Registro semiautomático entre imagens infravermelhas e RGB coletadas por um par de câmaras digitais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Formação de imagens multiespectrais por meio de fusão de imagens adquiridas por múltiplas câmaras

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Echolocation detections and digital video surveys provide reliable estimates of the relative density of harbour porpoises

Acknowledgements We would like to thank Erik Rexstad and Rob Williams for useful reviews of this manuscript. The collection of visual and acoustic data was funded by the UK Department of Energy & Climate Change, the Scottish Government, Collaborative Offshore Wind Research into the Environment (COWRIE) and Oil & Gas UK. Digital aerial surveys were funded by Moray Offshore Renewables Ltd and additional funding for analysis of the combined datasets was provided by Marine Scotland. Collaboration between the University of Aberdeen and Marine Scotland was supported by MarCRF. We thank colleagues at the University of Aberdeen, Moray First Marine, NERI, Hi-Def Aerial Surveying Ltd and Ravenair for essential support in the field, particularly Tim Barton, Bill Ruck, Rasmus Nielson and Dave Rutter. Thanks also to Andy Webb, David Borchers, Len Thomas, Kelly McLeod, David L. Miller, Dinara Sadykova and Thomas Cornulier for advice on survey design and statistical approache. Data Accessibility Data are available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.cf04g

Methods of eliminating ground surveying for control in aerial photography /

"The fifth of a series of papers on topographic mapping by aerial photography."

Reference guide outline; specifications for aerial surveys and mapping by photogrammetric methods for highways, prepared by the Photogrammetry for Highways Committee, jointly sponsored by the American Society of Photogrammetry, and the American Congress on Surveying and Mapping and recommended by the Committee for endorsement and distribution by these sponsoring societies.

Mode of access: Internet.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Land-cover classification from airborne LIDAR data fused with aerial optical images

Airborne LIght Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy Markov random field (FMRF) model is developed, by which the LIDAR data, its co-registered images acquired by optical sensors, i.e. aerial color image and near infrared image, and other derived features are fused effectively to improve the ability of the LIDAR system for the accurate land-cover classification. In the proposed FMRF model-based approach, the spatial contextual information is applied by modeling the image as a Markov random field (MRF), with which the fuzzy logic is introduced simultaneously to reduce the errors caused by the hard classification. Moreover, a Lagrange-Multiplier (LM) algorithm is employed to calculate a maximum A posteriori (MAP) estimate for the classification. The experimental results have proved that fusing the height data and optical images is particularly suited for the land-cover classification. The proposed approach works very well for the classification from airborne LIDAR data fused with its coregistered optical images and the average accuracy is improved to 88.9%.

Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.

Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.

A simple method of surveying from air photographs,

(Gt. Brit. Air survey committee. Professional papers, no. 8 Supplement)

Automatic Detection of Marine Mammal from Aerial Imagery

The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. We have developed and algorithm that automatically presents to a user a number of possible candidates of these mammals. We tested the algorithm in two distinct datasets taken from different altitudes. Analysis and discussion is presented in regards with the complexity of the input datasets, the detection performance.

The BEE Undergraduate Model for Knowledge Development applied to the QUT Spatial Science Course : Diversity in Surveying Curriculum

This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.

Debate on statutory control of the surveying profession in Queensland : 1907 to 1975

This article was written in 1997. After a 2009 review the content was left mostly unchanged - apart from this re-written abstract, restructured headings and a table of contents. The article deals directly with professional registration of surveyors; but it also relates to government procurement of professional services. The issues include public service and professional ethics; setting of professional fees; quality assurance; official corruption; and professional recruitment, education and training. Debate on the Land Surveyors Act 1908 (Qld) and its amendments to 1916 occurred at a time when industrial unrest of the 1890s and common market principles of the new Commonwealth were fresh in peoples’ minds. Industrial issues led to a constitutional crisis in the Queensland’s then bicameral legislature and frustrated a first attempt to pass a Surveyors Bill in 1907. The Bill was re-introduced in 1908 after fresh elections and Kidston’s return as state premier. Co-ordinated immigration and land settlement polices of the colonies were discontinued when the Commonwealth gained power over immigration in 1901. Concerns shifted to protecting jobs from foreign competition. Debate on 1974 amendments to the Act reflected concerns about skill shortages and professional accreditation. However, in times of economic downturn, a so-called ‘chronic shortage of surveyors’ could rapidly degenerate into oversupply and unemployment. Theorists championed a naïve ‘capture theory’ where the professions captured governments to create legislative barriers to entry to the professions. Supposedly, this allowed rent-seeking and monopoly profits through lack of competition. However, historical evidence suggests that governments have been capable of capturing and exploiting surveyors. More enlightened institutional arrangements are needed if the community is to receive benefits commensurate with sizable co-investments of public and private resources in developing human capital.