Elsevier

Applied Geography

Volume 67, February 2016, Pages 39-48
Applied Geography

Broad scale forest cover reconstruction from historical topographic maps

https://doi.org/10.1016/j.apgeog.2015.12.003Get rights and content

Highlights

  • Point-based reconstruction overestimated forest against wall-to-wall-mapping by 1–3%.

  • Backdating and map generalisation caused the differences between reconstructions.

  • Point-based method was eight times faster than wall-to-wall mapping.

Abstract

Land cover change is one of the major contributors to global change, but long-term, broad-scale, detailed and spatially explicit assessments of land cover change are largely missing, although the availability of historical maps in digital formats is increasing. The problem often lies in efficiency of analyses of historical maps for large areas. Our goal was to assess different methods to reconstruct land cover and land use from historical maps to identify a time-efficient and reliable method for broad-scale land cover change analysis. We compared two independent forest cover reconstruction methods: first, regular point sampling, and second, wall-to-wall mapping, and tested both methods for the Polish Carpathians (20,000 km2) for the 1860s, 1930s and 1970s. We compared the two methods in terms of their reliability for forest change analysis, relative to sampling error, point location and landscape context including local forest cover, area of the spatial reference unit and forest edge-to-core ratio. Our results showed that the point-based analysis overestimated forest cover in comparison to wall-to-wall mapping by 1–3%, depending on the mapping period. The reasons for the differences were mainly the backdating approach and map generalisation rather than the point grid position or sampling error. When we compared forest cover trajectories over time, we found that the point-based reconstruction captured forest cover dynamics with a comparable accuracy to the wall-to-wall mapping. More broadly, our assessment showed that historical maps can provide valuable data on long-term land cover trends, and that point-based sampling can be an efficient and accurate way to assess forest area and change trends. We suggest that our point-based approach could allow land cover mapping across much of Europe starting in the 1800s. Our findings are important because they suggest that land cover change, a key component of global change, can be assessed over large areas much further back in time than it is commonly done. This would allow to truly understand path dependencies, land use legacies, and historical drivers of land cover change.

Introduction

Land use and land cover changes are key components of global change (Foley et al., 2005), affecting changes in biodiversity (Allan et al., 2014, Newbold et al., 2015), climate (Heald and Spracklen, 2015, Stocker et al., 2014) and other ecosystem functions (Lawler et al., 2014). Therefore a clear understanding of land use changes over time is crucial to predict future changes and effectively manage ecosystems. Existing spatially explicit long term land use and land cover data offer excellent global products, but these are not suitable for regional applications (Klein Goldewijk et al., 2010, Pongratz et al., 2008, Ramankutty and Foley, 1999) leading to uncertainties in existing land use theories such as path dependency (Brown et al., 2014, Chavez and Perz, 2013, Lambin et al., 2006), land use legacies (Foster et al., 2003, Munteanu et al., 2014, Plieninger et al., 2010), and the interactions of change trajectories with other land change driving forces (Jepsen et al., 2013, Lambin and Meyfroidt, 2010, Meyfroidt et al., 2013). Similarly, high resolution satellite data on land cover change is only available since the mid-20th century (e.g. based on Corona missions; Song et al., 2015) and from Landsat mission launched in 1970s (Belward and Skøien, 2014, Griffiths et al., 2014, Hansen et al., 2013). However, valuable land use information can be obtained from historical maps. The combination of aerial photography, satellite imagery, and historical maps can provide valuable information about centuries of land change and their effects on humans and their environment (Fuchs et al., 2015, Gerard et al., 2010, Munteanu et al., 2015).

Despite its scientific value, historical map analysis over large areas is still relatively rare, because it requires extensive contextual knowledge (Kaim et al., 2014, Leyk et al., 2005, Plewe, 2002) and because the analysis of historical maps is time and labour intensive, due to geometrical rectification, digitization, and the manual assignment of land use and land cover classes. This is why long term, map-based land change studies are mostly confined to relatively small areas (e.g. Bürgi, Salzmann, & Gimmi, 2015), and historical maps are rarely used for global or continental reconstructions (Fuchs et al., 2015, Klein Goldewijk et al., 2010, Ramankutty and Foley, 1999). The existing global or continental reconstructions offer long time horizons, but their spatial resolution and local accuracy is too low to study land changes at the regional scales. Historical maps represent the only viable approach to assess centuries of land cover change for large areas reliably, and that is why it is important to develop methods to analyse such maps effectively.

Especially in Europe, a large amount of historical land use information is available in the form of triangulation-based historical maps starting in the 19th century. Extensive topographic map collections are available, for example, for the former Austrian Empire (Timár, Biszak, Székely, & Molnár, 2010), Belgium (Depuydt, 1975), the Netherlands, Portugal, and many other European countries (Böhme, 1989) and regions (Nordrhein-Westfalen, 1967) (Table 1). Many of these maps are already scanned and available on the Internet, as is the case for France (http://www.geoportail.gouv.fr), the United Kingdom (http://www.british-history.ac.uk/; http://maps.nls.uk/), Germany (http://gso.gbv.de/), Sweden (http://www.lantmateriet.se/), the Czech Republic (http://geoportal.cuzk.cz/), and Italy (http://www.igmi.org/). Similarly, many of the European historical cartographic sources have been successfully used to analyse different land use change processes at local scales. For example, in Germany, 18th century forest vegetation was reconstructed from historical maps (Wulf & Rujner, 2010), in Switzerland wetlands decline was assessed based on topographic maps since 1850 (Gimmi, Lachat, & Bürgi, 2011), and in Sweden 19th century maps showed the decline of deciduous forest over time (Axelsson, Östlund, & Hellberg, 2002). In western France the analysis of historical maps showed that over the last 200 years grasslands were generally rare, and dominated the area only in the 1950s, which is important because many conservation strategies in this areas have focused on the protection of grassland because of their supposed naturalness (Godet & Thomas, 2013). Similarly, in the Ukrainian Carpathians, map-based studies of mountain grasslands showed that livestock farming increased up to the Second World War, causing the timberline to decrease in elevation (Sitko & Troll, 2008). In contrast, in Romania due to the decline of transhumance, forest cover increased at the timberline (Shandra, Weisberg, & Martazinova, 2013). In Poland, historical maps confirmed the stability of the forest cover in the Białowieża Primeval Forest in the last 200 years (Mikusinska, Zawadzka, Samojlik, Jędrzejewska, & Mikusiński, 2013).

Case studies documenting land use change are usually prepared for relatively small areas, for many reasons, including limited availability and the time necessary to prepare and analyse historical maps. Furthermore, straightforward comparisons of case studies between countries and regions are often problematic because of differences in land use classification catalogues (Munteanu et al., 2014). Although such case studies may provide valuable insights into local long term land change processes (Flyvbjerg, 2006), broader comparative studies are necessary to better understand the full range of land use change patterns and their drivers (Bürgi, Hersperger, & Schneeberger, 2005). A meta-analysis approach can be useful to synthesize land use data at broader scales (Munteanu et al., 2014, Rudel, 2008, Van Asselen et al., 2013). However, such meta-analyses entail the risk of biased conclusions, because single local scale case studies are frequently designed to highlight special cases, and do not provide a representative sample of change.

The question thus is how to accurately and efficiently analyse historical maps not only in local studies, but also for large areas. A statistically sound sampling strategy represents one potential solution to this problem. Regularly spaced samples are currently used to assess global forest cover changes (FAO, 2010, Potapov et al., 2011), as well as to collect land use and land cover data at national levels. For instance, Switzerland is covered by a 100-m grid of sample points, each assigned to one of 74 land use categories (SFSO, 2001), and Norway by a 18-km grid used to monitor changes in 57 land cover classes (Strand, 2013). Across Europe, the LUCAS (Land Use/Cover Area frame statistical Survey) sample grid spaced at 2-km distance, is used to monitor and analyse land use changes across the European Union (Eurostat, 2003). The main idea behind sampling procedures, as opposed to complete mapping, is to limit the cost of data acquisition (Strand, 2013). To date, however, gridded sampling designs have rarely been used to collect and analyse historical land use data from archival maps (Loran et al., 2015, Munteanu et al., 2015), and most importantly, these sampling strategies have not been validated against a complete, continuous dataset to quantify their limitations.

Our goal here was to identify an efficient and accurate method to analyse historical land cover change at regional or even continental scale. Using the example of forest cover in the Polish Carpathians, we compared the accuracy of point sampling to wall-to-wall digitizing of historical maps, and evaluated the influence of the reconstruction method on forest cover change analysis. Furthermore, we assessed to what extent the differences in forest cover between point-based reconstruction and wall-to-wall mapping can be explained by sampling error, point position, and landscape context. We estimated also the time needed to assess forest cover and its changes using various reconstructions, for large study areas. Finally, we proposed a sound methodology for the efficient analysis of land use change from historical maps for large areas. Our research can thus inform a pan-European historical land use reconstruction initiative, using the already available Europe-wide point grid as a basis.

Section snippets

Materials and methods

Our study area covers the Polish Carpathians (20,000 km2), located in the northern part of the Carpathian arc with altitudes ranging from 300 m at the northern margin of the Carpathian Foothills and 2500 m in the Polish part of the Tatra Mts. (Balon et al., 1995). Typical landscapes consist of a mosaic of agricultural lands and forests, with most settlements located in valleys.

We conducted two independent forest cover reconstructions: a forest/non-forest map based on a regular set of points,

Differences at the regional level

The results for the entire Polish Carpathians showed that original points had slightly higher forest cover estimates than both polygons and automatically-assigned points (Fig. 4). Overestimation occurred in each time period, but it was highest for the 1930s (3.24% difference, compared to 1.87% for the 1860s, and 1.01% for the 1970s; Fig. 4). Differences between polygons and automatically-assigned points did not exceed 0.5 percentage points of forest cover at any time period.

The sampling error

Discussion

The main objective of our paper was to identify a time effective land use reconstruction method for broad-scale land change analysis. We compared regular point-based and wall-to-wall mapping reconstructions at two spatial scales (regional and local), focussing on the influence of point position, sampling error, human errors and potential contextual factors. We found that results from the point-based reconstruction did not differ substantially from wall-to-wall-mapping but required roughly one

Conclusions

Historical land use reconstructions are important for climate, carbon or biodiversity assessments (Fuchs et al., 2013, Gimmi et al., 2011, Ramankutty and Foley, 1999). They can be based on various data sources influencing the temporal and spatial extent of the analysis (Bürgi et al., 2007, Yang et al., 2014, Ye et al., 2015). Historical maps have one important advantage over land use statistics in that they show exact boundaries of various land use types. There are several problems when using

Acknowledgements

This work was carried out within the FORECOM project (Forest cover changes in mountainous regions – drivers, trajectories and implications, PSRP 008/2010) supported by a grant from Switzerland through the Swiss contribution to the enlarged European Union, the Land-Cover and Land-Use Change Program and an Earth and Spatial Science Fellowship of the National Aeronautic Space Administration (NASA). We are grateful to all team members of these projects who contributed to our work, in particular to

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