Proper Maps.

Digital mapping of peatlands – A critical review

The Soil Map of the Russian Federation, 1 : 2.5 M scale (1988) requires updating to include soil data that have been accumulated in the past decades, reflect real changes in the soil cover, including anthropogenic transformation, and ensure precise localization of soil objects and correspondence of the map to satellite data with the use of digital soil mapping technologies. The substantive-genetic classification system of Russian soils (2004, 2008) provides the conceptual basis for this updating. The conversion of soil information from the initial map of 1988 into the new classification system is being performed for each polygon of the digitized map. It is based on the analysis of a vast body of diverse information and includes both the search for analogues of the names of mapping units in the new classification system (renaming of the soils) and the correction of the composition of soils in the polygons: new natural soils, cultivated soils (agrosoils), and urban soils are added to the attribute database. The largest number of new natural soils has appeared in legend sections “Soils of tundra” and “Soils of taiga and broadleaved forests”. Anthropogenic soils (119 legend units) that are shown on the map for the first time, have their maximum representation (36 units) in the section “Soils of steppes”; it is close to the number of natural soils (37 units) in this zone. A considerable percent of anthropogenic soils (> 50% of the natural soils) is also typical of legend sections “Soils of broadleaved forests and forest-steppes,” “Soils of dry steppes and semideserts,” “Salt-affected and solonetzic soils”. The total number of natural and anthropogenic soil units (425) in the new legend is more than twice as large as the initial number of natural soil units in the base map (205). The results of the renaming and updating of soils for each soil polygon are fixed in a separate section of the attribute database to the map and will be used for generating the new map by the methods of digital soil mapping.

Learning and assessment are increasingly mediated by digital technologies. Thus, learners’ experiences with these digital technologies are growing in importance, as they might affect learning and assessment. The present paper explores the impact of user experience on digital concept mapping. It builds on user experience theory to explain variance in the intention to use digital concept mapping tools and in concept map-based assessment scores. Furthermore, it identifies fulfillment of psychological needs as an important driver of positive experiences. In a field study in three schools and a university (N = 71), we tested two concept mapping prototypes on computers and tablets. We found that user experience is a significant factor explaining variance in intention to use. User experience also explained variance in three out of four concept mapping scores on tablets, potentially related to the lower pragmatic quality of the tablet prototypes. Fulfillment of psychological needs strongly affected perceptions of different qualities of user experience with digital concept mapping. These results indicate that user experience needs to be considered in digital concept mapping to provide a positive and successful environment for learning and assessment. Finally, we discuss implications for designers of digital learning and assessment tools.

What is the Metaverse actually? It is an important issue in the terms of theory and practice with huge controversy. Regarding the Metaverse from a philosophical point of view, it could better highlight the inner essence behind the controversy of representation. From the connotation view, it is a digital mapping and mirror world of universe. Extensively, it is a comprehensive integration of digital information technologies. In the view of philosophy, it is an artificial universe created by human beings with digital technology, which is digital universe corresponding to the real universe. In the view of spiritual philosophy, it is a cosmic brain created by human beings with wisdom of natural universe, which is a cosmic heart for the body of natural universe. In the view of cognitive philosophy, it is a digital universe that recognizes everything, and a digital laboratory for human innovation and creation.

The digital map is an important and indispensable resource to the national strategic security and social economic development. At the present, needs to focus on resolving the utility question of digital vector map copyright protection technology, furthermore, the information hiding technology is the basic content of the research areas of the digital vector maps copyright protection. It is proposed a digital copyright protection scheme, based on the principle of unauthorized cannot resume, copyright embedding operation selection partly transform for the map content. Processing area determined by the spatial clustering analysis method that is based on grid density.

Floods are one of the most disastrous and dangerous catastrophes faced by humanity for ages. Though mostly deemed a natural phenomenon, floods can be anthropogenic and can be equally devastating in modern times. Remote sensing with its non-evasive data availability and high temporal resolution stands unparalleled for flood mapping and modelling. Since floods in India occur mainly in monsoon months, optical remote sensing has limited applications in proper flood mapping owing to lesser number of cloud-free days. Remotely sensed microwave/synthetic aperture radar (SAR) data has penetration ability and has high temporal data availability, making it both weather independent and highly versatile for the study of floods. This study uses space-borne SAR data in C-band with VV (vertically emitted and vertically received) and VH (vertically emitted and horizontally received) polarization channels from Sentinel-1A satellite for SAR interferometry-based flood mapping and runoff modeling for Rupnagar (Punjab) floods of 2019. The flood maps were prepared using coherence-based thresholding, and digital elevation map (DEM) was prepared by correlating the unwrapped phase to elevation. The DEM was further used for Soil Conservation Service-curve number (SCS-CN)-based runoff modelling. The maximum runoff on 18 August 2019 was 350mm while the average daily rainfall was 120mm. The estimated runoff significantly correlated with the rainfall with an R2 statistics value of 0.93 for 18 August 2019. On 18 August 2019, Rupnagar saw the most devastating floods and waterlogging that submerged acres of land and displaced thousands of people.

