摘要
林分郁闭度与遥感数据的相关性分析是郁闭度遥感估算的基础,郁闭度遥感是林业遥感的重要方向。以四川省石棉县为例,就不同林分探讨了其郁闭度与陆地资源卫星专题制图仪LANDSAT Thematic Mapper(TM,包括其波段1至7,分别表示为TM1、TM2、TM3、TM4、TM5、TM6和TM7)数据之间的相关性及其受地形校正的影响。建立了地形数据库和基于1994年调查数据的森林资源数据库;对1994年6月26日成像的LANDSAT TM数据进行了几何校正,并与森林资源数据库配准;分别利用Lambert Cosine Correction(LCC)模型和Sun Canopy Sensor(SCS)模型对TM数据进行地形校正,生成TM-LCC和TM-SCS数据;将TM、TM-LCC和TM-SCS各波段数据分别与森林资源数据叠加统计,得到各小班TM、TM-LCC和TM-SCS各波段数据的均值和标准差,并将其添入数据库中,选取标准差较小的小班共1194个作为样本。按优势树种将样本层化为8个林分层,分别计算其郁闭度与TM、TM-LCC和TM-SCS各波段数据间的相关系数,并分析其在不同林分不同波段上的差异及其受地形校正的影响。研究表明:铁杉、冷杉和云杉等林分郁闭度与TM部分波段数据的相关性在0.01的水平上均为显著;而桦木、栎类、桤木、软阔类和云南松等林分郁闭度与TM数据的相关性在0.05的水平上均不显著;TM的LCC校正提高了冷杉、铁杉和软阔等林分郁闭度与TM4和TM5的相关性,TM的LCC校正还提高了软阔类林分郁闭度与TM7的相关性,TM的SCS校正提高了冷杉林分郁闭度与TM4和TM5的相关性,且在0.01的水平上均为显著。TM的LCC和SCS校正未能明显提高桦木、栎类、桤木、云南松和云杉等林分郁闭度与TM数据的相关性。该研究对林分郁闭度遥感具有一定的科学意义和应用价值。
Correlation analysis of canopy density with remote sensing data for different forest stand is basis for estimating canopy density using remote sensing, which is an important field of forest remote sensing. The relationships of the canopy density with Landsat Thematic Mapper（TM, which includes seven bands represented as TM1 ,TM/,TM3 ~TM4 ,TM5 ,TM6 and TM7 ） data for different forest stand were explored in Shimian County of Sichuan Province of P. R. of China, and how they were influenced by topographically correcting TM using the Lambert Cosine Correction （ LCC ） model and the Sun Canopy Sensor（SCS） model was also studied here. Firstly, the topographic database and the forest resource GIS database whose data were acquired in1994 in field were created. Secondly, Landsat TM data acquired on June 26, 1994 were geometrically corrected by using topographic maps, and matched well with the forest resource database. Thirdly, TM-LCC and TM-SCS were respectively obtained by topographically correcting TM using LCC model and SCS model. Fourthly, the mean and standard deviation of each band of TM, TM-LCC and TM- SCS for each forest sub-compartment were calculated by overlaying the forest resource GIS data with each band of TM, TM-LCC and TM-SCS, and were added into the attribute table of the forest resource database. 1194 sub-compartment samples of relatively lower standard deviation were selected from the forest resource database. Finally, the samples were stratified into eight forest stands according to their dominant tree, and the correlation coefficients of canopy density with each band of TM, TM-LCC and TM- SCS were calculated for each forest stand. It was shown that the correlation coefficients differ along with different band and different forest stand. Correlation coefficients of canopy density with TM2, TM3, TM4, TM5 and TM7 for Tsuga chinensis, with TM4, TM5 and TM7 for Abies fabri, and with TM1 for Picea asperata stand were significant at the 99% level of confidence. The highest is the correlation coeffic
出处
《生态学报》
CAS
CSCD
北大核心
2015年第7期2119-2125,共7页
Acta Ecologica Sinica
基金
国家自然科学基金项目(40771144)
国家973项目(2009CB421105)
国家863项目(2009AA12Z140)
关键词
郁闭度
林分
遥感
相关性
小班
canopy density
forest stand
remote sensing
correlation
sub-compartment
