Selected aspects of settlement generalization in the General Geographic Database in Poland

The aim of the study was to investigate and highlight the specifics of settlements generalization in the General Geographic Database in Poland. As all the settlements are presented by signatures and selected, bigger ones by outlines – two important aspects were taken into consideration. First of all an attempt of formulating a formal criteria of settlements selection presented by signatures was conducted. The main challenge in this aspect was to achieve a high degree of formalization and automation in the generalization process with inclusion of the specifics of generalized features. In order to fulfil those conditions a concept of regional differentiation of parameters in the settlements selection process was proposed. Additionally the possibilities of contextual settlements’ outlines aggregation and simplification with the application of mathematical morphology operations were also investigated. By applying functions of modified erosion and dilation in the settlements’ outlines aggregation as well as using a simplification algorithm it was possible to achieve results which are cartographically correct in the terms of shape generalization

Make It simple: effective road selection for small-scale map design using decision-tree-based models

The complexity of a road network must be reduced after a scale change, so that the legibility of the map can be maintained. However, deciding whether to show a particular road section on the map is a very complex process. This process, called selection, constitutes the first step in a sequence of further generalization operations and it is a prerequisite to effective road network generalization. So far, not many comprehensive solutions have been developed for effective road selection specifically at small scales as the studies have mainly dealt with large-scale maps. The paper presents an experiment using machine learning (ML), specifically decision-tree-based (DT) models, to optimize the selection of the roads from 1:250,000 to 1:500,000 and 1:1,000,000 scales. The scope of this research covers designing and verifying road selection models on the example of three selected districts in Poland. The aim is to consider the problem of road generalization holistically, including numerous semantic, geometric, topological, and statistical road characteristics. The research resulted in a list of measurable road attributes that comprehensively describe the rank of a particular road section. The outcome also includes attribute weights, attribute correlation calculated for roads, and machine learning models designed for automatic road network selection. The performance of the machine learning models is very high and ranges from 80.94% to 91.23% for the 1:500,000 target scale and 98.21% to 99.86% for the 1:1,000,000 scale

Land use institutions and social-ecological systems: a spatial analysis of local landscape changes in Poland

Understanding the complex impacts of human settlement patterns on social and natural systems is critical for immediate and long-term policy decisions and ecosystem preservation. Land-use patterns can be conceptualized as a form of integrated natural-human system within urban regions. However, extant scholarship on urban development and sprawl often overlooks the institutional diversity which exists across countries and regions. Development and land-use are politically charged governance issues, and these studies have rarely examined the influences of local political institutions on land-use changes across countries and over time. To help build cumulative knowledge on such urban systems, this study examines landscape change in Poland, which has undergone significant institutional evolution since the fall of the Soviet Union. Drawing from the urban and social-ecological systems (SES) literatures, we estimate spatio-temporal models of the interactive effects of socio-economic and political variables on land-use intensity. Consistent with an SES approach, the analysis finds that characteristics of the institutional design of land-use regulation – local autonomy, the productivity of the resource, and the predictability of land-use dynamics – influence more-intensive landscape changes over the study period (2006–2018). Specifically, both the electoral stability of the mayor and wealth of the community have a positive interactive effect on the conversion of landscapes to more urban uses. Development is also influenced by spatial and temporal dependency, and the availability of European Union “cohesion” investments intended to address economic inequality and promote sustainable development. The findings advance our understanding of the complexity of urban land-use patterns and sustainability goals.This work was supported by the Polish National Science Center [2018/29/B/HS4/01183]. Antonio ´ Tavares acknowledges the financial support from the Research Center in Political Science (UIDB/CPO/ 00758/2020), University of Minho/University of Evora ´ supported by the Portuguese Foundation for Science and Technology (FCT) and the Portuguese Ministry of Education and Science through national fu

BVLOS UAV missions for vegetation mapping in maritime Antarctic

Polar areas are among the regions where climate change occurs faster than on most of the other areas on Earth. To study the effects of climate change on vegetation, there is a need for knowledge on its current status and properties. Both classic field observation methods and remote sensing methods based on manned aircraft or satellite image analysis have limitations. These include high logistic operation costs, limited research areas, high safety risks, direct human impact, and insufficient resolution of satellite images. Fixed-wing unmanned aerial vehicle beyond the visual line of sight (UAV BVLOS) missions can bridge the scale gap between field-based observations and full-scale airborne or satellite surveys. In this study the two operations of the UAV BVLOS, at an altitude of 350m ASL, have been successfully performed in Antarctic conditions. Maps of the vegetation of the western shore of Admiralty Bay (King George Island, South Shetlands, Western Antarctic) that included the Antarctic Specially Protected Area No. 128 (ASPA 128) were designed. The vegetation in the 7.5 km2 area was mapped in ultra-high-resolution(<5cm and DEM of 0.25m GSD), and from the Normalized Difference Vegetation Index (NDVI), four broad vegetation units were extracted: “dense moss carpets” (covering 0.14 km2 ,0.8%ofASPA128), “Sanionia uncinata moss bed” (0.31 km2 , 1.7% of ASPA 128), “Deschampsia antarctica grass meadow” (0.24 km2,1.3% of ASPA 128), and “Deschampsia antarctica–Usnea antarctica heath” (1.66 km2,9.4% of ASPA 128). Our results demonstrate that the presented UAV BVLOS–based surveys are time-effective (single flight lasting 2.5 h on a distance of 300 km) and cost-effective when compared to classical field-based observations and are less invasive for the ecosystem. Moreover, unmanned airborne vehicles significantly improve security, which is of particular interest in polar region research. Therefore, their development is highly recommended for monitoring areas in remote and fragile environments. KEYWORD

