New tools for the classification and filtering of historical maps

6openInternationalBothHistorical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi-automatic procedure for the digitalization of heritage maps and the successive filtering of undesirable features such as text, symbols and boundary lines. The digitalization step is carried out using Object-based Image Analysis (OBIA) in GRASS GIS and R, combining image segmentation and machine-learning classification. The filtering step is performed by two GRASS GIS modules developed during this study and made available as GRASS GIS add-ons. The first module evaluates the size of the filter window needed for the removal of text, symbols and lines; the second module replaces the values of pixels of the category to be removed with values of the surrounding pixels. The procedure has been tested on three maps with different characteristics, the “Historical Cadaster Map for the Province of Trento” (1859), the “Italian Kingdom Forest Map” (1926) and the “Map of the potential limit of the forest in Trentino” (1992), with an average classification accuracy of 97%. These results improve the performance of classification of heritage maps compared to more classical methods, making the proposed procedure that can be applied to heterogeneous sets of maps, a viable approachopenGobbi, Stefano; Ciolli, Marco; La Porta, Nicola; Rocchini, Duccio; Tattoni, Clara; Zatelli, PaoloGobbi, S.; Ciolli, M.; La Porta, N.; Rocchini, D.; Tattoni, C.; Zatelli, P

Deconstructing U.S. Army Maps of Korea: A Case Study for Rethinking Historical Environmental Data

At a time when the natural world and global climate are experiencing extreme changes at unprecedented speeds, understanding these environmental changes over time is more important than ever. With advances in remote sensing technology, large amounts of information about the natural world are becoming more accessible than ever before; however, satellite-collected data are only available from 1984 onwards. To understand how land use has changed on longer timescales, researchers have turned towards archival maps as a data source. Archival maps are a rich source of environmental information; however, they are often saturated with complicated colonial histories. Maps, more so than other historical materials, can hide behind the veneer of objectivity and thus escape important interrogation. As methods that utilize archival maps become more popular, the need to critically analyze the historical and social contexts of the maps becomes even stronger. This thesis argues for a rethinking of historical environmental data through a case study of U.S. Military Maps of Korea from 1945-1954. By providing appropriate historical and social context, three maps of Seoul are deconstructed, thereby illuminating their fallibility as objective environmental sources. This case study ultimately encourages scholars to engage with environmental history more critically and think beyond the analogues dictated by current technology

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Geographic features recognition for heritage landscape mapping – Case study: The Banda Islands, Maluku, Indonesia

This study examines methods of geographic features recognition from historic maps using CNN and OBIA. These two methods are compared to reveal which one is most suitable to be applied to the historic maps dataset of the Banda Islands, Indonesia. The characteristics of cartographic images become the main challenge in this study. The geographic features are divided into buildings, coastline, and fortress. The results show that CNN is superior to OBIA in terms of statistical performance. Buildings and coastline give excellent results for CNN analysis, while fortress is harder to be interpreted by the model. On the other hand, OBIA reveals a very satisfying result is very depending on the maps’ scales. In the aspect of technical procedure, OBIA offers easier steps in pre-processing, in-process and post-processing/finalisation which can be an advantage for a wide range of users over CNN

Reconstructing historical 3D city models

Historical maps are increasingly used for studying how cities have evolved over time, and their applications are multiple: understanding past outbreaks, urban morphology, economy, etc. However, these maps are usually scans of older paper maps, and they are therefore restricted to two dimensions. We investigate in this paper how historical maps can be ‘augmented’ with the third dimension so that buildings have heights, volumes, and roof shapes. The resulting 3D city models, also known as digital twins, have several benefits in practice since it is known that some spatial analyses are only possible in 3D: visibility studies, wind flow analyses, population estimation, etc. At this moment, reconstructing historical models is (mostly) a manual and very time-consuming operation, and it is plagued by inaccuracies in the 2D maps. In this paper, we present a new methodology to reconstruct 3D buildings from historical maps, we developed it with the aim of automating the process as much as possible, and we discuss the engineering decisions we made when implementing it. Our methodology uses extra datasets for height extraction, reuses the 3D models of buildings that still exist, and infers other buildings with procedural modelling. We have implemented and tested our methodology with real-world historical maps of European cities for different times between 1700 and 2000

Fine spatial scale modelling of Trentino past forest landscape and future change scenarios to study ecosystem services through the years

Ciolli, MarcoCantiani, Maria Giulia1openLandscape in Europe has dramatically changed in the last decades. This has been especially true for Alpine regions, where the progressive urbanization of the valleys has been accom- panied by the abandonment of smaller villages and areas at higher elevation. This trend has been clearly observable in the Provincia Autonoma di Trento (PAT) region in the Italian Alps. The impact has been substantial for many rural areas, with the progressive shrinking of meadows and pastures due to the forest natural recolonization. These modifications of the landscape affect biodiversity, social and cultural dynamics, including landscape perception and some ecosystem services. Literature review showed that this topic has been addressed by several authors across the Alps, but their researches are limited in space coverage, spatial resolution and time span. This thesis aims to create a comprehensive dataset of historical maps and multitemporal orthophotos in the area of PAT to perform data analysis to identify the changes in forest and open areas, being an evaluation of how these changes affected land- scape structure and ecosystems, create a future change scenario for a test area and highlight some major changes in ecosystem services through time. In this study a high resolution dataset of maps covering the whole PAT area for over a century was developed. The earlier representation of the PAT territory which contained reliable data about forest coverage was considered is the Historic Cadastral maps of the 1859. These maps in fact systematically and accurately represented the land use of each parcel in the Habsburg Empire, included the PAT. Then, the Italian Kingdom Forest Maps, was the next important source of information about the forest coverage after World War I, before coming to the most recent datasets of the greyscale images of 1954, 1994 and the multiband images of 2006 and 2015. The purpose of the dataset development is twofold: to create a series of maps describing the forest and open areas coverage in the last 160 years for the whole PAT on one hand and to setup and test procedures to extract the relevant information from imagery and historical maps on the other. The datasets were archived, processed and analysed using the Free and Open Source Software (FOSS) GIS GRASS, QGIS and R. The goal set by this work was achieved by a remote sensed analysis of said maps and aerial imagery. A series of procedures were applied to extract a land use map, with the forest categories reaching a level of detail rarely achieved for a study area of such an extension (6200 km2 ). The resolution of the original maps is in fact at a meter level, whereas the coarser resampling adopted is 10mx10m pixels. The great variety and size of the input data required the development, along the main part of the research, of a series of new tools for automatizing the analysis of the aerial imagery, to reduce the user intervention. New tools for historic map classification were as well developed, for eliminating from the resulting maps of land use from symbols (e.g.: signs), thus enhancing the results. Once the multitemporal forest maps were obtained, the second phase of the current work was a qualitative and quantitative assessment of the forest coverage and how it changed. This was performed by the evaluation of a number of landscape metrics, indexes used to quantify the compaction or the rarefaction of the forest areas. A recurring issue in the current Literature on the topic of landscape metrics was identified along their analysis in the current work, that was extensively studied. This highlighted the importance of specifying some parameters in the most used landscape fragmentation analy- sis software to make the results of different studies properly comparable. Within this analysis a set of data coming from other maps were used to characterize the process of afforestation in PAT, such as the potential forest maps, which were used to quantify the area of potential forest which were actually afforested through the years, the Digital Ele- vation Model, which was used to quantify the changes in forest area at a different ranges of altitude, and finally the forest class map, which was used to estimate how afforestation has affected each single forest type. The output forest maps were used to analyse and estimate some ecosystem services, in par- ticular the protection from soil erosion, the changes in biodiversity and the landscape of the forests. Finally, a procedure for the analysis of future changes scenarios was set up to study how afforestation will proceed in absence of external factors in a protected area of PAT. The pro- cedure was developed using Agent Based Models, which considers trees as thinking agents, able to choose where to expand the forest area. The first part of the results achieved consists in a temporal series of maps representing the situation of the forest in each year of the considered dataset. The analysis of these maps suggests a trend of afforestation across the PAT territory. The forest maps were then reclassi- fied by altitude ranges and forest types to show how the afforestation proceeded at different altitudes and forest types. The results showed that forest expansion acted homogeneously through different altitude and forest types. The analysis of a selected set of landscape met- rics showed a progressive compaction of the forests at the expenses of the open areas, in each altitude range and for each forest type. This generated on one hand a benefit for all those ecosystem services linked to a high forest cover, while reduced ecotonal habitats and affected biodiversity distribution and quality. Finally the ABM procedure resulted in a set of maps representing a possible evolution of the forest in an area of PAT, which represented a similar situation respect to other simulations developed using different models in the same area. A second part of the result achieved in the current work consisted in new open source tools for image analysis developed for achieving the results showed, but with a potentially wider field of application, along with new procedure for the evaluation of the image classification. The current work fulfilled its aims, while providing in the meantime new tools and enhance- ment of existing tools for remote sensing and leaving as heritage a large dataset that will be used to deepen he knowledge of the territory of PAT, and, more widely to study emerging pattern in afforestation in an alpine environment.openGobbi, S

