Use of ETM+ images to extend stem volume estimates obtained from lidar data

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 66, Issue 5, 2011, Pages 662-671

  Maselli, Fabio ^a   Chiesi, Marta ^a   Montaghi, Alessandro ^b   Pranzini, Enzo ^b  

^a CNR   (Italy)

^b UNIVERSITY OF FLORENCE   (Italy)

Author keywords

K NN; Landsat ETM+; LiDAR; Local regression; Stem volume

Indexed keywords

ACCURATE MEASUREMENT; AIRBORNE LIDAR; CENTRAL ITALY; COASTAL AREA; ESTIMATION METHODS; FOREST INVENTORY; FOREST STAND; GROUND DATA; K-NN; LANDSAT ETM+; LIDAR DATA; LOCAL REGRESSION; PARAMETRIC REGRESSION; PINE FOREST; SPATIAL PATTERNS; STEM VOLUME; TREE HEIGHT; WOODY BIOMASS;

COASTAL ZONES; FORESTRY; OPTICAL RADAR; REGRESSION ANALYSIS;

ESTIMATION;

ACCURACY ASSESSMENT; BIOMASS; CALIBRATION; COASTAL ZONE; CONIFEROUS FOREST; ESTIMATION METHOD; FOREST INVENTORY; LANDSAT THEMATIC MAPPER; LIDAR; REGRESSION ANALYSIS; SATELLITE IMAGERY; SPATIAL ANALYSIS; STAND DYNAMICS;

ESTIMATION; FORESTRY; FORESTS; ITALY; PINUS; RADAR; REGRESSION ANALYSIS; STEMS;

ITALY; SAN ROSSORE NATURAL PARK; TUSCANY;

EID: 80052788851     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2011.04.007     Document Type: Article

References (52)

