光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2010年
1期
184-187
,共4页
罗菊花%黄文江%顾晓鹤%李宁%马丽%宋晓宇%李伟国%韦朝领
囉菊花%黃文江%顧曉鶴%李寧%馬麗%宋曉宇%李偉國%韋朝領
라국화%황문강%고효학%리저%마려%송효우%리위국%위조령
推扫成像光谱仪(PHI)%敏感波段%条锈病%病情指数
推掃成像光譜儀(PHI)%敏感波段%條鏽病%病情指數
추소성상광보의(PHI)%민감파단%조수병%병정지수
Pushbroom imaging spectrometer (PHI)%Sensitive bands%Stripe rust%Disease indexes
利用ASD地面非成像光谱仪对不同严重度的冬小麦条锈病的冠层光谱反射率进行测定,同时调查病情指数.通过对地面实测的46组病情指数与相应的光谱反射率进行相关性分析,筛选出了小麦条锈病在350~1 500 nm的敏感波段.结合多时相的高光谱航空飞行遥感图像数据的特点和规律,最终选择红波段的620~718 nm与近红外波段的770~805 nm为条锈病在PHI影像上的敏感波段.并利用620~718nm和770~805 nm的平均光谱反射率与相应的病情指数建立了多元线性同归模型:DI=19.241 R_1-2.207 R_2+12.274,验证结果表明,该模型的历史拟合度很好.并利用此模型最终在PHI影像上成功的实现了对冬小麦条锈病发生程度与发生范围的监测.
利用ASD地麵非成像光譜儀對不同嚴重度的鼕小麥條鏽病的冠層光譜反射率進行測定,同時調查病情指數.通過對地麵實測的46組病情指數與相應的光譜反射率進行相關性分析,篩選齣瞭小麥條鏽病在350~1 500 nm的敏感波段.結閤多時相的高光譜航空飛行遙感圖像數據的特點和規律,最終選擇紅波段的620~718 nm與近紅外波段的770~805 nm為條鏽病在PHI影像上的敏感波段.併利用620~718nm和770~805 nm的平均光譜反射率與相應的病情指數建立瞭多元線性同歸模型:DI=19.241 R_1-2.207 R_2+12.274,驗證結果錶明,該模型的歷史擬閤度很好.併利用此模型最終在PHI影像上成功的實現瞭對鼕小麥條鏽病髮生程度與髮生範圍的鑑測.
이용ASD지면비성상광보의대불동엄중도적동소맥조수병적관층광보반사솔진행측정,동시조사병정지수.통과대지면실측적46조병정지수여상응적광보반사솔진행상관성분석,사선출료소맥조수병재350~1 500 nm적민감파단.결합다시상적고광보항공비행요감도상수거적특점화규률,최종선택홍파단적620~718 nm여근홍외파단적770~805 nm위조수병재PHI영상상적민감파단.병이용620~718nm화770~805 nm적평균광보반사솔여상응적병정지수건립료다원선성동귀모형:DI=19.241 R_1-2.207 R_2+12.274,험증결과표명,해모형적역사의합도흔호.병이용차모형최종재PHI영상상성공적실현료대동소맥조수병발생정도여발생범위적감측.
Forty six points representing different severity degree of stripe rust were established in winter wheat field. The canopy reflectance was collected by an ASD hand-held spectrometer at each point Meanwhile, the diseases index was investigated. These data were used for the following analysis. Firstly, the relationships between diseases index and reflectance of bands in the range of 300-1 500 nm were analyzed. The sensitive bands were selected for stripe rust detecting. Secondly, considering the character of PHI image, red bands (620-718 nm) and near infrared bands (770-805 nm) were assigned as the best bands. Finally, the mean reflectance of red bands (620-718 nm) and near infrared bands (770-805 nm) was calculated respectively to construct the reverse model with the observed diseases indexes: DI=19. 241R_1 -2. 206 67 R_2 + 12. 274 4. With this model, the severity degree of stripe rust of winter wheat was monitored successfully in PHI image.