Assessing the transferability of statistical predictive models for leaf area index between two airborne discrete return LiDAR sensor designs within multiple intensely managed Loblolly pine forest locations in the south-eastern USA

Remote Sensing of Environment

Volumn 176, Issue , 2016, Pages 308-319

  Sumnall, Matthew ^a   Peduzzi, Alicia ^b   Fox, Thomas R ^a   Wynne, Randolph H ^a   Thomas, Valerie A ^a   Cook, Bruce ^c  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^b U S DEPARTMENT OF AGRICULTURE   (United States)

^c NASA GODDARD SPACE FLIGHT CENTER   (United States)

Author keywords

Forest management; Leaf area index; LiDAR; Loblolly pine; Remote sensing

Indexed keywords

FORESTRY; REGRESSION ANALYSIS; REMOTE SENSING;

ACQUISITION PARAMETERS; DISCRETE-RETURN LIDAR; INDEPENDENT VARIABLES; INTENSITY DISTRIBUTION; LEAF AREA INDEX; LOBLOLLY PINE; LOBLOLLY PINE FOREST; STEPWISE LINEAR REGRESSION;

OPTICAL RADAR;

AIRBORNE SENSOR; CONIFEROUS FOREST; CORRELATION; DATA SET; DESIGN METHOD; FIELD METHOD; FOREST MANAGEMENT; INDEX METHOD; LEAF AREA INDEX; LIDAR; NUMERICAL MODEL; PLANTATION FORESTRY; REMOTE SENSING; STATISTICAL ANALYSIS; VEGETATION COVER;

NORTH CAROLINA; UNITED STATES; VIRGINIA;

PINUS TAEDA;

EID: 84957928220     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2016.02.012     Document Type: Article

References (49)

