*
 

iForest - Biogeosciences and Forestry

*

Are we ready for a National Forest Information System? State of the art of forest maps and airborne laser scanning data availability in Italy

Giovanni D’Amico (1)   , Elia Vangi (1-2), Saverio Francini (1-2-3), Francesca Giannetti (1-4-5), Antonino Nicolaci (6), Davide Travaglini (1), Lorenzo Massai (4-5), Yamuna Giambastiani (4-5-7), Carlo Terranova (8), Gherardo Chirici (1-5)

iForest - Biogeosciences and Forestry, Volume 14, Issue 2, Pages 144-154 (2021)
doi: https://doi.org/10.3832/ifor3648-014
Published: Mar 23, 2021 - Copyright © 2021 SISEF

Research Articles


Forest planning, forest management, and forest policy require updated, reliable, and harmonized spatial datasets. In Italy a national geographic Forest Information System (FIS) designed to store and facilitate the access and analysis of spatial datasets is still missing. Among the different information layers which are useful to start populating a FIS, two are essential for their multiple use in the assessment of forest resources: (i) forest mapping, and (ii) data from Airborne Laser Scanning (ALS). Both layers are not available wall-to-wall for Italy, though different local sources of information potentially useful for their implementation already exist. The objectives of this work were to: (i) review forest maps and ALS data availability in Italy; (ii) develop for the first time a high resolution forest mask of Italy which was validated against the official statistics of the Italian National Forest Inventory; (iii) develop the first mosaic of all the main ALS data available in Italy producing a consistent Canopy Height Model (CHM). An on-line geographic FIS with free access to both layers from (ii) and (iii) was developed for demonstration purposes. The total area of forest and other wooded lands computed from the forest mask was 102.608.82 km2 (34% of the Italian territory), i.e., 1.9% less than the NFI benchmark estimate. This map is currently the best wall-to-wall forest mask available for Italy. We showed that only the 63% of the Italian territory (the 60% of the forest area) is covered by ALS data. These results highlight the urgent need for a national strategy to complete the availability of forest data in Italy.

  Keywords


National Datasets, Forest Inventory, Forest Monitoring, Forest Mask, Airborne Laser Scanning, LiDAR

Authors’ address

(1)
(2)
Elia Vangi 0000-0002-9772-2258
Saverio Francini 0000-0001-6991-0289
Dept. of Bioscience and Territory (DiBT), University of Molise, c.da Fonte Lappone, I-86090 Pesche, IS (Italy)
(3)
Saverio Francini 0000-0001-6991-0289
Dept. of Innovation in Biological, Agro-Food and Forest System (DIBAF), University of Tuscia, v. San Camillo de Lellis, I-01100 Viterbo (Italy)
(4)
Francesca Giannetti 0000-0002-4590-827X
Lorenzo Massai 0000-0002-8252-0549
Yamuna Giambastiani 0000-0002-3613-2975
Bluebiloba startup Innovativa s.r.l., v. C. Salutati 78, 50126 Florence (Italy)
(5)
Francesca Giannetti 0000-0002-4590-827X
Lorenzo Massai 0000-0002-8252-0549
Yamuna Giambastiani 0000-0002-3613-2975
Gherardo Chirici 0000-0002-0669-5726
ForTech, University of Florence joint laboratory, v. San Bonaventura 13, 50145 Florence (Italy)
(6)
Antonino Nicolaci
Dept. of Computer Engineering, Modeling, Electronics, and Systems Science (DIMES), University of Calabria, v. P. Bucci 41C, I-87036 Rende, CS (Italy)
(7)
Yamuna Giambastiani 0000-0002-3613-2975
LAMMA Consortium - Environmental Modelling and Monitoring Laboratory for Sustainable Development, Florence (Italy)
(8)
Carlo Terranova
Geoportale Nazionale, Italian Ministry of the Environment, v. Cristoforo Colombo 44, 00147 Rome (Italy)

