MODIS数据在树种长势监测中的应用

近年来,世界各国日益重视利用“3S”(遥感、地理信息系统和全球定位系统)技术对陆地表面植被进行研究。利用Terra-MODIS数据,分别采用了归一化植被指数(NDVI)、环境植被指数(EVI)、土壤调节植被指数(SAVI)以及比值植被指数(RVI)对实验区典型树种的长势进行了比较研究;同时对实验区典型树种的植被指数的地域变化和时间变化进行了分析,为探讨我国可燃物的时空变化规律打下了基础。     

Comparing measures of urban land use mix

We review a variety of common measures of urban land use mix in order to understand their differences and to identify their strengths and limitations. We then apply these measures to data from a Monte Carlo simulation to ascertain statistical relationships among them, finding that they can be placed into four groups where measures within each group produce highly consistent results: Percentage and Exposure Index; all varieties of the Atkinson Index; Balance, Entropy, and Herfindahl–Hirschman indices; and the Dissimilarity and Gini indices. We find that when analyzing two dimensions of land use, generally both the Balance Index and the Dissimilarity Index should be used, and that the Dissimilarity Index should be tested at multiple scales. We provide a number of other practical recommendations about which mixed use measure to apply given the contextual information available to a researcher or analyst.     

Test-retest repeatability of the Strain Index

Fifteen raters individually, and in five teams of three, evaluated the test-retest repeatability of published data collection and rating methods of the Strain Index by analyzing 61 job video files twice over a 5-month period. Raters estimated average and peak hand forces, measured Duration of Exertion, cycle time, and exertions per job cycle, calculated percent Duration of Exertion and Efforts per Minute, and assigned ratings for five of the six Strain Index task variables. Twelve additional jobs were analyzed to determine Strain Index Score and hazard classification. Intraclass correlation (ICC) coefficients for task variable ratings and accompanying data ranged from 0.66 to 0.95 for both individuals and teams. The Strain Index Score ICC(2,1) for individuals and teams were 0.56 and 0.82, respectively. Intra-rater reliability for the hazard classification was 0.81 for individuals and 0.88 for teams. The results indicate that the Strain Index has good test-retest reliability.     

Reliability of self-administered Work Ability Index questionnaire among Korean workers

Although the Work Ability Index (WAI) has been used in many countries, its reliability is yet to be validated in Korea. In our study, test–retest results of WAI total score, WAI category and seven subscales were compared. The correlation coefficients of WAI total score and subscales 1 and 2 between test and retest were 0.70, 0.80 and 0.63, respectively. The κ values on WAI category, subscales 4, 5, 6 and 7 were 0.52, 0.32, 0.31, 0.48 and 0.85, respectively. The results of our reliability test show that WAI scores of female, younger and private company workers were found to be higher than those of male, older and public company workers, respectively. We conclude that overall test–retest reliability of WAI in Korea is acceptable. Another notable observation from our study is that work ability dimension (subscales 1, 2 and 7) had a higher reliability, whereas health dimension (subscales 3–6) had a lower reliability.     

Integration of Palmer Drought Severity Index and remote sensing data to simulate wetland water surface from 1910 to 2009 in Cottonwood Lake area, North Dakota

Spatiotemporal variations of wetland water in the Prairie Pothole Region are controlled by many factors; two of them are temperature and precipitation that form the basis of the Palmer Drought Severity Index (PDSI). Taking the 196 km² Cottonwood Lake area in North Dakota as our pilot study site, we integrated PDSI, Landsat images, and aerial photography records to simulate monthly water surface. First, we developed a new Wetland Water Area Index (WWAI) from PDSI to predict water surface area. Second, we developed a water allocation model to simulate the spatial distribution of water bodies at a resolution of 30 m. Third, we used an additional procedure to model the small wetlands (less than 0.8 ha) that could not be detected by Landsat. Our results showed that i) WWAI was highly correlated with water area with an R² of 0.90, resulting in a simple regression prediction of monthly water area to capture the intra- and inter-annual water change from 1910 to 2009; ii) the spatial distribution of water bodies modeled from our approach agreed well with the water locations visually identified from the aerial photography records; and iii) the R² between our modeled water bodies (including both large and small wetlands) and those from aerial photography records could be up to 0.83 with a mean average error of 0.64 km² within the study area where the modeled wetland water areas ranged from about 2 to 14 km². These results indicate that our approach holds great potential to simulate major changes in wetland water surface for ecosystem service; however, our products could capture neither the short-term water change caused by intensive rainstorm events nor the wetland change caused by human activities.     

