globalchange  > 影响、适应和脆弱性
DOI: 10.1016/j.foreco.2012.10.007
Scopus记录号: 2-s2.0-84878108913
论文题名:
Mapping local density of young Eucalyptus plantations by individual tree detection in high spatial resolution satellite images
作者: Zhou J.; Proisy C.; Descombes X.; le Maire G.; Nouvellon Y.; Stape J.-L.; Viennois G.; Zerubia J.; Couteron P.
刊名: Forest Ecology and Management
ISSN:  0378-1127
出版年: 2013
卷: 301
起始页码: 129
结束页码: 141
语种: 英语
英文关键词: Brazil ; Crown identification ; Forests ; Object detection ; Remote sensing ; Stochastic point process
Scopus关键词: Brazil ; Environmental conditions ; Forests ; Individual tree detections ; Object Detection ; Omission and commission errors ; Optical satellite images ; Stochastic point process ; Mean square error ; Quality control ; Remote sensing ; Satellite imagery ; Forestry ; algorithm ; biomass ; environmental conditions ; evergreen tree ; forest management ; index method ; mapping method ; monitoring ; plantation forestry ; remote sensing ; satellite imagery ; spatial resolution ; tree planting ; Brazil ; Forests ; Image Analysis ; Quality Control ; Random Processes ; Remote Sensing ; Satellites ; Brazil ; Eucalyptus
英文摘要: Local tree density may vary in young Eucalyptus plantations under the effects of environmental conditions or inadequate management, and these variations need to be mapped over large areas as they have a significant impact on the final biomass harvested. High spatial resolution optical satellite images have the potential to provide crucial information on tree density at an affordable cost for forest management. Here, we test the capacity of this promising technique to map the local density of young and small Eucalyptus trees in a large plantation in Brazil. We use three Worldview panchromatic images acquired at a 50cm resolution on different dates corresponding to trees aged 6, 9 and 13months and define an overall accuracy index to evaluate the quality of the detection results. The best agreement between the local densities obtained by visual detection and by marked point process modeling was found at 9months, with only small omission and commission errors and a stable 4% underestimation of the number of trees across the density gradient. We validated the capability of the MPP approach to detect trees aged 9months by making a comparison with local densities recorded on 112 plots of ∼590m2 and ranging between 1360 and 1700 trees per hectare. We obtained a good correlation (r2=0.88) with a root mean square error of 31trees/ha. We generalized detection by computing a consistent map over the whole plantation. Our results showed that local tree density was not uniformly distributed even in a well-controlled intensively-managed Eucalyptus plantation and therefore needed to be monitored and mapped. Use of the marked point process approach is then discussed with respect to stand characteristics (canopy closure), acquisition dates and recommendations for algorithm parameterization. © 2012 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/66593
Appears in Collections:影响、适应和脆弱性

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作者单位: Université de Montpellier 2, UMR AMAP, Boulevard de la Lironde, TA-A51/PS2, Montpellier Cedex 5 F-34398, France; Institut National de Recherche en Informatique et Automatique (INRIA), Sophia-Antipolis Méditerranée, BP 93, 2004 Route des Lucioles, Sophia-Antipolis Cedex F-06902, France; Institut de Recherche pour le Développement (IRD), UMR AMAP, Boulevard de la Lironde, TA-A51/PS2, Montpellier Cedex 5 F-34398, France; CIRAD, UMR Eco and Sols, 2 Place Viala, Montpellier cedex 01 F-34093, France; CIRAD, UMR TETIS, Maison de la Télédétection, Montpellier Cedex 5 F-34093, France; Atmospheric Sciences Department, Universidade de São Paulo, Rua do Matão 1226, 05508-090 São Paulo, Brazil; Department of Forestry and Environmental Sciences, North Carolina State University, Raleigh, NC 27695, United States; Centre National de la Recherche Scientifique (CNRS), UMR AMAP, TA A51 PS 2, Boulevard de la Lironde, Montpellier Cedex 5 F-34398, France

Recommended Citation:
Zhou J.,Proisy C.,Descombes X.,et al. Mapping local density of young Eucalyptus plantations by individual tree detection in high spatial resolution satellite images[J]. Forest Ecology and Management,2013-01-01,301
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