Polarized Lidar Reflectance Measurements of Vegetation at Near-Infrared and Green Wavelengths

There is growing interest in the use of lidar for remote sensing of vegetation owing to the emergence of reliable and rugged lasers and highly sensitive detectors. Lidar remote sensing has a distinct advantage over conventional techniques in vegetation remote sensing due to its capability for three-dimensional characterization of vegetative targets. The Multiwavelength Airborne Polarimetric Lidar (MAPL) system was developed primarily for vegetation remote sensing applications from an airborne platform of up to 1,000 -m altitude. The lidar system has full waveform capture and polarimetric measurement capability at two wavelengths in the near-infrared (1064 nm) and the green (532 nm) spectral regions. This study presents preliminary ground-based lidar reflectance measurements on a variety of deciduous and coniferous trees under fully foliated conditions with a view towards tree species discrimination. Variations in the reflectance characteristics of selected deciduous trees under unfoliated and fully foliated conditions were also investigated. Our study reveals distinct differences in the reflectance characteristics of various trees.     

Static headspace analysis of volatile organic compounds in soil and vegetation samples for site characterization

Traditional methodologies for the characterization of volatile organic compounds (VOCs) in subsurface soil are expensive, time-consuming processes that are often conducted on samples collected at random. The determination of VOCs in near-surface soils and vegetation is the foundation for a more efficient sampling strategy to characterize subsurface soil and improve understanding of environmental problems.In the absence of a standard methodology for the determination of VOCs in vegetation and in view of the high detection limits of the method for soils, we developed a methodology using headspace gas chromatography with an electron capture detector for the determination of low levels (parts-per-billion to parts-per-trillion) of VOCs in soils and vegetation. The technique demonstrates good sensitivity, good recoveries of internal standards and surrogate compounds, good performance, and minimal waste. A case study involving application of this technique as a first-step vadose-zone characterization methodology is presented.     

徐州市人工侧柏林的群落结构及物种多样性分析

以徐州周围山地人工侧柏林为研究对象,在全面勘察的基础上,建立了10块具有代表性的调查样地.通过对群落的生境条件、种类组成和结构等的调查,详细分析了徐州市现有侧柏林的群落结构和物种多样性.分析结果显示,徐州周围山地现有人工侧柏林群落结构简单,物种丰富度和多样性较低,生长更新缓慢.建议引种朴树、臭椿、黄连木、三角槭、梧桐、女贞等树种,以改造林相,促进地带性植被的恢复.     

FY-3C VIRR和Terra MODIS NDVI产品在湘赣地区的一致性

卫星遥感是监测大范围植被动态变化最有效的手段。随着中国遥感技术的发展,国产风云卫星也逐渐应用于植被变化研究,但有关国产风云卫星刻画植被动态变化表现方面仍不明晰。比较了国产风云卫星(FY-3C VIRR)和美国Terra卫星(MODIS)的归一化植被指数(normalized difference vegetation index, NDVI)产品在湖南省和江西省的时空一致性。结果表明：(1)两种卫星NDVI产品的空间分布与年、季、月的变化特征在湘赣地区有较好的一致性,江西省NDVI整体高于湖南省;(2)FY-3C和MODIS年均NDVI都呈现出2018年高于2017年和2019年的情况,基于MODIS的湘赣地区三年的年均NDVI(0.58)高出FY-3C(0.36)约60%;(3)FY-3C NDVI在各季节都整体低于MODIS NDVI,其中冬季差异最大,基于MODIS NDVI均值(0.42)约是FY-3C(0.21)的2倍,其余季节MODIS高出FY-3C约50%;(4)FY-3C NDVI与MODIS NDVI月变化趋势基本一致,二者年最大NDVI差异变化不大且较为稳定,年最小...     

基于遥感的承德围场县植被动态变化监测研究

以承德市围场县为例,探讨了利用遥感技术从Landsat-TM图像中监测植被动态变化的方法．该方法首先对1987年的Landsat-TM图像进行几何校正,并将1999年的Landsat-TM图像与其配准．先从1987年Landsat-TM图像中提取植被指数,再对1987年的植被指数图进行非监督分类,得到1987植被分布图．对1999年的Landsat-TM进行非监督分类,得到1999年的植被分布图．最后,对1987年和1999年的植被分布结构图应用ARCVIEW进行叠合分析,求出植被的变化．该研究表明,此法可以简单有效地将植被的动态变化信息予以监测,得出围场县1999年与1987年相比植被增加987．7Km^2的结论．     

