河北省黄骅市三个重点蝗区两个时段土壤湿度的遥感提取

蝗灾是人类历史上重要的自然灾害之一,影响蝗灾爆发的因素很多,其中土壤湿度是重要的影响因素之一。以位于河北省黄骅市境内的3个重点蝗区——黄灶、杨官庄和藤南大洼为监测样区,利用高时间分辨率MODIS遥感影像数据,分别提取2002年(东亚飞蝗大发生年)秋蝗产卵期到夏蝗孵化期间的土壤湿度信息以及2004年(东亚飞蝗轻为害年)相同时段的土壤湿度信息,发现蝗灾大爆发年份的土壤湿度明显低于轻发生年份,在秋蝗的产卵期(9—10月)和夏蝗的孵化期(3—5月)差异尤为明显。     

河北省黄骅市三个重点蝗区两个时段土壤湿度的遥感提取

蝗灾是人类历史上重要的自然灾害之一，影响蝗灾爆发的因素很多，其中土壤湿度是重要的影响因素之一。以位于河北省黄骅市境内的3个重点蝗区——黄灶、杨官庄和藤南大洼为监测样区，利用高时间分辨率MODIS遥感影像数据，分别提取2002年(东亚飞蝗大发生年)秋蝗产卵期到夏蝗孵化期间的土壤湿度信息以及2004年(东亚飞蝗轻为害年)相同时段的土壤湿度信息，发现蝗灾大爆发年份的土壤湿度明显低于轻发生年份，在秋蝗的产卵期(9—10月)和夏蝗的孵化期(3—5月)差异尤为明显。     

有关东亚飞蝗生殖的几个问题

一、为什么飞蝗这样厉害 飞蝗为我国农业上的大害虫,并且是一个有历史性的大害虫。早在周平王时代(公元前707年),书籍上就记录现在的山东一带发生蝗灾。这二千多年来,大大小小的蝗灾,有记载可查考的,就在八百次以上。不但如此,其他国家如印度、伊朗,巴基斯坦,菲律宾,埃及,苏联,美国以及非洲、澳洲许多地方过去或现在都发生过蝗灾。蝗虫有许多种类,在中国沿海,沿湖蝗区及台湾的是东亚飞蝗Locusta migratoria ma-nilensis Meyen。     

1995年白洋淀东亚飞蝗大发生原因及防治策略

白洋淀是华北地区最大的淡水湖,是历史老蝗区,河北省东亚飞蝗Locustamigratoriamanilensis（Meyen）重点蝗区之一。1995年夏蝗呈特大发生,形成大面积高密度群居型蝗蝻,是20年来极为罕见的。其发生特点为蝗蝻出土集中,非农田蝗区密度高于农田蝗区,高密度群居型蝗螨均发生在淀边苇田蝗区。发生面积1．2万hm2,防治1．l万hm2,其中发生10头／m2以上的有0.7万hm2,100头／m2以上的0.l万hm2。现将分析的特大发生原因及防治策略报道如下。1大发生原因1．1大发生的蝗虫基数：据调查,1994年秋残蝗面积为1．2万hm2,比中等发生年多0．3万hm2…     

我国蝗虫的六大种群的遗传分化分析

我们可以用蝗虫的遗传多样性的变化来检测蝗虫种群的动态变化情况,这有利于研究蝗灾的发生于成为灾害的原理,有利于对蝗灾进行预报,进而有利于蝗灾的防治。对东亚飞蝗、大垫尖翅蝗、中华稻蝗、中华蚱蜢、亚洲小车蝗和黄胫小车蝗这六种蝗虫利用凝胶电泳的技术分析对其进行遗传分化分析,在所研究的12个基因座位中有有3个基因座在蝗虫的六大种群中均成呈单态分布,6个基因在在蝗虫的六大种群中呈多态分布,其余蝗虫的基因座位在这几个种群中至少有一个基因座位存在等位基因。研究表明六种蝗虫的遗传多样化水平均不高,我们可以通过蝗虫基因型和蝗虫等位基因频率的变化情况来对蝗虫种群进行检测,从而为防止蝗灾的发生提供指导和参考,进而提高防治效率。     

