Recentemente, o uso dos Veículos Aéreos Não Tripulados (VANTs) surgiu como uma ferramenta para a aquisição de dados geoespaciais. Os Modelos Digitais de Elevação (MDEs), as ortoimagens e os modelos tridimensionais gerados a partir de imagens de VANT são produtos cartográficos de grande utilidade para as mais diversas aplicações. Em vista das limitações dos VANTs e da recentidade desta ferramenta, este estudo visa determinar a correlação da configuração dos pontos de apoio e dos parâmetros do voo com a acurácia de ortofotomosaicos elaborados a partir de dados de VANT. Esta pesquisa utilizou dados de três levantamentos aerofotogramétricos distintos realizados com três aeronaves diferentes e considerou parâmetros relacionados à configuração dos pontos de apoio e à execução do voo. Foram gerados 200 ortofotomosaicos e 200 MDEs. Ao todo foram feitas 4616 observações de pontos de controle. Os resultados mostraram baixa correlação linear entre acurácia planimétrica e altimétrica. Os melhores resultados foram obtidos de forma inversa às alturas de voo. No geral, sob as condições de processamento utilizadas neste trabalho, recomenda-se o uso de 4 a 5 pontos de apoio por km², além do uso de voo cruzado. / Recently, the use of Unmanned Aerial Vehicle (UAV) emerged as a tool for geospatial data acquisition. Digital Elevation Models (DEMs), orthoimages and three- dimensional models generated from UAV images are cartographic products of great utility for many different applications. Considering the recency and limitations of UAV, this study aims at determining the correlation of ground control points and flight configuration with the accuracy of orthophotomosaics based on UAV data. This research used data from three different aerial surveys, performed with three different aircrafts, and considered parameters related to ground-control points distribution and to flight missions. 200 orthophotomosaics and 200 DEMs were generated and a total of 4616 ground-control points measurements were performed. Results did not show a linear correlation between planimetric and altimetric accuracy. The best correlation results were obtained inversely related to flight height. In general, under the processing conditions used in this work, we recommend the use of 4 control points per km² and a cross flight pattern.

Recentemente, o uso dos Veículos Aéreos Não Tripulados (VANTs) surgiu como uma ferramenta para a aquisição de dados geoespaciais. Os Modelos Digitais de Elevação (MDEs), as ortoimagens e os modelos tridimensionais gerados a partir de imagens de VANT são produtos cartográficos de grande utilidade para as mais diversas aplicações. Em vista das limitações dos VANTs e da recentidade desta ferramenta, este estudo visa determinar a correlação da configuração dos pontos de apoio e dos parâmetros do voo com a acurácia de ortofotomosaicos elaborados a partir de dados de VANT. Esta pesquisa utilizou dados de três levantamentos aerofotogramétricos distintos realizados com três aeronaves diferentes e considerou parâmetros relacionados à configuração dos pontos de apoio e à execução do voo. Foram gerados 200 ortofotomosaicos e 200 MDEs. Ao todo foram feitas 4616 observações de pontos de controle. Os resultados mostraram baixa correlação linear entre acurácia planimétrica e altimétrica. Os melhores resultados foram obtidos de forma inversa às alturas de voo. No geral, sob as condições de processamento utilizadas neste trabalho, recomenda-se o uso de 4 a 5 pontos de apoio por km², além do uso de voo cruzado. / Recently, the use of Unmanned Aerial Vehicle (UAV) emerged as a tool for geospatial data acquisition. Digital Elevation Models (DEMs), orthoimages and three- dimensional models generated from UAV images are cartographic products of great utility for many different applications. Considering the recency and limitations of UAV, this study aims at determining the correlation of ground control points and flight configuration with the accuracy of orthophotomosaics based on UAV data. This research used data from three different aerial surveys, performed with three different aircrafts, and considered parameters related to ground-control points distribution and to flight missions. 200 orthophotomosaics and 200 DEMs were generated and a total of 4616 ground-control points measurements were performed. Results did not show a linear correlation between planimetric and altimetric accuracy. The best correlation results were obtained inversely related to flight height. In general, under the processing conditions used in this work, we recommend the use of 4 control points per km² and a cross flight pattern.