2017年至2019年海北州植被覆盖度时空动态变化分析研究

本文旨在对2017年至2019年海北州的植被覆盖度变化进行分析,获得其相关的时空变化规律。基于2017年至2019年生长季多时相的GF-1 WFV遥感影像,提取植被覆盖度。为了分析不同覆盖度等级的植被的时空变化,本文将植被覆盖度分为全植被、高植被、中植被、低植被和无植被五个不同等级,并在每个等级内结合DEM数据进一步划分为高山、中山、低山进行分析。研究结果表明：(1)对于植被空间分布特点而言,相对于全植被、高植被、中植被和低植被,无植被的面积占比比较少;(2)在空间分布上,针对不同的海拔高度而言,中山区的植被覆盖度较高,低山区次之,高山区的植被覆盖度最少;(3)从年际变化的角度来看,试验区在2017至2018年和2018至2019年期间,均会出现全植被和高植被相互转化的趋势;(4)从同一年度的生长季的分析发现,试验区内的植被覆盖度在6月至8月呈现上升趋势,在8月至9月呈现下降趋势,相对于其他等级,全植被的变化更加符合该趋势。通过本研究,可为掌握海北州植被覆盖度的时空动态变化规律提供支持。     

基于高光谱成像技术的油菜叶片SPAD值检测

以油菜叶片为研究对象,利用高光谱成像技术,成功建立了叶绿素相对值SPAD值的预测模型。共采集了160个油菜叶片样本在380～1030 nm范围内的高光谱图像。选择500～900 nm之间的平均光谱作为油菜叶片样本的光谱。利用蒙特卡罗最小二乘法(monte carlo partial least squares, MC-PLS)剔除了13个异常样本,基于剩余的147个样本光谱数据与SPAD测量值进行分析,采用了不同的方法建立了多种预测模型,包括：全光谱的偏最小二乘法(partial least squares, PLS)模型,连续投影算法(successive projections algorithm, SPA)选择特征波长的PLS预测模型,“红边”位置(λ_red)的简单经验估测模型,三种植被指数R₇₁₀/R₇₆₀,(R₇₅₀-R₇₀₅)/(R₇₅₀-R₇₀₅)和R₈₆₀/(R₅₅₀*R₇₀₈)分别建立的简单经验估测模型,以及基于这三种植被指数的PLS预测模型。建模结果显示,全光谱的PLS模型预测效果最为精确,其预测相关系数r_p为0.833 9,预测均方根误差RMSEP为1.52。而使用SPA算法选出的8个特征波长所建立的PLS模型其预测结果可达到与全光谱的PLS模型非常接近的水平,而且在保证一定精度的条件下减少了大量运算,节省了运算时间,大幅提高了建模的速度。而基于红边位置和选择的三种植被指数而建立的简单经验估计模型其预测结果虽与基于全光谱的PLS预测模型有一定差距,但模型简单、运算量小,适合用于对精度要求不高的场合,对后续的便携仪器设备开发有一定的指导作用。     

江西省五河治理防洪工程（赣江干支流及渌水）河岸带植被调查研究

对江西省五河治理防洪工程（赣江千支流及渌水）进行了河岸带植被调查研究.调查研究表明工程河岸带自然植被共有4个植被型组,8种植被型,51个群系.根据组成植被的区系成分、地带性分布规律,论述了工程河岸带植物区系特点及植被的分布特征,即植物区系呈现隐域性和过渡性特征,植被分布存在一定差异.通过对工程河岸带植被现状的基础性调查,为工程生态环境保护及生态建设提供了一定的科学依据和参考.     

Vegetation effects on mean daily maximum and minimum surface air temperatures over China

Changes in the daily maximum (Tmax) and minimum (Tmin) surface air temperatures and the associated temperature extremes have severe consequences on human society and the natural environment. In this study, we assess vegetation effects on mean Tmax and Tmin over China by computing a vegetation feedback parameter using the satellite-sensed Normalized Difference Vegetation Index (NDVI) and observed temperatures for the period 1982–2002. In all seasons, vegetation exerts a much stronger forcing on Tmax than on Tmin, and thus has a substantial effect on the diurnal temperature range (DTR) over China. Significant positive feedbacks on Tmax and the DTR occupy many areas of China with the feedback parameters exceeding 1°C (0.1 NDVI)–1, while significant negative effects only appear over the summertime climatic and ecological transition zone of northern China and some other isolated areas. Also, the vegetation feedbacks are found to vary with season. In areas where significant feedbacks occur, vegetation contributes to typically 10%–30% of the total variances in Tmax, Tmin, and the DTR. These findings suggest that vegetation memory offers the potential for improving monthly-to-seasonal forecasting of Tmax and Tmin, and the associated temperature extremes over China. Meanwhile, the limitations and uncertainties of the study should be recognized.     

安徽省山地丘陵区水土流失原因与防治措施探讨

安徽省山丘区水土流失严重。其影响因素是自然因素(地貌、降水、植被、岩性)和人为因素的综合作用。防治措施包括生物措施、生产措施、工程措施和生态措施。