基于GIS和GS的东亚飞蝗卵块空间格局的研究

本文以沿渤海蝗区东亚飞蝗Locusta migratoria manilensis (Meyen) 越冬卵块为研究对象,野外采用450 m和50 m规则栅格取样,包括卵量、植被覆盖度、土壤含水量、含盐量、土壤pH和有机质等,利用地统计学方法,在GIS平台下,分析研究区域内影响蝗虫产卵选择的环境因子、蝗虫卵块的空间异质性及分布格局。结果表明, 植被覆盖度、土壤含盐量和土壤含水量在有卵和无卵的环境中存在极显著的差异,飞蝗产卵时最适宜的植被覆盖度、土壤含水量和盐度范围分别为0～30%、10.1%～20.0%和0.09%～1.99%,且当小环境植被覆盖度>50%、土壤含水量>30%或含盐量>3%时,飞蝗不再选择产卵。蝗虫卵块具有高度空间异质性,其空间自相关范围平均为390 m且呈斑块、聚集分布,蝗虫卵块变异函数曲线为球状模型。利用块段克立格法进行空间局部插值,得到研究区域卵块的空间分布格局图,可较准确地描述飞蝗卵块在研究区域内的空间分布、形状、地理位置及相对位置。研究结果可为地面卵块抽样调查、实时跟踪蝗卵胚胎发育进程、确定蝗灾早期发生点、片防治区域及蝗灾早期遥感预警提供科学依据。     

新疆典型蝗虫适生区分布预测

新疆草原面积广阔,农牧业地位突出,蝗灾对当地经济、生态威胁很大,近年新疆极端天气日渐频发,蝗灾监测与防治任务艰巨。以意大利蝗、西伯利亚蝗和亚洲飞蝗为代表的蝗虫数据为基础,综合考虑对蝗虫各生命周期有重要影响的环境因素,运用BIOCLIM模型、领域模型（DOMAIN）、马氏距离模型（MAHAL）、广义线性模型（GLM）、随机森林模型（RF）、提升回归树模型（BRT）、支持向量机模型（SVM）、最大熵模型（MaxEnt）等八种经典物种分布模型及集成模型对新疆典型蝗虫适生区展开了预测。结果表明：（1）不同模型对新疆典型蝗虫适生区预测存在差异,其中DOMAIN最差（曲线下面积（AUC）=0.688,真实技巧统计（TSS）=0.301）,而提升回归树（BRT）最佳（AUC=0.920,TSS=0.910）,基于BRT、SVM和MaxEnt 3个集成模型预测的新疆蝗虫适生区可靠性更高;（2）新疆典型蝗虫不同等级适生区面积约56.844万km²,占新疆总面积的36%,其中高适生区面积16.568万km²;（3）新疆典型蝗虫适生区主要集中于北疆阿勒泰、塔城地区,此外东部哈密地区及南疆绿洲边缘地带亦有分布。研究可为新疆草原工作部门推进蝗虫监测防治工作提供支持。     

中国东亚飞蝗新蝗区──海南热带稀树草原蝗区

东亚飞蝗Locustamigraioriamanilensis（Meyen）自1987年在我国海南岛突然爆发以来,7年来每年均有发生为害,1993年又是大发生年,这不仅使海南道受很大的经济损失,而且由于没有掌握煌区的成因与煌区演变的生态规律,不能提出有效的改造蝗区与控制蝗害的生态对策,只能依靠农药防治,从而使控制煌害陷于被动局面。1992年通过整个煌区的考察,及近6年来的田间飞蝗发生动态规律,参考该岛近500年来该害虫的发生为害资料,结合该岛飞蝗发生地近100年来的生态地理的演变特征与东亚飞蝗的生态学特性的综合分析,明确了海南东亚飞蝗蝗区是“热…     

偃师市1998年东亚飞蝗大发生的原因分析

东亚飞蝗Ｌｏｃｕｓｔａ　ｍｉｇｒａｔｏｒｉａ　ｍａｎｉｌｅｎｓｉｓ（Ｍｅｇｅｎ）是农作物大害虫之一,１９９４年秋季,偃师市秋蝗曾大发生,秋粮欠收。以后的几年一直没有发生。１９９８年秋季,东亚飞蝗在偃师市南部丘岭地区的大口、庞村、李村等乡镇突然暴发,为害面积２０００多ｈｍ２,其中有１００多ｈｍ２玉米被吃成光杆,最大虫口密度每平方米有虫２２４头,单株玉米有虫２０～３０头。虫情发生后,经过迅速扑火,其本控制了为害。对于东亚飞蝗在非蝗区突然大发生的情况,比较少见,应引起高度重视。下面就大发生的原因进行分…     

