Geographic Objects Research Articles

Exploring semantic elements for urban scene recognition: Deep integration of high-resolution imagery and OpenStreetMap (OSM)

Urban scenes refer to city blocks which are basic units of megacities, they play an important role in citizens’ welfare and city management. Remote sensing imagery with largescale coverage and accurate target descriptions, has been regarded as an ideal solution for monitoring the urban environment. However, due to the heterogeneity of remote sensing images, it is difficult to access their geographical content at the object level, let alone understanding urban scenes at the block level. Recently, deep learning-based strategies have been applied to interpret urban scenes with remarkable accuracies. However, the deep neural networks require a substantial number of training samples which are hard to satisfy, especially for high-resolution images. Meanwhile, the crowed-sourced Open Street Map (OSM) data provides rich annotation information about the urban targets but may encounter the problem of insufficient sampling (limited by the places where people can go). As a result, the combination of OSM and remote sensing images for efficient urban scene recognition is urgently needed. In this paper, we present a novel strategy to transfer existing OSM data to high-resolution images for semantic element determination and urban scene understanding. To be specific, the object-based convolutional neural network (OCNN) can be utilized for geographical object detection by feeding it rich semantic elements derived from OSM data. Then, geographical objects are further delineated into their functional labels by integrating points of interest (POIs), which contain rich semantic terms, such as commercial or educational labels. Lastly, the categories of urban scenes are easily acquired from the semantic objects inside. Experimental results indicate that the proposed method has an ability to classify complex urban scenes. The classification accuracies of the Beijing dataset are as high as 91% at the object-level and 88% at the scene level. Additionally, we are probably the first to investigate the object level semantic mapping by incorporating high-resolution images and OSM data of urban areas. Consequently, the method presented is effective in delineating urban scenes that could further boost urban environment monitoring and planning with high-resolution images.

A clique-based approach for co-location pattern mining

Co-location pattern mining refers to the task of discovering the group of features (geographic object types) whose instances (geographic objects) are frequently located close together in a geometric space. Current approaches on this topic adopt a prevalence threshold (a measure of a user's interest in a pattern) to generate prevalent co-location patterns. However, in practice, it is not easy to specify a suitable prevalence threshold. Thus, users have to repeatedly execute the program to find a suitable prevalence threshold. Besides, the efficiency of these approaches is limited because of the expensive cost of identifying row-instances of co-location patterns. In this paper, we propose a novel clique-based approach for discovering complete and correct prevalent co-location patterns. The proposed approach avoids identifying row-instances of co-location patterns thus making it much easier to find a proper prevalence threshold. First, two efficient schemas are designed to generate complete and correct cliques. Next, these cliques are transformed into a hash structure which is independent of the prevalence threshold. Finally, the prevalence of each co-location pattern is efficiently calculated using the hash structure. The experiments on both real and synthetic datasets show the efficiency and effectiveness of our proposed approaches.

Impact of the Scale on Several Metrics Used in Geographical Object-Based Image Analysis: Does GEOBIA Mitigate the Modifiable Areal Unit Problem (MAUP)?

Using two GEOBIA (Geographical Object Based Image Analysis) algorithms on a set of segmented images compared to grid partitioning at different scales, we show that statistical metrics related to both objects and sets of pixels are (more or less) subject to the Modifiable Areal Unit Problem. Subsequently, even in a same spatial partition, there may be a bias in statistics describing the objects due to some size effect of the pixel samples. For instance, pixels homogeneity based on Grey Level Cooccurrence Matrices (GLCM), Landscape Shape Index, entropy, object compacity, perimeter/area ratio are studied according to scale. The approach consists in studying the behavior of a given statistical metrics through scales and to compare the results on several image segmentations, according to different partitioning processes, from GEOBIA (Baatz & Schäpe algorithm and Self Organizing Maps) or using reference grids. We finally discuss about the relationship between GEOBIA metrics and scale. By analysing object shape and pixels composition from different metrics points of views, we show that GEOBIA does not always mitigate the Modifiable Areal Unit Problem.

