干旱是全球范围内的灾害。协同利用遥感数据和气象数据来研究植被对干旱的响应并进行干旱评估和监测，对于减少干旱损失，制定决策和农业管理都有重大的现实意义。 / 本研究提出了两种新的处理多时相遥感数据的方法：一种是基于无云影像频域分析的植被时间序列获取；另一种是基于时间序列主成份分析的MODIS混合象元信息提取。这两种方法可以分别用于时间序列数据的预处理和估算生态干扰发生时陆地植被覆盖的变化。 / 本研究开展了地面试验，用ASD地面高光谱仪和SPAD502叶绿素仪测定了在控制梯度干旱下的玉米叶片光谱和叶绿素含量的动态变化。研究表明：随着干旱的加剧, 叶片光谱反射率也会相应增加。统计分析表明叶片510 nm和690 nm处的反射率可以用于玉米干旱的预警。本研究基于不同干旱程度和玉米不同发育时期的光谱数据，全面探讨了光谱变量和光谱指数对干旱胁迫下叶绿素变化的敏感性。 / 本研究探讨了中国的作物长势与气象因子的关系，首先基于温度，降水，光照和NDVI数据将中国分为7个研究区，然后基于多元线性回归提取了每个研究区在19822006年间限制作物生长的关键气候因子。研究表明在春季和夏季，温度，降水, 光照对作物NDVI的影响（R²>=0.35）要大于秋季和冬季 (R²<=0.14). 在分区1-3（华北，东北）中，全年作物NDVI呈现显著增加的趋势(p<0.1)，而在华南地区则没有明显的趋势。 / 在西南干旱中，两类遥感干旱指数（基于空间特征的TVDI和基于时间序列的VHI）与气象干旱指数SPI进行了比较。本研究进行了气象干旱指数和遥感干旱指数的时空一致性分析。TVDI受制于特定研究区提取的‘干边’和‘湿边’，而VHI则受时间序列数据噪声的影响。SPI36和遥感干旱指数存在相对稳定的关系，这与研究区的主要的植被类型是森林有关。 / 本研究用模型碳参数结合遥感数据估算了干旱引起的森林生态系统碳存储的变化。估算的结果与遥感获取的植被净光合速率的变化进行了比较，两者的一致性较高（r=0.32 p<0.001）。研究表明卫星遥感数据结合生态模型可以有效反演在全球变化背景下植被参数的变化。 / Studies on monitoring vegetative responses to drought by integrating remote sensing and meteorological data sets are of great practical meaning in mitigating losses, making decisions and managing agriculture. / A field experiment was conducted to test the hyperspectral sensitivity of corn responses to drought in controlled gradients. Statistical analysis shows that leaf reflectance at 510 nm and 690 nm under artificial illumination mode can indicate early drought significantly. The sensitivity of different hyperspectral indices and position-based variables on vegetative chlorophyll change under drought was also comprehensively compared. / China was divided into 7 regions based on the monthly anomaly of NDVI, precipitation, temperature and sunshine duration from 1982 to 2006 with hierarchical clustering. The impact of precipitation, temperature and sunshine duration on crop NDVI in spring and summer (average R² >=0.35) is higher than that in autumn and winter (average R² < =0.14). The full-year crop NDVI trend for region 1-3 increases (p<0.1), which is related with temperature increase as temperature is the limiting climatic factor for crop growth in these regions. / Time-frequency domain analysis was conducted to denoise multi-temporal remotely sensed data. These methods can be used for retrieving cloud-free phenological curves from multi-temporal satellite data. The two drought indices TVDI and VHI were spatio-temporally compared with the meteorological drought index, SPI. TVDI was subjected to extracted ‘wet edge’ and ‘dry edge’ in the study area while VHI was subjected to noises on NDVI and LST time series. SPI36 and remotely sensed drought indices can reach relative stable relationship, which may be due to the fact that most areas in the present study were covered by forest. / Carbon dynamics for forest ecosystem in drought can be quantified with carbon parameters from models and multi-temporal MODIS NDVI data sets. Sub-pixel percent forest cover was extracted based on principle component analysis (PCA) to multi-temporal MODIS NDVI. The estimated carbon change is highly correlated with the remotely sensed PsnNet change (r=0.32 p<0.001). Satellite remote sensing in conjunction with ecological models can retrieve many important variables caused by global change. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wang, Hongshuo. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 102-120). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.I / Table of contents --- p.IV / List of figures and tables --- p.VII / Acknowledgement --- p.XI / Chapter CHAPTER 1 --- Introduction --- p.1 / Chapter 1.1 --- Significance of the research --- p.1 / Chapter 1.2 --- Objectives of the study --- p.4 / Chapter 1.3 --- Dissertation structure --- p.4 / Chapter CHPATER 2 --- Literature Review --- p.6 / Chapter 2.1 --- Review on denoising multi-temporal data with time-frequency domain analysis --- p.6 / Chapter 2.2 --- Review on sub-pixel information extraction with multi-temporal NDVI --- p.9 / Chapter 2.3 --- Review on sensitivity of hyperspectral data in drought monitoring --- p.11 / Chapter 2.4 --- Review on spatio-temporal crop responses to climate change in China --- p.15 / Chapter 2.5 --- Review on spatio-temporal assessment of remotely- sensed drought indices --- p.18 / Chapter 2.5.1 --- Meteorological drought monitoring --- p.18 / Chapter 2.5.2 --- LST/NDVI space and its significance in drought monitoring --- p.20 / Chapter 2.6 --- Review on retrieving terrestrial carbon flux in drought --- p.23 / Chapter CHAPTER 3 --- Sensitivity of Hyperspectral Data in Monitoring Corn Responses to Drought --- p.25 / Chapter 3.1 --- Experiment --- p.25 / Chapter 3.2 --- Data analysis --- p.28 / Chapter 3.2.1 --- Sensitivity of hyerpspectral data to drought severity --- p.28 / Chapter 3.2.2 --- Comparison of different vegetation indices under drought --- p.30 / Chapter 3.3 --- Chlorophyll gradient under the threat of drought --- p.35 / Chapter 3.4 --- Discussion and conclusion --- p.36 / Chapter CHAPTER 4 --- Spatio-temporal Crop Responses to Climate Change in China --- p.39 / Chapter 4.1 --- Data description and preprocessing --- p.39 / Chapter 4.1.1 --- Data sets --- p.39 / Chapter 4.1.2 --- Data preprocessing --- p.40 / Chapter 4.1.3 --- Data standardization --- p.41 / Chapter 4.2 --- Conducting clustering analysis --- p.41 / Chapter 4.3 --- Regionalization result --- p.44 / Chapter 4.4 --- Crop responses to climate change --- p.44 / Chapter 4.4.1 --- Full-year crop responses to climate change --- p.48 / Chapter 4.4.2 --- Seasonal crop responses to climate change --- p.48 / Chapter 4.5 --- Drought trend of different scales and its potential influences on crop production --- p.54 / Chapter 4.6 --- Conclusion --- p.55 / Chapter CHAPTER 5 --- Spatio-temporal Assessment of Remotely-sensed Drought Indices a Case Study in Drought of Southwest China --- p.57 / Chapter 5.1 --- Denoising Multi-temporal data with frequency-time domain analysis --- p.57 / Chapter 5.1.1 --- Data Description --- p.57 / Chapter 5.1.2 --- Methods --- p.59 / Chapter 5.1.3. --- Comparison among Different Methods --- p.64 / Chapter 5.2. --- Drought indices --- p.65 / Chapter 5.2.1 --- data preprocessing --- p.67 / Chapter 5.2.2 --- VHI --- p.68 / Chapter 5.2.3 --- TVDI --- p.68 / Chapter 5.2.4 --- Spatial consistency between TVDI and VHI --- p.75 / Chapter 5.3 --- Conclusion and Discussion --- p.76 / Chapter CHAPTER 6 --- Monitoring Carbon Dynamic during Drought in Southwest China with MODIS --- p.78 / Chapter 6.1 --- Sub-pixel information retrieval based on multi-temporal MODIS NDVI --- p.78 / Chapter 6.1.1 --- Data collection and processing --- p.78 / Chapter 6.1.2 --- Methods --- p.82 / Chapter 6.1.3 --- Results and analysis --- p.86 / Chapter 6.2 --- Determining drought period --- p.89 / Chapter 6.3 --- Quantifying vegetative responses to drought with vegetation indices --- p.91 / Chapter 6.4 --- Quantifying carbon change of forest ecosystem during drought --- p.92 / Chapter 6.5 --- Conclusions and Discussions --- p.95 / Chapter CHAPTER 7 --- Innovations and Future Works --- p.98 / Chapter 7.1 --- Summary --- p.98 / Chapter 7.2 --- Innovations --- p.99 / Chapter 7.3 --- Future work --- p.101 / Reference --- p.102

