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61.
风云卫星遥感数据高精度地理定位软件系统开发研究 总被引:1,自引:0,他引:1
为了适应风云气象卫星遥感数据高精度地理定位要求,在研究和比较分析现有环境气象卫星遥感数据地理定位方法,尤其对其中关键的轨道计算模型进行对比研究之后,我们使用变阶变步长多步卫星轨道数值计算模型(DE/DEABM)进行气象卫星轨道计算,研制开发了新一代卫星轨道计算及遥感数据地理定位软件系统.该软件系统中卫星轨道数值积分计算模型包含了多项摄动因素计算,特别是对低轨卫星影响较大的因素,其中地球的球形引力项使用了高精度高阶EGM-96地球引力场模型,提高了非球形引力摄动计算精度,另外还考虑了太阳、月亮引力项,辐射光压摄动和大气摄动因素,使得轨道计算精度大大提高.在遥感数据定位算法开发工作中,以中国2002年5月发射的风云1号D星10通道扫描辐射计和计划2008年上半年发射的风云3号A卫星中分辨率光谱成像仪等遥感仪器为对象,比较详细地分析和研究了探测器、焦平面、主光学系统和扫描镜等遥感仪器几大关键部件的光学几何关系,提高了坐标转换系统计算精度.经过对风云1号D星多天逐日的轨道计算和定位计算试验,结果表明该软件系统24h风云1号D星轨道计算卫星矢径精度可达到几十厘米至几十米,较原来平根数分析解方法1000m左右精度有显著量级的提高.同时,风云1号D星遥感数据地理定位精度达到星下点1个像元. 相似文献
62.
基于蚁群智能的遥感影像分类新方法 总被引:5,自引:0,他引:5
智能式遥感分类是遥感研究的新热点.提出了一种基于蚁群智能规则挖掘(ant-miner)的遥感影像分类新方法.遥感数据各波段之间存在较强的相关性,这种相关性往往会导致分类产生误差.而ant-miner算法中的信息素是基于规则整体性能的,信息素的动态更新能有效地处理相关性较强的数据,所提供的正反馈信息能纠正启发式函数缺陷所造成的错误.因此,蚁群智能算法应用于遥感分类具有一定的优势.将该方法用于广州市地区的遥感影像,取得了较好的分类结果.并与See5.0决策树方法及最大似然方法(MLH)进行了对比研究,实验结果表明,蚁群智能算法分类精度比后两者的分类精度更高. 相似文献
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64.
基于LBV变换的遥感影像多步骤分类法研究 总被引:1,自引:0,他引:1
面对与日俱增的遥感数据,如何快速准确地进行影像分类成为遥感领域亟待解决的问题。本文在前人的基础上提出了一种基于LBV变换的遥感影像多步骤分类方法。L:地物的总辐射水平,集中反映了裸地的信息;B:地物的可见-红外光辐射平衡,是地面水分状况和水体存在的一个良好指标;V:地物辐射随波段变化的方向和速度向量,能集中反映地面植被状况。多步骤分类法遵循由易到难的原则,能克服类别之间的互相影响,从而提高分类精度。文章结合LBV变换和多步骤分类法的优点对影像进行了分类,结果表明该方法简单易行,且能达到良好的分类精度。 相似文献
65.
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
66.
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
67.
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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