Continuous wavelet analysis for the detection of green attack damage due to mountain pine beetle infestation

Mountain pine beetle (Dendroctonus ponderosae Hopkins) is the most destructive insect infesting mature pine forests in North America and has devastated millions of hectares of forest in western Canada. Past studies have demonstrated the use of multispectral imagery for remote identification and mapping of visible or red attack damage in forests. This study aims to detect pre-visual or green attack damage in lodgepole pine needles by means of hyperspectral measurements, particularly via continuous wavelet analysis. Field measurements of lodgepole pine stands were conducted at two sites located northwest of Edmonton, Alberta, Canada. In June and August of 2007, reflectance spectra (350-2500 nm) were collected for 16 pairs of trees. Each of the 16 tree pairs included one control tree (healthy), and one stressed tree (girdled to simulate the effects of beetle infestation). In addition, during the period of June through October 2008, spectra were collected from 15 pairs of control- and beetle-infested trees. Spectra derived from these 31 tree pairs were subjected to a continuous wavelet transform, generating a scalogram that compiles the wavelet power as a function of wavelength location and scale of decomposition. Linear relationships were then explored between the wavelet scalograms and chemical properties or class labels (control and non-control) of the sample populations in order to isolate the most useful distinguishing spectral features that related to infested or girdled trees vs. control trees.A deficit in water content is observed in infested trees while an additional deficit in chlorophyll content is seen for girdled trees. The measurable water deficit of infested and girdled tree samples was detectable from the wavelet analysis of the reflectance spectra providing a novel method for the detection of green attack. The spectral features distinguishing control and infested trees are predominantly located between 950 and 1390 nm from scales 1 to 8. Of those, five features between 1318 to 1322 nm at scale 7 are consistently found in the July and August 2008 datasets. These features are located at longer wavelengths than those investigated in previous studies (below 1100 nm) and provide new insights into the potential remote detection of green attack. Spectral features that distinguish control and girdled trees were mostly observed between 1550 and 2370 nm from scales 1 to 5. The differing response of girdled and infested trees appears to indicate that the girdling process does not provide a perfect simulation of the effects caused by beetle infestation.It remains to be determined if the location of the 1318-1322 nm features, near the edge of a strong atmospheric water absorption band, will be sufficiently separable for use in airborne detection of green attack. A plot comparing needle water content and wavelet power at 1320 nm reveals considerable overlap between data derived from both infested and control samples, though the groups are statistically separable. This obstacle may preclude a high accuracy separation of healthy and infected single individuals, but establishing threshold identification levels may provide an economical, efficient and expeditious method for discriminating between healthy and infested tree populations.     

Impact of orthorectification and spatial sampling on maximum NDVI composite data in mountain regions

Topography and accuracy of image geometric registration significantly affect the quality of satellite data, since pixels are displaced depending on surface elevation and viewing geometry. This effect should be corrected for through the process of accurate image navigation and orthorectification in order to meet the geolocation accuracy for systematic observations specified by the Global Climate Observing System (GCOS) requirements for satellite climate data records. We investigated the impact of orthorectification on the accuracy of maximum Normalized Difference Vegetation Index (NDVI) composite data for a mountain region in north-western Canada at various spatial resolutions (1 km, 4 km, 5 km, and 8 km). Data from AVHRR on board NOAA-11 (1989 and 1990) and NOAA-16 (2001, 2002, and 2003) processed using a system called CAPS (Canadian AVHRR Processing System) for the month of August were considered. Results demonstrate the significant impact of orthorectification on the quality of composite NDVI data in mountainous terrain. Differences between orthorectified and non-orthorectified NDVI composites (ΔNDVI) adopted both large positive and negative values, with the 1% and 99% percentiles of ΔNDVI at 1 km resolution spanning values between − 0.16 < ΔNDVI < 0.09. Differences were generally reduced to smaller numbers for coarser resolution data, but systematic positive biases for non-orthorectified composites were obtained at all spatial resolutions, ranging from 0.02 (1 km) to 0.004 (8 km). Analyzing the power spectra of maximum NDVI composites at 1 km resolution, large differences between orthorectified and non-orthorectified AVHRR data were identified at spatial scales between 4 km and 10 km. Validation of NOAA-16 AVHRR NDVI with MODIS NDVI composites revealed higher correlation coefficients (by up to 0.1) for orthorectified composites relative to the non-orthorectified case. Uncertainties due to the AVHRR Global Area Coverage (GAC) sampling scheme introduce an average positive bias of 0.02 ± 0.03 at maximum NDVI composite level that translates into an average relative bias of 10.6% ± 19.1 for sparsely vegetated mountain regions. This can at least partially explain the systematic average positive biases we observed relative to our results in AVHRR GAC-based composites from the Global Inventory Modeling and Mapping Studies (GIMMS) and Polar Pathfinder (PPF) datasets (0.19 and 0.05, respectively). With regard to the generation of AVHRR long-term climate data records, results suggest that orthorectification should be an integral part of AVHRR pre-processing, since neglecting the terrain displacement effect may lead to important biases and additional noise in time series at various spatial scales.     

