Ebook: Remote Sensing for a Changing Europe

Merhaba,

After Voss (Norway, 1981), Igls (Austria, 1982), Brussels (Belgium, 1983), Guildford (UK, 1984), Strasbourg (France, 1985), Lyngby (Denmark, 1986), Noordwijk (Netherlands, 1987), Capri (Italy, 1988), Helsinki (Finland, 1989), Toulouse (France, 1990), Graz (Austria, 1991), Eger (Hungary, 1992), Dundee (UK, 1993), Göteborg (Sweden, 1994), Basel (Switzerland, 1995), Malta (1996), Lyngby (Denmark, 1997), Enschede (Netherlands, 1998), Valladolid (Spain, 1999), Dresden (Germany, 2000), Paris (France, 2001), Prague (Czech Republic, 2002), Ghent (Belgium, 2003), Dubrovnik (Croatia, 2004), Porto (Portugal, 2005), Warsaw (Poland, 2006), and Bolzano (Italy, 2007), the EARSeL family met in a city where the continents meet. The ‘28th EARSeL Symposium and Workshops’ with the title ‘Remote Sensing for a Changing Europe’ took place in Istanbul, Turkey on 2–7 June 2008. Both the symposium and the accompanied two workshops were hosted by the Remote Sensing Division of the Istanbul Technical University (ITU) at the Süleyman Demirel Convention Center in the ITU Maslak Campus. The Symposium was chaired by Prof. Dr. Derya Maktav, Head of ITU Remote Sensing Department and co-chair of EARSeL SIG Urban Remote Sensing, and Prof. Dr. Rudi Goossens, Head of EARSeL. The Turkish Chamber of the Cadastre and Mapping Engineering, and the Scientific and Technological Research Council of Turkey (TÜBİTAK) also supported the meeting.

Technical presentations were on all fields of geoinformation and remote sensing, and especially on:

• Geoinformation and remote sensing

• New sensors and instruments

• Image processing techniques

• Time series analysis, data fusion

• Imaging spectroscopy

• Urban remote sensing, land use and land cover

• Radar remote sensing, LIDAR

• Land degradation and desertification

• Hydrology, land ice & snow, coastal zone

• Forestry, agriculture

• 3D spatial analysis

• World heritage

The meeting welcomed 220 registered participants from all over the world. Eighty papers were presented during the symposium (2–5 June) at the 21 oral sessions including the three special sessions. As well, 60 papers were presented at the poster sessions which were also presented during two ‘oral communications’ sessions where the authors had the opportunity to present their poster papers for 4–5 minutes and invite the participants to visit their posters for detailed information. The ITU Süleyman Demirel Convention Center with one conference hall, one senate hall and four workshop rooms served for the event.

In addition to these topics, the symposium also included three special sessions:

The special session ‘ASTER’, jointly held by ASTER and EARSeL, included applications of ASTER, such as the usefulness of thermal remote sensing images in the study of wet permafrost, and crop and water monitoring at the scale of a small agricultural region from ASTER data.

“SPOT” special session, jointly held by SPOT and EARSeL, focused on the new ASTROTERRA mission; a global database designed to build consistent and accurate geospatial datasets; assessing agri-environmental impact in the French West Indies and French Guyana; and the operational use of SPOT imagery for population and housing census in Africa.

The third special session ‘Seismic Geohazards’ chaired by Freek van der Meer, chair of the SIG Geological Applications, integrated valuable presentations on ASTER and geohazards; evaluation of the damaged provoked by seismic events through teledetected imagery; application of an integrated airborne hyperspectral and lidar dataset in resolving the frequency and intensity of earthquakes; predicting topographic aggravation of seismic ground shaking by applying geospatial tools; and tropical volcanic islands, coastal landslides and tsunami risk.

To encourage the establishment of two new SIG's, “Remote Sensing for Archaeology and Cultural Heritage” (3 June) and “Thermal Remote Sensing” (4 June), in addition to the already existing 14 SIG's, two lunch meetings were organized where the chairmen had the opportunity to advertise their new groups.

The ‘SIG on Remote Sensing for Archaeology and Cultural Heritage’, co-chaired by Dr. Rosa Lasaponara and Dr. Nicola Masini (Italy), addressed the researchers interested in the application of active and passive remote sensing technologies (ground, aerial and satellite) and in the information technologies for archaeological investigation, protection and valorization of cultural heritage.

