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EXTENSIBLE LAND USE AND LAND COVER CLASSIFICATION FRAMEWORK
DESIGN BASED ON REMOTELY SENSED DATA
Wang Juanle
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing,
China - wangjl@igsnrr.ac.cn
KEY WORDS: Land use, Land cover, Classification system, Extensible model, ISO 19115, Remote sensing interpretation
ABSTRACT:
There are lots of land use/land cover classification systems in the world facing to different research targets and objectivities. And
with the crossing of multi-disciplines and expanding of the research area, more and more land use/land cover classification systems
are designed. This brings the difficulties for datasets’ exchange, integration and fusion which use different classification systems.
The problem faced to land use/land cover classification systems are similar with the problem of metadata standards. ISO TC211
designed an extension metadata standard framework for geographic data, and drew up the ISO Metadata Standard 19115.
Enlightened by the ISO 19115 metadata extensible model, the paper brings forward the land use/land cover extensible classification
framework. The framework is composed of 3 tiers, i.e., land use/land cover core classes, corpora classes and application profile
classes. The core and corpora classes are derived from the main international land use/land cover classification systems in the world.
Extension principle and methods are designed in this framework. This ensures many application classification profiles can be
extended from the core classes and corpora classes easily.
1. INTRODUCTION
1.1 General Instructions
The Land Use and Land Cover Change (LUCC) Project is a
Programme Element of the International Geosphere-Biosphere
Programme (IGBP) and the International Human Dimensions
Programme on Global Environmental Change (IHDP). LUCC
was launched in 1995 and now it has been one of the key
research tasks in Global Environment Change Research area.
Land use/land cover classification system is not only the basic
of LUCC research, but also the interface for the datasets
exchange, integration and sharing in different countries and
regions. But, there are lots of land use/land cover classification
systems in the world facing to different research targets and
objectivities. These existed and being formed classifications
have their own content, syntax and semantic structures. This
brings the difficulties for datasets’ exchange, integration and
fusion which use different classification systems. With the
crossing of multi-disciplines and expanding of the research area,
more and more land use/land cover classification systems are
proposed. This adds the difficulties mentioned above. Face to
the problem, this paper try to design an extensible land use/land
cover classification framework, which will adapt to the change
of various research subjects and research objectives. With the
development of EOS, especially the development of GEOSS,
remotely sensed data has been one of the most important data
sources for LUCC research nowadays. The paper focuses on the
extensible classification framework for the application which
uses remotely sensed data.
1.2 Land Use/Land Cover Classification System Progress
There are many kinds of land use/land cover classification
systems based on remotely sensed data sources in the world.
Some popular ones used remotely sensed data sources are listed
as follows.
1. USGS land use/land cover classification system
USGS land use/land cover classification system was designed
in 1976. Because Anderson is its main designer, it is also called
Anderson classification system. It is divided into 4 levels. Level
I focus on the land use/land cover macro types and land
resources natural & ecological background. This classification
information can be acquired by remotely sensed data
interpretation. Level II is the detail types of level I. This
information can be acquired by the interpretation of Aerial
photographs. Level III and IV is designed based on level II.
Anderson classification system is used widely in America and it
has important influence in the world.
2. FAO/UNEP, IGBP and UMd classification system
Land Cover Classification System (LCCS) was proposed in
1996 by FAO/UNEP. LCCS actually is a decision tree which
includes two phases, i.e., Dichotomous phase and Modular
hierarchical phase. Although LCCS aims to promote its
application widely, it is restricted because it pays more
attention to the geographical special features and the
classification types are defined differently in various extended
systems. In 1990s, according to the global change research
requirements, based on AVHRR remotely sensed data IGBP
built the land cover classification system including 17 primary
types, and University of Maryland built the UMd land cover
classification system including 14 primary types. While, these
two classifications are restricted in macro global land cover,
they are not used in regional land use application with high
resolution.
3. Chinese Academy of Sciences land use classification
system
Chinese Academy of Sciences land use classification system
was designed in 1991. This classification was used in “National
Resources and Environment Macro Investigation and Dynamic
Change Research based on Remote Sensing” which is one of
the key application projects in eighth five year plan of China. It
is divided into 2 levels. Level I includes 6 primary types and
level II includes 25 types. It is suitable for regional land use
