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MODELING OF FOREST LANDSCAPE EVOLUTION AT REGIONAL LEVEL: A FOSS4G APPROACH

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Title: MODELING OF FOREST LANDSCAPE EVOLUTION AT REGIONAL LEVEL: A FOSS4G APPROACH
Authors: P. Zatelli, C. Tattoni, S. Gobbi, M. G. Cantiani, N. La Porta, M. Ciolli
Contributors: Zatelli, P., Tattoni, C., Gobbi, S., Cantiani, M.G., La Porta, N., Ciolli, M.
Source: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-4-W1-2022, Pp 553-560 (2022)
Publisher Information: Copernicus GmbH, 2022.
Publication Year: 2022
Subject Terms: Technology, OBIA, Time series, Settore AGR/05 - ASSESTAMENTO FORESTALE E SELVICOLTURA, 0211 other engineering and technologies, 02 engineering and technology, 15. Life on land, Engineering (General). Civil engineering (General), Land use/Land cover, 01 natural sciences, TA1501-1820, Landscape, Aereal Imagery, Historical maps, OBIA, Land use/Land cover, Time series, Landscape, Applied optics. Photonics, TA1-2040, Aereal Imagery, Historical maps, 0105 earth and related environmental sciences
Description: In the last decades the Alpine landscape has dramatically changed due to social and economic factors. The most visible impact has been the reduction of the population for mid and high altitude villages and the shrinking of the part of the land used for agriculture and grazing, with a progressive reduction of pastures and meadows and the expansion of the forested areas. For these reasons, a dataset describing the forest, meadows and pasture coverage for the Trentino region, in the eastern Italian Alps, has been created. A set of heterogeneous sources has been selected so that maps and images cover the longest possible time span on the whole Trentino region with comparable quality, creating a Land Use/Land Cover (LULC) map based on historical maps from 1859 to 1936 and aerial images from 1954 to 2015. The achieved accuracy ranges from 98% for historical maps to 94% for aereal imagery. The analysis of selected landscape metrics provided preliminary results about the forest distribution and patterns of recolonization during the last 155 years. It has been possible to create future scenarios for the forest evolution for the next 85 years. Given the large number of maps involved, the great flexibility provided by FOSS for spatial analysis, such as GRASS, R, QGIS and GAMA and the possibility of scripting all the operations have played a pivotal role in the success both in the creation of the dataset and in the extraction and modeling of land use changes.
Document Type: Article
Other literature type
Conference object
File Description: application/pdf
Language: English
ISSN: 2194-9034
DOI: 10.5194/isprs-archives-xlviii-4-w1-2022-553-2022
Access URL: https://isprs-archives.copernicus.org/articles/XLVIII-4-W1-2022/553/2022/
https://doaj.org/article/3eed629ee01f452eb066010a34f141db
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-4-W1-2022/553/2022/
https://hdl.handle.net/11572/352061
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-553-2022
Rights: CC BY
Accession Number: edsair.doi.dedup.....2f9ef433651685d87b6d8faf5d027d08
Database: OpenAIRE
Description
Abstract:In the last decades the Alpine landscape has dramatically changed due to social and economic factors. The most visible impact has been the reduction of the population for mid and high altitude villages and the shrinking of the part of the land used for agriculture and grazing, with a progressive reduction of pastures and meadows and the expansion of the forested areas. For these reasons, a dataset describing the forest, meadows and pasture coverage for the Trentino region, in the eastern Italian Alps, has been created. A set of heterogeneous sources has been selected so that maps and images cover the longest possible time span on the whole Trentino region with comparable quality, creating a Land Use/Land Cover (LULC) map based on historical maps from 1859 to 1936 and aerial images from 1954 to 2015. The achieved accuracy ranges from 98% for historical maps to 94% for aereal imagery. The analysis of selected landscape metrics provided preliminary results about the forest distribution and patterns of recolonization during the last 155 years. It has been possible to create future scenarios for the forest evolution for the next 85 years. Given the large number of maps involved, the great flexibility provided by FOSS for spatial analysis, such as GRASS, R, QGIS and GAMA and the possibility of scripting all the operations have played a pivotal role in the success both in the creation of the dataset and in the extraction and modeling of land use changes.
ISSN:21949034
DOI:10.5194/isprs-archives-xlviii-4-w1-2022-553-2022