Ebook: Imagin[e,g] Europe

29th EARSeL Symposium in Chania, Greece

Historical note

The idea of hosting an EARSeL symposium at the premises of the Mediterranean Agronomic Institute of Chania (MAICh) in Greece came up for the first time in 2005, during the 25th EARSeL symposium. Since then the idea has been pursued by Ioannis Manakos (head of the Environmental Management Department), who is strongly motivated and focused on Remote Sensing Applications in the Environment, and warmly welcomed by the EARSeL Bureau (Rudi Goossens, Rainer Reuter, Andre Marçal, and Lena Halounová). The organization of the symposium was initiated one and a half years in advance. MAICh personnel and MSc students were enthusiastic, and the authorities and people of the city of Chania embraced it. Attention was given to maintaining high scientific standards as well as making attendees feel at home, while at the same time promoting remote sensing to a wider audience of locals and tourists.

The title & the goal

Imagine Europe, because we would like to show through the common activities of our association how we imagine and envisage the future of our contribution to Europe, to the next generation of a lifelong learning society, and of remote sensing related scientists. Imaging Europe, because we are imaging Europe through our work; interpreting its nature, its man-made interventions and artifacts in various ways, and under the prism of various scientific fields and objectives. In this context, the title demonstrates the goal of the symposium to register the contemporary status of our Association and its recent achievements, and to pinpoint near and expected longer term future trends and developments.

The organization

From the first, the MAICh team wanted to organise a symposium which would be a success in all respects. Priority was given to the quality of the papers, and for this reason, the incoming contributions were sent to the leaders of the special interest groups for review, and also to prioritise their importance. Another concern was to keep the number of sessions as high as possible, while at the same time avoiding spreading the audience over many rooms. In addition, for the first time for some years, posters were thematically allocated to the respective oral sessions, and a short amount of time was assigned for their presentation to the audience, introducing in the best way the topics and tutors in the overall discussion. Time for poster presentation in a separate hall was, of course, built into the schedule.

The keynote speakers were selected with the strategic orientation of EARSeL in mind, having not only a high representation and involvement in latest EO developments in Europe, but also demonstrating a wider perspective and the will to learn about global developments, and strengthening existing or initiate new cooperations with the rest of the remote sensing world. Within this framework, Prof. Dr. Richard Bamler, director of IMF at the German Aerospace Center – Remote Sensing Technology Institute, presented “TerraSAR-X, TanDEM-X, EnMAP: Flagships of Germany's Earth Observation Program”, and Prof. Guo Huadong, Director General at the Center for Earth Observation and Digital Earth – Chinese Academy of Sciences, illustrated “Remote Sensing for Wenchuan Earthquake Disaster Monitoring in China”.

Another aspect of EARSeL role in remote sensing society was highlighted; the role of the association in joining or leading research consortia within EU funding frameworks, as indicated by its involvement in the GEOLAND II and SEOS projects. EARSeL already acts as a contact point for scientists who are interested in searching and building up working groups for the optimal promotion of their interests, while being confronted with the challenge of addressing calls for proposals. In this context Dr. Carine Petit, senior science officer from the COST office gave a talk about COST action, participation and perspectives.

Furthermore, a tutorial was carefully selected for presentation by a commercial company, to reflect the high value that EARSeL places on cooperation with software developers in remote sensing and geoinformation in general. Mr. Lawrie Jordan, ESRI Director Imagery Enterprise Solutions, presented “New trends for GIS and Remote Sensing software packages”. In addition, ESA, UNESCO, European companies and their Greek representatives, and Greek companies sponsored the Symposium and had a presence in the Company exhibition room.

Having strategically demonstrated EARSeL activities and vision, MAICh wanted to present the latest developments, which are unique by Greek standards. An in situ demonstration of MAICh's platform for field spectroradiometric measurements, which provides the capacity to be mobile, fast, and reach up to 9 metres high, took place at the conference center.

