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&Alpha, bstract: To date, countless satellite image fusions have been made, mainly with panchromatic spatial resolution to a multispectral image ratio of 1/4, fewer fusions with lower ratios, and relatively recently fusions with much higher spatial resolution ratios have been published. Apart from this, there is a small number of publications studying the fusion of aerial photographs with satellite images, with the year of image acquisition varying and the dates of acquisition not mentioned. In addition, in these publications, either no quantitative controls are performed on the composite images produced, or the aerial photographs are recent and colorful and only the RGB bands of the satellite images are used for data fusion purposes. The objective of this paper is the study of the addition of multispectral information from satellite images to black and white aerial photographs of the 80s decade (1980&ndash, 1990) with small difference (just a few days) in their image acquisition date, the same year and season. Quantitative tests are performed in two case studies and the results are encouraging, as the accuracy of the classification of the features and objects of the Earth&rsquo, s surface is improved and the automatic digital extraction of their form and shape from the archived aerial photographs is now allowed. This opens up a new field of use for the black and white aerial photographs and archived multispectral satellite images of the same period in a variety of applications, such as the temporal changes of cities, forests and archaeological sites.

Ancient Amphipolis (Eastern Macedonia, Greece) is one of the most important archaeological sites of Greece. Despite the restricted excavation studies, important monuments have been discovered, such as the city walls and the Macedonian burial site at the Kasta hill, etc. Currently, the location of the ancient theater is unknown and only assumptions can be made regarding its location. In the current study, we aim to detect the accurate location of the ancient theater using archaeological prospection tools, data collected from the excavated sites, and testimonies of people of the modern city. For the first step of the approach, the approximate location of the ancient theater was determined using information derived by archived geospatial data (multi-temporal aerial photographs, satellite image, and Digital Terrain Model (DTM) of the area) as well as information regarding the neighboring excavated sites. For the in-depth study of the area of interest, a drone was used for the acquisition of high-resolution geospatial data. The generated orthorectified image (3 cm spatial resolution), DTM, and Digital Surface Model (DSM) allowed the determination of the potential location of the buried orchestra’s center using geometric rules for the design of ancient theaters. Furthermore, using the produced DSM and DTM, terrain cross-sections were generated.

New techniques and methodological procedures, which would allow at a short time and at low cost for the identification of a new archaeological sites, were always in the interest of archaeologists. In addition, fast and accurate 3D modelling and documentation techniques were also always a hot research topic because they can help archeologists to document active excavation sites fast, thus helping them to advance the excavation in a timely manner. In this chapter, aerial and remote sensing archaeology issues will be analyzed, both as measuring tools for the documentation of existing archaeological structures as well as tools of archaeology prospection, which are based on the appearance of the reflection of covered structures in images (i.e., the so-called marks).

New techniques and methodological procedures, which would allow at a short time and at low cost for the identification of a new archaeological site, were always in the interest of archaeologists. In this paper, aerial and remote sensing archaeology issues will be analyzed, both as measuring tools for the documentation of existing archaeological structures as well as tools of archaeology prospection, which are based on the appearance of the reflection of covered structures in images, i.e. the so-called marks.

Improved sensor characteristics are generally assumed to increase the potential accuracy of image classification and information extraction from remote sensing imagery. However, the increase in data volume caused by these improvements raise challenges associated with the selection, storage, and processing of this data, and with the cost-effective and timely analysis of the remote sensing datasets. Previous research has extensively assessed the relevance and impact of spatial, spectral and temporal resolution of satellite data on classification accuracy, but little attention has been given to the impact of radiometric resolution. This study focuses on the role of radiometric resolution on classification accuracy of remote sensing data through different classification experiments over three different sites. The experiments were carried out using fine and low scale radiometric resolution images classified through a bagging classification tree. The classification experiments addressed different aspects of the classification road map, including among others, binary and multiclass classification schemes, spectrally and spatially enhanced images, as well as pixel and objects as units of the classification. In addition, the impact of image radiometric resolution on computational time and the information content in fine- and low-resolution images was also explored. While in certain cases, higher radiometric resolution has led to up to 8% higher classification accuracies compared to lower resolution radiometric data, other results indicate that higher radiometric resolution does not necessarily imply improved classification accuracy. Also, classification accuracy of spectral indices and texture bands is not related so much to the radiometric resolution of the original remote sensing images but rather to their own radiometric resolution. Overall, the results of this study suggest that data selection and classification need not always adhere to the highest possible radiometric resolution.

Within the field of forestry, forest road mapping and inventory plays an important role in management activities related to wood harvesting industry, sentiment and water run-off modelling, biodiversity distribution and ecological connectivity, recreation activities, future planning of forest road networks and wildfire protection and fire-fighting. Especially in countries of the Mediterranean Rim, knowledge at regional and national scales regarding the distribution and the characteristics of rural and forest road network is essential in order to ensure an effective emergency management and rapid response of the fire-fighting mechanism. Yet, the absence of accurate and updated geodatabases and the drawbacks related to the use of traditional cartographic methods arising from the forest environment settings, and the cost and efforts needed, as thousands of meters need to be surveyed per site, trigger the need for new data sources and innovative mapping approaches. Monitoring the condition of unpaved forest roads with unmanned aerial vehicle technology is an attractive option for substituting objective, laboursome surveys. Although photogrammetric processing of UAV imagery can achieve accuracy of 1-2 centimeters and dense point clouds, the process is commonly based on the establishment of control points. In the case of forest road networks, which are linear features, there is a need for a great number of control points. Our aim is to evaluate low-cost UAV orthoimages generated over forest areas with GCP’s captured from existing national scale aerial orthoimagery, satellite imagery available through a web mapping service (WMS), field surveys using Mobile Mapping System and GNSS receiver. We also explored the direct georeferencing potential through the GNSS onboard the low cost UAV. The results suggest that the GNSS approach proved to most accurate, while the positional accuracy derived using the WMS and the aerial orthoimagery datasets deemed satisfactory for the specific task at hand. The direct georeferencing procedure seems to be insufficient unless an onboard GNSS with improved specifications or Real-Time Kinematic (RTK) capabilities is used.

More than ever, there is a need from policy and decision makers, national governments, nongovernmentalorganizations, international initiatives, scientists, and individual citizens for timelyand accurate spatially-explicit information on Earth’s physical surface cover and the socio-economicfunction of land at multiple scales. Information on land-cover, land-use patterns and monitoring oftheir changes, can support regional policies and local action for sustainable development in terms ofefficiency in resources use, disaster risk reduction, and environmental protection [...]

There is a continuous and increasing demand for solutions, both software and hardware-based, that are able to productively handle underground utilities geospatial data. Innovative approaches that are based on the use of the European GNSS, Galileo and EGNOS, sensor technologies and LBS, are able to monitor, document and manage utility infrastructures’ data with an intuitive 3D augmented visualisation and navigation/positioning technology. A software and hardware-based system called LARA, currently under develop- ment through a H2020 co-funded project, aims at meeting that demand. The concept of LARA is to integrate the different innovative components of existing technologies in order to design and develop an integrated navigation/positioning and information system which coordinates GNSS, AR, 3D GIS and geodatabases on a mobile platform for monitoring, documenting and managing utility infrastruc- tures on-site. The LARA system will guide utility field workers to locate the working area by helping them see beneath the ground, rendering the complexity of the 3D models of the underground grid such as water, gas and electricity. The capacity and benefits of LARA are scheduled to be tested in two case studies located in Greece and the United Kingdom with various underground utilities. The paper aspires to present the first results from this initiative. The project leading to this application has received funding from the European GNSS Agency under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641460.