A questionnaire-based review of the operational use of remotely sensed data by national forest inventories

Remote Sensing of Environment

Volumn 174, Issue , 2016, Pages 279-289

  Barrett, Frank ^a   McRoberts, Ronald E ^b   Tomppo, Erkki ^c   Cienciala, Emil ^d   Waser, Lars T ^e  

^a Johnstown Castle Estate   (Ireland)

^b USDA FOREST SERVICE   (United States)

^c FINNISH FOREST RESEARCH INSTITUTE   (Finland)

^d Ustav pro vyzkum lesnich ekosystemu sro   (Czech Republic)

^e SWISS FEDERAL RESEARCH INSTITUTE WSL   (Switzerland)

Author keywords

Aerial photography; Case studies; COST action FP1001; Satellite imagery; Spaceborne data

Indexed keywords

AERIAL PHOTOGRAPHY; FORESTRY; MAPPING; PHOTOGRAPHIC EQUIPMENT; PHOTOGRAPHY; SATELLITE IMAGERY; SURVEYS;

ACCURACY AND PRECISION; CASE-STUDIES; DATA AND INFORMATION; FINANCIAL RESOURCES; NATIONAL FOREST INVENTORIES; REMOTELY SENSED DATA; SMALL AREA ESTIMATION; SPACEBORNE DATA;

REMOTE SENSING;

AERIAL PHOTOGRAPHY; AIRBORNE SENSOR; FOREST INVENTORY; FOREST RESOURCE; REMOTE SENSING; SATELLITE DATA; SATELLITE IMAGERY;

EUROPE; FINLAND; SWITZERLAND; UNITED STATES;

EID: 84952033973     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2015.08.029     Document Type: Review

References (77)