Last but not least, the organizers wanted to bring remote sensing in general and the association in particular closer to the local society and to the numerous tourists visiting Chania at the time. To this end, SPOT gallery donated its products and the Center for Architecture in the Mediterranean (CAM) hosted the exhibition “The Earth from Space: A Work of Art” at the center of the harbour area of the old city of Chania. Over 1500 people a day visited the exhibition to the sounds of relaxing music.

Local press and TV were present at all events, keeping the public informed daily with the latest news about the Symposium, accompanying workshops and events. At the same time, social events facilitated a better insight for the attendees into local traditions and life.

The events in brief

Starting on Monday, 15th of June, the EARSeL council met in the morning to address various issues concerning the association; the most important issue being the election of the new bureau. At noon, the symposium was initiated by Prof. Eberhard Parlow, former chairman of EARSeL, with a flash-back slide show with music and speech - about the foundation and development of the association, the people and the events, through the decades. For the older participants it was a chance to remember and for the younger ones, an opportunity to learn. The opening session continued with the keynote speakers taking the lead, giving their contributions, and discussing with the attendees. Sessions on forestry, land use and land cover, and urban remote sensing followed, with excellent presentations and vivid discussions. In the afternoon buses brought everyone to the icebreaker party and welcome reception at the CAM exhibition.

The sessions continued throughout the days that followed, giving chairmen and audience alike the chance to follow interesting presentations and get involved in discussions. Chairmen evaluation sheets reflect the excellent work of our colleagues, their thorough presentations, and fruitful discussions.

On Tuesday and Wednesday, the 2nd workshop on education and training “Earth Observation: From Research to Teaching in Schools and Universities” took place in parallel with the final SEOS project meeting, within which this special interest group (SIG) has been active for the last two years, providing 16 e-learning modules for high schools throughout Europe. Smaller discussion groups were formed, on the initiative of the SIG leader(s), like the newly established SIG on Thermal Remote Sensing, which discussed scientific issues, not only during but also in between sessions, in rooms provided by MAICh.

On Wednesday, the General Assembly took place and all members had the chance to learn about the developments within the association during the last year, and take part in its procedures. The same evening, a traditional dinner with local dancers and music put everybody into an excellent mood and communicative spirit.

On Thursday, the Tutorial and the presentation on the COST action took place before the closing session. “Imagin(e,g) Europe” became history. All involved personnel of MAICh, all students, our Greek “canaries” (the local assistants that are present in every symposium, wearing yellow t-shirts which makes them easy to spot), the local organization committee and, of course, the newly elected EARSeL bureau were present and acknowledged with applause for their efforts. The newly elected chairman of EARSeL, Dr. Rainer Reuter, concluded with a speech on the future expectations for the association.

As the symposium closed, the 4th workshop on remote sensing of the coastal zone “Coasts and Climate Conflicts” was opened, which again followed a success story, reaching its peak on Saturday the 20th of June, when, during a field excursion at sea a dedicated diving team demonstrated a series of surface and sea bottom experiments. At the end of the day, everybody was satisfied and happy about this experience.

A last statement

EARSeL and MAICh were honored to welcome you to Greece and greatly appreciated your presence and contributions. We would like to give a big “thank you” to all SIG leaders and council members for their engagement, and another big “thank you” to the scientific committee members for their contributions.

EARSeL would like to express its thank to MAICh for the excellent organization, and to the MSc students of MAICh (our Greek “canaries”) for their warm welcome and support during the symposium.

Finally, EARSeL would like to express gratitude to the authors that contributed to this proceedings book.

Enjoy reading and remember that we are looking forward to meeting you all during the next EARSeL event

With our kind regards, Ioannis Manakos & Chariton Kalaitzidis

Local Organizing Committee, Geoinformation in Environmental Management Dept., MAICh, (manakos@maich.gr, chariton@maich.gr)