Auswirkungen von Landnutzung und Landschaftsstruktur auf Ökosystemleistungen – Analyse am Beispiel der Untersuchungsgebiete Jesewitz (Nordsachsen) und Ilsenburg (Nordharz)

Die fortlaufenden Veränderungen von Landnutzung und Landschaftsstruktur in Europa und weltweit beeinflussen zunehmend die Fähigkeit der Landschaft, Ökosystemleistungen (Versorgungs-, Regulierungs- und kulturelle Leistungen) bereitzustellen, und führen zum Verlust historisch gewachsener Kulturlandschaften. Dabei haben Geschwindigkeit und Intensität dieser Veränderungsprozesse seit den 1960er Jahren deutlich zugenommen und die Verfügbarkeit und Qualität von Ökosystemleistungen signifikant verändert. In den in dieser Arbeit untersuchten Agrarräumen hat sich zum Beispiel das Erosionsrisiko (im Sinne eines Verlustes an natürlichem Erosionsschutz als Indikator für Regulierungsleistung) durch die Ausräumung der Landschaft und Bildung großflächiger Agrarflächen wesentlich erhöht und das natürliche Ertragspotential (Indikator für Versorgungsleistung) wurde durch zunehmende Bodendegradation gemindert. Das Risiko von Biodiversitätsabnahme (Indikator für kulturelle Leistung) ist durch Habitatverlust und zunehmender Homogenisierung der Standorte sowie durch veränderte Bewirtschaftungspraktiken (Technisierung und Chemisierung) stark angestiegen. Dabei kommt der Biodiversität eine Schlüsselrolle bei der Nahrungsmittelproduktion, bei Nährstoff- und Wasserkreisläufen oder dem Erosionsschutz sowie der Gesundheitsfürsorge (z. B. Erholung) zu. Andererseits konnten durch Meliorationsmaßnahmen und unter Einsatz neuer Bewirtschaftungspraktiken die Getreideerträge (Indikator für Versorgungsleistung) seit Beginn des 20. Jahrhunderts verdoppelt werden. Zielsetzung der vorliegenden Arbeit ist es, anhand von zwei ausgewählten Untersuchungsgebieten räumlich explizit und quantitativ Veränderungen in der Landnutzung und der Landschaftsstruktur und die Auswirkungen dieser Veränderungen auf ausgewählte bodenbezogene Ökosystemleistungen für den Zeitraum von 1750 bis 2018 zu analysieren. Damit soll ein Beitrag geleistet werden, historische und heutige Landnutzungsänderungen im Kontext gesellschaftspolitischer und ökonomischer Rahmenbedingungen zu verstehen und hinsichtlich ihrer Auswirkungen auf eine nachhaltige Landnutzung, auf die Erhaltung der Biodiversität sowie auf die Vermeidung von Landschafts- und Bodendegradation zu bewerten und entsprechende Handlungsempfehlungen ableiten zu können.:Zusammenfassung II Abstract IV Danksagung VI Inhaltsverzeichnis VII Abbildungs- und Tabellenverzeichnis VIII 1 Einführung 1 1.1 Einfluss von Landschaftsveränderungen auf Ökosystemleistungen 1 1.2 Rekonstruktion historischer Landschaftszustände seit 1750 als Ausgangspunkt einer historisch-ökologischen Landschaftsanalyse 5 1.3 Von der Landschaftsanalyse zur Bewertung von Ökosystemleistungen 15 2 Ergebnisse und Diskussion 18 2.1 Veränderung der Landschaftsstruktur und treibende Kräfte 18 2.2 Veränderung der Ökosystemleistungen 25 2.3 Methodische Herausforderungen bei historischen Analysen 33 3 Schlussfolgerung 35 Literatur 37 Anhang X A1: Changes in landscape structure and ecosystem services since 1850 analyzed using landscape metrics in two German municipalities. X A2: Land use change in an agricultural landscape causing degradation of soil based ecosystem services XXIV A3: Changes of landscape structure and soil production function since the 18th century in northwest Saxony XXXVI A4: Landschaftsdynamik und Produktionsfunktion im Kontext gesellschaftlicher und ökonomischer Veränderungen seit dem 18. Jahrhundert im Raum Taucha-Eilenburg L A5: Erklärung zur Autorenschaft LXXXVI A6: Bibliographische Informationen LXXXIXOngoing changes in land use and landscape structure in Europe and worldwide are increasingly affecting the ability of the landscape to provide ecosystem services (provisioning, regulation and cultural services). Furthermore, they lead to the loss of historically cultural landscapes. In the process, the speed and intensity of these change processes have increased markedly since the 1960s and significantly affecting the availability and quality