Nesting and Defoliation of Index Expressions for Information Retrieval

In this article, a formalisation of index expressions is presented. Index expressions are more expressive than keywords while maintaining a comprehensible complexity. Index expressions are well-known in Information Retrieval (IR), where they are used for characterising document contents, formulation of user interests, and matching mechanisms. In addition, index expressions have found both practical and theoretical applicability in 2-level hypermedia systems for IR. In these applications, properties of (the structure of) index expressions are heavily relied upon. However, the presupposed mathematical formalisation of index expressions and their properties still lacks. Our formalism is based on the structural notation of index expressions. It is complete in the sense that several notions of subexpressions and defoliation of index expressions are also formalised. Defoliation, which plays an important role in defining properties of index expressions, is provided as a recursively defined operator. Finally, two other representational formalisms for index expressions are compared to ours. Received 9 July 1998 / Revised 20 April 1999 / Accepted in revised form 28 May 1999     

Index preparation and processing

Index preparation is a tedious and time-consuming task. This paper indicates how the indexing process can be automated in a way that is largely independent of a specific typesetting system and independent of the format being used. Fundamental issues related to this process are identified and analysed. Specifically, we develop a framework for placing index commands in the document. In addition, the design of a general-purpose index processor that transforms a raw index into an alphabetized version is described. The resulting system has proved very useful and effective in producing indexes for several books, technical reports and manuals. A comparison of our system with indexing facilities available from a variety of other document preparation environments is given.     

基于P2P端点目录的索引方法APNI

针对在P2P环境中可扩展标记语言的端点目录管理的要求,提出一种APNI索引方法,该索引方法利用素数索引方法(Prime Number Index)并加以改进,借以素数索引表和层次索引表辅助。实验结果表明,APNI查询结果比Prime Number Index更快。     

Exploiting Wikipedia and EuroWordNet to solve Cross-Lingual Question Answering

This paper describes a new advance in solving Cross-Lingual Question Answering (CL-QA) tasks. It is built on three main pillars: (i) the use of several multilingual knowledge resources to reference words between languages (the Inter Lingual Index (ILI) module of EuroWordNet and the multilingual knowledge encoded in Wikipedia); (ii) the consideration of more than only one translation per word in order to search candidate answers; and (iii) the analysis of the question in the original language without any translation process. This novel approach overcomes the errors caused by the common use of Machine Translation (MT) services by CL-QA systems. We also expose some studies and experiments that justify the importance of analyzing whether a Named Entity should be translated or not. Experimental results in bilingual scenarios show that our approach performs better than an MT based CL-QA approach achieving an average improvement of 36.7%.     

Indices for the evaluation of wildfire spread simulations using contemporaneous predictions and observations of burnt area

Methods to objectively evaluate performance are critical for model development. In contrast to recent advances in wildfire simulation, there has been limited attention to evaluating fire model performance. Information to validate fire models is typically limited, commonly to a few perimeter observations at a small number of points in time. We review metrics for comparing two burnt areas at a point in time: observed and predicted. These are compared in an idealised landscape and with a case study evaluating the performance of simulations of an Australian wildfire. We assessed: Shape Deviation Index (SDI), Jaccard's coefficient, F1, Sørensen's Similarity and Area Difference Index (ADI). For decomposing fit into error components (overprediction and underprediction) we assessed the partial indices of SDI and ADI, Precision and Recall. The various metrics were evaluated for their ability to represent error and their suitability for use in model improvement frameworks.     

