Land cover GIS databases, support for the implementation of the European agriculture and environment programs.

Badea, Alexandru ; Dana, Iulia Florentina ; Moise, Cristian 等

1. INTRODUCTION

Land cover is the observed (bio) physical cover of the Earth's surface. Land use is characterized by the arrangements, activities and inputs people undertake in a certain land cover type to produce, change and maintain it (Di Gregorio & Jansen, 2000). Land Cover Classification System (LCCS) was initiated by the United Nations Environment Program (UNEP) and the Food and Agriculture Organization (FAO) in 1993. Its main objective was represented by the elaboration of a reference and standardized classification of land cover that may be applicable anywhere in the world.

In Romania, the FAO-LCCS project consists of two geo-databases created upon the coverage of Landsat TM satellite images corresponding to the years of 2000 and 2003. The project was able to provide to the Ministry of Agriculture an objective and accurate database of the land cover for the whole country and also detailed land cover/land use maps for areas of particular agricultural interest. Also, the output of the project was used in case of emergency situations, for example the floods that affected Romania in 2005 and 2006. Now, a third complete coverage of Romania, containing high resolution multispectral satellite images acquired in 2007, is added to this impressive dataset. The project is intended to develop a set of methods and rules for data processing and validation that can be applicable to images acquired once in three or four years.

Recently, European Space Agency (ESA) established an international partnership with UN FAO and others research institutes for the creation of a global and detailed portrait of Earth's land cover with a resolution never obtained before: GlobCover. GlobCover is based on the imagery acquired by the Medium Resolution Imaging Spectrometer (MERIS)--Envisat between 2005 and 2006 with the resolution of 300m. GlobCover is extremely useful for climate change study (modeling of the climate change extent and impacts), ecosystem management (study of the natural and managed ecosystems) and worldwide land-cover trends identification. GlobCover's thematic legend is compatible with LCCS (Arino et al., 2007).

2. METHODOLOGY

2.1 LCCS concept

In the frame of LCCS, the classification of the land cover classes is made in two main phases:

--Dichotomous Phase--in this phase there are identified 8 major land cover types: cultivated and managed areas, (semi) natural vegetation, cultivated aquatic areas, (semi) natural aquatic vegetation, artificial surfaces, bare areas, artificial water-bodies, natural water-bodies, snow and ice.

--Modular-Hierarchical Phase--in this phase a set of diagnostic criteria are defined for each major cover types.

A team of experts from different fields of activity was involved in the elaboration of the LCCS legend that comprises of land cover classes specific to Romania. During the realization of the three LCCS projects (the years of 2000, 2003 & 2007) the legend has been continuously updated.

The land cover classes that appear in the figure below represent: LDU--low density urban area, ORD--orchard, F forest, SSH--small sized herbaceous field, LSH--large sized herbaceous field, GRL--grassland, GRL/SHR/TRS grassland, shrubs, trees (mixed class). These are only a few of the complex legend which comprises of more than 50 land cover classes defined for the territory of Romania.

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2.2 Input data

The satellite images which represent the basis of the first two Romanian FAO-LCCS projects were acquired by Landsat TM in the years of 2000 and 2003. The identification of the land cover classes was made by direct photo interpretation.

Automatic image classification (Lillesand et al., 2004) was also performed for several test areas. The GIS interactive database (Arctur & Zeiler, 2004), which is used to guide the photo interpretation process, is land use/land cover focused and contains a description of the interpretation procedures according to the adopted methodology and also a more detailed classification of the identified classes. The geographic interface contains field data, pictures, satellite images, aerial photos, vegetation index images and other geo-referenced information (geology, soils, etc.).

In the framework of the RO-LCCS-2007 project, SPOT 5 multispectral images with the spatial resolution of 10m were acquired; these images allow a multi-temporal and detailed analysis adapted to specific characteristics of landscape.

2.3 Objectives

The data regarding the land use represent an important feature for the environment monitoring and for political decisional initiative. The land cover (Lambin & Geist, 2006) is the most important characteristic of nature and it is used for the following processes: diagnosis and forecast for sustainable management at the level of regions and countries; monitoring and use of natural resources (agriculture, water and forest), etc.

2.4 Work flow

The results are exported in vector format, compatible with the most known GIS systems. For each database, approximately 730 land cover maps are produced, at the scale of 1:50.000.

This research project takes into account the evolution of data acquired by the new Earth Observation satellites, as well as advanced methods for semi-automatic and automatic data processing. The automation limit that can be achieved without jeopardizing the quality of relevant information will be evaluated. A synthetic chart containing the processing steps of the LCCS project is presented next.

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3. CONCLUSION

The RO-LCCS-2007 project approach follows the GMES (Global Monitoring for Environment and Security) actions in Romania, according to the development and use of remote sensing techniques for national environment protection and rehabilitation.

The resulting database can be included in the Integrated Administration and Control System/Land Parcel Identification System (IACS/LPIS) database and other already functional databases from the Ministry of Environment.

The analysis of this dataset provides support for the development plans of the territorial infrastructure, sustainable development in agriculture and implementation of "Natura 2000" directives.

Indirectly, correlated with statistical data produced by the National Institute for Statistics, this unique database will offer the possibility to analyze the socio-economical relations from more objective points of view.

RO-LCCS-2007 will be part of the "Technical Assistance to Develop the Environmental Related GIS Maps--Romania" Phare Project elaborated by a consortium led by IGN France International. The beneficiary of the project is the Romanian Ministry for Environment and Sustainable Development.

In the future, the LCCS geo-database will be permanently updated and completed with different types of data. The results and the elaborated methodology will be published in a scientific guideline.

RO-LCCS-2007 offered the possibility to obtain the 3rd updated series of the FAO-LCCS database by using recent advanced technologies, adapted to the Romanian conditions. This way, Romania possesses a dataset unique at global level.

4. REFERENCES

Arctur, D. & Zeiler, M. (2004). Designing Geodatabases: Case Studies in GIS Data Modeling, ESRI Press, ISBN 9781589480216, Redlands, California

Arino, O.; Gross, D.; Ranera, F.; Bourg, L.; Leroy, M.; Bicheron, P.; Latham, J.; Di Gregorio, A.; Brockman, C., Witt, R.; Defourny, P.; Vancutsem, C., Herold, M.; Sambale, J.; Achard, F.; Durieux, L.; Plummer, S. & Weber, J.-L. (2007). GlobCover: ESA Service for Global Land Cover from MERIS, Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007), IEEE, pp. 2412-2415, ISBN 978-1-42441211-2, Barcelona, July 2007

Di Gregorio, A. & Jansen, L. (2000). Land Cover Classification System (LCCS): Classification Concepts and User Manual, FAO, ISBN 92-5-104216-0, Italy

Lambin, E. & Geist, H. (2006). Land Use and Land Cover Change--Local Processes and Global Impact, Springer, ISBN: 978-3-540-32201-6, Berlin, Heidelberg

Lillesand, T., Kiefer, R. & Chipman, J. (2004). Remote Sensing and Image Interpretation--Fifth Edition, John Wiley & Sons, Inc., ISBN 0-471-45152-5, USA