Cartographic Datasets Research Articles

INTEGRATED AIRBORNE LIDAR-UAV METHODS FOR ARCHAEOLOGICAL MAPPING IN VEGETATION-COVERED AREAS

Abstract. The research focuses on using 3D digitization in Landscape Heritage conservation processes, specifically in the context of the Spina Verde Park in Como, Italy. The aim of the research is to improve knowledge of the proto-urban archaeological sites of the park and its network of trails, which represent a significant heritage of the area. The study employs low-altitude airborne Light Detection and Ranging (LiDAR) and terrestrial survey methods to obtain high-resolution data, which are structured into a 3D geospatial database in a GIS environment. The integration and harmonization of multisensory 3D data, both airborne and terrestrial originated, and available cartographic datasets, allows for a flexible monitoring tool and supports the interpretation of the archaeological sites and landscape context. The research proposes a methodological approach that has applications in different built and natural heritage contexts and can monitor the conservation status of both archaeological heritage and natural components of the territorial context. The research focuses on testing automated classification algorithms that are useful for identifying and classifying archaeological sites and features within landscapes. By analysing the high-resolution raster generated from the airborne LiDAR point cloud, the research inquiries about the detecting, identifying, and mapping proto-historic archaeological traces efficiently and accurately, leading to better preservation and conservation of built and landscape heritage.

Semi-Automatic Method to Evaluate Ecological Value of Urban Settlements with the Biotope Area Factor Index: Sources and Logical Framework

As the number of people living in cities continues to increase and as their needs continue rapidly to evolve, planners and scholars have been encouraged to define what constitutes high levels of quality of life in urban settlements. The relationship of an area’s inhabitants with natural and green resources increases urban environmental value, which is one of the most relevant aspects in the determination of the quality of life in built-up contexts. Moreover, it is fundamental to find quantitative parameters that can monitor the development of planning processes, working together with natural systems. The authors present a comparative method that can be used to analyze and evaluate the ecological value of urban settlements, using a semi-automatic process that is based on calculating the biotope area factor (BAF) using different open-access databases (a cartographic dataset, aerial imagery, and Sentinel-2 images). Two different Italian case studies that are set in the Milan metropolitan area are presented. In this paper, the authors describe the two settlements using the city-planning parameters of physical structure and morphology; they show the ecological differences and similarities throughout the various remote sensing sources and data. Finally, the authors indicate how the research can be developed, highlighting the weaknesses, the potentiality, the replicability process, and the urban planning implications of the methodology.

Multi-Criteria Geographic Analysis for Automated Cartographic Generalization

ABSTRACT Cartographic generalization is a process similar to text summarization that transforms a map when scale is reduced. Cartographic generalization simplifies the map content while preserving as much as possible the initial characteristics and spatial relations of the map. The automation of this process requires a deep understanding of the context of each map feature, which involves different criteria such as the shape of the feature, the semantic nature of the feature, or the spatial patterns of its neighbouring features. This is why multiple criteria decision techniques can be relevant during the process. This paper proposes two use cases of cartographic generalization sub-tasks where multiple criteria decision techniques improve past techniques: the classification of urban building blocks and the ordering of the buildings to keep in the map as a priority. In both use cases, the proposed methods are experimented on large real cartographic datasets, and evaluated in comparison to alternative techniques.

Uso de Sentinel-2 y datos auxiliares para la generación, mediante clasificación de imágenes, del Mapa de Usos y Cubiertas del Suelo de Cataluña 2017