Recentemente, o uso dos Veículos Aéreos Não Tripulados (VANTs) surgiu como uma ferramenta para a aquisição de dados geoespaciais. Os Modelos Digitais de Elevação (MDEs), as ortoimagens e os modelos tridimensionais gerados a partir de imagens de VANT são produtos cartográficos de grande utilidade para as mais diversas aplicações. Em vista das limitações dos VANTs e da recentidade desta ferramenta, este estudo visa determinar a correlação da configuração dos pontos de apoio e dos parâmetros do voo com a acurácia de ortofotomosaicos elaborados a partir de dados de VANT. Esta pesquisa utilizou dados de três levantamentos aerofotogramétricos distintos realizados com três aeronaves diferentes e considerou parâmetros relacionados à configuração dos pontos de apoio e à execução do voo. Foram gerados 200 ortofotomosaicos e 200 MDEs. Ao todo foram feitas 4616 observações de pontos de controle. Os resultados mostraram baixa correlação linear entre acurácia planimétrica e altimétrica. Os melhores resultados foram obtidos de forma inversa às alturas de voo. No geral, sob as condições de processamento utilizadas neste trabalho, recomenda-se o uso de 4 a 5 pontos de apoio por km², além do uso de voo cruzado. / Recently, the use of Unmanned Aerial Vehicle (UAV) emerged as a tool for geospatial data acquisition. Digital Elevation Models (DEMs), orthoimages and three- dimensional models generated from UAV images are cartographic products of great utility for many different applications. Considering the recency and limitations of UAV, this study aims at determining the correlation of ground control points and flight configuration with the accuracy of orthophotomosaics based on UAV data. This research used data from three different aerial surveys, performed with three different aircrafts, and considered parameters related to ground-control points distribution and to flight missions. 200 orthophotomosaics and 200 DEMs were generated and a total of 4616 ground-control points measurements were performed. Results did not show a linear correlation between planimetric and altimetric accuracy. The best correlation results were obtained inversely related to flight height. In general, under the processing conditions used in this work, we recommend the use of 4 control points per km² and a cross flight pattern.

Σε αυτή την εργασία στόχος είναι να συντεθεί μία βάση φωτοσταθερών που θα μπορεί να χρησιμοποιηθεί για την γεωμετρική διόρθωση δορυφορικών εικόνων που έχουν ληφθεί από σαρωτές με παρόμοια χαρακτηριστικά σε διαφορετικές χρονικές στιγμές. Πιο συγκεκριμένα η βάση δεδομένων δημιουργήθηκε με φωτοσταθερά που προσδιορίσθηκαν από δορυφορική εικόνα Landsat–ETM (pixel=15m, παγχρωματικό) ενώ οι συντεταγμένες των φωτοσταθερών μετρήθηκαν στο έδαφος με GPS (φορητό, Garmin 12 ). Η περιοχή μελέτης είναι στο λεκανοπέδιο Αττικής. Τα φωτοσταθερά που χρησιμοποιήθηκαν κατά κανόνα αντιστοιχούσαν σε διασταυρώσεις κεντρικών οδών που αναγνωρίσθηκαν όχι μόνο στην εικόνα αλλά και σε τοπογραφικό χάρτη κλίμακας 1:10.000 προκειμένου να διευκολυνθεί η πρόσβαση στο ύπαιθρο. Η γεωμετρική διόρθωση υλοποιήθηκε με πολυώνυμο δευτέρου βαθμού (μη παραμετρικό μοντέλο στο λογισμικό επεξεργασίας εικόνας) ErMapper και το μέσο τετραγωνικό σφάλμα ήταν 7,01 μέτρα. Στην συνέχεια η πλειονότητα των φωτοσταθερών αναγνωρίσθηκαν και σε δορυφορική εικόνα (VNIR) με χωρική διακριτική ικανότητα 15μ, επιβεβαιώνοντας την δυνατότητα χρήσης της βάσης για την διόρθωση διαχρονικών (multi-temporal) δεδομένων. Προσδιορίσθηκαν οι κανόνες επιλογής φωτοσταθερών για την δημιουργία βάσεως δεδομένων και προσδιορίσθηκαν οικονομοτεχνικά στοιχεία που καθορίζουν το κόστος των εργασιών. / A database of Ground Control Points was established for the geometric correction of multi-temporal satellite imagery. More specifically the high resolution (15 meters ) panchromatic band of a Landsat image was used for the recognition of Ground Control Points, their coordinates were measured on the ground by a hand-held Garmin GPS. The GCPs selected corresponded to main streets intersections that were easily recognized in the 15th meter resolution image. A non parametric method (second order polynomial) was used for the geometric corrections of the images. The resulted RMS was equal to 7,01 meter. Then the majority GCPs were also recognized in an Aster (VNIR) image with resolution 15m.This fact indicated that a GCP database can be used for the corrections of multitemporal imagery (like Aster with revisit time 16 days) that covers Attiki Regions. The rules for the selection of GCPs in order to construct a database were determined as well as the cost of processing for GCP.