Fully Convolutional Networks and Geographic Object-Based Image Analysis for the Classification of VHR Imagery

Land cover Classified maps obtained from deep learning methods such as Convolutional neural networks (CNNs) and fully convolutional networks (FCNs) usually have high classification accuracy but with the detailed structures of objects lost or smoothed. In this work, we develop a methodology based on fully convolutional networks (FCN) that is trained in an end-to-end fashion using aerial RGB images only as input. Skip connections are introduced into the FCN architecture to recover high spatial details from the lower convolutional layers. The experiments are conducted on the city of Goma in the Democratic Republic of Congo. We compare the results to a state-of-the art approach based on a semi-automatic Geographic object image-based analysis (GEOBIA) processing chain. State-of-the art classification accuracies are obtained by both methods whereby FCN and the best baseline method have an overall accuracy of 91.3% and 89.5% respectively. The maps have good visual quality and the use of an FCN skip architecture minimizes the rounded edges that is characteristic of FCN maps. Additional experiments are done to refine FCN classified maps using segments obtained from GEOBIA generated at different scale and minimum segment size. High OA of up to 91.5% is achieved accompanied with an improved edge delineation in the FCN maps, and future work will involve explicitly incorporating boundary information from the GEOBIA segmentation into the FCN pipeline in an end-to-end fashion. Finally, we observe that FCN has a lower computational cost than the standard patch-based CNN approach especially at inference.

An Algorithm based on the Weighted Network Voronoi Diagram for Point Cluster Simplification

Points on maps that stand for geographic objects such as settlements are generally connected by road networks. However, in the existing algorithms for point cluster simplification, points are usually viewed as discrete objects or their distances are considered in Euclidean spaces, and therefore the point cluster generalization results obtained by these algorithms are sometimes unreasonable. To take roads into consideration so that point clusters can be simplified in appropriate ways, the network Voronoi diagram is used and a new algorithm is proposed in this paper. First, the weighted network Voronoi diagram is constructed taking into account the weights of the points and the properties of the related road segments. Second, the network Voronoi polygons are generated and two factors (i.e., the area of the network Voronoi polygon and the total length of the dilated road segments in the polygon) are considered as the basis for point simplification. Last, a Cartesian coordinate system is built based on the two factors and the point clusters are simplified by means of the “concentric quadrants”. Our experiments show that the algorithm can effectively and correctly transmit types of information in the process of point cluster simplification, and the results are more reasonable than that generated by the ordinary Voronoi-based algorithm and the weighted Voronoi-based algorithm.

Three-dimensional densely connected convolutional network for hyperspectral remote sensing image classification

Hyperspectral remote sensing images (HSIs) are rich in spatial and spectral information, thus they help to enhance the ability to distinguish geographic objects. In recent years, great progress have been made in image classification using deep learning (such as 2D-CNN and 3D-CNN). Compared with traditional machine learning methods, deep learning methods can automatically extract the abstract features from low to high levels and convert the images into more easily recognizable features. Most HSI classification tasks focus on spectral information but often ignore the rich spatial structures in HSIs, leading to a low classification accuracy. Moreover, most supervised learning methods use shallow structures in HSI classifications and hence exhibit weak performance in finding sparse geographic objects. We proposed to use the three-dimensional (3-D) structure to extract spectral–spatial information to build a deep neural network for HSI classifications. Based on DenseNet, the 3D densely connected convolutional network was improved to learn spectral-spatial features of HSIs. The densely connected structure can enhance feature transmission, support feature reuse, improve information flow in the network, and make deeper networks easier to train. The 3D-DenseNet has a deeper structure than 3D-CNN, thus it can learn more robust spectral–spatial features from HSIs. In fact, the deeper network structure has a regularized effect, which can effectively reduce overfitting on small sample datasets. The network uses HSIs instead of feature engineering as input data and is trained in an end-to-end manner. The experimental results of this model on the Indian Pines datasets and the Pavia University datasets show that deeper neural networks further improve the classification of complex objects, especially in the areas where geographic objects are sparse. It effectively improves the classification accuracy of HSIs.

Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective

Image segmentation is a critical and important step in (GEographic) Object-Based Image Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly dependent on the quality of image segmentation. Segmentation has been used in remote sensing image processing since the advent of the Landsat-1 satellite. However, after the launch of the high-resolution IKONOS satellite in 1999, the paradigm of image analysis moved from pixel-based to object-based. As a result, the purpose of segmentation has been changed from helping pixel labeling to object identification. Although several articles have reviewed segmentation algorithms, it is unclear if some segmentation algorithms are generally more suited for (GE)OBIA than others. This article has conducted an extensive state-of-the-art survey on OBIA techniques, discussed different segmentation techniques and their applicability to OBIA. Conceptual details of those techniques are explained along with the strengths and weaknesses. The available tools and software packages for segmentation are also summarized. The key challenge in image segmentation is to select optimal parameters and algorithms that can general image objects matching with the meaningful geographic objects. Recent research indicates an apparent movement towards the improvement of segmentation algorithms, aiming at more accurate, automated, and computationally efficient techniques.

