Land use and land cover data changes in Indian Ocean Islands: Case study of Unguja in Zanzibar Island

Land use and land cover changes will continue to affect resilient human communities and ecosystems as a result of climate change. However, an assessment of land use and land cover changes over time in Indian Ocean Islands is less documented. The land use/cover data changes over 10 years at smaller geographical scale across Unguja Island in Zanzibar were analyzed. Downscaling of the data was obtained from SERVIR through partnership with Kenya-based Regional Centre for Mapping of Resources for Development (RCMRD) database (http://www.servirglobal.net), and clipped down in ArcMap (Version 10.1) to Unguja Island. SERVIR and RCMRD Land Cover Dataset are mainly 30 m multispectral images include Landsat TM and ETM+Multispectral Images. Landscape ecology Statistics tool (LecoS) was used to analysis the land use and land cover changes. The data provide information on the status of the land use and land cover changes along the Unguja Island in Zanzibar. The data is of great significance to the future research on global change.


a b s t r a c t
Land use and land cover changes will continue to affect resilient human communities and ecosystems as a result of climate change. However, an assessment of land use and land cover changes over time in Indian Ocean Islands is less documented. The land use/ cover data changes over 10 years at smaller geographical scale across Unguja Island in Zanzibar were analyzed. Downscaling of the data was obtained from SERVIR through partnership with Kenya-based Regional Centre for Mapping of Resources for Development (RCMRD) database (http://www.servirglobal.net), and clipped down in ArcMap (Version 10.1) to Unguja Island. SERVIR and RCMRD Land Cover Dataset are mainly 30 m multispectral images include Landsat TM and ETMþ Multispectral Images. Landscape ecology Statistics tool (LecoS) was used to analysis the land use and land cover changes. The data provide information on the status of the land use and land cover changes along the Unguja Island in Zanzibar. The data is of great significance to the future research on global change. &

Value of the data
The data provide information on the status land use and land cover changes across Unguja Island. The data are important in environmental assessments and against the impact of climate changes due to emissions of green house gases.
The data can be used for modeling the effects on pollinators in Indian Ocean Islands, in particular Zanzibar Island.
The data is valuable for improvements computational facilities, insufficient land use/land cover and reliable downscaling at smaller geographical scale.
The data are important for agriculture, settlement, urban planning, researcher, scholar and academics.

Data
Figs. 1 and 2 show the distribution of the main land use/land cover data, drawing on the databases for the period 2000 and 2010. Fig. 1 shows spatially continuous data on land use/cover classification scheme one, with six land use/cover types. Fig. 2 shows spatially continuous data on land use/cover classification scheme two, with 10 land use/cover types. These are followed by Tables 1 and 2 (Table 1), and it is evident enough on the maps (Figs. 1B and 2D) that forest has been converted to settlement and agriculture, probably due to population pressure, poverty, and unemployment.

Experimental design, materials and methods
In brief, the study site is localized in Zanzibar Island in Eastern and South Eastern coast of Africa. The Island is a semi-autonomous archipelago in Tanzania, but it has an autonomous administrative government for matters that are not part of the union government. The target area was Unguja Island and is located between latitude 6°08 0 and Longitude 39°20 0 E.
Our dataset was obtained from Regional Centre for Mapping of Resources for Development (RCMRD)-SERVIR database (http://www.rcmrd.org or https://www.servirglobal.net). RCMRD-SERVIR has verified the land use/land cover maps through ground verification campaigns, and baseline data are provided in the form of Landsat satellite imagery, auxiliary data and as well as historical maps. The classification systems includes forestland, grassland, settlement, shadow, wetland, water bodies, cloud, cropland, bare soil, mangrove forest, dense forest, sparse forest, moderate forest, open grassland, open bushland, and closed bushland were considered. Classification scheme one (includes only six land use/cover types) and classification scheme two (includes only ten land use/cover types) for the year 2000 and 2010 were used for analysis. Landscape ecology statistics tool (LecoS) [1,2] was used to analysis the changes over time and Geographic Information System GIS software (ArcMap version 10.1) to generate maps showing the spatially continuous data across the study area.