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Historic Settlement and Landscape Analysis

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (10 April 2018) | Viewed by 54439

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Special Issue Editors

Dr. Hendrik Herold

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Guest Editor

Leibniz Institute of Ecological Urban and Regional Development, Dresden, Saxony, Germany
Interests: geoinformatics; image analysis (historical map image processing, remote sensing); land change; spatiotemporal information retrieval; uncertainty modeling; geocomputation

Dr. Martin Behnisch

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Guest Editor

Leibniz Institute of Ecological Urban and Regional Development, Dresden, Saxony, Germany
Interests: spatial analysis; geographic knowledge discovery; urban data mining; spatial science; quantitative geography; multivariate data analysis; research on building stocks and land consumption
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Dr. Robert Hecht

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Guest Editor

Leibniz Institute of Ecological Urban and Regional Development, Dresden, Saxony, Germany
Interests: urban structure analysis; building stock analysis; population mapping; urban green; VGI; data quality aspects; remote sensing; geovisualization

Dr. Stefan Leyk

E-Mail Website
Guest Editor

Department of Geography, University of Colorado, Boulder, CO 80309, USA
Interests: demographic small area estimation; information extraction and pattern analysis; spatio-temporal modeling; uncertainty modeling and integration; fuzzy set logic in GIScience

Special Issue Information

Dear Colleagues,

The International Land Use Symposium (ILUS) will be held from 1–3 November, 2017 in Dresden, Germany.

The symposium brings together leading academics and interested attendees for presentations, discussions, and collaborative networking in the fields of spatial sciences, environmental studies, geography, cartography, GIScience, urban planning, and architecture. In particular, the interdisciplinary meeting will examine new ideas in overlapping fields of studies with the goal of advancing our understanding of built-up areas, and how recent developments in spatial analysis and modeling can lead to sustainable resource management, a better support of planning and regional development, enhanced spatial information and knowledge, and optimized strategies, instruments, and tools. The symposium and a pre-conference workshop on Big Data Analytics (http://ilus2017.ioer.info/workshop.html) will be organized by the Leibniz Institute of Ecological Urban and Regional Development (IOER) in Dresden.

This Special Issue is organized in conjunctions with the symposium session “Historic Settlement and Landscape Analysis”. The aim of this Special Issue is to publish original research and review papers in order to stimulate discussions on recent trends in retrospective urban and landscape change research. Research on the historical evolution of settlements and landscapes has a long scientific tradition. The session invites contributions regarding theoretical foundations of Land Change Science, methodical concepts, and application-oriented works in this research field. Theoretical contributions may include concepts, ontologies, and critical reviews of the field. Methodical contributions may include algorithms for the data acquisition from historical data sources (i.e., old maps, archival satellite imagery, documents, etc.), such as map image processing, machine learning, but also crowdsourcing approaches; algorithms for the integration of multi-temporal and multi-scale data sources; and for change detection and uncertainty estimation for spatiotemporal modeling. Application-oriented contributions may comprise landscape change analyses and ecosystems services, patterns of urban sprawl and growth, historical demography, calibration of land-use change and climate models, digital humanities (archaeology, etc.), and research on land change (4D) visualizations using historical geodata. We welcome short-term (i.e., decades) investigations, as well as long-term (i.e., centuries, Anthropocene) studies.

Specifically, the topics of interest include (but are not limited to):

Methods

Information acquisition from historical data sources (old maps, historical imagery, documents, etc.)
Image analysis, map processing, crowd-sourcing, cartographic pattern recognition, machine learning
Semantic and geometric data integration, conflation, data fusion, multi-representation databases
Spatiotemporal modeling and analysis
Change detection and uncertainty modeling
Quality assessment and validation of historical geodata

Applications

Settlement development and building stock dynamics
Historical demography and small-scale population estimation
Environmental reconstruction and retrospective monitoring
Quantification and visualization landscape change
Historical proxies for geosimulation and climate modeling
Historical GIS and geovisualisation

Conference Information

Title: International Land Use Symposium (ILUS) 2017
Website: http://www.ilus2017.ioer.info
Date: November 1–3, 2017
Location: Dresden, Germany

The special issue is open for both symposium participants as well as other contributions related to the given topics.

