The third Italian National Forest Inventory: state of implementation, methodological issues and first results of the survey

Transcription

1 The third Italian National Forest Inventory: state of implementation, methodological issues and first results of the survey P. Gasparini Consiglio per la ricerca in agricoltura e l analisi dell economia agraria Unità di ricerca per il Monitoraggio e la Pianificazione Forestale (Council for Agricultural Research and Economics - Forest Monitoring and Management Research Unit) CREA-MPF (Trento, Italy) patrizia.gasparini@crea.gov.it

2 INTRODUCTION Italian National Forest Inventory and National Forest Statistics 1950s => 1980s ISTAT National Forest Statistics st Italian NFI (IFNI85) 1985 => 2007 ISTAT National Forest Statistics & IFNI1985 data nd Italian NFI (INFC2005) 2007 => today INFC as official statistics for national and international reporting on forest area, growing stock, annual growth, silvicultural aspects, etc.; ISTAT provides data on timber production, and forest sector (forest holdings, workforce, wood trade) ? 3 rd Italian NFI

3 INFC - National Inventory of Forests and of Forest Carbon Sinks INTRODUCTION National Forest Service (CFS-MiPAAF) (and Regional Forest Services) Budget management & organization, photointerpretation & field surveys CREA-MPF * Forest Monitoring and Management Research Unit * former ISAFA and CRA-MPF L. Cavini (cartography and topography) Linnaea Ambiente S.r.l and TerraData Environmetrics (quality assurance protocol) RDM Progetti S.r.l.( crews training, field check) University La Sapienza, Roma (vegetation classification-system) University of Siena, Quantitative Methods Department (statistical aspects) University of Padova (plant pathology survey protocol) Project, scientific support, training, data processing External consultants Fundings - Ministry of Agricultural, Food and Forestry Policies (MiPAAF)

4 SAMPLING DESIGN A three-phase sampling design for INFC Tessellated sampling, unaligned systematic distribution of the sampling units in the 1 st phase Stratified random sampling in the 2 nd and 3 rd phase Two-phase estimation for the areal extent of land categories (land cover/use, forest types), based on aerial photo-interpretation (1 st phase) and qualitative measurements on the ground (2 nd phase) Three-phase estimation of forest growing stock, biomass, deadwood volumes etc. based on field survey measurements (3 rd phase) Fattorini L., Marcheselli M., Pisani C., A three-phase sampling strategy for large-scale multiresource forest inventories. Journal of Agricoltural, Biological and Environmental Statistics, 11,

5 SAMPLING DESIGN 1 st phase sample N = 301,000 Photo-interpretation Land cover classification Forest cover (2 nd phase strata) No-Forest cover

6 SAMPLING DESIGN 1 st phase sample N = 301,000 Photo-interpretation Forest classes (2 nd phase strata) Land cover classes No-forest classes 2 nd phase subsample n = 30,000 Field survey: land use and forest categories classification + qualitative attributes assessment Land Use Other land uses Forest categories (3 rd phase strata) Forest No-forest Forest area estimates Area distribution by forest categories and qualitative attributes

7 SAMPLING DESIGN The forest category was classified in the field on the basis of the prevailing tree species in the sample plot In mixed stands the prevailing tree species was selected by linear transect sampling

8 1 st phase sample N = 301,000 Photo-interpretation: land cover classification Forest Cover Classes (2 nd phase strata) Land Cover Classes SAMPLING DESIGN No-forest Cover Classes 2 nd phase subsample n = 30,000 Field survey: land use and forest categories classification + qualitative attributes assessment Land Use Other land uses Forest categories (3 rd phase strata) Forest No-forest Forest area estimates Area distribution by forest categories and qualitative attributes 3 rd phase subsample m = 6,865 Field survey: measurements of quantitative attributes Total and density estimates

9 SAMPLING DESIGN N Plot design for tree/shrub & deadwood measurements and qualitative assessments trees (dbh >= 4.5 cm) 12 m cm 2 50 m m m 2 trees (dbh >= 10 cm) lying deadwood (min. diameter = 10 cm) stumps tree regeneration and shrubs (h>= 50 cm) qualitative attributes soil and litter

10 SAMPLING DESIGN

11 RESULTS INFC2005 Administrative Region Forest area Growing stock (ha) S.E.(%) (m 3 ) S.E.(%) Piemonte 870, ,776, Valle d'aosta 98, ,334, Lombardia 606, ,036, Alto Adige 336, ,188, Trentino 375, ,776, Veneto 397, ,195, Friuli V.G. 323, ,830, Liguria 339, ,438, Emilia Romagna 563, ,338, Toscana 1,015, ,955, Umbria 371, ,254, Marche 291, ,293, Lazio 543, ,510, Abruzzo 391, ,492, Molise 132, ,635, Campania 384, ,502, Puglia 145, ,160, Basilicata 263, ,661, Calabria 468, ,967, Sicilia 256, ,182, Sardegna 583, ,882, Italy 8,759, ,269,416,

