bluuebunny/crossref_metadata_2025 huggingface dataset:
MEASURE OF LANDSCAPE HETEROGENEITY BY AGENT-BASED METHODOLOGY
Authors: Wirth E. , Szabó Gy. , Czinkóczky A.
Published: August 2016

With the rapid increase of the world's population, the efficient food production is one of the key factors of the human survival. Since biodiversity and heterogeneity is the basis of the sustainable agriculture, the authors tried to measure the heterogeneity of a chosen landscape. The EU farming and subsidizing policies (EEA, 2014) support landscape heterogeneity and diversity, nevertheless exact measurements and calculations apart from statistical parameters (standard deviation, mean), do not really exist. In the present paper the authors’ goal is to find an objective, dynamic method that measures landscape heterogeneity. It is achieved with the so called agent-based modelling, where randomly dispatched dynamic scouts record the observed land cover parameters and sum up the features of a new type of land. During the simulation the agents collect a Monte Carlo integral as a diversity landscape potential which can be considered as the unit of the ‘greening’ measure. As a final product of the ABM method, a landscape potential map is obtained that can serve as a tool for objective decision making to support agricultural diversity.
COMPARISON OF HIGH AND LOW DENSITY AIRBORNE LIDAR DATA FOR FOREST ROAD QUALITY ASSESSMENT
Authors: Kiss K. , Malinen J. , Tokola T.
Published: August 2016

Good quality forest roads are important for forest management. Airborne laser scanning data can help create automatized road quality detection, thus avoiding field visits. Two different pulse density datasets have been used to assess road quality: high-density airborne laser scanning data from Kiihtelysvaara and low-density data from Tuusniemi, Finland. The field inventory mainly focused on the surface wear condition, structural condition, flatness, road side vegetation and drying of the road. Observations were divided into poor, satisfactory and good categories based on the current Finnish quality standards used for forest roads. Digital Elevation Models were derived from the laser point cloud, and indices were calculated to determine road quality. The calculated indices assessed the topographic differences on the road surface and road sides. The topographic position index works well in flat terrain only, while the standardized elevation index described the road surface better if the differences are bigger. Both indices require at least a 1 metre resolution. High-density data is necessary for analysis of the road surface, and the indices relate mostly to the surface wear and flatness. The classification was more precise (31–92%) than on low-density data (25–40%). However, ditch detection and classification can be carried out using the sparse dataset as well (with a success rate of 69%). The use of airborne laser scanning data can provide quality information on forest roads.
APPLICATION OF GIS AND GROUNDWATER MODELLING TECHNIQUES TO IDENTIFY THE PERCHED AQUIFERS TO DEMARKATE WATER LOGGING CONDITIONS IN PARTS OF MEHSANA
Authors: Rawal D. , Vyas A. , Rao S. S.
Published: August 2016

Groundwater is very important component of the hydrological cycle. It is an important source of water for drinking, domestic, industrial and agricultural uses. It plays a key role in meeting the water needs of various users sectors in India. Ground water resource is contributed by two major sources – rainfall and the other seepage from irrigation of the crops. A man-made effort through artificial recharge for water conservation structures adds to the ground water. The ground water behaviour in Indian sub-continent is highly complicated due to the occurrence of diversified geological formations with considerable lithological and chronological variations, complex tectonic framework, climatological dissimilarities and various hydro-chemical conditions. Assessment of ground water resources of an area requires proper identification and mapping of geological structures, geomorphic features along with sound information regarding slope, drainage, lithology, soil as well as thickness of the weathered zones.
 This study is to understand the ground water scenario in the water logged areas of Dharoi command while the surrounding areas showing continuous decline of water levels. The area falls in the command area of Dhorai dam and is in Mehsana District of Gujarat State. A part of northern command of Dharoi Command area falls in hard rock areas while the lower and southern portion fall in alluvial areas in the Dharoi Command (RBC) area in Mahsana Mehsana District of the Gujarat State.

 The study highlights the application of GIS in establishing the basic parameters of soil, land use and the distribution of water logging over a period of time and the groundwater modelling identifies the groundwater regime of the area and estimates the total recharge to the area due to surface water irrigation and rainfall and suggests suitable method to control water logging in the area.
TOWARDS "DRONE-BORNE" DISASTER MANAGEMENT: FUTURE APPLICATION SCENARIOS
Authors: Tanzi Tullio Joseph , Chandra Madhu , Isnard Jean , Camara Daniel , Sebastien Olivier , Harivelo Fanilo
Published: August 2016

Information plays a key role in crisis management and relief efforts for natural disaster scenarios. Given their flight properties, UAVs (Unmanned Aerial Vehicles) provide new and interesting perspectives on the data gathering for disaster management. A new generation of UAVs may help to improve situational awareness and information assessment. Among the advantages UAVs may bring to the disaster management field, we can highlight the gain in terms of time and human resources, as they can free rescue teams from time-consuming data collection tasks and assist research operations with more insightful and precise guidance thanks to advanced sensing capabilities. However, in order to be useful, UAVs need to overcome two main challenges. The first one is to achieve a sufficient autonomy level, both in terms of navigation and interpretation of the data sensed. The second major challenge relates to the reliability of the UAV, with respect to accidental (safety) or malicious (security) risks.

