Applying the global standard FAO LCCS to map land cover of rural Queensland
Article
Article Title | Applying the global standard FAO LCCS to map land cover of rural Queensland |
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ERA Journal ID | 4626 |
Article Category | Article |
Authors | Perera, Kithsiri (Author), Apan, Armando (Author), McDougall, Kevin (Author) and Samarakoon, Lal (Author) |
Journal Title | Asian Journal of Geoinformatics |
Journal Citation | 11 (3) |
Number of Pages | 11 |
Year | 2011 |
Place of Publication | Bangkok, Thailand |
ISSN | 1513-6728 |
Web Address (URL) | http://www.geoinfo.ait.ac.th/ajg/index.php/journal/article/view/4 |
Abstract | Production of land cover maps has developed rapidly with the introduction of satellite images. However, these mapping tasks face a common challenge in adopting an internationally accepted classification scheme. Classification schemes were generally tailored to match local conditions without a flexibility to apply in other parts of the world. Land cover mapping in Australia is also facing the same dilemma, “the lack of standard classification system” to classify its massive land mass and compare internally and internationally. To address this issue, the Food and Agriculture Organization (FAO) produced a widely acceptable land cover classification system (FAO LCCS) in year 2000, based on an a priori (pre-decided) approach to classify the land to match with any region of the world. In this study we classified rural Queensland land cover, using the hierarchical and the a priori method used in FAO LCCS. Under the a priori approach, all classes were determined before the classification start to maintain the standardization of categories. The hierarchical dichotomous approach was (divide into subcategories) applied afterward, to obtain classes without having any conflict between two given land cover types. We classified satellite images of two rural Queensland regions, Hughenden grasslands and semi-arid Mt Isa. After classifying regions into level 1 to level 3 (FAO pre-set classes), classifiers based on spectral values and field investigations were implemented to build the level 4. Primarily, SPOT 10m images were classified for land cover maps, however, all other available information were utilized for the classification process. Field investigations were carried out to verify uncertainties in spectral values and to collect ground truth information. Results of the study rendered well-classified two maps at 10m resolution with over 80% overall accuracy. The most significant outcome of the study is the successful implementation of FAO LCCS approach to local conditions of Queensland, which could serve as a guideline to map other regions in Queensland and other states of Australia. |
Keywords | FAO LCCS, a priori classification, dichotomous phase, Modular-hierarchical phase, land cover classifiers. SPOT 10m data |
ANZSRC Field of Research 2020 | 379999. Other earth sciences not elsewhere classified |
401399. Geomatic engineering not elsewhere classified | |
Public Notes | Open access. |
Byline Affiliations | Australian Centre for Sustainable Catchments |
Department of Surveying and Land Information | |
Asian Institute of Technology, Thailand | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q1283/applying-the-global-standard-fao-lccs-to-map-land-cover-of-rural-queensland
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