Using viewpoints to define domain requirements

Although requirements reuse has many potential benefits, a lack of accepted methodology for sorting through a domain's myriad requirement specifications makes the task daunting. The authors' VODRD (Viewpoint Oriented Domain Requirements Definition) method relies on stakeholder viewpoints to organize user requirements. They describe their method and its application in a mission planning system for the European Space Agency     

Estimating spatio-temporal patterns of agricultural productivity in fragmented landscapes using AVHRR NDVI time series

The characteristics of Normalized Difference Vegetation Index (NDVI) time series can be disaggregated into a set of quantitative metrics that may be used to derive information about vegetation phenology and land cover. In this paper, we examine the patterns observed in metrics calculated for a time series of 8 years over the southwest of Western Australia—an important crop and animal production area of Australia. Four analytical approaches were used; calculation of temporal mean and standard deviation layers for selected metrics showing significant spatial variability; classification based on temporal and spatial patterns of key NDVI metrics; metrics were analyzed for eight areas typical of climatic and production systems across the agricultural zone; and relationships between total production and productivity measured by dry sheep equivalents were developed with time integrated NDVI (TINDVI). Two metrics showed clear spatial patterns; the season duration based on the smooth curve produced seven zones based on increasing length of growing season; and TINDVI provided a set of classes characterized by differences in overall magnitude of response, and differences in response in particular years. Frequency histograms of TINDVI could be grouped on the basis of a simple shape classification: tall and narrow with high, medium or low mean indicating most land is responsive agricultural cover with uniform seasonal conditions; broad and short indicating that land is of mixed cover type or seasonal conditions are not spatially uniform. TINDVI showed a relationship to agricultural productivity that is dependent on the extent to which crop or total agricultural production was directly reduced by rainfall deficiency. TINDVI proved most sensitive to crop productivity for Statistical Local Areas (SLAs) having rainfall less than 600 mm, and in years when rainfall and crop production were highly correlated. It is concluded that metrics from standardized NDVI time series could be routinely and transparently used for retrospective assessment of seasonal conditions and changes in vegetation responses and cover.     

Using soft computing to define standards of care in glaucoma monitoring

A fuzzy knowledge base encapsulating core expert rules for glaucoma follow up is developed and subsequently refined into a standard of care by reconciling several expert opinions. The Learning from Examples (LFE) [1] technique is used in addition to expert interviews to generate fuzzy rules from numerical data, and soft competition defines a fuzzy consensus metrics for the expert opinions. Web-based extension of this system into a comprehensive set of e-Health services for the glaucoma community enables, besides wide accessibility of the expert knowledge, continuous improvement of the core rule set (standard of care) with the perspectives of several experts.This work is funded under Collaborative Health Research Project Grant by the National Science and Engineering Research Council (NSERC) of Canada. We gratefully acknowledge the contributions of TransferTech GmbH Germany(www.Transfertech.de) with their soft computing software suite as well as their valuable insights in solving the implementation challenges we are faced with constantly.     

Using pyramids to define local thresholds for blob detection

A method of detecting blobs in images is described. The method involves building a succession of lower resolution images and looking for spots in these images. A spot in a low resolution image corresponds to a distinguished compact region in a known position in the original image. Further, it is possible to calculate thresholds in the low resolution image, using very simple methods, and to apply those thresholds to the region of the original image corresponding to the spot. Examples are shown in which variations of the technique are applied to several images.     

Influence of heterogeneous landscapes on computed green-up dates based on daily AVHRR NDVI observations