Dr. Claudia Kuenzer of the German Remote Sensing Data Center, DFD of the German Aerospace Center, DLR presented the newly founded ‘SIG on Thermal Remote Sensing’. About 20 participants joined the lunch meeting and presentation, during which the goals of this new SIG were introduced. SIG-TRS envisages bringing the thermal community among the EARSeL laboratories closer together, and promoting a platform for exchange about methods, applications, new sensors and in-situ approaches in the field of thermal remote sensing.

The ITU-Center for Satellite Communications and Remote Sensing (ITU-CSCRS) where we had the technical visit, is located at the ITU Maslak Campus and is one of the foremost institutions around the world with a highly capable ground receiving station unit. It is the first center established in Turkey to conduct application oriented projects in remote sensing and satellite communications technologies and to serve national/international civil/military companies in their research, development, and educational activities. CSCRS has the capabilities of acquiring images from remote sensing satellites, processing data, and sending the products via satellite links to resident and foreign users. The station can receive images of the Earth's surface within a radius of 3000 km, which covers from Sweden to Sudan, and England to Kazakhistan. In the center the data acquired from SPOT-2, SPOT-4, RADARSAT-1, ERS-2, NOAA-11, NOAA-14, METEOSAT satellites are archived, formatted and processed with state-of-the-art technology.

After the technical visit at ITU-CSCRS on 2 June the icebreaker party of the symposium was organized in the same place on the same day.

In addition to the technical meetings, EARSeL-bureau meeting, Council meeting, co-editors meeting, and General Assembly took place on different dates during the event.

The participants of the symposium discovered the wealth of impressive sights all along the shores in a Bosphorus boat trip along Istanbul's famous waterway dividing Europe and Asia.

The symposium dinner took place at a restaurant close to the Fatih Sultan Mehmet Bridge from where a beautiful view of the Bosphorus could be enjoyed.

In conjunction with the symposium two workshops ran parallel and after the end of the symposium:

1st Workshop “Earth Observation From Research to Teaching in Schools and Universities” of the “Special Interest Group (SIG): Education and Training” of EARSeL chaired by Mario Hernandez, UNESCO; Rainer Reuter, University of Oldenburg, Germany; and Alexander Siegmund, University of Education Heidelberg, Germany, on 6 June, aimed at making the results obtained from more than 250 EARSeL member institutes available to the public.

The workshop further addressed the Global Environment and Security (GMES) programme of the European Commission (EC) and the European Space Agency (ESA).

The topics of the workshop included: earth observation for kids; science education in schools, high schools and universities; applications in biology, chemistry, geography, physics and mathematics curricula; training activities in GMES; the Global Earth Observation System of Systems (GEOSS) and other international programmes; and public outreach of environmental sciences and global change.

On 7 June, an open meeting of the EARSeL project “Science Education through Earth Observation for High Schools (SEOS)” followed the workshop, which was an initiative for using remote sensing in science education curricula in high schools funded under the 6th Framework Programme of the EC. Eleven different partners from several European countries in cooperation with the ESA have so far implemented the project.

The second workshop of the symposium was organized as the 4th Workshop of the EARSeL SIG on Developing Countries (chaired by Gürcan Büyüksalih, Turkey; Richard Sliuzas, Holland; and Peter Lohmann, Germany), in conjunction with the 8th workshop of the GIS in Developing Countries network (GISDECO 8), with the title “Integrating GIS and Remote Sensing in a Dynamic World” on 4–7 June 2008.

This workshop brought together experts from the EARSeL and GISDECO networks for the first time. Especially for developing countries, integration of remote sensing and GIS offers unique access to primary data on the status of land surfaces, as well as possibilities for analysis, visualisation and development of possible solutions to problems associated with dynamic changes of nature and humanity. Global urbanisation, climate change and its effects on natural and human systems, land use and land cover changes, and salinisation are imminent dangers. The workshop provided a forum for presenting and discussing results, and for exchanging expertise and experience among researchers and users engaged in solving the problems of developing countries.

The topics of this workshop included:

Adapted sensor and mapping methods (TerraSAR-X, ALOS, ASTER, IKONOS, QUICKBIRD, dynamics of urban development, biomass), environmental monitoring (land degradation, desertification, erosion), model development and integration (landuse and cover models, biosphere model, effects of climate change), DEM generation for developing countries (SRTM, Cartosat-2, ALOSPRISM), innovative remote sensing and GIS education (distance learning, professional development), theory and practice of partipatory GIS (case studies on community mapping and PGIS), GIT and poverty alleviation (food and water security, resilience), hazards and risk mitigation (measuring risks and adaptive planning systems), and managing global urbanisation (slum mapping, sustainable transport systems).

I would like to thank the members of the scientific committee who have contributed to the abstract review process, to the artist Beygü Gökçin who artistically combined space and music with piano; the band of the Turkish Air Force Academy for their exceptional performance at the opening session, to my colleagues from my department, and, of course, to my students for their great efforts before, during and after the symposium.

Finally, I wish good luck and success to my Greek colleauges who will organize the 29th EARSeL Symposium in Crete, Greece in 2009. See you in Crete.

With my best regards,

November, 2008, Istanbul

Prof. Dr. Derya Maktav, EDITOR

Istanbul Technical University, Remote Sensing Division, 34469 Maslak, Istanbul, Turkey

http://www.ins.itu.edu.tr/deryamaktav

dmaktav@ins.itu.edu.tr

Despite forecasts that global warming will increase Antarctic snowfall, there is some evidence that exactly the opposite is true. Analysis of the Global Precipitation Climatology Project (GPCP) data indicates a decrease in the accumulation on the Antarctic ice sheet over the last 29 years. The GPCP satellite remote sensing data, spanning the years 1979 to 2007, exhibits 6-year cycles in precipitation rate. Precipitation in these cycles from 1982 to 2005 has gradually decreased by 15%. This reduction is statistically significant.

Since the 27^th EARSeL symposium 2007 in Bolzano with WorldView-1 Cartosat-2A two more very high resolution optical satellites of a new group have been launched. Images with a ground sampling distance (GSD) of 0.45 m, which will be distributed with 0.5 m GSD, are operational available. In August 2008 GeoEye-1 shall be launched, having even 0.42 m GSD. With CBERS 2B an additional high resolution is in space. The system of 5 RapidEye satellites shall follow. The high number of new satellites gives a strong push to the 3D-Remote sensing. The wide spread of the stereo systems Cartosat-1 and ALOS/PRISM has improved the possibility of generating detailed and accurate digital elevation models based on space images. An overview of the new optical systems, but also a short information about new radar satellites and in near future planned missions together with the influence to the practical application is given. Only systems available for civilian use are respected in this overview.

As new trend in aerial application we have with mid format digital aerial cameras and the combination of vertical and oblique images like from Pictometry and Multivision. The digital mid format are now completed by combinations of cameras, closing the gap to the large format digital cameras.

Digital height models can be generated by interferometric synthetic aperture radar (IfSAR) or by automatic image matching. The images used for image matching should be taken within a short time interval to avoid changes of the object and different shadows. Stereo systems generating stereo combinations in general have some advantages.

For city planning and security services the combination of vertical and oblique images like from Pictometry and Multivision recently became very popular. For larger cities a high number of such image combinations are even included in Microsoft Virtual Earth. The geo-reference of the image combinations usually is based on direct sensor orientation – the combination of GPS and inertial measurement units. The images are taken by camera systems like Track'Air MIDAS, equipped with 5 Canon EOS cameras, each with 4992×3328 pixels. The Canon EOS is not really a metric camera; it keeps the inner and the system orientation only stable during one photo flight. The images are also used for simple measurement purposes as well as the generation of 3D-city models. If object information without disturbing loss of accuracy against the direct sensor orientation is required, a system calibration during the day of the photo flight has to be done. The method of calibration and achieved accuracy is described as well as the characteristics and potential of the image combinations.

This paper presents a comprehensive framework for determining the interaction between transport, land-use and environmental impacts, where the developed concepts were tested using a case study. As the study area, two bridges connecting Europe and Asia and the planned third bridge was selected, where the constructed transportation infrastructures had drastically changed the land-use profile and still have negative impacts on environment. After exploring the interaction systematically and identifying the land cover/use pattern specific for the Istanbul Metropolitan Area, possible alternatives routes for the new bridge were by means of multi-criteria decision making approach and potential prediction of impacts were performed. The former land-use, transport infrastructure data were integrated with Landsat TM satellite images retrieved in 1987, 1997 and 2005. In order to identify the pattern of interaction, the land use analyses of the Asian side of the Istanbul Metropolitan area were compared within a selected box buffering the current and planned highways. For the planned third bridge alternative scenarios were selected, where alternatives were environmental friendly, cost-efficient and compatible with the current infrastructure. The results show that, easy accessibility caused by the development in transportation infrastructures created an attraction in this region and urban areas expanded rapidly. By means of the shortly described methodology and achieved results, the proposed framework aids authorities and decision-makers to better facilitate sustainable transportation.

