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在大型压力容器的部件焊接过程中,由于预热、焊接等工艺流程会导致各部件产生变形,从而引起部件之间的位置关系产生变化。为保证压力容器成品满足设计要求,必须在制造过程中实施变形监测,依据变形数据适当调整焊接工艺流程,控制变形量。提出采用智能全站仪配以自动变形监测软件对大型压力容器焊接变形进行实时监测,并应用于生产实践中,监测结果表明该方法自动化程度高、实时性好,能同时给出位置和姿态变形数据。 相似文献
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生物多样性遥感研究进展 总被引:3,自引:0,他引:3
随着遥感技术和新型传感器的发展,遥感已成为目前区域或全球生物多样性研究的重要方法。综述了目前国内外生物多样性遥感研究的最新进展;分析了遥感生物多样性研究的主要理论基础,包括光谱变异假说、生产力假说和种—面积关系理论等;总结了利用高空间和高光谱分辨率遥感数据直接监测生物物种及其多样性的进展与局限性;基于遥感反演的不同环境变量进行生物多样性模拟和预测是目前最常用的方法,对其进行了较详细的分析,并介绍了相关模型的发展。最后,总结了该方法在我国的应用局限,指出增进学科合作、将遥感方法与生态学理论和模型相结合、重视地面验证数据的使用将是生物多样性遥感研究的发展趋势。 相似文献
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J.G.P.W. Clevers L. KooistraM.E. Schaepman 《International Journal of Applied Earth Observation and Geoinformation》2008
Canopy water content (CWC) is important for mapping and monitoring the condition of the terrestrial ecosystem. Spectral information related to the water absorption features at 970 nm and 1200 nm offers possibilities for deriving information on CWC. In this study, we compare the use of derivative spectra, spectral indices and continuum removal techniques for these regions. Hyperspectral reflectance data representing a range of canopies were simulated using the combined PROSPECT + SAILH model. Best results in estimating CWC were obtained by using spectral derivatives at the slopes of the 970 nm and 1200 nm water absorption features. Real data from two different test sites were analysed. Spectral information at both test sites was obtained with an ASD FieldSpec spectrometer, whereas at the second site HyMap airborne imaging spectrometer data were also acquired. Best results were obtained for the derivative spectra. In order to avoid the potential influence of atmospheric water vapour absorption bands the derivative of the reflectance on the right slope of the canopy water absorption feature at 970 nm can best be used for estimating CWC. 相似文献
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Jianqiang Ren Zhongxin Chen Qingbo Zhou Huajun Tang 《International Journal of Applied Earth Observation and Geoinformation》2008,10(4):403
The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha−1 lower than the RMSE (233.35 kg ha−1) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation. 相似文献
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S. Fritz M. Massart I. Savin J. Gallego F. Rembold 《International Journal of Applied Earth Observation and Geoinformation》2008,10(4):453
Recent developments in remote sensing technology, in particular improved spatial and temporal resolution, open new possibilities for estimating crop acreage over larger areas. Remotely sensed data allow in some cases the estimation of crop acreage statistics independently of sub-national survey statistics, which are sometimes biased and incomplete. This work focuses on the use of MODIS data acquired in 2001/2002 over the Rostov Oblast in Russia, by the Azov Sea. The region is characterised by large agricultural fields of around 75 ha on average. This paper presents a methodology to estimate crop acreage using the MODIS 16-day composite NDVI product. Particular emphasis is placed on a good quality crop mask and a good quality validation dataset. In order to have a second dataset which can be used for cross-checking the MODIS classification a Landsat ETM time series for four different dates in the season of 2002 was acquired and classified. We attempted to distinguish five different crop types and achieved satisfactory and good results for winter crops. Three hundred and sixty fields were identified to be suitable for the training and validation of the MODIS classification using a maximum likelihood classification. A novel method based on a pure pixel field sampling is introduced. This novel method is compared with the traditional hard classification of mixed pixels and was found to be superior. 相似文献
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