Title
FJ_Landuse Landcover
Abstract

Land cover refers to the physical and biological cover over the surface of land, including water, vegetation, bare soil, and/or artificial structures. Land use usually refers to signs of human activities such as agriculture, forestry and building construction that altered the original land surface processes. The Land Use / Land Cover (LULC) maps were developed using remotely sensed data (i.e., satellite imagery) of different resolution and vintage and validated with the aid of some ground truthing, virtual truthing (using high-resolution imagery of more recent vintage and other internet resources), agriculture census, and other ancillary data collected during the course of the project. Preliminary interpretation of the Land Use / Land Cover (LULC) data from the satellite imagery was carried out by using an image classification algorithm and was enhanced by using imagery parameters such as tone, texture, pattern, size, shape and contextual association. This process was further improved using onscreen digitization of the known crops on high resolution satellite imagery. A Normalized Difference Vegetation Index (NDVI) was generated and used for classifying forest areas classification into dense, open, or shrub forests. Given the methodology adopted, it is to be expected that in some instances the information included in the LULC maps may be obsolete and inaccurate. The LULC maps developed are suitable for the scope of assessing wind and flood hazard (roughness factors and precipitation runoff percentages) as well establishing a crop exposure database. Data Sources: Publically available EO-1, LandSat imagery, partial coverage 10m SPOT, others. Compiled by AIR Worldwide.

Publication Date
Type
Vector Data
Keywords
Landuse
Category
FJI
Owner
More info
-
Language
English
Supplemental Information

The detailed LULC map for Fiji was developed by AIR covers all the main islands. Additional field survey was done extensively in Viti Levu, the main Island o...

Attribute Name Label Description Range Average Median Standard Deviation
ID NA
CLASS_NAME NA
SUB_CLASS NA
COUNTRY NA

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