苹果叶片氮素含量快速检测模型

利用UV-2450型光谱分析仪测量苹果叶片光谱反射率,同时在实验室利用凯氏定氮法测量苹果叶片的氮素质量比,建立了适用于便携式检测仪的苹果叶片氮素含量快速检测模型.研究了苹果叶片光谱特性并进行了光谱反射率与氮素的相关性分析,获得了两个氮素敏感波长652 nm和772 nm.同时,利用分段减量精细采样法,构建了350 ～ 730 nm与740～880 nm波段内所有两两波段形成的归一化植被指数NDVI,并获取了与氮素含量相关性最高的波段组合(859 nm,364 nm)来构建苹果树NDVI.最后建立了基于苹果树NDVI、652 nm处反射率以及772 nm处反射率的偏最小二乘回归模型,建模精度达到0.904 8,均方根误差为0.159 7,检验模型精度达到0.917,均方根误差为0.283 3.     

基于高光谱成像技术的柑橘缺陷无损检测

应用高光谱成像技术无损检测柑橘的缺陷。选取蒂腐、黑斑、褐腐、结痂缺陷果和正常果各30个,提取并分析了5类果皮感兴趣区域光谱曲线并结合主成分分析法确定2个最佳波长(615nm和680nm),然后基于特征波长作主成分分析,选取第2主成分作为分类识别图像,提出采用特征波长主成分分析法与波段比算法相结合的方法,识别率达到94%。试验结果表明,高光谱成像技术可以有效地对带有蒂腐、黑斑、褐腐、结痂缺陷的柑橘进行分类识别。     

基于高光谱图像技术的油菜籽品种鉴别方法研究

提出了一种采用高光谱图像技术结合人工神经网络对油菜籽品种进行鉴别的方法.采集多个品种油菜籽400～1 000 nm范围的高光谱图像数据,通过主成分分析法(PCA)获得主成分图像,确定特征波长;采用基于灰度直方图和灰度共生矩阵联合的统计方法从特征图像中提取纹理特征参数,应用人工神经网络建立油菜籽品种鉴别模型.结果表明,模型训练时品种判别率为93.75%,预测的判别率为91.67%.说明高光谱图像技术对油菜籽品种具有较好的分类和鉴别作用.     

Estimating biomass of white spruce seedlings with vertical photo imagery

Estimation of individual tree seedling biomass isrequired in a variety of forest management andresearch applications such as assessment of netprimary productivity and carbon sequestrationpotential of forest stands, understory forest fuelinventories, and development of silviculturalguidelines to promote the growth of desired treespecies. Photo imagery is a promising non-destructivemethod for estimating the aboveground biomass of treeseedlings. This method was tested using naturallyregenerated white spruce (Picea glauca (Moench)Voss) seedlings growing in the understory of a mixedconifer shelterwood in central Ontario. In the fall of1997, 45 seedlings were sampled from plots exposed toone of three mechanical release treatments (earlyspring release, mid summer release, and no release(control)) in 1994. Each seedling was photographed inthe field to measure the vertical projected area(silhouette area) of the aboveground portion of theseedling. Seedlings were harvested, basal diameter andtotal height measured, and biomass (dry mass) offoliage, branches, main stem and total abovegroundplant tissue determined. Regression analysis revealeda strong relationship between both silhouette area andbasal diameter, and seedling biomass. Coefficients ofdetermination for regression equations usingsilhouette area were equal to 0.892, 0.918, 0.926, and0.937 for the main stem, branches, foliage, and totalaboveground biomass, respectively. Respectivecoefficients of determination for regression equationsusing basal diameter were 0.960, 0.945, 0.953, and0.977. Silhouette area-based equations for totalaboveground and foliar biomass differed significantly(P < 0.005) among release treatments. Nosignificant differences among treatments were observedbetween silhouette area-based equations for biomass ofbranches and main stem (P > 0.05), or betweenbasal diameter-biomass (allometric) equations for allcomponents (P > 0.1). The method was thentested by validating the biomass equations using anindependent data set from 35 white spruce seedlingsfrom the same site and cohort, but exposed todifferent treatments and microenvironmentalconditions. For each seedling, biomass components werepredicted using silhouette area-based and allometricequations, and a relative error of predictioncalculated. The mean relative error for silhouettearea-based predictions varied among biomass componentsfrom –20.25% to –3.21%, with standard deviation ofthe error ranging from 23.04% to 33.44%. The meanrelative error for allometric equations ranged from–2.46% to –21.75%, with standard deviations of23.34% to 32.61%. These results suggest that: (1)photo imagery can be used as an alternative to moretraditional allometric methods of biomass estimation,and (2) general (developed for a broad range ofgrowing conditions) equations derived by either methodare preferable to those specifically calibrated for agiven growing environment.     

