基于NDVI的新疆荒漠地区植被覆盖度遥感估算经验模型研究          下载免费PDF全文

岳健  穆桂金  唐自华  杨雪峰  林永崇  徐立帅 《干旱区地理》2020,43(1):153-160

新疆荒漠地区植被覆盖度遥感估算模型十分缺乏，给荒漠化监测等相关工作带来很大不便，开展植被覆盖度遥感估算经验模型研究，对于促进和完善相关地区的生态监测及研究工作具有积极的现实意义。通过对阜康市北部沙漠南缘和克拉玛依市中部平原荒漠进行无人机航拍，利用无人机遥感提取（光合）植被信息，并将无人机航拍影像的植被覆盖度统计单元与高分辨率卫星影像像元在空间上直接相对应，获取在高分辨率卫星影像像元尺度上的植被盖度，然后通过植被覆盖度和空间上与其相对应的源自高分辨率卫星影像的NDVI数据的拟合关系，建立基于源自高分二号影像的NDVI的阜康北部沙漠植被覆盖度遥感估算线性模型以及基于源自ZY1-02C影像的NDVI的克拉玛依平原荒漠植被覆盖度遥感估算二次多项式模型。研究中所采用的无人机遥感与卫星遥感相结合、植被覆盖度统计单元与卫星像元在空间上直接对应的方法，可避免以往相关工作中常以点位测量数据代表卫星像元数据所带来的不确定性。由于所用卫星影像的NDVI数据稳定性相对不足等原因，所建立的遥感估算模型的估算精度尚相对偏低，有待于今后进一步的工作加以改进。  相似文献   

Evaluating functional connectivity in a small agricultural catchment under contrasting flood events by using UAV     

Aleix Calsamiglia  Jorge Gago  Julián Garcia-Comendador  Josep Fortesa Bernat  Adolfo Calvo-Cases  Joan Estrany 《地球表面变化过程与地形》2020,45(4):800-815

Concentrated erosion, a major feature of land degradation, represents a serious problem for soil and water resources management and a threat to ecosystems. Understanding the internal mechanisms (de-)coupling sediment pathways can improve the management and resilience of catchments. In this study, concentrated erosion and deposition forms were mapped accurately through field and aerial unmanned aerial vehicle (UAV) campaigns, in order to assess the evolution of connectivity pathways over a series of three contrasted and consecutive flood events occurring between October 2016 and January 2017 (return period ranging from 0.5 to 25 years) in a small Mediterranean agricultural catchment (Can Revull, Mallorca, Spain; 1.4 km²). In addition, a morphometric index of connectivity (IC) was used to identify the potential trajectories of different concentrated erosion forms and deposition areas. IC predictions were calibrated by identifying the optimal critical thresholds, i.e. those most consistent with field observations after each of the events studied. The results found that the index performed well in predicting the occurrence and the length/area of the different type of landforms, giving kappa (κ) coefficients of variation ranging between 0.21 and 0.92 and linear correlations R² between 0.33 and 0.72. The type of landform affected the correspondence of IC predictions and field observations, with lower thresholds the greater the magnitude of their associated geomorphic processes. Rainfall magnitude proved to be a very important factor controlling the development of erosion and deposition landforms, with large differences in length/area between the contrasted events. The evolution of the observed trajectories revealed feedback dynamics between the structural and functional connectivity of the catchment, in which morphological changes determined the spatial distribution of the processes’ activity in the successive events and vice versa. © 2020 John Wiley & Sons, Ltd.  相似文献   

针对地质灾害隐患点的无人机航摄像控点布点方案     

吴波  李俊  蒋大鹏  冯志 《测绘通报》2020,(6):125

以陕西省某地质灾害隐患点1∶2000航飞生产任务为背景，本文结合垂直起降式无人机航摄技术特点和地质灾害隐患点区域实际情况，通过详细对比几种无人机航摄像控点布控方案的优劣，研究无人机像控点布设方案对空三加密精度的影响，总结了适用于不同地质灾害隐患点的像控点布设方案。通过本文研究，为今后制定地质灾害隐患点的无人机航摄像控点布设方案提供了参考依据。  相似文献   

姿态修正技术在黄河河口测验中的应用     

宋中华  田慧  王静 《测绘通报》2020,(11):120-123

为了解决黄河三角洲附近海区测验中测船姿态对单波束数字测深数据的影响，本文利用姿态传感器对测船的姿态进行了有效改正。试验结果表明，姿态修正技术对数字测深仪瞬时水深进行改正后，其测深结果与传统的人工水深曲线改正后成果比较，中误差为0.089 m，试验段面0 m线以下面积相差不超过0.22%，符合国家规范要求，提高了海区测验中测深成果的精度，为数字技术在海区测量的应用提供了技术保证。  相似文献   

