Showing papers in "ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences in 2014"

Generation of High Resolution Global DSM from ALOS PRISM

Abstract: Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), one of onboard sensors carried on the Advanced Land Observing Satellite (ALOS), was designed to generate worldwide topographic data with its optical stereoscopic observation. The sensor consists of three independent panchromatic radiometers for viewing forward, nadir, and backward in 2.5 m ground resolution producing a triplet stereoscopic image along its track. The sensor had observed huge amount of stereo images all over the world during the mission life of the satellite from 2006 through 2011. We have semi-automatically processed Digital Surface Model (DSM) data with the image archives in some limited areas. The height accuracy of the dataset was estimated at less than 5 m (rms) from the evaluation with ground control points (GCPs) or reference DSMs derived from the Light Detection and Ranging (LiDAR). Then, we decided to process the global DSM datasets from all available archives of PRISM stereo images by the end of March 2016. This paper briefly reports on the latest processing algorithms for the global DSM datasets as well as their preliminary results on some test sites. The accuracies and error characteristics of datasets are analyzed and discussed on various fields by the comparison with existing global datasets such as Ice, Cloud, and land Elevation Satellite (ICESat) data and Shuttle Radar Topography Mission (SRTM) data, as well as the GCPs and the reference airborne LiDAR/DSM.

Accuracy of typical photogrammetric networks in cultural heritage 3d modeling projects

Abstract: . The easy generation of 3D geometries (point clouds or polygonal models) with fully automated image-based methods poses nontrivial problems on how to check a posteriori the quality of the achieved results. Clear statements and procedures on how to plan the camera network, execute the survey and use automatic tools to achieve the prefixed requirements are still an open issue. Although such issues had been discussed and solved some years ago, the importance of camera network geometry is today often underestimated or neglected in the cultural heritage field. In this paper different camera network geometries, with normal and convergent images, are analyzed and the accuracy of the produced results are compared to ground truth measurements.

Oblique multi-camera systems - orientation and dense matching issues

Abstract: The use of oblique imagery has become a standard for many civil and mapping applications, thanks to the development of airborne digital multi-camera systems, as proposed by many companies (Blomoblique, IGI, Leica, Midas, Pictometry, Vexcel/Microsoft, VisionMap, etc.). The indisputable virtue of oblique photography lies in its simplicity of interpretation and understanding for inexperienced users allowing their use of oblique images in very different applications, such as building detection and reconstruction, building structural damage classification, road land updating and administration services, etc. The paper reports an overview of the actual oblique commercial systems and presents a workflow for the automated orientation and dense matching of large image blocks. Perspectives, potentialities, pitfalls and suggestions for achieving satisfactory results are given. Tests performed on two datasets acquired with two multi-camera systems over urban areas are also reported.

3D Modelling of interior spaces : learning the language of indoor architecture

Abstract: 3D models of indoor environments are important in many applications, but they usually exist only for newly constructed buildings. Automated approaches to modelling indoor environments from imagery and/or point clouds can make the process easier, faster and cheaper. We present an approach to 3D indoor modelling based on a shape grammar. We demonstrate that interior spaces can be modelled by iteratively placing, connecting and merging cuboid shapes. We also show that the parameters and sequence of grammar rules can be learned automatically from a point cloud. Experiments with simulated and real point clouds show promising results, and indicate the potential of the method in 3D modelling of large indoor environments.

Photogrammetry applied to Problematic artefacts

Abstract: . The process of creating 3D accurate and faithful textured models from 2D images has been a major endeavor within the cultural heritage field. This field has general requirements, such as accuracy, portability and costs, that are often integrated by more specific needs such as the integration of color information. The aim of this paper is to show how photogrammetry can be a valid and reliable techniques for creating 3D models of museum artefacts even in case of objects with materials featuring difficult optical properties (absorptivity, reflectivity, scattering), challenging texture and complex shape/geometry. The main objective is to establish some core specifications for data acquisition and modeling, in order to guarantee the scientific quality of data and the interoperability of 3D models with the archaeologists and conservators. All these aspects are taken into consideration and presented with three study cases (two statues – one made of marble and one made of bronze – and a restored ceramic jug). The established, comprehensive and accessible pipeline for the creation of complex artefacts 3D models in the field of cultural heritage is presented and discussed.

Automatic Single Tree Detection in Plantations using UAV-based Photogrammetric Point clouds

Abstract: For reasons of documentation, management and certification there is a high interest in efficient inventories of palm plantations on the single plant level. Recent developments in unmanned aerial vehicle (UAV) technology facilitate spatial and temporal flexible acquisition of high resolution 3D data. Common single tree detection approaches are based on Very High Resolution (VHR) satellite or Airborne Laser Scanning (ALS) data. However, VHR data is often limited to clouds and does commonly not allow for height measurements. VHR and in particualar ALS data are characterized by high relatively high acquisition costs. Sperlich et al. (2013) already demonstrated the high potential of UAV-based photogrammetric point clouds for single tree detection using pouring algorithms. This approach was adjusted and improved for an application on palm plantation. The 9.4ha test site on Tarawa, Kiribati, comprised densely scattered growing palms, as well as abundant undergrowth and trees. Using a standard consumer grade camera mounted on an octocopter two flight campaigns at 70m and 100m altitude were performed to evaluate the effect Ground Sampling Distance (GSD) and image overlap. To avoid comission errors and improve the terrain interpolation the point clouds were classified based on the geometric characteristics of the classes, i.e. (1) palm, (2) other vegetation (3) and ground. The mapping accuracy amounts for 86.1 % for the entire study area and 98.2 % for dense growing palm stands. We conclude that this flexible and automatic approach has high capabilities for operational use.

A comparison study of different kernel functions for svm-based classification of multi-temporal polarimetry sar data

Abstract: . In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

A comparison of multi-view 3d reconstruction of a rock wall using several cameras and a laser scanner

Abstract: . This work presents a comparative study between multi-view 3D reconstruction using various digital cameras and a terrestrial laser scanner (TLS). Five different digital cameras were used in order to estimate the limits related to the camera type and to establish the minimum camera requirements to obtain comparable results to the ones of the TLS. The cameras used for this study range from commercial grade to professional grade and included a GoPro Hero 1080 (5 Mp), iPhone 4S (8 Mp), Panasonic Lumix LX5 (9.5 Mp), Panasonic Lumix ZS20 (14.1 Mp) and Canon EOS 7D (18 Mp). The TLS used for this work was a FARO Focus 3D laser scanner with a range accuracy of ±2 mm. The study area is a small rock wall of about 6 m height and 20 m length. The wall is partly smooth with some evident geological features, such as non-persistent joints and sharp edges. Eight control points were placed on the wall and their coordinates were measured by using a total station. These coordinates were then used to georeference all models. A similar number of images was acquired from a distance of between approximately 5 to 10 m, depending on field of view of each camera. The commercial software package PhotoScan was used to process the images, georeference and scale the models, and to generate the dense point clouds. Finally, the open-source package CloudCompare was used to assess the accuracy of the multi-view results. Each point cloud obtained from a specific camera was compared to the point cloud obtained with the TLS. The latter is taken as ground truth. The result is a coloured point cloud for each camera showing the deviation in relation to the TLS data. The main goal of this study is to quantify the quality of the multi-view 3D reconstruction results obtained with various cameras as objectively as possible and to evaluate its applicability to geotechnical problems.

Benchmarking High Density Image Matching for Oblique Airborne Imagery

Abstract: . Both, improvements in camera technology and new pixel-wise matching approaches triggered the further development of software tools for image based 3D reconstruction. Meanwhile research groups as well as commercial vendors provide photogrammetric software to generate dense, reliable and accurate 3D point clouds and Digital Surface Models (DSM) from highly overlapping aerial images. In order to evaluate the potential of these algorithms in view of the ongoing software developments, a suitable test bed is provided by the ISPRS/EuroSDR initiative Benchmark on High Density Image Matching for DSM Computation. This paper discusses the proposed test scenario to investigate the potential of dense matching approaches for 3D data capture from oblique airborne imagery. For this purpose, an oblique aerial image block captured at a GSD of 6 cm in the west of Zurich by a Leica RCD30 Oblique Penta camera is used. Within this paper, the potential test scenario is demonstrated using matching results from two software packages, Agisoft PhotoScan and SURE from University of Stuttgart. As oblique images are frequently used for data capture at building facades, 3D point clouds are mainly investigated at such areas. Reference data from terrestrial laser scanning is used to evaluate data quality from dense image matching for several facade patches with respect to accuracy, density and reliability.

Crop Type Classification Using Vegetation Indices of RapidEye Imagery

Abstract: . Cutting-edge remote sensing technology has a significant role for managing the natural resources as well as the any other applications about the earth observation. Crop monitoring is the one of these applications since remote sensing provides us accurate, up-to-date and cost-effective information about the crop types at the different temporal and spatial resolution. In this study, the potential use of three different vegetation indices of RapidEye imagery on crop type classification as well as the effect of each indices on classification accuracy were investigated. The Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) are the three vegetation indices used in this study since all of these incorporated the near-infrared (NIR) band. RapidEye imagery is highly demanded and preferred for agricultural and forestry applications since it has red-edge and NIR bands. The study area is located in Aegean region of Turkey. Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Original bands of RapidEye imagery were excluded and classification was performed with only three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 87, 46 % was obtained using three vegetation indices. This obtained classification accuracy is higher than the classification accuracy of any dual-combination of these vegetation indices. Results demonstrate that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the RapidEye imagery can get satisfactory results of classification accuracy without original bands.

Crop height determination with UAS point clouds

Abstract: . The accurate determination of the height of agricultural crops helps to predict yield, biomass etc. These relationships are of great importance not only for crop production but also in grassland management, because the available biomass and food quality are valuable information. However there is no cost efficient and automatic system for the determination of the crop height available. 3D-point clouds generated from high resolution UAS imagery offer a new alternative. Two different approaches for crop height determination are presented. The "difference method" were the canopy height is determined by taking the difference between a current UAS-surface model and an existing digital terrain model (DTM) is the most suited and most accurate method. In situ measurements, vegetation indices and yield observations correlate well with the determined UAS crop heights.

Accuracy of cultural heritage 3D models by RPAS and terrestrial photogrammetry

Abstract: . The combined use of high-resolution digital images taken from ground as well as from RPAS (Remotely Piloted Aircraft Systems) have significantly increased the potential of close range digital photogrammetry applications in Cultural Heritage surveying and modeling. It is in fact possible, thanks to SfM (Structure from Motion), to simultaneously process great numbers of aerial and terrestrial images for the production of a dense point cloud of an object. In order to analyze the accuracy of results, we started numerous tests based on the comparison between 3D digital models of a monumental complex realized by the integration of aerial and terrestrial photogrammetry and an accurate TLS (Terrestrial Laser Scanner) reference model of the same object. A lot of digital images of a renaissance castle, assumed as test site, have been taken both by ground level and by RPAS at different distances and flight altitudes and with different flight patterns. As first step of the experimentation, the images were previously processed with Agisoft PhotoScan, one of the most popular photogrammetric software. The comparison between the photogrammetric DSM of the monument and a TLS reference one was carried out by evaluating the average deviation between the points belonging to the two entities, both globally and locally, on individual facades and architectural elements (sections and particular). In this paper the results of the first test are presented. A good agreement between photogrammetric and TLS digital models of the castle is pointed out.

Comparisons between different interpolation techniques

Abstract: Digital terrain models are key tools in land analysis and management as they are directly employable in GIS systems and other specific applications like hydraulic modelling, geotechnical analyses, road planning, telecommunication, and many others. TIN generation, from different kind of measurement techniques, is ruled by specific regulations. Interpolation techniques to compute a regular grid from a TIN, are, instead, still lacking in specific regulations: a unitary and shared methodology has not already been made compulsory in order to be used in cartographic production while generating digital models. Such ambiguity obviously involves non univocal results and can affect precision, which can lead to divergent analyses on the same territory. In the present study different algorithms will be analysed in order to spot an optimal interpolation methodology. The availability of the recent digital model produced by the Regione Piemonte with airborne LIDAR and the presence of sections of testing realized with higher resolutions and the presence of independent digital models on the same territory allow to set a series of analysis with consequent determination of the best methodologies of interpolation. The analysis of the residuals on the test sites allows to calculate the descriptive statistics of the computed values: all the algorithms have furnished interesting results; all the more interesting, notably for dense models, the IDW (Inverse Distance Weighing) algorithm results to give best results in this study case. Moreover, a comparative analysis was carried out by interpolating data at different input point density, with the purpose of highlighting thresholds in input density that may influence the quality reduction of the final output in the interpolation phase.

Spatio-temporal assessment of land use/ land cover dynamics and urban heat island of jaipur city using satellite data

Abstract: . Urban Heat Island (UHI) refers to the phenomena of higher surface temperature occurring in urban areas as compared to the surrounding countryside attributable to urbanization. Spatio-temporal changes in UHI can be quantified through Land Surface Temperature (LST) derived from satellite imageries. Spatial variations in LST occur due to complexity of land surface – combination of impervious surface materials, vegetation, exposed soils as well as water surfaces. Jaipur city has observed rapid urbanization over the last decade. Due to rising population pressure the city has expanded considerably in areal extent and has also observed substantial land use/land cover (LULC) changes. The paper aims to determine changes in the LST and UHI phenomena for Jaipur city over the period from 2000 to 2011 and analyzes the spatial distribution and temporal variation of LST in context of changes in LULC. Landsat 7 ETM+ (2000) and Landsat 5 TM (2011) images of summer season have been used. Results reveal that Jaipur city has witnessed considerable growth in built up area at the cost of greener patches over the last decade, which has had clear impact on variation in LST. There has been an average rise of 2.99 °C in overall summer temperature. New suburbs of the city record 2° to 4 °C increase in LST. LST change is inversely related to change in vegetation cover and positively related to extent of built up area. The study concludes that UHI of Jaipur city has intensified and extended over new areas.

A new bare-soil index for rapid mapping developing areas using LANDSAT 8 data

Abstract: . One of the most basic classification tasks is to distinguish bare-soil areas from urban region. Bare-soil plays an important role in the ecosystem. It could be the reason of dust storms and the indicator of urban expansion. It is also important to monitor the bare-soil areas, but there was no good idea to automatically extraction bare-soil areas using existing method. In this work, a new bareness index (BI) has been developed and applied to map developing region in Pearl River Delta using Landsat OLI/TIRS data in 2013. The BI based on the logical combination of the Tasseled Cap transformation (TCB) and Normalized Difference Bareness Index (NDBaI). Results show that the BI not only has a good effect on the enhancement of bare soil information, but also on the inhibition of the background information, and improve the accuracy of detection. The results of this study could be of scientific and practical merits in regional remote sensing monitoring and improve the accuracy of land use classification.

Automatic Building Extraction From LIDAR Data Covering Complex Urban Scenes

Abstract: This paper presents a new method for segmentation of LIDAR point cloud data for automatic building extraction. Using the ground height from a DEM (Digital Elevation Model), the non-ground points (mainly buildings and trees) are separated from the ground points. Points on walls are removed from the set of non-ground points by applying the following two approaches: If a plane fitted at a point and its neighbourhood is perpendicular to a fictitious horizontal plane, then this point is designated as a wall point. When LIDAR points are projected on a dense grid, points within a narrow area close to an imaginary vertical line on the wall should fall into the same grid cell. If three or more points fall into the same cell, then the intermediate points are removed as wall points. The remaining non-ground points are then divided into clusters based on height and local neighbourhood. One or more clusters are initialised based on the maximum height of the points and then each cluster is extended by applying height and neighbourhood constraints. Planar roof segments are extracted from each cluster of points following a region-growing technique. Planes are initialised using coplanar points as seed points and then grown using plane compatibility tests. If the estimated height of a point is similar to its LIDAR generated height, or if its normal distance to a plane is within a predefined limit, then the point is added to the plane. Once all the planar segments are extracted, the common points between the neghbouring planes are assigned to the appropriate planes based on the plane intersection line, locality and the angle between the normal at a common point and the corresponding plane. A rule-based procedure is applied to remove tree planes which are small in size and randomly oriented. The neighbouring planes are then merged to obtain individual building boundaries, which are regularised based on long line segments. Experimental results on ISPRS benchmark data sets show that the proposed method offers higher building detection and roof plane extraction rates than many existing methods, especially in complex urban scenes.

Evaluation of feature-based methods for automated network orientation

Abstract: . Every day new tools and algorithms for automated image processing and 3D reconstruction purposes become available, giving the possibility to process large networks of unoriented and markerless images, delivering sparse 3D point clouds at reasonable processing time. In this paper we evaluate some feature-based methods used to automatically extract the tie points necessary for calibration and orientation procedures, in order to better understand their performances for 3D reconstruction purposes. The performed tests – based on the analysis of the SIFT algorithm and its most used variants – processed some datasets and analysed various interesting parameters and outcomes (e.g. number of oriented cameras, average rays per 3D points, average intersection angles per 3D points, theoretical precision of the computed 3D object coordinates, etc.).

Landform monitoring in active volcano by uav and sfm-mvs technique

Abstract: Nishinoshima volcano in Ogasawara Islands has erupted since November, 2013. This volcanic eruption formed and enlarged a new island, and fused the new island with the old Nishinoshima Island. We performed automated aerial photographing using an Unmanned Aerial Vehicle (UAV) over the joined Nishinoshima Island on March 22 and July 4, 2014. We produced ortho-mosaic photos and digital elevation model (DEM) data by new photogrammetry software with computer vision technique, i.e. Structure from Motion (SfM) for estimating the photographic position of the camera and Multi-view Stereo (MVS) for generating the 3-D model. We also estimated the area and volume of the new island via analysis of ortho-mosaic photo and DEM data. Transition of volume estimated from the UAV photographing and other photographing shows the volcanic activity still keeps from initial level. The ortho-mosaic photos and DEM data were utilized to create an aerial photo interpretation map and a 3-D map. These operations revealed new knowledge and problems to be solved on the photographing and analysis using UAV and new techniques as this was first case in some respects.

Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

Abstract: . Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

Automatic building detection based on supervised classification using high resolution google earth images

Abstract: . This paper presents a novel approach to detect the buildings by automization of the training area collecting stage for supervised classification. The method based on the fact that a 3d building structure should cast a shadow under suitable imaging conditions. Therefore, the methodology begins with the detection and masking out the shadow areas using luminance component of the LAB color space, which indicates the lightness of the image, and a novel double thresholding technique. Further, the training areas for supervised classification are selected by automatically determining a buffer zone on each building whose shadow is detected by using the shadow shape and the sun illumination direction. Thereafter, by calculating the statistic values of each buffer zone which is collected from the building areas the Improved Parallelepiped Supervised Classification is executed to detect the buildings. Standard deviation thresholding applied to the Parallelepiped classification method to improve its accuracy. Finally, simple morphological operations conducted for releasing the noises and increasing the accuracy of the results. The experiments were performed on set of high resolution Google Earth images. The performance of the proposed approach was assessed by comparing the results of the proposed approach with the reference data by using well-known quality measurements (Precision, Recall and F1-score) to evaluate the pixel-based and object-based performances of the proposed approach. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.4 % and 853 % overall pixel-based and object-based precision performances, respectively.

Comparision of photogrammetric point clouds with bim building elements for construction progress monitoring

Abstract: For construction progress monitoring a planned stat e of the construction at a certain time (as-planed) has to be compared to the actual state (as-built). The as-planed state is derived fr om a building information model (BIM), which contains the geometry of the building and the construction schedule. In this paper we int roduce an approach for the generation of an as-buil t point cloud by photogrammetry. It is regarded that that images on a construction c annot be taken from everywhere it seems to be neces sary. Because of this we use a combination of structure from motion process togeth er with control points to create a scaled point clo ud in a consistent coordinate system. Subsequently this point cloud is used for a n as-built ‐ as-planed comparison. For that voxels of an octree are marked as occupied, free or unknown by raycasting based on th e triangulated points and the camera positions. Thi s allows to identify not existing building parts. For the verification of the existen ce of building parts a second test based on the poi nts in front and behind the as-planed model planes is performed. The proposed procedure is tested based on an inner city construction site u nder real conditions.

A voxel-based technique to estimate the volume of trees from terrestrial laser scanner data

Abstract: . The precise determination of the volume of standing trees is very important for ecological and economical considerations in forestry. If terrestrial laser scanner data are available, a simple approach for volume determination is given by allocating points into a voxel structure and subsequently counting the filled voxels. Generally, this method will overestimate the volume. The paper presents an improved algorithm to estimate the wood volume of trees using a voxel-based method which will correct for the overestimation. After voxel space transformation, each voxel which contains points is reduced to the volume of its surrounding bounding box. In a next step, occluded (inner stem) voxels are identified by a neighbourhood analysis sweeping in the X and Y direction of each filled voxel. Finally, the wood volume of the tree is composed by the sum of the bounding box volumes of the outer voxels and the volume of all occluded inner voxels. Scan data sets from several young Norway maple trees (Acer platanoides) were used to analyse the algorithm. Therefore, the scanned trees as well as their representing point clouds were separated in different components (stem, branches) to make a meaningful comparison. Two reference measurements were performed for validation: A direct wood volume measurement by placing the tree components into a water tank, and a frustum calculation of small trunk segments by measuring the radii along the trunk. Overall, the results show slightly underestimated volumes (–0.3% for a probe of 13 trees) with a RMSE of 11.6% for the individual tree volume calculated with the new approach.

UAV-based photogrammetry: monitoring of a building zone

Abstract: . The use of small-size unmanned aerial vehicles (UAV) for civil applications in many different fields such as archaeology, disaster monitoring, aerial surveying or mapping has significantly increased in recent years. The high flexibility and the low cost per acquired information compared to classical systems – terrestrial or aerial – offer a high variety of different applications. This paper addresses the photogrammetric analysis of a monitoring project and gives an insight into the potential of UAV using low cost sensors and present-day processing software. The area of interest is the "zero:e-park", a building zone of zero emission housing in Hannover, Germany, that we monitored in three different epochs over a period of five months. We show that we can derive three dimensional information with an accuracy of a few centimetres. Changes during the epochs, also small ones like the dismantling of scaffolding can be detected. We also depict the limitations of the DEM generation approach which occur at sharp edges and height jumps as well as repetitive structure. Additionally, we compare two different commercial software packages which reveals that some systematic errors still remain in the results.

Evaluation of partially overlapping 3d point cloud's registration by using icp variant and cloudcompare

Abstract: Terrestrial Laser Scanners (TLS) are used to get dense point samples of large object’s surface. TLS is new and efficient method to digitize large object or scene. The collected point samples come into different formats and coordinates. Different scans are required to scan large object such as heritage site. Point cloud registration is considered as important task to bring different scans into whole 3D model in one coordinate system. Point clouds can be registered by using one of the three ways or combination of them, Target based, feature extraction, point cloud based. For the present study we have gone through Point Cloud Based registration approach. We have collected partially overlapped 3D Point Cloud data of Department of Computer Science & IT (DCSIT) building located in Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. To get the complete point cloud information of the building we have taken 12 scans, 4 scans for exterior and 8 scans for interior facade data collection. There are various algorithms available in literature, but Iterative Closest Point (ICP) is most dominant algorithms. The various researchers have developed variants of ICP for better registration process. The ICP point cloud registration algorithm is based on the search of pairs of nearest points in a two adjacent scans and calculates the transformation parameters between them, it provides advantage that no artificial target is required for registration process. We studied and implemented three variants Brute Force, KDTree, Partial Matching of ICP algorithm in MATLAB. The result shows that the implemented version of ICP algorithm with its variants gives better result with speed and accuracy of registration as compared with CloudCompare Open Source software.

A Novel 3D Building Damage Detection Method Using Multiple Overlapping UAV Images

Abstract: . In this paper, a novel approach is presented that applies multiple overlapping UAV imagesto building damage detection. Traditional building damage detection method focus on 2D changes detection (i.e., those only in image appearance), whereas the 2D information delivered by the images is often not sufficient and accurate when dealing with building damage detection. Therefore the detection of building damage in 3D feature of scenes is desired. The key idea of 3D building damage detection is the 3D Change Detection using 3D point cloud obtained from aerial images through Structure from motion (SFM) techniques. The approach of building damage detection discussed in this paper not only uses the height changes of 3D feature of scene but also utilizes the image's shape and texture feature. Therefore, this method fully combines the 2D and 3D information of the real world to detect the building damage. The results, tested through field study, demonstrate that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and suited well for rapid damage assessment after natural disasters.

Kinect Fusion improvement using depth camera calibration

Abstract: . Scene's 3D modelling, gesture recognition and motion tracking are fields in rapid and continuous development which have caused growing demand on interactivity in video-game and e-entertainment market. Starting from the idea of creating a sensor that allows users to play without having to hold any remote controller, the Microsoft Kinect device was created. The Kinect has always attract researchers in different fields, from robotics to Computer Vision (CV) and biomedical engineering as well as third-party communities that have released several Software Development Kit (SDK) versions for Kinect in order to use it not only as a game device but as measurement system. Microsoft Kinect Fusion control libraries (firstly released in March 2013) allow using the device as a 3D scanning and produce meshed polygonal of a static scene just moving the Kinect around. A drawback of this sensor is the geometric quality of the delivered data and the low repeatability. For this reason the authors carried out some investigation in order to evaluate the accuracy and repeatability of the depth measured delivered by the Kinect. The paper will present a throughout calibration analysis of the Kinect imaging sensor, with the aim of establishing the accuracy and precision of the delivered information: a straightforward calibration of the depth sensor in presented and then the 3D data are correct accordingly. Integrating the depth correction algorithm and correcting the IR camera interior and exterior orientation parameters, the Fusion Libraries are corrected and a new reconstruction software is created to produce more accurate models.

Dynamics and forecasting of population growth and urban expansion in Srinagar City – A Geospatial Approach

Abstract: The urban areas of developing countries are densely populated and need the use of sophisticated monitoring systems, such as remote sensing and geographical information systems (GIS). The urban sprawl of a city is best understood by studying the dynamics of LULC change which can be easily generated by using sequential satellite images, required for the prediction of urban growth. Multivariate statistical techniques and regression models have been used to establish the relationship between the urban growth and its causative factors and for forecast of the population growth and urban expansion. In Srinagar city, one of the fastest growing metropolitan cities situated in Jammu and Kashmir State of India, sprawl is taking its toll on the natural resources at an alarming pace. The present study was carried over a period of 40 years (1971–2011), to understand the dynamics of spatial and temporal variability of urban sprawl. The results reveal that built-up area has increased by 585.08% while as the population has increased by 214.75%. The forecast showed an increase of 246.84 km 2 in built-up area which exceeds the overall carrying capacity of the city. The most common conversions were also evaluated.

Development and Comparison of Open Source based Web GIS Frameworks on WAMP and Apache Tomcat Web Servers

Abstract: Geographic Information System (GIS) is a tool used for capture, storage, manipulation, query and presentation of spatial data that have applicability in diverse fields. Web GIS has put GIS on Web, that made it available to common public which was earlier used by few elite users. In the present paper, development of Web GIS frameworks has been explained that provide the requisite knowledge for creating Web based GIS applications. Open Source Software (OSS) have been used to develop two Web GIS frameworks. In first Web GIS framework, WAMP server, ALOV, Quantum GIS and MySQL have been used while in second Web GIS framework, Apache Tomcat server, GeoServer, Quantum GIS, PostgreSQL and PostGIS have been used. These two Web GIS frameworks have been critically compared to bring out the suitability of each for a particular application as well as their performance. This will assist users in selecting the most suitable one for a particular Web GIS application.

Calibration of panoramic cameras with coded targets and a 3d calibration field

Abstract: The aim of this paper is to present results achieved with a 3D terrestrial calibration field, designed for calibrating digital cameras and omnidirectional sensors. This terrestrial calibration field is composed of 139 ARUCO coded targets. Some experiments were performed using a Nikon D3100 digital camera with 8mm Samyang Bower fisheye lens. The camera was calibrated in this terrestrial test field using a conventional bundle adjustment with the Collinearity and mathematical models specially designed for fisheye lenses. The CMC software (Calibration with Multiple Cameras), developed in-house, was used for the calibration trials. This software was modified to use fisheye models to which the Conrady-Brown distortion equations were added. The target identification and image measurements of its four corners were performed automatically with a public software. Several experiments were performed with 16 images and the results were presented and compared. Besides the calibration of fish-eye cameras, the field was designed for calibration of a catadrioptic system and brief informations on the calibration of this unit will be provided in the paper.

Lidar-equipped uav for building information modelling

Abstract: . The trend to minimize electronic devices in the last decades accounts for Unmanned Airborne Vehicles (UAVs) as well as for sensor technologies and imaging devices, resulting in a strong revolution in the surveying and mapping industries. However, only within the last few years the LIDAR sensor technology has achieved sufficiently reduction in terms of size and weight to be considered for UAV platforms. This paper presents an innovative solution to capture point cloud data from a Lidar-equipped UAV and further perform the 3D modelling of the whole envelope of buildings in BIM format. A mini-UAV platform is used (weigh less than 5 kg and up to 1.5 kg of sensor payload), and data from two different acquisition methodologies is processed and compared with the aim at finding the optimal configuration for the generation of 3D models of buildings for energy studies