En karta är en färskvara som är i ständigt behov av ajourhållning. Ajourhållning görs normalt med traditionella metoder: fotogrammetriska och/eller geodetiska. Men i och med att utvecklingen går framåt har intresset för en ny metod, UAS (Unmanned Aerial Systems), ökat. UAS är en relativt ny fotogrammetrisk metod där obemannade flygfarkoster används. Detta examensarbete har utvärderat vilken osäkerhet vanligt förekommande detaljer i en karta kan få i framställda "produkter" som genererats med hjälp av UAS-bilder som georefererats med naturliga stödpunkter. Produkterna som framställdes var en digital ytmodell och ett ortofoto och togs fram i datorprogrammet Agisoft Photoscan. Bilderna som bearbetades i denna studie erhölls från Swecos UAS-flygning och var tagna över deponiområdet Fågelmyra i Ornäs, Dalarnas län. I den digitala ytmodellen och i ortofotot mättes detaljer in för att sedan kontrolleras mot kontrollpunkter inmätta med nätverks-RTK (Real-Time Kinematic). Studien visade att detaljer inmätta i den digitala ytmodellen och ortofotot resulterade i en osäkerhet på 0,28 m respektive 0,08 m i plan. Varför osäkerheterna skiljer sig mellan den digitala ytmodellen och ortofotot kan ha att göra med att det är svårt att identifiera objekt i den digitala ytmodellen. Utifrån denna studie kan det konstateras att UAS och georeferering med naturliga stödpunkter lämpar sig för kartering av mindre områden. Dessutom kan det konstateras att UAS är effektiv och relativt enkel teknik. / A map is in constant need of being updated. Map updating is normally performed with traditional methods such as photogrammetric and/or geodetic. But by technical development the interest in new methods has increased, like in UAS (Unmanned Aerial Systems). UAS is a relatively new photogrammetric method using unmanned aerial vehicles (UAV). The purpose of this study is to evaluate what uncertainty common details in a map can get in "products" generated from UAS images georeferenced with natural ground control points. The products that were generated was a digital surface model and an orthophoto and was produced in the software Agisoft Photoscan. The images that were processed in this study were obtained from Sweco’s UAS flight and taken over landfill area Fågelmyra in Ornäs, Dalarna county. In the digital surface model and the orthophoto details were measured and controlled against check points surveyed with Network RTK (Real-Time Kinematic). The study has shown that the surveyed details in the digital surface model and ortohophoto resulted in a planimetric uncertainty of 0.28 m and 0.08 m, respectively. The reason for why the uncertainties for the digital surface model and orthophoto are different may be that it is difficult to identify objects in the digital surface model. Based on this study it can be concluded that UAS and georeferencing with natural ground control points is suitable for mapping of smaller areas. In addition, it can be concluded that UAS is efficient and relatively easy technique.

