Change detection of mountain birch using multi-temporal ALS point clouds

Remote Sensing Letters

Volumn 4, Issue 2, 2013, Pages 190-199

  Nyström, Mattias ^a   Holmgren, Johan ^a   Olsson, Hakan ^a  

^a SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

AIRBORNE LASER SCANNING; CHANGE DETECTION; CLASSIFICATION ACCURACY; DATA SETS; EXPLANATORY VARIABLES; FOREST-TUNDRA ECOTONE; HISTOGRAM MATCHING; LASER SCANNER DATA; MOUNTAIN BIRCH; MULTI-TEMPORAL; POINT CLOUD; RELATIVE CALIBRATIONS; TREE COVER; TREELINE; VEGETATION CHANGE;

LASER APPLICATIONS; LASERS; VEGETATION;

FORESTRY;

ACCURACY ASSESSMENT; BIOMASS; CALIBRATION; DATA SET; DECIDUOUS FOREST; ECOTONE; FOREST CANOPY; HISTOGRAM; IMAGE CLASSIFICATION; SAMPLING; TREELINE; TUNDRA;

FORESTRY; LASERS; PLANTS;

SWEDEN;

BETULA PUBESCENS SUBSP. TORTUOSA;

EID: 84869072933     PISSN: 2150704X     EISSN: 21507058     Source Type: Journal    
DOI: 10.1080/2150704X.2012.714087     Document Type: Article

References (22)

1. BATER, C.W., WULDER, M.A., COOPS, N.C., NELSON, R.F., HILKER, T. and NÆSSET, E., 2011, Stability of sample-based scanning-LiDAR-derived vegetation metrics for forest monitoring. IEEE Transactions on Geoscience and Remote Sensing, 49, pp. 2385-2392.
2. COPPIN, P., JONCKHEERE, I., NACKAERTS, K., MUYS, B. and LAMBIN, E., 2004, Digital change detection methods in ecosystem monitoring: a review. International Journal of Remote Sensing, 25, pp. 1565-1596. (Pubitemid 38516797)
3. FRITSCH, F.N. and CARLSON, R.E., 1980, Monotone piecewise cubic interpolation. SIAM Journal on Numerical Analysis, 17, pp. 238-246.
4. HOLMGREN, J., NILSSON, M. and OLSSON, H., 2003, Simulating the effect of LiDAR scanning angle for estimation of mean tree height and canopy closure. Canadian Journal of Remote Sensing, 29, pp. 623-632.
5. HOPKINSON, C., CHASMER, L. and HALL, R.J., 2008, The uncertainty in conifer plantation growth prediction from multi-temporal LiDAR datasets. Remote Sensing of Environment, 112, pp. 1168-1180. (Pubitemid 351296250)
6. HYYPPÄ, J., XIAOWEI, Y., RÖNNHOLM, P., KAARTINEN, H. and HAGGRÉN, H., 2003, Factors affecting object-oriented forest growth estimates obtained using laser scanning. The Photogrammetric Journal of Finland, 18, pp. 16-31.
7. NÆSSET, E., 2009, Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data. Remote Sensing of Environment, 113, pp. 148-159.
8. NÆSSET, E. and GOBAKKEN, T., 2005, Estimating forest growth using canopy metrics derived from airborne laser scanner data. Remote Sensing of Environment, 96, pp. 453-465. (Pubitemid 40912443)
9. NÆSSET, E. andGOBAKKEN, T., 2008, Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser. Remote Sensing of Environment, 112, pp. 3079-3090.
10. NILSSON, M., 1996, Estimation of tree weights and stand volume using an airborne LiDAR system. Remote Sensing of Environment, 56, pp. 1-7.
11. NYSTRÖM, M., HOLMGREN, J. and OLSSON, H., 2012, Prediction of tree biomass in the forest- tundra ecotone using airborne laser scanning. Remote Sensing of Environment, 123, pp. 271-279.
12. OLSSON, H., 1993, Regression functions for multitemporal relative calibration of Thematic Mapper data over boreal forests. Remote Sensing of Environment, 46, pp. 89-102. (Pubitemid 24399183)
13. RDEVELOPMENT CORE TEAM, 2011, R: A Language and Environment for Statistical Computing (Vienna: R Foundation for Statistical Computing).
14. SOININEN, A., 2010, TerraScan User's Guide. Available online at: www.terrasolid.fi (accessed 31 July 2010).
15. SOLBERG, S., NÆSSET, E., HANSSEN, K.H. and CHRISTIANSEN, E., 2006, Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning. Remote Sensing of Environment, 102, pp. 364-376. (Pubitemid 43776716)
16. ST-ONGE, B. andVEPAKOMMA.U., 2004, Assessing forest gap dynamics and growth usingmultitemporal laser-scanner data. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI 8/W2, 3-6 October 2004, M. Thies, B. Koch, H. Spiecker and H. Weinacker (Eds.), Freiburg, Germany, pp. 173-178.
17. Available online at: http://www.isprs.org/proceedings/XXXVI/8-W2
18. VASTARANTA, M., KORPELA, I., UOTILA, A., HOVI, A. and HOLOPAINEN, M., 2011, Mapping of snow-damaged trees based on bitemporal airborne LiDAR data. European Journal of Forest Research, 131, pp. 1-12.
19. VENABLES, W.N. and RIPLEY, B.D., 2002, Modern Applied Statistics with S (New York: Springer).
20. YU, X.,HYYPPÄ, J.,KAARTINEN,H.,MALTAMO,M. andHYYPPÄ,H., 2008, Obtaining plotwise mean height and volume growth in boreal forests using multi-temporal laser surveys and various change detection techniques. International Journal of Remote Sensing, 29, pp. 1367-1386. (Pubitemid 351321081)
21. YU, X.W., HYYPPÄ, J., KAARTINEN, H. andMALTAMO, M., 2004, Automatic detection of harvested trees and determination of forest growth using airborne laser scanning. Remote Sensing of Environment, 90, pp. 451-462. (Pubitemid 38583632)
22. YU, X.W.,HYYPPÄ, J.,KUKKO, A.,MALTAMO,M. andKAARTINEN,H., 2006, Change detection techniques for canopy height growth measurements using airborne laser scanner data. Photogrammetric Engineering and Remote Sensing, 72, pp. 1339-1348. (Pubitemid 44893887)