基于FLAASH的CBERS-02B星CCD影像大气校正

中巴资源卫星的CCD数据作为我国自主卫星数据源,在遥感应用方面发挥着重要作用。但由于CCD数据所获取的可见光-近红外波段信息易受大气因素干扰,因此寻求一种适合于中巴资源卫星CCD数据快速、有效的大气校正方法,以提高影像的利用率。介绍FLAASH大气校正的主要算法原理,并利用其进行CBERS-02B星CCD影像的大气纠正试验。通过分析校正前后的影像目视效果、典型地物光谱特征和NDVI值,表明FLAASH方法能够快速、有效地纠正大气因素对CBERS-02B星CCD影像的影响,对于植被覆盖地区纠正效果尤为明显。因此,FLAASH大气校正方法能够为大数据量的CBERS系列卫星CCD数据的大气校正提供了快速、可行及有效的方法。     

Performance evaluation of a crop/weed discriminating microsprayer

An intelligent real-time microspraying weed control system was developed. The system distinguishes between weed and crop plants and a herbicide (glyphosate) is selectively applied to the detected weed plants. The vision system captures 40 RGB images per second, each covering 140 mm by 105 mm with an image resolution of 800 × 600 pixels. From the captured images the forward velocity is estimated and the spraycommands for the microsprayer are calculated. Crop and weed plants are identified in the image, and weed plants are sprayed. Performance of the microsprayer system was evaluated under laboratory conditions simulating field conditions. A combination of maize (Zea mays L.), oilseed rape (Brassica napus L.) and scentless mayweed (Matricaria inodora L.) plants, in growth stage BBCH10, was placed in pots, which were then treated by the microspray system. Maize simulated crop plants, while the other species simulated weeds. The experiment were conducted at a velocity of 0.5 m/s. Two weeks after spraying, the fraction of injured plants was determined visually. None of the crop plants were harmed while 94% of the oilseed rape and 37% of the scentless mayweed plants were significantly limited in their growth. Given the size and shape of the scentless mayweed plants and the microsprayer geometry it was calculated that the microsprayer could only hit 64% of the scentless mayweed plants. The system was able to effectively control weeds larger than 11 mm × 11 mm.     

基于CBERS-02卫星遥感图像海岛棉与陆地棉植被指数的对比

随着遥感技术的发展,植被指数作为用来表征地表植被覆盖和生长状况的度量参数,已经在环境、生态、农业等领域有了广泛的应用。本文利用中巴资源卫星CBERS-02星CCD1-5波段遥感图像,比较了海岛棉与陆地棉5种植被指数(比值植被指数RVI,归一化差异植被指数NDVI,红色植被指数R I,转换型植被指数TVI,归一化差异绿度指数NDG I)的差异。结果表明:海岛棉与陆地棉的5种植被指数差异均未达到显著性水平(P>0.05);海岛棉与陆地棉之间比值植被指数RVI差异最大,而转换型植被指数TVI差异最小;在阿拉尔垦区利用7月份CBERS-02卫星遥感图像植被指数的差异很难区分出海岛棉与陆地棉。     

An effective biophysical indicator for opium yield estimation

Opium is a narcotic obtained from opium poppy and raw materials of heroin for illegal drug trade. Information on opium production is important for governments and international communities to understand the scale of illegal drug trade and to implement drug fighting policies. Opium production can be estimated from opium yield and poppy cultivation acreage. Poppy cultivation acreage in turn can be estimated using remote sensing technique. This study explores the feasibility of assessing opium yield using remote sensing technique. The objective of this study is to find an effective biophysical indicator that can be related to both opium yield estimation and remote sensing measurements. Data are obtained from three years ground experiments conducted in an official farm in North-Western China. Opium yield and main plant and environmental parameters of opium poppy are measured. A linear regression analysis measures the relationship between opium yield and main plant parameters. A strong correlation between opium yield and leaf area index (LAI) in flowering and harvesting periods of opium poppy is observed (R² = 0.826 and 0.862 respectively). LAI is a good indicator during flowering and harvesting periods and can be used to build a model for opium yield estimation. Furthermore, LAI can be retrieved using remote sensing at a region scale. The study shows that remote sensing could be used to estimate opium yield in opium poppy concentrated regions, and that a more comprehensive and precise opium production information could be obtained for further analysis of illegal drug circulating trend and policy.     