 This paper first discusses the potential of UAV in assisting in different humanitarian relief scenarios, as well as possible issues in such situations. Based on recent experiments, we discuss the inherent advantages of autonomous flight operations, both lone flights and formation flights. The question of autonomy is then addressed and a secure embedded architecture and its specific hardware capabilities is sketched out.

 We finally present a typical use case based on the new detection and observation abilities that UAVs can bring to rescue teams. Although this approach still has limits that have to be addressed, technically speaking as well as operationally speaking, it seems to be a very promising one to enhance disaster management efforts activities.
A METEOROLOGICAL RISK ASSESSMENT METHOD FOR POWER LINES BASED ON GIS AND MULTI-SENSOR INTEGRATION
Authors: Lin Zhiyong , Xu Zhimin
Published: August 2016

Power lines, exposed in the natural environment, are vulnerable to various kinds of meteorological factors. Traditional research mainly deals with the influence of a single meteorological condition on the power line, which lacks of comprehensive effects evaluation and analysis of the multiple meteorological factors. In this paper, we use multiple meteorological monitoring data obtained by multi-sensors to implement the meteorological risk assessment and early warning of power lines. Firstly, we generate meteorological raster map from discrete meteorological monitoring data using spatial interpolation. Secondly, the expert scoring based analytic hierarchy process is used to compute the power line risk index of all kinds of meteorological conditions and establish the mathematical model of meteorological risk. By adopting this model in raster calculator of ArcGIS, we will have a raster map showing overall meteorological risks for power line. Finally, by overlaying the power line buffer layer to that raster map, we will get to know the exact risk index around a certain part of power line, which will provide significant guidance for power line risk management. In the experiment, based on five kinds of observation data gathered from meteorological stations in Guizhou Province of China, including wind, lightning, rain, ice, temperature, we carry on the meteorological risk analysis for the real power lines, and experimental results have proved the feasibility and validity of our proposed method.
SPATIAL CORRELATIONS OF MALARIA INCIDENCE HOTSPOTS WITH ENVIRONMENTAL FACTORS IN ASSAM, NORTH EAST INDIA
Authors: Handique Bijoy K. , Khan Siraj A. , Dutta Prafulla , Nath Manash J. , Qadir Abdul , Raju P. L. N.
Published: August 2016

Malaria is endemic and a major public health problem in north east (NE) region of India and contributes about 8-12 % of India's malaria positives cases. Historical morbidity pattern of malaria in terms of API (Annual Parasite Incidence) in the state of Assam has been used for delineating the malaria incidence hotspots at health sub centre (HSC) level. Strong spatial autocorrelation (p < 0.01) among the HSCs have been observed in terms of API (Annual Parasite Incidence). Malaria incidence hot spots in the state could be identified based on General G statistics and tested for statistical significance. Spatial correlation of malaria incidence hotspots with physiographic and climatic parameters across 6 agro-climatic zones of the state reveals the types of land cover pattern and the range of elevation contributing to the malaria outbreaks. Analysis shows that villages under malaria hotspots are having more agricultural land, evergreen/semi-evergreen forests with abundant waterbodies. Statistical and spatial analyses of malaria incidence showed a significant positive correlation with malaria incidence hotspots and the elevation (p < 0.05) with villages under malaria hotspots are having average elevation ranging between 17 to 240 MSL. This conforms to the characteristics of two dominant mosquito species in the state Anopheles minimus and An. baimai that prefers the habitat of slow flowing streams in the foot hills and in forest ecosystems respectively.
COMPARISON OF VERY NEAR INFRARED (VNIR) WAVELENGTH FROM EO-1 HYPERION AND WORLDVIEW 2 IMAGES FOR SALTMARSH CLASSIFICATION
Authors: Rasel Sikdar M.M. , Chang Hsing-Chung , Diti Israt Jahan , Ralph Tim , Saintilan Neil
Published: August 2016

