遥感数字图像的无缝镶嵌

在遥感图像的应用中,当研究区处于几幅图像的交界处或研究区较大需多幅图像才能覆盖时,常常需要把覆盖研究区的那些图像进行配准并把这些图像镶嵌起来,才能更好地统一处理、解译分析和研究.以航空像片为例,利用图像处理软件ERMAPPER 6.2对图像进行数字镶嵌并作无缝接边处理.结果表明:这样,大大改善了镶嵌后图像的质量,解决了手工镶嵌图像中接缝偏移、色调不均匀、地质界线延伸、影像错位等许多问题 (大幅图像尤其明显),为后期的图像处理创造良好的基础.目前出现的米级高分辨率的卫星图像同本次采用的航空像片在波段和分辨率上具有相似性,因此本研究对这些高分辨率卫星图像的镶嵌同样适用.     

Comparison of image and rapid field assessments of riparian zone condition in Australian tropical savannas

Suitable methods for measuring and monitoring the condition of riparian environments are being investigated by government agencies responsible for maintaining these environments in Australia. The objective of this work was to compare two riparian condition assessment approaches, the Tropical Rapid Appraisal of Riparian Condition (TRARC) method developed for rapid on-ground assessment of the environmental condition of savanna riparian zones and an image based riparian condition monitoring scheme. Measurements derived from these two approaches were compared and correlated. The sample representativeness of the TRARC method was evaluated and the cost-effectiveness and suitability for multi-temporal analysis of the two approaches were assessed. Two high spatial resolution multi-spectral QuickBird satellite images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map indicators of riparian zone condition including percentage canopy cover, organic litter on the ground, canopy continuity, tree clearing, bank stability, and flood damage. Spectral vegetation indices, image segmentation, and supervised classification were used to produce riparian health indicator maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based estimates of riparian health indicators. Covering approximately 3% of the study area, the sample mean of the TRARC estimates of individual indicators of riparian zone condition were in most cases within 20% of the global mean derived from the whole imaged riparian area. The cost-effectiveness of the image based approach was compared to that of the ground based TRARC method. Results showed that the TRARC method was more cost-effective at spatial scales from 1 km to 200 km of river in relatively homogeneous riparian zones along rivers with only one channel, while image based assessment becomes more feasible at regional scales (200–2000 km of river). A change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method is less suited for multi-temporal analysis due to the ranked data format, which inhibits precise detection of change. However, results from both methods were considered to complement each other for single date assessment of riparian zones if used at appropriate spatial scales.     

荒漠化程度评价高光谱遥感信息模型

本文用国产高光谱分辨率成像光谱仪系统数据对荒漠化评价建立定量化遥感信息模型。对荒漠化评价因子中的主要定量因子 (植被盖度、生物量和土壤含水率 )进行了定量反演 ;对难于进行定量计算的评价指标 ,先通过目视解译获得各因子的编码图 ,分别进行影像化后参加荒漠化程度评价遥感信息模型计算。通过每个像元都可获取全部评价因子的指标值 ,在现有的荒漠化评价方法的基础上 ,建立以像元为单位的荒漠化程度评价的定量化遥感信息模型并输出荒漠化程度分布图。结果表明 ,用高光谱数据定量反演荒漠化地区植被生物量、盖度和土壤含水率是比较可靠的。当反演区域内灌木和草地同时存在时多项式模型的精度要明显高于线性模型 ;当植被类型单一时 ,模型即为较高精度的线性模型 ,但模型的应用地域范围受到限制 ,只能分块进行计算。因此 ,在只有灌木和草地的区域用多项式模型反演会提高效率。土壤含水量的反演方法适合于地形平坦、植被比较稀疏的条件。但研究发现 ,基于土壤热惯量的含水量模型具有一定的抗植被干扰能力。荒漠化程度评价的遥感信息模型的精度主要取决于现有荒漠化评价的方法 (即评价指标是否科学合理、专家给定的权重和等级标准是否客观 )以及各指标数据的获取精度     

园林树木遮荫功效研究进展

摘要：卫星遥感是现阶段测绘领域应用较为成熟的技术,然而在农林业病虫害监测预警方面使用较为迟缓,特别是针对省级管理机构缺乏监管技术和预警能力,本研究探索了利用卫星遥感技术开展异常变色林木监测的应用实践,以服务于区域松材线虫病防控的技术指导和督查。经过3年的应用表明,高空间分辨率卫星遥感技术具有客观、科学和实时的优势,能够为上级管理机构提供决策依据。     

基于热平衡法检测植物茎流传感器的标定

植物茎杆的茎流量是植物重要的生理信息之一,该文主要是对基于热平衡法的植物茎流传感器进行标定试验的研究,通过标定试验,测试了茎流检测装置的性能。试验结果表明,计算出传感器输出值与茎流量有很高的决定系数R2=0.96～0.97,分辨率为1×10-3 g/min,精度为±3%。因此参照标定试验,可以较准确地获取植株茎流速率,进而可以反映出植物的蒸腾及需水状态信息,并据此可以为植物生长环境的调控、节水灌溉等提供有效的监测工具。     

几种酚类多组份混合物的自模式曲线分辨红外光度法研究

提出低维空间多次寻优简化程序的方法，对加权函数等值图的研究表明几乎所有纯光谱点附近都存在极小值点，对ｏ－，ｍ－，ｐ－氨基酚，２，６－３，４－３，５－二甲酚等多组份高相似度体系分辨的平均贴近度均达０．９９８以上，且分辨快速。     

A Gis-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.)

