قابلیت‌سنجی کارایی داده‌های لیدار و اپتیک به منظور استخراج پارامترهای ساختاری جنگل

نویسنده
دانشگاه تربیت مدرس
چکیده
در سال‌های اخیر پیشرفت تکنولوژی‌های سنجش از دور و افزایش تنوع داده‌های قابل استفاده موجب شده تا ارزیابی و قابلیت‌سنجی داده‌های مختلف از اهمیت زیادی برخوردار بوده و به همین دلیل به عنوان مسأله‌ای که کمتر در تحقیقات گذشته بدان پرداخته شده است، هدف اصلی این تحقیق قرار گیرد. در این تحقیق داده‌های مستخرج از تصاویر وردویو-2 و اسپات-5 شامل اطلاعات بافتی این تصاویر و نیز خصوصیات آماری مستخرج از داده‌های لیدار به صورت مستقل برای تخمین پارامترهای ساختاری جنگل کاج تک‌گونه[1] استفاده گردید و نتایج حاصل از هر داده با نتایج حاصل از داده‌های دیگر مورد مقایسه قرار گرفت. نتایج حاصل از این تحقیق نشان داد در حالی که داده‌های وردویو-2 برای برآورد تراکم و قطر درختان دارای بهترین عملکرد است، داده‌های لیدار برای تخمین ارتفاع میانگین و حجم درختان مناسب است. در ضمن تفاوت آماری معنی‌داری بین داده‌های مختلف سنجش ازدور برای برآورد رویه سطح درختان وجود ندارد، همچنین در میان پارامترهای ساختاری، در حالی که ارتفاع میانگین و قطر درختان با خطایی قابل قبول برآورد شدند، تخمین تراکم، حجم و رویه سطح درختان با دقت کمتری انجام شد.