Saltmarsh is one of the important communities of wetlands. Due to a range of pressures, it has been declared as an EEC (Ecological Endangered Community) in Australia. In order to correctly identify different saltmarsh species, development of distinct spectral characteristics is essential to monitor this EEC. This research was conducted to classify saltmarsh species based on spectral characteristics in the VNIR wavelength of Hyperion Hyperspectral and Worldview 2 multispectral remote sensing data. Signal Noise Ratio (SNR) and Principal Component Analysis (PCA) were applied in Hyperion data to test data quality and to reduce data dimensionality respectively. FLAASH atmospheric correction was done to get surface reflectance data. Based on spectral and spatial information a supervised classification followed by Mapping Accuracy (%) was used to assess the classification result. SNR of Hyperion data was varied according to season and wavelength and it was higher for all land cover in VNIR wavelength. There was a significant difference between radiance and reflectance spectra. It was found that atmospheric correction improves the spectral information. Based on the PCA of 56 VNIR band of Hyperion, it was possible to segregate 16 bands that contain 99.83 % variability. Based on reference 16 bands were compared with 8 bands of Worldview 2 for classification accuracy. Overall Accuracy (OA) % for Worldview 2 was increased from 72 to 79 while for Hyperion, it was increased from 70.47 to 71.66 when bands were added orderly. Considering the significance test with z values and kappa statistics at 95% confidence level, Worldview 2 classification accuracy was higher than Hyperion data.
LEICA DMC III CALIBRATION AND GEOMETRIC SENSOR ACCURACY
Authors: Mueller C. , Neumann K.
Published: August 2016

As an evolution of the successful DMC II digital camera series, Leica Geosystems has introduced the Leica DMC III digital aerial camera using, for the first time in the industry, a large-format CMOS sensor as a panchromatic high-resolution camera head. This paper describes the Leica DMC III calibration and its quality assurance and quality control (QA/QC) procedures. It will explain how calibration was implemented within the production process for the Leica DMC III camera. Based on many years of experience with the DMC and DMC II camera series, it is know that the sensor flatness has a huge influence on the final achievable results. The Leica DMC III panchromatic CMOS sensor with its 100.3mm x 56.9mm size shows remaining errors in a range of 0.1 to 0.2μm for the root mean square and shows maximum values not higher that 1.0μm. The Leica DMC III is calibrated based on a 5cm Ground Sample Distance (GSD) grid pattern flight and evaluated with three different flying heights at 5cm, 8cm and 11cm GSD. The geometric QA/QC has been performed using the calibration field area, as well as using an independent test field. The geometric performance and accuracy is unique and gives ground accuracies far better than the flown GSD.
CO-REGISTRATION OF TERRESTRIAL AND UAV-BASED IMAGES – EXPERIMENTAL RESULTS
Authors: Gerke M. , Nex F. , Jende P.
Published: August 2016

For many applications within urban environments the combined use of images taken from the ground and from unmanned aerial platforms seems interesting: while from the airborne perspective the upper parts of objects including roofs can be observed, the ground images can complement the data from lateral views to retrieve a complete visualisation or 3D reconstruction of interesting areas. The automatic co-registration of air- and ground-based images is still a challenge and cannot be considered solved. The main obstacle is originating from the fact that objects are photographed from quite different angles, and hence state-of-the-art tie point measurement approaches cannot cope with the induced perspective transformation. One first important step towards a solution is to use airborne images taken under slant directions. Those oblique views not only help to connect vertical images and horizontal views but also provide image information from 3D-structures not visible from the other two directions. According to our experience, however, still a good planning and many images taken under different viewing angles are needed to support an automatic matching across all images and complete bundle block adjustment. Nevertheless, the entire process is still quite sensible – the removal of a single image might lead to a completely different or wrong solution, or separation of image blocks.

 In this paper we analyse the impact different parameters and strategies have on the solution. Those are a) the used tie point matcher, b) the used software for bundle adjustment. Using the data provided in the context of the ISPRS benchmark on multi-platform photogrammetry, we systematically address the mentioned influences. Concerning the tie-point matching we test the standard SIFT point extractor and descriptor, but also the SURF and ASIFT-approaches, the ORB technique, as well as (A)KAZE, which are based on a nonlinear scale space. In terms of pre-processing we analyse the Wallis-filter. Results show that in more challenging situations, in this case for data captured from different platforms at different days most approaches do not perform well. Wallis-filtering emerged to be most helpful especially for the SIFT approach. The commercial software pix4dmapper succeeds in overall bundle adjustment only for some configurations, and especially not for the entire image block provided.
AUTONOMOUS NAVIGATION OF SMALL UAVS BASED ON VEHICLE DYNAMIC MODEL
Authors: Khaghani M. , Skaloud J.
Published: August 2016