Corresponding author

 
Giovanni D’Amico
giovanni.damico@unifi.it

Citation

D’Amico G, Vangi E, Francini S, Giannetti F, Nicolaci A, Travaglini D, Massai L, Giambastiani Y, Terranova C, Chirici G (2021). Are we ready for a National Forest Information System? State of the art of forest maps and airborne laser scanning data availability in Italy. iForest 14: 144-154. - doi: 10.3832/ifor3648-014

Academic Editor

Matteo Garbarino

Paper history

Received: Sep 07, 2020
Accepted: Feb 18, 2021

First online: Mar 23, 2021
Publication Date: Apr 30, 2021
Publication Time: 1.10 months

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 4311
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 2651
Abstract Page Views: 382
PDF Downloads: 1205
Citation/Reference Downloads: 5
XML Downloads: 68

Web Metrics
Days since publication: 250
Overall contacts: 4311
Avg. contacts per week: 120.71

Article Citations

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Nov 2020)

(No citations were found up to date. Please come back later)


 

Publication Metrics

by Dimensions ©

Articles citing this article

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

 
(1)
Alberdi I, Cañellas I, Vallejo Bombín R (2017)
The Spanish national forest inventory: history, development, challenges and perspectives. Pesquisa Florestal Brasileira 37: 361.
CrossRef | Gscholar
(2)
Barbati A, Marchetti M, Chirici G, Corona P (2014)
European forest types and Forest Europe SFM indicators: tools for monitoring progress on forest biodiversity conservation. Forest Ecology and Management 321: 145-157.
CrossRef | Gscholar
(3)
Barilotti A, Turco S, Napolitano R, Bressan E (2005)
La tecnologia LiDAR per lo studio della biomassa negli ecosistemi forestali [LiDAR technology for biomass study in forest ecosystems]. In: Proceedings of “15th Meeting of the Italian Society of Ecology”. Turin (Italy) 12-14 Sept 2005, pp. 12-14. [In Italian]
Gscholar
(4)
Bartsch A, Widhalm B, Leibman M, Ermokhina K, Kumpula T, Skarin A, Wilcox EJ, Jones BM, Frost GV, Höfler A, Pointner G (2020)
Feasibility of tundra vegetation height retrieval from Sentinel-1 and Sentinel-2 data. Remote Sensing of Environment 237: 111515.
CrossRef | Gscholar
(5)
Bottalico F, Chirici G, Giannini R, Mele S, Mura M, Puxeddu M, McRoberts RE, Valbuena R, Travaglini D (2017)
Modeling Mediterranean forest structure using airborne laser scanning data. International Journal of Applied Earth Observation and Geoinformation 57: 145-153.
CrossRef | Gscholar
(6)
Buchhorn M, Smets B, Bertels L, Lesiv M, Tsendbazar NE, Herold M, Fritz S (2019)
Copernicus global land service: land cover 100m: epoch 2015: globe. Version V2.0.2. Presented at “ESA Living Planet Symposium 2019 (LPS2019)”, Milan (Italy) 13-17 May 2019. Zenodo, web site.
CrossRef | Gscholar
(7)
Chiavetta U, Camarretta N, Garfì V, Ottaviano M, Chirici G, Vizzarri M, Marchetti M (2016)
Harmonized forest categories in central Italy. Journal of Maps 12: 98-100.
CrossRef | Gscholar
(8)
Chirici G, McRoberts RE, Fattorini L, Mura M, Marchetti M (2016)
Comparing echo-based and canopy height model-based metrics for enhancing estimation of forest aboveground biomass in a model-assisted framework. Remote Sensing of Environment 174: 1-9.
CrossRef | Gscholar
(9)
Chirici G, Bottalico F, Giannetti F, Del Perugia B, Travaglini D, Nocentini S, Kutchartt E, Marchi E, Foderi C, Fioravanti M, Fattorini L, Bottai L, McRoberts RE, Corona P, Gozzini B (2018)
Assessing forest windthrow damage using single-date, post-event airborne laser scanning data. Forestry 91: 27-37.
CrossRef | Gscholar
(10)
Chirici G, Giannetti F, McRoberts RE, Travaglini D, Pecchi M, Maselli F, Chiesi M, Corona P (2020)
Wall-to-wall spatial prediction of growing stock volume based on Italian National Forest Inventory plots and remotely sensed data. International Journal of Applied Earth Observation and Geoinformatics 84, 101959.
CrossRef | Gscholar
(11)
Corona P, Chianucci F, Quatrini V, Civitarese V, Clementel F, Costa C, Floris A, Menesatti P, Puletti N, Sperandio G, Verani S, Turco R, Bernardini V, Plutino M, Scrinzi G (2017)
Precision forestry: concepts, tools and perspectives in Italy. Forest@ 14: 1-12. [In Italian with English summary]
CrossRef | Gscholar
(12)
Di Biase RM, Fattorini L, Marchi M (2018)
Statistical inferential techniques for approaching forest mapping. A review of methods. Annals of Silvicultural Research 42: 46-58.
CrossRef | Gscholar
(13)
Dubayah R, Blair JB, Goetz S, Fatoyinbo L, Hansen M, Healey S, Hofton M, Hutt G, Kellner J, Luthcke S, Armstrong J, Tang H, Duncanson L, Hancock S, Jantz P, Marselis S, Patterson PL, Qi W, Silva C (2020)
The global ecosystem dynamics investigation: high-resolution laser ranging of the Earth’s forests and topography. Science of Remote Sensing 1: 100002.
CrossRef | Gscholar
(14)
Fattorini L, Marcheselli M, Pisani C (2006)
A three-phase sampling strategy for large-scale multiresource forest inventories. Journal of Agricultural, Biological, and Environmental Statistics 11: 296-316.
CrossRef | Gscholar
(15)
Francini S, McRoberts RE, Giannetti F, Mencucci M, Marchetti M, Scarascia-Mugnozza G, Chirici G (2020)
Near-real time forest change detection using PlanetScope imagery. European Journal of Remote Sensing 53: 233-244.
CrossRef | Gscholar
(16)
Garnier M, Bastick C, Colin A, Commagnac L, Lallemant T, Maisonneuve B, Mazepa F, Simon M, Vega C (2019)
La BD Forêt® version 2. L’IF - Synthèse périodique de l’inventaire forestier no. 46, Institut National de L’information Géographique et Forestière - IGN, Saint-Mandé, France. [in French]
Online | Gscholar
(17)
Giannetti F, Puletti N, Quatrini V, Travaglini D, Bottalico F, Corona P, Chirici G (2018)
Integrating terrestrial and airborne laser scanning for the assessment of single-tree attributes in Mediterranean forest stands. European Journal of Remote Sensing 51: 795-807.
CrossRef | Gscholar
(18)
Giannetti F, Pegna R, Francini S, McRoberts RE, Travaglini D, Marchetti M, Scarascia-Mugnozza G, Chirici G (2020)
A new method for automated clear-cut disturbance detection in Mediterranean coppice forests using Landsat time series. Remote Sensing 12 (22): 3720.
CrossRef | Gscholar
(19)
Goodwin NR, Coops NC, Culvenor DS (2006)
Assessment of forest structure with airborne LiDAR and the effects of platform altitude. Remote Sensing of Environment 103: 140-152.
CrossRef | Gscholar
(20)
Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A (2013)
High-resolution global maps of 21st-century forest cover change. Science 342 (6160): 850-853.
CrossRef | Gscholar
(21)
Holopainen M, Vastaranta M, Hyyppä J (2014)
Outlook for the next generation’s precision forestry in Finland. Forests 5: 1682-1694.
CrossRef | Gscholar
(22)
Hüttich C, Korets M, Bartalev S, Zharko V, Schepaschenko D, Shvidenko A, Schmullius C (2014)
Exploiting growing stock volume maps for large scale forest resource assessment: cross-comparisons of ASAR- and PALSAR-based GSV estimates with forest inventory in Central Siberia. Forests 5: 1753-1776.
CrossRef | Gscholar
(23)
Hyyppä J, Hyyppä H, Leckie D, Gougeon F, Yu X, Maltamo M (2008)
Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. International Journal of Remote Sensing 29 (5): 1339-1366.
CrossRef | Gscholar
(24)
INFC (2007)
Le stime di superficie 2005 - Prima parte [Surface estimates - First part]. In: “Inventario Nazionale delle Foreste e dei Serbatoi Forestali di Carbonio” (Tabacchi G, De Natale F, Di Cosmo L, Floris A, Gagliano C, Gasparini P, Genchi L, Scrinzi G, Tosi V eds). MiPAF - Corpo Forestale dello Stato - Ispettorato Generale, CRA - ISAFA, Trento, Italy. [in Italian]
Online | Gscholar
(25)
Isenburg M (2017)
LAStools - efficient LiDAR processing software. Rapidlasso GmbH, Gilching, Germany, web site.
Online | Gscholar
(26)
Jakubowski MK, Guo Q, Kelly M (2013)
Tradeoffs between LIDAR pulse density and forest measurements accuracy. Remote Sensing of Environment 103: 245-253.
CrossRef | Gscholar
(27)
JAXA (2016)
Global 25m resolution PALSAR-2 / PALSAR mosaic and forest / non-forest map (FNF) dataset description. Japan Aerospace Exploration Agency - JAXA, Earth Observation Research Center - EORC, Japan, pp. 8.
Online | Gscholar
(28)
Kangas A, Astrup R, Breidenbach J, Fridman J, Gobakken T, Korhonen KT, Maltamo M, Nilsson M, Nord-Larsen T, Olsson H (2018)
Remote sensing and forest inventories in Nordic countries - Roadmap for the future. Scandinavian Journal of Forest Research 33: 397-412.
CrossRef | Gscholar
(29)
Langanke T (2017)
Copernicus land monitoring service - high resolution layer forest. Product Specifications Document, Copernicus team, EEA, Copenhagen, Denmark, pp. 38.
Online | Gscholar
(30)
Maltamo M, Packalén P, Peuhkurinen J, Suvanto A, Pesonen A, Hyyppä J (2007)
Experiences and possibilities of ALS based forest inventory in Finland. In: Proceedings of “ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007”. Espoo (Finland) 12-14 Sept 2007, pp. 270-279.
Gscholar
(31)
Maltamo M, Naesset E, Vauhkonen J (2014)
Forestry applications of airborne laser scanning: concepts and case studies. Springer, Dordrecht, Netherlands, pp. 464.
CrossRef | Gscholar
(32)
Maltamo M, Orka HO, Bollandsås OM, Gobakken T, Naesset E (2015)
Using pre-classification to improve the accuracy of species-specific forest attribute estimates from airborne laser scanner data and aerial images. Scandinavian Journal of Forest Research 30: 336-345.
CrossRef | Gscholar
(33)
McRoberts RE, Bechtold WA, Patterson PL, Scott CT, Reams GA (2005)
The enhanced Forest Inventory and Analysis program of the USDA Forest Service: historical perspective and announcement of statistical documentation. Journal of Forestry 103: 304-308.
Online | Gscholar
(34)
McRoberts RE, Naesset E, Gobakken T (2013)
Inference for LiDAR-assisted estimation of forest growing stock volume. Remote Sensing of Environment 128: 268-275.
CrossRef | Gscholar
(35)
McRoberts RE, Liknes GC, Domke GM (2014)
Using a remote sensing-based, percent tree cover map to enhance forest inventory estimation. Forest Ecology and Management 331: 12-18.
CrossRef | Gscholar
(36)
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
(37)
Mura M, McRoberts RE, Chirici G, Marchetti M (2016)
Statistical inference for forest structural diversity indices using airborne laser scanning data and the k-nearest neighbors technique. Remote Sensing of Environment 186: 678-686.
CrossRef | Gscholar
(38)
Naesset 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
(39)
Naesset E (2007)
Airborne laser scanning as a method in operational forest inventory: status of accuracy assessments accomplished in Scandinavia. Scandinavian Journal of Forest Research 22: 433-422.
CrossRef | Gscholar
(40)