There is an increased utilization of image fusion techniques for the combination of multispectral bands with higher resolution panchromatic bands of to produce so-called pan-sharpened images with both high spatial and spectral resolution. The objective of this study is to evaluate performance and quality of the following pan-sharpening algorithms: i) Discrete Wavelet Transformation (DWT), ii) À trous Wavelet Transforms fusion (ATWT), iii) Gram-Schmidt Spectral Sharpening (GS) and iv) Principal Component Spectral Sharpening (PC). We intended to evaluate the spectral and spatial quality of the pan-sharpened image by using Universal Image Quality Index (UIQI), Correlation Coefficient (CC), Variance Texture Filter and Change Class Difference. The variance texture images represent the high frequency domain data .The difference of the two variance images was used to estimate the spatial quality of the sharpened images. The variance images subtraction shows that ATWT pan-sharpening obtains the best results followed with PC and GS, whereas DWT achieves the poorest result. Applying CC as quality measure exhibits the same results; again DWT obtained the poorest correlation coefficient. The UIQI results, calculated for different land-cover classes, indicate that ATWT pan-sharpening achieves a good spectral and spatial quality compared to DWT. The percentage of changed classes indicates that both wavelet-based algorithms (ATWT and DWT) provide better quality than PC and GS pan-sharpening. Therefore the wavelet-based techniques seem to better preserve the spectral information of the original multispectral bands, whereas PC and GS come along with a larger modification of the spectral information.

The maximum land surface temperature related to hot and dry climatic condition, Clear sky causes that the highest radiation reaches to the land surface and land surface warms up fast during day time. Lut Desert seems ideal condition for studying and determining land surface temperature and model development. Therefore in this study, 12 NOAA-AVHRR and MODIS data and air temperature data were used to evaluate the model of land surface temperature of Yardang region in Lut Desert. To study the LST model, 8 ground measurements as ground truth were used. From the results obtained from this research. We concluded that in spite of some difficulties in estimating land surface temperatures, we can extract valuable information from surface features. We may also conclude that accurate emissivities are necessary to study surface features and soils and to monitor surface changes.

The anisotropy of backscattering heterodyne the spectral information, which is in general deemed as main information source in remote sensing. However, the anisotropy approach enables to gather information about differences in phenotypes or stand structures, if it is possible to analyze objects with help of satellite systems with multi-angle observation possibilities. Proba/CHRIS is such a new generation satellite system. This paper deals with the synergistic usage of spectral and angular signatures for image classification in order to calculate a possible information surplus. For this, the corresponding 36° off-view angle data sets were divided from each other so that the anisotropy ratios of spectral classified objects could be extracted. The results of the analysis and visual verification substantiate the high information content of angular signature images and the sub classification of vegetation objects. The temporal analysis shows that these sub classes are stable over the vegetation period. The information surplus is visible in the 680nm wavelength band of the anisotropy quotient images.

Strategic discussions among EEA member countries and the main EU institutions responsible for environmental policy, reporting and assessment have underlined an increasing need for quantitative information on the state of the environment based on timely, quality-assured data, concerning in particular land cover and land use. Based on these requirements EEA is collaborating since 2006 with the European Commission (EC) and the European Space Agency (ESA) on the implementation of a fast track service on land monitoring in line with the communication: “Global Monitoring for Environment and Security (GMES): From Concept to Reality” [1]. CORINE Land Cover 2006 is the third European Land Cover inventory (1990, 2000 and 2006). The number of participating countries is increasing, at present being 39. The project is co-financed by the EEA and the member countries, and covers 5.8 Mkm². Results will be freely available on the Internet. A Technical Team working under the ETC-LUSI (European Topic Centre Land Use and Spatial Information) is responsible for technical follow-up of the project, i.e. training of national teams and verification of results. National teams use multi-temporal SPOT-4/5 and IRS-P6 imagery to derive the minimum 5 ha land cover changes that occurred between 2000 and 2006. Particular emphasis is placed on mapping the real change processes. National teams usually have access to recent topographic maps and high-resolution digital orthophotos as in-situ data. CLC2006 is produced by combining CLC2000 and CLC-Changes in a GIS.

