*

Design-based methodological advances to support national forest inventories: a review of recent proposals

Lorenzo Fattorini   

iForest - Biogeosciences and Forestry, Volume 8, Issue 1, Pages 6-11 (2015)
doi: https://doi.org/10.3832/ifor1239-007
Published: Jun 18, 2014 - Copyright © 2015 SISEF

Review Papers


The aim of this paper is to give an overview of some recent proposals to support national forest inventories. The reviewed literature is strictly of design- based nature, i.e., uncertainty only stems from the sampling scheme actually adopted in the survey, rather than being assumed or modeled as in model- based approaches. National forest inventories are viewed as two-phase sample surveys to estimate at the same occasion the extent of the continuous population of points constituting the forest cover and the total of a forest attribute (e.g., volume or biomass) in the discrete population of trees for several forest types and/or administrative districts. The first phase is performed from remote sensing imagery while the second phase is performed on the field, possibly adopting the information acquired in the first phase as auxiliary information. A novel methodology is adopted based on Monte Carlo integration methods, which leads to a very general estimation strategy. Some recent proposals are considered in which remote sensing information acquired in the first phase is used to assess some physical characteristics of non-forest resources, such as woodlots, tree-rows and isolated trees outside the forest without additional field work. Finally, a new proposal is discussed in which canopy height from laser scanning is adopted as auxiliary information to recover missing data occurring when some sampled points cannot be reached because of hazardous terrain.

  Keywords


Two-phase Strategies, Aerial Information, Non-forest Resources, Missing Data, LiDAR, Calibration Weighting

Authors’ address

(1)
Lorenzo Fattorini
Department of Economics and Statistics, University of Siena, p.za S. Francesco 8, I-53100 Siena (Italy)

Corresponding author

 
Lorenzo Fattorini
lorenzo.fattorini@unisi.it

Citation

Fattorini L (2015). Design-based methodological advances to support national forest inventories: a review of recent proposals. iForest 8: 6-11. - doi: 10.3832/ifor1239-007

Academic Editor

Marco Borghetti

Paper history

Received: Jan 08, 2014
Accepted: Mar 11, 2014

First online: Jun 18, 2014
Publication Date: Feb 02, 2015
Publication Time: 3.30 months

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 10389
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 6775
Abstract Page Views: 181
PDF Downloads: 2734
Citation/Reference Downloads: 84
XML Downloads: 615

Web Metrics
Days since publication: 1921
Overall contacts: 10389
Avg. contacts per week: 37.86

Article Citations

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Aug 2019)

Total number of cites (since 2015): 10
Average cites per year: 2.00

 

Publication Metrics

by Dimensions ©

Articles citing this article

List of the papers citing this article based on CrossRef Cited-by.

