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- W812823374 abstract "Information on the extent, location and condition of semi-natural habitats is essential to deliver the national targets to achieve the UK commitment to Biodiversity 2020 (Defra, 2011). This strategy aims to halt overall biodiversity loss by 2020 and move towards a position of net gain. In order to achieve this, both local and national bodies need detailed information on the habitats present over their entire area. Remote sensing provides opportunities for cost-effective, rapid and repeatable habitat mapping. This paper presents a method used to produce a seamless habitat map of the county of Norfolk, UK, of sufficient detail to inform land management decisions. Key aspects of the method were the development of parallel classification systems using different input data combinations and a long-term, volunteer-based map validation and update procedure. The habitat classification method utilised multiple earth observation platforms characterised by differences in spatial resolution, spectral range and season of image capture. The combinations of image data used were very important for the success of the analyses. The classification process was guided by ecological principles and local knowledge, along with targeted ground-truthing to guide class associations, confirm underlying ecological processes and to assess accuracy, and map revision. The study found that automated methods of analysis were most effective when classifying habitats characterised by distinctive dominant cover species, or groups of dominant species. The methods were least effective at identifying habitats defined by the presence of low growth-form species at low frequency or where they form understorey vegetation; in such cases field checking is vital to confirm the habitat class assignment. This scale of mapping can be used in combination with targeted, sustainable field survey effort to provide the level of information needed by decision makers to support Biodviersity 2020 targets and a wide range of other policy needs. The map has already been adopted by a wide range of organisations and finding application in such areas as Green Infrastructure, Living Landscape and habitat suitability modelling." @default.
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- W812823374 date "2015-11-01" @default.
- W812823374 modified "2023-09-27" @default.
- W812823374 title "Use of remote sensing to produce a habitat map of Norfolk" @default.
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- W812823374 doi "https://doi.org/10.1016/j.ecoinf.2015.06.003" @default.
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