The problem of erosion is very prominent in Mediterranean karst area of Croatia, and one of the reason is the degraded forest ecosystems. The important relationship of soil erosion with the state of vegetation, its degradation stadiums and soil characteristics has been stated. It is widely known that the regression development of vegetation is followed by quick soil erosion, and its progression development causes only normal geologic erosion which is overwhelmed by soil formation. To state the impact of vegetation influence on the intensity of soil erosion by water in preserved and burned stands of Aleppo pine of the karst area of Croatia a forest experiment was made. On two experimental plots of 100 m² (20 x 5 m) during three years, from 2005–2007 the quantity and intensity of rainfall was observed, the surface flow off of rainfall and soil erosion. The results of research of given parameters are shown in this paper. The first experimental plot was set on the burnt area in forest ecosystem of Aleppo pine, GPS coordinates: N 43°33′, E 16°30′. The plot is set on eroded rendsina on marl, 20° inclination, sea level 212 m. The second experimental plot was set in the preserved stand of Aleppo pine of complete stand, GPS coordinates N 43°31′, E 16°32′, on inclination 26° and sea level 227 m. The plot is set on brown soil on marl, which is covered by thick layer of needles. The results show that in the time observed on burnt area 215 rainy days were recorded, out of which the surface flow off and soil erosion were caused in 71 cases. Surface runoff and soil erosion were caused by rainfall from 7.1 mm/m² to 78.6 mm/m². The yearly value of erosion alluvium amounted to 0.1 t/ha, surface runoff 11.30 mm/m², and the coefficient of runoff was from 0.0017 to 0.0824. In the preserved stand of Aleppo pine out of 215 rainy days, 59 were erodible. Surface runoff and soil erosion were caused by rainfall from 8.5 mm to 78.6 mm. Yearly value of erosion alluvium amounted to 0.015 t/ha, surface runoff 5.59mm/m², the coefficient of surface runoff was between 0.0003 to 0.0162.

This study shows the correlation between large fires emissions and Carbon Monoxide estimated by the atmospheric sensor MOPITT (Measurements of Pollution in the Troposphere) onboard Terra satellite. The zone analyzed is the Iberian Peninsula, Spain and Portugal, during the summer season. The CO is a very important trace gas produced by forest fire emissions and its role in the cycle of atmospheric carbon is very relevant. This study is focused on two main topics: the assessment of dispersion of CO emissions caused by large fires and the study of fires series and its CO emissions.

Comparing to traditional pixel based methods of land cover identification, the object based approach allows to increase the set of discriminant features, including elements related to texture, size, shape, widely understood spatial and geographical context. This extent has important influence on digital classification efficiency and final accuracy. The thematic and positional accuracy of extracted and identified objects strongly depends on segmentation stage, which is very crucial one for further steps.

The paper presents results from different variants of object based land cover classification with the main aim to test the influence of segmentation methods and their parameters on the accuracy of land cover form identification based on VHR satellite image. The influence of selected filtering effects applied on certain stage of image analysis procedure was also tested. The object oriented approach was realized based on Definiens Professional set of tools. The analyses were done for spatially and spectrally complex terrain. Due to the fact that final comparisons of thematic accuracy concern the classified objects the right procedure of accuracy evaluation was developed and applied in the study.

The results show certain positives and limitations of applied approaches and defined variants, and confirm the importance of proper selection of segmentation procedure and adequate parameters.

This study presents the production of Digital Elevation Models (DEM) and land cover (LC) databases for the islands of Cyprus, capable of being used in local studies. The 1:50.000 topographic maps present a nominal horizontal accuracy of 20 m and a nominal vertical accuracy of 10 m with 90% confidence. The Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER) offer along-track stereoscopic viewing capability. Its viewing geometry is suitable for DEM generation even without the use of ground control points. Recent studies have proved that in this case the vertical accuracy of DEM can be better than 20 m. In this paper we therefore examine the production of DEM and LC maps using ASTER multispectral stereo-imagery for the island of Cyprus. These products are capable of updating the 1:50.000 topographic maps of the island, as well as capable of supporting water resources management. A DEM from digitized contours from the 1:50.000 topographic maps was created and compared with ASTER derived DEMs. Several survey monuments were used to estimate the accuracy of these DEMs. It was founded that the horizontal and vertical accuracy of the ASTER derived DEM is similar to the respective accuracies of the DEM derived from digitized contours, therefore optical comparison of these two DEMs and statistical analysis can immediately prove if there is any need for update to the topographic maps. The CORINE 2000 LC map was used to evaluate the ASTER derived LC for Cyprus. The classification accuracy was better than 75%, therefore the ASTER derived LC map can be used to detect and update recent LC changes.

