A qualitative method for the spatial and thematic downscaling of land-use change scenarios

Download A qualitative method for the spatial and thematic downscaling of land-use change scenarios

Post on 26-Jun-2016




0 download


  • pge



    e n v i r onm en t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 2 6 8 2 7 8

    avai lable at www.sc iencedi rec t .com

    .elDrummond Street, Edinburgh EH8 9XP, UKbCollege of Resources Science and Technology, Beijing Normal University, Beijing 100875, ChinacCentre for Agri-Environmental Research, School of Agriculture, Policy and Development, University of Reading, RG6 6AR, UK

    1. Introduction

    Land-use/-cover change has increased dramatically in recent

    decades due to rapid demographic and societal changes; this is

    expected to continue in many European regions (Busch, 2006;

    Lambin et al., 2001). Agricultural and urban lands are

    particularly susceptible to these changes and affect habitat

    quality for both flora and fauna. Increased urbanisation and

    peri-urban settlement results in fragmentation, which affects

    various ecosystem processes (Lambin et al., 2001). Assessing

    the impact of land-cover changes on ecosystem processes or

    habitat quality requires data with a fine spatial and thematic

    resolution (Conway, 2009). Spatial resolution is necessary to

    calculate the degree of fragmentation (patch size, connectivi-

    ty) precisely (Fahrig, 2003; Reidsma et al., 2006) and to preserve

    the representation of land-use types with typically small

    patches, such as grasslands, which may be lost at coarser

    resolutions (Schmit et al., 2006). Using a finer resolution also

    reduces the errors inherent to mapping methods, such as

    representing continuous data in a raster (grid) format

    (Dendoncker et al., 2008). Without sufficient thematic resolu-

    tion it is impossible to assess habitat quality correctly:

    agricultural land may include very different land-cover

    types, such as highly intensivemonocultures or low intensity,

    species-rich pastures (de Chazal and Rounsevell, 2009). This

    level of precision is often available for recent land-cover

    changes (post-1990), for instance in the CORINE land-cover

    (CLC) datasets (Buttner et al., 2002). Even the finest CLC

    classification (level 3, 44 classes) is arguably not sufficient for

    some ecological applications, especially as themore natural

    a r t i c l e i n f o

    Published on line 8 December 2010


    Rule-based approach

    Bio-energy crops

    Land abandonment

    Local knowledge

    United Kingdom

    a b s t r a c t

    Assessing the potential impact of future land-cover changes on habitat quality requires

    projections with a fine spatial and thematic resolution. The former is usually addressed by

    downscaling methods, often at the expense of the latter. We present a new, rule-based

    method to downscale land-use change scenarios to the landscape levelwhile keeping a large

    number of land-cover classes (CORINE level 3). The method relies on the interpretation of

    European scenario storylines, the observation of past land-use changes, high-resolution

    regional data and expert knowledge.

    The results give a landscape-level transposition of the scenario storylines which reflects

    the local conditions. The method has a number of advantages, such as its potential

    application in dialogues with policy-makers and stakeholders. Possible further develop-

    ments include automating the rule-based selection to overcome the current limitations of

    this method in terms of spatial extent.

    # 2010 Elsevier Ltd. All rights reserved.

    * Corresponding author. Tel.: +44 131 651 4449; fax: +44 131 650 2524.E-mail address: sophie.rickebusch@ed.ac.uk (S. Rickebusch).

    1462-9011/$ see front matter # 2010 Elsevier Ltd. All rights reserved.doi:10.1016/j.envsci.2010.11.003A qualitative method for the sdownscaling of land-use chan

    Sophie Rickebusch a,*, Marc J. Metzger a, GuaSimon G. Potts c, Maria Teresa Stirpe c, MarkaCentre for the Study of Environmental Change and Sustainability (

    journal homepage: wwwatial and thematicscenarios

    cai Xu a,b, Ioannis N. Vogiatzakis c,.A. Rounsevell a

    S), School of GeoSciences, The University of Edinburgh,


  • e n v i r onm en t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 2 6 8 2 7 8 269land-cover types, such as forest or shrub, are not very well

    differentiated in CLC (Neumann et al., 2007; Waser and

    Schwarz, 2006). However, high thematic resolution is less

    common for older changes, which makes the calibration of

    land-use/-cover changemodels very difficult. One exception is

    the BIOPRESS transect data, which details CLC level 3 land-

    cover in 1950, 1990 and 2000 (Gerard et al., 2010; Kohler et al.,

    2006; Thomson et al., 2007).

    Scenarios providing alternative images of how the future

    may unfold are a popular tool for exploring alternative

    plausible land-use futures (Ewert et al., 2005; Rounsevell et al.,

    2005, 2006; Rounsevell andMetzger, 2010;Verburg et al., 2006).

