景谷县森林蓄积量遥感估测及其动态变化分析

以云南省景谷县为研究区,基于Landsat5和Landsat8遥感数据,利用2012年和2017年两期全国森林资源连续清查实地调查数据,建立多元逐步回归和随机森林模型对景谷县森林蓄积量进行遥感估测对比研究。结果显示:综合建模精度来看,随机森林法在相同样地数量条件下具有更好的估测效果;从估测结果与林地保护利用规划和林地变更数据结果相比较,随机森林法估测值接近真实值,估测精度较高。     

基于GF-1和Sentinel-2时序数据的茶园识别

由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶园的方法,以浙江省武义县王宅镇为研究区,采用GF-1号为主要数据源,并利用MODIS地表反射率产品和Sentinel-2反射率数据,基于时空融合算法得到时间分辨率5 d的10 m Sentinel-2完整的时序数据。综合利用GF-1在空间细节方面的优势和重建的Sentinel-2高观测频率时序数据在反映茶树生长过程方面的优势,分别基于GF-1的光谱和纹理特征及GF-1的光谱、纹理特征和Sentinel-2时序特征两种特征组合方式,采用随机森林算法提取茶园。结果表明,GF-1光谱、纹理信息结合Sentinel-2时序信息分类结果的准确率、错误率、精确率、召回率和F1分数分别为96.91%、3.09%、89.00%、83.09%和0.86,仅基于GF-1光谱和纹理信息的分类准确率、错误率、精确率、召回率和F1分数分别为94.72%、5.28%、73.09%、84.61%和0.78,添加时序信息分类结果总体优于未添加时序信息的分类结果。表明高空间分辨率结合高频率时序遥感数据是提高茶园分类精度的有效手段。     

施氮时期对葡萄叶片光合生理及内源激素水平的影响

以10 a生酿酒葡萄‘蛇龙珠’为试验材料，运用水肥一体化滴灌的方式分别在萌芽期（S1）、新梢旺长期（S2）、开花期（S3）、果实第一次膨大期（S4）和副梢生长旺期（S5）一次性施入300 kg·hm^-2尿素，对照为整个生育期均不施氮肥（CK），分别于花后50 d（DAF50）、花后85 d（DAF85）和花后120 d（DAF120）进行光合特性指标的测定，并采样分析氮肥施用时期对葡萄叶片光合生理及内源激素水平的影响。结果表明：各生育期施氮均能增加叶片净光合速率（Pn）及PSⅡ最大光化学效率（Fv/Fm），在花前施氮肥叶片Pn和Fv/Fm增加最为显著，最高分别达到18.22 μmol·m^-2·s^-1和0.854。S1、S2和S3处理显著增大了不同生育期叶片气孔导度（Gs）和蒸腾速率（Tr），且S2处理在DAF85时最显著，Gs和Tr分别比CK高18.5%和10.8%；S3、S4和S5处理显著降低了叶片的胞间CO₂浓度（Ci）和非光化学淬灭系数（NPQ），S1处理叶片Ci与CK之间无显著差异。果实第一次膨大期之前施入氮肥能够显著增大各生育期叶片的PSⅡ电子传递量子效率（ФPSⅡ）和光化学淬灭系数（qP），最高分别达到0.889和0.959。可见，不同时期施氮肥，通过改变光合荧光相关参数影响叶片光能的吸收、传递、耗散和分配，从而改善叶片光能利用效率。氮肥的施用时期影响各生育期叶片内源激素的含量，施氮肥均显著提高了DAF85后叶片玉米素（ZT）含量，与CK相比至少提高21.9%；花后施入氮肥叶片中IAA含量在果实采收时保持在34.9 μg·g^-1以上，S4和S2处理GA₃含量最高，分别为7.11 μg·g^-1和6.49 μg·g^-1。因此，氮肥施用时期影响葡萄各生育期不同内源激素的积累。     

Estimation of biomass change in montane forests in Norway along a 1200 km latitudinal gradient using airborne laser scanning: a comparison of direct and indirect prediction of change under a model-based inferential approach

The current study compared two approaches for estimating change of aboveground biomass (AGB) in montane forests in Norway using field- and remotely sensed data from airborne laser scanning (ALS) from two points in time (four-year interval). The first was an indirect method that involved modeling and prediction of AGB at two points in time using ALS metrics as predictors, estimating the change from differences between AGB predictions. The second was a direct method, where change was modeled and predicted directly using differences between corresponding ALS metrics derived at the two measurement occasions as predictors, and the estimate was based on the predicted differences. Both methods were applied over a 1500?km long and 250?m wide transect from south to north in Norway comprising 250?m² grid cells. The results showed that the indirect method was more precise than the direct method. The indirect method estimated 0.65?Mg?ha^?1 change in AGB over the observation period, with a corresponding 95% confidence interval of ±0.27?Mg?ha^?1. The corresponding figures for the direct method was 0.54 and ±0.51?Mg?ha^?1. The direct method has been recommended previously. We conclude that the indirect method is both more precise and versatile.     