Design of a spatial sampling scheme considering the spatial autocorrelation of crop acreage included in the sampling units

Information on crop acreage is important for formulating national food polices and economic planning.Spatial sampling,a combination of traditional sampling methods and remote sensing and geographic information system(GIS)technology,provides an efficient way to estimate crop acreage at the regional scale.Traditional sampling methods require that the sampling units should be independent of each other,but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units.In this study,using Dehui County in Jilin Province,China,as the study area,we used a thematic crop map derived from Systeme Probatoire d’Observation de la Terre(SPOT-5)imagery,cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes,and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units.Moran’s I,a global spatial autocorrelation index,was used to evaluate the spatial autocorrelation among the two crop acreages in this study.The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size,there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units(Moran’s I varied from 0.49 to 0.89),irrespective of the sampling unit size.When the sampling unit size was less than3 000 m,the stratification design that used crop planting intensity(CPI)as the stratification criterion,with a stratum number of 5 and a stratum interval of 20%decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum.Therefore,the traditional sampling methods can be used to estimate the two crop acreages.Compared with CPI,there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion.As far as the selection of stratification criteria and sampling unit size is concerned,this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.     

农作物分布格局动态变化的遥感监测——以东北三省为例

【目的】当前对涉及到耕地内部不同作物空间分布及其变化的研究较少。本文旨在探讨大尺度作物种植面积和分布格局遥感提取方法及景观生态学中景观格局指数在作物格局动态变化分析中的应用。【方法】基于2005年和2010年作物生育期内遥感影像全覆盖的MODIS-NDVI数据,利用RS、GIS技术,通过分析东北地区主要作物（水稻、玉米、大豆）的种植结构、物候历及NDVI曲线特征,建立不同作物面积遥感提取模型,提取大尺度农作物空间分布格局信息。同时,利用景观格局指数方法分析农作物格局动态变化特征和变化规律。【结果】与多年平均统计数据比较,基于MODIS遥感数据提取的作物面积信息,2005年和2010年平均精度达到了90%以上;5年间,东北地区主要作物种植结构发生了较大变化。其中大豆平均斑块面积减少,面积年动态度为-4.47%,水稻和玉米平均斑块面积均增加,且5年的变化幅度均超过20%。【结论】成本和收益是作物面积增加或减少的主要原因;用中等分辨率的遥感数据进行大尺度作物面积提取的方法是可行的;景观生态学中格局指数可以用来分析耕地内部作物格局的动态变化规律。     

遥感技术在玉米估产中的应用与研究

玉米是我国主要的粮食作物之一,在我国北方地区占有举足轻重的地位。及时了解玉米种植面积、长势及产量,对于国家粮食政策的制定、价格的宏观调控以及对外粮食贸易都具有重要意义。遥感估产技术在农业发展中具有传统的统计方法不可比拟的优势,能及时客观地获得作物长势、产量等信息,特别是种植面积及其不同区域分布的信息,对于遥感估产玉米生产具有非常重要的作用。     

巴彦淖尔地区作物的结构变化与调整分析

对2003~2012年巴彦淖尔地区作物结构的演变趋势及成因进行了简要地分析和探讨,结果表明:小麦、牧草的种植面积比例呈逐年下降趋势;玉米、向日葵、油料作物的种植面积比例呈上升趋势,并趋于稳定;番茄、红黑白瓜子、西甜瓜的种植面积比例波动不大。根据分析结果对该地区作物结构的调整方向提出了指导性建议:以政策为准绳,加大支持力度;以市场为导向,经济效益优先;以"优、特"为中心;以产量为基础,以科技为依托。     

Low-cost photochemical reflectance index measurements of micropropagated plantlets using image analysis

A system for imaging the photochemical reflectance index (PRI) of micropropagated plantlet leaves was developed using a low-cost charge-coupled device (CCD) camera. The reflected light intensities of leaves at 530 and 570 nm were imaged using a monochrome CCD camera with respective band-pass filters. The reflection images were used to estimate the PRI values of the leaves. The relationships between the PRI estimated from images and a chlorophyll fluorescence parameter ΔF/Fm′, determined by pulse-amplitude modulation (PAM) chlorophyll fluorometer and representing PSII quantum yield, were investigated for several plants under various conditions to test the performance of the system. The PRI estimated from images decreased with a decline in the ΔF/Fm′ for strawberry leaves treated with high intensity light under artificial light condition and lettuce leaves treated with abscisic acid. These results suggest that the system can be used for non-destructive estimation of the PRI of leaves. The system was used to estimate the PRI of micropropagated potato leaves from outside the culture vessels. The time course of PSII quantum yield for the individual leaf could be demonstrated by the PRI estimated from images of potato plantlet leaves treated with high light. The findings suggest that the system has the potential for inexpensive, simple and efficient estimation of PRI for micropropagated plantlets.     

