Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.

Spectrum map is the foundation of spectrum resource management, security governance and spectrum warfare. Aiming at the problem that the traditional spectrum mapping is limited to two-dimensional space, a three-dimensional spectrum data acquisition and mapping system architecture for the integration of space, sky and earth is presented, and a spectrum map reconstruction scheme driven by propagation model is proposed, which can achieve high-precision three-dimensional spectrum map rendering under the condition of sparse sampling. The spectrum map reconstructed by this method in the case of single radiation source and multiple radiation sources is in good agreement with the theoretical results based on ray tracing method. In addition, the measured results of typical scenes further verify the feasibility of this method.

Global navigation satellite system and its application fields are constantly expanding and deepening. This paper mainly introduces the current situation of global satellite navigation system and its application technology, development trend and application prospect. At the same time, this paper makes a comprehensive comparison of these navigation systems, analyzes the opportunities and challenges faced by China’s BeiDou satellite navigation system in the global context, and puts forward some suggestions for future work.

In order to promote the application of noise map in high-speed railway noise management, the high-speed railway noise map drawing technology based on the combination of noise prediction model and geographic information system (GIS) is studied. Firstly, according to the distribution characteristics of noise sources and line structure characteristics of high-speed railway, the prediction model of multi equivalent sound sources and the calculation method of sound barrier insertion loss of high-speed railway are optimized; secondly, a three-dimensional geographic information model of a high-speed railway is built in GIS software, and the railway noise prediction technology based on the model is developed again; then, the noise of discrete nodes is calculated, and the continuous noise distribution map is drawn by spatial interpolation. The research results show that the comparison error between the noise map of a high-speed railway drawn by this technology and the measured results is less than 1 dB (A), which verifies the accuracy and practicality of the high-speed railway noise map, and can be used as a reference for the railway noise management department to formulate noise control countermeasures.

This paper carries out an analysis and reflection on how technoscience reaches Geography through Geographic Information Technologies, how it impacts the production of geographic knowledge and how it derives in the possibility of digital experimentation in the discipline in an environment called geo-digital reality. It is shown that advances in GIT have allowed overcoming old limitations, enriching more and more the observations made by Geography, and it is also highlighted the promising future of digital experimentation in Geography through all the possibilities offered by current technological developments.

The wide distribution of the common beech (Fagus sylvatica) in Europe reveals its great adaptation to diverse conditions of temperature and humidity. This interesting aspect explains the context of the main objective of this work: to carry out a dendroclimatic analysis of the species Fagus sylvatica in the Polaciones valley (Cantabria), an area of transition with environmental conditions from a characteristic Atlantic type to more Mediterranean, at the southern limit of its growth. The methodology developed is based on the analysis of 25 local chronologies of growth rings sampled at different altitudes along the valley, generating a reference chronology for the study area. Subsequently, the patterns of growth and response to climatic variations are estimated through the response and correlation function, and the most significant monthly variables in the annual growth of the species are obtained. Finally, these are introduced into a Geographic Information System (GIS) where they are cartographically modeled in the altitudinal gradient through multivariate analysis, taking into account the different geographic and topographic variables that influence the zonal variability of the species response. The results of the analyses and cartographic models show which variables are most determinant in the annual growth of the species and the distribution of its climatic response according to the variables considered.

This paper presents a brief review of risk studies in Geography since the beginning of the 20th century, from approaches focused on physical-natural components or social aspects, to perspectives that incorporate a systemic approach seeking to understand and explain risk issues at a spatial level. The systemic approach considers principles of interaction between multiple variables and a dynamic organization of processes, as part of a new formulation of the scientific vision of the world. From this perspective, the Complex Systems Theory (CST) is presented as the appropriate conceptual-analytical framework for risk studies in Geography. Finally, the analysis and geographic information integration capabilities of Geographic Information Systems (GIS) based on spatial analysis are explained, which position it as a fundamental conceptual and methodological tool in risk analysis from a systemic approach.

The Guacimal River catchment has an area of 181 km² and is located in the NW of Costa Rica, between the coordinates 84.745° W-10.016° N and 84.909° W-10.325° N. In this territory, as in most of the country, detailed geomorphological studies are scarce; therefore, the objective of this paper is to present the geomorphological mapping at a scale of 1:25,000 of the Guacimal River, which allows us to explain the dynamics of the agents involved in the modeling of the catchment. The work methodology consisted of three stages: pre-mapping, field activity and post-mapping, which resulted in a map in which ten relief forms are represented, ordered according to their morphogenesis in endogenous modeled and exogenous (fluvial, gravitational and littoral). This document will be the base line for land use planning, both continental and coastal, and for local risk management.