Land-cover (LC) products, especially at the regional and global scales, comprise essential data for a wide range of environmental studies affecting biodiversity, climate, and human health. This review builds on previous compartmentalized efforts by summarizing 23 global and 41 regional LC products. Characteristics related to spatial resolution, overall accuracy, time of data acquisition, sensor used, classification scheme and method, support for LC change detection, download location, and key corresponding references are provided. Operational limitations and uncertainties are discussed, mostly as a result of different original modelling outcomes. Upcoming products are presented and future prospects towards increasing usability of different LC products are offered. Despite the common realization of product usage by non-experts, the remote-sensing community has not fully addressed the challenge. Algorithmic development for the effective representation of inherent product limitations to facilitate proper usage by non-experts is necessary. Further emphasis should be placed on international coordination and harmonization initiatives for compatible LC product generation. We expect the applicability of current and future LC products to increase, especially as our environmental understanding increases through multi-temporal studies.

In order to deal with semantic heterogeneity and achieve semantic interoperability between heterogeneous applications, it is necessary to formalize geographic knowledge. The present paper introduces a method to formalize and integrate different geographic categorizations. The method is based on the mathematical theory of Concept Lattices. These rich structures are used for managing multidimensional geographic categories and their overlapping relationships. The applicability of the method is tested on the problem of integrating different land cover/land use categorizations.

This paper proposes a methodology for the fusion of different geographical domain ontologies with top-level ontologies, in order to provide a solid base for information exchange. The proposed methodology discusses context formation and the formalization of geographical concepts using essential properties.

With the proliferation of satellite-derived data, it is now possible to link land cover with socioeconomic and environmental indicators. This manuscript focuses on the 2011 forest and cropland estimations for the European Union’s 28 countries (EU28) derived from moderate resolution imaging spectoradiometer observations and identifies links to socioeconomic indices such as the gross domestic product (GDP) per capita, urbanization degree (UD), Human Development Index (HDI), ecological footprint, and total biocapacity. Results show that GDP per capita and UD are related to forest decrease, as countries with high GDP per capita have a 10% higher urban population and on average 40% less forest share than the EU28 average. The negative relation between the urban population and forest share is even stronger within the moderate GDP countries. Linear fit models reveal that for these countries, a 5.0% increase in urban population leads to a 7.4% decrease of forest share and a 3.9 % increase of cropland share, something contradictory to the general belief that urban population increase is mostly at the expense of agricultural land. In addition, affluent countries with higher HDI tend to have smaller forest per capita values, which is less than half of the EU28 average. Such statistics can become an important indicator for policy advisors for assessing sustainable development.

Augmented Reality (AR) is a technology that has been used extensively in the field of cartography, with one particular application being that of navigation. However even now, AR in navigation is still at an active exploratory stage with multiple different approaches regarding the techniques, methodologies, and development processes. In this work, we present a systematic review of application development in AR navigation research, aiming to fill the gap in the literature by identifying trends in aspects such as hardware, software, and methodologies in AR navigation. We review 107 publications from the past 25 years that present AR navigation software for real-world environments, and analyze their main characteristics regarding intended environments and users, hardware, development platforms, and AR methodologies. We note a rise in AR navigation research interest from 2010 onward, driven in large part by smartphone and mobile device ubiquity, supported further by significant advances and streamlined processes in AR application development. Furthermore, we highlight a rise in the use of increasingly more complex AR methodologies in recent years, signaling that the field is steadily evolving and maturing. At the same time, we also identify significant inconsistencies and omissions regarding the reporting of technical details, with nearly half of reviewed works not reporting one or more of the aspects of interest. After identifying the level of maturity and complexity in the field AR navigation, we provide a list of recommendations and future directions for researchers aiming to develop AR navigation applications.