<p>This paper details the process of generating the 2017 Land Use/Land Cover Map of Catalonia (MUCSC) using automatic classification of satellite imagery and auxiliary cartographic and remote sensing data. A total of 60 images (6 dates for each of the 10 tiles covering Catalonia) captured by the Sentininel-2A and Sentinel-2B satellites were used. These images as well as texture variables, terrain models derived from lidar processing, and vegetation and wetness indices were classified using the k-Nearest Neighbor algorithm (kNN) to obtain a map with 25 categories. The categories related to urbanized areas (urban areas, urbanizations and industrial zones/ commercial areas), road infrastructures and burned areas were edited using official cartographic datasets of the Catalan Government [Generalitat]. The results have an overall accuracy greater than 98 %, which was evaluated with a set of more than 8.6 million independent test pixels. This work represents an important milestone in terms of the computational effort it involves due to the territorial extension (32 000 km<sup>2</sup>), the spatial detail of between 2 and 20 m, the use of up to 58 variables, the relative completeness of the legend and the level of success achieved. The MUCSC 2017, which is part of a 30-year quinquennial series beginning in 1987, can be downloaded in different formats (also in MMZX: new ISO 19165-2) and at resolutions of 10 m and 30 m pixel side from the Ministry of Territory and Sustainability website of the Catalan Government.</p>

Perpetual Motion: Energy and American Studies

Perpetual Motion:Energy and American Studies Michael Ziser (bio), Natasha Zaretsky (bio), and Julie Sze (bio) From early 2016, when construction on the Dakota Access Pipeline began, through February 2017, when the last protectors were forcibly removed by law enforcement officials, the eyes of Americans (and the world) were riveted on a spectacle of energy politics that played directly into established cultural narratives about extraction and its victims. On one side: Energy Transfer Partners, the pipeline construction and management corporation (and its financial backers in the US and Canadian oil and banking industries), who were eager to connect the shale oil freed by fracking from the Bakken formation in North Dakota to existing distribution infrastructure in Illinois, through which it would enter the energy networks of the continent and beyond. On the other: the Standing Rock Sioux and over three hundred other Native nations concerned about threats to their land, water supplies, and cultural heritage sites (including ceremonial sites and burial grounds) along the thousand-plus milelong route of the pipeline, and allies concerned with the global climate crisis. Harking back to the native resistance to settler land theft during the Black Hills gold rush more than a century before, the Dakota Access protests allowed a new generation to see in vivid detail the ongoing violence against native people and lands that are more often hidden from public view. But the Mni Wiconi (Water Is Life) and #NoDAPL movements did more than reopen the painful genre of settler extractive depredation: they also stimulated a broader sort of energy education, one that would illuminate the less familiar and more dauntingly complex historical realities of the nation's energy infrastructure. As Nick Estes (Lower Brule Sioux) details in Our History Is the Future, the protests were rooted in earlier mobilizations against another pipeline, the Keystone XL, and connected to a long tradition of Native resistance to infrastructure and energy projects built in the service of distant populations by corporations and governments indifferent to their impacts on indigenous lands affected by centuries of colonial aggression. The scope and scale of the issues raised could not be limited to a single pipeline but traversed time and space, encompassing people and places widely separated by geography and history. [End Page 543] For outsiders inclined to connect what was happening in the Dakotas to their own daily existence, a new set of technical tools was available to help them. Accompanying the protests were maps of the existing and planned pipelines that make up the nearly half-million miles of large oil and gas pipelines that sit three to six feet below the surface in every state in the union; some of these included a link to the National Pipeline Mapping System database and mobile app (pvnpms.phmsa.dot.gov/PublicViewer/), which allows the public to see a county-by-county map of the oil, gas, and liquid propane pipelines moving fossil fuels through their neighborhoods. Cartographic data sets help visualize the otherwise concealed energy infrastructure that undergirds the alliances and complicities of social life in the contemporary United States, its global networks, and the counterpublics ranged against it.1 Ubiquitous but not evenly spread across the landscape, complex in both their technical details and the affective responses they engender, these routes of literal and figurative power demand careful investigation and debate from scholars in American studies. Energy Studies, Sciences, Histories, and Humanities As in other fields where strict disciplinary boundaries have been abandoned in favor of more flexible inquiries, energy studies is coalescing around the recognition that the energetic basis of the modern world is in a crisis that requires a response from across many categories of knowledge. This broad coalition is made up of four converging approaches (each of them internally complex in ways that we cannot do justice to here). To some, energy studies is the technical study of fuel-stock and energy production, distribution, and consumption (energy sciences); to others, it is the historical account of the development of various industrial prime movers (energy histories); to still others, it is the evolving cultural and political meaning of energy as a concept and construct (energy humanities); and for others, it is the study and...

