A study of the usefulness of Skylab EREP data for earth resources studies in Australia

The author has identified the following significant results. In subhumid, vegetated areas, S190B photography: (1) has a potentially operational role in detecting lineaments in 1:100,000 scale geological mapping and in major civil engineering surveys; (2) is of limited value for regional lithological mapping at 1:500,000 scale; and (3) provided much useful synoptic information and some detailed information of direct value to the mapping of nonmineral natural resources such as vegetation, land soil, and water. In arid, well exposed areas, S190B photography could be used: (1) with a limited amount of field traverses, to produce reliable 1:500,000 scale geological maps of sedimentary sequences; (2) to update superficial geology on 1:250,000 scale maps; and (3) together with the necessary field studies, to prepare landform, soil, and vegetation maps at 1:1,000,000 scale. Skylab photography was found to be more useful than LANDSAT images for small scale mapping of geology and land types, and for the revision of topographic maps at 1:100,000 scale, because of superior spatial resolution and stereoscopic coverage

Future internet enablers for VGI applications

This paper presents the authors experiences with the development of mobile Volunteered Geographic Information (VGI) applications in the context of the ENVIROFI project and Future Internet Public Private Partnership (FI-PPP) FP7 research programme.FI-PPP has an ambitious goal of developing a set of Generic FI Enablers (GEs) - software and hardware tools that will simplify development of thematic future internet applications. Our role in the programme was to provide requirements and assess the usability of the GEs from the point of view of the environmental usage area, In addition, we specified and developed three proof of concept implementations of environmental FI applications, and a set of specific environmental enablers (SEs) complementing the functionality offered by GEs. Rather than trying to rebuild the whole infrastructure of the Environmental Information Space (EIS), we concentrated on two aspects: (1) how to assure the existing and future EIS services and applications can be integrated and reused in FI context; and (2) how to profit from the GEs in future environmental applications.This paper concentrates on the GEs and SEs which were used in two of the ENVIROFI pilots which are representative for the emerging class of Volunteered Geographic Information (VGI) use-cases: one of them is pertinent to biodiversity and another to influence of weather and airborne pollution on users’ wellbeing. In VGI applications, the EIS and SensorWeb overlap with the Social web and potentially huge amounts of information from mobile citizens needs to be assessed and fused with the observations from official sources. On the whole, the authors are confident that the FI-PPP programme will greatly influence the EIS, but the paper also warns of the shortcomings in the current GE implementations and provides recommendations for further developments

The iNaturalist Species Classification and Detection Dataset

Existing image classification datasets used in computer vision tend to have a uniform distribution of images across object categories. In contrast, the natural world is heavily imbalanced, as some species are more abundant and easier to photograph than others. To encourage further progress in challenging real world conditions we present the iNaturalist species classification and detection dataset, consisting of 859,000 images from over 5,000 different species of plants and animals. It features visually similar species, captured in a wide variety of situations, from all over the world. Images were collected with different camera types, have varying image quality, feature a large class imbalance, and have been verified by multiple citizen scientists. We discuss the collection of the dataset and present extensive baseline experiments using state-of-the-art computer vision classification and detection models. Results show that current non-ensemble based methods achieve only 67% top one classification accuracy, illustrating the difficulty of the dataset. Specifically, we observe poor results for classes with small numbers of training examples suggesting more attention is needed in low-shot learning.Comment: CVPR 201

Direct Image-to-Geometry Registration Using Mobile Sensor Data

Peer reviewedPublisher PD

A Hybrid Framework for Matching Printing Design Files to Product Photos

We propose a real-time image matching framework, which is hybrid in the sense that it uses both hand-crafted features and deep features obtained from a well-tuned deep convolutional network. The matching problem, which we concentrate on, is specific to a certain application, that is, printing design to product photo matching. Printing designs are any kind of template image files, created using a design tool, thus are perfect image signals. However, photographs of a printed product suffer many unwanted effects, such as uncontrolled shooting angle, uncontrolled illumination, occlusions, printing deficiencies in color, camera noise, optic blur, et cetera. For this purpose, we create an image set that includes printing design and corresponding product photo pairs with collaboration of an actual printing facility. Using this image set, we benchmark various hand-crafted and deep features for matching performance and propose a framework in which deep learning is utilized with highest contribution, but without disabling real-time operation using an ordinary desktop computer

1.4. DIY Digital Workflows on the Athienou Archaeological Project, Cyprus

For the last 25 years, the Athienou Archaeological Project (AAP) has conducted pedestrian survey and excavations of domestic, religious, and funerary sites in the Malloura Valley on Cyprus. To enhance the project’s research goals, excavation methods, and pedagogical mission, AAP has recognized the utility of thoughtfully integrating emergent technologies into the excavation process and has acknowledged the importance of acquainting students with such technologies. Indeed, AAP has participated in the transition from handwritten notebooks to born-digital, tablet-based recording. In 2011 AAP was among the earliest projects to embrace the “paperless” archaeology revolution that is quickly becoming standard in field archaeology. This chapter describes AAP’s transition to a do-it-yourself (DIY) hybrid archaeological recording system that integrates both born-digital and tablet-based on-site methods with existing paper-based modes of field recording. We discuss the benefits and drawbacks of system implementation and consider the impact of born-digital data recording on project workflows, research, and teaching.https://dc.uwm.edu/arthist_mobilizingthepast/1005/thumbnail.jp