12 Forest category area (ha) RESULTS INFC2005 1,200,000 1,000, , , ,000 1 Oak forests (Q.petraea, Q. pubescens, Q. robur) 2 Beech forests (F. sylvatica) 3 Oak forests (Q. cerris, Q. fraineto, other species) 4 Mixed deciduous broadleaved forests 5 Hornbeam forests (Carpinus sp., Ostrya carpinifolia) 6 Chestnut forests (C. sativa) 7 Holm oak forests (Q. ilex) 8 Norway spruce forests (P.abies) 9 Larch and stone pine forests (L. decidua, P. cembra) 10 Black pines, (P.nigra, P. laricio, P.leucodermis) 11 Hygrophilous forests 12 Mediterranean pines (P. domestica, P.marittima, P.halepensis) 13 Coark oak (Q. suber) 14 Scots pine (P. sylvestris) and Mountain pine (P. mugo) 15 Other evergreen broadleaved forests 16 Fir forests 17 Other coniferous forests 200, Forest category Min S.E.%= 1.8% Max S.E.%= 7.7%

13 RESULTS INFC Billions tons Carbon stored in Italian forests t 57.6% t 38.1% t 2.3% t 2.0% Aboveground biomass Deadwood Litter Soil

14 RESULTS INFC2005 Arguments for Precision of estimates, both for forest area and quantitative parameters Reduction of costs High accuracy of the classification of forest land (implementation of FAO definition) and forest categories Possibility to implement additional surveys on the INFC sampling grid, using INFC stratification

15 RESULTS INFC2005 INFC2005 three phases RESULTS S.E. = 0.4 % Forest area: 8,759,000 Forest cover percentage: 29% COSTS N photoplots: 300,000 man-days: 2,000 (1 photo-interpreter 150 points/day) n field survey: 30,000 (2 nd phase) man-days : 45,000 (2 points/day for a 3 surv. field crew) m field survey: 6,900 (3 rd phase) man-days : 20,700 (1 point/day for a 3 surv. field crew) TOT man-days : 67,700 One-phase NFI (simulation) RESULTS S.E. = 0.45 % (0.9/2) Forest area: 8,759,000 Forest cover percentage: 29% COSTS N sampling point: 134,000 m field survey: 38,900 man-days: 116,700 (1 point/day for a 3 surv. field crew) TOT man days: 116,700

16 RESULTS INFC2005 INFC2005 three phases RESULTS s.e. = 0.4 % Forest area: 8,759,000 Forest cover percentage: 29% COSTS N photoplots: 300,000 man-days: 2,000 (1 photo-interpreter 150 points/day) n field survey: 30,000 (2 nd phase) man-days : 45,000 (2 points/day for a 3 surv. field crew) m field survey: 6,900 (3 rd phase) man-days : 20,700 (1 point/day for a 3 surv. field crew) TOT man-days : 67,700 Two-phase (simulation) RESULTS s.e. = 0.4 % Forest area: 8,759,000 Forest cover percentage: 29% COSTS N photoplots: 300,000 man-days: 2,000 (1 photo-interpreter 150 points/day) n field survey: 30,000 (2 nd phase) man-days : 90,000 (1 point/day for a 3 surv. field crew) TOT man days: 92,000

17 RESULTS INFC2005 Arguments against Organisation complexity, time scheduling 56 photo-interpreters, located in 21 different offices 101 and 84 crews for the 2 nd and 3 rd phase respectively, 850 training days during the period sample selection in 2 nd and 3 rd phase depending on the results of the previous phase

18 RESULTS INFC2005 Large number of sampling strata Arguments against land cover classes (5 sampled) 2 nd phase strata (95) administrative regions (21) The actual number of strata was smaller than the therorical one, but very large 2 nd phase strata 3 rd phase strata (478) forest types (21)

19 RESULTS INFC2005 Efficiency of the sampling strategy we saved some thousands man-days work with respect to a one-phase or two-phase design; precision and accuracy of the estimates is quite good in relation to the survey costs Organisation and planning are demanding and subjected to unpredictable factors (e.g delays in survey activities or funding opportunities) Flexibility of the design to perform partial or integrative surveys using the same sampling strategy Possible problems in providing data users with particular purposes because of the complexity of design and the small sample used for quantitative measurements