QuikScat and SeaWiFS data (2000–2007) covering the Mediterranean Sea were used for a multisensor study of the coupling between wind patterns and algal blooms in the Gulf of Lion and the Rhodes-Ierapetra gyre systems. In these near-coastal hotspots, atmospheric forcing creates (albeit with different mechanisms) surface conditions that cause convective processes and consequent nutrient upwelling from deeper layers. As phytoplankton growth in the otherwise oligotrophic Mediterranean basin is always nutrient-limited, the blooming triggered by these processes reflects the prevailing wind patterns. Highly dynamic features recur systematically in the pigment field of both regions, in the same periods (January to May).

Floods are among the most devastating natural hazards in Turkey and worldwide, causing the largest amount of casualties and property damage. GIS and remote sensing methods are very attractive, fast, and reliable tools for various flood applications and management. In this study, we investigated floods which occurred and are likely to occur in a study area in Istanbul, Turkey, to determine the potential use of these tools with respect to these floods. Floods which caused loss of life and property in the Yeniçiftlik stream basin located within the boundaries of Beykoz, a suburb of Istanbul, attracted our attention due to their negative impact on human life and activities, and this was selected as the study area. Many geographical parameters such as vegetation, topographic and geologic features, precipitation, and land use features play a significant role in the occurrence of flood related disasters. Data used were topographic, soil, vegetation, and geological maps at scale 1:25000, IKONOS pan-sharpened imaging (02.03.2008), as well as aerial photographs taken in 2006. Using the Arcinfo 9.2 Spatial Analyst module, flood risk maps were created, assigning different weights to vegetation, geologic and land use features, and other morphometric features such as slope, aspect, and so on. Land use and vegetation features were determined by applying a supervised classification technique to IKONOS data. All data were processed using HEC-GeoRAS (in ArcGIS) and HEC-RAS software. The results indicate that the precision and diversity of the data used greatly affects the precision of these risk maps.

The presented project being a part of rainfall-runoff modeling is focused on determination of relations between soil moisture changes detected in radar data and precipitations. One catchment area of– the Olse River in the northern Moravia is used for. The catchment's land cover classes derived from Thematic Mapper data are decisive for creation of homogenous land cover patches. The changes are determined from ERS-2 data. The radar data were chosen according to the flood precipitations date in the catchments covering either before and after flood period or only after a flood one. Radar image data processing is performed by following working steps: image data filtering, band subtraction, delineation and selection of the same land cover patches; these areas were subdivided according to their change values derived from the radar data subtraction. These subareas were evaluated in GIS to find relations between the spatial distribution of the radar data changes and hydrological, morphological, and soil conditions.

One of the most important events that cause anomalies in nature's balance is forest fires. Forest fires are also very serious threats in Turkey, which is located in the Mediterranean Region. While complete prevention of a forest fire is impossible, it is possible to reduce the damages of forest fires by constructing a forest fire risk map. In this study, we analyze a forest fire that took place at Kibriz Stream Canyon near the city of Antalya. The most important aspect of this fire was that the interference was very difficult due to the canyon's harsh landscape. Here, we show that a fire risk map can be especially beneficial for this area, and for other areas where fire interference is very difficult due to the unfriendly topography. Remote Sensing and Geographic Information System (GIS) were applied in this study for the assessment of the situation before and after the fire and for forming the fire risk map. Landsat TM (01.08.1990), Spot XS (24.06.2007) imageries and 1/25000 scale topography maps were used to generate a digital terrain model and to establish the land use classes by means of unsupervised and supervised classification algorithms. In addition, the normalized difference vegetation index (NDVI) was computed to compare the classified imageries before and after the fire. Comparison of the NDVI values helped us to determine the vegetation pattern change after the fire.

Topography and its derivatives (altitude, slope and aspect) have an effect on satellite-measured radiances. For mountainous areas the sun zenith and azimuth angles, as well as direction of observation relative to these are more limiting factors. In this paper four topographic normalization methods were used to correct the reflectance values of medium spatial resolution satellite data, namely MODIS. The performance of the topographic normalization methods is examined for snow covered areas of the study area located in the eastern part of Turkey. Modeling of snow-covered area in the mountainous regions of Eastern Turkey has significant importance in order to forecast snowmelt discharge especially for optimum use of water in energy production, flood control, irrigation and reservoir operation optimization. MOD09GKM data, which have the land surface reflectance having atmospheric correction, digital elevation model (DEM) and the geo-location files (MOD03) were used. It is obtained that statistical empirical correction method worked better compared to the other methods in removing the terrain effects for snow covered areas. The importance of topographic normalization in mapping the effective snow covered area in snowmelt modeling is also discussed and the early findings of Satellite Application Facilities on Hydrology (H-SAF) project, which is financially supported by EUMETSAT, is presented. Turkey is a part of the H-SAF project, both in product generation (e.g. snow recognition, fractional snow cover and snow water equivalent) for mountainous regions for whole Europe, cal/val of satellite-derived snow products with ground observations (synoptic, automated weather stations and snow courses) and impact studies with hydrological modeling in the mountainous terrain of Europe.

