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Humanitarian demining is an indispensable part of any post-conflict reconstruction and rehabilitation efforts, as landmines and other unexploded ordnance (UXO) continue to pose a significant threat to civilians and infrastructure. Traditional non- technical survey demining methods are typically time-consuming, labor-intensive, and require professional familiarity with a number of different complex tools and involved procedures. The emergence of the latest artificial intelligence (AI) technologies for deep learning (DL) and data analysis techniques presents an opportunity to transform humanitarian demining by significantly improving its efficiency, speed, accuracy, and safety. One such approach is the development of a data observatory that implements data ingestion pipelines into a data lake using data transformation to improve the usability of unstructured data about a mine scene. This paper addresses the key characteristics and benefits of such a system and its potential to improve humanitarian demining.

Logical representation of knowledge enables reasoning based on formal logic, integration of heterogeneous data sources, augmentation of existing knowledge, and discovery of hidden knowledge that is hidden or unknown even to experienced professionals. Moreover, many high- performance software tools and services for logical reasoning are readily available in the academic community. Computational ontologies, or ontologies for short, are a comprehensive, formal, scalable, and adaptable methods for knowledge representation and automated reasoning. They have been successfully used in many diverse application domains, from medicine and natural sciences to engineering and applied sciences. However, the use of ontologies in the context of demining is novel and has not been exploited to the full advantage. In this context, a new core ontology called MINEONT (an acronym for "MINE-action ONTology") has been proposed. The MINEONT is written in the OWL-DL 2 formalism and allows an expressive and formal representation of concepts in mine action, high- level semantics, geospatial metadata, and information obtained through method of remote sensing, non-technical surveys, and other mine action survey types. The vocabulary of this ontology supports, among others, the following corpora: multisensory aerial and satellite imagery, derived indicators of mine presence and absence, contextual data, terrain analysis information, formalized knowledge of the humanitarian demining specialists in the form of declarations and procedures. The designed ontology has many advantages in describing data for non- technical surveys. However, it is also relevant for building a specialized recommender artificial intelligence (AI) expert system. Such an ontology- based decision support system (DSS) would integrate a large amount of collected data and facilitate interpretation and decision-making processes. In the paper, details about the Web Ontology Language (OWL) are given and its advantages for application in the aerial non- technical survey for humanitarian demining are explained. The MINEONT model is introduced and described in detail. The advantages of MINEONT compared to other existing methods in the aerial non-technical survey system are planned to be tested and demonstrated as part of scientific projects in which domestic and foreign partners, including CROMAC, will participate.

In mountainous regions such as mountainous Croatia, natural and semi-natural landscapes are most common and are changing due to climate change and more intense economic activities. Due to these changes, there is a need of inventarisation and valorisation of mountainous landscapes in order to manage and preserve them. In Croatia, there is no inventory that would provide us with a zero status of mountain landscapes. On the other hand, the mountainous environment and the size of the area ​ present an obstacle for landscape mapping. The use of Sentinel-2a imagery and a digital relief model allow ​a fast, inexpensive, and accurate mapping of landscapes in large areas such as mountainous Croatia. Orthophoto images were used to increase the accuracy of sampling and thus the accuracy of the final classification. Remote sensing techniques, GIS analysis and field validation were used to create an inventory of the landscapes types. This type of landscape mapping, which includes geological, geomorphological and land cover data, provides a better understanding of the composition and configuration of mountain landscapes, leading to knowledge-based management and landscape-level protection.

Centar izvrsnosti za računalni vid na Fakultetu elektrotehnike i računarstva (FER) osnovan je 2012. godine sa ciljem okupljanja relevantnih istraživača s FER-a i s drugih sastavnica Sveučilišta. U osnivanju Centra sudjelovalo je sedam sastavnica Sveučilišta u Zagrebu. Ciljevi Centra su jačanje međunarodne vidljivosti Sveučilišta u Zagrebu u području računalnog vida, stvaranje kritične mase istraživača za zajednički nastup u većim znanstvenoistraživačkim i razvojnim projektima, poboljšanje kvalitete doktorskih istraživanja u području računalnog vida i poticanje zajedničkog nastupa prema gospodarstvu radi suradnje i transfera tehnologije. U radu je predstavljena motivacija za osnivanje Centra te znanstvene i stručne aktivnosti članova Centra.