超高密度电法和激电法在河北某地找水实例分析

通过介绍由澳大利亚引进的全新超高密度电法反演系统对河北省行唐县几个村庄的地下水勘查实例,对新兴的超高密度电法与传统的大功率激电测深法相结合的方式在太行山灰岩地区基岩水勘查的应用进行了可行性分析。高密度电法工作效率高、探测速度快,而大功率激电测深法探测精度高。二者有机结合,既可以提高工作效率、又可以互相印证,是一种很好的综合物探地下水勘查模式。通过平行布置电阻率测量剖面的工作方式很好的把控了破碎构造的走向,圈定了富水异常区,并最终取得了很好的勘探效果,实践证明该电法组合的勘探方式在同类地区中进行地下水勘查是很有推广价值的。     

阿拉山口供水工程运行监控 管理系统研究

本文介绍了阿拉山口供水工程运行监控管理系统的建设。该系统通过监测数据判断系统运行状况及对设备的控制,完成了工程运行过程的自动化。在硬件上,采用了中控室、分控室、监测节点的分级结构,使用光纤和无线模式进行数据传输,以采集压力计、水位计、流量计、测沙仪、阀门开度等传感器数据;在软件上,开发了服务器端、客户端的监控程序,实现了数据采集传输、设备控制和信息报警等功能。系统已应用于阿拉山口供水工程实际的运行管理工作中。     

龙门山盆-山耦合带遥感地质解译

随着晚三叠世龙门山造山带的崛起,四川前陆盆地开始形成。强烈的喜马拉雅运动使龙门山进一步崛起,造就了龙门山与四川前陆盆地的盆-山耦合景观。结合遥感解译与实地调查,发现江油-灌县断裂带控制着前陆盆地的边缘,是一个构造形迹较为复杂的盆-山耦合断裂,由二王庙断裂和香水断裂组成,其主体断裂为二王庙断裂。而在四川前陆盆地西缘的香水断裂是半隐伏乃至全隐伏的盆地基底断裂构造,断裂在江油南西裸露地表且控制盆地边界,但在江油北东到广元则处于隐伏状态。香水断裂对盆地边缘早-中侏罗世盆地沉积相和晚侏罗世-早白垩世所谓＂城墙岩系＂巨厚磨拉石建造的形成均具有较强的控制性。     

河北太行山区泥石流启动的水岩相互作用

泥石流作为一种固-液混合而形成的地质灾害,其启动过程中必然存在着水与岩土体之间的相互作用。根据对太行山区泥石流形成的地形地貌、降雨、物源和人类活动特征等影响因素的分析,确定太行山区泥石流的崩滑动力和洪水动力两种启动类型。在此基础上,从水-岩系统耦合作用的角度,研究了太行山区泥石流形成过程中,洪水与固体颗粒之间彼此促进、相互制约的水岩化学作用、水岩物理作用和水岩力学作用,阐明了水岩相互作用对泥石流初始形成的促进机制,从而为泥石流启动预测预报体系的建立提供理论支撑。     

试论武当山旅游资源之道教文化

武当山素有“天下第一仙山”之誉,武当道教更是驰名宇内,其所存宗教建筑规模宏大,古代文物精美绝伦,道学思想精深卓著,同时武当武学压盏环宇,武当道医神玄超然。然而自清末至今,武当宫观未得到大规模的修复,其神髓没有得到发掘。     

利用GIS方法建立山区温度分布模型

提出了一种在气象站点实测数据基础上，利用ＧＩＳ技术建立山区温度分布模型的方法。通过建立数字地形模型（ＤＴＭ），获取影响山地温度分布的地形要素，并结合太阳年运动轨迹求出任一地点的天文太阳辐射值，同时考虑海拔高度、地理位置等影响气温的因素以及站点实测数据建立山区温度分布模型。     

自然山区大气景观模拟显示方法初探

提出了一个模拟大气、云雾等自然环境的照明模型，对视线距离较大，视野开阔的自然景物造型，如山体造型，更具有真实感效果，可获得模拟云、雾等天气特征的三维地形风景图。实验效果令人满意，并具有简单实用之特点。     

地热水医疗保健作用评价

在查阅大量文献的基础上,分析了地热水中各种有益组分的医疗保健作用机理;以河南省出露温度最高的洛阳九龙山疗养院温泉为典型例子,根据水质检测结果,按照《医疗矿泉水水质标准》(GB11615-89)对其医疗作用进行了评价;结果表明,该处地热水中多种组分具有医疗价值质量浓度或达到命名医疗热矿水名称的质量浓度,具有较高的医疗价值和保健作用.