295
© Springer International Publishing AG 2017
R. Díaz-Delgado et al. (eds.), The Roles of Remote Sensing in Nature Conservation,
DOI 10.1007/978-3-319-64332-8_15
Integrated Land Cover and Change
Classifications
Richard Lucas and Anthea Mitchell
Abstract For nature conservation, regular provision of consistent, timely and useable classifications of land covers and change is highly beneficial but is rarely
achieved. This chapter outlines the concepts behind the Earth Observation Data for
Ecosystem Monitoring (EODESM) system, which facilitates the description and
classification of any site worldwide according to the Food and Agriculture
Organisations (FAO) Land Cover Classification System (LCCS; Version 2) and with
reference to environmental variables retrieved from earth observation. Changes in
land cover, as well as causes and consequences, are described through the accumulation of evidence and the system recognises these to be numerous, highly variable
and specific to different elements of the landscapes. Hence, they can be captured by
considering information provided by a range of sensors operating in different modes
and over different temporal frequencies and scales. The EODESM system is available at no cost and its ease of use makes it well suited to supporting nature
conservation.
Keywords Land cover • Land cover change • Environmental variables • Earth
observation • Classification • Ecopotential
Introduction
Imagine you are driving through a landscape and you are able to select any area of
ground and go back in time, seeing all its transitions and freezing the frame as and
when you liked. Was it covered in snow last winter, and was this deep or just a light
covering; or when did the spring leaves start to appear and then fall? Or, you want
to know whether the road you are now driving along is flooded or clear given there
had been intense rainfall in the mountains the night before? What kind of landscape
might this be in 50 years time and what might determine how it got there?
Within decades or less, the ability to routinely look back in time, assess current
situations and perhaps predict the future will most likely be a reality, particularly
R. Lucas (*) • A. Mitchell
Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences,
The University of New South Wales, High Street, Kensington (Sydney), NSW 2052, Australia
e-mail: richard.lucas@unsw.edu.au; anthea.mitchell@unsw.edu.au
© Springer International Publishing AG 2017
R. Díaz-Delgado et al. (eds.), The Roles of Remote Sensing in Nature Conservation,
DOI 10.1007/978-3-319-64332-8_15
Integrated Land Cover and Change
Classifications
Richard Lucas and Anthea Mitchell
Abstract For nature conservation, regular provision of consistent, timely and useable classifications of land covers and change is highly beneficial but is rarely
achieved. This chapter outlines the concepts behind the Earth Observation Data for
Ecosystem Monitoring (EODESM) system, which facilitates the description and
classification of any site worldwide according to the Food and Agriculture
Organisations (FAO) Land Cover Classification System (LCCS; Version 2) and with
reference to environmental variables retrieved from earth observation. Changes in
land cover, as well as causes and consequences, are described through the accumulation of evidence and the system recognises these to be numerous, highly variable
and specific to different elements of the landscapes. Hence, they can be captured by
considering information provided by a range of sensors operating in different modes
and over different temporal frequencies and scales. The EODESM system is available at no cost and its ease of use makes it well suited to supporting nature
conservation.
Keywords Land cover • Land cover change • Environmental variables • Earth
observation • Classification • Ecopotential
Introduction
Imagine you are driving through a landscape and you are able to select any area of
ground and go back in time, seeing all its transitions and freezing the frame as and
when you liked. Was it covered in snow last winter, and was this deep or just a light
covering; or when did the spring leaves start to appear and then fall? Or, you want
to know whether the road you are now driving along is flooded or clear given there
had been intense rainfall in the mountains the night before? What kind of landscape
might this be in 50 years time and what might determine how it got there?
Within decades or less, the ability to routinely look back in time, assess current
situations and perhaps predict the future will most likely be a reality, particularly
R. Lucas (*) • A. Mitchell
Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences,
The University of New South Wales, High Street, Kensington (Sydney), NSW 2052, Australia
e-mail: richard.lucas@unsw.edu.au; anthea.mitchell@unsw.edu.au