基于遥感影像的青海省环境变化监测     

韩建平 《测绘通报》2021,(10):123-126,145

本文通过对遥感影像的分析,针对土地利用及植被变化情况,利用优化的K-means算法对青海省环境变化进行检测,以此对土地的利用进行合理的规划,以期实现可持续发展。同时将试验结果与外业实际结果及当地政策规划进行比对,结果显示文中算法对土地的变化和未来走势预测准确率超过75%,从而验证了监测方法的可行性。这不仅保证了在经济发展的同时能够合理地使用土地资源,而且能对环境进行有效的保护。  相似文献   

中国区域DMSP-OLS与NPP-VIIRS夜间灯光影像校正     

关靖云  李东  王亚菲  王新芸 《测绘通报》2021,(9):1-8

本文基于对传统不变目标区域校正法的改进,选择4期辐射定标参考影像对DMSP-OLS影像进行了饱和校正与时间序列连续性校正。通过阈值法去除了NPP-VIIRS影像的背景噪声及异常值,利用对数变换压缩了其灯光辐射值的动态范围,使其亮度分布更接近于DMSP-OLS数据。利用BiDoseResp函数模型对NPP-VIIRS影像进行了一致性校正,获得了1992-2019年长时间序列夜间灯光影像。从定性、定量及校正影像与社会经济参量的相关性方面对校正结果进行了精度验证。结果表明,改进后的校正方法改善了DMSP-OLS影像饱和严重的现象,使其获得了长时间序列纵向可比性。BiDoseResp函数模型可以很好地拟合DMSP-OLS和对数变换后的NPP-VIIRS之间的回归。校正后的长时间序列灯光影像数据与社会经济参量高度契合。校正结果对推广长时间序列夜间灯光影像的广泛应用、深化长时间序列科学问题的研究具有重要价值。  相似文献   

轨道扣件病害自动化检测研究及应用     

侯海倩  唐超  赵丽凤  张昊 《测绘通报》2021,(8):88-92

传统扣件检查基本采用人工检查方式,不仅工作效率低、劳动强度大,而且人为干扰因素多、检查采样率低。针对以上问题,本文提出了一种基于线结构光传感器的轨道扣件损伤和松动检测方法,并开发了轨道扣件智能监测系统以实现扣件病害自动检测。最终将研究成果应用于徐州市某地铁区间轨道扣件检测,验证了该方法的可行性和准确率,为地铁轨道扣件检查提供了新方法。  相似文献   

海洋三维遥感与海洋剖面激光雷达     

唐军武  陈戈  陈卫标  赵朝方  贺岩  吴松华  刘秉义  毛志华  何惠馨  杨杰  陈树果  胡连波  何兴道  史久林  郑永超  刘建强  林明森  吴立新  郭华东  蒋兴伟  潘德炉  顾逸东 《遥感学报》2021,25(1):460-500

本文从海洋与气候变化等重大前沿科学与应用对空间海洋观测系统的需求出发,基于当前国内外空间激光技术水平与前期海洋激光遥感的探索,提出了海洋遥感从二维向三维发展的紧迫性,并将海洋剖面探测激光雷达作为未来“海洋三维遥感”的主要技术手段。本文对近50年国内外激光海洋剖面探测技术的理论与应用、基础性关键探测机理问题,尤其是近10年来的试验性探索及其在多个海洋科学问题中的应用进行了综述。结合中国自主“观澜号”海洋科学卫星计划中海洋剖面探测激光雷达的系统论证与指标要求,提出了未来海洋剖面探测激光雷达发展路线图建议以及中国有望率先在空间海洋剖面激光探测领域取得突破的设想。  相似文献   

基于显著性图像与纹理特征的遥感影像云检测     

黄宇  潘励 《测绘地理信息》2021,46(2):16-19

遥感影像云检测是遥感影像处理中非常关键的环节,准确识别影像含云区域能够提升影像的利用价值。根据遥感影像的成像特点,将阈值法和纹理特征结合实现云和下垫面的分割。首先将影像从RGB(red-green-blue)空间转化为HSI(hue-saturation-intensity)空间,进而构建影像的显著性图像,利用Otsu法对显著性图像进行粗分割,再基于灰度共生矩阵分析云和下垫面的纹理特征,进一步提取出准确的云区。实验表明,该算法复杂度较低,提取效果良好。  相似文献   

浙江省测震观测台网井下地震计方位角检测与校正     

张明  陈军辉  严俊峰  尹晶飞  戴陈兵 《地震地磁观测与研究》2019,40(4):125-129

选取浙江省测震台网景宁、北仑、南麂岛地震台井下地震计观测数据，采用地震数据波形相关性分析法，与地表地震计同步观测数据进行相关性分析，检测并校正井下地震计方位角，结果发现，3个地震台井下地震计方位角实际偏差分别为82.2°、-22.8°、32.2°。分析认为，井下地震计安装易受线缆应力影响，导致方位角与实际偏差过大，应在应力释放完成后固定地震计，并架设地表地震计进行数据相关性分析，以确定方位角可靠性。  相似文献   

经济海藻病害及防控技术的研究进展     

杨慧超  李杰  阎永伟  唐磊  茅云翔  莫照兰 《海洋科学》2019,43(1):101-111

经济海藻的病害一直是海藻人工栽培的一大障碍,往往造成严重的经济损失。目前对藻类病害的研究大多集中于病原鉴定,而病原的多样性和复杂的海区微环境增加了病原分离和鉴定的难度。本文综述了经济海藻病害发生的原因、病原的多样性和致病机制、病原的鉴定、检测和防治方法,并对未来我国海藻病害研究方向进行了展望,以期对藻类病害的防控提供参考。  相似文献   

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis     

Ali Almagbile 《地球空间信息科学学报》2019,22(1):23-34

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.  相似文献   

Classification of glacial lakes using integrated approach of DFPS technique and gradient analysis using Sentinel 2A data     

Prateek Verma  Sanjay Kumar Ghosh 《国际地球制图》2019,34(10):1075-1088

It is important to identify and locate glacial lakes for assessing any potential hazard. This study presents a combination of semi-automatic method Double-Window Flexible Pace Search (DFPS) and edge detection technique to identify glacial lakes using Sentinel 2A satellite data. Initially, Normalized Difference Water Index (NDWI) has been used to identify water and non-water areas, while DFPS and Edge detection technique has been used to identify an optimum threshold value to distinguish between water and shadow areas. The optimal threshold from DFPS process is 0.21, while threshold value of gradient magnitude using edge detection process is 0.318. The number of glacial lakes identified using the above algorithm is in close agreement with previously published results on glacial lakes in Gangotri glacier using different techniques. Thus, a combination of DFPS and edge detection process has successfully segregated glacial lakes from other features present in Gangotri glacier.  相似文献   

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas     

Lei Deng  Ying He  Zhi-hui Mao  Jie Yu 《地理信息系统科学与遥感》2019,56(1):1-21

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.  相似文献