The industry of sensors and unmanned aerial systems (UAV) enables the advancement of detection of explosive objects (landmines, unexploded ordnance, improvised explosive devices) and the non-technical survey of areas contaminated by explosive threats. In the last ten years, dominates research and development of the direct detection of explosive devices versus detection of indirect indicators of the explosive threats on large areas in frame of civilian Non-Technical Survey (NTS). The impact of the mentioned phenomena is not used to its full potentials in the civilian domain of NTS. Although UAV technology can provide a large amount of data, interpretation of the data and the decision-making as an outcome of the interpretation are not developed yet. Between 1998 and 2020 many research and technology development projects on aerial NTS are realized. Some of them applied Decision Support System (DSS) paradigms: GIS-based DSS paradigm, Multi-Criteria-based DSS paradigm, Automatic Target Recognition (ATR) paradigm. The Scientific Council of HCR Center for testing, development, and training, initiated in December 2019 research and development of the Aerial Non- Technical Survey, based on UAV data acquisition, and a recommender system in its DSS functions. The proposed recommender system utilizes deep learning algorithms and collaborative filtering (CF) that rely on datasets containing selection preferences for different objects. DSS knowledge database will be based on ontologies to facilitate formal description of complex semantic structures, knowledge transfer, and reuse. The objects and preferences will be derived by fusion of features of secondary indicators, ranked by eigenvalues. The novel DSS will be implemented in the new Aerial Non-Technical Survey System which will be realized through projects by several partners. The operational validation will be done by CROMAC in mine suspected areas of Croatia.

On 19 June 2020, Ivan Racetin defended his doctoral thesis Anomaly detection on hyperspectral and multispectral digital images of a mine suspected area at the Faculty of Geodesy, University of Zagreb., Ivan Racetin obranio je 19. lipnja 2020. na Geodetskom fakultetu Sveučilišta u Zagrebu doktorski rad Detekcija anomalija na hiper­spek­tra­lnim i višespektralnim digitalnim snimkama minski sumnjivog područja.

The key object of interest in airborne and satellite Non-technical Survey are the indicators of mine presence and absence. That is why it is of great importance to establish an adequate list of indicators that will ensure the quality use and implementation of aerial and satellite Non- technical Survey. Close cooperation of all experts in the process of airborne and satellite Non- technical Survey is needed. Experts in the Mine Action Centers conduct an analytical assessment of existing Mine Information System data and establish a list of special and general requests for collecting additional information from the depth of Suspected Hazardous Area. Experts in remote sensing methods help them in forming the list of indicators for a specific geographic area. After multi-sensor airborne data collection and procurement of satellite images of a particular Suspected Hazardous Area, mine scene interpreters are locating and extracting the indicators from these images. The level of confidence is then assigned to the extracted indicators. In locating the indicators in the images, mine scene interpreters use expert and contextual knowledge of conducting war doctrines in particular geographic areas and (optional) simpler image processing methods. Geocoded indicators and their confidences are input for the production of Mine Danger Maps. This paper describes the role of indicators in Non-technical Survey processes in Croatia and Bosnia and Herzegovina within TIRAMISU – Advanced Intelligent Decision Support System.