1. Bickford C.A. The sampling design used in the forest survey of the northeast. Journal of Forestry 1952, 50:290-293.
2. Brassel P., Lischke H. Swiss National Forest Inventory: Methods and models of the second assessment 2001, Federal Research Institute WSL, Birmensdorf, Swiss.
3. Cienciala E., Tomppo E., Snorrason A., Broadmeadow M., Colin A., Dunger K., Ståhl G. Preparing emission reporting from forests: Use of national forest inventories in European countries. Silva Fennica 2008, 42:73-88.
4. Clement J. LiDAR derived 3D forest stand parameters of Dutch pine 2003, (Thesis), Wageningen University, The Netherlands, (64 pp.).
5. Cochran W.G. Sampling techniques 1977, Wiley, New York. 3rd ed.
6. COST European Cooperation in Science and Technology 2014, Available at:, (Last accessed: June 1015). http://www.cost.eu.
7. COST FP1001 USEWOOD: Improving data and information on the potential supply of wood resources, a European approach from multisource national forest inventories 2014, Available at:, (Last accessed: June 2015). https://sites.google.com/site/costactionfp1001/.
8. Danson F.M. Preliminary evaluation of the relationships between SPOT-1 HRV data and forest stand parameters. International Journal of Remote Sensing 1987, 8:1571-1575.
9. de Foresta H., Somarriba E., Temu A., Boulanger D., Feuilly H., Gauthier M. Towards the assessment of trees outside forests. Resources assessment working paper 2013, 183. FAO, Rome.
10. FAO Technical review of FAO's approach and methods for National Forest Monitoring and Assessment (NFMA). By Erkki Tomppo and Krister Andersson. National Forest Monitoring and Assessment working paper NFMA 38 2008, (Rome).
11. FAO Global forest resources assessment 2010. FAO Forestry Paper 2010, 163. FAO, Rome.
12. Fix E., Hodges J.L. Discriminatory analysis - Nonparametric discrimination: Consistency properties. Report no. 4. Random Field, Texas, USA: USAF of Aviation Medicine 1951, Randolph Field, Texas.
13. Franco-Lopez H., Ek A.R., Bauer M.E. Estimation and mapping of forest stand density, volume, and cover type using the k-nearest neighbors method. Remote Sensing of Environment 2001, 77:251-274.
14. Ginzler C., Hobi M.L. Countrywide stereo-image matching for updating digital surface models in the framework of the Swiss National Forest Inventory. Remote Sensing 2015, 7:4343-4370.
15. Ginzler C., Bärtschi H., Bedolla A., Brassel P., Hägeli M., Hauser M., Zulliger D. Luftbildinterpretation LFI3 - Interpretationsanleitung zum dritten Landesforstinventar 2005, Forschungsanstalt für Wald, Schnee und Landschaft WSL, Birmensdorf, Eidg, (87 S).
16. Ginzler C., Boehl J., Boesch R., Waser L.T. Accuracy of forest parameters derived from medium footprint lidar under operational constraints. Proceedings of ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007 2007, (Espoo, Finland. 2007, September 12-14), Available at: http://www.isprs.org/proceedings/XXXVI/3-W52/; last accessed September 2015.
17. Gjertsen A. Accuracy of forest mapping based on Landsat TM data and a kNN-based method. Remote Sensing of Environment 2007, 110:420-430.
18. Hajnsek I., Kugler F., Seungkuk L., Papathanassiou K. Tropical forest parameter estimation by means of Pol-InSAR: The INDREX-II campaign. IEEE Transactions on Geoscience and Remote Sensing 2009, 47:481-493.
19. Halme T., Tomppo E. Stand-based forest inventory from satellite images. General description. Research Notes No. 19 1987, 45-46. Department of Forest Mensuration and Management, University of Helsinki.
20. Hansen M.H. A comprehensive sampling system for forest inventory based on an individual tree growth model 1990, (PhD dissertation), University of Minnesota, College of Natural Resources, St. Paul, MN.
21. Hansen M.H., Wendt D.G. Using classified Landsat Thematic Mapper data for stratification in a statewide forest inventory. U.S. Forest Service General Technical Report NC-213 2000, 20-27. (1999, 2-3 November, San Antonio, Texas). R.E. McRoberts, G.A. Reams, P.C. Van Deusen (Eds.).
22. Homer C., Huang C., Yang L., Wylie B., Coan M. Development of a 2001 national land cover database for the United States. Photogrammetric Engineering and Remote Sensing 2004, 70:829-840.
23. Homer C., Dewitz J., Fry J., Coan M., Hossain N., Larson C., Wickham J. Completion of the 2001 national land cover database for the conterminous United States. Photogrammetric Engineering and Remote Sensing 2007, 73:337-341.
24. Katila M., Tomppo E. Selecting estimation parameters for the Finnish multisource National Forest Inventory. Remote Sensing of Environment 2001, 76:16-32.
25. Katila M., Heikkinen J., Tomppo E. Calibration of small-area estimates for map errors in multisource forest inventory. Canadian Journal of Forest Research 2000, 30:1329-1339.
26. Koch B. Remote sensing supporting national forest inventories NFA. FAO knowledge reference for national forest assessments 2013, (Available at: http://www.fao.org/fileadmin/user_upload/national_forest_assessment/images/PDFs/English/KR2_EN__8_pdf).
27. Köhl M., Päivinen R. Definition of a system of nomenclature for mapping European forests and for compiling a Pan-European Forest Information System. Final report of the project 1996, Office for Official Publications of the European Communities, Luxembourg.