1. Anderson T.W. An Introduction to Multivariate Statistical Analysis 1984, John Wiley & Sons, New York.
2. Blair J.B., Rabine D.L., Hofton M.A. The Laser Vegetation Imaging Sensor: a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topography. ISPRS Journal of Photogrammetry and Remote Sensing 1999, 54(2-3):115-122.
3. Bowman D., Pranzini E. Reversed response within a segmented detached breakwater - the Gombo case, Tuscany coast, Italy. Coastal Engineering 2003, 49(4):263-274.
4. Bortolot Z.J., Wynne R.H. Estimating forest biomass using small footprint LiDAR data: an individual tree-based approach that incorporates training data. ISPRS Journal of Photogrammetry and Remote Sensing 2005, 59(6):342-360.
5. Bresci D., Carli S., Pranzini E., Rossi L. Studio geomorfologico delle dune costiere di Marina di Cecina (Toscana) con rilievi Lidar da aereo. Studi costieri 2006, 11:17-30.
6. Brunsdon C., Fotheringham A.S., Charlton M.E. Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis 1996, 28(4):281-298.
7. Cleveland W.S., Devlin S.J. Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association 1988, 83(403):596-610.
8. Chirici G., Barbati A., Corona P., Marchetti M., Travaglini D., Maselli F., Bertini R. Non-parametric and parametric methods using satellite images for estimating growing stock volume in alpine and Mediterranean forest ecosystems. Remote Sensing of Environment 2008, 112(5):2686-2700.
9. Corona P., Fattorini L. Area-based lidar-assisted estimation of forest standing volume. Canadian Journal of Forest Research 2008, 38(11):2911-2916.
10. Corona P. Integration of forest mapping and inventory to support forest management. iForest 2010, 3:59-64.
11. Drake J.B., Dubayah R.O., Knox R.G., Clark D.B., Blair J.B. Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest. Remote Sensing of Environment 2002, 81(2-3):378-392.
12. D.R.E.Am Tenuta di San Rossore. Note illustrative della carta forestale e della fruizione turistica 2003, S.EL.CA, Firenze.
13. Dubayah R.O., Drake J.B. Lidar remote sensing for forestry. Journal of Forestry 2000, 98(6):44-46.
14. Fazakas Z., Nilsson M., Olsson H. Regional forest biomass and wood volume estimation using satellite data and ancillary data. Agricultural and Forest Meteorology 1999, 98:417-425.
15. Federici S., Vitullo M., Tulipano S., De Lauretis R., Seufert G. An approach to estimate carbon stocks change in forest carbon pools under the UNFCCC: the Italian case. iForest 2008, 1:86-95.
16. Franco-Lopez H., Ek A.R., Bauer M.E. Estimation and mapping of forest stand density, volume, and cover type using the k-Nearest Neighbours method. Remote Sensing of Environment 2001, 77(3):251-274.
17. García M., Riaño D., Chuvieco E., Danson F.M. Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sensing of Environment 2010, 114(4):816-830.
18. Haapanen R., Ek A.R., Bauer M.E., Finley A.O. Delineation of forest/nonforest land use classes using nearest neighbour methods. Remote Sensing of Environment 2004, 89(3):265-271.
19. Holmgren J., Nilsson M., Olsson H. Estimation of tree height and stem volume on plots using airborne laser scanning. Forest Science 2003, 49(3):419-428.
20. Horler D.N.H., Ahern F.J. Forestry information content of Thematic Mapper data. International Journal of Remote Sensing 1986, 7(3):1785-1796.
21. Hudak A.T., Lefsky M.A., Cohen W.B., Berterretche M. Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height. Remote Sensing of Environment 2002, 82(2-3):397-416.
22. Katila M., Tomppo E. Selecting estimation parameters for the Finnish multisource national forest inventory. Remote Sensing of Environment 2001, 76(1):16-32.
23. La Marca O. Elementi di dendrometria 1999, Patron Editore, Bologna, Italy.
24. Lawrence M., McRoberts R.E., Tomppo E., Gschwantner T., Gabler K. Comparisons of national forest inventories. National Forest Inventories. Pathways for Common Reporting 2010, 19-32. Springer, Heidelberg. E. Tomppo, T. Gschwantner, M. Lawrence, R.E. McRoberts (Eds.).
25. Lefsky M.A., Harding D., Cohen W.B., Parker G., Shugart H.H. Surface lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA. Remote Sensing of Environment 1999, 67(1):83-98.
26. Lefsky M.A., Cohen W.B., Parker G.G., Harding D.J. Lidar remote sensing for ecosystem studies. BioScience 2002, 52(1):19-30.
27. Maltamo M., Eerikäinen K., Packalén P., Hyyppä J. Estimation of stem volume using laser scanning-based canopy height metrics. Forestry 2006, 79(2):217-229.
28. Maselli F. Improved estimation of environmental parameters through locally calibrated multivariate regression analysis. Photogrammetric Engineering & Remote Sensing 2002, 68(11):1163-1171.
29. 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, 26(17):3781-3796.
30. Maselli F., Chiesi M. Evaluation of statistical methods to estimate forest volume in a Mediterranean region. IEEE Transaction of Geoscience and Remote Sensing 2006, 44(8):2239-2250.
31. Maselli F., Chiesi M., Moriondo M., Fibbi L., Bindi M., Running S.W. Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data. Ecological Modelling 2009, 220(3):330-342.
32. McRoberts R.E., Bechtold W.A., Patterson P.L., Scott C.T., Reams G.A. The enhanced forest inventory and analysis program of the USDA Forest Service: historical perspective and announcement of statistical documentation. Journal of Forestry 2005, 103(6):304-308.
33. McRoberts R.E., Tomppo E.O. Remote sensing support for national forest inventories. Remote Sensing of Environment 2007, 110(4):412-419.
34. McRoberts R.E. Diagnostic tools for nearest neighbors techniques when used with satellite imagery. Remote Sensing of Environment 2009, 113(3):489-499.
35. McRoberts R.E., Stahl G., Vidal C., Lawrence M., Tomppo E.O., Schadauer K., Chirici G., Bastrup-Birk A. National forest inventories: prospects for harmonised international reporting. National Forest Inventories. Pathways for Common Reporting 2010, 33-44. Springer, Heidelberg. E. Tomppo, T. Gschwantner, M. Lawrence, R.E. McRoberts (Eds.).
36. Means J.E., Acker S.A., Fitt B.J., Renslow M., Emerson L., Hendrix C.J. Predicting forest stand characteristics with airborne scanning Lidar. Photogrammetric Engineering & Remote Sensing 2000, 66(11):1367-1371.
37. Naesset E., Gobakken T. Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser. Remote Sensing of Environment 2008, 112(6):3079-3090.
38. Nelson R., Parker G., Hom M. A portable airborne laser system for forest inventory. Photogrammetric Engineering & Remote Sensing 2003, 69(3):267-273.
39. Pascual C., García-Abril A., Cohen W.B., Martín-Fernandez S. Relationship between LiDAR-derived forest canopy height and Landsat images. International Journal of Remote Sensing 2010, 31(5):1261-1280.
40. Popescu S.C., Wynne R.H., Nelson R.F. Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass. Canadian Journal of Remote Sensing 2003, 29(5):564-577.
41. Pranzini E. Updrift river mouth migration on cuspate deltas: two examples from the coast of Tuscany (Italy). Geomorphology 2001, 38(1-2):125-132.
42. Pranzini E. Airborne LIDAR survey applied to the analysis of the historical evolution of the Arno River delta (Italy). Journal of Coastal Research 2007, 50:400-409.
43. Rapetti F., Vittorini S. Carta climatica della Toscana 1995, Pacini Editore, Pisa (Italy).
44. Reutebuch S.E., Andersen H.-E., McGaughey R.J. Light Detection and Ranging (LIDAR): an emerging tool for multiple resource inventory. Journal of Forestry 2005, 103(6):286-292.
45. Rosell J.R., Llorens J., Sanz R., Arnò J., Ribes-Dasi M., Masip J., Escolà A., Camp F., Solanelles F., Gracia F., Gil E., Val L., Planas S., Palacìn J. Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology 2009, 149(9):1505-1510.
46. Thomas V., Treitz P., McCaughey J.H., Morrison I. Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar: an examination of scanning density. Canadian Journal of Forest Research 2006, 36(1):34-47.
47. 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):1-20.
48. Vidal C., Lanz A., Tomppo E., Schadauer K., Gschwantner T., di Cosmo L., Robert N. Establishing forest inventory reference definitions for forest and growing stock: a study towards common reporting. Silva Fennica 2008, 42(2):247-266.
49. Wang F. Fuzzy supervised classification of remote sensing images. IEEE Transaction of Geoscience and Remote Sensing 1990, 28(2):194-201.
50. Waring R.H., Running S.W. Forest Ecosystems: Analysis at Multiple Scales 2007, Academic Press, San Diego, California, USA, pp. 263-291. third ed.
51. Wulder M.A., Seeman D. Forest inventory height update through the integration of lidar data with segmented Landsat imagery. Canadian Journal of Remote Sensing 2003, 29(5):536-543.
52. Zadeh L.A. Fuzzy sets. Informatics and Control 1965, 8(3):338-353.