耦动论下的遥感方向硕士教育与职业衔接实践     

盛庆红  肖晖 《测绘工程》2016,25(12):77-80

没实习单位可去、无企业导师指导、没实际东西可学是导致遥感领域硕士研究生就业难的主要原因,而不同的教育理念会对学生培养有不同程度的影响。文中将耦动理论运用到实践中,在校企合作、双导师制和前沿科技讲座互动式教学3个方面进行改革创新,注重理论与实践的互动、专硕教育与职业的衔接,为培养遥感领域研究生实践能力、工作能力提供参照。  相似文献   

清水河流域1978-2010年土地利用变化时空特征     

周秋文  韦小茶  许幼霞  周旭  张继  梁建方 《测绘工程》2016,25(11):12-17

通过对1978年、1998年和2010年3期遥感影像目视解译获得3期土地利用数据,分析清水河流域1978－2010年土地利用变化时空特征。研究表明：清水河流域1978－2010年期间,农用地、难利用地面积持续减少,林地、建设用地面积持续增加,草地面积先有所减少后增多,除林地以外其它土地类型变化幅度后期都较前期大;流域土地利用转移方向主要是农用地转为低、中、高覆盖度草地、林地和建设用地,中覆盖度草地转为低、高覆盖度草地和林地,低覆盖度草地转为中、高覆盖度草地、林地。结果表明,近年来清水河流域水土保持措施效果明显。  相似文献   

结合像元分解和STARFM模型的遥感数据融合   总被引：4，自引：2，他引：2  

谢登峰  张锦水  孙佩军  潘耀忠  云雅  袁周米琪 《遥感学报》2016,20(1):62-72

高空间、时间分辨率遥感数据在监测地表快速变化方面具有重要的作用。然而,对于特定传感器获取的遥感影像在空间分辨率和时间分辨率上存在不可调和的矛盾,遥感数据时空融合技术是解决这一矛盾的有效方法。本文利用像元分解降尺方法(Downscaling mixed pixel)和STARFM模型(Spatial and Temporal Adaptive Reflectance Fusion Model)相结合的CDSTARFM算法(Combination of Downscaling Mixed Pixel Algorithm and Spatial and Temporal Adaptive Reflectance Fusion Model)进行遥感数据融合。首先,利用像元分解降尺度方法对参与融合的MODIS数据进行分解降尺度处理;其次,利用分解降尺度的MODIS数据替代STARFM模型中直接重采样的MODIS数据进行数据融合;最后以Landsat 8和MODIS遥感影像数据对该方法进行了实验。结果表明:(1)CDSTARFM算法比STARFM和像元分解降尺度算法具有更高的融合精度;(2)CDSTARFM能够在较小的窗口下获得更高的融合精度,在相同的窗口下其融合精度也高于STARFM;(3)CDSTARFM融合的影像更接近真实影像,消除了像元分解降尺度影像中的"图斑"和STARFM模型融合影像中的"MODIS像元边界"。  相似文献   

非均匀地表蒸散遥感研究综述   总被引：2，自引：0，他引：2  

周倜  彭志晴  辛晓洲  李福根 《遥感学报》2016,20(2):257-277

本文评述了目前常用的遥感估算地表蒸散方法,包括地表能量平衡模型、Penman-Monteith类模型、温度—植被指数特征空间方法、Priestley-Taylor类模型和其他方法。然而使用这些方法估算地表蒸散时会面临严重的尺度效应,而产生尺度效应的根本原因之一是地表异质性,在分析了非均匀下垫面对水热通量遥感反演造成的影响后,介绍了面积加权、校正因子补偿与温度降尺度3种尺度误差纠正方法;并从地面观测实验的角度简述了非均匀下垫面水热通量真实性检验的研究;最后探讨了将来建立更具时空代表性的非均匀下垫面地表蒸散遥感估算模型可能会面临的一些挑战。  相似文献   

资源三号卫星影像融合优化方法探讨     

吴满意  付冬暇  王占宏  田怀启  张光辉  于金芝 《测绘科学》2016,41(6):108-112

针对资源三号卫星影像如何进行影像融合、波段组合才能到达到最佳视觉效果还没有统一意见的问题,该文提出了利用目前测绘项目中普遍采用的融合算法、波段组合比例对不同地形类别资源三号卫星影像进行实验验证的方法。综合主观评价与客观评价融合后的影像质量,得出了Subtractive、Pansharp和Pansharp2方法较为适合资源三号卫星影像融合的结论,其中绿波段与近红外波段的最佳组合比为9∶1。同时,分析了资源三号卫星影像融合后数据量大大增加、如何将近红外波段的波谱信息合理地加入到红、绿、蓝波段中等问题。  相似文献   