 
(1)
Baffetta F, Corona P, Fattorini L (2011a)
Assessing the attributes of scattered trees outside the forest by a multi-phase sampling strategy. Forestry 84: 315-325.
CrossRef | Gscholar
(2)
Baffetta F, Fattorini L, Corona P (2011b)
Estimation of small woodlot and tree row attributes in large scale forest inventories. Environental and Ecological Statistics 18: 147-167.
CrossRef | Gscholar
(3)
Barabesi L (2003)
A Monte Carlo integration approach to Horvitz-Thompson estimation in replicated environmental designs. Metron 61: 355-374.
Gscholar
(4)
Barabesi L, Marcheselli M (2003)
A modified Monte-Carlo integration. International Mathematical Journal 3: 555-565.
Gscholar
(5)
Barabesi L, Franceschi S (2011)
Sampling properties of spatial total estimators under tessellation stratified designs. Environmetrics 22: 271-278.
CrossRef | Gscholar
(6)
Corona P (2000)
Introduzione al rilevamento campionario delle risorse forestali [Introduction to sampling of forest resources]. Edizioni CUSL, Firenze, Italy, pp. 284. [in Italian].
Gscholar
(7)
Corona P, Fattorini L (2006)
The assessment of tree row attributes by stratified two-stage sampling. European Journal of Forest Research 125: 57-66.
CrossRef | Gscholar
(8)
Corona P, Fattorini L (2008)
Area-based LiDAR-assisted estimation of forest standing volume. Canadian Journal of Forest Research 38: 2911-2916.
CrossRef | Gscholar
(9)
Corona P, Marchetti M (2007)
Outlining multi- purpose forest inventories to assess the ecosystem approach in forestry. Plant Biosystems 141: 243-251.
CrossRef | Gscholar
(10)
Corona P, Fattorini L, Franceschi S (2011a)
Two-stage sector sampling for estimating small woodlot attributes. Canadian. Journal of Forest Research 41: 1819-1826.
CrossRef | Gscholar
(11)
Corona P, Chirici G, McRoberts RE, Winter S, Barbati A (2011b)
Contribution of large-scale forest inventories to biodiversity assessment and monitoring. Forest Ecology and Management 262: 2061-2069.
CrossRef | Gscholar
(12)
Corona P, Agrimi M, Baffetta F, Barbati A, Chiriacò MV, Fattorini L, Pompei E, Valentini R, Mattioli W (2012a)
Extending large-scale forest inventories to assess urban forests. Environmental Monitoring and Assessment 184: 1409-1422.
CrossRef | Gscholar
(13)
Corona P, Cartisano R, Salvati R, Chirici G, Floris A, Di Martino P, Marchetti M, Scrinzi G, Clementel F, Travaglini D, Torresan C (2012b)
Airborne laser scanning to support forest resource management under alpine, temperate and Mediterranean environments in Italy. European Journal of Remote Sensing 45: 27-37.
CrossRef | Gscholar
(14)
Corona P, Chirici G, Franceschi S, Maffei D, Marcheselli M, Pisani C, Fattorini L (2014)
Design-based treatment of missing data in two-phase forest inventories using canopy height from laser scanning. Canadian Journal of Forest Research (early view).
CrossRef | Gscholar
(15)
de Vries PG (1986)
Sampling theory for forest inventory. Springer, Berlin, Germany, pp. 399.
Gscholar
(16)
Fattorini L, Marcheselli M, Pisani C (2004)
Two-phase estimation of coverages with second-phase corrections. Environmetrics 15: 357-368.
CrossRef | Gscholar
(17)
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: 1-21.
CrossRef | Gscholar
(18)
Fattorini L, Franceschi S, Maffei D (2013)
Design-based treatment of unit nonresponse in environmental surveys using calibration weighting. Biometrical Journal 55: 925-943.
CrossRef | Gscholar
(19)
Fewster RM (2011)
Variance estimation for systematic designs in spatial surveys. Biometrics 67: 1518-1531.
CrossRef | Gscholar
(20)
Gabler K, Schadauer K (2007)
Ansätse und Stichprobenpläne nationale Forstinventuren [Some approaches and designs of sample-based national forest inventories]. Austrian Journal of Forest Science 124: 105-133. [in German].
Gscholar
(21)
Gillis MD (2001)
Canada’s national forest inventory (responding to current information needs). Environmental Monitoring and Assessment 67: 121-129.
CrossRef | Gscholar
(22)
Gregoire TG, Valentine HT (2008)
Sampling strategies for natural resources and the environment. Chapmam & Hall, Boca Raton, FL, USA, pp. 492.
Gscholar
(23)
Gregoire TG, Ståhl G, Næsset E, Gobakken T, Nelson R, Holm S (2011)
Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, Norway. Canadian Journal of Forest Research 41: 83-95.
CrossRef | Gscholar
(24)
Haziza D, Thompson KJ, Yung W (2010)
The effect of nonresponse adjustments on variance estimation. Survey Methodology 36: 35-43.
Online | Gscholar
(25)
Kleinn C (2000)
On large area inventory and assessment of trees outside forests. Unasylva 51: 3-10.
Gscholar
(26)
Kleinn C (2002)
New technologies and methodologies for national forest inventories. Unasylva 53: 10-15.
Gscholar
(27)
Little RJA, Rubin DB (2002)
Statistical analysis with missing data (2nd edn). Wiley, New York, USA, pp. 381.
Gscholar
(28)
Maffei D (2011)
Design-based treatment of nonresponse in large-scale forest inventories: an application to the Italian National Forest Inventory. PhD thesis, Department of Statistics, University of Florence, Florence, Italy, pp. 79.
Gscholar
(29)
Mandallaz D (2008)
Sampling techniques for forest inventories. Chapman & Hall, Boca Raton, FL, USA, pp. 256.
Gscholar
(30)
McRoberts RE (2003)
Compensating for missing plot observations in forest inventory estimation. Canadian Journal of Forest Research 33: 1990-1997.
CrossRef | Gscholar
(31)
Montaghi A, Corona P, Dalponte M, Gianelle D, Chirici G, Olsson H (2013)
Airborne laser scanning of forest resources: an overview of research in Italy as a commentary case study. International Journal of Applied Earth Observation and Geoinformation 23: 288-300.
CrossRef | Gscholar
(32)
Næsset E (2002)
Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment 80: 88-99.
CrossRef | Gscholar
(33)
Næsset E (2004)
Practical large-scale forest stand inventory using small-footprint airborne scanning laser. Scandinavian Journal of Forest Research 19: 164-179.
CrossRef | Gscholar
(34)
Næsset E, Gobakken T, Holmgren J, Hyyppä H, Hyyppä J, Maltamo M, Olsson H, Persson A, Söderman U (2004)
Laser scanning of forest resources: the Nordic experience. Scandinavian Journal of Forest Research 19: 482-499.
CrossRef | Gscholar
(35)
Opsomer JD, Breidt FG, Moisen GG, Kauermann G (2007)
Model-assisted estimation of forest resources with generalized additive models. Journal of the American Statistical Association 102: 400-416.
CrossRef | Gscholar
(36)
Parker RC, Evans DL (2004)
An application of LiDAR in a double-sample forest inventory. Western Journal of Applied Forestry 19: 95-101.
Gscholar
(37)
Petersen YM, Rost HB (2011)
Swedish lidar project. New nationwide elevation model. GIM International 25, web site.
Online | Gscholar
(38)
Särndal CE, Lundström S (2005)
Estimation in survey with nonresponse. Wiley, New York, USA, pp. 199.
Gscholar
(39)
Särndal CE, Swensson B, Wretman J (1992)
Model-assisted survey sampling. Springer-Verlag, New York, USA, pp. 694.
Gscholar
(40)
Schreuder HT, Gregoire TG, Wood GB (1993)
Sampling methods for multiresource forest inventory. Wiley, New York, USA, pp. 446.
Gscholar
(41)
Scott CT, Bechtold WA, Reams GA, Smith WD, Hansen MH, Moisen GG (2004)
Sample-based estimators utilized by the forest inventory and analysis national information management system. In: “The Enhanced Forest Inventory and Analysis Programmational Sampling Design and Estimation Procedures” (Bechtold WA, Patterson PL eds). Southern Research Station, USDA Forest Service, Asheville, NC, USA, pp. 43-68.
Gscholar
(42)
Stephens PR, Kimberley MO, Beets PN, Paul TSH, Searles N, Bell A, Brack C, Broadley J (2012)
Airbone scanning LiDAR in a double sampling forest carbon inventory. Remote Sensing of Environment 117: 348-357.
CrossRef | Gscholar
(43)
Swart LMT (2010)
Swart LMT (2010) How the up-to-date height model of the Netherlands (AHN) became a massive point data cloud. In: “Management of massive point cloud data: wet and dry” (van Oosterom PJM, Vosselman MG, van Dijk TAGP, Uitentuis M eds). Netherlands Geodetic Commission, Delft, The Netherlands, pp. 17-32.
Online | Gscholar
(44)
Tomppo E, Gschwantner LM, McRoberts R (2010)
National forest inventories: pathways for common reporting. Springer, Heidelberg, Germany, pp. 612.
Gscholar
(45)
Wolter KM (1985)
Introduction to variance estimation. Springer-Verlag, New York, USA, pp. 427.
Gscholar
 

This website uses cookies to ensure you get the best experience on our website