Naesset E, Gobakken T, Solberg S, Gregoire TG, Nelson R, Ståhl G, Weydahl D (2011)
Model-assisted regional forest biomass estimation using LiDAR and InSAR as auxiliary data: a case study from a boreal forest area. Remote Sensing of Environment 115: 3599-3614.
CrossRef | Gscholar
(41)
Nilsson M, Nordkvist K, Jonzén J, Lindgren N, Axensten P, Wallerman J, Egberth M, Larsson S, Nilsson L, Eriksson J, Olsson H (2017)
A nationwide forest attribute map of Sweden predicted using airborne laser scanning data and field data from the National Forest Inventory. Remote Sensing of Environment 194: 447-454.
CrossRef | Gscholar
(42)
Puletti N, Floris A, Scrinzi G, Chianucci F, Colle G, Michelini T, Pedot N, Penasa A, Scalercio S, Corona P (2017)
CFOR: a spatial decision support system dedicated to forest management in Calabria. Forest@ 14: 135-140. [In Italian with English summary]
CrossRef | Gscholar
(43)
Saarela S, Holm S, Grafström A, Schnell S, Gregoire TG, Nelson RF, Ståhl G (2016)
Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science 73: 895-910.
CrossRef | Gscholar
(44)
Scrinzi G, Floris A, Clementel F, Bernardini V, Chianucci F, Greco S, Michelini T, Penasa A, Puletti N, Rizzo M, Turco R, Corona P (2017)
Models of stand volume and biomass estimation based on LiDAR data for the main forest types in Calabria (southern Italy). Forest@ 14: 175-187. [In Italian with English summary]
CrossRef | Gscholar
(45)
Smith S, Gilbert J, Bull G, Gillam S, Whitton E (2010)
National inventory of woodland and trees (1995-99): methodology. Forestry Commission Research Report, Forestry Commission Scotland, Edinburgh, UK, vol. i-iv, pp. 1-60.
Gscholar
(46)
Tompalski P, White JC, Coops NC, Wulder MA (2019)
Demonstrating the transferability of forest inventory attribute models derived using airborne laser scanning data. Remote Sensing of Environment 227: 110-124.
CrossRef | Gscholar
(47)
Valbuena R, Packalen P, Mehtätalo L, García-Abril A, Maltamo M (2013)
Characterizing forest structural types and shelterwood dynamics from Lorenz-based indicators predicted by airborne laser scanning. Canadian Journal of Forest Research 43: 1063-1074.
CrossRef | Gscholar
(48)
Vihervaara P, Mononen L, Auvinen AP, Virkkala R, Lü Y, Pippuri I, Packalen P, Valbuena R, Valkama J (2015)
How to integrate remotely sensed data and biodiversity for ecosystem assessments at landscape scale. Landscape Ecology 30: 501-516.
CrossRef | Gscholar
(49)
Vizzarri M, Sallustio L, Travaglini D, Bottalico F, Chirici G, Garfì V, Lafortezza R, Veca DSLM, Lombardi F, Maetzke F, Marchetti M (2017)
The MIMOSE approach to support sustainable forest management planning at regional scale in Mediterranean contexts. Sustainability 9 (2): 316.
CrossRef | Gscholar
(50)
Vogeler JC, Hudak AT, Vierling LA, Evans J, Green P, Vierling KT (2014)
Terrain and vegetation structural influences on local avian species richness in two mixed-conifer forests. Remote Sensing of Environment 147: 13-22.
CrossRef | Gscholar
(51)
Waser LT, Ginzler C, Rehush N (2017)
Wall-to-wall tree type mapping from countrywide airborne remote sensing surveys. Remote Sensing 9 (8): 766.
CrossRef | Gscholar
(52)
White JC, Coops NC, Wulder MA, Vastaranta M, Hilker T, Tompalski P (2016)
Remote sensing technologies for enhancing forest inventories: a review. Canadian Journal of Remote Sensing 42: 619-641.
CrossRef | Gscholar
(53)
Wulder MA, Bater CW, Coops NC, Hilker T, White JC (2008)
The role of LiDAR in sustainable forest management. Forest Chronicle 84: 807-826.
CrossRef | Gscholar
 

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