Dr. Hendrik Herold
Dr. Martin Behnisch
Dr. Robert Hecht
Dr. Stefan Leyk
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Land Change Science
Historical GIS
Historical Maps
Geosimulation
Data Integration
Research on Building Stocks
Urban and Regional Studies
Spatiotemporal Modelling
Retrospective Monitoring

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Published Papers (9 papers)

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Editorial

Jump to: Research

5 pages, 193 KiB

Open AccessEditorial

Geospatial Modeling Approaches to Historical Settlement and Landscape Analysis

by Hendrik Herold, Martin Behnisch, Robert Hecht and Stefan Leyk

ISPRS Int. J. Geo-Inf. 2022, 11(2), 75; https://doi.org/10.3390/ijgi11020075 - 19 Jan 2022

Cited by 3 | Viewed by 2743

Abstract

Landscapes and human settlements evolve over long periods of time. Land change, as one of the drivers of the ecological crisis in the Anthropocene, therefore, needs to be studied with a long-term perspective. Over the past decades, a substantial body of research has accumulated in the field of land change science. The quantitative geospatial analysis of land change, however, still faces many challenges; be that methodological or data accessibility related. This editorial introduces several scientific contributions to an open-access Special Issue on historical settlement and landscape analysis. The featured articles cover all phases of the analysis process in this field: from the exploration and geocoding of data sources and the acquisition and processing of data to the adequate visualization and application of the retrieved historical geoinformation for knowledge generation. The data used in this research include archival maps, cadastral and master plans, crowdsourced data, airborne LiDAR and satellite-based data products. From a geographical perspective, the issue covers urban and rural regions in Central Europe and North America as well as regions subject to highly dynamic urbanization in East Asia. In the view of global environmental challenges, both the need for long-term studies on land change within Earth system research and the current advancement in AI methods for the retrieval, processing and integration of historical geoinformation will further fuel this field of research. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

Research

Jump to: Editorial

21 pages, 5459 KiB

Open AccessArticle

Mapping Long-Term Dynamics of Population and Dwellings Based on a Multi-Temporal Analysis of Urban Morphologies

by Robert Hecht, Hendrik Herold, Martin Behnisch and Mathias Jehling

ISPRS Int. J. Geo-Inf. 2019, 8(1), 2; https://doi.org/10.3390/ijgi8010002 - 21 Dec 2018

Cited by 20 | Viewed by 6265

Abstract

Information on the distribution and dynamics of dwellings and their inhabitants is essential to support decision-making in various fields such as energy provision, land use planning, risk assessment and disaster management. However, as various different of approaches to estimate the current distribution of population and dwellings exists, further evidence on past dynamics is needed for a better understanding of urban processes. This article therefore addresses the question of whether and how accurately historical distributions of dwellings and inhabitants can be reconstructed with commonly available geodata from national mapping and cadastral agencies. For this purpose, an approach for the automatic derivation of such information is presented. The data basis is constituted by a current digital landscape model and a 3D building model combined with historical land use information automatically extracted from historical topographic maps. For this purpose, methods of image processing, machine learning, change detection and dasymetric mapping are applied. The results for a study area in Germany show that it is possible to automatically derive decadal historical patterns of population and dwellings from 1950 to 2011 at the level of a 100 m grid with slight underestimations and acceptable standard deviations. By a differentiated analysis we were able to quantify the errors for different urban structure types. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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16 pages, 4786 KiB

Open AccessArticle

Task-Oriented Visualization Approaches for Landscape and Urban Change Analysis

by Jochen Schiewe

ISPRS Int. J. Geo-Inf. 2018, 7(8), 288; https://doi.org/10.3390/ijgi7080288 - 24 Jul 2018

Cited by 8 | Viewed by 3819

Abstract

Approaches to landscape and urban change analysis are still far away from being fully automatic or operational. For this reason, the concept of Geovisual Analytics is proposed, combining computational and visual/manual processing steps. This contribution concentrates on the latter part with the overall goal of improving its usability. For this purpose, a classification of tasks is created, which often occur in the context of change analysis. This serves as the basis for the assignment of suitable map types to change processing results. Beyond this, it is pointed out that in many cases an appropriate pre-processing of data is imperative to preserve or enhance certain spatial relationships or characteristics for visualization. This is demonstrated using the example of data classification prior to choropleth mapping. Methods are described which allow the preservation of local extreme values, large value differences between adjacent polygons, clusters, and hot/cold spots. Finally, discussing future research and developments, it will be stressed that the importance of visual methods in the context of big data change analysis will continue to increase, which is due to the particular ability of maps to generalize and reduce complex data to a minimum. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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28 pages, 3873 KiB