Landmines affect the lives of people living in war-affected countries. The real challenge in humanitarian demining nowadays, within Non-technical Survey, is finding new approaches to SHA reduction. The establishment and use of mine information systems in humanitarian demining can improve the land release process by efficient mapping of suspected hazardous areas and visualizing of mine risk on it. Croatian Mine Action Center established such system and uses it for marking all suspected hazardous areas in Croatia. Nevertheless, data in this system comes from different sources and contains some inherent uncertainty. The level of ambiguity is being attempted to diminish by conducting analytical assessments of mine information system data and by collecting additional information about suspected hazardous areas. The landmine risk mapping requires defining the input data (indicators) from mine information systems and additional data that most suitably capture the association between the spatial objects of interest in the surrounding geographic area. The confidence level for each indicator is determined, which is, in fact, an estimate of the level of uncertainty. The fusion of all existing data is used after that for the purposes of creating of mine danger maps. These maps show the overall uncertainty of all input data and need further action for their use in reduction according to the Croatian Mine Action Center Standard Operational Procedures.

U članku je opisan koncept otkrivanja ilegalnih odlagališta otpada na dijelu područja grada Zagreba primjenom metoda daljinskih istraživanja na satelitskim snimkama visoke rezolucije WorldView-2. Obavljena je segmentacija vrijednosti piksela brojčanih satelitskih snimki, a nakon toga je provedena objektno orijentirana klasifikacija (u softverskom paketu Definiens Professional 5.0) na odabranim izvornim i poboljšanim snimkama navedenog satelitskog sustava prema parametrima: srednjak i standardno odstupanje. Nakon provedene klasifikacije dobiveni su rezultati filtrirani pomoću indikatora ilegalnih odlagališta otpada u GIS-softverskom paketu ArcGIS. Konačni su rezultati interpretirani (parametrima matrice konfuzije) i provjereni (validirani) preklapanjem s referentnim podacima o poznatim ilegalnim nesaniranim odlagalištima otpada i izlaskom na teren.

In the mine action community, Non-Technical Survey is implemented to provide information for better spatial definition of mine or explosive remnants of war contamination. Airborne and spaceborne surveys of wider Suspected Hazardous Area (SHA) regions are often executed to collect information about physical changes and circumstances that may be employed in the subsequent technical interventions. Simple electro-optical sensors which acquire data from the visible part of electromagnetic spectrum, like DSLR or SLR cameras, can be used for this kind of surveys. These aerial RGB images are then inspected by trained human photo (mine scene) interpreter who is familiar with the military doctrine and specific characteristics of the conflict. Mine scene interpreter seeks for the indicators of mine presence and absence. Novel image processing techniques could provide benefits to the standard photointerpretation workflow by making it more efficient. Geographic object-based image analysis (GEOBIA) is one of them. The idea of GEOBIA is to process georeferenced images at the object level, as the entities found in the environment are usually objects (or grouped pixels) instead of single pixels. This approach enables analysis of spatial relations and geometrical object parameters. The main step influencing the GEOBIA results is the quality of image segmentation. In this paper, results of more image segmentation algorithms are tested on the color aerial images of SHA and images of exploded ammunition depot in the Croatia. Acquired results are discussed, while potential and constraints of image segmentation for application in the Non-technical survey are underlined.

Although calibration during geocoding process shows drastic improvements in achieved geocoding accuracy, the internal orientation error remains. In order to properly determine these errors, we must first of all know the mathematical model of mapping of the line sensor. The mathematical model of mapping of the line sensor has been expanded to account for the distortion of the lens in order to eliminate all systematic errors induced by displacement of the real sensor mapping plane from the ideal mathematical model of the central projection. After a mathematical model was established, a calibration of the hyperspectral scanner was performed in the laboratory, observing test samples from 5 different recording sites. Calibration elements are determined by airborne beam equation (BBA method).