基于温度植被干旱指数的兖州煤田煤炭开采影响边界遥感提取

为识别植被覆盖区煤炭开采的生态影响边界,该文以兖州煤田为研究区域,应用温度植被干旱指数TVDI(temperature vegetation drought index)反演沉陷积水区外围的土壤湿度空间分布特征,利用MATLAB拟合TVDI变化趋势并依据其趋于稳定的渐近线,反解煤炭开采活动对矿区生态的影响边界,将其与采用MSCS(mining subsidence prediction system,MSCS)软件预计获得的下沉10 mm沉陷边界进行对比。结果表明:不同距离的TVDI中位数随距积水区边缘距离的变化表现为先增加后趋于平稳、呈指数变化特征;基于TVDI分析得到的煤炭开采的非积水影响范围,仅相当于沉陷积水面积的2.07倍,预计沉陷非积水面积与预计沉陷积水面积之比为4.63倍。通过模型拟合遥感指数随距离的变化特征,能够获得煤炭开采的影响边界;兖州煤田基于TVDI获取的煤炭开采影响面积,相对小于预计的开采沉陷面积。该研究可为确定煤炭开采对生态影响的边界提供参考。     

细菌群体感应抑制剂研究进展

多重耐药菌的出现已成为农业防治植物病害的一大难题，目前急需发展新的防治策略。群体感应 (quorum sensing, QS) 是一种微生物之间普遍存在的依赖于菌体密度的沟通协调机制，控制着细菌的生长、增殖、致病性、生物被膜形成及相关群体活动行为。群体感应抑制剂在抑制细菌毒性基因表达时不会对细菌生长产生压力，从而避免了细菌耐药性的产生。这一新颖的抑菌机制使其在开发新型农药方面有很大潜力。本文着重介绍了细菌群体感应机制、天然的及合成的细菌群体感应抑制剂种类及其应用。     

Comparison of estimators and feature selection procedures in forest inventory based on airborne laser scanning and digital aerial imagery

Digital maps of forest resources are a crucial factor in successful forestry applications. Since manual measurement of this data on large areas is infeasible, maps must be constructed using a sample field data set and a prediction model constructed from remote sensing materials, of which airborne laser scanning (ALS) data and aerial images are currently widely used in management planning inventories. ALS data is suitable for the prediction of variables related to the size and volume of trees, whereas optical imagery helps in improving distinction between tree species. We studied the prediction of forest attributes using field data from National Forest Inventory complemented with ad hoc field plots in combination with ALS and aerial imagery data in Aland province, Finland. We applied feature selection with genetic algorithm and greedy forward selection and compared multiple linear and nonlinear estimators. Maximally around 40 features from a total of 154 were required to achieve the best prediction performances. Tree height was predicted with normalized root mean squared error value of 0.1 and tree volume with a value around 0.25. Predicting the volumes of spruce and broadleaved trees was the most challenging due to small proportions of these tree species in the study area.     

基于GF-1卫星遥感数据识别京津冀冬小麦面积

省级尺度冬小麦面积的精准获取技术是农作物面积遥感监测研究的主要内容之一。为了获取省级尺度的冬小麦种植面积,该文以北京市(京)、天津市(津)和河北省(冀)3个省域范围为例,以国家标准地形图分幅为分类的图幅单元,利用国产GF-1/WFV数据,构建冬小麦面积指数,实现了省级尺度冬小麦面积的识别。本文以冬小麦全部9个月生育期的984景影像作为数据源,依次经过数据预处理、标准图幅单元的NDVI合成、样本点选择、冬小麦面积指数构建、冬小麦作物类型确认、省域范围制图及精度验证等步骤完成研究区域内冬小麦面积的提取。采用区域网平差和6S大气校正算法对数据源预处理,以中国1︰10万标准地形图分幅为分类图幅单元构建冬小麦面积指数,将冬小麦面积指数按照1%的比例等分,并将面积指数从0到100%分割为101个提取节点,将提取节点的NDVI值依次与类型确认样本比较,精度最高的则确认为冬小麦面积提取阈值,同时将该阈值应用于图幅单元内冬小麦面积指数影像,获取冬小麦种植分布。最后冬小麦面积识别的精度表明,以标准地图分幅作为计算单元,在GF-1影像基础上,利用冬小麦面积指数能够显著提高冬小麦与其他地物类型的波谱差异,且冬小麦的总体识别精度达到89.6%,用户精度达到89.8%,制图精度96.5%,Kappa系数0.72。在典型区域,本文算法与监督分类算法精度结果较为一致,除制图精度相差4.77%外,总体精度与用户精度差都在1.00%以内,说明本文算法具有精度高、运行效率高、分类单元识别结果一致性强的特点,能够满足省级尺度农情遥感业务监测的需要。     