The main objective of the current paper is to evaluate and explain differences between computed green-up dates of vegetated land surface derived from satellite observations and budburst dates from ground observational networks. Landscapes dominated by deciduous broad-leaved trees in Germany are analysed. While ground observations generally record the onset of bud break, remote sensing refers to a detectable change of surface reflectance, which accounts for the unfolding of the majority of the leaves. The satellite detects, even in a homogeneous stand, two signals: the green-up of the understorey and, shortly after, the green-up of the canopy (overstorey). Results of comparisons indicate an earlier, although not consistently, satellite-derived green-up than bud break derived from ground observations.We hypothesise that this is due to heterogeneous ground cover and a detection of the greening of non-tree vegetation by the satellite. This hypothesis is tested by analysing the difference between satellite-derived green-up dates (d_GU) and budburst observed on the ground (d_BB) in function of the proportion of non-deciduous-forest (ndf) land use types in satellite scenes. The satellite data (a daily 1-km resolution AVHRR product) are analysed with progressively more restricted selection criteria regarding the land surface elements. The two sets of observations are compared using Gaussian Mixture Models to evaluate the statistical properties of the probability density functions (pdf) as produced by the two sets rather than comparisons of geographically coincident data. It is shown that a heterogeneous vegetation cover is likely to be the main factor determining the difference between the computed green-up date and date of budburst of the dominating tree species.     

利用计算方法识别定义内含子保留的基因组特征

超过90%的人基因都存在选择性剪接。正确识别不同的选择性剪接模式对深刻理解基因剪接调控机制具有重要意义。内含子保留是一种较为常见的基因剪接模式。从基因组序列本身出发, 利用计算方法识别定义内含子保留的各种基因组特征,抽取统计意义上显著差异的特征,利用三种分类方法（SVM,NN,NB）对这些基因组特征进行了分类预测验证实验,保留内含子的平均预测精度达到70%,整体平均精度达到90%,取得了良好效果。研究方法也可应用于其他基因剪接模式的研究。     

Improving classification of woodland types using modified prior probabilities and Gaussian mixed model in mountainous landscapes

A modified maximum-likelihood (ML) classifier was applied to increase the accuracy of land-cover classification over a complex mountain landscape. The traditional ML classifier is a robust parametric approach in remote-sensing image classification. However, it is difficult to improve classification accuracy when using the traditional ML classifier in complex landscapes such as mountainous regions. In this study, we demonstrated a modified ML classifier that uses the non-equal prior probabilities derived from digital elevation model (DEM) ancillary data and a Gaussian mixed model (GMM) to delineate land-cover types within forest stands. We designed and compared four experiments using Landsat Thematic Mapper (TM) images covering the Culai Hill region of the eastern territory of China: (1) traditional ML classification with equal prior probability, (2) modified ML classification with non-equal prior probability derived from elevation information, (3) Gaussian mixed classifier (GMC) with equal prior probability, and (4) GMC with non-equal prior probability. Overall, the highest accuracy (80.5%) was obtained using the GMC with variable prior probabilities. The GMC with equal prior probabilities and the ML using non-equal prior probabilities yielded maps with accuracy of 74.7% and 78.0%, respectively, values significantly higher than that obtained using the conventional ML method. This implies that use of modified prior probabilities and GMM analysis has considerable potential to increase the accuracy of land-use and land-cover classification using TM imagery for complex landscapes such as the Culai Hill region.     

利用NDVI时间序列识别汶川地震滑坡的分布

利用MODIS NDVI产品,生成了全年16天间隔的NDVI时间序列,再经过Savitzky-Golay滤波后消除了云的影响,可以用来识别滑坡。假设2007年、2008年研究区土地利用状况基本不变,对比2007年和2008年两年的NDVI序列,并结合汶川地震的发生时间,可以识别出研究区发生滑坡的区域分布。结合平武县30mETM目视解译滑坡结果,对自动识别方法进行了验证。结果表明:MODIS识别出的滑坡与目视解译结果匹配较好。在此基础上,将本文方法应用到受汶川地震影响最严重的13个县区级行政区,并综合研究区坡度信息,识别出了汶川重灾区滑坡分布概图。     

利用NOAANDVI数据集分析中国植被绿波推移规律

利用ＮＯＡＡＡＶＨＲＲ时间序列数据集进行中国植被胡季相变化的规律分析。研究结果表明,植被绿波在一年中沿纬和经度变化有很大差异,并有一定的规律。在同一经度,绿波随着季变化由南向北推进。在同一纬度绿波的强度与一年的降雨量有密切关第,绿被指数由东向西逐渐减小。     

利用NOAA NDVI数据集分析中国植被绿波推移规律

利用NOAA AVHRR时间序列数据集进行中国植被绿波随季相变化的规律分析.研究结果表明,植被绿波在一年中沿纬和经度变化有很大差异,并有一定的规律.在同一经度,绿波随着季相变化由南向北推进.在同一纬度绿波的强度与一年的降雨量有密切关系,绿被指数由东向西逐渐减小.从每月绿度等级图宏观分析表明,夏季植被绿波向北推移可占全国陆地70%以上的面积;而冬季褐波向南推移也覆盖了全国陆地70%以上的面积.     

Using multiple image endmember spectral mixture analysis to study chaparral regrowth in southern California

This research tested the ability of a multiple endmember (EM) spectral mixture analysis (SMA) approach, applied to multi-temporal Landsat Thematic Mapper (TM) data, to produce realistic and meaningful EM fractions for the study of post-fire regrowth in a southern California chaparral landscape. Eight different image EMs were used, two types for each EM class of interest (green vegetation (GV), non-photosynthetic vegetation (NPV), soil, and shade); the best EM combination was selected for each pixel. These EM fractions were validated with fractions derived from 1?m Airborne Data Acquisition and Registration multi-spectral image data. The EM fractions from the two datasets were similar (r=0.873, 0.776, 0.790 for GV, NPV, and soil, respectively). Chaparral stands were delineated using vegetation type, fire history and slope aspect GIS layers. Mean EM fractions were calculated for each stand, and analysis of variance was performed to determine if EM fractions were different for stands of different age. Short-term trajectories of individual stands appeared to exhibit trends consistent with trends reported in the literature. However, only the youngest and oldest stands were consistently significantly different.     

Using bathymetric lidar to define nearshore benthic habitat complexity: Implications for management of reef fish assemblages in Hawaii

Habitat complexity plays a major role in determining the distribution and structure of fish assemblages in the aquatic environment. These locations are critical for ecosystem function and have significant implications for conservation and management. In this study, we evaluated the utility of remotely sensed lidar (light detection and ranging) data for deriving substrate rugosity (a measure of habitat complexity) on a coral reef in Hawaii. We also assessed the potential application of lidar data for examining the relationship between habitat complexity and Hawaiian reef fish assemblage characteristics. Lidar-derived rugosity (4 m grid size) was found to be highly correlated with in-situ rugosity and was concluded to be a viable method for measuring rugosity in analogous coral reef environments. We established that lidar-derived rugosity was a good predictor of fish biomass and demonstrated a strong relationship with several fish assemblage metrics in hard bottom habitat at multiple spatial resolutions. This research demonstrates (i) the efficacy of lidar data to provide substrate rugosity measures at scales commensurate with the resources and their environment (ii) the applicability of lidar-derived rugosity for examining fish–habitat relationships on a coral reef in Hawaii and (iii) the potential of lidar to provide information about the seascape structure that can ultimately be used to prioritize areas for conservation and management.     

Using the NDVI as auxiliary data for rapid quality assessment of rainfall estimates in Africa

Rainfall estimates derived from satellite imagery and global circulation models are frequently used for vegetation monitoring in many areas of Africa because of the shortage of observed rainfall data and the sparse network of meteorological stations. At the same time, this scarce density of rain gauge stations makes the calibration and validation of the modelled data nearly impossible. In this study we propose a methodology for a rapid quality assessment of rainfall estimates that is based on the well-known relationship between rainfall and the Normalized Difference Vegetation Index (NDVI). The results clearly confirm that the NDVI can be used as an indicator of the quality of rainfall estimates at the continental/regional scale and allow a rapid detection of major over- and underestimations of the two rainfall datasets examined for the African continent.     