Grapevine phenology observations are essential for ecological adaptability of grape varieties, crop management and crop modelling. Phenological events have traditionally been ground based, with observations mainly providing information concerning grape varieties over a limited spatial area and few inseason observations. Time-series of satellite imagery can rapidly provide a synoptic and objective view of grape vegetation dynamics that may be used for vineyard management. Ten-day VEGETATION image composites from 1999 to 2007 were used to examine temporal profile in the Normalized Difference Vegetation Index (NDVI) and their relationship with ground based observation of grapevine phenology. In Portugal is Douro wine region, 2 suitable tests sites with over 70% or more of their area occupied by grapevines were selected. A number of NDVI metrics were obtained for each year through logistic model adjusted to NDVI time series after noise reduction using a Savitzky-Golay filter. The comparison of ground-based vineyard phenology and satellite-derived flowering, show an average spread deviation of 3 days. The satellite derived full canopy date was significantly correlated to the veraison date (r=0.87; n=7; p<0.02). The data set provided by the VEGETATION sensor proved to be a valuable tool for vineyard monitoring, mainly for inter-annual comparisons on regional scale.

Earth Observation data give high potential to assess the biomass of vegetation. Initially, methods of deriving information on vegetation growth conditions and biomass were based on optical data, collected by environmental satellites with sensors of different resolutions (low and high-resolution satellite images). However due to frequent clouds cover, the application of multi-temporal SAR data proved to be very useful for classification of vegetation and application for biomass assessment. The presented paper gives an overview of the state-of-the art in the field of radar applications for vegetation studies with the special emphasis put to evaluation of biomass. Applications of different types of SAR sensors are presented for two types of vegetation relevant for biomass production: agricultural crops and forests. As far as forests are concerned, multiple approaches are presented, which apply various radar wavelengths (C-band, L-band, P-band) and different wave polarizations (VV, HH, HV). Results from regression analyses with forest variables: biomass, height, dbh (diameter-breast-height) and total stem number were demonstrated with conclusions concerning optimal choice of radar band and polarization for assessment of these variables with high accuracy. Usefulness of various radar techniques was tested, like PPD (Polarization Phased Difference), or semi-empirical algorithms based on a two layer radar backscatter model. Also applicability of special indices, useful for better assessment of forest biomass, like BCI (Biomass Consolidation Index), which is the combination of biomass density (t/ha) and stand consolidation (amount of trees per ha), was presented. Analogous analysis of recent achievements was done for SAR applications related to agricultural crops. Conclusions concerning optimal SAR wavelengths and polarizations for crop type mapping were presented, including own Author's experience in crop classification based on various SAR sensors (X and L bands). Results concerning interactions of a backscatter signal with soil and vegetation were demonstrated, with their implications on accuracy of biomass assessment. Methods incorporating multi-frequency polarimetric SAR into the crop canopy models aimed at obtaining physical parameters related to biomass, as Leaf Area Index and crop height, were discussed. Finally, the summary table, presenting possibilities of applications and ordering data from different sensors (past and present), wavelengths, polarizations, spatial resolutions for assessment of various vegetation parameters, with the special emphasis put to biomass, was created as a result of the study.

A method is presented for the automatic identification of lost or undiscovered archaeological sites in Egypt by using shape detection techniques on satellite imagery superposed in a GIS environment. For an area of interest, the EO data available from various satellites is pre-processed and from historical plans a shape file of the archaeological structure of interest is produced. A shape detection algorithm employing a shape matched operator is applied to the EO image to produce a detection image identifying the most probable location of the archaeological structure of interest. The shape-matched operator employed is the derivative of double exponential (DODE) operator. The final product is a GIS data set assembled as a list of required features and layers, all converted and processed in the same Geographical Reference System.

