A GPS-BASED RECREATION ECOSYSTEM SERVICE
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1 A GPS-BASED RECREATION ECOSYSTEM SERVICE FOR THE GRENOBLE URBAN AREA, FRANCE Coline Byczek Pierre-Yves Longaretti Sandra Lavorel Credits: Isère Tourisme Grenoble Tourisme
2 ECOSYSTEM SERVICES NETWORKS FOR URBAN PLANNING 1. Case study: Grenoble urban planning area Lyon 2. Set of case-relevant ES models ES 1 ES 2 ES 3 ES 4 ES 5 Grenoble 30 KM 3. Analysis of spatial interactions ES networks «determining» ES, target ES 4. Scenario analysis: - Urban sprawl - Land use change ES 1 ES 2 ES 3 ES 4 ES 5 ES 4 ES 5 ES 1 ES 2 ES 3 5. ES projections Evolution of networks ES 1 ES 2 ES 3 ES 4 ES 5 ES 1 ES 2 ES 3 ES 4 ES 5
3 LANDSCAPES OF THE GRENOBLE AREA URBAN AND AGRICULTURAL PLAINS Grenoble urban area Chartreuse mountain range Valley of the Grésivaudan N.-E. agricultural plains Belledonne mountain range 10km Vercors mountain range Trièves Matheysine plateau Credits: Isère Tourisme Grenoble Tourisme
4 LANDSCAPES OF THE GRENOBLE AREA MOUNTAIN RANGES Grenoble urban area Chartreuse Valley of the Grésivaudan N.-E. agricultural plains Belledonne 10km Vercors Trièves Matheysine plateau Credits: Isère Tourisme Grenoble Tourisme
5 LANDSCAPES OF THE GRENOBLE AREA SEMI-MOUNTAINOUS AREAS Grenoble urban area Chartreuse mountain range Valley of the Grésivaudan N.-E. agricultural plains Belledonne mountain range 10km Vercors mountain range Trièves Matheysine Credits: Isère Tourisme Grenoble Tourisme
6 LANDSCAPES OF THE GRENOBLE AREA Grenoble urban area Chartreuse mountain range Valley of the Grésivaudan N.-E. agricultural plains Belledonne mountain range 10km Vercors mountain range Trièves Matheysine plateau Credits: Isère Tourisme Grenoble Tourisme
7 RECREATION DIFFERENT LANDSCAPES DIFFERENT PRACTICES Leisure areas near water bodies and rivers Easy hikes to nearby belvederes A great variety of sports in the mountain Credits: Béatrice Koumanov Manu Tessane Isère Tourisme Grenoble Bastille
8 CHALLENGES OF MODELLING RECREATION PRACTICES o Low data availability on site visitation rates No entrance gate data Cost and difficulty of surveys o Spatial diffusion of recreation practices Itineraries are up to the people Off-track venturing o Different uses of the same road and trail networks Estimation and spatialization are difficult But an increasing opportunity related to geo-referenced data on crowd-sourced websites
9 THE RECREATION OPPORTUNITY SPECTRUM MODEL Provision vs. demand Ecosystem service Maes et al. 2012
10 THE RECREATION OPPORTUNITY SPECTRUM MODEL Factors Provision vs. demand Ecosystem service Maes et al. 2012
11 THE RECREATION OPPORTUNITY SPECTRUM MODEL Spatial indicators Factors Provision vs. demand Ecosystem service Maes et al. 2012
12 THE RECREATION OPPORTUNITY SPECTRUM MODEL Provision vs. accessibility Spatial indicators Factors Provision vs. demand Ecosystem service Maes et al. 2012
13 THE RECREATION OPPORTUNITY SPECTRUM MODEL 10km Provision vs. accessibility Sub-models: lowlands vs. mountains Spatial indicators Factors Provision vs. demand Ecosystem service Maes et al. 2012
14 THE RECREATION OPPORTUNITY SPECTRUM MODEL 10km Provision vs. accessibility Sub-models: lowlands vs. mountains Accurate mapping of facilities (networks) Standardization Spatial indicators Factors Provision vs. demand Ecosystem service Maes et al. 2012
15 MODELLING FACTORS Spatial indicators Factors Provision vs. demand Ecosystem service
16 MODELLING FACTORS 10km Spatial indicators Factors
17 MODELLING FACTORS 10km Spatial indicators Factors
18 MODELLING FACTORS 10km Spatial indicators Factors Provision vs. demand
19 MODELLING FACTORS 10km Spatial indicators Factors
20 MODELLING FACTORS Common networks: roads, trails But where exactly? Spatial indicators Factors