28. Köhl M., Magnussen S.S., Marchetti M. Sampling methods, remote sensing, and GIS multiresource forest inventory 2006, Springer, Berlin.
29. Koukal T., Suppan F., Schneider W. The impact of relative radiometric calibration on the accuracy of kNN-predictions of forest attributes. Remote Sensing of Environment 2007, 110:431-437.
30. LaBau V.J., Bones J.T., Kingsley N.P., Lund G.H., Smith W.B. A history of the forest survey in the United States: 1830-2004 2007, Department of Agriculture. Forest Service FS-877, United States.
31. Lawrence M., McRoberts R.E., Tomppo E., Gschwantner T., Gabler K. Chapter 2, comparisons of national forest inventories. National forest inventories - Pathways for common reporting 2010, 19-32. Springer, Heidelberg Dordrecht London New York. E. Tomppo, T. Gschwantner, M. Lawrence, R.E. McRoberts (Eds.).
32. Loetsch F., Haller K.E. Forest inventory: vol. 1. Statistics of forest inventory and information from aerial photographs 1964, BLV Verlagsgesellschaft, Munchen, Germany.
33. Loveland T.R., Hansen M.C. Chapter 4, global data availability from U.S. satellites: Landsat and MODIS. Global forest monitoring from earth observation 2012, 69-78. CRC Press.
34. Luke File service for publicly available data 2015, Available at:, (Last accessed Jun 28, 2015). http://kartta.metla.fi/index-en.html.
35. Martinez M., Condes S. Country report for Spain. Reports on forestry inventory and survey systems 1997, Vols. 1 and 2. Office for official publications of the European Communities. R. Päivinen, M. Köhl (Eds.).
36. Maselli F., Chirici G., Bottai L., Corona P., Marchetti M. Estimation of Mediterranean forest attributes by the application of k-NN procedures to multitemporal Landsat ETM+ images. International Journal of Remote Sensing 2005, 17:3781-3796.
37. Massey A., Mandallaz D., Lanz A. Integrating remote sensing and past inventory data under the new annual design of the Swiss national forest inventory using three-phase design-based regression estimation. Canadian Journal of Forest Research 2014, 44:1177-1186.
38. McInerney D., Pekkarinen A., Haakana M. Combining Landsat ETM+ with field data for Ireland's national forest inventory - A pilot study for Co. Clare. Proceedings of ForestSat 2005 2005, 12-16. (Borås, Sweden, 31 May-3 June 2005). (Available at: http://shop.skogsstyrelsen.se/shop/9098/art92/4646092-23ff72-1740-1.pdf). H. Olsson (Ed.).
39. McInerney D., Barrett F., Tomppo E. Applying ikNN in Southern Ireland using NFI data. Presented at the final meeting of COST Action FP1001 2014, Institut National De L'Information Géographique et Forestière (IGN), Paris, (23/09/2015-24/09/2015).
40. McRoberts R.E. Estimating forest attribute parameters for small areas using nearest neighbors techniques. Forest Ecology and Management 2012, 272:3-12.
41. McRoberts R.E., Tomppo E.O. Remote sensing support for national forest inventories. Remote Sensing of Environment 2007, 110:412-419.
42. McRoberts R.E., Nelson M.D., Wendt D.G. Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique. Remote Sensing of Environment 2002, 82:457-468.
43. McRoberts R.E., Wendt D.G., Nelson M.D., Hansen M.D. Using a land cover classification based on satellite imagery to improve the precision of forest inventory area estimates. Remote Sensing of Environment 2002, 81:36-44.
44. McRoberts R.E., Holden G.R., Nelson M.D., Liknes G.C., Gormanson D.D. Using satellite imagery as ancillary data for increasing the precision of estimates for the forest inventory and analysis program of the USDA forest service. Canadian Journal of Forest Research 2006, 36:2968-2980.
45. McRoberts R.E., Tomppo E.O., Næsset E. Advances and emerging issues in national forest inventories. Scandinavian Journal of Forest Research 2010, 25:368-381.
46. McRoberts R.E., Gobakken T., Næsset E. Post-stratified estimation of forest area and growing stock volume using lidar-based stratifications. Remote Sensing of Environment 2012, 125:157-166.
47. McRoberts R.E., Næsset E., Gobakken T. Inference for lidar-assisted estimation of forest growing stock volume. Remote Sensing of Environment 2013, 128:268-275.
48. McRoberts R.E., Liknes G.C., Domke G.M. Using a remote sensing-based, percent tree cover map to enhance forest inventory estimation. Forest Ecology and Management 2014, 331:12-18.
49. Muinonen E., Tokola T. An application of remote sensing for communal forest inventory. The usability of remote sensing for forest inventory and planning, proceedings from SNS/IUFRO workshop, Report 4 1990, 35-42. Remote Sensing Laboratory, Swedish University of Agricultural Sciences, Umeå, Sweden. R. Sylvander, S. Poso (Eds.).
50. Naesset E. Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia. Scandinavian Journal of Forest Research 2007, 22:433-442.
51. Næsset E., Gobakken T., Solberg S., Gregoire T.G., Nelson R., Ståhl G., Weydahl D. 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 2011, 115:3599-3614.
52. NASA NASA science missions: Global Ecosystem Dynamics Investigation Lidar (GEDI) 2015, Available at:, (Last accessed: August 13, 2015). http://science.nasa.gov/missions/gedi/.