Predicting Enhanced Vegetation Index (EVI) curves for ecosystem modeling applications

Vegetation indices derived from remote sensing data provide information about the variability in stature, growth and vigor of the vegetation across a region, and have been used to model plant processes. For example, the Enhanced Vegetation Index (EVI) provides a measure of greenness of the vegetation that can be used to predict net primary production. However, ecosystem models relying on remote sensing data for EVI or other vegetation indices are limited by the time series of the satellite data record. Our objective was to develop a statistical model to predict EVI in order to extend the time series for modeling applications. To explain the functional behavior of the seasonal EVI curves, a two-stage multiple regression fitting procedure within a semi-parametric mixed effect (SPME) model framework was used. First, a linear mixed effect (LME) model was fitted to the EVI with climate indexes, crop and irrigation information as predictor variables. Second, Penalized B-splines were used to explain the behavior of the smooth residuals, which result from a smooth model fit to the smooth EVI data curve, in order to describe the uncertainty of the EVI curve. Individual models were fit within individual Major Land Resources Areas (MLRAs). Predicted seasonal EVI, derived from our regression equations, showed a strong agreement with the observed EVI and was able to capture the site by site and year by year variation in the EVI curve. Out-of-sample prediction produced excellent results for a majority of the sites, except for sites without clear seasonal patterns, which may have resulted from cloud contamination and/or snow cover. Therefore, given the appropriate climate, crop, and irrigation information, the proposed approach can be used to predict seasonal EVI curves for extending the time series into the past and future.     

Moving towards efficient decision tree construction

Motivated by the desire to construct compact (in terms of expected length to be traversed to reach a decision) decision trees, we propose a new node splitting measure for decision tree construction. We show that the proposed measure is convex and cumulative and utilize this in the construction of decision trees for classification. Results obtained from several datasets from the UCI repository show that the proposed measure results in decision trees that are more compact with classification accuracy that is comparable to that obtained using popular node splitting measures such as Gain Ratio and the Gini Index.     

基于连续分布方向图的指纹奇异点检测

在指纹连续分布方向图(场)的基础上,对经典的PoincaréIndex计算公式进行了改进,提出了一种新的基于连续分布方向图的指纹奇异点检测算法。由于指纹连续分布方向图过渡平滑、自然,既具有很好的连续性、渐变性和抗噪性,又具有较高的精确度;而改进后的PoincaréIndex不仅能精确表示向量场的旋转角度,而且还能精确表示向量场的旋转方向。所以,该算法能够在像素级水平精确定位指纹奇异点(core point和delta point),精确度达到一个像素。在FVC2000、FVC2002和FVC2004的训练指纹库(Set B)以及笔者采集的AFIS2004指纹库(含4000幅指纹)上的实验结果验证了该算法的有效性。     

Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data

View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or unquantified. We use the ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy) providing spaceborne imaging spectrometer and multiangular data to assess the reflectance anisotropy of broadband as well as recently developed narrowband indices. Multiangular variability of Hemispherical Directional Reflectance Factor (HDRF) is a prime factor determining the indices´ angular response. Two contrasting structural vegetation types, pine forest and meadow, were selected to study the effect of reflectance anisotropy on the angular response. Calculated indices were standardized and statistically evaluated for their varying HDRF. Additionally we employ a coupled radiative transfer model (PROSPECT/FLIGHT) to quantify and substantiate the findings beyond an incidental case study. Nearly all tested indices manifested a prominent anisotropic behaviour. Apart from the conventional broadband greenness indices [e.g. Simple Ratio Index (SRI), Normalized Difference Vegetation Index (NDVI)], light use efficiency and leaf pigment indices [e.g. Structure Insensitive Pigment Index (SIPI), Photochemical Reflectance Index (PRI) and Anthocyanin Reflectance Index (ARI)] did express significant different angular responses depending on the vegetation type. Following the quantification of the impact, we conclude that the angular-dependent fraction of non-photosynthetic material is of critical importance shaping the angular signature of these VIs. This work highlights the influence of viewing geometry and surface reflectance anisotropy, particularly when using light use efficiency and leaf pigment indices.     

Impacts of hydrologic soil properties on drought detection with MODIS thermal data

Remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), a climatic water budget model, and the STATSGO database were used within a GIS environment to determine the influences of hydrologic soil properties on soil moisture and thermal emission in western-central Kansas for a dry year, 2000. Two important variables, water-holding capacity (WHC) and hydrologic soil group (HSG), were controlled in our water budget experiment to evaluate their impacts on soil moisture content (SMC) changes throughout the period. Results showed that HSG affected drought detection and occurrence very little, but WHC variations explained most local variations of soil moisture content. As a strong indicator of relative soil moisture deficit, the Standardized Thermal Index (STI) patterns were also influenced by WHC. Generally, the earlier the soil moisture content drops below 40%, the earlier the STI reaches a threshold value of 0.2 or higher. Vegetation responses to thermal detection lagged behind the STI by up to 8 weeks, which was computed by comparing the STI and Normalized Difference Vegetation Index (NDVI) deviation from a 10-year mean. The spatial pattern of lag-times was not apparent, but lag-times were correlated with a WHC component.     

