光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2014年
12期
3358-3362
,共5页
林海军%张绘芳%高亚琪%李霞%杨帆%周艳飞
林海軍%張繪芳%高亞琪%李霞%楊帆%週豔飛
림해군%장회방%고아기%리하%양범%주염비
高光谱%荒漠树种%马氏距离%逐步判别分析
高光譜%荒漠樹種%馬氏距離%逐步判彆分析
고광보%황막수충%마씨거리%축보판별분석
Hyperspectral%Desert tree species%Mahalanobis Distance%Stepwise discriminant analysis
地面实测地物光谱可提供细致的光谱信息,表现同种地物不同理化特性和不同种类地物光谱的微小差异,使利用光谱进行地物识别成为可能。使用美国H R-768型地物光谱仪,在塔里木河下游和吐鲁番沙漠植物园实测胡杨、柽柳、梭梭和沙拐枣高光谱数据,利用包络线去除、一阶微分和二阶微分法对原始光谱进行变换处理,使用马氏距离法确定所测树种原始光谱和变换光谱的差异显著波段,利用逐步判别法检验所选差异波段的识别效果。结果表明:马氏距离法可准确确定树种识别的最佳波段,且上述4树种光谱识别波段大多位于近红外区。原始光谱、包络线去除、一阶微分和二阶微分四种光谱对4树种的识别精度分别为:85%,93.8%,92.4%和95.5%;可见,原始光谱经变换处理可提高树种的识别精度。但不同研究对象、不同光谱处理方法,提高识别精度的效率不同。研究结果将为大尺度高光谱遥感影像用于荒漠植物分类与生境监测和评价提供依据。
地麵實測地物光譜可提供細緻的光譜信息,錶現同種地物不同理化特性和不同種類地物光譜的微小差異,使利用光譜進行地物識彆成為可能。使用美國H R-768型地物光譜儀,在塔裏木河下遊和吐魯番沙漠植物園實測鬍楊、檉柳、梭梭和沙枴棘高光譜數據,利用包絡線去除、一階微分和二階微分法對原始光譜進行變換處理,使用馬氏距離法確定所測樹種原始光譜和變換光譜的差異顯著波段,利用逐步判彆法檢驗所選差異波段的識彆效果。結果錶明:馬氏距離法可準確確定樹種識彆的最佳波段,且上述4樹種光譜識彆波段大多位于近紅外區。原始光譜、包絡線去除、一階微分和二階微分四種光譜對4樹種的識彆精度分彆為:85%,93.8%,92.4%和95.5%;可見,原始光譜經變換處理可提高樹種的識彆精度。但不同研究對象、不同光譜處理方法,提高識彆精度的效率不同。研究結果將為大呎度高光譜遙感影像用于荒漠植物分類與生境鑑測和評價提供依據。
지면실측지물광보가제공세치적광보신식,표현동충지물불동이화특성화불동충류지물광보적미소차이,사이용광보진행지물식별성위가능。사용미국H R-768형지물광보의,재탑리목하하유화토로번사막식물완실측호양、정류、사사화사괴조고광보수거,이용포락선거제、일계미분화이계미분법대원시광보진행변환처리,사용마씨거리법학정소측수충원시광보화변환광보적차이현저파단,이용축보판별법검험소선차이파단적식별효과。결과표명:마씨거리법가준학학정수충식별적최가파단,차상술4수충광보식별파단대다위우근홍외구。원시광보、포락선거제、일계미분화이계미분사충광보대4수충적식별정도분별위:85%,93.8%,92.4%화95.5%;가견,원시광보경변환처리가제고수충적식별정도。단불동연구대상、불동광보처리방법,제고식별정도적효솔불동。연구결과장위대척도고광보요감영상용우황막식물분류여생경감측화평개제공의거。
The hyperspectral reflectance of Populus euphratica ,Tamarix hispida ,Haloxylon ammodendron and Calligonum mongolicum in the lower reaches of Tarim River and Turpan Desert Botanical Garden was measured by using the HR-768 field-portable spectroradiometer .The method of continuum removal ,first derivative reflectance and second derivative reflectance were used to deal with the original spectral data of four tree species .The method of Mahalanobis Distance was used to select the bands with significant differences in the original spectral data and transform spectral data to identify the different tree species .The pro-gressive discrimination analyses were used to test the selective bands used to identify different tree species .The results showed that The Mahalanobis Distance method was an effective method in feature band extraction .The bands for identifying different tree species were most near-infrared bands .The recognition accuracy of four methods was 85% ,93.8% ,92.4% and 95.5% re-spectively .Spectrum transform could improve the recognition accuracy .The recognition accuracy of different research objects and different spectrum transform methods were different .The research provided evidence for desert tree species classification , monitoring biodiversity and the analysis of area in desert by using large scale remote sensing method .