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Environ Monit Assess. 2016 Aug;188(8):470. doi: 10.1007/s10661-016-5469-y. Epub 2016 Jul 14.

Mapping deforestation and urban expansion in Freetown, Sierra Leone, from pre- to post-war economic recovery.

Author information

1
Magbosi Land, Water and Environment Research Center (MLWERC), Sierra Leone Agricultural Research Institute (SLARI), PMB 1313, Mile 91, Northern Province, Sierra Leone. l.mansaray@slari.gov.sl.
2
Institute of Remote Sensing and Information Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China. l.mansaray@slari.gov.sl.
3
Key Laboratory of Agricultural Remote Sensing and Information Systems, Zhejiang Province, Hangzhou, 310058, People's Republic of China. l.mansaray@slari.gov.sl.
4
Institute of Remote Sensing and Information Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China.
5
Key Laboratory of Agricultural Remote Sensing and Information Systems, Zhejiang Province, Hangzhou, 310058, People's Republic of China.
6
Magbosi Land, Water and Environment Research Center (MLWERC), Sierra Leone Agricultural Research Institute (SLARI), PMB 1313, Mile 91, Northern Province, Sierra Leone.

Abstract

Freetown, the capital of Sierra Leone has experienced vast land-cover changes over the past three decades. In Sierra Leone, however, availability of updated land-cover data is still a problem even for environmental managers. This study was therefore, conducted to provide up-to-date land-cover data for Freetown. Multi-temporal Landsat data at 1986, 2001, and 2015 were obtained, and a maximum likelihood supervised classification was employed. Eight land-cover classes or categories were recognized as follows: water, wetland, built-up, dense forest, sparse forest, grassland, barren, and mangrove. Land-cover changes were mapped via post-classification change detection. The persistence, gain, and loss of each land-cover class, and selected land conversions were also quantified. An overall classification accuracy of 87.3 % and a Kappa statistic of 0.85 were obtained for the 2015 map. From 1986 to 2015, water, built-up, grassland, and barren had net gains, whereas forests, wetlands, and mangrove had net loses. Conversion analyses among forests, grassland, and built-up show that built-up had targeted grassland and avoided forests. This study also revealed that, the overall land-cover change at 2001-2015 was higher (28.5 %) than that recorded at 1986-2001 (20.9 %). This is attributable to the population increase in Freetown and the high economic growth and infrastructural development recorded countrywide after the civil war. In view of the rapid land-cover change and its associated environmental impacts, this study recommends the enactment of policies that would strike a balance between urbanization and environmental sustainability in Freetown.

KEYWORDS:

Change detection; Civil war; Freetown; GDP growth; Land-cover; Population growth

PMID:
27418077
DOI:
10.1007/s10661-016-5469-y
[Indexed for MEDLINE]

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