Quantitative Assessments of Geodiversity in the Area of the Seridó Geopark Project, Northeast Brazil: Grid and Centroid Analysis

The evaluation of geodiversity is one of the initial and main steps in the development of geoconservation actions. It is fundamental to establish parameters that quantify elements and places of abiotic nature in order to draw attention to those that are richer than the average. In doing so, it is possible to manage areas for the protection of notable geoheritage and to develop sustainable activities such as geotourism. The literature comprises several methodologies for the quantitative assessment of geodiversity, but the use of geoprocessing tools appears to be the least subjective type of analysis. From this standpoint, this work aimed to analyze the geodiversity in an area of geological interest in the northeast of Brazil by using two methodologies. The first is widely used and involved the definition of a grid to overlay the cartographic datasets that are used to define the geodiversity index. The second method is based on a centroid analysis of intersected datasets. These investigations showed that the two methodologies have similar aspects and produce a high geodiversity index for the area. This outcome supports the reliability of these methods when the results converge, with respect to the delimitation of the valuable places where geodiversity should be protected. These methods may be used as basis for the sustainable management of natural resources.

Method of intelligent support of decision-making at dispatching the geospatial processes

ABSTRACTState-of-the-art means of intelligent support of decision-making at dispatching the geospatial processes that use the digital cartographic data sets do not allow for an operative and adequate enough consideration of the rapidly varying natural environment’s characteristics influencing upon the dispatching decisions being made when controlling the complexly distributed geospatial processes’ totalities. At that dispatching is an overall manifestation of a versatile process of geospatial processes’ management. As a rule, the task of managing the objects realising geospatial processes is solved in isolation from the current state of their natural environment, and does not consider the environment radio, physical and other characteristics’ variability. The issues of changes in navigational and meteorological conditions, as well as the issues related to ensuring spatial security, are exclusively subjected to the consideration. Under current conditions becomes meaningful a more complex version of the spatial processes dispatching problem, when the environment variability determines the unique conditions for dispatching at each point of the coordinated geographical space. This statement of a problem is especially relevant under an introduction of modern adaptive means intended for monitoring and sensing the natural environment, like subsystems for monitoring the corresponding systems of spatial processes dispatching. The novelty both of this formulation and the method of this version problem-solving consists in the data fusion from the representation of spatial processes subject domain and those corresponding to the standard models of digital data sets, the integration of software mechanisms for working with information on geospatial processes and programmes for working with cartographic data sets. Development of a reasonable problem statement and a method for this problem’s version solving is the essence of this article.

Method of intellectualization for geospatial processes control systems

Modern means of management intellectualization or dispatching of geospatial processes do not allow to take into account quickly and with sufficient degree of adequacy the changing properties of the natural environment that affect the managerial decisions made in dispatching by complexly distributed sets of geospatial processes. At the same time dispatching is the final manifestation of a multifaceted process of managing geospatial processes. Traditionally, the task of managing objects implementing geospatial processes is solved in isolation from the current state of the natural environment of their flow, without taking into account the variability of its radio technical, physical and other characteristics. Only issues of changes in navigational and meteorological conditions, as well as issues related to ensuring spatial security, are subject into account. Considerable interest in modern conditions presents a more complex variant of the problem of intelligent dispatching of spatial processes: when the variability of the environment determines unique conditions for dispatching at each point of the coordinated geographical space. Especially such a statement of the problem is relevant in the context of the introduction of modern adaptive means of monitoring and sensing the natural environment, as subsystems for monitoring the corresponding control systems for spatial processes. The novelty of this formulation and the method of solving this version of the problem lies in the merging of data from the domain of representation of spatial processes with knowledge, data corresponding to typical models of digital data sets, integration of software mechanisms for working with information on geospatial processes and programs for working with cartographic data sets. The development of a well-founded formulation and a method for solving this variant of the problem is the essence of this article.