1. Anderson J.E., Plourde L.C., Martin M.E., Braswell B.H., Smith M.L., Dubayah R.O., Blair J.B. Integrating waveform LiDAR with hyperspectral imagery for inventory of a northern temperate forest. Remote Sensing of Environment 2008, 112(4):1856-1870.
2. Albaugh T.J., Allen H.L., Dougherty P.M., Kress L.W., King J.S. Leaf area and above- and belowground growth responses of Loblolly pine to nutrient and water additions. For. Sci. 1998, 44:317-328.
3. Armston, J. (2014) RSC Las Tools - version 1.9.3 [Computer program] Available from: <. https://code.google.com/p/rsclastools/%3E.
4. Bannaria A., Morina D., Bonna F., Hueteb A.R. A review of vegetation indices. Remote Sensing Reviews 1995, 13(1-2):95-120.
5. Barilotti A., Turco S., Napolitano R., Bressan E. La tecnologia LiDAR per lo studio della biomassa negli ecosistemi forestali. 15th Meeting of the Italian Society of Ecology, Torino, Italy 2005.
6. Bioucas-Dias J.M., Plaza A., Dobigeon N. Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2012, 5(2):354-379.
7. Bowerman B.L., O'Connell R.T. Linear statistical models: An applied approach 1990, Duxbury, Belmont, CA. 2nd ed.
8. Broge N.H., Leblanc A. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment 2001, 76(2):156-172.
9. Chauve A., Mallet C., Bretar F., Durrieu S., Deseillgny M., Puech W. Processing full-waveform lidar data: Modelling raw signals. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 2007.
10. Chen J.M., Black T.A. Defining leaf area index for non-flat leaves. Plant cell and environment. 1992, 15:421-429.
11. Chen J., Chilar J. Retrieving leaf area index of boreal forests using Landsat TM images. Remote Sensing of Environment 1996, 55:153-162.
12. Chen J.M., Chen X.Y., Ju W.M., Geng X.Y. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs. Journal of Hydrology 2005, 305:15-39.
13. Cleugh H.A., Leuning R., Mu Q., Running S.W. Regional evaporation estimates from fluxtower and MODIS satellite data. Remote Sensing of Environment 2007, 106:285-304.
14. Cook B.D., Corp L.W., Nelson R.F., Middleton E.M., Morton D.C., McCorkel J.T., Montesano P.M. NASA Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) airborne imager. Remote Sensing 2013, 5:4045-4066.
15. Dewey J.C., Roberts S.D., Hartley I. A comparison of tools for remotely estimating Leaf area index in Loblolly pine plantations. Proceedings of the 13th biennial southern silvicultural research conference Gen. Tech. Rep. SRS92 (pp. 77-75) Ashville, NC: US Dept. of Agriculture, Forest service, southern research station 2006, 640. K.F. Connor (Ed.).
16. Duchemin B., Hadriab R., Errakib S., Bouleta G., Maisongrandea P., Chehbounia A., Simonneauxa V. Monitoring wheat phenology and irrigation in: Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leafarea index and remotely-sensed vegetation indices. Agricultural Water Management 2006, 79:1-27.
17. Erikson H.M., Eklundh L., Kuusk T. Impact of understory vegetation on forest canopy reflectance and remotely sensed LAI estimates. Remote Sensing of Environment 2006, 103:408-418.
18. Evans J.S., Hudak A.T., Faux R., Smith A.M.S. Discrete return LiDAR in natural resources: Recommendations for project planning, data processing, and deliverables. Remote Sensing 2009, 1(4):776-794.
19. Falkowski M.J., Evans J.S., Martinuzzi S., Gessler P.E., Hudak A.T. Characterizing forest succession with LiDAR data: An evaluation for the inland northwest, USA. Remote Sensing of Environment 2009, 113(5):946-956.
20. Field A. Discovering statistics using SPSS 2013, SAGE Publications Ltd, California, USA. 4th ed.
21. Hill R.A., Broughton R.K. Mapping the understorey of deciduous woodland from leaf-on and leaf-off airborne LiDAR data: A case study in lowland Britain. ISPRS Journal of Photogrammetry and Remote Sensing 2009, 64(2):223-233.
22. Hopkinson C. The influence of LiDAR acquisition settings on canopy penetration and laser pulse return characteristics. Proceeding of: Geoscience and Remote Sensing Symposium 2006.
23. Hopkinson C., Chasmer L. Testing LiDAR models of fractional cover across multiple forest ecozones. Remote Sensing of Environment 2009, 113:275-288.
24. Hudak A.T., Crookston N.L., Evans J.S., Hall D.E., Falkowski M.J. Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data. Remote Sensing of Environment 2008, 112(5):2232-2245.
25. Kaartinen H., Hyyppa J., Yu X.W., Vastaranta M., Hyyppa H., Kukko A., Wu J.C. An international comparison of individual tree detection and extraction using airborne laser scanning. Remote Sensing 2012, 4(4):950-974.