РЕАЛІЗАЦІЯ КОМПЕТЕНТНІСНОГО ПІДХОДУ В СУЧАСНІЙ ШКОЛІ ШЛЯХОМ ВСТАНОВЛЕННЯ МІЖПРЕДМЕТНИХ ТА КУЛЬТУРОЛОГІЧНИХ ЗВ’ЯЗКІВ ЗАСОБАМИ ХУДОЖНЬОЇ ЛІТЕРАТУРИ

The article is devoted to the description of a methodology for the implementation of interdisciplinary and cultural links with fiction in contemporary school during the study of basic disciplines on an example of a geography course. The advantages of using literary works in class are determined; the expediency of their systematic use is substantiated; the general methodical features of the fiction usage at geography lessons are revealed. Scilicet: the directions of the literary works usage at the lessons, the methodical features of the use of large volume of works, their separate plot lines, types of tasks for the activization of cognitive activity and interest, development of analytical and logical thinking, the formation of cartographic culture are described. The tasks for the development of analytical thinking on the basis of literary works are aimed at the selection and structuring of geographical information, the explanation of the properties of geographical objects and phenomena, the identification of factors that influence their formation, the compilation of characteristics. For the development of logical thinking the tasks to the artistic works are applied; their content allows to link geographic phenomena and patterns that have already been studied or to discover the new ones. The tasks aimed at the formation of cartographic culture include: tracking the route of on the map according to the plot of the work; the self-made possible routing for the literary heroes; the search of the locations of the described objects and their coordinates on the map.

ОБРАЗНО-МЕТАФОРИЧЕСКАЯ РЕПРЕЗЕНТАЦИЯ ПРИРОДНОГО ЛАНДШАФТА В РЕКЛАМНОМ ТУРИСТИЧЕСКОМ НАРРАТИВЕ

The article is devoted to the study of the figurative-metaphorical means of representing natural landscape in tourism advertising narrative. In the course of the material analysis, it has been found out that most geographical objects are used as a source of the metaphorical representation of natural landscape: forests, mountains, volcanoes, rivers, waterfalls, lakes, seas, oceans, etc. The author shows that metaphors, comparisons, epithets and personification are the most common figurative-metaphorical means of describing natural landscape.

МНОГОСЛОВНЫЕ ТОПОНИМЫ С ЗООНИМИЧЕСКОЙ ОСНОВОЙ В КАРАЧАЕВО-БАЛКАРСКОМ ЯЗЫКЕ И ИХ ЛЕКСИКО-ГРАММАТИЧЕСКАЯ ХАРАКТЕРИСТИКА

The article deals with compound (three-, four-, and five-word) toponyms with the zoonymic basis in the Karachay-Balkar language. Their structural-semantic and grammatical analysis is carried out, for derivative formations it is emphasized with the help of which affixes toponyms of this category are formed. The part-of-speech belonging of appellatives forming toponyms is noted, their motivational features connected with the spatial and parametric characteristics of geographic objects and use in economic activity are presented.

Class-Specific Anchor Based and Context-Guided Multi-Class Object Detection in High Resolution Remote Sensing Imagery with a Convolutional Neural Network

In this paper, the problem of multi-scale geospatial object detection in High Resolution Remote Sensing Images (HRRSI) is tackled. The different flight heights, shooting angles and sizes of geographic objects in the HRRSI lead to large scale variance in geographic objects. The inappropriate anchor size to propose the objects and the indiscriminative ability of features for describing the objects are the main causes of missing detection and false detection in multi-scale geographic object detection. To address these challenges, we propose a class-specific anchor based and context-guided multi-class object detection method with a convolutional neural network (CNN), which can be divided into two parts: a class-specific anchor based region proposal network (RPN) and a discriminative feature with a context information classification network. A class-specific anchor block providing better initial values for RPN is proposed to generate the anchor of the most suitable scale for each category in order to increase the recall ratio. Meanwhile, we proposed to incorporate the context information into the original convolutional feature to improve the discriminative ability of the features and increase classification accuracy. Considering the quality of samples for classification, the soft filter is proposed to select effective boxes to improve the diversity of the samples for the classifier and avoid missing or false detection to some extent. We also introduced the focal loss in order to improve the classifier in classifying the hard samples. The proposed method is tested on a benchmark dataset of ten classes to prove the superiority. The proposed method outperforms some state-of-the-art methods with a mean average precision (mAP) of 90.4% and better detects the multi-scale objects, especially when objects show a minor shape change.