中国东亚飞蝗新类型蝗区──海南热带稀树草原蝗区的生态地理特征及其与大沙河蝗区比较

本文系统地对海南热带稀树草原螟区的生态地理结构特征进行了分析,说明本蝗区是Ｕｖａｒｏｖ（１９３６）提出的飞蝗两类蝗区理论中．由于森林破坏而形成的一类蝗区,作者将它定名为＂热带稀树草原蝗区＂。这类蝗区在我国过去尚缺乏研究。文中进而根据本蝗区的成因、生态特征以及对蝗区的生态控制对策,分别与我国大陆的东亚飞蝗大沙河类型蝗区进行了比较。     

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km²in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km². The lake area decreased by -9.3% at an annual rate of -53.7 km² yr^-1 during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.     

Coupling historical prospection data and a remotely-sensed vegetation index for the preventative control of Desert locusts

Locusts are grasshopper species that exhibit phase polyphenism resulting in the expression of gregarious behaviors that favor the development of large devastating bands and swarms. Desert locust preventative management aims to prevent crop damage by controlling populations before they can reach high densities and form mass migrating swarms. The areas of potential gregarization for Desert locust are large and need to be physically assessed by survey teams for efficient preventative management. An ongoing challenge is to be able to guide where prospection surveys should occur depending on local meteorological and vegetation conditions. In this study, we analyzed the relationship between historical prospection data of Desert locust observations from 2005 to 2009 and spatio-temporal statistics of a vegetation index gathered by remote-sensing with the help of multiple models of logistic regression. The vegetation index was a composite Normalized Difference Vegetation Index (NDVI) given every 16 days and at 250 m spatial resolution (MOD13Q1 from MODIS satellite). The statistics extracted from this index were: (1) spatial means at different scales around the prospection point, (2) relative differences of NDVI variation through time before the prospection, and (3) large-scale summary of vegetation quantity. The multi-model framework showed that vegetation development a month and a half before the survey was amongst the best predictors of locust presence. Also, the local vegetation quantity was not enough to predict locust presence. Vegetation quantity on a scale of a few kilometers was a better predictor but varied non-linearly, reflecting specific biotope types that support Desert locust development. Using one of the best logistic regression models and NDVI data, we were able to derive a predictive model of probability of finding locusts in specific areas. This methodology should help in more efficiently focusing survey efforts on specific parts of the gregarization areas based on the predicted probability of locusts being present.     

Can late summer Landsat data be used for locating Asian migratory locust,Locusta migratoria migratoria,oviposition sites in the Amudarya River delta,Uzbekistan?

Existing survey methods for assessing the Asian migratory locust, Locusta migratoria migratoria L. (Orthoptera: Acrididae), infestation risk in the Amudarya River delta, Uzbekistan, are largely constrained by economic resources and site accessibility. The surveys are restricted to a few easily accessible areas, which leads to a misinterpretation of the threat of locust infestation. This often results in indiscriminate blanket treatments of vast areas of wetlands with broad-spectrum insecticides, which may adversely impact non-target fauna and flora. In order to minimize the bias during surveys, one approach would be to allocate the sampling locations based on the distribution of the primary food and shelter plant of the locusts, the common reed, Phragmites australis (Cav.) Trin. ex Steud (Poaceae). In this study, we evaluated the utility of satellite-based remotely sensed data (Landsat TM) acquired in August 2006 to characterize reed distribution in the delta and identify potential locust oviposition sites. The overall accuracy of the Landsat data to map land cover classes in the delta was 84%. The Landsat TM data identified 90% of the reeds, but it was less useful in identifying areas where other vegetations (shrubs and grasses) were mixed with reeds. During the following summer field survey in June 2007, we identified 37 sites that were infested with early-instar locusts. The low migration capacity of young nymphs in dense reed vegetation allowed us to presume that these sites were used for oviposition in the previous summer. Twenty-eight (74%) of these 37 sites had reeds in the previous year. Results from these studies demonstrate that reed distribution maps derived from satellite data could be used for targeting locust egg-pod survey locations, in order to minimize sampling bias while predicting locust infestation risks for the following season.     