Statistical Evaluation and Analysis of Road Extraction Methodologies Using a Unique Dataset from Remote Sensing

In the scientific literature, multiple studies address the application of road extraction methodologies to a particular cartographic dataset. However, it is difficult for any study to perform a more reliable comparison among road extraction methodologies when their results come from different cartographic datasets. Therefore, aiming to enable a more reliable comparison among different road extraction methodologies from the scientific literature, this study proposed a statistical evaluation and analysis of road extraction methodologies using a common image dataset. To achieve this goal, we setup a dataset containing remote sensing images of three different road types, highways, cities network and rural paths, and a group of images from the ISPRS (International Society for Photogrammetry and Remote Sensing) dataset. Furthermore, three road extraction methodologies were selected from the literature, in accordance with their availability, to be processed and evaluated using well-known statistical metrics. The achieved results are encouraging and indicate that the proposed statistical evaluation and analysis can allow researchers to evaluate and compare road extraction methodologies using this common dataset extracting similar characteristics to obtain a more reliable comparison among them.

Rule-based topology system for spatial databases to validate complex geographic datasets

A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper.Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend.The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

USING WORLDVIEW-2 SATELLITE IMAGERY TO SUPPORT GEOSCIENCE STUDIES ON PHLEGRAEAN AREA

WorldView-2 satellite imagery includes half-meter p anchromatic resolution and 2 m multispectral resolution. Because of the reduced dimensions of pi xels and articulated spectral acquisition these ima ges supply detailed information that can be used for ge oscience applications, above all to investigate are as, identify land cover, bound vegetated zones, outline transformations (change detection). The aim of thi s study is to remark possibilities to use WorldView-2 imagery for analysis of Phlegrean area (Italy), facilitating monitoring actions and increasing leve l of knowledge of territorial and environmental fea tures. This area is emblematic for many aspects such as it s geological history, the presence of volcanic acti vities, the Roman ruins and the natural forest. The study i s centered on methodological aspects about the use of WorldView-2 imagery for increasing dataset and level of information. For consequence attention is firs tly focalized on possibilities to obtain geometrical co rrected data with adequate accuracy (comparable to pixel dimensions): using Rational Polynomial Functi ons for ortho-rectification, references are already georeferred air-photos with cell-size equal to that of WorldView-2 higher resolution images (panchromatic band: 0.50 ×0.50 m), while Digital Terrain Model (DTM) is built with cartographic dataset in scale 1: 5,000. Then other two methodolo gical aspects on WorlView-2 imagery use are considered: Normalized Difference Vegetation Index (NDVI) application and 3d photo-realistic model construction. In the first case thresholds determin ation to distinguish vegetated areas is conducted using Maximum Likelihood method based on training sites to achieve high level of thematic accuracy; in the second RGB composition is obtained and overlapped to DTM.

Artificial fluvial diversions in the mainland of the Lagoon of Venice during the 16th and 17th centuries inferred by historical cartography analysis

During the 15th c., the Lagoon of Venice was part of a large coastal belt of lagoons and swamps, up to 20 km wide, bordering the western side of the northern Adriatic coast. The area of interest, including the whole Lagoon of Venice, extends from Adige River to the Livenza River to the North. Lagoons’ extent was regulated by the presence of river deltas and lagoon inlets, being controlled in their evolution by river sedimentary loads and tidal dynamics. The lagoon inlets were menaced by progressive decreasing of water depth due to sand deposition caused by the near fluvial deltas, forming outside the lagoon (mostly Piave and Adige rivers); for that reason, the Repubblic of Venice decided to undertake an epic struggle against rivers, diverting them outside the Lagoon or turning them far away; the projects were only partially carried out, mostly during 16th and 17th c., changing the morphology of the alluvial plain and the coastal margin. The ancient hydrographical and geomorphological framework was reconstructed for the whole area (more than 2000 km2). More than 7000 maps were observed; 356 of them were analysed, while the most representatives were georeferenced and their main feature were redrawn. The reconstruction made use of the full cartographic data set, comparing information with historical documents and geological, geomorphological and geo-chronological data. Two case studies are presented (Piave and Brenta diversions) to illustrate actions and consequences on the geomorphology of the plain. The outcome maps give precious information on the diversion project, their effectiveness, the geomorphological changes both related to human interventions and recent climatic changes.