A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position (rather than elevation) change drastically at the fine scale and strongly influence many ecological functions. Elevational contours, soil series mapping units, and plot locations were digitized for the Vinton Furnace Experimental Forest in southeastern Ohio and gridded to 7.5-m cells for GIS modeling. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and water-holding capacity of the soil) were used to create the IMI, which was then statistically analyzed with site-index values and composition data for plots. On the basis of IMI values for forest land harvested in the past 30 years, we estimated oak site index and the percentage composition of two major species groups in the region: oak (Quercus spp.), and yellow poplar (Liriodendron tulipifera) plus black cherry (Prunus serotina). The derived statistical relationships were then applied in the GIS to create maps of site index and composition, and verified with independent data. The maps show the oaks will dominate on dry, ridge top positions (i.e., low site index), while the yellow poplar and black cherry will predominate on mesic sites. Digital elevation models with coarser resolution (1:24K, 1:100K, 1:250K) also were tested in the same manner. We had generally good success for 1:24K, moderate success for 1:100K, but no success for 1:250K data. This simple and portable approach has the advantage of using readily available GIS information which is time-invariant and requires no fieldwork. The IMI can be used to better manage forest resources where moisture is limiting and to predict how the resource will change under various forms of ecosystem management.     

APPLICATION OF THE PIN-HOLE COLLIMATOR IN SMALL ANIMAL NUCLEAR SCINTIGRAPHY: A REVIEW

The pin-hole collimator is used to improve spatial resolution and magnify areas of interest. The pin-hole collimator has many applications in small animal veterinary scintigraphy. The principles of image formation for the pin-hole and parallel hole collimators are reviewed. The effects of distance on resolution and sensitivity are presented for the pin-hole and parallel hole collimators. Specific application of the pin-hole and parallel hole collimators. Specific application of the pin-hole collimator in veternary scintigraphy are discussed.     

黑河流域ASTER与MODIS融合生成高分辨率地表温度的验证

融合多源遥感数据生成高时空分辨率数据具有重要的应用价值。为了解决高空间分辨率数据重访周期长及云雨天气带来的数据短缺问题,该文基于增强自适应的遥感图像时空融合方法(enhanced spatial and temporal adaptive reflectance fusion model,ESTARFM),使用多时相MODIS数据提供地物时间变化信息,结合ASTER影像提供的空间细节信息,选择多波段数据(可见光近红外数据和地表温度数据)共同作为输入变量融合生成高时空地表温度。融合结果分别与地表红外辐射计观测温度和ASTER温度产品进行了验证。验证结果表明:基于ESTARFM方法降尺度地表温度影像清晰,融合结果与地表红外辐射计观测温度呈显著的线性正相关关系,相关系数均高于为0.71,预测得到的地表温度与真实测得的数据的平均绝对偏差均低于2.00 K,均方根误差均低于2.60 K。与ASTER地表温度产品的验证中,整体验证结果的R2均在0.95以上。此外,ESTARFM方法在各个地类中的融合效果较好,均表现出非植被区域的相关性高于植被和水体,尤其在2012年8月27日非植被的R2达到0.91。     

气象要素时间分辨率对参考作物蒸散估算的影响

参考作物蒸散(reference evapotranspiration,ET0)的准确估算是农业水资源合理利用的重要环节。为了明确气象要素不同时间分辨率对参考作物蒸散估算的影响,该文基于寿县国家气候观象台2007-2013年观测资料,将1min时间分辨率数据平均值作为真实值,分析了10、20、30、40、60 min、4次/d(02:00、08:00、14:00、20:00)和3次/d(08:00、14:00、20:00)这7种不同时间分辨率对逐日气温、风速、太阳辐射、相对湿度和日、月及年参考作物蒸散(ET0)估算的误差情况。结果表明:ET0和气象要素的误差整体上随时间分辨率降低而增大。4个气象因子中,日平均风速估算受时间分辨率变化的影响最显著,误差最大;其次是太阳辐射。逐日ET0估算在7种时间分辨率的平均绝对相对误差(mean absolute relative error,MAPE)依次为0.53%、1.01%、1.38%、1.72%、2.46%、4.72%和6.14%,表明10至60min时间分辨率的估算效果相较3次/d和4次/d有明显改善。10至40 min的绝对误差超过95%都在-0.20~0.20 mm/d区间内,误差较小且集中度高;太阳辐射时间分辨率变化对ET0估算误差贡献最大,其次是风速,这主要是由于两个要素本身对分辨率较敏感且分别是ET0辐射项和动力项的主要组成因子。时间分辨率的变化对累计后长时间尺度ET0的影响较小,月和年ET0的误差明显小于逐日ET0,月ET0在7种时间分辨率的MAPE值依次为0.13%、0.21%、0.27%、0.40%、0.50%、1.18%和1.48%;各年ET0相对误差(relative error,PE)的绝对值多数均小于0.50%。