Spatial Data Infrastructure for Pro-poor Land Management (4171) |
| Kevin McDougall and Dev Raj Paudyal (Australia) |
Mr. Dev Raj Paudyal
PhD Candidate
Faculty of Engineering and Surveying
University of Southern Queensland
West Street
Toowoomba
4350
Australia
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| Corresponding author Mr. Dev Raj Paudyal (email: paudyal[at]usq.edu.au, tel.: + 61 7 4631-2633) |
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| [ abstract ] [ paper ] [ handouts ] |
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Published on the web 2010-01-14
Received 2009-11-19 / Accepted 2010-01-14 |
| This paper is one of selection of papers published for the FIG Congress 2010 in Sydney, Australia and has undergone the FIG Peer Review Process. |
FIG Congress 2010
ISBN 978-87-90907-87-7 ISSN 2308-3441
http://www.fig.net/resources/proceedings/fig_proceedings/fig2010/index.htm
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Abstract |
| Most of the developing countries experience a massive migration from rural areas to cities where the majority of the new urban dwellers settle in non-regularised areas, often in locations that are exposed to natural hazards (such as land slides and flooding) and to ill health, illiteracy and unemployment. Lack of secure tenure discourages residents from improving conditions through investment in their houses and in common services such as water, sewerage, roads, etc. City authorities generally consider slum or informal settlement as illegal. Since these settlements are not part of the formal land management system there is also a general lack of reliable information necessary for planning and policy formulation required for upgrading and regularisation of these areas. Various organisations are working to improve the living conditions of slum dwellers and move them into the formal system. UN-HABITAT is one of the organisations working for the Habitat Agenda and has launched a pro-poor land management concept to improve the lives of slum dwellers through a flexible approach. Spatial information infrastructure is critical to planning and decision making for pro-poor land management. However, the conventional Spatial Data Infrastructure (SDI) concept is inadequate for informal settlement upgrading and regularisation. Therefore it is important to explore an appropriate SDI to accommodate new forms of legal evidence, utilisation of new technologies and open spatial information services.
The aim of this paper is to explore a Spatial Data Infrastructure model for Pro-poor Land Management in developing countries. In this context, a case study methodology has been adopted. Two cities Kathmandu Valley (five major municipalities; Kathmandu, Lalitpur, Bhaktapur, Kritipur, and Thimi from Nepal) and Allahabad (from India) are selected for the study. In both of the cities, the slum dwellers live without tenure rights, in very poor conditions, and mostly occupied public land. The slum conditions and their characteristics are described. A five step approach for pro-poor land management has been identified as slum identification and mapping, development of a relevant framework, application of GI technology, building spatial data infrastructure, city-wide slum upgrading and spatial planning. An alternative model of spatial data infrastructure for pro-poor land management has been suggested and its characteristics are described.
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| Keywords: GSDI; Land management; Security of tenure; Access to land; Informal settlements; land administration; pro-poor land management; informal settlement; spatial data infrastructure; slum |