of ecosystem services. In the agricultural areas studied in this paper, for example, the risk of erosion (indicator of regulating service) has increased substantially due to the clearing of the countryside and formation of large-scale agricultural areas, and the natural yield potential (indicators of provisioning service) has been reduced by increasing soil degradation. The risk of biodiversity (indicator of cultural service) decline has greatly increased due to habitat loss and increasing homogenisation of sites, and changes in farming practices (mechanisation and chemicalisation). In this context, biodiversity plays a key role in food production, nutrient and water cycles or erosion control, as well as health care (e.g. recreation). On the other hand, improvement measures and the use of new farming practices have doubled cereal yields (indicators of provisioning service) since the beginning of the 20th century. The objective of this paper is to spatially and quantitatively analyse changes in land use and landscape structure and the effects of these changes on selected soil-related ecosystem services for the period from 1750 to 2018, using two selected study areas. The aim is to contribute to understanding historical and present-day land use changes in the context of socio-political and economic framework conditions and to evaluate them with regard to their effects on sustainable land use, on the conservation of biodiversity, and on the prevention of landscape and soil degradation, and to be able to derive respective recommendations for action.:Zusammenfassung II Abstract IV Danksagung VI Inhaltsverzeichnis VII Abbildungs- und Tabellenverzeichnis VIII 1 Einführung 1 1.1 Einfluss von Landschaftsveränderungen auf Ökosystemleistungen 1 1.2 Rekonstruktion historischer Landschaftszustände seit 1750 als Ausgangspunkt einer historisch-ökologischen Landschaftsanalyse 5 1.3 Von der Landschaftsanalyse zur Bewertung von Ökosystemleistungen 15 2 Ergebnisse und Diskussion 18 2.1 Veränderung der Landschaftsstruktur und treibende Kräfte 18 2.2 Veränderung der Ökosystemleistungen 25 2.3 Methodische Herausforderungen bei historischen Analysen 33 3 Schlussfolgerung 35 Literatur 37 Anhang X A1: Changes in landscape structure and ecosystem services since 1850 analyzed using landscape metrics in two German municipalities. X A2: Land use change in an agricultural landscape causing degradation of soil based ecosystem services XXIV A3: Changes of landscape structure and soil production function since the 18th century in northwest Saxony XXXVI A4: Landschaftsdynamik und Produktionsfunktion im Kontext gesellschaftlicher und ökonomischer Veränderungen seit dem 18. Jahrhundert im Raum Taucha-Eilenburg L A5: Erklärung zur Autorenschaft LXXXVI A6: Bibliographische Informationen LXXXI

New Tools for the Classification and Filtering of Historical Maps

Historical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi-automatic procedure for the digitalization of heritage maps and the successive filtering of undesirable features such as text, symbols and boundary lines. The digitalization step is carried out using Object-based Image Analysis (OBIA) in GRASS GIS and R, combining image segmentation and machine-learning classification. The filtering step is performed by two GRASS GIS modules developed during this study and made available as GRASS GIS add-ons. The first module evaluates the size of the filter window needed for the removal of text, symbols and lines; the second module replaces the values of pixels of the category to be removed with values of the surrounding pixels. The procedure has been tested on three maps with different characteristics, the \u201cHistorical Cadaster Map for the Province of Trento\u201d (1859), the \u201cItalian Kingdom Forest Map\u201d (1926) and the \u201cMap of the potential limit of the forest in Trentino\u201d (1992), with an average classification accuracy of 97%. These results improve the performance of classification of heritage maps compared to more classical methods, making the proposed procedure that can be applied to heterogeneous sets of maps, a viable approach