This paper presents a novel approach to autonomous navigation for small UAVs, in which the vehicle dynamic model (VDM) serves as the main process model within the navigation filter. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs on-board. This is achieved with no extra sensor added to the conventional INS/GNSS setup. This improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The VDM is also fed with the control input to the UAV, which is available within the control/autopilot system. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS navigation system during the autonomous phase, when satellite signals are not available due to physical obstruction or electromagnetic interference for example. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to inertial coasting. It means that during such scenario, the position-velocity-attitude (PVA) determination is sufficiently accurate to navigate the UAV to a home position without any signal that depends on vehicle environment.
GEOMETRIC CALIBRATION AND VALIDATION OF ULTRACAM AERIAL SENSORS
Authors: Gruber Michael , Schachinger Bernhard , Muick Marc , Neuner Christian , Tschemmernegg Helfried
Published: August 2016

We present details of the calibration and validation procedure of UltraCam Aerial Camera systems. Results from the laboratory calibration and from validation flights are presented for both, the large format nadir cameras and the oblique cameras as well. Thus in this contribution we show results from the UltraCam Eagle and the UltraCam Falcon, both nadir mapping cameras, and the UltraCam Osprey, our oblique camera system. This sensor offers a mapping grade nadir component together with the four oblique camera heads. The geometric processing after the flight mission is being covered by the UltraMap software product. Thus we present details about the workflow as well. The first part consists of the initial post-processing which combines image information as well as camera parameters derived from the laboratory calibration. The second part, the traditional automated aerial triangulation (AAT) is the step from single images to blocks and enables an additional optimization process. We also present some special features of our software, which are designed to better support the operator to analyze large blocks of aerial images and to judge the quality of the photogrammetric set-up.
CALIBRATION AND STABILITY ANALYSIS OF THE VLP-16 LASER SCANNER
Authors: Glennie C. L. , Kusari A. , Facchin A.
Published: August 2016

We report on a calibration and stability analysis of the Velodyne VLP-16 LiDAR scanner. The sensor is evaluated for long-term stability, geometric calibration and the effect of temperature variations. To generalize the results, three separate VLP-16 sensors were examined. The results and conclusions from the analysis of each of the individual sensors was similar. We found that the VLP-16 showed a consistent level of performance, in terms of range bias and noise level over the tested temperature range from 0–40 °C. A geometric calibration was able to marginally improve the accuracy of the VLP-16 point cloud (by approximately 20%) for a single collection, however the temporal stability of the geometric calibration negated this accuracy improvement. Overall, it was found that there is some long-term walk in the ranging observations from individual lasers within the VLP-16, which likely causes the instability in the determination of geometric calibration parameters. However, despite this range walk, the point cloud delivered from the VLP-16 sensors tested showed an accuracy level within the manufacturer specifications of 3 cm RMSE, with an overall estimated RMSE of range residuals between 22 mm and 27 mm.
INTRODUCTION OF A PHOTOGRAMMETRIC CAMERA SYSTEM FOR RPAS WITH HIGHLY ACCURATE GNSS/IMU INFORMATION FOR STANDARDIZED WORKFLOWS
Authors: Kraft T. , Geßner M. , Meißner H. , Przybilla H. J. , Gerke M.
Published: August 2016

In this paper we present the evaluation of DLR’s modular airborne camera system MACS-Micro for remotely piloted aircraft system (RPAS) with a maximum takeoff weight (MTOW) less than 5kg. The main focus is on standardized calibration and test procedures as well as on standardized photogrammetric workflows as a proof of feasibility for this aerial camera concept. The prototype consists of an industrial grade frame imaging camera and a compact GNSS/IMU solution which are operated by an embedded PC. The camera has been calibrated pre- and post- flight using a three dimensional test field. The validation of the latest prototype is done by a traditional photogrammetric evaluation of an aerial survey using 39 ground control points. The results, concerning geometric and radiometric features of the present system concept as well as the quality of the aero triangulation, fulfill many of the aimed keyspecifications.
NOVEL APPROACH FOR ESTIMATING NITROGEN CONTENT IN PADDY FIELDS USING LOW ALTITUDE REMOTE SENSING SYSTEM
Authors: Saberioon M. M. , Gholizadeh A.
Published: August 2016

