This paper presents the process of creating a model for automated georeferencing of geo- images using image matching technology, an increasingly popular computer vision concept that has not received proper attention in cartography to date. LoFTR (Local Feature Matching with Transformers), a new approach to find and match key points in pairs of images was used as a basis for the developed model. At the first stage, a model architecture and successive stages of input data processing were defined. At the second stage, the model was implemented as a program in accordance with the previously outlined steps. At the third stage, the resulting model was tested on several pairs of geoimages to further evaluate its effectiveness and applicability in various scientific tasks. Results show that the developed model provides a universal algorithm for automated georeferencing of geo-images, demonstrating high-quality results

The European territory of Russia (ETR) is characterised by a variety of natural conditions and diverse water use. The region under consideration is also of great interest due to the fact that the observed climatic changes here also significantly influence changes in the water regime of rivers. To integrate, display and analyze data on the water regime of the rivers of the ETR and its changes for scientific and educational purposes, hydrologists and cartographers of the Lomonosov Moscow State University developed a web application “Water regime of the rivers of the ETR”.

Global small-scale hydrological modeling datasets are in demand in many geosciences. The results of corresponding simulations include flow directions, catchment area, watershed delineation and stream networks. Regardless of the method of obtaining global product, one will face the task of processing at least continent-scale datasets, which may be time-consuming or hardware-expensive. The recent research on hydrological modeling shows that calculations performed on a hexagonal mesh grid outperformed those on a rectangular one. Therefore, there is increasing interest in globalscale hydrological simulations on hexagonal grids. Discrete global grid systems (DGGS) which are spatial reference systems that use a hierarchy of equal area tessellations to partition the surface of the spherical Earth into grid cells; it seems to be an efficient way to manage big geospatial data. There are studies where hydrological algorithms are successfully applied on hexagonal DGGS, although locally. This research presents an algorithm for parallel computation of flow directions and upslope area on the hexagonal DGGS using the example of the African hydrological system. Referring to the hierarchical nature of DGGS, we cut the study area into tiles along the cells’ boundaries of one of the small-scale levels. Hydrological modeling is then performed on the desired level child cells of each tile. Afterwards the results are stitched into a single coverage. This study is practical not only for hydrological analysis, but also for combining the results of raster algebra analysis in any other areas

The authors analyze the change in the amount of information at each level of hexagonal discrete global grid systems with an aperture of 7. They provide mechanisms for sampling spatial data and changing their granularity through hierarchical transitions between levels. The resolution is related to the volume of spatial data that can be displayed with the current grid. Three metrics are used to estimate the parameter having quantitative findings on the built-up areas and qualitative land use-and-cover data as an example. The results showed that the amount of information decreases non-linearly with increasing grid cell size; the nature of the change differs for different data types and aggregation methods. The study led to the conclusion that it is possible to predict the number of levels within which the information content reduces insignificantly with a cutback in detail for a specific DGGS configuration and data type

The vulnerability of urban ecosystems to global climate change becomes a key issue in research and political agendas. Urban green infrastructures (UGIs) are widely considered as a nature-based solution to mitigate climate change and adapt to local urban climate anomalies in cities. However, UGI-induced cooling effect depends on the size, location and geometry of green spaces, and such dependencies remain overlooked. This research aimed to investigate the cooling effect of UGIs of different size under extreme conditions of 2021 summer heat wave for the case of Moscow megacity (Russia) using a numerical mesoclimatic model COSMO. UGIs objects were assigned to one of the four size categories (S, M, L and XL) based on their area. Their cooling effects at the local, non-local and city scales were evaluated based on comparison between the model outcomes for the realistic land cover and simulations for which UGI of a particular size category were replaced by the built-up areas typical for their surroundings. The highest cooling effect was observed for XL size UGIs, which reduced the local heat-wave-averaged air temperatures by up to 3.4 degrees C, whereas for the S size UGIs it did not exceed 2 degrees C. The cooling effectiveness for XL category was higher than for S category by 23 % inside the green spaces (locally), by 40-90 % in the buffer zones around the green space (non-locally) and by 35 % for the whole city. More effective cooling of large UGIs is partially explained by their stronger park breeze effect, i.e., impact on the airflow increasing the divergence over green spaces. However, when standardized to the population affected by cooling, the M size UGIs made the strongest contribution to the thermal environment where people live and work. The stronger non local cooling induced by the largest UGI objects cannot compensate for their remoteness from the built environment.