    Rounsevell et al. (2006) describe how the Intergovernmental

    Panel on Climate Change (IPCC) Special Report on Emissions

    Scenarios (SRES) (Nakicenovic and Swart, 2000) can be

    interpreted to derive European land-use change scenarios.

    The same methodology was used to develop the ALARM

    scenarios (Settele et al., 2005), which we use in this study. At

    theEuropean level, theALARMscenarios showacontinuation

    of current trends in land-use change, but with differing

    magnitudes between the scenarios (Reginster et al., 2010;

    Spangenberg et al., in press). Unfortunately, the 100 spatialresolution (approximately 16 km 16 km) of these projec-tions is too coarse for studies relating to biodiversity or

    ecosystem services, for instance. A number of quantitative

    downscaling methods have been used to refine the spatial

    resolution of land-use change projections (Dendoncker et al.,

    2006, 2008; Verburg et al., 2008, 2006). However, automated

    quantitative downscaling has limitations, such as the

    inability to adjust to the local context and the lack of control

    over the results. With fewer than 10 land-use categories, the

    thematic resolution of many current land-use scenarios also

    remains too coarse. Some studies use a finer thematic

    resolution in their particular field of interest, e.g. agriculture,

    but group all other land-uses into a single other category

    (Chakir, 2009). As observed by Conway (2009), increasing the

    number of classes in land-use change models may in some

    cases be detrimental tomodel accuracy, especiallywhere less

    frequent types of conversions are concerned. This may

    explain why so little attention has been paid to improving

    thematic resolution, despite its importance for ecological and

    other applications.

    For planners and policy-makers, it is essential to under-

    stand how land-use change might affect biodiversity and

    other ecosystem services, so that these services can be

    preserved and potential synergies or conflicts identified

    (Verburg et al., 2009). In turn, planners and policy-makers

    can also inform research by bringing local knowledge into the

    interpretation of scenario storylines for their region. This

    interaction is often overlooked when developing models and

    decision-making tools for management purposes (Jakeman

    et al., 2006).

    We describe here a rule-based downscaling method which

    provides plausible projections of land-cover change at the

    landscape level, with fine spatial and, more importantly,

    thematic resolution. By using a qualitative method, we

    circumvent the main problem with calibrating models for

    rare events, namely insufficient data. As it relies on visualisingthe data, this method enables us to check during the

    downscaling process that the results are representative oflocal conditions and has the potential to be used for policy

    dialogue. Finally, working at the local level allows the use of

    detailed data and ancillary knowledge, which are often not

    available for large-scale data.

    2. Materials and methods

    Projected land-use changes from the pan-European ALARM

    scenarios (Reginster et al., 2010; Spangenberg, 2007; Spangen-

    berg et al., in press) were thematically disaggregated and

    spatially allocated in a three-step process. Firstly, we derived

    the relative changes in four aggregated land-use categories

    from the ALARM scenarios and converted them to absolute

    increases or decreases in number of 100 m 100 m (1 ha) gridcellswithin seven transects from the BIOPRESS project (Gerard

    et al., 2010; Kohler et al., 2006; Thomson et al., 2007). Secondly,

    we disaggregated these changes to the more detailed CLC

    categories used in the transects, to obtain the number of 1 ha

    grid cells by which each land-cover category will increase or

    decrease under each scenario. Finally, we allocated these

    changes spatially within the transect using a combination of

    scenario-specific rules, regional information and expert

    judgement (by the author team at this stage). These three

    steps are detailed in Sections

    2.1. Land-cover data and scenarios

    We used land-cover data from seven transects in the United

    Kingdom (Fig. 1), taken from the BIOPRESS project (Gerard

    et al., 2010; Kohler et al., 2006; Thomson et al., 2007). The

    transects in that project were chosen to intersect with Natura

    2000 sites and are 15 km 2 km rectangles, though some havemissing sections due to lack of coverage by the aerial

    photographs from which the data is derived. The data follows

    CLC level 3 (44 classes). Each transect consists of a mosaic of

    polygons representing contiguous areas with a common land-

    cover history.

    For our purpose, the polygon data for each transect was

    converted to 100 m (1 ha) grids, one per time step (1950, 1990,

    2000). Thesewere then converted to point data,with the points

    in the centres of the grid cells. The associated attribute table

    contained the land-cover classes for the three past time steps,

    to which we added three fields for 2030, one per scenario.

    These were initially filled with the land-cover class for 2000.