21 USING GPS TRACKS FROM CROWD-SOURCED WEBSITES FOR MAPPING PRACTICES 4451 GPS tracks Merci Jeoren! 10 sports hiking trail running mountain biking cycling skiing snowshoe-hiking multi-pitch climbing mountaineering ice-climbing horse-riding Whole spatial extent of itinerary Sport-specific spatial networks Hiking Biking Skiing
22 MAPPING RECREATION SITES AND WATER-RELATED ACTIVITIES Climbing Water-related activities Slope filter: 35 Site coordinates Site guides Climbing site extents
23 MODELLING FACTORS 10km Spatial indicators Factors
24 MODELLING FACTORS 10km Spatial indicators Factors Provision vs. demand
25 MODELLING FACTORS 10km Provision vs. demand Ecosystem service
26 ES VALUES GEOREFERENCING RECREATION ES IN THE LOCAL OUTDOORS 1) Absolute values 2) Relative values (deciles) 10km 3) Hotspot analysis (Getis-Ord algorithm) 10km Predominance of mountain ranges Major hotspots in belvedere and high-profile hikes In the plains, local hotspots in natural areas near urban poles 10km
27 MODEL VALIDATION: COMPARISON WITH THE INVEST MODEL InVEST model: (Wood et al. 2013) - Georeferenced pictures (FlickR) - Spatial regression (user indicators) - Estimation of visitation rate Mountains Plains and valleys Estimate Std. Error sign. Estimate Std. Error sign. (Intercept) -2,259 0,018 *** -2,713 0,023 *** Natural landscapes -0,105 0,015 *** -0,159 0,017 *** Scenic beauty 0,189 0,014 *** Protected areas 0,133 0,021 *** Water proximity 0,107 0,021 *** Urban avoidance -0,132 0,013 *** -0,499 0,021 *** Noise avoidance -0,047 0,010 *** Hiking 0,304 0,016 *** 0,134 0,012 *** Cycling 0,211 0,013 *** 0,206 0,014 *** Skiing 0,257 0,012 *** Trail running 0,138 0,015 *** 0,066 0,012 *** Mountain biking 0,070 0,016 *** 0,194 0,018 *** Water stroll 0,028 0,012 * -0,103 0,02 *** Multi-pitch climbing 0,031 0,008 *** Climbing sites 0,057 0,009 *** Snowshoe-hiking 0,023 0,007 ** Lake leisure 0,078 0,010 *** 0,079 0,009 *** Accessibility (bus) 0,088 0,015 *** 0,057 0,017 *** Accessibility (car) 0,087 0,017 *** 0,140 0,019 *** ESNET > InVEST = ESNET < InVEST 10km Actual visitor presence Invest ESNET Perceived extent Point Trajectory Bias Urban Performance-oriented sports
28 MODEL VALIDATION: ONLINE SURVEY Ecosystem service perception Hypothesis validation Model parameterization Validation of results
29 MODEL VALIDATION: RESPONDENT PROFILES 935 valid answers Most respondents are avid sportsmen Mainly living in Grenoble (294) and immediate surroundings (225)
30 MODEL VALIDATION: SERVICE PERCEPTION
31 MODEL VALIDATION: HYPOTHESES VALIDATION Landscape preferences Different behaviours Importance of mountains and waterscapes Avoidance of human-impacted landscapes lowlands vs. highlands
32 MODEL VALIDATION: VALIDATION OF MODEL OUTPUTS Pearson's product-moment correlation data: grelou_db$stm_sum and esnet$n t = , df = 53, p-value < 2.2e-16 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: sample estimates: cor
33 PROJECTION OPPORTUNITIES FOR SCENARIO ANALYSIS Evolution of level of protection: - Sanctuary vs. resort mountains - Protected sites and biological corridors Land use change: - Evolution of land cover and landscape mosaic Success or failure at containing urban sprawl: - Urban sprawl in the valleys - Secondary poles in the plateaus Creation or abandonment of: - Leisure areas, mountain resorts - Restriction of access Evolution of snow cover in the winter Accessibility of natural sites: - Disappearance, or building of new access roads - Cable transport
34 PROJECTION OPPORTUNITIES FOR SCENARIO ANALYSIS: PEOPLE S DECLARED PREFERENCES
35 PROJECTION OPPORTUNITIES FOR SCENARIO ANALYSIS: PEOPLE S DECLARED PREFERENCES
36 CONCLUSION Insight on full extent of ecosystem use, accurate mapping Easy mapping of any number of activities > context of sport development Provide opportunities for management & conservation In our case, can be used as a proxy for visitation rates Hopefully GPS track access and processing will be automated soon
37 THANK YOU FOR YOUR ATTENTION
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