Att tidigt kunna detektera samt åtgärda sättningar och deformationer är viktigt inom exempelvis bygg-, anläggnings- och gruvindustrin för att kontrollera att verksamheten inte påverkar närliggande områden och strukturer. UAV (Unmanned Aerial Vehicle) fotogrammetri är en lämplig metod för att utföra upprepade mätningar i svårtillgänglig miljö där sättningar kan uppkomma. Syftet med denna studie har varit att undersöka möjligheten till att detektera sättningar med UAV fotogrammetri samt att jämföra direkt och indirekt georeferering. Detta har undersökts genom att ett antal objekt har använts till att simulera sättningar med förändringar på centimeternivå. Området som studien utfördes på flögs över med en fotogrammetrisk UAV i två epoker varav den första epoken var innan sättning och den andra epoken var efter en simulerad sättning av objekten. Punkter markerades på objekten vilka mättes in med totalstation för båda epokerna och dessa mätningar användes som referensvärden (hädanefter kallat True Value). Bearbetning skedde därefter i två programvaror: Agisoft Metashape och Leica Infinity. I Metashape skapades punktmoln för båda epokerna indirekt georefererade med markstödpunkter. I Infinity skapades punktmoln för båda epokerna direkt georefererade med Nätverks-RTK (N-RTK). Punktmolnens avvikelser mot kontrollpunkter kontrollerades. Koordinater för markeringarna på objekten extraherades och jämfördes med koordinater inmätta med totalstation. Resultatet av bearbetningen blev fyra olika punktmoln. I de indirekt georefererade punktmolnen var det möjligt att detektera deformeringar på centimeternivå. Det var däremot inte möjligt i de direkt georefererade punktmolnen då de var påverkade av ett systematiskt fel i höjd. De två programvarornas arbetsgång och resultat jämfördes även mot varandra och där kan det konstateras att om de två programvarorna båda har höga systemkrav så var Leica Infinity betydligt mer krävande både vad gäller hårdvara och tidsåtgång än Agisoft Metashape. De slutsatser vi kan dra utifrån denna studie är att N-RTK ännu inte är en tillräckligt bra georefereringsmetod när låga osäkerheter efterfrågas. I detta fall är indirekt georeferering eller registrering av punktmolnen med hjälp av ICP (Iterative Closest Point) algoritmer att föredra. Det är också viktigt att generera punktmoln med en så hög punkttäthet som möjligt för att kunna göra noggranna mätningar i molnen. / The early detection and measure of subsidence and deformations is important within construction-, civil engineering and the mining industry to control whether the operations affect nearby areas and structures. UAV (Unmanned Aerial Vehicle) photogrammetry is a suitable method to conduct repeated measurements in environments which is hard to access where subsidence can occur. The purpose of this study has been to investigate the possibility of detecting subsidence with UAV photogrammetry and compare direct and indirect georeferencing. This has been investigated by using several objects to simulate subsidence at centimeter level. The area where the study was conducted was flown over with a photogrammetric UAV in two epochs of which the first epoch was before subsidence and the second epoch was after a simulated subsidence of the objects. Points was marked on the objects who were measured with a total station for both epochs and these measurements was used as reference values (hereafter called True Value). Processing was thereafter done in two different software: Agisoft Metashape and Leica Infinity. In Metashape point clouds was created for both epochs indirectly georeferenced with ground control points. In Infinity point clouds was created for both epochs directly georeferenced with Network-RTK (N-RTK). The deviations of the point clouds towards checkpoints were verified. Coordinates of the markings on the objects was extracted and compared against coordinates measured with total station. The photogrammetric processing resulted in four different point clouds. In the indirectly georeferenced pointclouds it was possible to detect deformations at centimeterlevel. This was however not possible using the directly georeferenced pointclouds as they were affected by a systematic error in heigth. The workflow and the resulting point clouds from the two different software was also compared to each other and by that it was established that even though they both have high system requirements the Leica Infinity software was much more demanding and additionally time consuming. The conclusion from this study is that N-RTK is not yet a satisfactory method for georeferencing when low uncertainties are required. In this case, indirect georeferencing or registration of the point clouds with ICP (Iterative Closest Point) algorithms is to be preferred. It is also important to create point clouds with the highest density possible to be able to make exact measurements.