应用NOAA/AVHRR资料监测松毛虫危害研究初探

探讨了利用气象卫星定量监测松毛虫危害程度的可能性.以针叶被害率代表松毛虫的危害程度,轻度、中度、重度危害分别定义为针叶被害率<30%、30%～60%和>60%.根据地面光谱观测资料,建立了归一化植被指数与针叶被害率的相关方程,无松毛虫危害时NDVI为0.8823;为了消除大气等因子影响,利用松毛虫危害与未被危害的植被指数相对值表示松毛虫轻、中、重危害程度的遥感监测指标,无危害为1,0.78～1为轻度危害,0.57～0.78为中度危害,<0.57为重度危害.监测危害面积时,利用线性可加垂直植被指数进行混合象元分解.并分别对严重、中度、轻度3种类型发生年进行了定量监测分析,结果表明,AVHRR资料对中等以上松毛虫危害可进行定量监测分析,监测受灾面积比用同期的陆地卫星TM资料监测的受灾面积小12.1%～14.3%;对于轻度危害区域,采用气象卫星不易分辨,主要是由于不同下垫面和大气影响的差异,以及气象卫星空间分辨率较低.     

西藏自治区草地地上生物量遥感反演研究

草地地上生物量（Aboveground Biomass,AGB）是反映草地生态系统功能和质量的关键指标,大尺度地准确估算草地AGB对草地生态系统经营管理至关重要。研究以MODIS影像为数据源,提取反射率、植被指数和植被产品三种不同类型的特征变量,结合野外实测样地草地AGB数据,构建以多元线性逐步回归为代表的参数模型以及随机森林、支持向量机和kNN等非参数模型进行西藏自治区草地AGB估测及空间分布制图。结果表明：（1）多元线性逐步回归、随机森林、支持向量机和kNN模型在加入植被产品特征变量后,RMSE分别降低了15.8%、13.5%、4.1%和17.3%,表明植被产品作为建模变量用于草地AGB估测可有效提高模型精度;（2）三种组合变量构建的草地AGB估测模型中,反射率、植被指数、植被产品组合构建的模型效果最佳,其中kNN模型估测精度最高,R²达到0.60,RMSE和MAE分别为0.43、0.34 t/hm²;（3）草地AGB空间分布呈现出西北地区较低、中部地区较高且分布形态较破碎和东部地区较高的变化特征;（4）利用MODIS植被产品结合kNN模型的预测值与草地实测的AGB空间分布趋势基本一致。综上,MODIS植被产品结合kNN模型可作为大尺度区域草地AGB遥感估测的有效参考。     

Area-averaged vegetative cover fraction estimated from satellite data

The relationship was analysed between the vegetation cover factor expressed as a percentage and the area-averaged normalized difference vegetation index (NDVI). On selected days the NDVI was calculated from channel 1 and 2 reflectance data of the National Oceanic and Atmospheric Administration (NOAA—11) satellite's advanced very high-resolution radiometer (AVHRR) for five test areas under agricultural and forestry use. No ground-based reflectance measurements could be made for validation of these data. Therefore the land surface NDVI, which varied with time, and percentage vegetation cover of the test areas were deduced from time-independent but site-specific statistical land use data updated by temporal phenological observations, and from surface-specific reflectance curves published in the literature. The result indicated that the area-averaged NDVI, as obtained from the NOAA—11 radiometer, was less than the value calculated from the land surface NDVI. After correction to reduce the offset of the data, the values would be a suitable indicator of the fraction of vegetation cover.     

植被叶面积指数遥感反演的尺度效应及空间变异性

遥感作为宏观生态学研究中数据获取的一种便捷手段,有助于把握较大尺度内生态学现象的特征.应用遥感数据反演LAI时,由于像元的异质性,不同尺度遥感数据之间的转换是遥感发展的一个重要问题.以河北省黄骅市为研究区,在利用TM和MODIS遥感数据对芦苇LAI反演误差产生原因进行分析的基础上,利用半变异函数对像元空间异质性进行了定量描述.发现NDVI算法的非线性带给LAI尺度转换的误差很小,而LAI的空间异质性则是引起LAI尺度效应的根本原因.并且当像元内空间异质性很大时半变异函数的基台值比纯像元要大得多,空间自相关的程度是引起LAI尺度转换误差的主要原因;反之,像元内空间异质性不大时,随机误差是引起LAI尺度转换误差的主要原因.当像元为纯像元时,由像元异质性引起的反演误差基本可以忽略.此外,研究区芦苇的空间相关有效尺度约为360m,超过此距离空间相关性则不复存在.     