外键列索引的效率分析

索引是与表或视图关联的磁盘上结构,可以加快从表或视图中检索行的速度。高效的索引对于获得良好的数据库和应用程序性能极为重要。参照完整性是关系数据库管理系统必须满足的完整性约束条件,可以维护主外键数据的一致性。通过实验分析验证在外键字段上建立索引的必要性。     

Document Similarity Using a Phrase Indexing Graph Model

Document clustering techniques mostly rely on single term analysis of text, such as the vector space model. To better capture the structure of documents, the underlying data model should be able to represent the phrases in the document as well as single terms. We present a novel data model, the Document Index Graph, which indexes Web documents based on phrases rather than on single terms only. The semistructured Web documents help in identifying potential phrases that when matched with other documents indicate strong similarity between the documents. The Document Index Graph captures this information, and finding significant matching phrases between documents becomes easy and efficient with such model. The model is flexible in that it could revert to a compact representation of the vector space model if we choose not to index phrases. However, using phrase indexing yields more accurate document similarity calculations. The similarity between documents is based on both single term weights and matching phrase weights. The combined similarities are used with standard document clustering techniques to test their effect on the clustering quality. Experimental results show that our phrase-based similarity, combined with single-term similarity measures, gives a more accurate measure of document similarity and thus significantly enhances Web document clustering quality.     

Estimating the effect of gypsy moth defoliation using MODIS

The area of North American forests affected by gypsy moth defoliation continues to expand despite efforts to slow the spread. With the increased area of infestation, ecological, environmental and economic concerns about gypsy moth disturbance remain significant, necessitating coordinated, repeatable and comprehensive monitoring of the areas affected. In this study, our primary objective was to estimate the magnitude of defoliation using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for a gypsy moth outbreak that occurred in the US central Appalachian Mountains in 2000 and 2001. We focused on determining the appropriate spectral MODIS indices and temporal compositing method to best monitor the effects of gypsy moth defoliation. We tested MODIS-based Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), and two versions of the Normalized Difference Infrared Index (NDIIb6 and NDIIb7, using the channels centered on 1640 nm and 2130 nm respectively) for their capacity to map defoliation as estimated by ground observations. In addition, we evaluated three temporal resolutions: daily, 8-day and 16-day data. We validated the results through quantitative comparison to Landsat based defoliation estimates and traditional sketch maps. Our MODIS based defoliation estimates based on NDIIb6 and NDIIb7 closely matched Landsat defoliation estimates derived from field data as well as sketch maps. We conclude that daily MODIS data can be used with confidence to monitor insect defoliation on an annual time scale, at least for larger patches (> 0.63 km²). Eight-day and 16-day MODIS composites may be of lesser use due to the ephemeral character of disturbance by the gypsy moth.     

On time series model selection involving many candidate ARMA models

We study how to perform model selection for time series data where millions of candidate ARMA models may be eligible for selection. We propose a feasible computing method based on the Gibbs sampler. By this method model selection is performed through a random sample generation algorithm, and given a model of fixed dimension the parameter estimation is done through the maximum likelihood method. Our method takes into account several computing difficulties encountered in estimating ARMA models. The method is found to have probability of 1 in the limit in selecting the best candidate model under some regularity conditions. We then propose several empirical rules to implement our computing method for applications. Finally, a simulation study and an example on modelling China's Consumer Price Index (CPI) data are presented for purpose of illustration and verification.     

On time series model selection involving many candidate ARMA models

We study how to perform model selection for time series data where millions of candidate ARMA models may be eligible for selection. We propose a feasible computing method based on the Gibbs sampler. By this method model selection is performed through a random sample generation algorithm, and given a model of fixed dimension the parameter estimation is done through the maximum likelihood method. Our method takes into account several computing difficulties encountered in estimating ARMA models. The method is found to have probability of 1 in the limit in selecting the best candidate model under some regularity conditions. We then propose several empirical rules to implement our computing method for applications. Finally, a simulation study and an example on modelling China's Consumer Price Index (CPI) data are presented for purpose of illustration and verification.