Computer-assisted image processing for extracting of IMP on the basis of object oriented analysis (using images segmentation) was carried out (by means of factor and cluster analysis) within the interactive interpretation of images. The final evaluation will be conducted by experienced interpreter and it will be also carried out on the basis of NIIRS and IQM parameters. The one aim of this research is to establish a methodology and guidelines for interactive semi-automatic interpretation of digital images in humanitarian demining for the purpose of detection and extraction of (strong) indicators of mine presence and absence which can be seen on the images. The experience gathered in working with AI DSS in undertaken projects led to the conclusion that a man (the human eye and contextual view on the scene) as interpreter (of mine scene) can hardly be replaced by automatic methods of digital image processing. However, some methods of digital image processing (implemented in certain ways) may help the interpreter in the identification of certain anomalies in the scene and easier detection of indicators. The basic idea of interactive methods of semi-automatic interpretation of digital images of SHA is to provide assistance to the interpreter in the interpretation of digital images rather than to replace him. The objective of this method is to be sensor independent and independent of object of research. The concept of this method was defined and initial research carried out in 2013.

The crucial document for the success of T-AI DSS application is the analytical assessment of the suspected hazardous area (SHA) based on data and information that are available in MIS of MACs. The outcomes of this analysis are the general and specific requirements for the airborne and space borne collecting and producing new, additional data, information and evidences about the former situation in SHA. The requirement for improvement of this module implies the determination of general guidelines for the implementation of this analysis in any MAC’s of mine-affected countries. According to this requirement, within this T-AI DSS’s module, general guidelines for conducting of the analytical assessment for better definition of the SHA and the definition of general and specific requirements for the collection of additional data (with T-AI DSS) for better re-definition of the SHA have been developed.

The module of T-AI DSS for data acquisition should provide the stability and reliability of (aerial) data acquisition on each platform. Subsystems (system configurations are different for different platforms) for aerial data acquisition will be examined on multiple platforms (Mi-8, blimp, Bell-206) and should have stable operation, without cancellation, on every platform. A new system for aerial hyperspectral survey: TIRAMISU light hyperspectral imaging system (T-LHSIS), was conceptualized by CTDT, designed, constructed and manufactured by FGUNIZ. T-LHSIS was tested on two platforms: blimp and Bell-206 helicopter by CTDT and FGUNIZ. The features of the system shown in the following text. T-LHSIS is a new tool, which can be used as stand alone equipment or in T-AIDSS. The helicopter Bell- 206 is a new platform which can be used within T-AI DSS. The continuous and stable electricity supply for the aerial acquisition multisensor subsystem is re- designed, developed and built up in T-AI DSS. It is necessary to provide the independence of the power supply for the aerial acquisition system of AI DSS. This module is used for the collection of additional data from the depths of SHA. The requirements (general and specific) for the collection of additional data on SHA-in are the result of work in the module for the analytical assessment of the data in MIS.

The general survey of the unexploded ordnance (UXO) scattered around the ammunition depot after its unplanned explosion and the ground based measurements of the hyper spectral samples (end members) of UXO have been done in order to create initial spectral library of UXO. The methods, technique and collected data are presented and evaluated. The Johnson’s criterion was used for detection, classification, recognition and identification of UXO in the airborne images (visible and near infrared wavelengths) of the surrounding of the ammunition depot. The test site near Benkovac contains 1000 landmines and 524 metal debris buried in the year 2001 in squares 1x1 m, at depths from 5 to 20 cm below the surface. The locations of 885 landmines and debris are not public and the blind tests are possible. The sparse vegetation covers some squares since the soil is meager. The hyper spectral data have been collected of the 1x1 m squares by the ground based mechanic scanner. The spectral samples of the vegetation inside and outside of the test site have been collected and total Nitrogen contents were measured.