КОНЦЕПТУАЛІЗАЦІЯ ПОНЯТТЯ ГЕОГРАФІЧНИЙ ПРОСТІР У НАУКОВІЙ ЛІТЕРАТУРІ

Space is one of the fundamental concepts of human consciousness. Many sciences use the concept of space to describe their own subject areas. For geography, this concept is basic. By analogy with other sciences, geography has formed its own understanding of space – geographical space. In different historical epochs, people have differently represented space. Today, the most widespread are substantive and relational approaches to the interpretation of space. According to the substantive approach, space is a substance, independent of time and matter that acts next to and independently of them. According to the relational approach, space is understood as systems of relations that are formed between objects in the process of their interaction. Among Ukrainian geographers, E. Marunyak, K. Nemets, Y. Oliynyk, A. Stepanenko, O. Smyrnov, O. Topchiyev, O. Shabliy and others elaborated on the concept of geospace and geospatiality. Geographic space is a set of objects that are ordered on the earth's surface, together with the sum of all their connections and interrelations. It is not just the total sum of the geographical positions of all geographical objects, but a new quality that appears as a result of the general interactions of the objects on the earth’s surface. In interpretations of geographical space, the following common features can be distinguished: geospace is one of the aspects of ordering geographical objects; geospace is a collection of relationships between objects; geographical space is characterized by both discreteness and continuity. Meanwhile, in Western scientific literature the concept of geographical space has not become noticeably widespread. Researchers often use the terms “space” and “social space”. Geospace in English-language scientific literature is understood as the outer space near the Earth, including the upper atmosphere, the ionosphere, and the magnetosphere.

Features of content of the section «Modern political map of the world» in school programs for geography in Transnistria on the border of XX-XXI centuries

The purpose of this article is to study the features of the content of the section «Modern political map of the world» in the modern school curriculum in geography in the PMR, as well as a comparative assessment of the content of school General education programs under the section «Political map of the world», operating in the PMR at the turn of XX-XXI centuries. The main material. Political map – a dynamic spatial system, actively changing under the infl uence of events taking place in the world, which is refl ected in school curricula and textbooks on geography. The content of school curricula of the Soviet period directly depended on the policy and ideology of the time. They provided for the study of documents of the party and the Government on major issues and trends of world development. The content of the section «Political map of the world» in the school programs of Transnistria since the 1990s required updating due to socio - economic and political events of that time. The article presents a comparative analysis of the content of school General education programs under the section «Political map of the world», operating on the territory of PMR at the border of XX-XXI centuries. For comparison, some school programs in geography are taken 1981, 1993, 1998, 2000, 2006, 2016 years. The most significant changes in the content of the theme «Political map of the world» happened at the turn of XX–XXI centuries. The geography pilot program for the 1993 secondary school was developed on the basis of the political and socio–economic events that took place at that time in connection with the collapse of the USSR. Each state that was part of the Union, faced with the problem of further development of education, and had to adapt to new realities. The team of authors of the program initially created an experimental program on geography, taking into account the socio-economic and political situation characteristic of our state in the 90s. For the fi rst time, the authors of the program abandoned the division of countries and regions by political and socio-economic system. The study of the political map and administrative - territorial structure of the countries of the modern world is based on the offi cial classifi cation developed by the UN. The following important questions are suggested for study: – subject and objectives of the study of political geography; – introduced a new concept of «political-territorial organization of society», with its main elements - sovereign States and dependent territories; – the main stages of the formation of the political map of the world and individual regions; – administrative and territorial structure; – typology of countries by administrative-territorial structure, geographical location. It should be emphasized that the program introduces the most important concepts of socio – economic and political geography – «political and geographical position» and «economic and geographical position». Valuable in the program of 1993 is the section «Applications» containing plans-characteristics of economic and geographical objects that are convenient to use in their study. Further, in all subsequent school programs in 1998, 2000, 2006, 2016, the section «Modern political map of the world» in its content has changed little. Conclusions. The analysis confi rms that the most signifi cant changes in the content of the theme «Political map of the world» happened at the turn of XX–XXI centuries. It can be concluded that the content and structure of school programs in geography, and in particular sections related to the study of political geography, is a refl ection of the situation in the world community, national policy and ideology, processes covering the educational space of Russia and CIS countries.