20 INFC rd Italian NFI Main topics Sampling grid and sampling units INFC grid, 1x1 km Unaligned systematic -> same 300,000 inventory units selected for INFC2005 Sampling design Three phases for estimation (area estimates from data of two phases, totals and densities for quantitative variables from data of three phases) Two campaigns for the data collection: photo-interpretation + field survey on 2 nd phase plots and 3 rd phase plots, at the same time; unified survey protocol (qualitative assessment of forest stands + quantitative measurements on trees in forest plots)

21 INFC rd Italian NFI Main topics NFI structure and organisation Same structure and subjects: organizational/logistic unit (NFS) + scientific/technical unit (CREA-MPF) + external consultants (for IT - sw) Smaller number of field crews (~ 50, 1 to 3 by administrative region) Ongoing re-organization of the National Forest Service -> army corp (Carabinieri) Ongoing re-organization of CRA -> CREA Forestry Research Centre (?) Time schedule 2013 Photo-interpretation of the 1 st phase sampling units (photo-plots) 2014-today Planning of the field survey (survey protocols, pilot studies, analysis of first phase results, preliminary sample size assessment) ( ) -> two years field surveys

22 INFC rd Italian NFI 1 st phase - photo-interpretation of land cover/use Updating of photo-interpretation manual WebGIS development and implementation Training of photo-interpreters (2 sessions, 3 days each, May 2013) Photointerpretation (June-December 2013)

23 INFC rd Italian NFI Photo-interpretation of land cover/use Colour -infrared orthophotos (AGEA), years , resolution 0.5 m Web-GIS GeoINFO (SIN SpA & e-geos) -> automatic NFI-points assignment and selection during the photointerpretation, GIS layers visualization (DTM, topographic map, ), area and length measurement tools, graphic tool forest classification (fast check of minimum area, crown cover), GUI to assist classification, data storage

24 INFC rd Italian NFI Photo-interpretation of land cover/use FAO definition of Forest (as in INFC2005), same classification scheme for land cover (5 CORINE main classes, 13 photo-interpretation classes, 5 of which of interest for NFI) Land cover classes Artificial surfaces Land cover sub-classes Urban parks Plantations for timber production prob. Forest land (cc>10%) Agricultural areas Forest plantations prob. OWL (cc 5-10%) Forest and seminatural areas Wetlands Waterbodies Forest and other wooded land Temporary unstocked areas Unclassified (clouds, shadows, bad quality ortophotos, unrecognizable land cover/use)

25 INFC rd Italian NFI Photo-interpretation of land cover/use Orthophotos of years , used in INFC2005, to detect land cover/use changes (blind check) Quality assurance: classification check of approx. 15,000 photoplots by skilled photo-interpreters (50% during the photo-interpretation, to get harmonized classification, 50% as final check); 10% of the photoplots blind checked

26 INFC rd Italian NFI Preliminary estimates of forest area Forest area estimate based on photointerpretation + simulation of 2 nd phase classification We derived the preliminary estimation of forest area using updated photointerpretation data and the rate of confirmed forest plots observed in INFC2005 (for carbon reporting, end of 1 st CP) INFC2005 INFC2015 Aree boscate da fotointerpretazione F+OWL area after photointerpretation? INFC2005 INFC2015 Bosco esclusi Impianti Arboricoltura Altre terre boscate Superficie forestale totale esclusi Impianti Arboricoltura F+OWL area after 2 nd phase field surveys

27 Preliminary estimates of forest area INFC rd Italian NFI Forest area increase confirmed, but at a lower rate Forest area increase for all administrative regions

28 Sample selection for the field survey INFC rd Italian NFI INFC2015 photo-interpretation to derive 2 nd phase strata weights Same classification scheme Additional information on evident land cover/use changes (~) Land cover/use changes due to subjectivity of classification Need for reduction of the number of strata

29 INFC rd Italian NFI Sample selection for the field survey Use of INFC nd phase data Forest category classification (FOR**FOR** strata) (assumption that the dominant species has not changed during the last 10 years) Check of land cover/use change (FOR**NO-FOR** strata) (on orthophotos?) Additional sub-sample from NO-FOR**FOR** strata Check of land cover/use change first on orthophotos and, if needed, in the field Forest category classification Measurements of quantitative variables

30 Sample selection for the field survey INFC rd Italian NFI Pilot study re-classification on orthophotos of two sub-samples of NFI points with land cover/use change Preliminary sample size for the field survey, based on 1 st phase results and pilot study: 8580 plots Pilot study in two regions to investigate the difficulty of correctly repositioning plots in the field after ten years (85-90% )

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