<p>‘Strategic objective 1’ of the United Nations Convention to Combat Desertification (UNCCD) aims to improve conditions of affected ecosystems, combat desertification/land degradation, promote sustainable land management, and contribute to land degradation neutrality. The indicator ‘Proportion of land that is degraded over total land area’ (SO1) is compiled from three sub-indicators: ‘Trends in land cover’ (SO1-1), ‘Trends in land productivity or functioning of the land’ (SO1-2), ‘Trends in carbon stocks above and below ground’ (SO1-3).</p><p>Soil organic carbon (SOC) stock can be adopted as the metric of SO1-3, until globally accepted methods for estimating the total terrestrial system carbon stocks will be elaborated. SOC can be considered as one of the most important properties of soil, which shows not just spatial but temporal variability. According to our previous results in the topic, UNCCD default data of SOC stock for Hungary is strongly recommended to be replaced with country specific estimation of SOC stock.</p><p>SOC stock maps were compiled in the framework of DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) initiative, predicted by proper digital soil mapping (DSM) method. Reference soil data were derived from a countrywide monitoring system. The selection of environmental covariates was based on the SCORPAN model. The elaborated SOC stock mapping methodology have two components: (1) point support modelling, where SOC stock is computed at the level of soil profile, and (2) spatial modelling (quantile regression forest), where spatial prediction and uncertainty quantification are carried out using the computed SOC stock values.</p><p>We analyzed how SOC stock changed between 1998 and 2016.  Nationwide SOC stock predictions were compiled for the years 1998, 2010, 2013, and 2016. For the intermediate years, we do not recommend to calculate SOC stock values, because we have no information on the dynamics of change in the intervening years. Based on the 1998 SOC stock prediction, we compiled a SOC stock map for 2018, using only land use conversion factors, according to the default data conversion values.</p><p>According to the elaborated scheme during the respective period, significant changes cannot be detected, only tendentious SOC stock changes appear. Based on our results, we recommend to use spatially predicted layers for all years when data are available, rather than calculating SOC stock change based on land use conversion factors.</p><p><strong>Acknowledgment:</strong> Our research was supported by the Hungarian National Research, Development and Innovation Office (NKFIH; K-131820) and by the Premium Postdoctoral Scholarship of the Hungarian Academy of Sciences (PREMIUM-2019-390) (Gábor Szatmári).</p>

A wide variety of color schemes have been devised for mapping scalar data to color. We address the challenge of color-mapping multivariate data. While a number of methods can map low-dimensional data to color, for example, using bilinear or barycentric interpolation for two or three variables, these methods do not scale to higher data dimensions. Likewise, schemes that take a more artistic approach through color mixing and the like also face limits when it comes to the number of variables they can encode. Our approach does not have these limitations. It is data driven in that it determines a proper and consistent color map from first embedding the data samples into a circular interactive multivariate color mapping display (ICD) and then fusing this display with a convex (CIE HCL) color space. The variables (data attributes) are arranged in terms of their similarity and mapped to the ICD's boundary to control the embedding. Using this layout, the color of a multivariate data sample is then obtained via modified generalized barycentric coordinate interpolation of the map. The system we devised has facilities for contrast and feature enhancement, supports both regular and irregular grids, can deal with multi-field as well as multispectral data, and can produce heat maps, choropleth maps, and diagrams such as scatterplots.

New Digital Technologies Applied to the Management of Geoheritage

Now the sharing economy has impacted the entire Chinese market, including car sharing, bicycle sharing, umbrella sharing, and so on. The advent of the Internet era has brought hope to many of these emerging industries, and various digital technologies have provided many companies with the premise of free development. But as far as Mobike shared bikes are concerned, when they are more freely and easy to park, the impact of the dockless design combined with digital technology will be worth pondering. This paper analyzes the dockless design of Mobike, at the same time, it also focuses on the impact of Mobike digital technology (online payment, GPS system, app data). Finally, it proposes a solution for the Chinese-style sharing economy that evolved from dockless and digital. Overall, the dockless design and the Digital technology have a huge impact on Mobike, both positive and negative. Now Mobike has been acquired by Meituan, but I still discuss this article under the original name of Mobike, thinking that it is the first sharing-bicycle brand in the Chinese market, and although it has been acquired, it is still a successful brand.

Contemporarily, with technological progress and accelerated digitization, some traditional agricultural insurance has also started digital conversion, such as Ping An's digital map of agricultural insurance using DRS Hawk-Eye technology and data platforms. However, considering the level of awareness and production methods of rural agricultural farmers in China, this new form of agricultural insurance combined with big data suffers from a low level of trust as well as insufficient on-the-ground coverage. This report analyzes the strengths, weaknesses, opportunities and challenges of digital agricultural insurance in Ping An's case using SWOT analysis. The results of the study show that the digital agricultural insurance map promotes the development of agricultural insurance in terms of risk reduction and fast claims settlement, but the acceptance of this type of digital agricultural insurance still needs to be improved. This study seeks to provide a number of strategic recommendations to promote the high-quality development of digitized agricultural insurance and expects to provide a marginal contribution to the deep integration of digital technology and the insurance industry.

