The third Italian National Forest Inventory: state of...

2nd International Workshop on Forest Inventory Statistics

Kromeriz, Czech Republic, 24th-26th May 2016

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)

[email protected]

mailto:[email protected]



1950s => 1980s ISTAT National Forest Statistics

1983 -1987 1st Italian NFI (IFNI85)

1985 => 2007 ISTAT National Forest Statistics & IFNI1985 data

2003-2007 2nd 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)

2013-2018? 3rd Italian NFI

INTRODUCTION

Italian National Forest Inventory and National Forest Statistics



National Forest Service (CFS-MiPAAF)

(and Regional Forest Services)

INFC - National Inventory of Forests and of Forest Carbon Sinks

2003 -2007

Fundings - Ministry of Agricultural, Food and Forestry Policies (MiPAAF)

CREA-MPF*

Forest Monitoring and Management

Research Unit

Budget management & organization,

photointerpretation & field surveys

Project, scientific support,

training, data processing

External consultants

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)

INTRODUCTION

* former ISAFA and CRA-MPF



Fattorini L., Marcheselli M., Pisani C., 2006 - A three-phase sampling strategy for large-scale multiresource forest inventories. Journal

of Agricoltural, Biological and Environmental Statistics, 11, 296-316

A three-phase sampling design for INFC

Tessellated sampling, unaligned systematic

distribution of the sampling units in the 1st phase

Stratified random sampling in the 2nd and 3rd phase

Two-phase estimation for the areal extent of land

categories (land cover/use, forest types), based on

aerial photo-interpretation (1st phase) and qualitative

measurements on the ground (2nd phase)

Three-phase estimation of forest growing stock,

biomass, deadwood volumes etc. based on field

survey measurements (3rd phase)

SAMPLING DESIGN



1st phase sample

N = 301,000 Land cover classification

No-Forest cover Forest cover

(2nd phase strata)

Photo-interpretation

SAMPLING DESIGN



1st phase sample

N = 301,000

Land cover

classes

No-forest

classes Forest classes

(2nd phase strata)

2nd phase subsample

n = 30,000

Forest

Photo-interpretation

Land Use

No-forest Forest categories

(3rd phase strata)

Other

land uses

Area distribution by forest categories and

qualitative attributes

Forest area estimates

Field survey: land use and forest

categories classification +

qualitative attributes assessment

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

SAMPLING DESIGN



1st phase sample

N = 301,000

Land Cover

Classes

No-forest

Cover Classes Forest Cover Classes

(2nd phase strata)

2nd phase subsample

n = 30,000

Forest

Photo-interpretation: land cover

classification

Land Use

No-forest Forest categories

(3rd phase strata)

Other

land uses

Area distribution by forest categories and


3rd phase subsample

m = 6,865 Total and density estimates

Forest area estimates

Field survey: measurements of

quantitative attributes

Field survey: land use and forest

categories classification +

qualitative attributes assessment

SAMPLING DESIGN



SAMPLING DESIGN

Plot design for tree/shrub & deadwood measurements and qualitative assessments

trees (dbh >= 10 cm) lying deadwood (min. diameter = 10 cm) stumps

tree regeneration and shrubs (h>= 50 cm)

trees (dbh >= 4.5 cm)


soil and litter

50 m2

530 m2

N

12 m2

2000 m2

900 cm2



SAMPLING DESIGN



(ha) S.E.(%) (m3) S.E.(%)

Piemonte 870,594 1.1 129,776,430 3.0

Valle d'Aosta 98,439 3.1 15,334,302 7.6

Lombardia 606,045 1.4 108,036,723 4.1

Alto Adige 336,689 1.6 105,188,527 4.6

Trentino 375,402 1.4 105,776,549 4.7

Veneto 397,889 1.7 81,195,960 4.6

Friuli V.G. 323,832 1.7 67,830,001 5.3

Liguria 339,107 1.5 49,438,791 4.5

Emilia Romagna 563,263 1.4 72,338,122 3.9

Toscana 1,015,728 1.0 131,955,985 3.1

Umbria 371,574 1.4 29,254,669 4.8

Marche 291,394 1.8 24,293,622 6.6

Lazio 543,884 1.4 57,510,635 4.6

Abruzzo 391,492 1.5 50,492,831 4.6

Molise 132,562 2.9 14,635,984 8.9

Campania 384,395 1.9 42,502,693 6.0

Puglia 145,889 3.4 12,160,485 10.9

Basilicata 263,098 2.4 27,661,206 6.9

Calabria 468,151 1.8 87,967,454 4.7

Sicilia 256,303 2.7 23,182,797 6.7

Sardegna 583,472 2.0 32,882,733 5.6

Italy 8,759,200 0.4 1,269,416,499 1.1

Forest area Growing stockAdministrative Region

RESULTS – INFC2005



0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Forest category

Fo

rest

ca

teg

ory

are

a (

ha)