Hrvatski centar za razminiranje (HCR) je još 2004. godine pregledao, definirao i označio cjelokupnu minski sumnjivu površinu (MSP) u Republici Hrvatskoj (RH). Međutim, zbog smanjenja rizika i nedostatka informacija iz dubine MSP-a, njezine granice definirane su u većim površinama nego što ih zauzima u stvarnosti. Razminiranje je dugotrajan i skup proces, a RH se obvezala da će do 201 9. godine riješiti problem mina na svome teritoriju. Takav razvoj situacije dovodi do traženja i pronalaženja rješenja za ubrzavanje rješavanja minskog problema u RH (a i u svijetu) redukcijom definiranog MSP-a. Za redukciju već definiranih MSP-a potrebni su dodatni podaci i informacije iz dubine MSP-a na osnovi kojih će se revizijom postojećeg MSP-a izvršiti redukcija. Svi naknadno prikupljeni podaci i informacije, zajedno s poznatim podacima iz minskog informacijskog sustava (MIS) HCR-a, obrađuju se u sustavu za potporu odlučivanja u uvjetima neodređenosti. Tako dobiveni rezultati prikazuju se na različitim tematskim kartama koje prikazuju položaje objekta i njihove utjecaje na okolinu u prostoru. Dakle, tematske karte na jednom prikazu daju uvid u teme na osnovi kojih eksperti u humanitarnom razminiranju mogu donositi odluke u tom procesu. Takve tematske karte rezultat su metodologije stvarane unutar projekta Space and Airborne Mined Area Reduction Tools (SMART), a dalje su razvijane: u tehnologijskom projektu Sustav za multisenzorsko zrakoplovno izviđanje i nadzor u izvanrednim situacijama i zaštiti okoliša, TP-06/0007-01, Ministarstva znanosti, obrazovanja i sporta RH ; u projektu Deployment of the Advanced Intelligence Advanced Intelligence Decision Support System for Mine Suspected Area Reduction in Bosnia and Herzegovina i autorovoj doktorskoj disertaciji. Ovim radom se uspostavljaju novi nazivi unaprijeđenih i novih tematskih karata koji nedvosmisleno definiraju ono što prikazuju i olakšavaju čitljivost i komunikaciju između proizvođača i korisnika.

A frequent and quite normal situation in the crisis management is an instance of uncertainty and a lack of amount, structure, time adequacy and quality of information and data, thus the decisions makers and reacting managers have to deal with this problem. In the technologic project TP-06/0007-01 was implemented Decision Support System (DSS) for the area reduction for mine action management on a strategic level through the use of data fusion methodological approach and the upgrade of the results from SMART project . Although the DSS was applied on the problems of the humanitarian mine, it has wider potential and could be applied in other crisis situations. Data fusion methodological approach is based on (1) the interpreted and fused multi-sensor imagery collected by aerial reconnaissance and surveillance, (2) enhanced and extracted indicators of mine presence and indicators of mine absence, (3) the formalized expert knowledge, (4) on the combined contextual data, (5) the spatial data provided by geographic information system (GIS) and (6) on the data contained in other information systems (e.g. Mine Information System (MIS) of the mine action centre (MAC)). The generic solutions from SMART have been integrated with data fusion methodological approach and implemented in the form of the DSS. SMART is intended to provide some of this additional information that would help in two ways: it can reinforce the suspicion of some places and reduce the suspected area on others. Output of the DSS at the final stage consist of three maps: (1) the map of mine danger measure, (2) confidence map of indicators of mine presence and indicators of mine absence, (3) the map of spatial stability of results. The methodological combination of three of them enables the validation or dismissal of areas proposed for reduction, thus they are suitable for practical use in mine action management of the humanitarian demining.