Recent access to Very High Spatial Resolution (VHSR) Satellite Images allows vegetation monitoring at metric and sub-metric scale, with individual trees now detectable. Therefore, it discloses new applications in precision agriculture for orchards and other tree crops.

In this paper, we present some methodological directions for classification, and extraction of specific agricultural information from these images. Aims are tree crop detection, plot mapping, species identification, and cropping-system characterization. This latter includes for instance row management (e.g. grid vs. line pattern, width of rows and inter-rows, row orientation), crown shape, and crown size estimation.

In this paper, we skip the segmentation step and consider that we have got a precise delimitation of plots that have a homogeneous content. To classify these plots, we have used expert knowledge in agronomy combined with image information in a decision tree.

Classification criteria were based on parameters resulting from the Fourier transform analysis or vegetation indices, derived as one single descriptor for the whole plot.

As a conclusion, the proposed methodology was found capable of classification and characterization of tree crops, provided the trees are clearly seen from above, and their planting is regular enough to give a response with Fourier analysis.

In order to improve operation on active fire detection, geostationary satellites as GOES, MSG and MTSAT are already operative and they have led the international community to think that the global observation network in real time may become a reality. The implementation of this network is the aim of the Global Observations of Forest Cover and Land Cover Dynamics (GOFC/GOLD) FIRE Mapping and Monitoring program, focused internationally on taking decisions concerning the research of the Global Change. The estimation of the minimal burning area detected by MSG-SEVIRI is analyzed in this work; it's a very relevant issue since it implies the sensor's operational availability in active fire detection. This minimum size is conditional on the fire location inside the pixel, as shown before from the theoretical point of view, among other factors such as atmospheric conditions, fire temperature, among others. A spatial analysis has been carried out, analyzing several parameters referred to spatial performances of MSG-SEVIRI sensor as pixel footprint in the 3.9 microns spectral band. In order to obtain results based on real data, a large data base focused on the active fire detection in the Iberian Peninsula has been studied. Statistical results obtained from a large data base of fires detections, show that the probability to detect a minimal size of 10ha is 90% and 4ha with 50%.

In Hydrology Satellite Application Facilities (HydroSAF) Project which is a financially supported project by EUMETSAT, the use of snow products retrieved from satellite images in hydrological applications and to observe the impact of the products are key issues. Turkey is a part of the HydroSAF project, both in developing satellite derived snow products (snow recognition, effective snow cover, and snow water equivalent) for mountainous areas, cal/val of satellite-derived snow products with ground observations and impact studies with hydrological modeling in the mountainous terrain of Europe. The snow recognition product for mountainous regions is evaluated in this paper. An algorithm has been developed for snow recognition over mountainous areas of Europe. The proposed algorithm uses Satellite Application Facility to support Nowcasting and Very Short Range Forecasting's (SAFNWC) cloud products. Two main validation processes have been applied for the snow cover product belonging to 19th January 2008 produced with SEVIRI data. First, the comparison of the SEVIRI snow cover product with the snow cover product produced from a single NOAA AVHRR data for the same date 19th January 2008 has been performed. Second, SEVIRI snow cover product was validated with 43 synoptic weather stations distributed over Europe.

The availability of high resolution satellite stereopairs also for the civil users opens new possible fields of application among which the automatic extraction of digital models of the surface, the stereoscopic restitution, as well as the possibility to appraise changes and transformations of areas following catastrophic events, as for instance seismic events. In this last case, obviously, as for all the monitoring studies, it is necessary to effect a comparison with the situation before the event.

Photogrammetry can fortunately also use older aerial acquisitions, very useful when substantial changes have occurred in the territory; normally, such historical aerial frames are easily available at a very reasonable cost.