基于深度学习理论的无人机影像分类     

阳成 《北京测绘》2020,(4):481-484

针对无人机影像深度学习分类方法缺乏现状,本文利用深度学习理论卷积神经网络方法对无人机影像进行了分类。该法首先抽取无人机影像作为训练集和检验集,然后建立一个2个卷积层-池化层的卷积神经网络模型进行深度学习,通过设定参数并运行模型实现无人机影像分类。实验表明,本文提出的方法可完成较复杂地区无人机影像分类,其分类精度与支持向量机方法相当,为无人机遥感影像分类提供了一个崭新的技术视点。  相似文献   

山地叶面积指数反演理论、方法与研究进展   总被引：2，自引：0，他引：2  

江海英  贾坤  赵祥  魏香琴  王冰  姚云军  张晓通  江波 《遥感学报》2020,24(12):1433-1449

叶面积指数LAI（Leaf Area Index）是表征叶片疏密程度和冠层结构特征的重要植被参数，在气候变化、作物生长模型以及碳、水循环研究中发挥着重要作用。遥感是获取区域及全球尺度LAI的一个重要手段，当前LAI产品主要基于遥感数据反演得到，但是多数LAI产品算法并未考虑地形特征的影响，导致山地LAI遥感反演精度不确定性大。提高山地LAI遥感反演精度亟需考虑地形因子对冠层反射率的影响，其中山地冠层反射率模型和遥感数据地形校正是提升山地LAI遥感反演精度的关键。本文围绕山地LAI遥感反演理论与方法，综合分析了国内外山地冠层反射率模型和地形校正模型的研究进展，总结了目前山地LAI遥感反演存在的问题，并讨论了未来研究的发展趋势。  相似文献   

Intra-continental deformation and tectonic evolution of the West Junggar Orogenic Belt,Central Asia:Evidence from remote sensing and structural geological analyses     

Wei-Cui Ding  Ting-Dong Li  Xuan-Hua Chen  Jian-Ping Chen  Sheng-Lin Xu  Yi-Ping Zhang  Bing Li  Qiang Yang 《地学前缘(英文版)》2020,(2):651-663

The West Junggar Orogenic Belt(WJOB)in northwestern Xinjiang,China,is located in the core of the western part of the Central Asian Orogenic Belt(CAOB).It has suffered two stage tectonic evolutions in Phanerozoic,before and after the ocean–continental conversion in Late Paleozoic.The later on intracontinental deformation,characterized by the development of the NE-trending West Junggar sinistral strike-slip fault system(WJFS)since Late Carboniferous and Early Permian,and the NW-trending Chingiz-Junggar dextral strike-slip fault(CJF)in Mesozoic and Cenozoic,has an important significance for the tectonic evolution of the WJOB and the CAOB.In this paper,we conduct geometric and kinematic analyses of the WJOB,based on field geological survey and structural interpretation of remote sensing image data.Using some piercing points such as truncated plutons and anticlines,an average magnitude of^73 km for the left-lateral strike-slip is calculated for the Darabut Fault,a major fault of the WJFS.Some partial of the displacement should be accommodated by strike-slip fault-related folds developed during the strike-slip faulting.Circular and curved faults,asymmetrical folds,and irregular contribution of ultramafic bodies,implies potential opposite vertical rotation of the Miao’ergou and the Akebasitao batholiths,resulted from the sinistral strike-slipping along the Darabut Fault.Due to conjugate shearing set of the sinistral WJFS and the dextral CJF since Early Mesozoic,superimposed folds formed with N–S convergence in southwestern part of the WJOB.  相似文献   

