The article presents the results of an analysis of the distribution and nature of the use of second suburban housing (second homes) in the Moscow capital region using an indicative approach based on data from mobile network operators. The research methodology included a multiscale analysis of fluctuations in the nighttime population in several marker time slices, which made it possible to indirectly estimate the usage scale of year-round and seasonal dacha housing. The dacha settlement system of the Moscow capital region forms an extensive and populous spatial structure. In addition to the classic summer residence format, dwellings that are periodically or permanently inhabited during the cold season are gaining in popularity, and the number of such summer residents, according to rough estimates, exceeds 1 mln people. The suburbanization pattern is characterized by pronounced belt-sector segmentation and can be represented as a dacha settlement model with four identified zones according to the mode of suburban housing use. The first, at a distance of 10 km from the Moscow Ring Road (MKAD), is characterized by the dominance of year-round dacha housing and represents focal inclusions of dacha settlements in a dense urbanized continuum. At a distance of 10–20 km, and to west and southwest up to 40 km from the MKAD, year-round dacha housing is widely encountered. Farther, in some places up to 60 km from the MKAD, dachas are used in a mixed summer–winter regime; past 60 km, seasonally inhabited dwellings dominate. In general, the impulsive rhythms show the blurring and interpenetration of boundaries between the city and countryside, as well as the formation of mosaic spatiotemporal residence patterns. At the same time, the gradual spread in the Moscow capital region of the year-round residence format by city dwellers in second homes, while maintaining housing in the city, serves as stark evidence of a generation of dacha innovations here, transforming both traditional Soviet and Western examples of dacha behavior.

Moscow as a world city combines territories with various functional content. At the same time, the complexity of the morphological structure of the capital is supplemented by the high dynamism of the socio-economic processes taking place in it. In this context, an important task is to assess the role of large infrastructure projects, intensifying the processes of transformation of the urban structure and in a short time changing the historically established functional roles of vast urban spaces. The article uses the data of mobile operators to analyze functional changes in the zone of influence of the largest urban megaproject – the Moscow Central Ring (MCC) from 2015 to 2018. The available information on mobile telephony about the distribution of the population at night and daytime allows us to characterize the degree of “dormancy” and “attractiveness” of urban areas near the MCC, and accordingly their functional roles. The analysis showed that during the period under review, the day and night population of 43 municipalities surrounding the MCC showed an equal increase of 0.35 million people with a significant differentiation of its pace in certain areas. The ratio between the day and night population of the areas, as well as its change from 2015 to 2018 allowed to distinguish the characteristic functional types of districts. The typology demonstrated that the role of the MCC in spatial development for the attractive territories of the center and subcenter of Moscow turned out to be significantly less noticeable than for areas located on the side of the MCC external to the city center. This influence was more replaceable in municipalities, where the railway ring became the first type of high-speed off-street transport, as well as in areas that have significant areas of industrial zones, the majority of the observed structural and functional movements in urban morphology are associated with the synergy of renovation.

A feature tracking techniques for sea ice drift retrieval from a pair of sequential satellite synthetic aperture radar (SAR) images are discussed. The Scale Invariant Feature Transform (SIFT), its alternative called ORB and A-KAZE features are selected for the intercomparison. The experimental results obtained for dual polarized Sentinel-1 C-SAR Extended Wide Swath mode data showed high relevance of feature tracking using nonlinear scale-spaces: A-KAZE. The approach exploits the benefits of nonlinear multi-scale image representations using A-KAZE features, which is a method that detects and describes image features in an anisotropic scale space that preserves important object boundaries while adaptively removing noise and small image details. It found that feature tracking using nonlinear scale-spaces on SAR images is preferable compared to other existing feature tracking alternatives that make use of Gaussian or linear scale spaces.

An open software implementation of the algorithm for retrieving the land surface temperature (LST) from Landsat 8 remote sensing satellite data is presented using the split-window algorithm, supplemented by a covariance-variational technique to modeling the water-vapor content in the atmosphere. The implementation also uses the Simplified and Robust Surface Reflectance Estimation Method (SREM), a physical-based atmospheric correction method, and the FMASK cloud and cloud-shadow detection algorithm. All components of the complex algorithm are fully automated and do not require additional information, including external data on the state of the atmosphere. The implementation of the algorithm has been validated at various settings on the basis of ten ground stations in the United States that publish data on observations of the LST with a high time resolution; the average absolute error according to its results was 1.1°C. The software component is developed in Python and is available in the public repository https://github.com/eduard-kazakov/Landsat8_LST_PSWA; the source code is distributed under an open license.

Server-side processing is principal for most of the current Web-based geospatial data processing tools. However, in some cases the client-side geoprocessing may be more convenient and acceptable. This study is dedicated to the development of methodology and techniques of Web services elaboration, which allow the client-side geoprocessing also. The practical objectives of the research are focused on the remote sensing data processing, which are one of the most resource-intensive data types. The idea underlying the study is to propose such geoprocessing Web service schema that will be compatible with the current serveroriented Open Geospatial Consortium standard (OGC WPS standard), and additionally will allow to run the processing on the client, transmitting processing tool (executable code) over the network instead of the data. At the same time, the unity of executable code must be preserved, and the transmitted code should be the same to that is used for server-side processing. This unity should provide unconditional identity of the processing results that performed using of any schema. The appropriate services are pointed by the authors as a Hybrid Geoprocessing Web Services (HGWSs). The common approaches to architecture and structure of the HGWSs are proposed at the current stage as like as a number of service prototypes. For the testing of selected approaches, the geoportal prototype was implemented, which provides access to created HGWS. Further works are conducted on the formalization of platform independent HGWSs implementation techniques, and on the approaches to conceptualization of theirs safe use and chaining possibilities. The proposed schema of HGWSs implementation could become one of the possible solutions for the distributed systems, assuming that the processing servers could play the role of the clients connecting to the service supply server. The study was partially supported by Russian Foundation for Basic Research (RFBR), research project No. 13-05-12079 ofi_m.

To promote sustainable development and guide the responsible use of natural ecosystems, the United Nations introduced the concept of ecosystem accounting. Ecosystem services are key components of ecosystem accounting. Water-related ecosystem services (ES) are of primary importance for Armenia due to relatively dry climate, and dependence on irrigation water for agriculture. This study aims to conduct a pilot-level quantitative scoping assessment and mapping of key water-related regulating ES in accordance with the SEEA-EA guidelines, and to offer recommendations to initiate their accounting in Armenia. We used three Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models—Seasonal Water Yield, Sediment Delivery Ratio, and Urban Flood Risk Mitigation. Input data for these models were sourced from global and national databases, as well as ESRI land cover datasets for 2017 and 2023. Government-reported data on river flow and water consumption were used to assess the ES supply–use balance. The results show that natural ecosystems contribute between 11% and 96% of the modeled ES, with the strongest impact on baseflow supply and erosion prevention. The average current erosion is estimated at 2.3 t/ha/year, and avoided erosion at 46.4 t/ha/year. Ecosystems provide 93% of baseflow, with an average baseflow index of 34%, while on bare ground it is only 3%. Changes in land cover from 2017 to 2023 have resulted in alterations across all assessed ES. Comparison of total water flow and baseflow with water consumption revealed water-deficient provinces. InVEST models show their general operability at the scoping phase of ecosystem accounting planning. Advancing ES accounting in Armenia requires model calibration and validation using local data, along with the integration of InVEST and hydrological and meteorological models to account for the high diversity of natural conditions in Armenia, including terrain, geological structure, soil types, and regional climatic differences.