Effects of Exogenous 24-epibrassinolide on Photosynthetic Physiology of CottonSeedlings under Low Temperature

[Objective] The objective of this study was to investigate the effects of exogenous 24-epibrassinolide (EBR) on the photosynthetic physiology of cotton seedlings under low temperature and to provide basis for improving the cold tolerance of cotton by using EBR as growth regulator. [Method] Taking CCRI 60, Lumianyan 28 and Simian 3 as materials, a field experiment was carried out in Institute of Cotton Research of CAAS(Anyang county, Henan province). Before the first low temperature treatment, the cotton seedlings were sprayed with distilled water (Control) and different concentrations of EBR (0.1 mg·L^－1 and 0.2 mg·L^－1), respectively. After 3 days, the relative electrical conductivity, chlorophyll content, rapid chlorophyll fluorescence induction kinetic curve (OJIP) and fluorescence parameters were measured. [Result] Under low temperature, the relative conductivity of CCRI 60, Lumianyan 28 and Simian 3 spraying with EBR decreased by 17.7%～32.8% compared with control, and there was no significant difference between CCRI 60 and Lumianyan 28 in different concentrations of EBR treatments, butthe relative conductivity of Simian 3 treating with 0.2 mg·L^－1 EBR was significantly lower than those treatments with 0.1 mg·L^－1 EBR . The chl a and chl b contents increased by 9.7%～32.6% and 15.0%～18.9%, respectively. The maximum photochemical efficiency of photosystemⅡ (F_v/F_M) and photosynthetic performance index on absorption basis(PI_ABS) increased significantly. PI_ABS of CCRI 60 increase the maximum by 75.6% using 0.1 mg·L^－1 EBR. Lumianyan 28 and Simian 3 increased the maximum by 101.1% and 265.6% using 0.2 mg·L^－1 EBR, respectively; Absorbed photon flux per cross section (ABS/CSm), electron transport flux (further than QA) per active reactive center (ETo/RC) and probability for electron transport (φEo) are significantly increased. [Conclusion] Exogenous EBR can enhance the ability of low temperature tolerance of cotton seedlings and alleviate the inhibition of photosynthesis in cotton at low temperature. The study showed that 0.1 mg·L^－1 EBR performs well in CCRI 60 and 0.2 mg·L^－1 in Lumianyan 28 and Simian 3.     

基于GF-1影像NDVI年度间相关分析的冬小麦面积变化监测

为实现区域冬小麦种植面积变化的快速监测,减少监测难度,提高监测效率和精度,该文提出一种基于年际NDVI相关关系的监测方法(relationship analysis of normal difference vegetation index,rNDVI)。选择河北省黄骅市、孟村县、海兴县3个县市为研究区,基于2014年4月14日、2017年4月26日两个时期的GF-1/WFV数据,基于rNDVI方法,通过将样本点两年度的NDVI值构建二维空间,采用最小二乘法拟合的方法获得不变地物点的上下包络线方程,进而得到冬小麦变化区域的监测阈值,提取冬小麦种植增加和减少区域,实现对研究区域的变化监测。结果表明,采用rNDVI算法总体精度分别为90.60%,Kappa系数为0.84,相比传统的先最大似然分类后再提取冬小麦种植变化区域的方法,总体精度与Kappa系数分别提高了6.6个百分点和16.7%。对冬小麦增加区域、冬小麦减少区域的变化监测结果进行分析,发现基于rNDVI的变化监测方法可以有效提高裸地、线状道路、破碎的冬小麦地块等区域的变化识别能力,提高监测精度。同时分别利用2014年3月1日和2017年3月12日、2014年5月17日与2017年5月20日两对GF-1/WFV数据进行基于rNDVI的冬小麦变化区域监测,结果表明3月份的监测精度较低,主要是由于3月份冬小麦长势尚不明显,5月份与4月份的总体精度相近,主要是由于5月份冬小麦NDVI已较高,易于识别。上述研究结果表明,基于rNDVI的冬小麦变化快速监测方法可以有效监测区域冬小麦种植面积的变化情况,算法简单高效,且能够在种植结构相对单一的冬小麦分布区域保持较高精度,能够满足农情遥感监测信息快速获取的需要。