Analyze the contribution of Land Cover data base created in LCCS …€¦ · BRIEF DESCRIPTION OF THE RESEARCH TOPIC (1) Remote Sensing technology and products support agricultural

Analyze the contribution of Land Cover data base created in LCCS-3 style to support the design of the Area Frame Activity: “Improving methods for using existing land cover – land use databases for agricultural statistics”

JOHN S. LATHAM FAO-NRL

BRIEF DESCRIPTION OF THE RESEARCH TOPIC (1)

Remote Sensing technology and products support agricultural statistics in many ways. At the design level, using satellite images as source of information, the preparation of a land cover database can be useful to:

• Characterize the landscape

• Assist in the definition of the sampling frame

• Support the stratification

• Guide the sample allocation and ground survey

• Support Quality Control

The first Scientific Advisory Committee

FAO Headquarters, 18 and 19 July 2013

We would like to understand

how the FAO-NRL approach for the generation of a land cover object-oriented vector database created

using LCCS3 can contribute to the statistical agriculture and in particular to the

Area Frame design




The Land Cover Classification System (LCCS) is a very sophisticated description engine to characterize the

land cover features of the Earth

from LCCS2 to LCML (Land Cover Meta Language)

• LCCS 2, first version presented in 2002 (formalization of the concepts)

• Last version LCCS 3 LCML (Land Cover Meta Language)

approved in July, 2012 as an ISO standard

TC211 19144 – II LMCL

(Land Cover Meta Language)

model




The Unified Model Language Schema

of the LCML

The Land Cover Classification System (LCCS) LCML • Adheres to the concept that it is more efficient to standardize and formalize the rules and the conditions for the creation of the land cover classes rather than the specific categories(classes)/attribute terminology.

•A common protocol of rules to describe the “Real World” (meta-language) guarantee complete flexibility in the creation of categories and in the same time ensure semantic interoperability between them.

•The emphasis is no longer on the class name or class description but on the elements of the meta-language used to create a class. LCCS works by creating a standardized syntax to describe the Land Cover.

•The complex relationship between the elements of the language as the syntax rules regulating them are expressed in a standard modern modelling language the UML.

•UML diagram is a visual representation of a series of rules and their language structure.

•A predefined set of basic elements (BIOTIC and ABIOTIC) and their properties enriched in their semantic significance with “element” characteristics can be arranged in different types of vertical and horizontal patterns to describe a wide variety of distinctive and detailed land cover situations.

The Unified Model Language Schema of the LCML




• An ISO standard multipurpose db available in the country with the involvement and collaboration of many Institutions, Agencies for its generation.

• Creation of comparable databases, very important for a harmonized approach at any level of implementation.

• It provides an accurate definition of the landscape, kind of agriculture, size of the fields, etc..

• It provides a robust baseline at the design level • It provides a robust baseline for the definition of the sample size, the

stratification, the construction of the PSUs and sample allocation • The accuracy of the database can be evaluated • Land cover changes can be easily updated • Its creation is an opportunity for improved and sustainable capacity

development in Remote Sensing, GIS.

Benefits



Applications at the global scale (1) SEEA (System of Environmental-Economic Accounting)

Legend using ISO Standard for Land Cover Classification Land Cover Meta Language (LCML)



Applications at the global scale (2) SEEA (System of Environmental-Economic Accounting)

Legend using ISO Standard for Land Cover Classification Land Cover Meta Language (LCML)



Applications at the global scale (3)



LCCS-LCML Applications at the national/regional scale (1)















LITERATURE REVIEW (1)

• RS assist in many applications; • RS assist to the creation of vector databases through

interpretation. • Reviewed the main national approaches to

understand utilization of LCCS/land cover • No attempts to utilize a LCCS3 land cover database. • In Pakistan and Ethiopia, two FAO operational

projects this approach is applied.



LITERATURE REVIEW (2)

Libya Ethiopia Pakistan Technical support

Agency FAO FAO FAO

Implementing Agency MOA

CSA Central Statistical

Authority

EMA Ethiopia Mapping

Agency

SUPARCO

National Space Agency of

Pakistan

Data used

Landsat MSS

80m

Dated 1980

SPOT 5 5m resolution

2085 scenes

Dated 2006-2007

SPOT 5 m resolution

310 scenes

Dated 2012

Team 10mpersons with no

background in RS

12-15 persons

with no background in RS

10 persons

with background in RS

Methods

Digital processing

and Visual

interpretation

Segmentation Object-

based Segmentation Object-based

LC Classification system

adopted

Land Cover Classif –

precursor to LCCS FAO - LCCS2 FAO- LCCS3

Mapping Period From 1981 to 1983 From 2008 up to date

Intermittent

From 2012 up to date

continuous

Training On th job over 2

years Initial course of 2 weeks Initial course of 2 weeks

Supervision 1 land cover /RS

expert for 2 years

2 land cover experts

constantly present for the

first years

After the first 6 months

2 weeks land cover expert

supervision

To date

% of country mapped completed

50% circa Where the main agricultural

activities

of the country are located

30% circa Where the main agricultural

activities

of the country are located

Completion of the

mapping activities 1981 2016 2014



• Evaluate technical advantages to produce a multipurpose land cover database in LCCS3 style to assist sampling design at the national level.

• Prepare a concept note for suggestions and guidelines for the preparation of the LC db.

• Evaluate of the implications for the production of LCCS3 database in relation to:

- production cost; - technical capacity/technical structures in country; - life-expectancy of the Area Frame and the Land Cover database; - availability of remote sensing products and their costs; - Efficiency vs list frame approach - Efficacy of the sample size

SUB-TOPICS REQUIRING FURTHER RESEARCH (1)



• LCCS/LCML forms a viable and consistent harmonized DB `for use in supporting the development of area frames, improves the stratification process and achieves efficiencies in sample allocation

• Several countries in Africa and Asia are already complete and others can be added to the Global Strategy for Agri. Stats based on the available funding

• Updating the land cover and its associated changes will be an easier and more consistent process based on the use of LCCS/LCML

Recommendations



THANK YOU

[email protected]



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Documents

Analyze the contribution of Land Cover data base created in LCCS …€¦ · BRIEF DESCRIPTION OF THE RESEARCH TOPIC (1) Remote Sensing technology and products support agricultural