The purpose of the research is to understand the potential of polarimetric and SAR response of different archaeological structures on the surface and subsurface over different landscapes and to define and propose a methodology for the integration of information extracted from polarimetric radar as a new, additional tool for archaeological applications. Test sites selected for this work are Vulci, Arpi (Italy), Gebel Barkal (Sudan) and Calakmul (Mexico). Interesting preliminary results of relevance for this humanistic science are shown, based on the joint use of polarimetric SAR and optical data.

The Hyperion sensor is unique because it is the only high spectral resolution hyperspectral sensor on a satellite platform. The hyperspectral capability of the sensor could potentially allow for classifications of increased accuracy, in comparison to those produced from multispectral data. This study evaluates the capability of Hyperion data for discriminating land-cover classes in the Anopoli region (southwest Crete, Greece), through different classification techniques and spectral unmixing procedure. Preprocessing of Hyperion data is essential before any analysis takes place, and it includes interpolation of the wavelengths to a common set, noise reduction by using the minimum noise fraction (MNF), and other commonly applied corrections. Land-cover classifications were performed on the Hyperion satellite data through the Spectral Angle Mapper (SAM) pixel-based technique, as well as the object-based technique. In order to take advantage of the hyperspectral data of Hyperion, and overcome the problem of low spatial resolution, non-linear spectral unmixing approaches were employed, by using artificial neural network (ANN). The spectral end-members used in those approaches were constructed from QuickBird data. All the results were evaluated using the ground truth data derived from high spatial resolution imagery (QuickBird) and field data. All classification results mainly appeared to suffer from the relatively low spatial resolution of the Hyperion sensor and the spectral similarity among many land cover classes. The results show that the object-based classification outperformed the pixel-based classification and achieved the highest overall accuracy. The pixel-based classification and ANN results were highly dependent on the extent that the end-members were representative of the class. However, the pixel-based technique was very successful in differentiating land cover classes with dense vegetation cover.

The Etna's plume has been measured by in-situ gas analyzers at the main crater, atmospheric lidar deployed on the volcano East flank and satellite radiometers. Thanks to the integration of those different techniques, a 3D reconstruction of the plume has been achieved. This approach could lead to a deeper understanding of the chemicophysical phenomena taking place inside the plume.

The objective of this research is to investigate the extent of land-cover change in and around Stockholm from 1986 to 2006 and the nature of the resulting landscape fragmentation with a particular focus on the possible environmental impact. Four scenes of SPOT imagery over the Stockholm area were acquired for this study: two on 13 June 1986, one on 5 August 2006 and one on 4 June 2008. Various image processing and classification algorithms were tested and compared. The best classification results were obtained using an object-based and rule-based approach with texture measures as well as spectral data as inputs. The image pairs from the two decades were classified into seven land cover categories for Stockholm Municipality, i.e., low-density built-up, high-density built-up, industrial areas, open land, forest, mixed forest and open land, and water. The overall accuracies were 93% (kappa: 0.91) for 1986 and 97% (kappa: 0.96) for 2006. Landscape fragmentation and change was evaluated using spatial metrics. The spatial metric results reveal that urban areas increased at the expense of non-built up areas by around 2% both on the municipal and regional levels. The 2006/2008 classification gives evidence of being a more fragmented landscape than that of 1986. While urban areas have become denser within Stockholm municipality, which is in line with the region's development policy, more natural land cover types have at the same time been eroded; a development not in line with the regional goal of maintaining the area's green spaces. The classification technique used on the municipality will be expanded to the region as a whole, and regional trends and consequent recommendations will be the focus of future research.

The main goal of this work is to prove the potentiality of a methodology which combines Growing Cell Structures (GCS), satellite imagery and in situ data to estimate spatial distribution of biophysical parameters involved in the determination of Trophic Level Index (TLI). In particular, in this work spatial chlorophyll-a distribution maps have been estimated. These maps have been also estimated for fused images, improving the results obtained for the original multispectral satellite images.