    The ALARM land-use change scenarios (Reginster et al.,

    2010; Spangenberg, 2007; Spangenberg et al., in press) give

    projections of the percentage cover per 100 grid cell in 2030 forseven land-use categories, following the three storylines in

    Table 1. The land-use categories are: urban, cropland,

    grassland, permanent crops, biofuels, forests and land in

    succession (i.e. abandoned agricultural land). The construc-

    tion of the ALARM scenarios involved three steps: (1)

    construction of three alternative scenario storylines (Table

    1), (2) estimation of the aggregate totals of land-use change

    using a supply/demand model and (3) spatial allocation of

    these aggregate quantities using spatially explicit rules

    (Rounsevell et al., 2006). The methodology is described indetail by Reginster et al. (2010) and Spangenberg et al. (in


  • e n v i r onm en t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 2 6 8 2 7 82702.2. Change in aggregated land-use categories

    To quantify the land-cover changes in the transects, we need

    to know the relative changes compared to the current

    situation. This is done for five aggregated categories (cropland,

    forest, grassland, built-up areas and surplus land). As some

    Fig. 1 Location of the seven United Kingdom transects used an

    BIOPRESS transect UK1 (Gerard et al., 2010; Kohler et al., 2006).

    Table 1 Summary of the three ALARM scenario storylines: GR2007; Spangenberg et al., in press).

    In the GRAS (GRowth Applied Strategy) storyline, deregulation and free m

    regions. The guidelines of the European planning policies (The Europe

    patterns for new urbanisation are urban sprawl and diffuse peri-urban

    the free market policy and regional subsidies and compensation withi

    areas are only maintained in optimal locations with a comparative ad

    areas are preserved, but the NATURA 2000 site network is not enforce

    In the BAMBU (Business-As-Might-Be-Usual) storyline, the European plan

    Perspective, ESDP) are applied. Compact city development and limits o

    agricultural policy (CAP) is maintained, but adapted to avoid overprodu

    comparative advantage and a minimum level of agriculture is preserv

    current European afforestation policy is maintained. Current protected

    In the SEDG (Sustainable European Development Goal) storyline, integra

    extensification of agriculture and the encouragement of organic farmi

    biodiversity by, for example, limiting nitrogen and pesticide use. Small

    rural areas. Planning policies are strict and favour compact settlement

    public transport and other energy savings. Current protected areas areALARM categories such as bio-energy crops and surplus

    land are not currently present, we cannot calculate relative

    change figures for these. For bio-energy crops, we solved this

    by calculating the relative change for aggregated categories

    (total crops and total forests, Table 2) which incorporate

    the various bio-energy crop types. These relative changeswere

    d example of past land-cover changes (195019902000) in

    AS, BAMBU and SEDG (Reginster et al., 2010; Spangenberg,

    arket objectives lead to the reduction or abolition of zoning in

    an Spatial Development Perspective, ESDP) are not applied and the

    isation. Liberalisation of food trade is one of the consequences of

    n the common agricultural policy (CAP) are abolished. Agricultural

    vantage, where the agricultural rent is positive. Current protected


    ning policy guidelines (The European Spatial Development

    n peri-urbanisation are implemented and enforced. The common

    ction. Agricultural areas are maintained in optimal locations with a

    ed in traditional landscape for rural development objectives. The

    areas are preserved and the NATURA 2000 site network is enforced.

    ted social, environmental and economic policies lead to the

    ng. This reduces the effect of agricultural intensification on

    decreases in agricultural areas help to reduce unemployment in

    to reduce travel needs. This provides opportunities for efficient

    preserved and the NATURA 2000 site network is enforced.

  • e n v i r onm en t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 2 6 8 2 7 8 271thenused to calculate the absolute change in 1 ha grid cells per

    transect, whichwas then disaggregated to CLC level 3 (plus the

    new bio-energy categories).

    Two other land-cover category groups can be discerned.

    First, categorieswhich are assumed to be uninfluenced by the

    main land-use change drivers (Rounsevell et al., 2005). These

    include bare rock, water bodies, glaciers and natural areas,

    which were left out of this analysis as they do not change

    under the ALARM scenario assumptions. Second, the sur-

    plus land category, which consists mainly of abandoned

    agricultural land. It is defined as land remaining after the

    demand for urban uses, agriculture and forestry has been

    met. It can therefore be calculated as the difference between

    total land-use change and the sum of changes in all other


    TheALARMscenarioswere constructed using the relatively

    coarse 1 km resolution PELCOM land-cover map, which can

    deviate considerably from detailed regional land-use patterns

    (Dendoncker et al., 2008; Schmit et al., 2006), especially for

    land-uses with small spatial extents. Consequently, using

    individual 100 ALARM grid cells to derive future change maycause problems. For example, the ALARM grid cell might not

    Table 2 Correspondence...


View more >