Digital topographic maps are created in a series of scales from large to small, and the underlying spatial data is commonly organized as a multiscale database consisting of several levels of detail (LoDs). Spatial density of features (or spatial objects) in such database varies both between LoDs (coarser levels are less densely populated with features) and within each LoD (feature density changes over the area). While the former type of density variation is caused by generalization, the latter one is mainly conditioned by geographic location and its properties, such as landscape complexity or fraction of urban areas. Since topographic database LoDs are derived using different data sources and generalization techniques, there is a need for a method that can help with automated evaluation of resulting feature density in terms of its appropriateness for the specified location and level of detail. This paper provides such method by uncovering dependencies between the location properties and the density of spatial data in multiscale topographic database. Changes in feature density are modeled as a function of spatial (landscape complexity and terrain ruggedness) and non-spatial (land cover types ratio) measures estimated via independent data sources. Resulting model predicts how much higher or lower is the expected spatial density of features over the area in comparison to the average density for the LoD. This information can be used further to assess the fitness of the data to the desired level of detail of the topographic map.

The main parameters of wind waves in the World Ocean are connected with global climate change. Renewable energy technologies, intensive shipping, fishery, marine infrastructure, and many different human marine activities in the coastal zone and open sea need knowledge about the wind-wave climate. The main motivation of this research is to share various wind wave parameters with high spatial resolution in the coastal zone via a modern cartographic web atlas. The developed atlas contains information on 13 Russian Seas, including the Azov, Black, Baltic, Caspian, White, Barents, Kara, Laptev, East Siberian, Chukchi, Bering Seas, the Sea of Okhotsk, and the Sea of Japan/East Sea. The analysis of wave climate was based on the results of wave modeling by WAVEWATCH III with input NCEP/CFSR wind and ice data. The web atlas was organized using the classic three-tier architecture, which includes a data storage subsystem (database server), a data analysis and publishing subsystem (GIS server), and a web application subsystem that provides a user interface for interacting with data and map services (webserver). The web atlas provides access to the following parameters: mean and maximum significant wave height, wave length and period, wave energy flux, wind speed, and wind power. The developed atlas allows changing the map scale (zoom) for detailed analysis of wave parameters in the coastal zones where the wave model spatial resolution is 300–1000 m.

River hydrograph separation is one of the most important operations applied to the streamflow data. Numerous separation techniques and and their software implementations have been developed so far. In operational practice of Russian hydrological organizations and research institutes an event-based approach is commonly used for the hydrograph separation. Different meteorological events such as temperature transition through zero and rains are recognized in meteorological data, and then the corresponding changes in river hydrograph are identified, which eventually helps to attribute each peak in hydrograph with corresponding genetic component. The base flow component is traditionally defined according to Kudelin’s approach, taking into consideration different schemes of surface-ground water runoff interaction. In contrast, the most widespread separation approach in Western school is filtering-based. Lyne-Hollick, Maxwell, Boughton, Jakeman, Chapman and some more sophisiticated filters can be applied to separate the flow into quick and base. Results of two approaches are quite different, especially in terms of the baseflow component. In current study we present the updated open-source grwat R package, which puts both worlds together. It contains both the genetic event based and filtering-based hydrograph separation approaches with the ability to mix them together. In particular, applying the filtering-based separation inside the detected genetic events provides curve of the baseflow well corresponding to tracer-based studies. The second novelty of the package is the intellectual procedure for determination of the second-order events that complicate the freshet (seasonal) flood, such as rain floods. Finally, the updated package contains the internal spatial database of hydrograph separation parameters which is obtained over the European territory of Russia through experimental work. This database allows automated selection of the optimal separation parameters based on the location of the river gauge supplied by package user. The database can be extended to other regions of the world through collaborative work of package users. The study was supported by the Russian Science Foundation grant No. 19-77-10032

One of the key applications of digital elevation models (DEMs) is cartographic relief presentation. DEMs are widely used in mapping, most commonly in the form of contours, hypsometric tints, and hill shading. Recent advancements in the coverage, quality, and resolution of global DEMs facilitate the overall improvement of the detail and reliability of terrain-related research. At the same time, geographic problem solving is conducted in a wide variety of scales, and the data used for mapping should have the corresponding level of detail. Specifically, at small scales, intensive generalization is needed, which is also true for elevation data. With the widespread accessibility of detailed DEMs, this principle is often violated, and the data are used for mapping at scales far smaller than what is appropriate. Small-scale relief shading obtained from fine-resolution DEMs is excessively detailed and brings an unclear representation of the Earth’s surface instead of emphasizing what is important at the scale of visualization. Existing coarse-resolution global DEMs do not resolve the issue, since they accumulate the maximum possible information in every pixel, and therefore also require reduction in detail to obtain a high-quality cartographic image. It is clear that guidelines and effective principles for DEM generalization at small scales are needed. Numerous algorithms have been developed for the generalization of elevation data represented either in gridded, contoured, or pointwise form. However, the answer to the most important question—When should we stop surface simplification?—remains unclear. Primitive error-based measures such as vertical distance are not effective for cartography, since they do not account for the landform structure of the surface perceived by the map reader. The current paper approached the problem by elaborating the granularity—a newly developed property of DEMs, which characterizes the typical size of a landform represented on the DEM surface. A methodology of estimating the granularity through a landform width measure was conceptualized and implemented as software. Using the developed program tools, the optimal granularity was statistically learned from DEMs reconstructed for multiple fragments of manually drawn 1:200,000, 1:500,000, and 1:1,000,000 topographic maps covering different relief types. It was shown that the relative granularity should be 5–6 mm at the mapping scale to achieve the clearness of relief presentation typical for manually drawn maps. We then demonstrate how the granularity measure can be used effectively as a constraint during DEM generalization. Experimental results on a combination of contours, hypsometric tints, and hill shading indicated clearly that the optimal level of detail in small-scale cartographic relief presentation can be achieved by DEM generalization constrained by granularity in combination with fine DEM resolution, which facilitates high-quality rendering.

Abstract. Empirical study of the isotopic features of river runoff were conducted at three hydrological posts in three different river basins: the Zakza river in the center of East European Plane (southwest of Moscow), the Dubna river (north of Moscow) and the Sosna Bystraya river in the south of central region. Samples of river water, groundwater, and precipitation for the October 2019–October 2021 were collected at weekly intervals. At total 332 samples of river water, 275 samples of groundwater and 194 samples of precipitation were collected. Precipitation was collected as an integral sample of all precipitation fallen during the week before sampling date. For each precipitation samples, the total amount of precipitation and air temperature, weighted by precipitation amount, are given according to weather station in river basin. During the observation period, there were two completely different conditions in terms of runoff formation. First, from October 2019 to October 2020, there was an unusually low spring freshet followed by a big rain flood in July. From October 2020–October 2021, there was a normal intra-annual flow pattern with high spring freshet. A significant supply of melted snow during spring freshet is the key factor influencing water regimes in these three river basins; varying degrees of anthropogenic flow regulation are also present. The new height frequency and complete data of stable isotope signature of river runoff component can help to study the response of a river runoff to climate change.