Open AccessArticle

Historical Collaborative Geocoding

by Rémi Cura, Bertrand Dumenieu, Nathalie Abadie, Benoit Costes, Julien Perret and Maurizio Gribaudi

ISPRS Int. J. Geo-Inf. 2018, 7(7), 262; https://doi.org/10.3390/ijgi7070262 - 4 Jul 2018

Cited by 21 | Viewed by 5361

Abstract

The latest developments in the field of digital humanities have increasingly enabled the construction of large data sets which can be easily accessed and used. These data sets often contain indirect spatial information, such as historical addresses. Historical geocoding is the process of transforming indirect spatial information into direct locations which can be placed on a map, thus allowing for spatial analysis and cross-referencing. There are many geocoders that work efficiently for current addresses. However, these do not tackle temporal information, and usually follow a strict hierarchy (country, city, street, house number, etc.) which is difficult—if not impossible—to use with historical data. Historical data is filled with uncertainty (pertaining to temporal, textual, and positional accuracy, as well as to the reliability of historical sources) which can neither be ignored nor entirely resolved. Our open source, open data, and extensible solution for geocoding is based on extracting a large number of simple gazetteers composed of geohistorical objects, from historical maps. Geocoding a historical address becomes the process of finding one or several geohistorical objects in the gazetteers which best match the historical address searched by the user. The matching criteria are customisable, weighted, and include several dimensions (fuzzy string, fuzzy temporal, level of detail, positional accuracy). Since our goal is to facilitate historical work, we also put forward web-based user interfaces which help geocode (one address or batch mode) and display results over current or historical maps. Geocoded results can then be checked and edited collaboratively (no source is modified). The system was tested on the city of Paris, France, for the 19th and 20th centuries. It showed high response rates and worked quickly enough to be used interactively. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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14 pages, 4108 KiB

Open AccessArticle

Ex Post Impact Assessment of Master Plans—The Case of Shenzhen in Shaping a Polycentric Urban Structure

by Xiaoping Xie, Wei Hou and Hendrik Herold

ISPRS Int. J. Geo-Inf. 2018, 7(7), 252; https://doi.org/10.3390/ijgi7070252 - 27 Jun 2018

Cited by 9 | Viewed by 6750

Abstract

This study of ex post impact assessment aims to review the lessons learned from the implementation of previous master plans in the case study city of Shenzhen (China) in order to provide evidence-based input for the possible integration of impact assessment in future master planning in Shenzhen and other world cities, particularly in developing and emerging countries. The paper uses GIS data to derive maps for the visualization of spatial developmental patterns with complementary quantitative analysis for the spatial-temporal impact assessment. The ex post impact assessment shows that the master plans of Shenzhen have successfully guided urban development towards a polycentric spatial structure. Regarding the data used in the study, Global Human Settlement Layer (GSHL) is a valuable dataset that is generally suited to assessing the urban development pattern. The time series mapping of growth in built-up areas as well as population and built-up intensity mapping based on time specific categorization supplemented by the quantitative assessment of high urban concentrations (hUCs) based on time specific thresholding allows the identification of development patterns over a long period of time. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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22 pages, 26807 KiB

Open AccessArticle

Feasibility of the Space–Time Cube in Temporal Cultural Landscape Visualization

by Edyta P. Bogucka and Mathias Jahnke

ISPRS Int. J. Geo-Inf. 2018, 7(6), 209; https://doi.org/10.3390/ijgi7060209 - 31 May 2018

Cited by 15 | Viewed by 6981

Abstract

Change acts as an inherent characteristic of the landscape, and expresses dynamic interactions between its tangible and intangible elements. While the documentation and analysis of spatiotemporal patterns have been broadly discussed, major challenges concern the design of task-oriented, user-friendly landscape visualizations. Geographic information system (GIS) techniques and approaches from visual analytics may bring solutions to those questions. This paper considers the milestone documents for the representation of cultural heritage, and proposes a workflow for assessing the feasibility of the space–time cube concept in landscape representation. The usability of the visualization was examined during the interview with domain experts and potential interdisciplinary users. The evaluation session covered benchmark tasks, feedback, and eye-tracking. The performance of the space–time cube was compared with another spatiotemporal visualization technique and measured in terms of correctness, response time, and satisfaction. The Royal Castle in Warsaw, which was registered in 1980 as a part of Warsaw’s World Heritage Site of United Nations Educational, Scientific and Cultural Organization (UNESCO), served as the case study. The user tests show that the designed space–time cube excels for the completion rate; however, more time is required to provide answers to question tasks focusing on comparisons. Together, the case study and feedback from domain experts and participants demonstrate the benefit of the space–time cube concept in designing landscape visualizations. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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19 pages, 119109 KiB

