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排序方式： 共有10000条查询结果，搜索用时 15 毫秒
1.
介绍了雪粒径遥感反演的研究历史,阐述了球形或非球形假设下基于雪在可见光波段高反射,在红外区雪面反射率显著下降且对雪粒径变化敏感原理的遥感反演基础,其中包括诸如温度、波长、颗粒形状等,并总结了目前研究中所应用的模型和算法,指出其优点和不足之处.此外,为了得到反演粒径的准确性,讨论了诸如温度、波长、颗粒形状等因素对粒径反演... 相似文献
2.
随着现代化教学手段在地理教学中的应用,传统的教学挂图可利用计算机作为辅助工具,制作成电子教学地图。本文论述了利用遥感数字图像制作电子教学地图的指导思想、必要性和可行性,并探讨了遥感数字影像教学地图的制作方法。 相似文献
3.
浅谈基于ERDAS IMAGINE软件的几何精纠正方法 总被引：1，自引：0，他引：1
随着遥感技术日新月异的发展,它在各个领域的应用已经越来越广泛。目前市场上遥感软件的种类很多,比较具有代表性的软件为美国ERDAS公司开发的遥感图像处理系统。遥感图像的几何精纠正是遥感图像分类、专题制图的基础,也是遥感应用研究的基础。本文正是基于ERDAS IMAGINE软件浅谈遥感影像的几何精纠正方法。 相似文献
4.
Stefanie M. Herrmann Assaf Anyamba Compton J. Tucker 《Global Environmental Change》2005,15(4):394-404
Contrary to assertions of widespread irreversible desertification in the African Sahel, a recent increase in seasonal greenness over large areas of the Sahel has been observed, which has been interpreted as a recovery from the great Sahelian droughts. This research investigates temporal and spatial patterns of vegetation greenness and rainfall variability in the African Sahel and their interrelationships based on analyses of Normalized Difference Vegetation Index (NDVI) time series for the period 1982–2003 and gridded satellite rainfall estimates. While rainfall emerges as the dominant causative factor for the increase in vegetation greenness, there is evidence of another causative factor, hypothetically a human-induced change superimposed on the climate trend. 相似文献
5.
《International Journal of Digital Earth》2013,6(2):118-132
Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies. 相似文献
6.
7.
从美国发射其第一颗遥感卫星一陆地卫星－1算起的30余年里,世界范围内商业遥感卫星技术已经有了巨大的进步,越来越多的国家和国际团体拥有自己的遥感卫星。除了更多各类的遥感器得以使用外,卫星的图像分辨率和覆盖能力也有了很大的改进。未来的发展更加令人振奋。国外遥感卫星（包括已经发射和计划要发射的卫星）简介是根据从国内外出版物中获得的信息整编而成,旨在给遥感应用提供一个现在和未来图像信息源的总的概念。 相似文献
8.
Sophie Sobanska Cécile Coeur Willy Maenhaut Freddy Adams 《Journal of Atmospheric Chemistry》2003,44(3):299-322
Individual aerosol particles collected in the Negev desert in Israel during a summer and winter campaign in 1996–1997 were analysed by scanning electron microscopy with energy-dispersive X-ray analysis. Hierarchical cluster analysis was performed to interpret the data on the basis of particle diameter and composition. Eleven particle classes (groups) provided clues on sources and/or particle formation. The summer samples were enriched in sulphates and mineral dusts; the winter samples contained more sea salts, aged sea salts, and industrial particles. The fine size fraction below 1 m diameter was enriched in secondary particles and showed evidence of atmospheric processing. The secondary sulphate particles were mainly attributed to long-range transport. A regional conversion from calcite to calcium sulphate occurred during summer. Industrial particles originating from local pollution appeared during winter. 相似文献
9.
Chudamani Joshi Jan De Leeuw Andrew K. Skidmore Iris C. van Duren Henk van Oosten 《International Journal of Applied Earth Observation and Geoinformation》2006
In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories. 相似文献
10.
Carl J. Legleiter 《地球表面变化过程与地形》2012,37(5):499-518
This study developed and evaluated a hybrid approach to remote measurement of river morphology that combines LiDAR topography with spectrally based bathymetry. Comparison of filtered LiDAR point clouds with surveyed cross‐sections indicated that subtle features on low‐relief floodplains were accurately resolved by LiDAR but that submerged areas could not be detected due to strong absorption of near‐infrared laser pulses by water. The reduced number of returns made the active channel evident in a LiDAR point density map. A second dataset suggested that pulse intensity also could be used to discriminate land from water via a threshold‐based masking procedure. Fusion of LiDAR and optical data required accurate co‐registration of images to the LiDAR, and we developed an object‐oriented procedure for achieving this alignment. Information on flow depths was derived by correlating pixel values with field measurements of depth. Highly turbid conditions dictated a positive relation between green band radiance and flow depth and contributed to under‐prediction of pool depths. Water surface elevations extracted from the LiDAR along the water's edge were used to produce a continuous water surface that preserved along‐channel variations in slope. Subtracting local flow depths from this surface yielded estimates of the bed elevation that were then combined with LiDAR topography for exposed areas to create a composite representation of the riverine terrain. The accuracy of this terrain model was assessed via comparison with detailed field surveys. A map of elevation residuals showed that the greatest errors were associated with underestimation of pool depths and failure to capture cross‐stream differences in water surface elevation. Nevertheless, fusion of LiDAR and passive optical image data provided an efficient means of characterizing river morphology that would not have been possible if either dataset had been used in isolation. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
