Fine Spatial Scale Modelling of Trentino Past Forest Landscape (Trentinoland): A Case Study of Foss Application

Gobbi, Stefano; Cantiani, Maria Giulia; Rocchini, Duccio; Zatelli, Paolo; Tattoni, Clara; Porta, Nicola La; Ciolli, Marco

doi:10.5194/isprs-archives-xlii-4-w14-71-2019

Cited by 8 publications

(9 citation statements)

References 24 publications

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“…This work aims to a more general extraction of land use/land cover (LULC) classes from maps with very different features. Together with thematic maps created from orthoimages [23] will form a comprehensive dataset (Trentinoland) for the study of the forest landscape evolution in the last few centuries [24] in the Italian region of Trentino. Several techniques are available for text extraction from printed documents [25], but they focus on the development of effective document processing methods rather than map categories' preservation.…”

Section: Introductionmentioning

confidence: 99%

New Tools for the Classification and Filtering of Historical Maps

Gobbi

Ciolli

Porta

et al. 2019

IJGI

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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 “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 approach.

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Section: Introductionmentioning

confidence: 99%

New Tools for the Classification and Filtering of Historical Maps

Gobbi

Ciolli

Porta

et al. 2019

IJGI

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“…The digitalization of the Historical Cadaster Map of the Trentino region is part of a wider project (Gobbi et al, 2019) which aims to build a dataset containing a large number of digital maps, created from historical maps and historical aereal images (Gobbi et al, 2018), covering a long time span for the Trentino region, as a base for the study of the landscape and ecologic evolution of the area. In particular, the application of this technique to the 1936 Italian Kingdom Forest Map (Ferretti et al, 2018) is planned in the next future.…”

Section: Discussionmentioning

confidence: 99%

Object-Based Image Analysis for Historic Maps Classification

Zatelli

Gobbi

Tattoni

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Heritage maps represent fundamental information for the study of the evolution of a region, especially in terms of landscape and ecologic features. Historical maps present two kinds of hurdle before they can be used in a modern GIS: they must be geometrically corrected to correspond to the datum in use and they must be classified to exploit the information they contain. This study deals the latter problem: the Historical Cadaster Map, created between 1851 and 1861, for the Trentino region in the North of Italy is available as a collection of maps in the ETRS89/UTM 32N datum. The map is a high resolution scan (230 DPI, 24 bit) of the original map and has been used in several ecological studies, since it provides detailed information not only about land property but also about land use. In the past the cadaster map has been manually digitized and for each area a set of attributes has been recorded. Since this approach is time consuming and prone to errors, automatic and semi-automatic procedures have been tested. Traditional image classification techniques, such as maximum likelihood classification, supervised or un-supervised, pixelwise and contextual, do not provide satisfactory results for many reasons: map colors are very variable within the same area, symbols and characters are used to identify cadaster parcels and locations, lines, drawn by hand on the original map, have variable thickness and colors. The availability of FOSS tools for the Object-based Image Analysis (OBIA) has made possible the application of this technique to the cadaster map. This paper describes the use of GRASS GIS and R for the implementation of the OBIA approach for the supervised classification of the historic cadaster map. It describes the determination of the optimal segments, the choice of their attributes and relevant statistics, and their classification. The result has been evaluated with respect to a manually digitized map using Cohens Kappa and the analysis of the confusion matrix. The result of the OBIA classification has also been compared to the classification of the same map using maximum likelihood classification, un-supervised and supervised, both pixelwise and contextual. The OBIA approach has provided very satisfactory results with the ability to automatically remove the background and symbols and characters, creating a ready to be used classified map. This study highlights the effectiveness of the OBIA processing chain available in the FOSS4G ecosystem, and in particular the added value of the interoperability between GRASS GIS and R.</p>

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“…The complete analysis was based on 4 years of study (1955-1988-2008-2017) so as to cover the period with greater dynamics of transformation and for which it is possible to retrieve comparable datasets for large-scale analysis. All operations have been carried out only in FoSS (Free and Open Source Software) environment within an open-source Geographical Information System (QGIS 3.10) which, thanks to different plugins and interoperability with other software, allows a workflow in a single environment (Gobbi et al, 2019). This approach guarantees the possibility to integrate different types of data from historical cartography with datasets from classical cartography to remote sensed data (aerial photos, orthophotos and satellite images) (Statuto et al, 2019a).…”

Section: Preliminary and Mapping Elaborationsmentioning

confidence: 99%

“…After this operation, the land cover classes (Table 1) were mapped by manual digitisation. Also for this operation, it is possible to carry out semi-automatic classification operations, but given the reduced surface areas, the manual procedure has been chosen as more speditive (Gobbi et al, 2019) in order to improve the identification of the different classes, the 1:25,000 scale maps of the 1955 IGM were also used as an additional support.…”

Section: Preliminary and Mapping Elaborationsmentioning

confidence: 99%

Integrating Remote-Sensed and Historical Geodata to Assess Interactions Between Rural Buildings and Agroforestry Land

Cillis

Statuto

Picuno

2021

Journal of Environmental Engineering and Landscape Management

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The rural built heritage constitutes a unique example, due to architectural and technical issues, which plays a central role in the formation of rural landscape. In this research, interactions between rural buildings and the surrounding land have been examined. Two case studies exemplifying some of typical dynamics of some internal mountain areas of Mediterranean region have been considered. These areas are located in Basilicata Region (Southern Italy) and suffer from land and rural buildings heritage abandonment, as well as from the concurrent disappearance of agroforestry systems with high ecological value. A multi-chronological geo-database incorporating different land cover datasets over a period of 62 years (1955–1988–2008–2017) has been implemented into a GIS to assess relationships between some rural buildings and the surrounding land have been then assessed. This has been achieved by integrating different types of remote-sensed geodata: historical aerial photos, digital orthophotos and satellite images. The analyses carried out have shown that the intensity of land abandonment can also be related to the type of rural building and prevalent agricultural activity. Moreover, thanks to this methodology, it has been possible to produce several spatial information useful to support public decisionmakers at different level.

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Fine Spatial Scale Modelling of Trentino Past Forest Landscape (Trentinoland): A Case Study of Foss Application

Cited by 8 publications

References 24 publications

New Tools for the Classification and Filtering of Historical Maps

New Tools for the Classification and Filtering of Historical Maps

Object-Based Image Analysis for Historic Maps Classification

Integrating Remote-Sensed and Historical Geodata to Assess Interactions Between Rural Buildings and Agroforestry Land

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