WIO Mangroves

Title
WIO Mangroves
Abstract

This dataset shows the regional (WIO) distribution of mangrove forests, derived from earth observation satellite imagery. The dataset was created using Global Land Survey (GLS) data and the Landsat
archive. Approximately 1,000 Landsat scenes were interpreted using hybrid
supervised and unsupervised digital image classification techniques. See Giri et al.(2011) for full details.

Publication Date
Type
Vector Data
Keywords
blue carbon , coastal , mangrove
Category
Biota
flora and/or fauna in natural environment. Examples: wildlife, vegetation, biological sciences, ecology, wilderness, sealife, wetlands, habitat
Regions
Africa , East Africa , Western Indian Ocean , Comoros , Kenya , Madagascar , Mauritius , Mayotte , Mozambique , Reunion , Seychelles , Somalia , South Africa , Tanzania
Owner
More info
-
Maintenance Frequency
Data Is Repeatedly And Frequently Updated
Restrictions
none
Purpose

The aim was to use a globally consistent and repeatable methodology, to produce a high-resolution dataset.

Language
English
Data Quality
Results were validated using existing distribution data and published literature. Note that small patches (< 900-2,700 sq-m) of mangrove forests cannot be identified using this approach. This methodological approach had a number of challenges, such as cloud cover and noise. There may also be areas where land cover was misclassified. As the dataset may still contain overlapping polygons, a dissolve operation (within a GIS) might be needed before surface area calculations are carried out. In addition to the present dataset (WCMC-010 (2011)), UNEP-WCMC distributes two other global mangrove data layers (WCMC-011 (2010), WCMC-012 (1997)). The two most recent datasets were both created using satellite imagery: WCMC-10 (2011) used a globally consistent methodology, whilst WCMC-011 (2010) also included observed data from various national/regional/international and other contributors.
Supplemental Information

Attribute table: country code (ISO3); surface area (AREA_KM2; in sq-km; calculated
using Global Mollweide equal-area projection); surface area (AREA_M2; in ...

Spatial Representation Type
vector data is used to represent geographic data
Attribute Name Label Description Range Average Median Standard Deviation
OBJECTID NA 16627.75 278340.00 159316.64
grid_code NA 1.00 1.00 0.00
ISO3 NA
PARISO3 NA
CTYPE NA
AREA_KM2 NA 0.06 0.00 0.79
AREA_M2 NA 6.40 0.21 78.63

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  • About

    Owner

    MOZALINK

    Project Partners: IRD (REUNION ISLAND), CORDIO (KENYA), Eduardo Mondlane University (MOZAMBIQUE), IHSM (MADAGASCAR), Ulanga Ngazidja (COMORES), University of Dar es Salaam (TANZANIA)

    Point of Contact

    cordio

    CORDIO East Africa

    Metadata Author

    cordio

    CORDIO East Africa