Nazewnicze powroty w kontekście językowych uniwersaliów. Dawne i współczesne nazwy miejscowe o charakterze internacjonalnym

The Return of Names in the Context of Language Universals: Ancient and Contemporary Local Names with an International Character The article concerns the history and unique nature of local names derived from exonyms, such as Alexandria, Spain and Lisbon. It describes both past and contemporary onyms, i.e. the names of housing estates, such as Little Tuscany, and apartment buildings, such as Rome, London and Mont Blanc, which are the continuations of the toponymic model launched in the past. The author embeds this model of names in a broader cultural context by referring to language universals. In addition to the rich collection of the oldest biblical names that have been transferred to present names, transfers of old names can be observed among contemporary names. In the past (in the early nineteenth and twentieth centuries), these were mainly the names of countries and, less frequently, those of cities, lands and geographic objects. Today, toponyms are usually based on the names of European cities, attractive geographic objects (lakes, rivers, islands, mountains, volcanoes) and, more rarely, states. While the names of biblical lands were fascinating and attractive in the past, they are almost absent in contemporary names, and if they are present, they concern culturally fixed images such as that of Eden. Both formerly and today, the creators of this kind of names show a longing for the creation of a new world which is no longer inhabited by God in a strictly religious dimension, but a secular one where happiness, peace and joy are sought. In both characterised spaces, the names transferred serve commemorative functions and also imitate coveted spaces which cannot be physically inhabited but can at least be imitated by their names. Formerly, they were real imago mundi representing sacred places (e.g. names such as Calvary). Today, they are created as part of the contemporary architectural tendency for coherence in planning space, names and design.

Етнокультурна маркованість англійських та українських складних метафоричних номінацій з топонімним компонентом

The article deals with the units in the structura-semantic and comparative aspects. The nominal units are divided as to the toponimical component. Their nominal structure is compared in two languages. The paper suggests a new approach to the contrastive and typological study of the linguistic and cultural information of the phraseologisms with toponimical components. Idiomatic expressions in English and Ukraine and in all others languages may be performed common functions in the sentence. National idioms present a suparate universal feature pertained to all languages. These idioms are formed on the basis of the component parts images characteristic of a definite national community and its languages. A productive model for complex metaphorical names with a toponymic component is the names of states, regions, and US territorial areas through zoosseism and coloration. In the Ukrainian language – the designation of the size of the natural, geographic objects. In the future, it is considered relevant to explore other classes of units with a removable component, which will more fully represent the overall role of their own names in the phrases of non-verbal names. The research defines the motivation basis for the formation of the figurative meaning of the phraseologisms with name components in two languages. To research the national-cultural specificity of semantics idioms with toponimical components is very important and usefull for people. The nominal structure is compared in English and Ukrainian.

Вещь как эталон цвета: образование неосновных цветонаименований в русском языке

The analysis of secondary colour nominations attributing a shade by means of attraction of real images is carried out. The material for the study was “The Unique Reference with Parameters (RGB, HSV, CMYK, hex) and Names of about 1,000 Colours” on the web-site http://tinyurl.ru/services/colour/list. Names of shades of colour are characterized from the point of view of their structural characteristics and motivational characteristics. It is found that colour names with the subject reference may be single-word units, and may provide a simple and comprehensive phrases, the structure of which is not always a colour symbol or a reference to a colour of any object. It is shown that the studied colour nominations are often derived from phytonyms, zoonyms, hydronyms and other words naming objects of living and inanimate nature. It is noted that some of the non-basic colour names are derived from nouns that name personalities, geographical objects, organizations, etc. Usually such colour names are focused on attracting the attention of an educated recipient of speech. The analysis of the material confirms the opinion of other researchers of colour nominations: they believe that colour naming is often based on metaphorical and metonymic transfer of a meaning.