Nastojanjem dobivanja boljeg uvida u min-sko sumnjivo područje (MSP) u Republici Hrvatskoj, u okviru projekta Europske komisije Airborne Minefield Area Reduction (ARC, EC IST-2000-25300, http://www.arc.vub.ac.be) formiran je digitalni zrakoplovni višesenzorski i višerazlučivi sustav za prikupljanje in-formacija (snimki) o minsko sumnjivoj površini. Sustav se sastoji od matrične kamere (vidljivi i blisko infra-crveni dio elektromagnetskog spektra, 0.4-1.1 µm), termalnog (termalni dio elektromagnetskog spektra, 8-12 µm) i hiperspektralnog linijskog skenera. Zbog specifične namjene sustava i objekata koje je trebalo otkriti na sceni, snimanja su provođena sa relativnih visina leta platforme (helikopter) od 130 do 900 m. Kako su relativne visine leta bile male, a MSP velika, broj snimki bio je također velik i pojavila se potreba za spajanjem snimki u veće cjeline kako bi se dobio uvid u cjelinu područja i interakciju utjecaja detek-tiranih objekata na sceni. Sustav nije raspolagao s modulom za automatsko mozaiciranje i geokodiranje pa se u tu svrhu prišlo ručnoj izradi mozaika, a nakon toga ručnom geokodiranju. Ti su postupci zatim omo-gućili klasifikaciju scene, kako bi se scena što bolje raščlanila i fuziju višesenzorskih i višerazlučivih slika kako bi se što više informacija moglo iz nje dobiti. U ovom radu pokazano je da je moguće provesti spomenute procese i uz pomoć ručnog mozaiciranja i geokodiranja., The digital airborne multisensor and multiresolution system for collection of information (images) about mine suspected area was created, within European commission project Airborne Minefield Area Reduction (ARC, EC IST-2000-25300, http://www.arc.vub.ac.be) to gain a better perspective in mine suspected areas (MSP) in the Republic of Croatia. The system consists of a matrix camera (visible and near infrared range of electromagnetic spectrum, 0.4-1.1 µm), thermal (thermal range of electromagnetic spectrum, 8-14 µm) and a hyperspectral linear scanner. Because of a specific purpose and seeking object on the scene, the flights for collecting the images took place at heights from 130 m to 900 m above the ground. The result of a small relative flight height and large MSPs was a large number of images which cover MSPs. Therefore, the need for merging images in largest parts, for a better perspective in whole MSPs and the interaction of detected object influences on the scene appeared. The mentioned system did not dispose of the module for automatic mosaicking and geocoding, so mosaicking and after that geocoding were done manually. This process made the classification of the scene (better distinguishing of objects on the scene) and fusion of multispectral and multiresolution images after that possible. Classification and image fusion can be even done by manually mosaicking and geocoding. This article demonstrated this claim.

Recent research in projects ARC and SMART (European Commission IST programme) shows that long wave thermal IR images enable detection of the objects that are otherwise not detectable. However, the important conclusion from this research is that the spatial resolution of available thermal IR cameras is not satisfactory. The possible way to compensate partially this deficiency can be data fusion. Due to the experience gained and the lessons learned in many years of the airborne remote sensing with thermal IR cameras we decided to analyze the fusion of the thermal IR images with images from visible and near IR wavelengths. The first goal was improvement of spatial resolution (sharpening) and this has been achieved. More important goal was the evaluation the radiometric quality of the fusion due to different physical background of the images. For this purpose many statistical parameters of different objects in the source thermal IR image were analysed and compared to the respective statistical parameters set for the same objects in the image obtained by fusion. The objects used in the analysis selected by use of the ground truth data that were available for the identification. The thermal IR contrast C between object “o” and background “b” used for comparison of the fused and source images too. The results of the analysis approved that the applied fusion method provides improvement of the spatial resolution and that thermal information of the analyzed objects conserved. Due to ap-proved quality of the fusion method, we recommend its application.