A logistic regression model (LRRI) and a neural network model (NNRI) for RI forecasting of TCs are developed for the period 2000--2007. The five significant predictors are intensity change in the previous 12 h, intensification potential, lower-level relative humidity, eddy flux convergence at 200 hPa, and vertical wind shear. The verification of forecasts in 2008 typhoon season shows that NNRI outperforms LRRI for RI detection. / Despite improvements in statistical and dynamic models in recent years, the prediction of tropical cyclone (TC) intensity still lags that of track forecasting. Recent advances in satellite remote sensing coupled with artificial intelligence techniques offer us an opportunity to improve the forecasting skill of typhoon intensity. / In this study rapid intensification (RI) of TCs is defined as over-water minimum central pressure fall in excess of 20 hPa over a 24-h period. Composite analysis shows satellite-based surface latent heat flux (SLHF) and inner-core rain rate (IRR) are related to rapid intensifying TCs over the western North Pacific, suggesting SLHF and IRR have the potential to add value to TC intensity forecasting. / Several linear regression models and neural network models are developed for the intensity prediction of western North Pacific TC at 24-h, 48-h, and 72-h intervals. The datasets include Japan Meteorological Agency (JMA) Regional Specialized Meteorological Center Tokyo (RSMC Tokyo) best track data, the National Centers for Environmental Prediction (NCEP) Global Forecasting System Final analysis, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager sea surface temperature (SST), the Objectively Analyzed Air-sea Fluxes (OAflux) SLHF and TRMM Multisatellite Precipitation Analysis (TMPA) rain rate data. The models include climatology and persistence (CLIPER), a model based on Statistical Typhoon Intensity Prediction System (STIPS), which serves as the BASE model, and a model of STIPS with additional satellite estimates of IRR and SLHF (STIPER). A revised equation of TC maximum potential intensity (MPI) is derived using TMI Optimally Interpolated Sea Surface Temperature data (OISST) with higher temporal and spatial resolutions. Analysis of the resulting models indicates that the STIPER model reduces the mean absolute intensity forecast error by 6% for TC intensity forecasts out to 72 h compared to the CLIPER and BASE. Neural network models with the same predictors as STIPER can provide up to 28% error reduction compared to STIPER. The largest improvement is the intensity forecasts of the rapidly intensifying and rapidly decaying TCs. / Gao, Si. / Adviser: Long Song Willie Chiu. / Source: Dissertation Abstracts International, Volume: 73-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 94-105). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Yan, Su. / "December 2010"--Abstract. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 154-165). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