26. Korhonen L., Korpela I., Heiskanen J., Maltamo M. Airborne discrete-return LiDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index. Remote Sensing of Environment 2011, 115:1065-1080.
27. Lefsky M.A., Cohen W.B., Parker G.G., Harding D.J. LiDAR remote sensing for ecosystem studies. Bioscience 2002, 52(1):19-30.
28. Leuning R., Cleugh H.A., Zegelin S.J., Hughes D. Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: Measurements and comparison with MODIS remote sensing estimates. Agricultural and Forest Meteorology 2005, 129:151-173.
29. Li Z., Douglas E., Strahler A., Schaaf C., Yang X.Y., Wang Z.S., Lovell J.L. Separating leaves from trunks and branches with duel-wavelength terrestrial LiDAR scanning. IEEE International Symposium on Geoscience and Remote Sensing IGARSS. Melbourne, Australia 2013, 3383-3386.
30. Lim K., Treitz P., Baldwin K., Morrison I., Green J. LiDAR remote sensing of biophysical properties of tolerant northern hardwood forests. Canadian Journal of Remote Sensing 2003, 29(5):658-678.
31. Lim K., Treitz P., Wulder M., St-Onge B., Flood M. LiDAR remote sensing of forest structure. Progress in Physical Geography 2003, 27(1):88-106.
32. Maltamo M., Packalen P., Yu X., Eerikainen K., Hyyppa J., Pitkanen J. Identifying and quantifying structural characteristics of heterogeneous boreal forests using laser scanner data. Forest Ecology and Management 2005, 216(1-3):41-50.
33. Morsdorf F., Kötz B., Meier E., Itten K.I., Allgöwer B. Estimation of LAI and fractional cover from small footprint airborne laser scanning data based in gap fraction. Remote Sensing of Environment 2006, 104:50-61.
34. Næsset E. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment 2002, 80(1):88-99.
35. Naesset E. 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 2009, 113:148-159.
36. Peduzzi A., Wynne R.H., Thomas V.A., Nelson R.F., Reis J.J., Sanford M. Combined use of airborne LiDAR and DBInSAR data to estimate LAI in temperate mixed forests. Remote Sensing 2012, 4(6):1758-1780.
37. Peduzzi A., Wynne R.H., Fox T.R., Nelson R., Thomas V.A. Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data. Forest Ecology and Management 2012, 270:54-65.
38. Reitberger J., Krzystek P., Stilla U. Analysis of full waveform LiDAR data for the classification of deciduous and coniferous trees. International Journal of Remote Sensing 2008, 29(5):1407-1431.
39. Richardson J., Moskal M., Kim S. Modeling approaches to estimate effective leaf area index from aerial discrete return LiDAR. Agricultural and Forest Meteorology 2009, 149:1152-1160.
40. Solberg S., Brunner A., Hanssen K.H., Lange H., Næsset E., Rautiainen M., Stenberg P. Mapping LAI in Norway spruce forest using airborne laser scanning. Remote Sensing of Environment 2009, 113:2317-2327.
41. Stenberg P. Correcting LAI-2000 estimates for the clumping of needles in shoots of conifers. Agricultural and Forest Meteorology 1996, 79:1-8.
42. Strunk J., Temesgen H., Andersen H.E., Flewelling J.P., Madsen L. Effects of LiDAR pulse density and sample size on a model-assisted approach to estimate forest inventory variables. Canadian Journal of Remote Sensing 2012, 38(5):644-654.
43. Sumnall M.J., Fox T.R., Wynne R.H., Blinn C., Thomas V.A. Estimating leaf area index at multiple heights within the understorey component of Loblolly pine forests from airborne discrete-return lidar. International Journal of Remote Sensing 2016, 37(1):78-99.
44. Turner D.P., Cohen W.B., Kennedy R.E., Fassnacht K.S., Briggs J.M. Relationship between leaf area index and Landsat spectral vegetation indices across three temperate zone sites. Remote Sensing of Environment 1999, 70:52-68.
45. Varhola A., Frazier G.W., Teti P., Coops N.C. Estimation of forest structure metrics relevant to hydrological modelling using coordinate transformation of airborne laser scanning data. Hydrology and Earth System Sciences 2012, 16:3749-4376.
46. Wang Q., Adiku S., Tenhunen J., Granier A. On the relationship of NDVI with leaf area index in a deciduous forest site. Remote Sensing of Environment 2005, 94(2):244-255.
47. Welles J.M., Norman J.M. Instrument for indirect measurement of canopy architecture. Argon. J. 1991, 83:818-825.
48. Zhang K., Chen S., Whitman D., Shyu M., Yan J., Zhang C. A progressive morphological filter for removing nonground measurements from airborne LiDAR data. IEEE Transactions on Geoscience and Remote Sensing 2003, 41(4):872-882.
49. Zhao K., Popescu S. LiDAR-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA. Remote Sensing of Environment 2009, 113:1628-1645.