Concerns over the use of nitrogen have been increasing due to the high cost of fertilizers and environmental pollutions caused by excess nitrogen application in agricultural fields. Several methods are available to assess the amount of nitrogen in crops, however, they are expensive, time-consuming, inaccurate, and/or require specialists to operate the tools. Researcher recently suggested remote sensing and specifically Low Altitude Remote Sensing (LARS) system of chlorophyll content in crop canopies as a low-cost alternative to estimate plant nitrogen status. The main objective of this study was to develop and test a new Vegetation Index (VI) to determine the status of nitrogen and chlorophyll content in rice leaf by analysing and considering all Visible (Vis) bands. Besides, capability of introduced VI has compared with all known VIs in both Vis and Near Infrared (NIR) bands in canopy scale. To develop the VI, images from 6-pannel leaf colour chart were acquired using Basler Scout scA640-70fc under light-emitting diode lighting, in which principal component analysis was used to retain the lower order principal component to develop a new index called IPCA. A conventional digital camera mounted to an Unmanned Aerial Vehicle (UAV) was also used to acquire images over the rice canopy in Vis bands. Simultaneously, Tetracam agriculture digital camera was employed to acquire rice canopy image in Vis-NIR bands. The results indicated that the proposed index at canopy (r = 0.78) scale could be used as a sensor to determine the status of chlorophyll content consequently for monitoring nitrogen in rice plant through different growth stages. Moreover, results confirmed that a lowcost LARS system would be suited for high spatial and temporal resolution images and data analysis for proper assessment of key nutrients in crop farming in a fast, inexpensive and non-destructive way.
UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS
Authors: Sona Giovanna , Passoni Daniele , Pinto Livio , Pagliari Diana , Masseroni Daniele , Ortuani Bianca , Facchi Arianna
Published: August 2016

New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients). Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field), to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB) and false color (NIR-RG) images, were used.

 The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM) of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation.

 Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.
The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area
Authors: Yeh M. L. , Chou Y. T. , Yang L. S.
Published: August 2016

The efficiency and high mobility of Unmanned Aerial Vehicle (UAV) made them essential to aerial photography assisted survey and mapping. Especially for urban land use and land cover, that they often changes, and need UAVs to obtain new terrain data and the new changes of land use. This study aims to collect image data and three dimensional ground control points in Taichung city area with Unmanned Aerial Vehicle (UAV), general camera and Real-Time Kinematic with positioning accuracy down to centimetre. The study area is an ecological park that has a low topography which support the city as a detention basin. A digital surface model was also built with Agisoft PhotoScan, and there will also be a high resolution orthophotos. There will be two conditions for this study, with or without ground control points and both were discussed and compared for the accuracy level of each of the digital surface models. According to check point deviation estimate, the model without ground control points has an average two-dimension error up to 40 centimeter, altitude error within one meter. The GCP-free RTK-airborne approach produces centimeter-level accuracy with excellent to low risk to the UAS operators. As in the case of the model with ground control points, the accuracy of x, y, z coordinates has gone up 54.62%, 49.07%, and 87.74%, and the accuracy of altitude has improved the most.
A WORKFLOW FOR UAV’s INTEGRATION INTO A GEODESIGN PLATFORM
Authors: Anca P. , Calugaru A. , Alixandroae I. , Nazarie R.
Published: August 2016

This paper presents a workflow for the development of various Geodesign scenarios. The subject is important in the context of identifying patterns and designing solutions for a Smart City with optimized public transportation, efficient buildings, efficient utilities, recreational facilities a.s.o.. The workflow describes the procedures starting with acquiring data in the field, data processing, orthophoto generation, DTM generation, integration into a GIS platform and analyzing for a better support for Geodesign. Esri’s City Engine is used mostly for 3D modeling capabilities that enable the user to obtain 3D realistic models. The workflow uses as inputs information extracted from images acquired using UAVs technologies, namely eBee, existing 2D GIS geodatabases, and a set of CGA rules. The method that we used further, is called procedural modeling, and uses rules in order to extrude buildings, the street network, parcel zoning and side details, based on the initial attributes from the geodatabase. The resulted products are various scenarios for redesigning, for analyzing new exploitation sites. Finally, these scenarios can be published as interactive web scenes for internal, groups or pubic consultation. In this way, problems like the impact of new constructions being build, re-arranging green spaces or changing routes for public transportation, etc. are revealed through impact and visibility analysis or shadowing analysis and are brought to the citizen’s attention. This leads to better decisions.
UAV MONITORING FOR ENVIROMENTAL MANAGEMENT IN GALAPAGOS ISLANDS
Authors: Ballaria D. , Orellana D. , Acostaa E. , Espinoza A. , Morocho V.
Published: August 2016

In the Galapagos Islands, where 97% of the territory is protected and ecosystem dynamics are highly vulnerable, timely and accurate information is key for decision making. An appropriate monitoring system must meet two key features: on one hand, being able to capture information in a systematic and regular basis, and on the other hand, to quickly gather information on demand for specific purposes. The lack of such a system for geographic information limits the ability of Galapagos Islands’ institutions to evaluate and act upon environmental threats such as invasive species spread and vegetation degradation. In this context, the use of UAVs (unmanned aerial vehicles) for capturing georeferenced images is a promising technology for environmental monitoring and management. This paper explores the potential of UAV images for monitoring degradation of littoral vegetation in Puerto Villamil (Isabela Island, Galapagos, Ecuador). Imagery was captured using two camera types: Red Green Blue (RGB) and Infrarred Red Green (NIR). First, vegetation presence was identified through NDVI. Second, object-based classification was carried out for characterization of vegetation vigor. Results demonstrates the feasibility of UAV technology for base-line studies and monitoring on the amount and vigorousness of littoral vegetation in the Galapagos Islands. It is also showed that UAV images are not only useful for visual interpretation and object delineation, but also to timely produce useful thematic information for environmental management.
POTENTIAL OF UAV-BASED LASER SCANNER AND MULTISPECTRAL CAMERA DATA IN BUILDING INSPECTION
Authors: Mader D. , Blaskow R. , Westfeld P. , Weller C.
Published: August 2016

