Forest cover mask from historical topographic maps based on image processing

This study aimed to obtain accurate binary forest masks which might be directly used in analysis of land cover changes over large areas. A sequence of image processing operations was conceived, parameterized and tested using various topographic maps from mountain areas in Poland and Switzerland. First, the input maps were filtered and binarized by thresholding in Hue‐Saturation‐Value colour space. The second step consisted of a set of morphological image analysis procedures leading to final forest masks. The forest masks were then assessed and compared to manual forest boundary vectorization. The Polish topographical map published in the 1930s showed low accuracy which could be attributed to methods of cartographic presentation used and degradation of original colour prints. For maps published in the 1970s, the automated forest extraction performed very well, with accuracy exceeding 97%, comparable to accuracies of manual vectorization of the same maps performed by nontrained operators. With this method, we obtained a forest cover mask for the entire area of the Polish Carpathians, easily readable in any Geographic Information System software.

[1]  Danny A. P. Hooftman,et al.  HistMapR: Rapid digitization of historical land-use maps in R , 2017, bioRxiv.

[2]  Heather Wood,et al.  HistMapR: Rapid digitization of historical land-use maps in R , 2017, bioRxiv.

[3]  Volker C. Radeloff,et al.  Broad scale forest cover reconstruction from historical topographic maps , 2016 .

[4]  M. Herold,et al.  The potential of old maps and encyclopaedias for reconstructing historic European land cover/use change , 2015 .

[5]  M. Bürgi,et al.  264 years of change and persistence in an agrarian landscape: a case study from the Swiss lowlands , 2015, Landscape Ecology.

[6]  Bruce Godfrey,et al.  An Adaptable Approach for Generating Vector Features from Scanned Historical Thematic Maps Using Image Enhancement and Remote Sensing Techniques in a Geographic Information System , 2015 .

[7]  J. Kozak,et al.  Uncertainty in Historical Land-Use Reconstructions with Topographic Maps , 2014 .

[8]  Shuwen Zhang,et al.  A review of historical reconstruction methods of land use/land cover , 2014, Journal of Geographical Sciences.

[9]  V. Radeloff,et al.  orest and agricultural land change in the Carpathian region — meta-analysis of long-term patterns and drivers of change , 2014 .

[10]  Craig A. Knoblock,et al.  A Survey of Digital Map Processing Techniques , 2014, ACM Comput. Surv..

[11]  Marika Kornaś ICE PHENOMENA IN THE WARTA RIVER IN POZNAŃ IN 1961– 2010 , 2014 .

[12]  Craig A. Knoblock,et al.  Recognizing text in raster maps , 2014, GeoInformatica.

[13]  Martin Paegelow,et al.  Automatic Extraction of Forests from Historical Maps Based on Unsupervised Classification in the CIELab Color Space , 2013, AGILE Conf..

[14]  Koshy Varghese,et al.  Vectorization of contour lines from scanned topographic maps , 2012 .

[15]  Jacek Kozak,et al.  Automatic detection of forest regions on scanned old maps , 2012 .

[16]  Aria Pezeshk,et al.  Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Craig A. Knoblock,et al.  Efficient and Robust Graphics Recognition from Historical Maps , 2011, GREC.

[18]  Stefan Leyk,et al.  Colors of the past: color image segmentation in historical topographic maps based on homogeneity , 2010, GeoInformatica.

[19]  R. Brad,et al.  CONTOUR LINES EXTRACTION AND RECONSTRUCTION FROM TOPOGRAPHIC MAPS , 2010 .

[20]  Rui-Qing Wu,et al.  Extracting contour lines from topographic maps based on cartography and graphics knowledge , 2009 .

[21]  Stefan Leyk,et al.  Extracting Composite Cartographic Area Features in Low-Quality Maps , 2009 .

[22]  Christine Estreguil,et al.  Forest cover changes in the northern Carpathians in the 20th century: a slow transition , 2007 .

[23]  Robert Weibel,et al.  Saliency and semantic processing: Extracting forest cover from historical topographic maps , 2006, Pattern Recognit..

[24]  Stefan Leyk,et al.  A Conceptual Framework for Uncertainty Investigation in Map‐based Land Cover Change Modelling , 2005, Trans. GIS.

[25]  Walter Anheier,et al.  An image analysis system for automatic data acquisition from colored scanned maps , 1994, Machine Vision and Applications.

[26]  Pierre Soille,et al.  Morphological Image Analysis: Principles and Applications , 2003 .

[27]  Stephen Wise Capturing Raster Data From Scanned Thematic Maps Using Desktop Graphics Software , 2002, Trans. GIS.

[28]  Chew Lim Tan,et al.  Text/Graphics Separation in Maps , 2001, GREC.

[29]  L. Östlund,et al.  Retrospective gap analysis in a Swedish boreal forest landscape using historical data , 2001 .

[30]  Pierre Soille,et al.  From scanned topographic maps to digital elevation models by , 2001 .

[31]  Luyang Li,et al.  Integrated text and line-art extraction from a topographic map , 2000, International Journal on Document Analysis and Recognition.

[32]  Stephen Wise Extracting raster GIS data from scanned thematic maps , 1999, Trans. GIS.

[33]  Prasanna G. Mulgaonkar,et al.  Verification-Based Approach for Automated Text and Feature Extraction from Raster-Scanned Maps , 1995, GREC.

[34]  Luc Vincent,et al.  Morphological grayscale reconstruction in image analysis: applications and efficient algorithms , 1993, IEEE Trans. Image Process..

[35]  Toru Kaneko Line structure extraction from line-drawing images , 1992, Pattern Recognit..

[36]  Spencer W. Thomas EFFICIENT INVERSE COLOR MAP COMPUTATION , 1991 .

[37]  Marc M. Ansoult,et al.  Mathematical Morphology : A Tool for Automated GIs Data ~ cquisition from Scanned Thematic Maps , 2007 .

[38]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .