On Projective Plane of Order 13 with a Frobenius Group of Order 39 as a Collineation Group

One of the most outstanding problems in combinatorial mathematics and geometry is the problem of existence of finite projective planes whose order is not a prime power.

Symplectic Representation of a Braid Group on 3-Sheeted Covers of the Riemann Sphere

We define Picard cycles on each smooth three-sheeted Galois cover C of the Riemann sphere. The moduli space of all these algebraic curves is a nice Shimura surface, namely a symmetric quotient of the projective plane uniformized by the complex two-dimensional unit ball. We show that all Picard cycles on C form a simple orbit of the Picard modular group of Eisenstein numbers. The proof uses a special surface classification in connection with the uniformization of a classical Picard-Fuchs system. It yields an explicit symplectic representation of the braid groups (coloured or not) of four strings.

Usability of VGI for validation of land cover maps

Volunteered Geographic Information (VGI) represents a growing source of potentially valuable data for many applications, including land cover map validation. It is still an emerging field and many different approaches can be used to take value from VGI, but also many pros and cons are related to its use. Therefore, since it is timely to get an overview of the subject, the aim of this article is to review the use of VGI as reference data for land cover map validation. The main platforms and types of VGI that are used and that are potentially useful are analysed. Since quality is a fundamental issue in map validation, the quality procedures used by the platforms that collect VGI to increase and control data quality are reviewed and a framework for addressing VGI quality assessment is proposed. A review of cases where VGI was used as an additional data source to assist in map validation is made, as well as cases where only VGI was used, indicating the procedures used to assess VGI quality and fitness for use. A discussion and some conclusions are drawn on best practices, future potential and the challenges of the use of VGI for land cover map validation.

Projective Methods of Image Recognition

We propose a method for image recognition on the base of projections. Radon transform gives an opportunity to map image into space of its projections. Projection properties allow constructing informative features on the base of moments that can be successfully used for invariant recognition. Offered approach gives about 91-97% of correct recognition.

A Metaheuristic Approach to Solving the Generalized Vertex Cover Problem

AMS Subj. Classification: 90C27, 05C85, 90C59

Essential Cover and Closure

2000 Mathematics Subject Classification: 16N80, 16S70, 16D25, 13G05.

Predegree Polynomials of Plane Configurations in Projective Space

2000 Mathematics Subject Classification: 14N10, 14C17.

Land-cover detection and landscape structure analysis in the Pachitea Basin, Peruvian Amazon

Classification procedures, including atmospheric correction satellite images as well as classification performance utilizing calibration and validation at different levels, have been investigated in the context of a coarse land-cover classification scheme for the Pachitea Basin. Two different correction methods were tested against no correction in terms of reflectance correction towards a common response for pseudo-invariant features (PIF). The accuracy of classifications derived from each of the three methods was then assessed in a discriminant analysis using crossvalidation at pixel, polygon, region, and image levels. Results indicate that only regression adjusted images using PIFs show no significant difference between images in any of the bands. A comparison of classifications at different levels suggests though that at pixel, polygon, and region levels the accuracy of the classifications do not significantly differ between corrected and uncorrected images. Spatial patterns of land-cover were analyzed in terms of colonization history, infrastructure, suitability of the land, and landownership. The actual use of the land is driven mainly by the ability to access the land and markets as is obvious in the distribution of land cover as a function of distance to rivers and roads. When considering all rivers and roads a threshold distance at which disproportional agro-pastoral land cover switches from over represented to under represented is at about 1km. Best land use suggestions seem not to affect the choice of land use. Differences in abundance of land cover between watersheds are more prevailing than differences between colonist and indigenous groups.

Assessing the legacy of the pine point mine: post-industrial land cover and land use

While mining is a major component of the northern Canadian economy, including the contemporary mixed economy of Aboriginal communities, it often leaves legacies of environmental and economic transformation that persist after closure. The legacies of historical mines in northern Canada challenge industry claims of sustainability. This thesis addresses how industrial mineral development and closure continue to affect local environments and economies after abandonment. The abandoned Pine Point mine in the Northwest Territories provides a case study for explaining the ongoing relationships among land cover, land use, and the post-industrial landscape. Drawing from landscape ecology and micropolitical ecology, I adopt an interdisciplinary approach to examine environmental and socioeconomic changes in the wake of industrial development and closure at Pine Point. The results show that passive reclamation is not sufficient for restoring ecological function in a subarctic environment. Land use, however, persists as land users adapt to the post-industrial landscape despite grave concern about its environmental condition. If mining is to be considered sustainable, decommissioning and reclamation must explicitly account for long-term environmental transformation as well as ongoing post-industrial land use, particularly in Aboriginal contexts.

