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Mission With Niassa National Reserve

Mission with Niassa National Reserve

Conducting GIS Databank design, Needs Assessment, and Training in Mozambique

The Niassa National Reserve, a non-profit organization located in northern Mozambique requested a GISCorps volunteer to assist them in two capacities: 1) conducting a GIS Needs Assessment of their existing GIS (remotely), and 2) training their local staff on the use of ArcGIS software for 3 weeks. Established in 1954, Niassa is one of the oldest Reserves in Mozambique and holds the greatest abundance and variety of wildlife in the country.

In cooperation with Madyo Couto, the reserve’s representative for several months, the Rutgers volunteer team cataloged, classified and organized all of the GIS data for the reserve into a file-based data structure built to reflect the way the reserve collects and uses data. In addition, they designed a data template for standardization and documentation of future data.

Dave Smith, a former Rutgers graduate student was brought onto the project to handle on-site training of the reserve’s staff. However, a change in reserve management led to changes in priorities, and on-site training was no longer feasible. A number of options were discussed. Ultimately it was decided that, since the reserve’s use of GIS would be primarily focused on producing maps for planning and communication purposes, simplifying the map generation process would minimize the training needed to perform entry-level tasks.

Dave created a series of map templates designed to dramatically simplify the map design process. Defining a structured system of layer groups would allow staff to quickly create maps by simply dropping data of a given type into the corresponding layer group. This, along with a set layout and basic contextual datasets, streamlined the map design process and established a consistent look and feel for all of the reserve’s map products.

Finally, in lieu of on-site training, Dave developed a user manual covering the basic use of the templates, along with topics such as labeling features, editing the legend, and the treatment of symbology for different types of data.

The end results of this project are structured, well-defined data management and mapping procedures that should allow for significant improvements to the way the reserve management are able to use their GIS data for planning, communications, and analysis.

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