Mapping Glacier Forelands Based on UAV BVLOS Operation in Antarctica

The aim of this article is to show geomorphological mapping of remote Antarctic locations usingimagestakenbyafixed-wingunmannedaerialvehicle(UAV)duringtheBeyondVisualLineof Sight (BVLOS) operations. We mapped landform assemblages developed in forelands of Ecology Glacier (EGF), Sphinx Glacier (SGF) and Baranowski Glacier (BGF) in Antarctic Specially Protected Area No. 128 (ASPA 128) on King George Island (South Shetland Islands) and inferred about glacial dynamics. The orthophoto and digital elevation model allowed for geomorphological mapping of glacial forelands, including (i) glacial depositional landforms, (ii) fluvial and fluvioglacial landforms, (iii) littoral and lacustrine landforms, (iv) bodies of water, and (v) other. The largest area is occupied by ground moraine and glacial lagoons on EGF and BGF. The most profound features of EGF are the largelatero-frontalmoraineridgesfromLittleIceAgeandthefirsthalfofthe20thcentury. Largeareas of ground moraine, frequently fluted and marked with large recessional moraine ridges, dominate on SGF. A significant percentage of bedrock outcrops and end moraine complexes characterize BGF. The landform assemblages are typical for discontinuous fast ice flow of tidewater glaciers over a deformable bed. It is inferred that ice flow velocity decreased as a result of recession from the sea coast, resulting in a significant decrease in the length of ice cliffs and decrease in calving rate. Image acquisition during the fixed-wing UAV BVLOS operation proved to be a very robust technique in harsh polar conditions of King George Island

Study of fauna population changes on Penguin Island and Turret Point Oasis (King George Island, Antarctica) using an unmanned aerial vehicle

An unmanned aerial vehicle (UAV) as an alternative to manned aircrafts is an excellent, less invasive, safe tool, especially in sensitive polar regions. Here we used a fixed-wing UAV to collect data on seabird and pinniped populations in hardly accessible Antarctic areas. The implementation of an auto-piloted UAV equipped with a digital camera (Canon EOS 700D, 35 mm f/2.0 lens) allowed us to collect high-quality material applicable to a quantitative analysis of the fauna populations. A successful photogrammetric mission, at an altitude of 550 m above sea level, was accomplished during one Beyond Visual Line of Sight flight above hard-to-access Penguin Island and Turret Point Oasis (King George Island). Obtained selected RGB images were processed to generate a panoramic image stitch with resolution of 0.07 m ground sampling distance. A total of 4290 (SD = 33.08) breeding individuals of two penguin species, Adélie (Pygoscelis adeliae) and chinstrap (Pygoscelis antarcticus), 426 (SD = 7.78) individuals of the southern elephant seal (Mirounga leonina) and 6 individuals of the Weddell seal (Leptonychotes weddellii) were identified in both study areas. Additionally, 222 (SD = 2.0) individuals of the southern giant petrel (Macronectes giganteus) and 76 (SD = 1.0) of the Antarctic shag (Phalacrocorax atriceps bransfieldensis) in the Turret Point area were recognized. The presented observations on the natural history of the investigated fauna together with the available literature may be useful in future research on population trends. A comparison with available historical data for both investigated areas suggests a decrease of 68.29% in both penguin species in the 1980–2016 period. The presented results confirmed that UAVs are useful for remote census work for Antarctic seabirds

Application of UAV BVLOS remote sensing data for multi-faceted analysis of Antarctic ecosystem

A photogrammetric flight was performed in December 2016 as BVLOS (Beyond Visual Line of Sight) operation over Penguin Island (South Shetland Islands, Western Antarctica). Images were taken by the PW-ZOOM fixed-wing UAV equipped with a digital SLR Canon 700D camera. The flight was performed at 550 m ASL and covered a total distance of 231.58 km. The plane takeoff and landing site was near the H. Arctowski Polish Antarctic Station (Arctowski) on King George Island, South Shetlands. The main aim of the mission was to collect environmental data to estimate the size of penguin and pinniped breeding populations and to map vegetation cover and landforms. The plane returned to Arctowski with 1630 images of Penguin Island with the ground sample distance (GSD) lower than 0.07 m. The analysis of developed ortophoto allowed us to locate and identify individuals of two penguin species (Adélie and chinstrap), and individuals of two species of pinnipeds (Southern elephant seal and Weddell seal). Three types of tundra communities were mapped together with numerous landforms such as: volcanic, mass movement, fluvial, coastal and aeolian ones. The UAV BVLOS photogram-metric operation proved to be very robust in gathering valuable qualitative and quantitative data necessary for monitoring distant and isolated polar environments

Improving settlement selection for small-scale maps using data enrichment and machine learning

Acquiring and formalizing cartographic knowledge still is a challenge, especially when the generalization process concerns small-scale maps. We concentrate on the settlement selection process for small-scale maps, with the aim of rendering it more holistic, and making methodological contributions in four areas. First, we show how written specifications and rules can be validated against the actual published map products, thus pointing to gaps and potential improvements. Second, we use data enrichment based on supplementing information extracted from point-of-interest data in order to assign functional importance to particular settlements. Third, we use machine learning (ML) algorithms to infer additional rules from existing maps, thus making explicit the deep knowledge of cartographers and allowing to extend the cartographic rule set. And fourth, we show how the results of ML can be transformed into human-readable form for potential use in the guidelines of national mapping agencies. We use the case of settlement selection in the small-scale maps published by the Polish national mapping agency (GUGiK). However, we believe that the methods and findings of this paper can be adapted to other environments with minor modifications