生态敏感性限制下的城市建设用地适宜性评价     

崔耀平  吕可文  何春玲  路婧琦  张帅帅  黄向球  冯永杰  麻永健 《测绘科学》2016,41(9):47-53,59

针对当前城市规划中对建设用地适宜性评价框架的不尽合理问题,以河南省西峡县为例构建了包含主导性和限制性逻辑的综合评价方案。利用遥感与地理信息系统相结合的方法,将生态敏感性作为限制性因素进行城市建设用地适宜性研究。研究区的分析结果显示:西峡县整体新增城镇建设区呈现南北区域不适宜而中间适宜的特征,而适宜和较适宜城市建设的用地主要分布在鹳河及其支流形成的河谷地带。但在中心城区外缘某些区域生态敏感性强,应禁止开发活动。研究结果有效体现出建设用地和生态用地的空间格局,对城市总体规划具有一定的参考价值。  相似文献   

植被生物量高光谱遥感监测研究进展   总被引：2，自引：0，他引：2  

姚阔  郭旭东  南颖  李坤  江淑芳  孙婷婷 《测绘科学》2016,(8):48-53

植被生物量的评估对于研究全球碳循环具有重大意义,而高光谱遥感技术为精确反演地表属性提供了重要的数据支持。针对如何更好地应用高光谱遥感技术进行植被生物量精确反演的问题,该文详细阐述了国内外应用高光谱技术估测植被生物量的研究进展。对反演植被生物量所涉及的数据源、反演模型的构建方法及其模型特点、反演模型应用对象等内容进行了综合评述,并通过分析认为,高光谱遥感技术较传统的多光谱遥感技术在生物量反演精度上有了显著的提高。同时,对建模方法、多源遥感数据融合以及模型通用性等方面的研究进行了展望,以达到在大尺度范围内对植被生物量进行准确反演的目的。  相似文献   

Quantification of LST and CO2 levels using Landsat-8 thermal bands on urban environment     

Venkatesh Reddy Chejarla  Pramod Kumar Maheshuni 《国际地球制图》2016,31(8):913-926

Land surface temperature (LST) is an important aspect in global to regional change studies, for control of climate change and balancing of high temperature. Urbanization is one of the influencing factors increasing land surface and atmospheric temperature, by the emission of greenhouse gases (e.g. CO₂, NO and methane). In the present study, LST was derived from Landsat-8 of multitemporal data sets to analyse the spatial structure of the urban thermal environment in relation to the urban surface characteristics and land use–land cover (LULC). LST is influenced by the greenhouse gases i.e. CO₂ plays an important role in increasing the earth’s surface temperature. In order to provide the evidence of influence of CO₂ on LST, the relationship between LST, air temperature and CO₂ was analysed. Landsat-8 satellite has two thermal bands, 10 and 11. These bands were used to accurately to calculate the temperature over the study area. Results showed that the strength of correlation between ground monitoring data and satellite data was high. Based on correlation values of each month April (R² = 0.994), May (R² = 0.297) and June (R² = 0.934), observed results show that band 10 was significantly correlating with air temperature. Relationship between LST and CO₂ levels were obtained from linear regression analysis. band 11 was correlating significantly with CO₂ values in each of the months April (R² = 0.217), May (R² = 0.914) and June, (R² = 0.934), because band 11 is closer to the 15-micron band of CO₂. From the results, it was observed that band 10 can be used for calculating air temperature and band 11 can be used for estimation of greenhouse gases.  相似文献   

Remote sensing and information value (IV) model for regional mapping of fluvial channels and topographic wetness in the Saudi Arabia     

Mohamed Mostafa Mohamed 《地理信息系统科学与遥感》2016,53(4):520-541

This study aims to map regions of near surface fluvial channels, mega-basins and topographic wetness in Saudi Arabia using remote sensing data and an information value (IV) model, which is a modified approach of weight of evidence. We used the new version of the Shuttle Radar Topographic Mission (SRTM) to delineate the fluvial channels, mega-basin, and slope. These hydrological parameters were used to index the topographic wetness of each mega-basin in the region based on IV in a Geographic Information System. We validated our method using the Space Imaging Radar-C and Landsat 8 images and compared the textural features (fluvial channels) evident from SRTM digital elevation model and to determine whether these patterns were different. Our results revealed that the region is drained by nine tributaries and that the Err Rub Al Khali and Sahba mega-basins have the highest value of the IV and topographic wetness values; the Arran and coastal mega-basins have the lowest value of the IV and topographic wetness values. An integrated approach is timely and economically effective and can be applied throughout the arid and semi-arid regions to help hydrologists and urban developers.  相似文献   

A variable precision rough set approach to knowledge discovery in land cover classification     

Iftikhar U. Sikder 《International Journal of Digital Earth》2016,9(12):1206-1223

This paper presents a granular computing approach to spatial classification and prediction of land cover classes using rough set variable precision methods. In particular, it presents an approach to characterizing large spatially clustered data sets to discover knowledge in multi-source supervised classification. The evidential structure of spatial classification is founded on the notions of equivalence relations of rough set theory. It allows expressing spatial concepts in terms of approximation space wherein a decision class can be approximated through the partition of boundary regions. The paper also identifies how approximate reasoning can be introduced by using variable precision rough sets in the context of land cover characterization. The rough set theory is applied to demonstrate an empirical application and the predictive performance is compared with popular baseline machine learning algorithms. A comparison shows that the predictive performance of the rough set rule induction is slightly higher than the decision tree and significantly outperforms the baseline models such as neural network, naïve Bayesian and support vector machine methods.  相似文献