红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2014年
2期
586-594
,共9页
张东彦%赵晋陵%黄林生%马雯萩
張東彥%趙晉陵%黃林生%馬雯萩
장동언%조진릉%황림생%마문추
高光谱成像%归一化光谱指数%图像分类%光谱提纯%小麦%大豆
高光譜成像%歸一化光譜指數%圖像分類%光譜提純%小麥%大豆
고광보성상%귀일화광보지수%도상분류%광보제순%소맥%대두
hyperspectral imaging%normalized spectral index%imagery classification%spectrum purification%wheat%soybean
成像高光谱的近地田间应用为农业定量遥感的发展提供了新的契机。如何发挥其图谱合一的数据优势，尤其在解析土壤、阴影等背景地物对作物养分反演模型的影响需要关注。该研究借助可见/近红外成像高光仪，在近地田间采集小麦群体的成像立方体，根据影像中光照裸土、阴影裸土、光照叶片和阴影叶片的反射光谱特征建立了归一化光谱分类指数，并应用该指数提取大豆影像中不同类型地物的光谱，分析了背景土壤剔除前后的大豆植被归一化光谱与叶绿素密度的决定系数变化情况。结果表明：土壤和阴影叶片光谱去除后，反演叶绿素密度的敏感波段由红-近红外区间(727 nm，922 nm)向蓝、绿，尤其是红波段(710 nm,711 nm)移动。对叶绿素密度敏感的波段区间表现为可见光增加,近红外减少，且红边波段决定系数最高。由此说明，基于归一化光谱指数的植被光谱提纯对定量遥感反演研究具有重要意义。
成像高光譜的近地田間應用為農業定量遙感的髮展提供瞭新的契機。如何髮揮其圖譜閤一的數據優勢，尤其在解析土壤、陰影等揹景地物對作物養分反縯模型的影響需要關註。該研究藉助可見/近紅外成像高光儀，在近地田間採集小麥群體的成像立方體，根據影像中光照裸土、陰影裸土、光照葉片和陰影葉片的反射光譜特徵建立瞭歸一化光譜分類指數，併應用該指數提取大豆影像中不同類型地物的光譜，分析瞭揹景土壤剔除前後的大豆植被歸一化光譜與葉綠素密度的決定繫數變化情況。結果錶明：土壤和陰影葉片光譜去除後，反縯葉綠素密度的敏感波段由紅-近紅外區間(727 nm，922 nm)嚮藍、綠，尤其是紅波段(710 nm,711 nm)移動。對葉綠素密度敏感的波段區間錶現為可見光增加,近紅外減少，且紅邊波段決定繫數最高。由此說明，基于歸一化光譜指數的植被光譜提純對定量遙感反縯研究具有重要意義。
성상고광보적근지전간응용위농업정량요감적발전제공료신적계궤。여하발휘기도보합일적수거우세，우기재해석토양、음영등배경지물대작물양분반연모형적영향수요관주。해연구차조가견/근홍외성상고광의，재근지전간채집소맥군체적성상립방체，근거영상중광조라토、음영라토、광조협편화음영협편적반사광보특정건립료귀일화광보분류지수，병응용해지수제취대두영상중불동류형지물적광보，분석료배경토양척제전후적대두식피귀일화광보여협록소밀도적결정계수변화정황。결과표명：토양화음영협편광보거제후，반연협록소밀도적민감파단유홍-근홍외구간(727 nm，922 nm)향람、록，우기시홍파단(710 nm,711 nm)이동。대협록소밀도민감적파단구간표현위가견광증가,근홍외감소，차홍변파단결정계수최고。유차설명，기우귀일화광보지수적식피광보제순대정량요감반연연구구유중요의의。
Near-ground imaging spectroscopy applied in field provides new opportunity for development of quantitative remote sensing in agriculture. It deserves concern about how to exert its data advantage of integrating image and spectra into one, particularly in analyzing the influence of background targets, such as soil, shadow on crop nutrient inversion model. In this research, imaging cubes of wheat group in the field were collected by visible/near-infrared imaging spectrometer (VNIS). A normalized spectral index was set up according to reflectance characteristics of illuminated soil, shadow soil, illuminated leaf and shadow leaf in the image. Furthermore, the index was used to extract spectra of different targets in soybean images and analyze the variation of determination coefficient R2 between normalized spectra of soybean group and chlorophyll density before and after removing background soil. The results showed that when spectra of soil and shadow leaf were removed, the sensitive bands of chlorophyll density shifted from red and near-infrared ranges (727 nm, 922 nm) to red ranges (710 nm, 711 nm), meanwhile, the overall trend was that visible ranges increased, near-infrared regions decreased and red bands had the highest determination coefficient. Therefore, it can be concluded that spectral purification based on normalized spectral index has important significance for quantitative research in agricultural remote sensing.