The usage of the historical cartographic datasets and the remote sensing data for the better understanding and mapping of the 2006 Danube floods in Romania

The advantages brought by high resolution satellite data in activities related to flood mapping and flood monitoring are well know in the scientific community. The paper aims to prove that slighter older geospatial documents, such as historical maps, are also a valuable resource for cartographers and decision makers to achieve a better understanding of flood patterns and evolution. Some preparatory actions are needed in order to integrate the old maps into GIS environments for advanced analysis. This includes scanning, color enhancements, georeferencing, reprojection and metadata creation. To illustrate the process, the paper includes a real case scenario: the April 2006 Danube River flood. For one of the most affected sectors along the Danube, close to Rast village, three generations of historical maps (the Austrian 1:200 000 ‘degree maps’, the Romanian 1:20 000 ‘Lambert-Cholesky’ maps and the Soviet Union 1:100 000 ‘Gauss-Krüger’ maps) were processed and included in a large repository. At any time, the maps can be identified and accessed through open standard protocols like CSW and WMS. In this way, we were able to integrate and analyze the flood water masks, extracted from satellite data, along with the historical data sets. The results were very promising. It was possible to understand some flood patterns and to clearly demonstrate that, after the dike failure, the water filled up an area which in the past, before river regulation, was the natural Danube floodplain.

Amalgamation in cartographic generalization using Kohonen's feature nets

Empirical observations of the way cartographers deal with generalization problems lead to the hypothesis that they first detect patterns of anomalies in the cartographic data set and then eliminate anomalies by transforming the data. Automatically identifying patterns of anomalies on the map is a difficult task when using GIS functions or traditional algorithmic approaches. Techniques based on the use of neural networks have been widely used in artificial intelligence in order to solve pattern‐recognition problems. In this paper, we explore how Kohonen‐type neural networks can be used to deal with map generalization applications in which the main problem is to identify high‐density regions that include cartographic elements of the same type. We also propose an algorithm to replace cartographic elements located in a region by its surrounding polygon. The use of this type of neural network permitted us to generate different levels of grouping according to the chosen zoom‐scale on the map. These levels correspond to a multiple representation of the generalized cartographic elements. As an illustration, we apply our approach to the automatic replacement of a group of houses represented as a set of very close points in the original data set, by a polygon representing the corresponding urban area in the generalized map.

A new bedrock and surface elevation dataset for modelling the Greenland ice sheet

AbstractA new digital elevation model of the surface of the Greenland ice sheet and surrounding rock outcrops has been produced from a comprehensive suite of satellite and airborne remote-sensing and cartographic datasets. The surface model has been regridded to a resolution of 5 km, and combined with a new ice-thickness grid derived from ice-penetrating radar data collected in the 1970s and 1990s. A further dataset, the International Bathymetric Chart of the Arctic Ocean, was used to extend the bed elevations to include the continental shelf. The new bed topography was compared with a previous version used for ice-sheet modelling. Near the margins of the ice sheet and, in particular, in the vicinity of small-scale features associated with outlet glaciers and rapid ice motion, significant differences were noted. This was highlighted by a detailed comparison of the bed topography around the northeast Greenland ice stream.