In this paper is illustrated an experimentation including a first series of tests to evaluate the real possibilities of use of high resolution satellite images, acquired by the Ikonos satellite, to estimate changes caused by a seismic event happened in September 1997 in central Italy, causing relevant damages to a lot of buildings in the zone. It is interesting to evaluate the different capabilities of change detection tecniques on single images and the difference of DSMs extracted by aerial and satellite stereopairs. As reference have been assumed ortophoto maps and aerial frames of the same zone, acquired in years antecedent to the seismic event. From the comparisons, it is possible to underline the variations in the urban areas as the presence of new constructions, changes of the roads, areas with different use of the ground, etc.

“Lameiros” are ancestral semi-natural meadows, essential elements of mountain landscapes in Northern Portugal. In the “lameiros” a traditional irrigation system is used and water is applied all year around. They are mainly used for forage production for autochthonous bovine feeding, but they are also important for the water and nutrients cycle regulation, erosion control and as barrier to forest fires propagation. Although recognized for their economical, environmental, landscaping, cultural and genetic value, the perpetuation of these “lameiros” could be at risk, at medium term, due to human desertification in the mountain regions and to the announced constraints in use of water resources. To preserve these landscapes it is essential to know them better and to better characterize them. Therefore a monitoring program using remote sensing tools is now being developed to evaluate different patterns of “lameiros”, and their spatial extent and evolution. Two important questions are determinant in this program: the selection of the most appropriate spatial resolution for monitoring “lameiros”, and the availability of satellite historical data. In this context, NDVI were compared in two selected test sites, with and without full irrigation. Data were derived from several field campaigns with a spectroradiometer and using different sensors: i) Landsat 5 and Landsat 7 (30m pixel), ii) SPOT 4 and SPOT 2 (20m pixel), iii) SPOT 5 (10m pixel). The NDVI temporal series produced were evaluated considering “lameiros” management and weather data. Results obtained so far indicate that the SPOT images provide data at the most adequate scale.

Methods of estimating vegetation biomass are invaluable, as they allow the forecast of potential bioenergy production, the assessment of carbon sequestration and the sustainable planning of natural resources. Traditionally, biomass estimation procedures have been employing in situ measurements of plant characteristics, which accurately determine the current and predict potential biomass production. As remote sensing platforms and sensors evolve, earth observation is developing in a reliable source of information that can be used towards the same purpose.

Each European member-state, and particularly those in Eastern Europe and the Balkan peninsula, employ a variety of individual or combination of biomass estimation methods. This study focuses on the differences in the present status of terrestrial methods and earth observation techniques for biomass estimation in Greece and Europe. Information regarding the methods of biomass estimation was acquired through personal interviews with the directors of regional Greek Forest Service departments and supplemented by a thorough review of scientific and ‘gray’ literature. A comparison was also made with the state-of-the-art terrestrial and earth observation methods, applied in other European countries, for the same purpose. Recommendations on harmonizing remote sensing techniques to terrestrial methods, in order to achieve low cost and increased accuracy of biomass estimation, are finally proposed in this article.

ASTER-satellite data provide useful information for a soil erosion risk model application. An orthorectified FCC and a DEM are the results of a digital photogrammetric restitution. An elevation model can be used to calculate slope angles and the drainage area of each location. So the sensitivity for erosion due to the topographic situation is estimated. In the Mediterranean, rainfall is often of an orographic origin. A linear regression equation taken from literature with the height above sea level as independent variable, and the mean annual rainfall as dependent variable has been adapted for the Chios island. Then the erosivity of the rainfall is estimated. The orthorectified bands are used to make a LULC-classification by means of the maximum likelihood classifier. Before classifying, the image is corrected for differential illumination effects to improve the classification. The different LULC classes have a different sensitivity towards erosion. One non-satellite based information source has been added to the dataset, namely a generalised lithologic map. This map allows tracking of the parent material, which is an important factor determining the soil formation. Different lithologic formations have different erodibility characteristics. When the rainfall erosivity and the sensitivity for erosion due to the topographic situation and the lithology are combined, the potential soil erosion risk is estimated. The potential soil erosion risk is the erosion risk in a virtual world without vegetation. When the sensitivity for erosion of the land cover is taken in account, the actual soil erosion risk is estimated; this is the current soil erosion risk like. At the island of Chios a high potential soil erosion risk is prevalent for most of the land. However the actual soil erosion risk is relatively low for most parts of the island. Vegetation tempers soil erosion. Nevertheless the Mount Epos area is badly degraded and has high actual soil erosion risks.