Max S.E.%= 7.7% Min S.E.%= 1.8%

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





472 725 143 t 38.1%

24 855 508 t 2.0%

28 322 932 t 2.3%

715 673 675 t 57.6%

Aboveground biomass Deadwood Litter Soil

1.24 Billions tons

Carbon stored in Italian forests




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



COSTS N photoplots: 300,000 man-days: 2,000 (1 photo-interpreter – 150 points/day) n field survey: 30,000 (2nd phase) man-days : 45,000 (2 points/day for a 3 surv. field crew) m field survey: 6,900 (3rd phase) man-days : 20,700 (1 point/day for a 3 surv. field crew)

TOT man-days : 67,700

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

INFC2005 – three phases One-phase NFI (simulation) RESULTS

S.E. = 0.4 %

Forest area: 8,759,000

Forest cover percentage: 29%

RESULTS

S.E. = 0.45 % (0.9/2)






COSTS

N photoplots: 300,000 man-days: 2,000 (1 photo-interpreter – 150 points/day) n field survey: 30,000 (2nd phase) man-days : 90,000 (1 point/day for a 3 surv. field crew)

TOT man days: 92,000

Two-phase (simulation)

RESULTS

s.e. = 0.4 %



RESULTS

s.e. = 0.4 %



COSTS N photoplots: 300,000 man-days: 2,000 (1 photo-interpreter – 150 points/day) n field survey: 30,000 (2nd phase) man-days : 45,000 (2 points/day for a 3 surv. field crew) m field survey: 6,900 (3rd phase) man-days : 20,700 (1 point/day for a 3 surv. field crew)

TOT man-days : 67,700

INFC2005 – three phases




Arguments against

Organisation complexity, time scheduling 56 photo-interpreters, located in 21 different offices

101 and 84 crews for the 2nd and 3rd phase respectively, 850 training days during the period 2002-

2005

sample selection in 2nd and 3rd phase depending on the results of the previous phase




land cover

classes

(5 sampled)

administrative

regions

(21)

2nd phase strata

(95)

2nd phase

strata

forest

types

(21)

3rd phase

strata

(478)

The actual number of strata was

smaller than the therorical one, but

very large


Arguments against

Large number of sampling strata



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




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 2nd phase

plots and 3rd phase plots, at the same time; unified survey protocol (qualitative assessment

of forest stands + quantitative measurements on trees in forest plots)

INFC2015 – 3rd 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 1st 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)

(2015-16) -> 2017-18 – two years field surveys


Main topics




1st 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)




Photo-interpretation of land cover/use

Colour -infrared orthophotos (AGEA), years 2010-12, 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





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

Land cover sub-classes

Artificial surfaces Urban parks

Agricultural areas Forest plantations

Forest and semi-natural areas

Forest and other wooded land

Wetlands

Waterbodies

Plantations for timber production

prob. Forest land (cc>10%)

prob. OWL (cc 5-10%)

Temporary unstocked areas

Unclassified (clouds, shadows, bad

quality ortophotos, unrecognizable

land cover/use)





Orthophotos of years 2000-2002, 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



Forest area estimate based on photointerpretation + simulation of 2nd phase

classification

We derived the preliminary estimation of forest area using updated photo-

interpretation data and the rate of confirmed forest plots observed in

INFC2005 (for carbon reporting, end of 1st CP)


Preliminary estimates of forest area

?

INFC2005 INFC2015

Aree boscate da fotointerpretazione 10 995 410 11 678 133

INFC2005 INFC2015

Bosco esclusi Impianti Arboricoltura 8 636 949 9 165 505

Altre terre boscate 1 708 333 1 816 508

Superficie forestale totale esclusi Impianti Arboricoltura 10 345 282 10 982 013

F+OWL area after

photointerpretation

F+OWL area after

2nd phase field

surveys




Preliminary estimates of forest area

Forest area increase

confirmed, but at a lower rate

Forest area increase for all

administrative regions




Sample selection for the field survey

INFC2015 photo-interpretation to

derive 2nd 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





Use of INFC2005 2nd 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





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 1st phase results and

pilot study: 8580 plots

Pilot study in two regions to investigate the difficulty of correctly re-

positioning plots in the field after ten years (85-90% )



THANK YOU FOR YOUR ATTENTION

The third Italian National Forest Inventory: state of...

Documents

Transcript of The third Italian National Forest Inventory: state of...