Forest land change assessment by continuous inventory
P. Corona1, E. Pompei2 and G. Scarascia Mugnozza1
1
Dipartimento di Scienze dell’Ambiente Forestale e delle Sue Risorse, University of Tuscia,
via San Camillo de Lellis, 01100 Viterbo, Italy.
e-mail: piermaria.corona@unitus.it
2
National Forest Service, Ministry of Agricultural and Forest Policies, Italy (PhD student,
University of Tuscia).
Introduction
Forest expansion is one of the main factors characterizing the landscape dynamics in many
European countries, and inventory and management of the areas recolonized by forests are
focal issues for sustainable forestry. A probabilistic estimation approach based on land-use
classification repeated on the same sampling points for two successive analyses is here
proposed.
The approach was experimented in the Abruzzo region (a region wider than 1-million-ha in
Central Italy), where the rate of forest expansion was assessed by multitemporal
classification of permanent sampling points on orthocorrected aerial photographs. The forest
area at the year 1990, a figure of great interest under the Kyoto protocol, was also
assessed.
Materials and methods
The sampling design in the time domain is a pure panel in which the same sampling units are
observed at every point in time. The number and geographical locations of the sampling points
were the same used for the first phase of the current Italian National Forest Inventory (INFC).
Orthocorrected panchromatic aerial photos, taken in 2002 and during the 1980s, were used for the
multi-temporal assessment of the forest area. Both series of orthophotos have 1-m2 pixel resolution
(nominal scale: 1:10000). The sampling points were classified into six land-use categories
according to a classification system similar to that officially adopted for the first phase of INFC.
The area change of the i-th land-use category between the first and the second forest inventories
can be estimated as
Zˆi = Azˆi
where: zˆi = pˆ i 2 − pˆ i1 ; pˆ i 2 = estimated proportion of sampling points of the i-th land-use category at
the time of the second inventory; pˆ i1 = estimated proportion of sampling points of the i-th land-use
category at the time of the first inventory; A = land area (known without error).
The estimated standard error of Ẑ i is
sˆZˆ = Asˆzˆi
i
where: sˆzˆi =
sˆ 2pˆ i 2 + sˆ 2pˆ i1 − 2 sˆ pˆ i 2 pi1 ; sˆ 2pˆ i 2 =
pˆ i 2 (1 − pˆ i 2 )
pˆ (1 − pˆ i1 )
pˆ − pˆ i 2 pˆ i1
; sˆ 2pˆ i1 = i1
; sˆ pi 2 pi1 = i1=2
; pˆ i1= 2
n −1
n −1
n −1
= proportion of the sampling points classified in the i-th land-use category both at the first and the
second inventories.
The average annual area change of the i-th land-use category can be estimated by vˆi = Zˆi l ,
where l is the number of years between the first and the second inventory occasion. The estimator
of the standard error of v̂i is sˆvˆi = sˆZˆ l .
i
The area of the i-th land-use category at an intermediate year between the two successive
inventory occasions, like, for example, the base year 1990, can be straightforwardly estimated
assuming that the annual area change between the two occasions is constant. Thus, the estimator
Aˆi ( 2− x ) of the area of the i-th land-use category x years before the second occasion is
x
⎛ x⎞
Aˆi ( 2− x ) = Aˆi 2 − xvˆi = ⎜1 − ⎟ Aˆi 2 + Aˆi1
l
⎝ l⎠
where: Aˆi 2 = pˆ i 2 A = estimated area of the i-th land-use category at the second inventory occasion;
Aˆ = pˆ A = estimated area of the i-th land-use category at the first inventory occasion.
i1
i1
The estimator of the standard error of Aˆi ( 2− x ) is
lx − x 2
⎛ x⎞
⎛ x⎞
= ⎜1 − ⎟ sˆ A2ˆ + ⎜ ⎟ sˆA2ˆ + 2 2 sˆAˆ Aˆ
i ( 2− x )
i 2 i1
l
⎝ l ⎠ i 2 ⎝ l ⎠ i1
where: sˆ A2ˆ = A2 sˆ 2pi 2 ; sˆ A2ˆ = A2 sˆ 2pi1 ; sˆ Aˆ Aˆ = A2 sˆ pi 2 pi1 .
2
2
sˆ Aˆ
i2
i1
i 2 i1
Results
In the whole Abruzzo region, the average annual area change of the observed land-use categories
is estimated to be (confidence intervals at 0.05 probability level are reported in brackets):
settlements: +323 (±83) ha year-1; cropland: -720 (±124) ha year -1; forest: +2439 (±219) ha year -1;
other wooded land: -1053 (±186) ha year -1; grassland: -989 (±144) ha year -1.
Forest area estimated at the base year 1990 is 403426 (±9295) ha, while the area of other wooded
land covered 38635 (±3242) ha. Overall, in 1990, wooded areas amounted to 442061 (±9844) ha.
Conclusions
According to the obtained results, the multitemporal assessment procedure tested proves to be
relatively easy to implement, and the proposed estimators as well as the estimators of the
corresponding variances are straightforwardly applicable. Moreover, they have turned out to be
satisfyingly efficient, considering the adopted sampling intensity (1 sampling point per km2, the
same of the first phase of the current National Forest Inventory): in this case study concerning a
repeated photopoint classification on orthocorrected aerial panchromatic images over a territory of
1081070 ha where forest covers around 40% of the land, a sampling effort corresponding to 200
days man-1 (for an approximate cost of 30000 euros, according to standard labour cost in Italy) has
provided a standard error below 5% for the estimation of forest annual expansion and a standard
error around 1% for the estimation of forest area at the year 1990.
To conclude, the assessment of forest dynamics on wide territories (and the eventually associated
carbon figures) obtained by a probabilistic estimation like that here tested (land-use classification
by permanent sampling points) is a viable, easy and objectively repeatable approach.