NDVI response to rainfall in different ecological zones in Jordan

The response of NDVI to rainfall was analyzed using NOAA/AVHRR satellite imagery acquired over a time period of ten growing seasons (1981 to 1992) and rainfall data from 16 weather stations in four ecological zones in Jordan. Results of linear regression analysis showed better response of NDVI to cumulative rainfall than to 10-day rainfall with best correlation in the Mediterranean zone. Significant relationships were found between seasonal rainfall and NDVI range (Δ_NDVI) with better correlations for logarithmic and power relationships than for linear relationship. A strong linear relationship occurred between the annual rainfall and end-of-season NDVI in the Mediterranean zone and weak or no correlation in other zones. The correlations were improved when the rainfall data were averaged, summed and correlated with the average NDVI. More agreement, however, was observed between the maximum NDVI image and rainfall than for the average NDVI image and rainfall. Results also showed that stratification of the data according to soil type and/or land cover would not necessarily improve the correlation. However, stratification of the data according to ecological zone demonstrated obvious differences between the NDVI-rainfall in the different zones.     

Using a cool spot to improve the thermal comfort of glassmakers

Glassmakers monitoring a rolled plate process suffered discomfort from the high temperature environment. This was caused by the radiant heat emitted by the furnaces and associated equipment surrounding the glassmakers' working area, combined with a high air temperature. The glassmakers are responsible for monitoring the glass rolling machine to ensure that the product is manufactured to specification, and to prevent the molten glass sticking to the rollers. This study improved their thermal comfort by the construction of a cool area. They were also brought nearer to the rolling machine. This, with the addition of a cooler environment, improved their monitoring performance. The cool spot was constructed using glass and aluminium radiant heat shields, air curtains and low velocity cooling air.     

Spatiotemporal crop NDVI responses to climatic factors in mainland China

Climate change has caused a great impact on vegetation growth, production and distribution through variations of precipitation, temperature and sunshine. In this study, a categorization of zones for vegetation responses to climatic variability was conducted. Seasonal and annual crop responses to climate change in each region were analysed with multiple linear regression. The results show that the annual impact of climatic factors on crop growth was most significant in lower North China (R² = 0.48) and most insignificant in Northeast China (R² = 0.22). Temperature is the limiting climatic factor for crop growth annually in North China and Northeast China (zones 1–3), (p ≤ 0.05), while sunshine duration plays an important role for crop growth in zones which are more southern (zones 3 ~ 5). Precipitation significantly affects the annual crop growth in Inner Mongolia-Hebei-Shandong zone (zone 2) and Southeast zone (zone 5). Therefore, more attention should be paid to these zones. The spring temperature is the limiting climatic factor for crop growth in all the zones (p ≤ 0.05). Spring warming is helpful for crop growth in mainland China. Different agricultural and administrative measures should be taken in each zone to adapt to future climate change.     

Depicting the Asymmetries of Vegetation Phenology over Northeast China Using Remote Sensing NDVI Dataset

Vegetation phenology is an important ecological indicator for global climate change.Plant greenup phenology in the spring time has been well studied,whereas autumn phenology and its asymmetry with spring phenology still remain unclear.Here,the GIMMS NDVI3g dataset for Northeast China was applied to extract the key phenological parameters during plant growth process,then three phenological asymmetry indices were defined according to the difference between greenup rate and senescence rate(AsyR),growth length in spring and autumn(AsyL),mean vegetation greenness index in spring and autumn(AsyV).First,plant growing curve was fitted with double logistic function and the phenological parameters was calculated.Second,the spatiotemporal pattern of asymmetry indices was explored.The results indicate that the three phenological asymmetry indices show a significant interannual variability and a time cycle of around ten years.The direction of amplitude for AsyV and AsyL was opposite with that of AsyR.Three indices could depict the phenological asymmetries from various perspectives and have a degree of uncertainty.The landscape pattern for AsyV and Asy R is similar.AsyV and AsyR show a capability of distinguishing cropland and natural vegetation cover.AsyL reflects a complex spatial distribution.Phenological asymmetries reveal that coniferous forest and broad-leaved forest present a dominant control of senescence vegetation activities.These natural vegetation commonly show a growth feature of rapid growth in spring and slow decrease in autumn.Cropland exhibits a slowly growing rate in spring and a rapid decrease in autumn.Phenological asymmetry is not significant in grassland area.Phenological asymmetry could enhance our knowledge on ecosystem carbon sink.In a practical way,phenological asymmetry could serve as a useful tools in vegetation type classification,agricultural investigation and plant ecosystem management.