利用水稻成熟期冠层高光谱数据进行估产研究

通过大田小区试验,测定了2个品种、3个供氮水平处理的水稻抽穗后不同时期冠层的高光谱反射率、叶面积指数及理论产量和实际产量。结果表明,抽穗后水稻冠层光谱反射率随发育期推移在可见光范围逐渐增大,在近红外区域逐渐减小;理论产量、实际产量与差值植被指数R1200-R680、R990-R680、R800-R680、R1200-R550、R990-R550、R     

高光谱遥感监测农作物病虫害研究进展

832003 石河子大学农学院农业昆虫与害虫防治专业2003级硕士研究生     

玉米和大豆LAI高光谱遥感估算模型研究

以ASD FieldSpec光谱仪实测了不同生长季的大田玉米、大豆的冠层高光谱与作物的叶面积指数LAI。采用单变量线性与非线性拟合和逐步回归分析的方式,建立了玉米、大豆LAI高光谱遥感估算模型,并对模型的估算结果进行了初步分析。分析结果表明,绿光波段反射峰区、红光波段以及近红外区的单波段反射率与作物的LAI有较强的相关性,而其他波段的反射率与作物的LAI的相关性相对较弱;以高光谱的窄波段构造的NDVI和RVI与作物的LAI的相关程度高,回归模型的预测水平高;而以多波段逐步回归方式构造的统计模型的预测效果最好。     

高光谱技术在作物信息诊断监测中的应用

概述了高光谱遥感技术的概念和发展;介绍了在叶面积指数及生物量、养分及水分、作物病虫害3个方面信息诊断监测的具体应用;指出了研究工作中亟待解决的一些问题,并提出了基于多传感信息融合的作物长势监测的设想.     

Relationships Between Yield Monitor Data and Airborne Multidate Multispectral Digital Imagery for Grain Sorghum

Remote sensing imagery taken during a growing season not only provides spatial and temporal information about crop growth conditions, but also is indicative of crop yield. The objective of this study was to evaluate the relationships between yield monitor data and airborne multidate multispectral digital imagery and to identify optimal time periods for image acquisition. Color-infrared (CIR) digital images were acquired from three grain sorghum fields on five different dates during the 1998 growing season. Yield data were also collected from these fields using a yield monitor. The images and the yield data were georeferenced to a common coordinate system. Four vegetation indices (two band ratios and two normalized differences) were derived from the green, red, and near-infrared (NIR) band images. The image data for the three bands and the four vegetation indices were aggregated to generate reduced-resolution images with a cell size equivalent to the combine's effective cutting width. Correlation analyses showed that grain yield was significantly related to the digital image data for each of the three bands and the four vegetation indices. Multiple regression analyses were also performed to relate grain yield to the three bands and to the three bands plus the four indices for each of the five dates. Images taken around peak vegetative development produced the best relationships with yield and explained approximately 63, 82, and 85% of yield variability for fields 1, 2, and 3, respectively. Yield maps generated from the image data using the regression equations agreed well with those from the yield monitor data. These results demonstrated that airborne digital imagery can be a very useful tool for determining yield patterns before harvest for precision agriculture.     

成土母质对水稻土高光谱特性及其有机质含量光谱参数模型影响的初步研究

以青紫泥 (BlueclayeyPaddysoil,BP)和红黄泥 (RedPaddysoil,RP)为例 ,研究发育于不同母质的水稻土高光谱和SOM含量光谱参数模型的差异性。结果表明 ,发育于河湖沉积物的BP的反射系数总体上高于发育于第四纪红色粘土母质的RP ,在与铁的氧化物有关的吸收波段 ,RP的吸收特性较BP强 ;RP的一阶微分的变化趋势总体上也比BP剧烈 ,特别是与铁的氧化物相关的波段及 2 2 0 0nm处 ;BP与RP的SOM的光谱参数模型所包含光谱波段的个数和位置有较大的差异 ,水稻土SOM含量光谱参数模型具有母质的独特性