With an increasing number of satellite systems and applications one can see a growing demand for data at universities and research institutions. Department of Applied Geoinformatics and Cartography have installed a receiving station for continuously acquiring data from the following selected satellite systems – Envisat (Meris), MSG second generation, NOAA and Metop. This system represents a very intensive daily data flow. Received data are filtered and stored within disk arrays and magnetic tapes. These steps need to be taken prior to data storage in file systems. SDI was created with an emphasis on a simple common gateway to the spatial data at the Faculty of Science.

It is important to have a general access to search this data with a newly received data. The implemented features have to manage following tasks-search based on location, search based on resolution, search based on descriptive metadata, etc.

In the paper we shall describe reprocessing raster datasets, in a sense of getting information for SDI. In this context the methods are the same for all satellite sources – read data, select appropriate data to store (automatic filter or application specific selection), creation footprints which are inserted in a spatial database and creating metadata in standard way.

The chosen study area Alaçatı is one of the most significant tourist regions in Turkey. Due to its natural and geographical characteristics it faces different threats, such as coastline changes by moving solid matter or formation of filled areas caused by anthropogenic effects. The detection of the coastline and land cover changes in Alaçatı has been investigated by using multitemporal satellite images, such as CORONA of 1963, LANDSAT of 1987 and 2000, and ASTER of 2007. Object oriented remote sensing software was used. This software is preferred due to its capability of generating fuzzy segmentation and classification by using both texture and reflection attributes of images and also for different types of data. Thus, the purpose of this study was to establish a basis for planning of preventing Alaçatı region.

Water scarcity has always been a severe problem for agricultural purposes in Cyprus. Meteorological data refer to the problem since their existence. The authorities, responsible for this environmental, social and economic constraint, have managed a great development and deployment of a dam's network in order to save water from losses and use it during low rainfall years. Lately, Cyprus is facing a period with very low rainfall which has caused curtailments to irrigation water schedule, which in turn has resulted to very low or no yield for the seasonal and multiannual crops. The monitoring of agricultural areas in Cyprus provides important data for efficient water supply plans and for avoiding unnecessary water lost due to inefficient irrigation. Thus, the monitoring through Satellite Remote Sensing is an essential and useful tool to provide irrigation data for water demand management. There is a need for an effective method of establishing crop water use in large irrigation projects so that crop demand can be accurately met by supply in order to eliminate problems such as lack of up to date information on the cropped area, evaporative demand in the agricultural fields and water supply. The project aims to the sustainable use of irrigation water from both the competent authorities and the producers. The wise and sustainable use of irrigation water will result to higher efficiency and will increase the water reserve funds for the future generations. Sustainable use of irrigation water will preserve the agricultural activity alive. The aim of this paper is firstly to assess and apply some of the existing methods of determining the evapotranspiration and secondly to present our novel methodology. Indeed the novel approach consists an integration of the following: remote sensing data, meteorological data, in-situ spectroradiometric, sunphotometer measurements and micro sensor technology.

The performance of image classifiers in large-scale land cover mapping and the relevance of input variables for classification accuracy are investigated in order to assess and to quantify the importance of these components in image classification. Specifically tested are maximum likelihood classification, artificial neural networks and discriminant analysis for landscape-scale land cover assessments in the alpine region. DEM-derived ancillary data and radiometric modifications of spectral data (Landsat7 ETM+) are incorporated step-wise into the classifications to document the relevance of these input data. Including ancillary data did show large potential for increasing classification accuracy, comparable to the selection of the classifier. Multi-temporal spectral information further increased classification accuracy, despite temporary snow cover in the images.