In construction project management, the most critical part is monitoring and tracking construction productivity. The measurement of productivity in a previous way manually where the process and workers’ productivity are recorded and then analyzed. With the rapid rise of the Industrial Revolution 4.0 (IR 4.0), the application of digital technology will further enhance productivity and continuous process improvement. There is various digital technology available during this IR 4.0; among the technology potentially adopted in the Oil and Gas (O&G) construction is digitalisation through Internet of Things (IoT). With the availability of digital solution in the market, the research study to understand and investigate the application of Digital Value Stream Mapping (DVSM) to monitor and track construction productivity. After that, the investigation was conducted to develop the Digital Value Stream Map (VSM) framework for productivity monitoring and tracking for construction work in Oil and Gas (O&G) activity. Then, to validate the developed DVSM framework through expert interviews and case studies of the actual implementation of the DVSM. The application of the DVSM will come out with the analysis of the existing process flow, then to come out with the future state of the process flow by eliminating the waste of labour and material. Finally, the DVSM model success then the study recommends that the DVSM can further expand to utilize at the offshore environment for tracking and improving the overall construction productivity during the hook-up and commissioning phase for Brownfield and Greenfield projects.

One of the features of the transition from traditional soil cartography to digital technologies for compiling and using soil maps is a qualitative change in both the concept of “map” and the concept of “map scale”. A map in digital cartography is a spatially coordinated database that can consist of many layers of information and can be visualized at any scale. The scale of traditionally compiled paper soil maps is of great importance for understanding the semantic load of the map and the degree of its generalization. When using digital soil mapping, the concept of “scale” loses its meaning. This happens because the level of generalization of soil information in this case is not determined by the scale at which the map is visualized on the computer monitor or printed, but by what pixel size the map was created (in the case of raster maps) or which map served the basis for creating a vector layer of the soil map. For raster soil maps it is more logical to use the concept of “pixel size” instead of “scale”. For vector soil maps it is more important to indicate the scale of the original soil map (which was vectorized), rather than the scale of their visualization. The scale of visualization of the digital soil map is not important in the computer (digital) applied analysis of soil data. When creating raster soil maps, it is impossible to use source materials of different scales without bringing them to a unified level of generalization. All this must be taken into account when using digital soil mapping technology.

Place names are a linguistic message carrying spatial information. These names contain a wealth of knowledge in regard to descriptions of landscape, environment, navigation, past events, and people’s overall relationships to place. In cases where this information is part of an intergenerational, long-term relationship with a specific landscape, place names can be considered Indigenous knowledge and thus, may be especially significant within the context of places that have been subject to colonization, or have undergone significant environmental change. Until very recently, place name studies were often limited to a focus on linguistic elements and confined to paper as text. However, the advent of new digital technologies can now allow us to look at place names in new and different ways by using them as the input on digital mapping platforms to create visualizations of space. This chapter outlines three specific techniques that I developed over the course of my dissertation working together with members of the Kanyen’kehá:ka (Mohawk) on place names and Indigenous place naming conventions. Using the structures, meanings, and sounds of some of these names, I demonstrate how mapping these different aspects can produce visual patterns that allow us to see a landscape in new ways. These techniques, when used with community participatory mapping, can facilitate better understanding and representation of Indigenous relationships to place through digital mapping.

The pine wilt disease is a devastating disease of pine trees. In China, the first discoveries of the pine wilt disease on 1982 at Dr. Sun Yat-sen's Mausoleum in Nanjing. It occurred an area of 77000 hm² in 2005, More than 1540000 pine trees deaths in the year. Many districts of Chongqing in Three Gorges Reservoir have different degrees of pine wilt disease occurrence. It is a serious threat to the ecological environment of the reservoir area. Use unmanned airship to carry high spectrum remote sensing monitoring technology to develop the study on pine wood nematode disease early diagnosis and early warning and forecasting in this study. The hyper spectral data and the digital orthophoto map data of Fuling District Yongsheng Forestry had been achieved In September 2015. Using digital image processing technology to deal with the digital orthophoto map, the number of disease tree and its distribution is automatic identified. Hyper spectral remote sensing data is processed by the spectrum comparison algorithm, and the number and distribution of disease pine trees are also obtained. Two results are compared, the distribution area of disease pine trees are basically the same, indicating that using low air remote sensing technology to monitor the pine wood nematode distribution is successful. From the results we can see that the hyper spectral data analysis results more accurate and less affected by environmental factors than digital orthophoto map analysis results, and more environment variable can be extracted, so the hyper spectral data study is future development direction.