SDI strategic planning using the system dynamics technique: A case study in Tanzania

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Development of spatial data Infrastructure (SDI) is a long term process, which requires long-term plans. The complexity of SDI, which is a matter of technical, institutional and financial challenges and their interactions, makes the development of such a plan complicated. It is also generally hard to convince policy-makers about the reliability of a plan and the future effect of that to get their supports. The system dynamics technique has been shown to be a proper approach for SDI planning, responding to the above issues. This paper summarizes the application of the system dynamics technique for SDI modelling in Tanzania

Investigating Spatial Data Infrastructure Planning in Tanzania using System Modelling and Social Concepts

Spatial Data Infrastructure is one of the requirements for sustainable development and many countries worldwide are at different stages of implementation. Several researchers have shown that SDI has helped governments to recover funds due to reduction in duplication of efforts and also has increased efficiency in resource management and planning.Tanzania as other developing countries, is at initial stages of establishing the National SDI with a policy proposal and the national steering committee in place. However, lack of knowledge and experience among the stakeholders, complexity and dynamics of its components and their interaction are major challenges that hamper the growth of SDI. Although many studies have explained the complexity and dynamics of SDI, little has been done that involves stakeholders to model complexities for more reliable plans.In this thesis, social concepts and system modelling are used to understand SDI planning process in Tanzania. Input data were obtained based on mixed methods approach, including questionnaire survey and workshops involving local and central government officials and other stakeholders that are producers or users of spatial data. This thesis begins with the application of Theory of Planned Behavior (TPB) for understanding spatial data sharing and the results showed that TPB was effective in accounting for intention to share spatial data in Tanzania.Second part was a methodology for SDI planning in Tanzania based on system dynamics technique and the community of practice concept where an optimum model was developed with consensus of SDI stakeholders. The model, gave theplanners an insight about the future effects of today’s plans and decisions. The proposed models and concepts are highly recommended for SDI planning and for raising awareness to gain support from policy makers.Third part was on investigating the Agent Based Modelling (ABM) approach for simulating SDI development. The output was evaluated and was within a reasonable range and depicted the main attributes, roles and interactions of agents. The results will help SDI planners and other stakeholders in making reliable SDI strategic plans.Finally a case study for an operational SDI was demonstrated. A land use plan was proposed based on a spatial Multi-Objective Optimization approach where influencing conflicting factors needed to be considered and satisfied. NSGA IIalgorithm was used in optimization. The proposed approach and output can considerably facilitate land use planning. Similar approaches are highly recommended for other countries in Africa of which their cities are under development

Applying the theory of planned behavior to explain geospatial data sharing for urban planning and management : Cases from urban centers in Tanzania

This paper illustrates the potential use of the theory of planned behavior as a guiding framework for understanding intentions and behavior in geospatial data sharing in Tanzania. A structured questionnaire survey, was constructed and sent to local governments as well as academic and private organizations that are major producers and/or users of geodata. The questionnaire covered issues of how collection of geodata is financed, management of geospatial data, and compatibility of spatial data-sets. The theory was found to be generally effective in accounting for intentions to share geospatial data in Tanzania (p <.01). Results show potential for data sharing between local governments and other organizations in Tanzania, and it is suggested that creating awareness among spatial data stakeholders and the establishment of a spatial data infrastructure policy framework will speed up geospatial data sharing

Land-use planning for sustainable urban development in africa : A spatial and multi-objective optimization approach

Land-use planning, which requires finding a balance among different conflicting social, economic and environment factors, is a complex task needed everywhere, including Africa. One example is the city of Zanzibar in Tanzania, which is under special consideration for land-use revision. From one side, the city has high potentials for tourist industry and at the other side there are major challenges with the city structure and poor accessibilities. In order to prepare a proper land-use plan for the city, a variety of influencing conflicting factors needs to be considered and satisfied. This can be regarded as a common problem in many African cities, which are under development. This paper aims to address the problem by proposing and demonstrating the use of Geographical Information System (GIS) and multi-objective optimization for land-use planning, in Zanzibar as a case study. The measures which have been taken by Zanzibar government to address the development challenges through the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) were identified by studying related documents and interviewing experts. Based on these, two objective functions were developed for land-use planning. Optimum base land-use plans were developed and mapped by optimizing the objective functions using the NSGA-II algorithm. The results show that the proposed approach and outputs can considerably facilitate land-use planning in Zanzibar. Similar approaches are highly recommended for other cities in Africa which are under development