Remote sensing offers opportunities to efficiently acquire data of intertidal flats and characterize intertidal sediments. Each type of imagery with a different spatial resolution offers a distinctive perception. The objective of this research is to investigate the impact of these properties on sediment characterization. A hyperspectral airborne image of 4 m pixel size accompanied by field data is used. The study consists of a geostatistical analysis of spatial correlations for the hyperspectral image and imagery depicting specific sediment properties (moisture content and chlorophyll a content). The results show that there is information lost when the pixel size of the image increases to 24 m pixel size. To characterize relative moisture content, a maximum pixel size of 12 m can be used. While for chlorophyll a content characterization, increasing the pixel size (investigated up to 72 m) does not degrade the information significantly. The research presented in this paper is funded by the Belgian Science Policy Office in the frame of the STEREO II programme (ALGASED project).

With the new very high resolution optical satellites WorldView-1 and GeoEye-1 images with 0.5m ground sampling distance (GSD) are available. By the rule of thumb of required 0.1mm GSD in the presentation scale of a topographic data base, it should be possible to generate topographic maps up to the scale 1:5000 with such satellite imagery. The orientation of WorldView-1 images is possible with sub-pixel accuracy – totally satisfying for topographic data acquisition. More difficult as before is the required accuracy of digital elevation models for the generation of ortho images if the data acquisition shall be done by on-screen digitizing of ortho images.

WorldView-1 scenes, from the city area of Istanbul and from Zonguldak, have been used for acquisition of topographic data and compared with available reference data. The mentioned rule of thumb has been confirmed – it is possible to get the details required for topographic mapping in the scale 1:5000. Both areas are partially mountainous. Together with the incidence angle of the WorldView-1 scene of 31.5°, in the build up areas larger shadow regions cannot be avoided. On the screen the shadow areas are very dark and do not allow the identification of objects even if the brightness is optimized. By Wallis filtering with a floating window of just 19² pixels a lot of details can be seen with satisfying contrast, which could not be recognized without filtering.

The use of vegetation indices is a fast and efficient method for vegetation monitoring by the use of remote sensing data. Throughout the years, a large number of multispectral vegetation indices have been formulated, each having variable degrees of efficiency in estimating one or more vegetation parameters such as, health status, nutrient or water deficiency, crop yield, vegetation cover fraction, leaf area index, absorbed photosynthetically active radiation, net primary production and above-ground biomass. Additionally some of them also consider atmospheric effects and/ or the soil background for an enhanced retrieval. With the production of biofuels appearing as a partial alleviation of global energy problem, accurate methods of estimating potential available biomass could prove invaluable for the energy budgeting at a national or international level. The paper is looking back in the past at the vegetation indices that have been used for the estimation of biomass, either directly though empirical relationships or through the estimation of other vegetation parameters such as the Leaf Area Index (LAI) and Absorbed Photosynthetically Active Radiation (APAR). This review was performed within the framework of the FP7 funded “Classification of European Biomass potential for Bioenergy using terrestrial and earth observations” (CEUBIOM) project.

In Image fusion the objective is generally to combine the spatial structure of a high resolution panchromatic image with the spectral information of a low resolution multispectral image to produce a high resolution multispectral image. The fused image should preserve the spectral characteristics of the multispectral image during the process and only the spatial structure of the panchromatic image should be inserted into the fused image. As a substitute for the panchromatic input we used image data of the German Radar satellite TerraSAR-X in this study. In the spotlight mode, the satellite is able to record data with one meter spatial resolution. The Radar image data was combined with SPOT multispectral data in a region in northern Spain. In this study we investigated if such an image fusion method could improve the results of a multispectral classification using unfiltered Radar image data as input for classification. Usually this would lead to worse classification results, because of its inherent speckle noise. This is especially true if the multispectral and the Radar image are from different dates. Therefore, only the highpass filtered information of the TerraSAR-X image is used during the fusion process. Use was made of the Ehlers Fusion, a fusion technique that was developed for preserving maximum spectral information. It has already proven its superiority over standard pansharpening techniques such as IHS, PC, Brovey, multiplicative fusion and Wavelet fusion methods. The Ehlers fusion is based on an IHS transformation combined with filtering in the Fourier domain and was developed for fusing panchromatic and multispectral electro-optical data. The Ehlers Fusion was then modified to integrate Radar data with optical data. Different classification algorithms were applied to show that the pansharpening method could improve the results, but this depends on the chosen classification algorithm.