53. National Land Survey of Finland Paikkatietoikkuna - Geographic information and information about geographic information in Finland and the rest of the world 2015, Available at:, (Last accessed Jun 28, 2015). http://www.paikkatietoikkuna.fi/web/en/frontpage.
54. Nord-Larsen T., Riis-Nielsen T. Developing an airborne laser scanning dominant height model from a countrywide scanning survey and national forest inventory data. Scandinavian Journal of Forest Research 2010, 25(3):262-272.
55. Poso S. A method of combining photo and field samples in forest inventory. Commununicationes Instituti Forestalis Fenniae 1972, 76:1-133.
56. Poso S., Hame T., Paananen R. A method of estimating the stand characteristics of a forest compartment using satellite imagery. Silva Fennica 1984, 18:261-292.
57. Poso S., Paananen R., Similä M. Forest inventory by compartments using satellite imagery. Silva Fennica 1987, 21:69-94.
58. Praks J., Kugler F., Papathanassiou K., Hajnsek I., Hallikainen M. Height estimation of boreal forest: Interferometric model based inversion at L- and X-band vs. HUTSCAT profiling scatterometer. IEEE Geoscience and Remote Sensing Letters 2007, 4:466-470.
59. Reese H., Nilsson M., Pahén T.G., Hagner O., Joyce S., Tingelöf U., Olsson H. Countrywide estimates of forest variables using satellite data and field data from the National Forest Inventory. Ambio 2003, 32:542-548.
60. Särndal C.E., Swensson B., Wretman J. Model assisted survey sampling. Springer series in statistics 1992, Springer-Verlag, Inc., New York.
61. Solberg S., Astrup R., Bollandsås O.M., Næsset E., Weydahl D.J. Deriving forest monitoring variables from X-band InSAR SRTM height. Canadian Journal of Remote Sensing 2010, 36:68-79.
62. Spurr S.H. Photogrammetry and photo-interpretation 1960, The Ronald Press Company, New York. 2nd ed.
63. Tomppo E. Standwise forest variate estimation by means of satellite images. Research Notes 1988, 21:103-111. Department of Forest Mensuration and Management, University of Helsinki.
64. Tomppo E. Satellite image-based National Forest Inventory of Finland. International Archives of Photogrammetry and Remote Sensing 1991, 28:419-424.
65. Tomppo E., Halme M. Using coarse scale forest variables as ancillary information and weighting of variables in k-nn estimation: A genetic algorithm approach. Remote Sensing of Environment 2004, 92:1-20.
66. Tomppo E., Haakana M., Katila M., Peräsaari J. Multi-source national forest inventory - Methods and applications. Managing forest ecosystems 2008, 18. Springer, Dordrecht, The Netherlands.
67. Tomppo E., Olsson H., Ståhl G., Nilsson M., Hagner O., Katila M. Combining national forest inventory field plots and remote sensing data for forest databases. Remote Sensing of Environment 2008, 112:1982-1999.
68. National forest inventories pathways for common reporting 2010, Springer, Heidelberg Dordrecht London New York. E. Tomppo, T. Gschwantner, M. Lawrence, R.E. McRoberts (Eds.).
69. Tomppo E., Heikkinen J., Henttonen H.M., Ihalainen A., Katila M., Mäkelä H., Vainikainen N. Designing and Conducting a Forest Inventory - Case. 9th National Forest Inventory of Finland, Managing Forest Ecosystems 2011, 22. Springer, Dordrecht, The Netherlands.
70. Tomppo E., Katila M., Mäkisara K., Peräsaari J. The Multi-source National Forest Inventory of Finland - Methods and results 2011. Working papers of the Finnish Forest Research Institute 2014, 319. (Available at http://www.metla.fi/julkaisut/workingpapers/2014/mwp319.htm).
71. USDA Forest Service (USDA-FS) Operational procedures. Forest Service handbook 4809.11 1970, (Chapter 10, Section 11-1), USDA Forest Service, Washington, DC.
72. Vastaranta M., Wulder M.A., White J.C., Pekkarinen A., Tuominen S., Ginzler C., Hyyppä H. Airborne laser scanning and digital stereo imagery measures of forest structure: Comparative results and implications to forest mapping and inventory update. Canadian Journal of Remote Sensing 2013, 39:382-395.
73. Vibrans A.C., McRoberts R.E., Moser P., Nicoletti A.L. Using satellite image-based maps and ground inventory data to estimate the area of the remaining Atlantic forest in the Brazilian state of Santa Catarina. Remote Sensing of Environment 2013, 130:87-95.
74. Vogelmann J.E., Howard S.M., Yang L., Larson C.R., Wylie B.K., Van Driel J.N. Completion of the 1990s national land cover data set for the conterminous United States from Landsat thematic mapper data and ancillary data sources. Photogrammetric Engineering and Remote Sensing 2001, 67:650-662.
75. Westinga E., Bijker W., van Dijk K., Savenije H., Symons H., Heering J., Nobbe E. User requirements study for remote sensing based spatial information for the sustainable management of forests. Technical document 4: User needs assessment for spatial forest information: Results and analysis 1999, International Institute for Aerospace Survey and Earth Sciences, Enschede, Netherlands.
76. Winter S., Chirici G., McRoberts R.E., Hauk E., Tomppo E. Possibilities for harmonizing national forest inventory data for use in forest biodiversity assessments. Forestry 2008, 81:33-44.
77. Wulder M.A., Coops N.C., Hudak A.T., Morsdorf F., Nelson R., Newnham G., Vastaranta M. Status and prospects for LiDAR remote sensing of forested ecosystems. Canadian Journal of Remote Sensing 2013, 39:1-5.