine scale and resolution in a cost-efficient manner.
9Impact, le film from Onalukusu Luambo on Vimeo.