| 基于纹理特征的香格里拉县冷杉林郁闭度遥感估测研究 |
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| 引用本文： | 付虎艳,;张军,;舒清态.基于纹理特征的香格里拉县冷杉林郁闭度遥感估测研究[J].云南地理环境研究,2014(3):68-72. |
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| 作者姓名： | 付虎艳 ;张军 ;舒清态 |
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| 作者单位： | [1]西南林业大学林学院,云南昆明650224; [2]云南大学资源环境与地球科学学院,云南昆明650091 |
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| 基金项目： | 国家自然科学基金（31060114）;国家林业局林业公益性科研专项（201404309）. |
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| 摘 要： | 以香格里拉县2006年TM影像、2006年森林资源二类调查小班数据为信息源,结合研究区冷杉林地面实测标准地（30m×30m）数据,提取香格里拉县冷杉林TM影像分布信息及标准地纹理特征因子（共48个）,对各因子进行相关分析;利用主成分法对纹理特征因子进行因子分析,最终选出13个纹理特征因子利用偏最小二乘法进行回归建模并进行模型精度检验。根据回归估测模型以及提取出的冷杉林各波段纹理特征因子,进行研究区冷杉林郁闭度反演。结果表明,基于遥感影像纹理特征建立的郁闭度遥感估测模型,其RE=13.8%,RMSE=10.39,精度为83.3%。研究区冷杉林郁闭度反演可知冷杉林郁闭度多分布在0.6~0.7范围内,多为中度郁闭林地。
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| 关 键 词： | 郁闭度 偏最小二乘法 遥感估测 冷杉林 香格里拉县 |
STUDY ON THE REMOTE SENSING ESTIMATION OF FIR FOREST CANOPY CLOSURE IN SHANGRI- LA COUNTY BASED ON THE TEXTURE FEATURE |
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| Institution: | FU Hu -yan , ZHANG Jun, SHU Qing -tai ( 1. Southwest Forestry University ＆ College of Forestry, Kunming 650224, Yunnan, China ; 2. School of Resources Environment ＆Earth Science, Yunnan University, Kunming 650221, Yunnan, China) |
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| Abstract: | TM remote sensing image of Shangri - La County In 2006, the Forest Resource Inventory data in 2006 as the information source, combined with the fir forest ground standard （30m × 30m） data, extracted the fir forest＇s distribution information of Shangri -La County, and extracted the ground standard＇s texture features factors of TM image in Shangri - La County （48 in total）, though the correlation analysis of each factor, then u- sing the principal component methods analyze the texture characteristic factor, and ultimately selected 13 texture factors, using partial least squares regression modeling created the model and test its accuracy, using the estimation model and the extracted texture feature factors of fir forest, canopy density inversion of fir forest for study ar- ea. The results showed that canopy density estimation model based on texture features of remote sensing image, its RE = 13.8%, RMSE = 10. 39, estimation accuracy = 83.3% o From the fir forest canopy density inversion for study area showed that the fir forest canopy density distribution in the 0. 6 × 0. 7 range, mostly moderate canopy forest |
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| Keywords: | canopy closure PLS remote Sensing estimation fir forest Shangri -La County |
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