济南市粮食生产与耕地变化的分析及预测

采用最小人均耕地面积、耕地压力指数模型、回归分析方法和平滑预测法及Excel软件,在分析1986～2005年济南市耕地、人口、粮食动态变化的基础上,对未来15年耕地、人口、粮食、最小人均耕地面积和耕地压力指数进行了预测。结果表明:1986年以来,虽然济南市人均耕地面积持续减少,但由于耕地生产率不断提高,粮食总产量和人均粮食产量总体上呈增加趋势;未来15年,最小人均耕地面积和耕地压力指数将进一步降低。可见,依靠增加投入和科技进步从而不断提高耕地生产率,是减轻耕地压力、保证粮食安全生产的根本途径。     

Determination of differences in crop injury from aerial application of glyphosate using vegetation indices

Crop injury caused by off-target drift of herbicide can seriously reduce growth and yield and is of great concern to farmers and aerial applicators. Farmers can benefit from identifying an indirect method for assessing the level of crop injury. This study evaluates the combined use of statistical methods and vegetation indices (VIs) derived from multispectral images to assess the level of crop injury. An experiment was conducted in 2009 to determine glyphosate injury differences among the cotton, corn, and soybean crops. The crops were planted in eight rows spaced 102 cm apart and 80 m long with four replications. Seven VIs were calculated from multispectral images collected at 7 and 21 days after the glyphosate application (DAA). At each image collection date, visual injury estimates were assessed and data were collected for plant height, chlorophyll content, and shoot dry weight. From the seven VIs evaluated as surrogate for glyphosate injury identification using a canonical correlation analysis (CCA), the Chlorophyll Vegetation Index (CVI) showed the highest correlation with field-measured plant injury data. CVI image values were subtracted from the CVI average values of the non-injured area to generate CVI residual images (CVI_res). Frequency distribution histograms of CVI_res image values were calculated to assess the level of injury between crops. These data suggested that injury increased from 7DAA to 21DAA with corn exhibiting higher severity of injury than cotton or soybean, while only moderate injury was observed for cotton. The techniques evaluated in this study are promising for estimating the level of glyphosate herbicide drift, which can be used to make appropriate management decisions considering crop proximity.     

Digital image analysis to estimate the live weight of broiler

Computer assisted digital image analysis was performed to investigate the possibility of estimating body weight of live broiler. To achieve the stated objective, 100 Arbor acres broiler chicks were reared under standard rearing condition and 1200 digital images were captured from 20 randomly selected broilers during the 7-42 days growing period. The captured images were analyzed by raster image analysis software (IDRISI 32) to determine the broiler body surface area and developed a linear equation to estimate weights of the broiler from its body surface-area pixels. The developed weight predicted equation based on surface-area pixels was log W = 1.060406(log P) + 0.173756(log A) − 2.029268 (W = estimated body weight, P = surface-area pixels and A = age at weighing) and the degree of goodness of fit of this equation was 0.999. The relative error in weight estimation of broiler chicken by image analysis, expressed in terms of percent error of the residuals from surface-area pixels was in between 0.04 and 16.47. On the other hand, the estimated body weights were not significantly (p > 0.05) difference from manually measured body weights up to 35 days of age. Thus, the development of a practical imaging system for weighing live broiler is feasible.     

土地利用宏观监测中国产卫星的变化信息提取方法评估

选取全国范围内5个地形各异的地区,针对中等分辨率的国产卫星影像中巴资源卫星(CBERS-02B)、环境一号卫星(HJ-1)和北京一号卫星(BJ-1),采用多种土地利用变化信息提取方法,进行了土地利用变化信息提取方法的分析评估。通过实验得出比值法较适用于CBERS-02B数据,大部分地区属性精度和面积精度可达70%以上;差值法较适用于HJ-1和BJ-1数据,属性精度和面积精度也可达70%以上。在实际的宏观监测应用中,可优化各种数据使用模式,组合运用针对各种数据的最佳方法进行变化信息提取。     