There are several data fusion methods widely used to produce a high resolution multi-spectral image from a pair of images – a panchromatic high resolution and a multi-spectral lower resolution image. Although the fused images can be visually satisfactory, it is not clear whether they provide additional information for quantitative measurements made from satellite images. A methodology to evaluate data fusion algorithms is proposed, based on the production of synthetic images that reproduce real satellite images. An experiment was conducted testing the performance of six data fusion methods in the production of NDVI values for land parcels from SPOT HRG and Landsat TM data. The fusion methods evaluated were: Brovey, IHS Hex-cone, IHS Cylinder, PCA, Wavelet IHS and Wavelet Single Band. The best data fusion method overall was found to be Wavelet IHS, although better results were obtained by using directly the lower resolution multi-spectral data instead. The software tools developed and a number of test images datasets are freely available at the SITEF website (www.fc.up.pt/sitef).

Meter to sub-meter resolution satellite images have generated new interests in extracting man-made structures in the urban area. However, classification accuracies for such purposes are far from satisfactory. Spectral characteristics of urban land cover classes are so similar that they cannot be separated using only spectral information. As a result, there is an increased interest in incorporating geometrical information. In current literature, this is achieved by using an object-based approach. This requires a segmentation process. However, the complex objects in urban remote sensing images make this process very difficult. In this paper, we propose a method to measure the minimum and maximum dimension of an object, without however performing a segmentation. This method is based on morphological profiles (MP). Previous work on MP's have shown the potential for improving classification results. However, an MP contains many values for each pixel, which can lead to problems of dimensionality. Feature extraction algorithms could reduce the dimensionality, but the resulting features are no longer interpretable. In this paper we use MP's to derive a measure of minimum and maximum object dimension. These two measures allow to differentiate between long (roads) and more compact objects (buildings). We show that these new features improve the classification substantially.

Modern remote sensing technologies for Land Use/Land Cover applications rely on the integration of a big variety of data from both airborne and ground-based instruments. The final product highly depends on the proper and successful exploitation of as much data as possible. This is the reason why a unified data integration and management system should be at the disposal of researchers from different science fields. One possible approach is to develop an information system (IS) based on an open source technology providing an easy data access. Also a standard way of seamless addition of new data should be considered. The approach adopted in this research study is based on a distributed database management system with simple web interface to the data and models. A single cluster contains the following components: a subsystem for data archiving and exchange; a subsystem for specific data preprocessing and calibration; a subsystem for metadata management and integration; a subsystem for the whole catalogue management; a subsystem in support of external users.

The above-described IS was developed in the framework of a joint Russian-Bulgarian project for distributed system infrastructure for aerospace and in-situ data. The system consists of a set of archived data and is supported by hardware/software facilities allowing the exchange of catalogue and ancillary information in an on-line mode. The infrastructure allows to carry out general and detailed data search and to prepare orders for data delivery. The focus at this stage of the work was put on the refinement of the system specification, details of interchange protocols and archive formats, the development of software prototypes ensuring metadata exchange between the system's clusters and access to the information resources of the system. Along with a description of the IS the paper presents a detailed operational scheme of a single standard cluster.

Mining plants are one of the factors having major negative impact on the area where they are situated. In the case of Mirkovo floatation plant, located in the outskirts of Stara Planina Mountain in the middle of Bulgaria, the pollution comes from two major sources – dust from milling shop and waste water from floatation shop. The investigations are carried out deal with determination of the impact on the soils and vegetation in the neighborhood areas using reflectance information from multispectral data and supporting hyperspectral in-situ measurements. During the research preliminary information about mineral content of the ore material coming from the mine and soil type is also considered.

Numerous studies have analyzed the variance of spectral reflectance of rocks, soils and vegetation in response to their cover using remote sensing. The goal of the study is to show land cover changes detected through vegetation indices as NDVI, RVI, SAVI and the soil line concept in remote sensing. On the next step change detection methods are used to support local authorities in preparation of short-term reclamation plans and as well to recommend farmers in planting suitable vegetation spices in assisting the rehabilitation of the top soils. In this research the data from Landsat TM/ETM+ combined with in-situ measured data are used. The obtained results show that the analyzed data and the implemented approach are useful in environmental monitoring and economically attractive for the company responsible for the ecological state of the region.

Remote sensing is an established technique in environmental studies. First of all, this concerns soil-vegetation ecosystems where the availability of means for vegetation monitoring, stress detection and state assessment is of great importance. A significant amount of research has been performed to develop efficient methods for monitoring of vegetation dynamics. A prevailing part of the works is devoted to the use of multispectral data transformations (vegetation indices) such as spectral bands ratios and linear combinations in order to estimate vegetation parameters. The dependence of vegetation spectral features in the visible and near infrared bands on plant biomass, chlorophyll content, canopy cover, etc. lies at the root of this approach.