Benzo[a]pyrene (BaP) is one of the priority pollutants in the urban environment. For the first time, the accumulation of BaP in road dust on different types of Moscow roads has been determined. The average BaP content in road dust is 0.26 mg/kg, which is 53 times higher than the BaP content in the background topsoils (Umbric Albeluvisols) of the Moscow Meshchera lowland, 50 km east of the city. The most polluted territories are large roads (0.29 mg/kg, excess of the maximum permissible concentration (MPC) in soils by 14 times) and parking lots in the courtyards (0.37 mg/kg, MPC excess by 19 times). In the city center, the BaP content in the dust of courtyards reaches 1.02 mg/kg (MPC excess by 51 times). The accumulation of BaP depends on the parameters of street canyons formed by buildings along the roads: in short canyons (< 500 m), the content of BaP reaches maximum. Relatively wide canyons accumulate BaP 1.6 times more actively than narrow canyons. The BaP accumulation in road dust significantly increases on the Third Ring Road (TRR), highways, medium and small roads with an average height of the canyon > 20 m. Public health risks from exposure to BaP-contaminated road dust particles were assessed using the US EPA methodology. The main BaP exposure pathway is oral via ingestion (> 90% of the total BaP intake). The carcinogenic risk for adults is the highest in courtyard areas in the south, southwest, northwest, and center of Moscow. The minimum carcinogenic risk is characteristic of the highways and TRR with predominance of nonstop traffic.

The problems of climate change, high-impact weather phenomena and human thermal comfort in urban areas nowadays receives more and more attention not only from urban scientific community, but also from professionals in related fields as well as from general public. Today, publicly available weather-focused web services and applications experience rapid development and expansion. However, such services focused on urban climate are very rare and have limited usability. In this presentation, we share our experience in development of web-mapping application for urban climate monitoring & research for Moscow megacity in Russia. We aim to develop the web-application which provides observation-based evidence about current and historical weather conditions and human thermal comfort in Moscow region. Such application could be a valuable tool not only for urban climate researchers, but also for citizens planning their outdoor activity, weather and climate enthusiasts, weather-focused media, popularization of science, school and university education, etc. Previously, we have developed a prototype of such web-mapping application, which collects and maps observations at official weather stations and crowdsourced observations at Netatmo citizen weather stations (Varentsov et al., 2020). Application backend includes software for automated data collection, PostgreSQL database, data preprocessing tools (quality control for Netatmo data, spatial interpolation, simple model for on-the-fly calculations of Universal Thermal Climate Index representing human thermal comfort), GIS-server Geoserver for showing raster data. The application frontend is based on the OpenLayers web mapping library. The database is accessed by using the supplementary Node.js server application. Current stage of development includes several new tasks. Firstly, we plan to increase the timespan of historical data available in the application by 2005-2022. Secondly, we plan to develop interactive tools for data analysis, including time series plots and temporal averaging. Finally, we plan to supplement the application by the catalogue of illustrative weather events, such as cases with intense urban heat island, extreme precipitation, and dangerous thermal stress, and to provide popular description of such cases. The recent version of web-application under development is available at http://carto.geogr.msu.ru/mosclim2/. Acknowledgements: Development of web-application was supported by Russian Geographic Society under grant No. 03/2021-Р. Selection of intense precipitation cases for catalogue of illustrative weather events was supported by the grant of President of Russian Federation for young PhD scientists No. МК-5988.2021.1.5. Data analysis performed by Mikhail Varentsov was also funded by Non-commercial Foundation for the Advancement of Science and Education INTELLECT. Reference: Varentsov M. I., Samsonov T. E., Kargashin P. E., Korosteleva P. A., Varentsov A. I., Perkhurova A. A., & Konstantinov P. I. (2020). Citizen weather stations data for monitoring applications and urban climate research: an example of Moscow megacity. IOP Conference Series: Earth and Environmental Science, 611(1), 012055. https://doi.org/10.1088/1755-1315/611/1/012055

