光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2015年
5期
1365-1369
,共5页
彭杰%王家强%向红英%牛建龙%迟春明%柳维扬
彭傑%王傢彊%嚮紅英%牛建龍%遲春明%柳維颺
팽걸%왕가강%향홍영%우건룡%지춘명%류유양
南疆%香梨%叶面降尘%高光谱%反演
南疆%香梨%葉麵降塵%高光譜%反縯
남강%향리%협면강진%고광보%반연
South Xinjiang%Pear%Foliar dust%Hyperspectrum%Quantitative inversion
叶面降尘指大气中的浮尘经重力沉降后,在植物叶片表面所形成的一层明显积尘,对其进行监测,可为沙尘区的环境评价及农业灾害评估提供基本依据。在量化叶面降尘的基础上,研究了叶面降尘对南疆香梨叶片高光谱特征的影响,分析了叶面降尘与反射率的相关性,并建立了叶面降尘的高光谱定量反演模型。研究结果表明,叶面降尘使可见光(400~700 nm )反射率增加,最大变幅位于666 nm ,绝对变化率为-10.50%,相对变化率为62.89%;使近红外(701~1050 nm )的反射率降低,最大变幅位于758 nm ,绝对变化率为12.04%,相对变化率为-41.75%。叶面降尘量大于20 g?m -2时,叶片除尘后,绿峰、红光吸收谷、蓝光吸收谷得到凸现,500~750 nm波段的斜率明显变大。叶面降尘量低于20 g?m-2时,其对绿峰的形状和面积影响不大。叶面降尘与反射率在可见光波段呈正相关,与近红外波段呈负相关,可见光波段的相关性要优于近红外波段,最大相关系数(0.61)出现在663 nm。在构建的七种PLSR反演模型中,倒数对数一阶微分模型具有较好的稳定性及预测能力,决定系数(R2)、均方根误差(RMSE)、预测方差比(RPD)分别为0.78,3.37和2.09,对叶面降尘具有很好的预测能力,其余模型的RPD均小于2.0。研究结果为叶面降尘的高光谱遥感监测提供了一定的理论依据,同时为沙尘区环境评价及农业灾害评估提供了新的数据获取方法与思路。
葉麵降塵指大氣中的浮塵經重力沉降後,在植物葉片錶麵所形成的一層明顯積塵,對其進行鑑測,可為沙塵區的環境評價及農業災害評估提供基本依據。在量化葉麵降塵的基礎上,研究瞭葉麵降塵對南疆香梨葉片高光譜特徵的影響,分析瞭葉麵降塵與反射率的相關性,併建立瞭葉麵降塵的高光譜定量反縯模型。研究結果錶明,葉麵降塵使可見光(400~700 nm )反射率增加,最大變幅位于666 nm ,絕對變化率為-10.50%,相對變化率為62.89%;使近紅外(701~1050 nm )的反射率降低,最大變幅位于758 nm ,絕對變化率為12.04%,相對變化率為-41.75%。葉麵降塵量大于20 g?m -2時,葉片除塵後,綠峰、紅光吸收穀、藍光吸收穀得到凸現,500~750 nm波段的斜率明顯變大。葉麵降塵量低于20 g?m-2時,其對綠峰的形狀和麵積影響不大。葉麵降塵與反射率在可見光波段呈正相關,與近紅外波段呈負相關,可見光波段的相關性要優于近紅外波段,最大相關繫數(0.61)齣現在663 nm。在構建的七種PLSR反縯模型中,倒數對數一階微分模型具有較好的穩定性及預測能力,決定繫數(R2)、均方根誤差(RMSE)、預測方差比(RPD)分彆為0.78,3.37和2.09,對葉麵降塵具有很好的預測能力,其餘模型的RPD均小于2.0。研究結果為葉麵降塵的高光譜遙感鑑測提供瞭一定的理論依據,同時為沙塵區環境評價及農業災害評估提供瞭新的數據穫取方法與思路。
협면강진지대기중적부진경중력침강후,재식물협편표면소형성적일층명현적진,대기진행감측,가위사진구적배경평개급농업재해평고제공기본의거。재양화협면강진적기출상,연구료협면강진대남강향리협편고광보특정적영향,분석료협면강진여반사솔적상관성,병건립료협면강진적고광보정량반연모형。연구결과표명,협면강진사가견광(400~700 nm )반사솔증가,최대변폭위우666 nm ,절대변화솔위-10.50%,상대변화솔위62.89%;사근홍외(701~1050 nm )적반사솔강저,최대변폭위우758 nm ,절대변화솔위12.04%,상대변화솔위-41.75%。협면강진량대우20 g?m -2시,협편제진후,록봉、홍광흡수곡、람광흡수곡득도철현,500~750 nm파단적사솔명현변대。협면강진량저우20 g?m-2시,기대록봉적형상화면적영향불대。협면강진여반사솔재가견광파단정정상관,여근홍외파단정부상관,가견광파단적상관성요우우근홍외파단,최대상관계수(0.61)출현재663 nm。재구건적칠충PLSR반연모형중,도수대수일계미분모형구유교호적은정성급예측능력,결정계수(R2)、균방근오차(RMSE)、예측방차비(RPD)분별위0.78,3.37화2.09,대협면강진구유흔호적예측능력,기여모형적RPD균소우2.0。연구결과위협면강진적고광보요감감측제공료일정적이론의거,동시위사진구배경평개급농업재해평고제공료신적수거획취방법여사로。
The precipitation of floating and sinking dust on leaves of plants is called as foliar dustfall .To monitor foliar dust-fallIt ,it will provide fundamental basis for environmental assessment and agricultural disaster evaluation of dust area .There-fore ,the aim of this work to (1) study the effect of foliar dustfall content (FDC) on high spectral characteristics of pear leaves , (2) analyze the relationship between reflectances and FDC ,and (3) establish high spectral remote sensing quantitative inversion model of FDC .The results showed that FDC increased reflectances of visible band (400~700 nm) with maximum band of 666 nm .Absolute and relative rates of change were -10.50% and -62.89% ,respectively .The FDC decreased reflectances of near infrared band (701 ~ 1 050 nm) with maximum band of 758 nm .Absolute and relative rates of change were 12.04% and 41.75% ,respectively .After dustfall was removed ,reflection peak of green light and absorption valley of red and blue light be-came prominent ,and slope of 500~750 nm wave band increased when FDC was more than 20 g?m -2 .While FDC just slightly affected shape and area of reflection peak of green light when FDC was less than 20 g?m -2 .FDC were positive and negative cor-related with reflectances of visible band and near infrared band ,respectively .Maximum correlation coefficient (0.61) showed at 663 nm .All of 7 inversion models ,the model based on the first-order differential of logarithm of the reciprocal had better stabili-ty and predictive ability .The coefficient of determination(R2 ) ,root mean square error (RMSE) and relative percent deviation (RPD) of this model were 0.78 ,3.37 and 2.09 ,respectively .The results of this study can provide a certain reference basis for hyperspectral remote sensing of FDC .