A new, high‐resolution digital elevation model of Greenland fully validated with airborne laser altimeter data

A new digital elevation model of the Greenland ice sheet and surrounding rock outcrops has been produced at 1‐km postings from a comprehensive suite of satellite remote sensing and cartographic data sets. Height data over the ice sheet were mainly from ERS‐1 and Geosat radar altimetry. These data were corrected for a slope‐dependent bias that had been identified in a previous study. The radar altimetry was supplemented with stereophotogrammetric data sets, synthetic aperture radar interferometry, and digitized cartographic maps over regions of bare rock and where gaps in the satellite altimeter coverage existed. The data were interpolated onto a regular grid with a spacing of ∼1 km. The accuracy of the resultant digital elevation model over the ice sheet was assessed using independent and spatially extensive measurements from an airborne laser altimeter that had an accuracy of between 10 and 12 cm. In a comparison with the laser altimetry the digital elevation model was found to have a slope‐dependent accuracy ranging from −1.04±1.98 m to −0.06±14.33 m over the ice sheet for a slope range of 0.0–1.0°. The mean accuracy over the whole ice sheet was −0.33±6.97 m. Over the bare rock areas the accuracy ranged from 20 to 200 m, dependent on the data source available. The new digital elevation model was used as an input data set for a positive degree day model of ablation. The new elevation model was found to reduce ablation by only 2% compared with using an older, 2.5‐km resolution model, which suggests that resolution‐induced errors in estimating ablation are no longer important.

A Prototype System for Propagating Updates Between Cartographic Data Sets

This paper describes a prototype system for the propagation of updates between cartographic data sets at different scales. The prototype system is based on object-oriented techniques and a multiple representation database. The latter consists of a master and a target data set together with connectivities between those objects referring to the same physical entities. The prototype is based on a conceptual framework of four steps: examination, propagation, generalization of updates and solution of spatial conflicts. The rules in these steps are triggered when an object is edited in the master data set. In the examination step it is determined which object should be created, deleted or modified in the target data set according to certain rules. In the propagation step the outcome of the examination step is executed. In addition, in this step the integrity of the multiple representation database is maintained, e.g. connectivities between related objects are set. In the third step the new or modified object in the target data set is generalized to suit the scale of the target data set. Finally, in the last step the constraint method is used to solve the spatial conflicts caused by the update. The paper concludes with a case study, where a map produced by the prototype system is compared to a map produced manually by cartographers.

A knowledge-based approach for evaluadng forestry-map congruency with remotely sensed imagery

Simple algorithmic methods for integrating remotely sensed data with existing cartographic databases do not provide satisfactory results. One of the main difficulties is in reconciling spatial differences between the two data sources. The differences are due to such diverse factors as temporal variations, spatial errors in the map data, and topographic effects in the remotely sensed data. To investigate the extent of this data-integration problem, a map—image congruency evaluation (MICE) knowledge-based system was developed which performs three distinct operations: (i) pre-processing for uniform representation of both the image and cartographic datasets; (ii) spatial reasoning on the data with the MICE system; (iii) presentation of a congruency evaluation map. Results are presented for a forested area in British Columbia, where Landsat multispectral scanner data are integrated with a provincial forest-cover map.

Conflation Automated map compilation

Map conflation is the compilation or reconciliation of two variants of a map of the same region. The theory and practice of automated map conflation evolved from a pilot project at the United States Bureau of the Census from 1983 through 1985. During that project, a prototype system was designed and built for automated map conflation of a large collection of pairs of digital cartographic files of major metropolitan areas in the United States. Although the project focused on matching and merging specific concrete cartographic data sets, it engendered a collection of computer science techniques and mathematical generalizations that have since become interesting in their own right. A map conflation system requires efficient and robust combinatorial, numerical, and geometric algorithms to implement a rather broad spectrum of mathematical theories. This dissertation provides a broad mathematical context for map conflation, a collection of algorithms and tools for building a map conflation system, an analysis of the performance of those algorithms, an assessment of overall performance of systems that were built following a simple paradigm, and a brief discussion of other areas of automated cartography and spatial data handling that could benefit from lessons learned in developing the conflation system.