The Lena River Delta - Land cover classification of tundra environments based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

GPS linked photos of benthic cover transect surveys in Heron Reef

Underwater photo-transect surveys were conducted on September 23-27, 2007 at different sections of the reef flat, reef crest and reef slope in Heron Reef. This survey was done by swimming along pre-defined transect sites and taking a picture of the bottom substrate parallel to the bottom at constant vertical distance (30cm) every two to three metres. A total of 3,586 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of transect surveys. Approximation of the coordinates for each benthic photo was based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software. Coordinates of each photo were interpolated by finding the the gps coordinates that were logged at a set time before and after the photo was captured. The output of this process was an ArcMap point shapefile, a Google Earth KML file and a thumbnail of each benthic photo taken. The data in the ArcMap shapefile and in the Google Earth KML file consisted of the approximated coordinate of each benthic photo taken during the survey. Using the GPS Photo Link extension within the ArcMap environment, opening the ArcMap shapefile will enable thumbnail to be displayed on the associated benthic cover photo whenever hovering with the mouse over a point on the transect. By downloading the GPSPhotoLink software from the www.geospatialexperts.com, and installing it as a trial version the ArcMap exstension will be installed in the ArcMap environment.

Benthic and substrate cover data derived from photo-transect surveys in Lizard Island Reef conducted on December 10-15, 2011

Underwater georeferenced photo-transect surveys were conducted on December 10-15, 2011 at various sections of the reef at Lizard Island, Great Barrier Reef. For this survey a snorkeler or diver swam over the bottom while taking photos of the benthos at a set height using a standard digital camera and towing a GPS in a surface float which logged the track every five seconds. A standard digital compact camera was placed in an underwater housing and fitted with a 16 mm lens which provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by three fin kicks of the survey diver/snorkeler, which corresponded to a surface distance of approximately 2.0 - 4.0 m. The GPS was placed in a dry-bag and logged the position as it floated at the surface while being towed by the photographer. A total of 5,735 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of each benthic photo (Roelfsema 2009). Approximation of coordinates of each benthic photo was conducted based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the GPS coordinates that were logged at a set time before and after the photo was captured. Benthic or substrate cover data was derived from each photo by randomly placing 24 points over each image using the Coral Point Count for Microsoft Excel program (Kohler and Gill, 2006). Each point was then assigned to 1 of 78 cover types, which represented the benthic feature beneath it. Benthic cover composition summary of each photo scores was generated automatically using CPCE program. The resulting benthic cover data of each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 55 South.

Benthic and substrate cover data derived from photo-transect surveys in Lizard Island, Great Barrier Reef conducted on October 3-7, 2012

Underwater georeferenced photo-transect surveys were conducted on October 3-7, 2012 at various sections of the reef and lagoon at Lizard Island, Great Barrier Reef. For this survey a snorkeler swam while taking photos of the benthos at a set distance from the benthos using a standard digital camera and towing a GPS in a surface float which logged the track every five seconds. A Canon G12 digital camera was placed in a Canon underwater housing and photos were taken at 1 m height above the benthos. Horizontal distance between photos was estimated by three fin kicks of the survey snorkeler, which corresponded to a surface distance of approximately 2.0 - 4.0 m. The GPS was placed in a dry bag and logged the position at the surface while being towed by the photographer (Roelfsema, 2009). A total of 1,265 benthic photos were taken. Approximation of coordinates of each benthic photo was conducted based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the GPS coordinates that were logged at a set time before and after the photo was captured. Benthic or substrate cover data was derived from each photo by randomly placing 24 points over each image using the Coral Point Count for Microsoft Excel program (Kohler and Gill, 2006). Each point was then assigned to 1 of 79 cover types, which represented the benthic feature beneath it. Benthic cover composition summary of each photo scores was generated automatically using CPCE program. The resulting benthic cover data of each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 55 South.