Conventional building inspection of bridges, dams or large constructions in general is rather time consuming and often cost expensive due to traffic closures and the need of special heavy vehicles such as under-bridge inspection units or other large lifting platforms. In consideration that, an unmanned aerial vehicle (UAV) will be more reliable and efficient as well as less expensive and simpler to operate. The utilisation of UAVs as an assisting tool in building inspections is obviously. Furthermore, light-weight special sensors such as infrared and thermal cameras as well as laser scanner are available and predestined for usage on unmanned aircraft systems. Such a flexible low-cost system is realized in the ADFEX project with the goal of time-efficient object exploration, monitoring and damage detection. For this purpose, a fleet of UAVs, equipped with several sensors for navigation, obstacle avoidance and 3D object-data acquisition, has been developed and constructed. This contribution deals with the potential of UAV-based data in building inspection. Therefore, an overview of the ADFEX project, sensor specifications and requirements of building inspections in general are given. On the basis of results achieved in practical studies, the applicability and potential of the UAV system in building inspection will be presented and discussed.
UAS BASED TREE SPECIES IDENTIFICATION USING THE NOVEL FPI BASED HYPERSPECTRAL CAMERAS IN VISIBLE, NIR AND SWIR SPECTRAL RANGES
Authors: Näsi R. , Honkavaara E. , Tuominen S. , Saari H. , Pölönen I. , Hakala T. , Viljanen N. , Soukkamäki J. , Näkki I. , Ojanen H. , Reinikainen J.
Published: August 2016

Unmanned airborne systems (UAS) based remote sensing offers flexible tool for environmental monitoring. Novel lightweight Fabry-Perot interferometer (FPI) based, frame format, hyperspectral imaging in the spectral range from 400 to 1600 nm was used for identifying different species of trees in a forest area. To the best of the authors’ knowledge, this was the first research where stereoscopic, hyperspectral VIS, NIR, SWIR data is collected for tree species identification using UAS. The first results of the analysis based on fusion of two FPI-based hyperspectral imagers and RGB camera showed that the novel FPI hyperspectral technology provided accurate geometric, radiometric and spectral information in a forested scene and is operational for environmental remote sensing applications.
SENSORS FOR LOCATION-BASED AUGMENTED REALITY THE EXAMPLE OF GALILEO AND EGNOS
Authors: Pagani Alain , Henriques José , Stricker Didier
Published: August 2016

Augmented Reality has long been approached from the point of view of Computer Vision and Image Analysis only. However, much more sensors can be used, in particular for location-based Augmented Reality scenarios. This paper reviews the various sensors that can be used for location-based Augmented Reality. It then presents and discusses several examples of the usage of Galileo and EGNOS in conjonction with Augmented Reality.
LBS AUGMENTED REALITY ASSISTIVE SYSTEM FOR UTILITIES INFRASTRUCTURE MANAGEMENT THROUGH GALILEO AND EGNOS
Authors: Stylianidis E. , Valaria E. , Smagas K. , Pagani A. , Henriques J. , Garca A. , Jimeno E. , Carrillo I. , Patias P. , Georgiadis C. , Kounoudes A. , Michail K.
Published: August 2016

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.
SYNTHETIC APERTURE RADAR (SAR) BASED CLASSIFIERS FOR LAND APPLICATIONS IN GERMANY
Authors: Suresh G. , Gehrke R. , Wiatr T. , Hovenbitzer M.
Published: August 2016

Land cover information is essential for urban planning and for land cover change monitoring. This paper presents an overview of the work conducted at the Federal Agency for Cartography and Geodesy (BKG) with respect to Synthetic Aperture Radar (SAR) based land cover classification. Two land cover classification approaches using SAR images are reported in this paper. The first method involves a rule-based classification using only SAR backscatter intensity while the other method involves supervised classification of a polarimetric composite of the same SAR image. The LBM-DE has been used for training and validation of the SAR classification results. Images acquired from the Sentinel-1a satellite are used for classification and the results have been reported and discussed. The availability of Sentinel-1a images that are weather and daylight independent allows for the creation of a land cover classification system that can be updated and validated periodically, and hence, be used to assist other land cover classification systems that use optical data. With the availability of Sentinel-2 data, land cover classification combining Sentinel-1a and Sentinel-2 images present a path for the future.
COMMERCIAL OFF THE SHELF GROUND CONTROL SUPPORTS CALIBRATION AND CONFLATION FROM GROUND TO SPACE BASED SENSORS
Authors: Danielová M. , Hummel P.
Published: August 2016

The need for rapid deployment of aerial and satellite imagery in support of GIS and engineering integration projects require new sources of geodetic control to ensure the accuracy for geospatial projects. In the past, teams of surveyors would need to deploy to project areas to provide targeted or photo identifiable points that are used to provide data for orthorecificaion, QA/QC and calibration for multi-platform sensors. The challenge of integrating street view, UAS, airborne and Space based sensors to produce the common operational picture requires control to tie multiple sources together. Today commercial off the shelf delivery of existing photo identifiable control is increasing the speed of deployment of this data without having to revisit sites over and over again. The presentation will discuss the processes developed by CompassData to build a global library of 40,000 control points available today. International Organization for Standardization (ISO) based processes and initiatives ensure consistent quality of survey data, photo identifiable features selected and meta data to support photogrammetrist, engineers and GIS professionals to quickly deliver projects with better accuracy.
MULTI SENSOR AND PLATFORMS SETUPS FOR VARIOUS AIRBORNE APPLICATIONS
Authors: Kemper G. , Vasel R.
Published: August 2016

To combine various sensors to get a system for specific use became popular within the last 10 years. Metric mid format cameras meanwhile reach the 100 MPix and entered the mapping market to compete with the big format sensors. Beside that also other sensors as SLR Cameras provide high resolution and enter the aerial surveying market for orthophoto production or monitoring applications. Flexibility, purchase-costs, size and weight are common aspects to design multi-sensor systems. Some sensors are useful for mapping while others are part of environmental monitoring systems. Beside classical surveying aircrafts also UL Airplanes, Para/Trikes or UAVs make use of multi sensor systems. Many of them are customer specific while other already are frequently used in the market. This paper aims to show some setup, their application, what are the results and what are the pros and cons of them are.
DEVELOPING THE STABILIZED MAPPING SYSTEM FOR THE GYROCOPTER – REPORT FROM THE FIRST TESTS
Authors: Kolecki J. , Prochaska M. , Kurczyński Z. , Piątek P. , Baranowski J.
Published: August 2016

The LiDAR mapping carried out using gyrocopters provides a relatively cheap alternative for traditional mapping involving airplanes. The costs of the fuel and the overall maintenance are much lower when compared to planes. At the same time the flight kinematics of the gyrocopter makes it an ideal vehicle for corridor mapping. However a limited payload and a strongly limited space prevent using stabilized platforms dedicated for aerial photogrammetry. As the proper stabilization of the laser scanner during the flight is crucial in order to keep the desirable quality of the LiDAR data, it was decided to develop the prototype of the stabilized, ultra-light mapping platform that can meet the restricted requirements of the gyrocopter. The paper starts with the brief discussion of the legal and practical aspects of the LiDAR data quality, dealing mostly with the influence of the flight imperfections on the point pattern and point density. Afterwards the mapping system prototype is characterized, taking into account three main components: stabilized platform, sensors and control. Subsequently first in-flight tests are described. Though the data are still not perfect mostly due to vibrations, the stabilization provides a substantial improvement of their geometry, reducing both roll and pitch deflections.
DE-STRIPING FOR TDICCD REMOTE SENSING IMAGE BASED ON STATISTICAL FEATURES OF HISTOGRAM
Authors: Gao Hui-ting , Liu Wei , He Hong-yan , Zhang Bing-xian , Jiang Cheng
Published: August 2016

Aim to striping noise brought by non-uniform response of remote sensing TDI CCD, a novel de-striping method based on statistical features of image histogram is put forward. By analysing the distribution of histograms,the centroid of histogram is selected to be an eigenvalue representing uniformity of ground objects,histogrammic centroid of whole image and each pixels are calculated first,the differences between them are regard as rough correction coefficients, then in order to avoid the sensitivity caused by single parameter and considering the strong continuity and pertinence of ground objects between two adjacent pixels,correlation coefficient of the histograms is introduces to reflect the similarities between them,fine correction coefficient is obtained by searching around the rough correction coefficient,additionally,in view of the influence of bright cloud on histogram,an automatic cloud detection based on multi-feature including grey level,texture,fractal dimension and edge is used to pre-process image.Two 0-level panchromatic images of SJ-9A satellite with obvious strip noise are processed by proposed method to evaluate the performance, results show that the visual quality of images are improved because the strip noise is entirely removed,we quantitatively analyse the result by calculating the non-uniformity ,which has reached about 1% and is better than histogram matching method.
ANALYSIS AND CORRECTION OF SYSTEMATIC HEIGHT MODEL ERRORS
Authors: Jacobsen K.
Published: August 2016

The geometry of digital height models (DHM) determined with optical satellite stereo combinations depends upon the image orientation, influenced by the satellite camera, the system calibration and attitude registration. As standard these days the image orientation is available in form of rational polynomial coefficients (RPC). Usually a bias correction of the RPC based on ground control points is required. In most cases the bias correction requires affine transformation, sometimes only shifts, in image or object space. For some satellites and some cases, as caused by small base length, such an image orientation does not lead to the possible accuracy of height models. As reported e.g. by Yong-hua et al. 2015 and Zhang et al. 2015, especially the Chinese stereo satellite ZiYuan-3 (ZY-3) has a limited calibration accuracy and just an attitude recording of 4 Hz which may not be satisfying. Zhang et al. 2015 tried to improve the attitude based on the color sensor bands of ZY-3, but the color images are not always available as also detailed satellite orientation information. There is a tendency of systematic deformation at a Pléiades tri-stereo combination with small base length. The small base length enlarges small systematic errors to object space. But also in some other satellite stereo combinations systematic height model errors have been detected. The largest influence is the not satisfying leveling of height models, but also low frequency height deformations can be seen.

 A tilt of the DHM by theory can be eliminated by ground control points (GCP), but often the GCP accuracy and distribution is not optimal, not allowing a correct leveling of the height model. In addition a model deformation at GCP locations may lead to not optimal DHM leveling. Supported by reference height models better accuracy has been reached. As reference height model the Shuttle Radar Topography Mission (SRTM) digital surface model (DSM) or the new AW3D30 DSM, based on ALOS PRISM images, are satisfying. They allow the leveling and correction of low frequency height errors and lead to satisfying correction of the DSM based on optical satellite images.

 The potential of DHM generation, influence of systematic model deformation and possibilities of improvement has been investigated.
AIRBORNE LINEAR ARRAY IMAGE GEOMETRIC RECTIFICATION METHOD BASED ON UNEQUAL SEGMENTATION
Authors: Li J. M. , Li C. R. , Zhou M , Hu J. , Yang C. M.
Published: August 2016

As the linear array sensor such as multispectral and hyperspectral sensor has great potential in disaster monitoring and geological survey, the quality of the image geometric rectification should be guaranteed. Different from the geometric rectification of airborne planar array images or multi linear array images, exterior orientation elements need to be determined for each scan line of single linear array images. Internal distortion persists after applying GPS/IMU data directly to geometrical rectification. Straight lines may be curving and jagged. Straight line feature -based geometrical rectification algorithm was applied to solve this problem, whereby the exterior orientation elements were fitted by piecewise polynomial and evaluated with the straight line feature as constraint. However, atmospheric turbulence during the flight is unstable, equal piecewise can hardly provide good fitting, resulting in limited precision improvement of geometric rectification or, in a worse case, the iteration cannot converge. To solve this problem, drawing on dynamic programming ideas, unequal segmentation of line feature-based geometric rectification method is developed. The angle elements fitting error is minimized to determine the optimum boundary. Then the exterior orientation elements of each segment are fitted and evaluated with the straight line feature as constraint. The result indicates that the algorithm is effective in improving the precision of geometric rectification.
A METHOD FOR SELF-CALIBRATION IN SATELLITE WITH HIGH PRECISION OF SPACE LINEAR ARRAY CAMERA
Authors: Liu Wei , Qian Fangming , Miao Yuzhe , Wang Rongjian
Published: August 2016

At present, the on-orbit calibration of the geometric parameters of a space surveying camera is usually processed by data from a ground calibration field after capturing the images. The entire process is very complicated and lengthy and cannot monitor and calibrate the geometric parameters in real time. On the basis of a large number of on-orbit calibrations, we found that owing to the influence of many factors, e.g., weather, it is often difficult to capture images of the ground calibration field. Thus, regular calibration using field data cannot be ensured. This article proposes a real time self-calibration method for a space linear array camera on a satellite using the optical auto collimation principle. A collimating light source and small matrix array CCD devices are installed inside the load system of the satellite; these use the same light path as the linear array camera. We can extract the location changes of the cross marks in the matrix array CCD to determine the real-time variations in the focal length and angle parameters of the linear array camera. The on-orbit status of the camera is rapidly obtained using this method. On one hand, the camera’s change regulation can be mastered accurately and the camera’s attitude can be adjusted in a timely manner to ensure optimal photography; in contrast, self-calibration of the camera aboard the satellite can be realized quickly, which improves the efficiency and reliability of photogrammetric processing.