Evaluating high resolution SPOT 5 satellite imagery for crop identification

High resolution satellite imagery offers new opportunities for crop monitoring and assessment. A SPOT 5 image acquired in May 2006 with four spectral bands (green, red, near-infrared, and short-wave infrared) and 10-m pixel size covering intensively cropped areas in south Texas was evaluated for crop identification. Two images with pixel sizes of 20 m and 30 m were also generated from the original image to simulate coarser resolution satellite imagery. Two subset images covering a variety of crops with different growth stages were extracted from the satellite image and five supervised classification techniques, including minimum distance, Mahalanobis distance, maximum likelihood, spectral angle mapper (SAM), and support vector machine (SVM), were applied to the 10-m subset images and the two coarser resolution images to identify crop types. The effects of the short-wave infrared band and pixel size on classification results were also examined. Kappa analysis showed that maximum likelihood and SVM performed better than the other three classifiers, though there were no statistical differences between the two best classifiers. Accuracy assessment showed that the 10-m, four-band images based on maximum likelihood resulted in the best overall accuracy values of 91% and 87% for the two respective sites. The inclusion of the short-wave infrared band statistically significantly increased the overall accuracy from 82% to 91% for site 1 and from 75% to 87% for site 2. The increase in pixel size from 10 m to 20 m or 30 m did not significantly affect the classification accuracy for crop identification. These results indicate that SPOT 5 multispectral imagery in conjunction with maximum likelihood and SVM classification techniques can be used for identifying crop types and estimating crop areas.     

于遥感的土地利用/覆盖信息动态变化监测分析——以扬州市为例

以正在高速发展的扬州市为例,利用不同时相的TM数据、CBERS-02的CCD数据和中国资源卫星二号星的全色数据,研究了城市主要地物信息快速准确提取的原理和方法,采用土壤调节植被指数(ISAV)与其它波段组合的方法对城市绿地信息进行提取;利用非监督分类法提取城市硬质建筑表面信息,决策树分类法提取城市水体信息,多重滤波处理对线性地物提取方面的优势提取道路信息.完成主要地物信息的提取后,对各项提取指标进行动态变化识别及分析,并结合扬州市社会经济指标寻求城市扩展的驱动因子.     

基于耕地压力指数的云南粮食产能安全动态分析

运用灰色系统模型,在分析1 949-2008年云南省人口、耕地和粮食产量动态变化的基础上,分别按温饱型、小康型和富裕型粮食消费水平对最小人均耕地面积和耕地压力指数进行分析和预测,从而对未来云南粮食产能安全态势进行评估。研究表明:2000年以来,最小人均耕地面积呈波动变化,但总体有下降趋势;耕地压力指数K也呈波动变化,变幅在1.03-1.1 1之间。根据预测结果,在未来25年内,无论按何类粮食消费水平计算,最小人均耕地面积和耕地压力指数都呈下降趋势,耕地所提供的粮食能满足全省居民温饱型和小康型的粮食消费水平,但要达到富裕型粮食消费的压力较大。     

交替沟灌玉米灌浆期茎流影响因子敏感性分析与模型适用性研究

【目的】应用人工神经网络对不同处理玉米茎流进行精准预测,为推算玉米蒸腾耗水量以及制定合理的灌水方案提供新思路。【方法】试验研究对象为夏玉米,品种为西农985。试验设置3个处理,分别为交替沟灌高水处理（alternate furrow irrigation,AFI1）、交替沟灌低水处理（alternate furrow irrigation,AFI2）和常规沟灌处理（conventional furrow irrigation,CFI）。AFI1、AFI2每次灌水量为CFI灌水量的2/3和1/2。利用通径系数与互信息分析不同处理的影响因素与玉米茎流相关关系,基于人工神经网络理论建立了玉米茎流速率估算模型,以主成分回归模型为对比,对两个模型预测精度和稳定性进行评价。【结果】（1）不同处理对环境因子的响应有所差异,影响CFI、AFI1玉米茎流的主要因素是气象因子,影响AFI2处理玉米茎流的主要因素是土壤水分;（2）不同土层含水量对各处理茎流的影响也有所不同,研究发现10-20 cm和20-30 cm土层含水量与玉米茎流相关程度最高。利用不确定性分析法进一步分析得出,常规处理与高水处理水平下,与茎液流变化关系最密切的土壤含水层为20-30 cm,其次是10-20 cm,低水处理水平下,最敏感的土层为10-20 cm,其次是20-30 cm;（3）根据模型误差分析与模型不确定性分析,神经网络模型RMSE、d-factor值较小,R²值达到了0.9以上,说明神经网络模型预测精度更高,模型更稳定。【结论】与传统方法相比,人工神经网络模型可以快速准确地对茎流进行预测,对指导玉米灌溉具有重要的指导意义。     

Software to quantify and map vegetative cover in fallow fields for weed management decisions

