Victorian Dominant Land Cover, 2009-2013


Autoria(s): Sheffield, Kathryn; Morse-McNabb, Elizabeth; Clark, Rob; Robson, Susan; Lewis, Hayden
Cobertura

LATITUDE: -37.000000 * LONGITUDE: 144.000000

Data(s)

20/04/2015

Resumo

There is a demand for regularly updated, broad-scale, accurate land cover information in Victoria from multiple stakeholders. This paper documents the methods used to generate an annual dominant land cover (DLC) map for Victoria, Australia from 2009 to 2013. Vegetation phenology parameters derived from an annual time series of the Moderate Resolution Imaging Spectroradiometer Vegetation Indices 16-day 250 m (MOD13Q1) product were used to generate annual DLC maps, using a three-tiered hierarchical classification scheme. Classification accuracy at the broadest (primary) class level was over 91% for all years, while it ranged from 72 to 81% at the secondary class level. The most detailed class level (tertiary) had accuracy levels ranging from 61 to 68%. The approach used was able to accommodate variable climatic conditions, which had substantial impacts on vegetation growth patterns and agricultural production across the state between both regions and years. The production of an annual dataset with complete spatial coverage for Victoria provides a reliable base data set with an accuracy that is fit-for-purpose for many applications.

Formato

application/zip, 8447.0 kBytes

Identificador

https://doi.pangaea.de/10.1594/PANGAEA.845372

doi:10.1594/PANGAEA.845372

Idioma(s)

en

Publicador

PANGAEA

Relação

Victorian Dominant Land Cover, Metadata (URI: http://store.pangaea.de/Publications/SheffieldK_et_al_2015/Land_cover_metadata.pdf)

Direitos

CC-BY: Creative Commons Attribution 3.0 Unported

Access constraints: unrestricted

Fonte

Supplement to: Sheffield, Kathryn; Morse-McNabb, Elizabeth; Clark, Rob; Robson, Susan; Lewis, Hayden (2015): Mapping dominant annual land cover from 2009 to 2013 across Victoria, Australia using satellite imagery. Scientific Data, 2, 150069, doi:10.1038/sdata.2015.69

Palavras-Chave #SAT; Satellite remote sensing; victoria
Tipo

Dataset