Open AccessFeature PaperArticle

Map Archive Mining: Visual-Analytical Approaches to Explore Large Historical Map Collections

by Johannes H. Uhl, Stefan Leyk, Yao-Yi Chiang, Weiwei Duan and Craig A. Knoblock

ISPRS Int. J. Geo-Inf. 2018, 7(4), 148; https://doi.org/10.3390/ijgi7040148 - 13 Apr 2018

Cited by 40 | Viewed by 8685

Abstract

Historical maps are unique sources of retrospective geographical information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geographical information contained in such data archives makes it possible to extend geospatial analysis retrospectively beyond the era of digital cartography. However, given the large data volumes of such archives (e.g., more than 200,000 map sheets in the United States Geological Survey topographic map archive) and the low graphical quality of older, manually-produced map sheets, the process to extract geographical information from these map archives needs to be automated to the highest degree possible. To understand the potential challenges (e.g., salient map characteristics and data quality variations) in automating large-scale information extraction tasks for map archives, it is useful to efficiently assess spatio-temporal coverage, approximate map content, and spatial accuracy of georeferenced map sheets at different map scales. Such preliminary analytical steps are often neglected or ignored in the map processing literature but represent critical phases that lay the foundation for any subsequent computational processes including recognition. Exemplified for the United States Geological Survey topographic map and the Sanborn fire insurance map archives, we demonstrate how such preliminary analyses can be systematically conducted using traditional analytical and cartographic techniques, as well as visual-analytical data mining tools originating from machine learning and data science. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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12 pages, 36920 KiB

Open AccessArticle

Long-Term Changes of the Wildland–Urban Interface in the Polish Carpathians

by Dominik Kaim, Volker C. Radeloff, Marcin Szwagrzyk, Monika Dobosz and Krzysztof Ostafin

ISPRS Int. J. Geo-Inf. 2018, 7(4), 137; https://doi.org/10.3390/ijgi7040137 - 1 Apr 2018

Cited by 16 | Viewed by 6140

Abstract

The Wildland–Urban Interface (WUI) is the area where houses and wildland vegetation meet or intermingle, which causes many environmental problems. The current WUI is widespread in many regions, but it is unclear how the WUI evolved, especially in regions where both houses and forest cover have increased. Here we compared WUI change in the Polish Carpathians for 1860 and 2013 in two study areas with different land use history. Our western study area experienced gradual forest increase and housing growth over time, while the eastern study area was subject to a shock due to post-war resettlements, which triggered rapid reforestation. We found that in both study areas WUI extent increased from 1860 to 2013 (41.3 to 54.6%, and 12.2 to 33.3%, in the west and east, respectively). However the causes of WUI growth were very different. In the western study area new houses were the main cause for new WUI, while in the eastern study area forest cover increase was more important. Our results highlight that regions with similar current WUI cover have evolved very differently, and that the WUI has grown rapidly and is widespread in the Polish Carpathians. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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15964 KiB

Open AccessArticle

Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM

by Hone-Jay Chu, Min-Lang Huang, Yu-Ching Tain, Mon-Shieh Yang and Bernhard Höfle

ISPRS Int. J. Geo-Inf. 2017, 6(11), 346; https://doi.org/10.3390/ijgi6110346 - 7 Nov 2017

Cited by 4 | Viewed by 5980

Abstract

Coral walls protect vegetation gardens from strong winds that sweep across Xiji Island, Taiwan Strait for half the year. Topographic parameters based on light detection and ranging (LiDAR)-based high-resolution digital elevation model (DEM) provide obvious correspondence with the expected form of landscape features. The information on slope, curvature, and openness can help identify the location of landscape features. This study applied the automatic landscape line detection to extract historic vegetable garden wall lines from a LiDAR-derived DEM. The three rapid processes used in this study included the derivation of topographic parameters, line extraction, and aggregation. The rules were extracted from a decision tree to check the line detection from multiple topographic parameters. Results show that wall line detection with multiple topographic parameter images is an alternative means of obtaining essential historic wall feature information. Multiple topographic parameters are highly related to low wall feature identification. Furthermore, the accuracy of wall feature detection is 74% compared with manual interpretation. Thus, this study provides rapid wall detection systems with multiple topographic parameters for further historic landscape management. Full article

(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)

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