Investigating an Agent Based Modelling approach for SDI planning: A case study of Tanzania NSDI development

Spatial Data Infrastructure (SDI) provides a platform for spatial data sharing and is a key for sustainable development. Developing countries, including Tanzania, are at different stages of implementing SDIs. The importance and advantage of implementation lie in the fact that considerable funds can be saved by avoiding duplication of data, and improving quality of decisions making as well as public services. However, SDI is very complex in nature, including many influencing factors and different stakeholders. This paper investigates the possibilities of using Agent-Based Modelling (ABM) for simulating an SDI development process in Tanzania, for better understanding and making better planning. The roles and actions of organizations were identified through interviews, and the results were analysed. The behaviour of individual organizations (stakeholders) while interacting with the system were observed and analysed. The growth results in terms of data availability, standards, and data sharing for each organization were plotted and priority tables were generated. The model was evaluated for consistency and the results were judged to be within a reasonable range. The ABM simulation depicted the main attributes of agents, their roles and their interactions while pursuing SDI development in Tanzania. The results will help SDI planners and stakeholders to understand the roles of partners and prioritize activities and actions for successful SDI implementation

SDI planning using the system dynamics technique within a community of practice: lessons learnt from Tanzania

There exist major challenges in accelerating the spatial data infrastructure (SDI) planning process in the developing countries as well as advocating for politicians to support the development of SDI, due to the high complexity of SDI, lack of knowledge and experience, and limited insight in the benefits. To address these challenges, a methodology for SDI planning in Tanzania, based on the system dynamics technique and the communities of practice concept, was adopted and applied within a community consisting of experts from stakeholder organizations. The groups gathered to develop an SDI plan, while they shared their knowledge and discussed their ideas that helped their understanding of SDI. By running the system dynamics model, the development of SDI over time could be simulated that gave the planning community an insight about the future effects of today’s plans and decisions. Finally, an optimum model could be developed by refinements and improvements done with the consensus of the SDI stakeholders. This model included the components and policies that are essential for a successful SDI implementation in Tanzania and can be used as a basis for SDI planning and help to gain political support. Lessons learnt from this research were promising regarding the usability of the methodology for SDI planning in comparable countries

Evaluating the land cover dynamics in the protected areas using GIS and Remote sensing techniques:the case of Nyerere National Park, Tanzania

Understanding land cover dynamics of protected areas is one area of active research and several studies have been done in this direction. However, such studies are limited with few parameters and lack a long-range spatial-temporal analysis to effectively understand land cover dynamics and thereby helping countries manage their protected areas sustainably. This research used Nyerere National Park (NNP) to explore its land cover dynamics from 1991 to 2021 and projected to 2050, vegetation health from 2000 to 2021 and surrounding human population from 1988 to 2021. The park’s land cover of 1991 and 2021 was explored using a smileCart classifier after training 897 samples of water, bareland, grassland, bushland and forest from the Landsat imagery. Its 2050 land cover was simulated using CA-Markov model. The park's vegetation health was studied using NDVI and EVI from the Landsat and MODIS imagery. Land cover classes with significant changes are forest and grassland. The forest areas showed a decreasing trend from 62%-to-52%-to-41% from 1991-to-2021-to-2050, while the grassland areas showed an increasing trend from 9%-to-17%-to-24%. The maximum NDVI values from the Landsat imagery showed a minimal decrease from 0.76 in 1991 to 0.75 in 2021. Many park’s areas have weak vegetation based on the overall NDVI and EVI results. The study also identified rapid increase in human population around the park, and agricultural activities taking place in some of its areas. The results of this study provide a new reference to NNP and other studies in all other protected areas