[1]. Pinus Radiata

کلیدواژه‌ها

موضوعات


Asner, G. P., Bustamante, M. M. C. & Townsend, A. R. (2003), “Scale dependence of biophysical structure in deforested areas bordering the Tapajós National Forest, Central Amazon”, Remote Sensing of Environment, 87(4), 507-520.
Bi, H., Fox, J. C., Li, Y., Lei, Y., & Pang, Y. (2012), “Evaluation of nonlinear equations for predicting diameter from tree height”, Canadian Journal of Forest Research, 42(4), 789-806.
Boyd, D. S., & Danson, F. M. (2005), “Satellite remote sensing of forest resources: three decades of research development”, Progress in Physical Geography, 29(1), 1-26.
Dean, T. J., Cao, Q. V., Roberts, S. D., & Evans, D. L. (2009), “Measuring heights to crown base and crown median with LiDAR in a mature, even-aged loblolly pine stand”, Forest Ecology and Management, 257(1), 126-133.
Efron, E., & Tibshirani, R. (1993), An Introduction to the Bootstrap. New York: Champman & Hall.
Erody, T. L., & Moskal, L. M. (2010), “Fusion of LiDAR and imagery for estimating forest canopy fuels”, Remote sensing of environment, 114(4), 725-737.
Eyles, A., Robinson, A. P., Smith, D., Carnegie, A., Smith, I., Stone, C. (2011), “Quantifying stem growth loss at the tree-level in a Pinus radiata plantation to repeated attack by the aphid, Essigella californica”, Forest ecology and management, 261(1), 120-127.
Gao, X., Huete, A. R., Ni, W., & Miura, T. (2000), “Optical-biophysical relationships of vegetation spectra without background contamination”, Remote sensing of environment, 74(3), 609-620.
Gill, S. J., Biging, G. S., & Murphy, E. C. (2000), “Modeling conifer tree crown radius and estimating canopy cover”, Forest ecology and management, 126(3), 405-416.
Harris, R. J. (1985), A primer of multivariate statistics, New York: Academic Press.
Holmgren, P., & Thuresson, T. (1998), “Satellite remote sensing for forestry planning. A review”, Scandinavian journal of forest research, 13(1-4), 90-110.
Hyde, P., Dubayah, R., Walker, W., Blair, J. B., Hofton, M., & Hunsaker, C. (2006), “Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy”, Remote sensing of environment, 102(1-2), 63-73.
Hyyppä, J., Hyyppä, H., Inkinen, M., Engdahl, M., Linko, S., & Zhu, Y. H. (2000), “Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes”, Forest ecology and management, 128(1-2), 109-120.
Kayitakire, F., Hamel, C., & Defourny, P. (2006), “Retrieving forest structure variables based on image texture analysis and IKONOS-2 imagery”, Remote sensing of environment, 102(3-4), 390-401.
Lefsky, M. A., Cohen, W. B., Acker, S. A., Parker, G. G., Spies, T. A. & Harding, D. (1999), “LiDAR remote sensing of the canopy structure and biophysical properties of Douglas-Fir Western Hemlock Forests”, Remote sensing of environment, 70(3), 339-361.
Le Toan, T., Shaun, Q., Woodward, I., Lomas, M., Delbart, N., & Picard, G. (2004), “Relating RADAR remote sensing of biomass to modelling of forest carbon budgets”, Climate change, 67, 379-402.
Lim, K., Treitz, P., Wulder, M., St-Onge, B., & Flood, M. (2003), “LiDAR remote sensing of forest structure”, Progress in physical geography, 27(1), 88-106.
Linder, S., Benson, M., Myers, B., & Raison, R. (1987), “Canopy dynamics and growth of Pinus radiata: I. Effects of irrigation and fertilization during a drought”, Canadian journal of forest research, 17(10), 1157-1165.
Lu, D. (2005), “Above-ground biomass estimation using Landsat TM data in the Brazilian Amazon”, International journal of remote sensing, 26(12), 2509 - 2525.
Lutz, D. A., Washington-Allen, R. A. & Shugart, H. H. (2008), “Remote sensing of boreal forest biophysical and inventory parameters: a review”, Canadian journal of remote sensing, 34(S2), 286-313.
Madgwick, H. A. I. (1994), Pinus radiata: Biomass, form, and growth. Rotorua, Madgwick.
Næsset, E. (1997), “Determination of mean tree height of forest stands using airborne laser scanner data”, ISPRS journal of photogrammetry and remote sensing, 52(2), 49-56.
Neumann, M., Ferro-Famil, L., & Reigber, A. (2010), “Estimation of forest structure, ground, and canopy layer characteristics from multi-baseline polarimetric interferometric SAR data”, IEEE transactions on geoscience and remote sensing, 48(3), 1086-1104.
Nilsson, M. (1996), “Estimation of tree heights and stand volume using an airborne LiDAR system”, Remote sensing of environment, 56(1), 1-7.
Popescu, S. C., Wynne, R. H., & Nelson, R. F. (2003), “Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass”, Canadian journal of remote sensing, 29(5), 564-577.
Popescu, S. C., Wynne, R. H., & Scrivani, J. A. (2004), “Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA”, Forest science, 50(4), 551-565.
Riano, D., Chuvieco, E., Salas, J., & Aguado, I. (2003), “Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types”, IEEE transactions on geoscience and remote sensing, 41(5), 1056-1061.
Roberts, J. W., Van Aardt, J. A. N., & Ahmed, F. B. (2011), “Image fusion for enhanced forest structural assessment”, International journal of remote sensing, 32(1), 243-266.
Shamsoddini, A. (2016), “Pine forest structural parameter retrieval using radar images”, The journal of spatial planning, 20(1), 53-78. [In Persian]
Shamsoddini, A., Trinder, J. C., & Turner, R. (2015), “Paired-data fusion for improved estimation of pine plantation structure”, International journal of remote sensing, 36(8), 1995-2009.
Shamsoddini, A., Trinder, J. C., & Turner, R. (2013a), “Pine plantation structure mapping using WorldView-2 multispectral image”, International journal of remote sensing, 34, 3986-4007.
Shamsoddini, A., Turner, R. & Trinder, J. C. (2013b) “Improving LiDAR-based forest structure mapping with crown-level pit removal”, Journal of spatial science, 58, 29-51.
Song, C. (2007), “Estimating tree crown size with spatial information of high resolution optical remotely sensed imagery”, International journal of remote sensing, 28(15), 3305-3322.
Song, C. & Woodcock, C. E. (2002), “The spatial manifestation of forest succession in optical imagery: The potential of multiresolution imagery”, Remote sensing of environment, 82(2-3), 271-284.
Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2001), “Classification and change detection using Landsat TM Data: When and how to correct atmospheric effects?”, Remote sensing of environment, 75(2), 230-244.
Timothy, D., Onisimo, M., & Riyad, I. (2016), “Quantifying aboveground biomass in African environments: A review of the trade-offs between sensor estimation accuracy and costs”, Tropical ecology, 57(3), 393-405.
Tonolli, S., Dalponte, M., Neteler, M., Rodeghiero, M., Vescovo, L., & Gianelle, D. (2011), “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps”, Remote sensing of environment, 115, 2486-2498.
Trotter, C. M., Dymond, J. R., & Goulding, C. J. (1997), “Estimation of timber volume in a coniferous plantation forest using Landsat TM”, International journal of remote sensing, 18(10), 2209- 2223.
Van der Colff, M., & Kimberley, M. (2013), “A national height-age model for Pinus radiata in New Zealand”, New Zealand journal of forestry science, 43(4), 1-11.
Vermote, E. F., Tanre, D., Deuze, J. L., Herman, M., & Morcette, J. J. (1997), “Second simulation of the satellite signal in the solar spectrum, 6S: an overview”, IEEE transactions on geoscience and remote sensing, 35(3), 675-686.
Vincini, M., & Frazzi, E. (2003), “Multi-temporal evaluation of topographic normalization methods on deciduous forest TM data”, IEEE transactions on geoscience and remote sensing, 41(11), 2586-2590.
Waring, R. H., Way, J., Hunt, E. R., JR., Morrissey, L., Ranson, K. J., Weishampel, J. F., Oren, R. & Franklin, S. E. (1995), “Imaging radar for ecosystem studies”, BioScience, 45(10), 715-723.
Wolter, P. T., Berkley, E. A., Peckham, S. D., Singh, A., & Townsend, P. A. (2012), “Exploiting tree shadows on snow for estimating forest basal area using Landsat data”, Remote sensing of environment, 121, 69-79.
Wulder, M. A., Hall, R. J., Coops, N. C., & Franklin, S. E. (2004), “High spatial resolution remotely sensed data for ecosystem characterization”, BioScience, 54(6), 511-521.
Wulder, M. A., Ledrew, E. F., Franklin, S. E., & Lavigne, M. B. (1998), “Aerial image texture information in the estimation of Northern deciduous and mixed wood forest leaf area index (LAI)”, Remote sensing of environment, 64(1), 64-76.
Yan, H., Bi, H., Li, R., Eldridge, R., Wu, Z., Li, Y. & Simpson, J. (2006), “Assessing climatic suitability of Pinus radiata (D. Don) for summer rainfall environment of southwest China”, Forest ecology and management, 234(1-3), 199-208