Ali A. Abkar
Assistant Professor in RS image analysis
Soil Conservation and Watershed Management Research Institute
Tel: +98 21 8786216 Fax: +98 21 8786215
Email: [email protected]
Ali Sadeghi Naeni
MSc student in RS
KN Toosi University of technology
Iranian Remote Sensing Center
+98 21 8786215
Email: [email protected]
Vegetation is one of the most important parameter for human environment assessment and monitoring, due to their specific role in geosphere-biosphere-atmosphere interactions and plays an important role in global climate change. The vegetation amount, control the partitioning of incoming solar energy in to sensible and latent heat fluxes, and consequently changes in vegetation amount will results in long term changes in the global and local climate, which in turn will affect the vegetation growth as a feedback. Vegetation has a special characteristic due to its distinct annual and seasonal changes. So it also is a sensitive indicator on the study of global and local environment change caused by climate or human activities.
In this decade, human being consequently realized the significance for global change monitoring, several international organizations, such as IGBP, have lunched very important programs among which land cover and vegetation change monitoring is a key project. The method for studying land use and vegetation change is developed very quickly as the progress of remote sensing technique in the world. Recent year, a number of global and regional land cover and vegetation studies have focused on the data of National Oceanographic and Atmospheric Administration (NOAA) advanced Very High Resolution Radiometer (AVHRR), principally due to its daily coverage, synoptic overview, data volume, and low cost. Multi-temporal, multi-resolution land coveruse datasets at different scales (local, regional, national, continental, and global) are very useful for scientific research in various disciplines and management of natural resources and environment.
IRAN is a large country with complex terrestrial land covers. Thus, it is necessary to pay enough attention to land cover monitoring and land use planning, so as to protect natural environment and ecosystem effectively. Many programs have been done to extract land coverland use information for small areas e.g., urban areas at local or regional scale by using high-resolution satellite data such as LANDSAT and SPOT involving small areas.
The main objective of this research is to define and evaluate the potential of coarse resolution data such as TERRA-MODIS 1-KM imagery for discriminating different vegetation covers and finally generating a land coverland use map for north half of IRAN for the year 2002.
The first satellite of EOS series is EOS AM-1 or TERRA satellite, which have 5 different sensors. MODIS radiometer is a key instrument in all of EOS satellites. MODIS with its 36 different bands from visible range of electromagnetic spectrum to thermal range with spatial resolution from 250 meter to 1000 meter is designed to develop the abilities of previous sensors such as AVHRR and CZCS radiometers. MODIS has better spatial, spectral and radiometric resolution than these sensors. Because of the MODIS capabilities in monitoring of changes in land, ocean and atmosphere, IRSC (Iranian Remote Sensing Center) decided to receive MODIS data every day.
The method used in this study for landcover mapping is a hybrid classification of monthly composites of NDVI data obtained from MODIS images received in IRSC. It is composed of several steps:
- Receiving MODIS data in IRSC UPGS (Universal Personal Ground Station),
- Radiometric and geometric correction of selected MODIS data,
- Calculating monthly composites of NDVI,
- Unsupervised classification of NDVI composites,
- Cluster Labeling,
- Supervised classification of mixed clusters,
It means that, the classification algorithm is a knowledge-based method. In this research the IGBP-DIS (Friedl, et al., 2002) Land-cover Classification System was adopted to develop a land cover map for north half of Iran.
Friedl, M.A., et al., 2002: Global Land Cover Mapping from MODIS: Algorithms and Early Results, Remote Sensing of Environment, Elsevier, 83 (2002), 287-302
Chen, X., Tateishi, R. , Wang, C., 1999: Developing of a 1-km landcover dataset of China using AVHRR data, ISPRS, 54 (1999), 305-316.
NASA’s Earth Observing System and TERRA as new sensors:
MODIS (MODERATE RESOLUTION IMAGING SPECTRORADIOMETER) Homepage: