Orientation and integration of images and image blocks with laser scanning data

Laser scanning and photogrammetry are methods for effective and accurate measurement and classification of urban and forest areas. Because these methods complement each other, then integration or integrated use brings additional benefits to real-life applications. However, finding tie features between data sets is a challenging task since laser scanning and imagery are far from each other in nature. The aim of this thesis was to create methods for solving relative orientations between laser scanning data and imagery that would assist in near-future applications integrating laser scanning and photogrammetry. Moreover, a further goal was to create methods enabling the use of data acquired from very different perspectives, such as terrestrial and airborne data. To meet these aims, an interactive orientation method enabling the use of single images, stereo images or larger image blocks was developed and tested. The multi-view approach usually has a significant advantage over the use of a single image. After accurate orientation of laser scanning data and imagery, versatile applications become available. Such applications include, e.g., automatic object recognition, accurate classification of individual trees, point cloud densification, automatic classification of land use, system calibration, and generation of photorealistic 3D models. Besides the orientation part, another aim of the research was to investigate how to fuse or use these two data types together in applications. As a result, examples that evaluated the behavior of laser point clouds in both urban and forestry areas, detection and visualization of temporal changes, enhanced data understanding, stereo visualization, multi-source and multi-angle data fusion, point cloud colorizing, and detailed examination of full waveform laser scanning data were given

Termite mound architecture regulates nest temperature and correlates with species identities of symbiotic fungi.

Background Large and complex mounds built by termites of the genus Macrotermes characterize many dry African landscapes, including the savannas, bushlands, and dry forests of the Tsavo Ecosystem in southern Kenya. The termites live in obligate symbiosis with filamentous fungi of the genus Termitomyces. The insects collect dead plant material from their environment and deposit it into their nests where indigestible cell wall compounds are effectively decomposed by the fungus. Above-ground mounds are built to enhance nest ventilation and to maintain nest interior microclimates favorable for fungal growth. Objectives In Tsavo Ecosystem two Macrotermes species associate with three different Termitomyces symbionts, always with a monoculture of one fungal species within each termite nest. As mound architecture differs considerably both between and within termite species we explored potential relationships between nest thermoregulatory strategies and species identity of fungal symbionts. Methods External dimensions were measured from 164 Macrotermes mounds and the cultivated Termitomyces species were identified by sequencing internal transcribed spacer (ITS) region of ribosomal DNA. We also recorded the annual temperature regimes of several termite mounds to determine relations between mound architecture and nest temperatures during different seasons. Results Mound architecture had a major effect on nest temperatures. Relatively cool temperatures were always recorded from large mounds with open ventilation systems, while the internal temperatures of mounds with closed ventilation systems and small mounds with open ventilation systems were consistently higher. The distribution of the three fungal symbionts in different mounds was not random, with one fungal species confined to “hot nests.” Conclusions Our results indicate that different Termitomyces species have different temperature requirements, and that one of the cultivated species is relatively intolerant of low temperatures. The dominant Macrotermes species in our study area can clearly modify its mound architecture to meet the thermal requirements of several different symbionts. However, a treacherous balance seems to exist between symbiont identity and mound architecture, as the maintenance of the thermophilic fungal species obviously requires reduced mound architecture that, in turn, leads to inadequate gas exchange. Hence, our study concludes that while the limited ventilation capacity of small mounds sets strict limits to insect colony growth, in this case, improving nest ventilation would invariable lead to excessively low nest temperatures, with negative consequences to the symbiotic fungus.Peer reviewe

Evaluating the performance of university course units using data envelopment analysis

The technique of data envelopment analysis (DEA) for measuring the relative efficiency has been widely used in the higher education sector. However, measuring the performance of a set of course units or modules that are part of a university curriculum has received little attention. In this article, DEA was used in a visual way to measure the performance of 12 course units that are part of a Photogrammetry curriculum taught at Aalto University. The results pinpointed the weakest performing units, i.e. units where the provided teaching efforts might not be adequately reflected in the students’ marks in the unit. Based on the results, a single unit was considered to offer poor performance with respect to its teaching resources and was selected as a candidate for revision of its contents. Financial resources were not used as such; instead, the performance of students in previous pre-requisite units was used as the inputs. For clarity, a single output covering the overall student performance in the examined unit was used. The technique should be widely applicable assuming the grade point averages of the students who took the course unit are available along with the marks obtained in the evaluated units and their pre-requisites

Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters

Kaksikuvamittaus digitaalisilta ilmakuvilta

Tässä diplomityössä on esitetty menetelmä jo olemassa olevan tiedon tarkistamiseen ja päivitykseen sekä ennen mittaamattomien kohteiden sijainnin selvittämiseen digitaalisilta ilmakuvilta kaksikuvamittauksen avulla. Kaksikuvamittauksella tarkoitetaan kohteen kolmiulotteisten koordinaattien mittaamista kahden kuvan avulla ilman fyysistä stereokatselua. Menetelmässä ilmakuville ei tehdä oikaisuja, mutta kuvien orientoinnit ovat tunnettuja. Menetelmässä käytetään apuna kohteesta muodostettavaa geometrista mallia. Tällaista kohdemallia voidaan liikuttaa, kiertää ja skaalata kolmiulotteisessa koordinaatistossa. Muunnosten tulokset projisoidaan kuville, jolloin virheet erottuvat visuaalisesti. Mallin kohdentamisessa ja virheen tunnistamisessa käytetään apuna nadiirisuoria, jotka paljastavat, onko virhe vain Z-koordinaatissa vai ovatko kaikki koordinaatit virheellisiä. Mallien käyttö on edullista lähinnä silloin, kun kohde ei ole pistemäinen. Koetyötä varten kirjoitettiin ohjelma, jossa voitiin kokeilla kaksikuvamittausta. Käytössä oli kaksi ilmakuvaa, jotka oli kuvattu 1:16 000 mittakaavaan. Lentokorkeus oli 3500 metriä ja kameravakio oli 210 mm. Kuvat oli skannattu 15 mikrometrin tarkkuudella. Testiaineistolla saavutettiin likimääräisesti XY-tasossa 0.25 metrin ja Z-suunnassa 0.5 metrin tarkkuudet. Menetelmä soveltuu tarkkuudeltaan hyvin esimerkiksi suurimittakaavaisen kartan ja peruskartan tarkistamiseen, päivitykseen ja uudiskartoitukseen. Jotta menetelmä olisi sovellettavissa käytännön töihin, tulee ohjelman käyttöliittymää ja toimintoja edelleen kehittää

On Selecting Images from An Unaimed Video Stream for Photogrammetric Modelling

In this paper, we illustrate how convolutional neural networks and voxel-based processing together with voxel visualizations can be utilized for the selection of unaimed images for a photogrammetric image block. Our research included the detection of an ear from images with a convolutional neural network, computation of image orientations with a structure-from-motion algorithm, visualization of camera locations in a voxel representation to detect the goodness of the imaging geometry, rejection of unnecessary images with an XYZ buffer, the creation of 3D models in two different example cases, and the comparison of resulting 3D models. Two test data sets were taken of an ear with the video recorder of a mobile phone. In the first test case, a special emphasis was taken to ensure good imaging geometry. On the contrary, in the second test case the trajectory was limited to approximately horizontal movement, leading to poor imaging geometry. A convolutional neural network together with an XYZ buffer managed to select a useful set of images for the photogrammetric 3D measuring phase. The voxel representation well illustrated the imaging geometry and has potential for early detection where data is suitable for photogrammetric modelling. The comparison of 3D models revealed that the model from poor imaging geometry was noisy and flattened. The results emphasize the importance of good imaging geometry.Peer reviewe

On the Atmospheric Refraction in Aerial Photogrammetry

We present an alternative, and possibly more intuitive, method for deriving the equation for correcting the atmospheric effect in near-vertical aerial images. For near-vertical images a horizontally stratified atmospheric model is assumed to be sufficient because the amount of error at the image plane is relatively small. Our derivation utilises Snell’s law and models the apparent uplift of a terrain point due refraction along the path from the ground object to the image. We show the approximate equivalence with older results in the literature, especially for aerial mapping flight heights under 7 km.Peer reviewe