In this paper we report some results of the colorimetrical analysis of vegetation spectral data. The work was conducted in order to reveal plant senescence effects due to plant growth or stress factors and the impact of the soil background on vegetation reflectance. One of the goals of the study was to evaluate the potential of various colorimetric features for vegetation assessment. Another objective was to compare this approach to the results of the implementation of vegetation indices for plant bioparameters retrieval from multispectral data. The integration of both methods was examined as well showing good predictive capabilities.

Remote Sensing is an important technique for mapping land use and land cover in the vast acreages. In this sense, the fusion of optical and radar remote sensing data offers the opportunity to combine complementary sensors with different features. In this study, beside the capability of the combined multi source imagery, the contribution of SAR images to the optical images for identifying land use/cover types was investigated. For this purpose, using the synergy between SAR and Optical data, the improvement in the classification accuracy was analyzed. The study area, covering urban and agricultural areas, lies in the Menemen Plain to the west of Gediz Basin in the Aegean Region of Turkey. The satellite data used in this study are multispectral SPOT, ENVISAT-ASAR, and ALOS-PALSAR images. The 3-2-1 band combination of a SPOT-2 image was fused with C band ASAR imagery and with the new mission L band PALSAR imagery. The land use/cover types were defined from both of the fused images. In this case, since the SAR images have different bands (C band and L band) the penetration property is the key factor to see the affects on extracting information from fused images. Before the fusion application, the speckle reducing filter techniques were used for the preprocessing of SAR images. For the filtering of SAR images, kernel windows with different size were tried. Then the SPOT image was registered to SAR images. For the registration of SAR images, image to image registration method was used with a root mean square error of less than 1 pixel. A pixel based fusion method was carried out. Both of the fused images (SPOT-ASAR and SPOT-PALSAR) were classified to determine the land use/cover map. The results were compared with a classified SPOT image, which is commonly used to define land cover types. While processing the classification, the training areas were selected covering a large portion of the individual fields and were away from the field boundaries to reduce the mixed pixels. The ground truth data were used for the accuracy assessment process.

Didim peninsula is the fattest growing urban area in the Aydin province, Turkey. Since 1990, the Town of Didim has changed significantly after discovered by domestic and international tourist. In spite of the recent rapid LULC change, Didim has not been spoiled compared to other big touristic towns of Turkey. Didim has been announced as “Tourism hot spot” in 2000, thus its planning is overseen by the Ministry of Culture and Tourism. Monitoring of the Didim's development is necessary to guide the Ministry in promoting sustainable planning guidelines. The present work aims to determine the characteristics and the amount of urban growth in Didim by using remote sensing and GIS technology. Already rectified Aster (dated 04/27/2005) and Spot 2X (03/02/1994) images were used as well as the population information, aerial photographs, city plans and thematic maps from previous studies. Object oriented classification technique is employed. Some complementary information is extracted from aerials and maps by on-screen digitization. Total of 16 LULC categories are defined. After, putting all information in the GIS database, the pattern of landscape change in Didim is described by using selected landscape metrics. The case study of the Town of Didim offers a good example of the impact of national policies on land use dynamics at local landscape scale. The findings indicate three simultaneous key trends: loss of coniferous forests, the thinning of the maqui vegetation cover, and intensification of urban areas on valuable class II type of soils. Identified trends have significant consequences in terms of the response that ecosystems have given to these anthropogenic landscape alterations. A strategy to promote sustainable land use management should be generated timely manner.

Due to the complex spatial structure of the earth surface, obtaining a detailed and accurate land use/land cover (LULC) classification results with satellite data have still been problematic. The overall goal of this research is to compare the pixel based and object oriented image classification approaches in terms of the overall accuracies and robustness of the final classification product. An Aster image, dated 4/27/2005, with 3 bands from spectral regions of VNIR is used to perform the LULC classification for 16 different LULC classes. Ground truth data are collected from field surveys, available maps and Quickbird images.In pixel-based image analysis, supervised classification is performed by using maximum-likelihood classifier in Erdas 8.7. Object-oriented image analysis is conducted by utilizing Definiens Professional 5.0: The segmentation algorithm does not solely rely on the single pixel value, but also on shape, texture, and pixel spatial continuity. During the implementation, several different sets of parameters were tested for image segmentation, 20 was selected as a scale parameter and nearest neighbor was used as the classifier. At the end, the performance of pixel based and object-oriented classifications are compared based on the accuracy assessment results.