Mapping weed cover during the fallow period of dryland crop rotations would be valuable for weed management in subsequent crops and could be done with low cost color digital cameras, however most managers lack the specialized software and expertise needed to create a map from the images. A system of software was developed to quantify weed cover in fallow fields in digital images and to simplify and automate the most challenging tasks that non-GIS professionals confront in creating and using maps derived from a large number of images. A GIS file of image locations is created with inexpensive consumer software. Images are classified, a GIS file is generated and the map is displayed in a simple GIS viewer with free software we developed. A map can be generated from 1000 images and 5000 GPS coordinates in 30 min, including image classification. The classified and original images for all locations can be viewed together easily from the map application. The accuracy of estimating weed cover was evaluated using images collected in 15 fields under natural light with a consumer grade camera mounted on an ATV driving 8-11 km h⁻¹. Weed cover was estimated with 96% accuracy for images, regardless of the amount of crop residue, unless part of the image was shaded by the camera. In those images, accuracy was 90% or better. This system will work with many professional and consumer digital cameras and GPS units and the classification algorithm can be easily modified for other applications.     

基于PyWOFOST作物模型的东北玉米估产及精度评估

【目的】构建合理的作物估产方案,提高作物估产精度。【方法】本文以基于集合卡尔曼滤波（Ensemble Kalman Filter,EnKF）构建的遥感信息-作物模型结合模型（PyWOFOST）为基础,建立了以LAI为结合点,适用于中国东北地区玉米的同化模拟模型,并使用MODIS LAI数据作为外部同化数据进行同化模拟,重点分析了遥感观测（MODIS LAI）和模型参数（出苗-开花期所需积温,TSUM1）的不确定性（即随机误差）对同化模拟结果的影响。最后,利用PyWOFOST模型实现了区域尺度上的玉米估产。【结果】同化外部观测数据后的玉米模拟产量较未同化外部数据的模拟产量有明显改善,20个未受灾害影响的农气站玉米产量同化前的模拟误差及在TSUM1的不确定性为0、10、20、30℃时的同化后模拟误差分别为14.04%、12.71%、11.91%、10.44%及10.48%;同化后的模拟LAI普遍较同化前的模拟LAI更接近实测LAI,更符合玉米LAI的变化趋势;同化前模拟发育期与实测发育期平均绝对误差为3.4 d,而同化后在TSUM1的不确定性为0、10、20、30℃时模拟发育期与实测发育期的平均误差分别为3.5、4.3、5.0、5.5 d。区域尺度上玉米估产结果表明,58.82%的区域玉米估产误差在15%以内,同化产量和统计产量的确定系数为0.806。【结论】基于集合卡尔曼滤波同化遥感信息进行作物估产是可行的。     

基于多时相HJ-1B CCD影像的玉米倒伏灾情遥感监测

【目的】通过对倒伏发生前后的多时相HJ-1B卫星CCD多光谱影像植被指数的变化分析,实现区域尺度下的玉米倒伏受灾范围监测和灾情评估。【方法】以2015年8月3日因大风暴雨导致大面积玉米倒伏的河北省藁城市为研究区,提取HJ-1B CCD多光谱影像的多种植被指数,根据多时相植被指数变化量与实测倒伏样本的关联分析,筛选玉米倒伏敏感植被指数,采用正态(偏正态)统计理论的双阈值划分策略划定阈值,构建基于植被指数变化分析的玉米倒伏灾情遥感监测模型,评价玉米倒伏灾情严重程度,并基于野外实测样本进行精度评价。【结果】基于城镇、水体、倒伏与未倒伏玉米的HJ-1B CCD2多光谱反射率曲线可得,玉米与城镇建筑物和水体的光谱反射率存在较大差异,在可见光波段,倒伏玉米要高于未倒伏玉米的反射率,然而在近红外波段(830 nm),未倒伏玉米略高于倒伏玉米的反射率。由已提取出玉米种植区域后的前后两期HJ星的差值影像分析可得其像元整体分布趋势基本符合正态(偏正态)分布。由相关性分析可得,倒伏前后的比值植被指数(RVI)差值与玉米倒伏比例具有最高的相关性(R=0.9377),而且倒伏越严重,其RVI差值越大;通过野外实测样本与模型验证结果进行混淆矩阵分析,总体分类精度达到85.7%,Kappa系数为0.804;研究区玉米倒伏遥感空间制图结果与当地农业技术推广站监测结果基本一致。【结论】倒伏发生后,其玉米长势以及灾后恢复程度均存在较大差异,因此,基于玉米倒伏前后RVI差值的遥感监测模型能有效反映不同倒伏程度的冠层群体变化信息以及长势恢复情况,能在区域尺度下实现玉米倒伏受灾范围监测和灾情等级评估。