This study sought to explore the relationship between spatial scale and canopy chemistry through the use of remotely sensed videography data and total nitrogen content of potato petioles. A range of broad band spectral indices were employed along with standard red and green wavelengths to define an optimum scale or range of scales in which the accuracy of predicting leaf canopy chemistry could be improved. Difficulties inherent within video imagery due to the method in which the National Television System Committee's (NTSC) analog signal is comprised were studied. Spectral quantification of the video signal was not possible within the study, instead attention centered on showing the consistent and well correlated results that could be obtained using such data. Spectroradiometer measurements were also obtained for comparison with video response. Correlation between the two sensors was low, primarily due to the nature of the respective signals. Multispectral imagery was obtained from SPOT for spatial resolution comparison. The light research aircraft employed to collect the aerial video imagery proved to be a versatile and cost effective alternative to traditional remote sensing platforms. The data produced within the study support the project objectives in defining regions of high to low prediction accuracy. A reduction in spatial scale increases the ground area represented by an individual pixel and reduces the quantity and quality of information available to the sensor. The study illustrated a possible spatial resolution breakoff point at which nitrogen content prediction accuracy is greatly diminished. / Graduation date: 1995

To troubleshoot equipment installed in geographically distant locations, equipment manufacturers and system integrators are increasingly resorting to remote diagnosis in order to reduce the down time of the equipment, thereby achieving savings in cost and time on both the customer and manufacturer side. Remote diagnosis involves the use of communication technologies to perform fault diagnosis of a system located at a site distant to a troubleshooter. In order to achieve remote diagnosis, several frameworks have been proposed incorporating advancements such as automated fault diagnosis, collaborative diagnosis and mobile communication techniques. Standards exist for the capabilities representative of different levels of remote equipment diagnosis. Several studies have been performed to analyze the ability of human machine interface to assist troubleshooters in local fault diagnosis. However, the ability of a remote diagnosis system architecture to assist the troubleshooter in performing diagnosis and the effects of the failure types and other factors in a remote diagnosis environment on remote troubleshooting performance are not frequently addressed. In this thesis, an attempt is made to understand the factors that affect remote troubleshooting performance: remote diagnosis architecture, nature of failure, skill level of the local operator and level of expertise of the remote troubleshooter. For this purpose, three hierarchical levels of remote diagnosis architectures to diagnose failures in a PLC based automated assembly system were built based on existing standards. Common failures in automated assembly systems were identified and duplicated. Experiments were performed in which expert and novice troubleshooters used these remote diagnosis architectures to diagnose different types of failures while working with novice and engineer operators. The results suggest that in the diagnosis of failures related to measured or monitored system variables by remote expert troubleshooters, remote troubleshooting performance improved with the increase in the levels of the remote diagnosis architectures. In contrast, in the diagnosis of these failures by novice troubleshooters, no significant difference was observed among the three architectures in terms of remote troubleshooting performance and the novice troubleshooters experienced problems with managing the increased information available. Failures unrelated to monitored system parameters resulted in significantly reduced remote troubleshooting performance with all the three architectures in comparison to the failures related to monitored system parameters for both expert and novice troubleshooters. The experts exhibited better information gathering capabilities by spending more time per information source and making fewer transitions between information sources while diagnosing failures. The increase in capabilities of the architectures resulted in reduced operator interaction to a to a greater extent with experts. The difference in terms of overall remote troubleshooting performance between engineer and novice operators was not found to be significant.

None

Thesis (Ph. D.)--University of California, San Diego, 2003. / Vita. Includes bibliographical references.

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / The Mars Rover Design Team at Missouri University of Science and Technology developed a multifunctional rover for the Mars Society's University Rover Challenge. The main processor of the rover controls various rover subsystems based on commands received from a base station, acquires data from these subsystems, collects primary location and environmental data, and transmits information to the base station. The methodology and technical design of the processor hardware and software will be described in the overall context of the collaborative team development. The paper will also discuss the process, challenges and outcomes of working with limited resources on a student design team.

Satellite-based remotely sensed data were used to estimate regional-scale surface energy fluxes and a water deficit index of a semi-arid heterogeneous region in southeast Arizona. Spectral reflectance and radiometric temperature of the surface, derived from the digital counts of TM bands of LANDSAT-5 satellite, were used for this purpose. These reflectance and temperature, along with conventional meteorological information of the region, were used as inputs to numerical models which estimate surface energy fluxes. Point-based meteorological data of the region were spatially extrapolated over a grid of 120 m X 120 m so that it could be used with the spatially continuous remotely sensed data. The water deficit index (WDI) was estimated using surface temperature and a spectral vegetation index, "soil adjusted vegetation index" (SAVI). The surface fluxes were net radiation flux, sensible heat flux, soil heat flux and latent heat flux. Measured values obtained from the meteorological flux measurement (METFLUX) stations in the study area were compared with the modeled fluxes. Latent heat flux (LE) was the most important one to estimate in the scope of this study. The method of spatially extrapolating the point-based meteorological information and combining with the remotely sensed data produced good estimation of LE for the region, with a mean absolute difference (MAD) of 65 W/m² over a range of 67 to 196 W/m² . Also it was found that the numerical models that were previously used to estimate daily LE values from a region using mid-day remotely sensed data (mostly from NOAAAVHRR) can also be used with the mid-morning remotely sensed data (from LANDSAT). Out of the two models tested for this purpose (`Seguin-Itier' and 'Jackson' models), one was found to need some modification so that it could use mid-morning remotely sensed data as inputs. The other was found to be useable as it is, without any modification. Outputs from both models compared well with the measured fluxes from the METFLUX stations. In an effort of estimating the water deficit of the different biomes of the region, WDI of the biomes were estimated. The main goal of this effort was to be able to monitor the surface hydrologic conditions of the region using remotely sensed vegetation and surface information, and minimum ground data. Good estimation of the water deficit condition of the area were obtained by this method. This method was found to be sensitive to a few of the ground information such as wind speed and leaf area index (LAI). It was also found that if the required ground data were correctly estimated, this method could be used as an operational procedure for monitoring the vegetation water stress of the biomes and hence for better management of the region.

Geologic applications of Landsat images in northeastern Arizona to the location of water supplies for municipal and industrial uses / A Final Report of Work Performed Under OWRT Matching Grant B-066-ARIZ, Agreement number: 14-34-0001-8060 / April 1979