Airborne acquisition of the same part of terrain was done from different heights (500 and 900 meters), by digital matrix camera which collects data about landscape in four wavelengths: three visible channels (V: 0.4-0.5 µm, 0.5-0.6 µm, 0.6-0.7µm) and one near infrared channel (NIR: 0.7-0.9 µm). The set of images of the same terrain which are chosen consists of two RGB images (they are made of: green (G), red (R) and infrared (IR) = color infrared (CIR)) collected from: 500 m (higher space resolution) and 900 m (lower space resolution). With data fusion (used methods are: proncipal components, IHS and method of relative contribution) two products were made: RGB image with higher space resolution inside of the mentioned set of images (higher space resolution (from image collected from 500 m) was implemented in the image collected from 900 m) and RGB image with lower space resolution inside of the set of images (lower space resolution (from image collected from 900 m) was implemented in image collected from 500 m). This action produced two pairs of comparable images: the first one – the product of data fusion with higher spatial resolution and original image with higher spatial resolution (image collected from 500 m) ; and the second product of data fusion with lower spatial resolution and original image with lower resolution (image collected from 900 m). Namely, the main problem in the analysis of the quality of fused product is how to get reference image. In the majority cases that image needs to be produced, which means that both images are produced (result of fusion and reference image). On the contrary, in this work we provide the analysis of the qualitiy of fused products (on pixel level) on the existing original image basis. Those images are images collected from 500 and 900 m. Changes of images in both directions were monitored, regarding the improving and degradation of spatial resolution. The analysis of qualitiy of fused products was done through statistical parameters (mean, standard deviation, variance, corelation, scatter plot), contrast of images. At the end the existing proposition for protocol for assessment of the quality of fused product basis (Thomas& Wald, 2004) is discussed.

The main issue of the work was the measurement of the response of particular channels of the VNIR high resolution camera aimed for the development of the radiometric calibration. The analysed VNIR camera has several controlable parameters: gain, integration (exposition) time, bias, separately for near infrared (NIR) and red (R), channels and common for green and blue (G/B) channels. The control of these parameters is possible during the airborne acquisition and this provides very flexible imaging system that can be matched to the actual visibility above the mapped terrain. The measurements show that the channels of the VNIR camera have very different responses in NIR and R channels in comparison to G/B channels, if the gain was changed from minimum to maximum. The particulary powerfull feature of the considered digital VNIR camera is the available dynamic range, it can be 8 bits (from one to all four channels) or 10 bits (from one to three channels). Preliminary measurements and analysis show that 10 bits range enables robust mode of imaging during the changeable visibilty. The price for this is increase of the requirment to the memory of the acquisition system. The selection of the imaging parameters is not strightforward, it depends strongly on the features of the mapped scene. Recent analysis was performed with aim to enable production of the mosaics in visible (V) or in colour and the infrared bands (CIR). These mosaics serve as background for the subjective in-terpreetation of the shown scene, while outputs were landuse thematic map in CORINE methodology and specific features (vectors). Due to radiometric imperfection of the considered VNIR camera, the obtained VNIR images are radiometricaly distorted. The analysis of the influ-ence of the radiometric features of acquired images was performed on raw and on calibrated images, by analysis of the quality of the classification. The obtained results enable conclusion that the well calibrated digital VNIR camera can provide automated detection of objects in the scene and their thematic interpretation that was not possible on panchromatic digital ortho photo image map.

The 20th Congress of ISPRS (International society for Photogrammetry and Remote Sensing) was held in Istanbul, Turkey, July 12-23. in 2004.

Zagađenost minama je jedno od najtežih nasljeđa rata koje za sobom ostavlja posljedice dugi niz godina. Redukcija površina kontaminiranih minama multidisciplinarna je zadaća u kojoj svoje mjesto nalaze i daljinska istraživanja i fotogrametrija i GIS. U ovom trenutku u RH se u okviru dvaju projekata koje financira Europska komisija istražuju i verificiraju metode i alati koji bi omogućili smanjivanje sumnjivih površina bez izravnog kontakta sa tlom. Radi se o uporabi zrakoplovnih senzora (digitalnih kamera, radara sa sintetičkom antenom), naprednih tehnologija objektivne interoretacije (združivanje podataka, posredovanje znanja, integracija kontekstualnih informacija) te GIS-a kao integratora podataka. U projektima sudjeluju hrvatski timovi, s istaknutim doprinosom geodetskog fakulteta Sveučilišta u Zagrebu. U radu su prikazane osnovne ideje primjene daljinskih istraživanja, fotogrametrije i GIS-a u službi razminiranja, s primjerima iz navedenih projekata.