Competence of the cartographic literacy of schoolchildren: essence and methodological foundations of the formation

The purpose of this article is to characterize the theoretical foundations of the cartographic method in school geography and to highlight the competencies of schoolchildren’s cartographic literacy, the analysis of teaching methods for the formation and development of cartographic literacy of schoolchildren in the process of studying geography. The main material. The main attention is paid to the analysis of the elements of cartographic literacy of pupils, which is formed when studying geography at school. As such elements, not only theoretical knowledge of schoolchildren about the map, but also practical skills to work with the mathematical basis of the map, cartographic image, conventional signs, carry out measurements on the map, and find geographical coordinates are highlighted. Cartographic competencies higher level of pupils are the ability to analyze geographic objects using maps, determine their dynamics, make geographic forecasts, models, apply a map when conducting geographic expertise and design. At the same time, attention is focused on the fact that the competences of cartographic literacy of schoolchildren are initially formed at the initial stage of studying geography at school, and will be claimed and developed throughout the entire geographical education. Cartographic literacy of schoolchildren is based on the use of maps for studying objects and phenomena displayed on them. Its elements are consistently and systematically formed and developed in geography lessons and are of practical importance both in the educational process and in everyday life. Traditionally, in the process of teaching geography, tasks associated with determining the geographical coordinates of objects, measuring distances and orientation on the map are used. In order to increase the creative focus in the study of geography, you can use design tasks based on the use of maps, methods of cartometry and morphometry, modeling of geographical objects, solving tasks of a problem character. Conclusions and further research. These tasks of cartographic subjects significantly expand the competencies of schoolchildren and their horizons, increase the interest in the academic subject and introduce the creative component into the educational process. Further research may be related to the determination of the most effective methodologies for the development and expansion of the cartographic competencies of schoolchildren both in geography and extracurricular activities.

Distant monitoring of entangled macro-objects

The paper discusses application of long-range signal transmission system for distant monitoring of entangled macro-objects. The 'activity index' is introduced as a characteristic of distant objects and its meaning is analysed for different experimental and environmental conditions. Probabilistic parameters of non-local measurements, methods for increasing their reproducibility and reliability, as well as various configurations of the measuring system are described. The results of calibration and control experiments with geographic, physical, biological and symbolic objects are represented. The system enables testing entangled macro-objects on possessing specific features/properties measured by multiple devices in parallel. Distant monitoring can be used as part of a system conducting interactions with biological objects, as well as for independent usage as diagnostic or surveillance equipment.

Direction-Aware Nearest Neighbor Query

Although the direction aspect is as important as the distance aspect when retrieving spatial objects, the studies of direction-aware queries are limited. The direction-based surrounder query cannot guarantee good directional diversity. In this paper, we propose the direction-aware nearest neighbor query (DNN query), which can recommend the nearest objects and ensure that the results have good directional diversity. Given a query point $q$ and an angular threshold $\theta $ , the DNN query searches for the nearest neighbors on various directions around $q$ . The DNN query can apply to the scenario where the user searches for the nearest objects around him. It can also apply to the scenario where the user searches for the photos of a geographic object according to the locations where the photos are taken. It can find photos that capture different views of the query object. In this paper, we propose the point-DNN query, where the query object is a point, and extend it to the range-DNN query, where the query object is a rectangle. We design algorithms to answer the DNN queries and also conduct comprehensive experiments to evaluate the performances of the algorithms.

О некоторых пространственных моделях в микротопонимии Пермского края

The relevance of the work is determined by the analysis of microtoponymy of the Perm Region, which is poorly studied. The language models of spatial relations expression on the material of Perm toponymy are considered for the first time. The author dwells on the characteristics of the spatial model of proximity / remoteness in toponymic system of Perm Region. The article determines the main indicators of proximity / remoteness of geographical object from the settlement, these indicators are the attributes дальний / ближний , as well as their partial synonyms окольный / удворный, уличный . It is noted that the idea of remoteness can be expressed indirectly, with the help of attributes of non-spatial nature: дикий , глухой , бедняцкий / поваренный , назёмный , поповский . The paper also analyzes geographical terms that are the parts of microtoponyms that can have the semantics of remoteness. As a rule, these terms are related to slash-and-burn farming system. The author also describes microtoponyms expressing the idea of spatial proximity by means of adjectives formed from the names of settlements and by means of prepositional-case constructions. It is concluded that in the Perm microtoponymy there are the same spatial patterns that exist in other toponymic systems, but some of them are specific.