An algorithm for automated graph-analytical separation of hydrograph, underlying grwat software package is described in detail and analyzed. This system is designed for separation of runoff hydrograph into base runoff, spring f lood, rain and thaw runoff events by the method proposed by B.I. Kudelin. The starts and ends of water regime phases are identified by algorithms for distinguishing breaks on the hydrograph and analyzing their meeting some criteria for passage of water regime phases, based on the physics of runoff formation in river basins. The input data are daily series of water discharges, air temperatures, and rainfall values. Weather data are used as an indicator and means to refer hydrograph peaks to groups of events, i.e., thaws or rain (mixed) f loods, and to determine the start of winter low-water season. A series of calibrated parameters are used to specify criteria for phase separation. The program calculates 52 annual runoff characteristics, as well as more than 30 characteristics for each individual f lood: time characteristics (the dates of start, end, and maximum; the duration, and the time of rise), discharge characteristics (maximal discharge, f lood volume, water discharge before f lood start, the excess of maximal discharge over basic f lood level), various weather characteristics (the regimes of air temperature and precipitation before the f lood and during it), and others. The values of calibrated parameters of grwat were found to be stable for the majority of rivers throughout the calculation period, and their values were similar for rivers with the same type of water regime and size. Algorithm gwart also showed high tolerance to changes in the values of calibration parameters. Recommendations are given for specifying their values. The main causes of errors in determination of water regime phases and the development perspectives of the algorithm are discussed.

This volume is the much anticipated update of Menno-Jan Kraak and Ferjan Ormeling's popular academic textbook-first published in 1996, with subsequent editions in 2003 and 2010.My review will focus mainly on how much the book has changed since its last incarnation, and how well the text reflects recent technological advancements in cartography, as readers are likely most curious about these aspects.

The paper reveals dependencies between the character of the line shape and combination of constraining metrics that allows comparable reduction in detail by different geometric simplification algorithms. The study was conducted in a form of the expert survey. geometrically simplified versions of three coastline fragments were prepared using three different geometric simplification algorithms—Douglas-peucker, Visvalingam-Whyatt and Li-Openshaw. Simplification was constrained by similar value of modified hausdorff distance (linear offset) and similar reduction of number of line bends (compression of the number of detail elements). Respondents were asked to give a numerical estimate of the detail of each image, based on personal perception, using a scale from one to ten. The results of the survey showed that lines perceived by respondents as having similar detail can be obtained by different algorithms. however, the choice of the metric used as a constraint depends on the nature of the line. Simplification of lines that have a shallow hierarchy of small bends is most effectively constrained by linear offset. As the line complexity increases, the compression metric for the number of detail elements (bends) increases its influence in the perception of detail. For one of the three lines, the best result was consistently obtained with a weighted combination of the analyzed metrics as a constraint. None of the survey results showed that only reducing the number of bends can be used as an effective characteristic of similar reduction in detail. It was therefore found that the linear offset metric is more indicative when describing changes in line detail.

Despite the fact, that against the background of global warming the Russian Arctic is still a region with severe winters and cool summers; the likelihood of thermal stress conditions in summer is also increasing. At the same time, urban conditions can significantly affect the human heat perception due to the appearance of the urban heat island effect and other factors. Using the example of the city of Nadym (Yamalo-Nenets Autonomous Okrug), the authors have assessed the possibility of the summer urban heat stress occurrence and analyzed its spatial heterogeneity. The article presents the detailed modeling results of the meteorological regime of the city within the framework of the COSMO-CLM model and the assessment of bioclimatic comfort using the Physiologically Equivalent Temperature (PET) index and Universal Thermal Climate Index (UTCI). During periods of the extremely hot weather events in Nadym, the territory meso- and microclimatic mosaicism clearly manifests itself. In anthropogenically altered territories, the frequency of strong heat stress events can exceed that in the background areas by 1.7 times. Urban planning solutions should take into account not only the climatic resistance of Arctic cities to the winter cold, but also be adapted to the occurrence of summer heat.