近30年新疆植被生长异常值时空变化及驱动因子

作为陆地生态系统的主体,植被的时空变化深刻地影响着景观格局和生态功能,深入理解植被动态及其对气候变化的响应,对于提高对生态过程的认识、加强生态管理具有重要意义。在一致性检验的基础上,利用中分辨率成像光谱仪(moderateresolution imaging Spectroradiometer,MODIS)的归一化植被指数(normalized Difference Vegetation Index,NDVI)数据集将新疆地区全球检测与模型研究组(Global Inventory Modeling and Mapping Studies,GIMMS)开发的NDVI数据集的时间序列拓展到2012年,探讨了生长季和各季节植被绿度、气候异常值的动态变化,分析了植被对气候变化的响应。研究结果显示,区域尺度和像元尺度GIMMS与MODIS NDVI之间的一致性较强。1982—2012年,研究区域生长季和各季节植被绿度呈显著增加趋势,但生长季存在明显阶段性:1998年前后分别呈显著增加和显著减少,夏季与秋季与生长季类似,而春季则不存在变化趋势的逆转。NDVI呈正异常值的面积比例与区域尺度NDVI的变化趋势一致;极端异常值、较大异常值多呈明显减少趋势,而一般异常值多呈增加趋势,NDVI的变化倾向于逐渐平稳。区域变暖趋势显著,降水量略有增加,潜在蒸散发显著提高,而湿润指数变化不明显。气温、潜在蒸散发主要在春季、秋季促进植被生长,而夏季降水量、湿润指数对植被生长的调节作用更为突出。     

Anatomical Characteristics Affecting the Musical Performance of Clarinet Reeds Made fromArundo donaxL. (Gramineae)

The musical performance of clarinet reeds made fromArundo donaxstemswas assessed by two experienced clarinettists, and the anatomyof the reeds was studied using confocal laser scanning microscopyto determine the relationship between anatomical characteristicsand musical performance. Statistically significant differencesbetween musically good and poor reeds were found in the anatomyof the cortical vascular bundles. Good musical performance wasassociated with reeds with a high proportion of vascular bundleswith continuous fibre rings, and bundles with a high proportionof fibre and a low proportion of xylem and phloem. Significantdifferences in these anatomical characteristics were also foundbetween reeds originating from cultivated plantation plantswhen compared to reeds produced from agricultural windbreakplants.Copyright 1998 Annals of Botany Company Arundo donax; clarinet reeds; stem anatomy; musical performance.     

于星载通道光谱指数与小麦冠层叶片氮素营养指标的定量关系

利用空间遥感信息大面积监测小麦冠层氮素营养状况和生产力指标具有重要意义和应用前景.本研究基于不同施氮水平下小麦冠层反射光谱信息,利用响应函数模拟基于不同卫星通道构建的光谱指数(包括单波段、比值光谱指数和归一化光谱指数),分析基于星载通道的光谱指数与小麦冠层叶片氮素营养指标的定量关系,确定监测小麦冠层叶片氮素营养的较好卫星传感器和光谱波段,建立小麦冠层氮素营养指标监测方程.结果表明：利用NDVI(MSS₇, MSS₅)、NDVI(RBV₃, RBV₂)、TM₄、CH₂、MODIS₁和MODIS₂遥感数据可以预估小麦叶片氮含量(LNC),其决定系数（R₂）在0.60以上;应用NDVI(PB₄, PB₂)、NDVI(CH₂, CH₁)、NDVI(MSS₇, MSS₅)、RVI(MSS₇, MSS₅)、MODIS₁和MODIS₂可以预测小麦叶片氮积累量(LNA),其R₂大于0.86.比较而言,NDVI(MSS₇, MSS₅)和NDVI(PB₄, PB₂)分别为预测小麦LNC和LNA的适宜星载通道光谱参数.