@book{113f0d04febf4f628fa4e24721e90bc8,
title = "Automated production of spatial datasets for land categories from historical maps: Method development and results for a pilot study of Danish late-1800s topographical maps",
abstract = "This report records the methods and the results of a pilot project aimed at automatedproduction of machine-readable spatial datasets for land categories from Danishtopographical maps from the late 1800s. The study was undertaken for two studyareas in Jutland, covering around 300 km². Target land categories were: heath, sanddune, wetland, forest and water bodies. The automated geo-data productioncomprised a combination of object based image analysis, vector GIS, coloursegmentation and machine learning processes. Results of an accuracy assessmentindicate accuracies that for most categories are around 90 % or higher. A changeassessment for the period from the late 1800s until today, revealed a dynamiccharacterised by decrease in open habitat types due to cultivation and afforestation.We conclude, that automated production of LULC category digital geo-data fromhistorical maps offers a less time consuming and consequently more resourceefficient alternative to traditional manual vectorisation",
keywords = "Historical maps, landscape change, automated production, object based image processing, H{\o}je M{\aa}lebordsblade, topographical maps, landscape change, automated production, object based image processing, H{\o}je M{\aa}lebordsblade, topographical maps, Historical maps",
author = "Gregor Levin and Groom, {Geoffrey Brian} and Svenningsen, {Stig Roar} and Perner, {Mads Linnet}",
year = "2020",
language = "English",
isbn = "978-87-7156-511-9",
series = "Scientific Report from DCE",
number = "389",
publisher = "Aarhus Universitet, DCE – Nationalt Center for Milj{\o} og Energi",
}