2010-2018年北极夏季中国北极科学考察航行期间被动微波遥感海冰密集度与船基目视观测资料的比较   总被引：2，自引：0，他引：2  

修苑人  李志军  雷瑞波  王庆凯  卢鹏  Lepp&#;ranta Matti 《海洋学报(英文版)》2020,39(9):38-49

为了更有效地将卫星数据应用于北极航行导航，被动微波（PM）产品的海冰密集度（SIC）与从中国北极科学考察中收集到的船基目视观测（OBS）资料进行了比较。在2010、2012、2014、2016和2018年的北极夏季总共收集了3667组目测数据。PM SIC取自基于SSMIS传感器的NASA-Team（NT）、Bootstrap（BT）以及Climate Data Record（CDR）算法和基于AMSR-E/AMSR-2传感器的BT、enhanced NT（NT2）以及ARTIST Sea Ice（ASI）算法。使用PM SIC的日算术平均值和OBS SIC的日加权平均值进行比较。比较了PM SIC和OBS SIC之间的相关系数，偏差和均方根偏差，包括总体趋势以及在轻度/普通/严重冰况下的情况。使用OBS数据，浮冰尺寸和冰厚对不同PM产品SIC反演的影响可以通过计算浮冰尺寸编码和冰厚的日加权平均值来评估。我们的结果显示相关系数的范围为0.89（AMSR-E/AMSR-2 NT2）到0.95（SSMIS NT），偏差的范围为-3.96%（SSMIS NT）到12.05%（AMSR-E/AMSR-2），均方根偏差的范围为10.81%（SSMIS NT）到20.15%（AMSR-E/AMSR-2 NT2）。浮冰尺寸对PM产品的SIC反演有显著的影响，大多数PM产品倾向于在小浮冰尺寸情况下低估SIC，而在大浮冰尺寸情况下高估SIC。超过30 cm的冰厚对于PM产品的SIC反演没有明显影响。总体来看，在北极夏季，SSMIS NT SIC与OBS SIC之间有着最好的一致性，而AMSR-E/AMSR-2 NT2 SIC与OBS SIC的一致性最差。  相似文献   

水面菲涅尔反射对~761 nm叶绿素荧光估算的影响     

温颜沙  邓建明  毛志华  石静  周杨  鲁婷  陆应诚 《遥感学报》2018,22(3):424-431

叶绿素荧光是光合作用的有效探针,可用于海洋浮游植物的监测与定量评估。太阳诱导叶绿素荧光覆盖可见光—近红外650—800 nm,在～685 nm与～740 nm表现出两个形态不同的荧光峰特征。基于～685 nm荧光峰的叶绿素浓度反演算法较为成熟,但在高悬浮物和高叶绿素浓度的水体中,算法的有效性不足。基于叶绿素荧光在氧气吸收谱段(O2-A)的填充作用,水体遥感反射率光谱～761 nm峰值中包含有太阳诱导叶绿素荧光信号,能用于水体叶绿素浓度的估算,但该反射峰形态特征还取决于传感器的光谱分辨率。本研究基于不同光谱分辨率的大气吸收谱线特征,模拟了水体遥感反射率光谱(750—775 nm)上太阳诱导叶绿素荧光的信号响应特征;分析了利用遥感反射率(～761 nm)计算叶绿素荧光的原理,阐明了不同光谱分辨率条件下水体叶绿素荧光信号在反射光谱上的形态变化规律。采用水面以上测量法获取的离水光谱辐亮度,包含了水面的菲涅尔反射信号,由于真实的菲涅尔系数难以准确测量,这给基于～761 nm处遥感反射率峰值的荧光信号估算带来不确定性影响。研究表明,假定菲涅尔系数为0时,虽然～761 nm叶绿素荧光信号与其浓度具有较好的线性统计关系,但却带来较大的不确定性;这种不确定的影响,在低浓度叶绿素水体中表现明显,在高浓度叶绿素水体中,影响相对较小;准确估算菲涅尔系数,有助于减少这种不确定性影响。对基于遥感反射率～761 nm叶绿素荧光信号的深入探讨,将能推动未来水体叶绿素荧光的识别与利用。  相似文献   

2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models   总被引：1，自引：0，他引：1  

Ali Ozgun Ok  Asli Ozdarici-Ok 《International Journal of Digital Earth》2018,11(6):583-608

One of the challenges of remote sensing and computer vision lies in the three-dimensional (3-D) reconstruction of individual trees by using automated methods through very high-resolution (VHR) data sets. However, a successful and complete 3-D reconstruction relies on precise delineation of the trees in two dimensions. In this paper, we present an original approach to detect and delineate citrus trees using unmanned aerial vehicles based on photogrammetric digital surface models (DSMs). The symmetry of the citrus trees in a DSM is handled by an orientation-based radial symmetry transform which is computed in a unique way. Next, we propose an efficient strategy to accurately build influence regions of each tree, and then we delineate individual citrus trees through active contours by taking into account the influence region of each canopy. We also present two efficient strategies to filter out erroneously detected canopy regions without having any height thresholds. Experiments are carried out on eight test DSMs composed of different types of citrus orchards with varying densities and canopy sizes. Extensive comparisons to the state-of-the-art approaches reveal that our proposed approach provides superior detection and delineation performances through supporting a nice balance between precision and recall measures.  相似文献