Estimating tree canopy cover using harmonic regression coefficients derived from multitemporal Landsat data     

《International Journal of Applied Earth Observation and Geoinformation》2020

The goal of this study was to evaluate whether harmonic regression coefficients derived using all available cloud-free observations in a given Landsat pixel for a three-year period can be used to estimate tree canopy cover (TCC), and whether models developed using harmonic regression coefficients as predictor variables are better than models developed using median composite predictor variables, the previous operational standard for the National Land Cover Database (NLCD). The two study areas in the conterminous USA were as follows: West (Oregon), bounded by Landsat Worldwide Reference System 2 (WRS-2) paths/rows 43/30, 44/30, and 45/30; and South (Georgia/South Carolina), bounded by WRS-2 paths/rows 16/37, 17/37, and 18/37. Plot-specific tree canopy cover (the response variable) was collected by experienced interpreters using a dot grid overlaid on 1 m spatial resolution National Agricultural Imagery Program (NAIP) images at two different times per region, circa 2010 and circa 2014. Random forest model comparisons (using 500 independent model runs for each comparison) revealed the following (1) harmonic regression coefficients (one harmonic) are better predictors for every time/region of TCC than median composite focal means and standard deviations (across times/regions, mean increase in pseudo R² of 6.7% and mean decrease in RMSE of 1.7% TCC) and (2) harmonic regression coefficients (one harmonic, from NDVI, SWIR1, and SWIR2), when added to the full suite of median composite and terrain variables used for the NLCD 2011 product, improve the quality of TCC models for every time/region (mean increase in pseudo R² of 3.6% and mean decrease in RMSE of 1.0% TCC). The harmonic regression NDVI constant was always one of the top four most important predictors across times/regions, and is more correlated with TCC than the NDVI median composite focal mean. Eigen analysis revealed that there is little to no additional information in the full suite of predictor variables (47 bands) when compared to the harmonic regression coefficients alone (using NDVI, SWIR1, and SWIR2; 9 bands), a finding echoed by both model fit statistics and the resulting maps. We conclude that harmonic regression coefficients derived from Landsat (or, by extension, other comparable earth resource satellite data) can be used to map TCC, either alone or in combination with other TCC-related variables.  相似文献   

共模误差对坐标时间序列分析的影响     

孙阳  徐爽  崔志浩  周海龙 《北京测绘》2020,(1):113-117

基于2013年至2018年环渤海地区GPS基站6年的观测数据,研究了共模误差对坐标时间序列分析的影响。首先利用主成分分析方法提取环渤海区域27个基准站的共模误差,以N、E、U三个方向的第一主成分来计算共模误差;然后使用最大似然估计法得到各测站剔除共模误差前后的噪声。发现在消除共模误差后,N,E,U方向的相对坐标时间序列得到改善,白噪声,闪烁噪声和随机行走噪声明显减小。结果表明,共模误差的剔除有效的提高了坐标时间序列分析的精度。  相似文献   

基于高斯模型的样本缺失GPS时间序列重构方法     

周知红 《北京测绘》2020,(2):255-259

缺失样本的存在会造成GPS时间序列速度估计的不确定性,从而影响GPS时间序列的应用。针对该问题本文提出一种基于高斯模型的样本缺失GPS时间序列重构方法,首先利用高斯概率密度函数对GPS时间序列的先验分布进行建模,在此基础上构建全概率贝叶斯统计模型,采用期望最大(Expectation Maximization,EM)算法对模型参数(隐变量)进行迭代更新并计算其最大似然估计值,最终完成信号重构。分别对随机缺失和分段连续缺失两种情况进行实验分析,结果表明所提方法相对于传统插值方法可以获得更好的重构性能。  相似文献   

基于Google Earth Engine的红树林年际变化监测研究   总被引：1，自引：0，他引：1  

刘凯  彭力恒  李想  谭敏  王树功 《地球信息科学学报》2019,21(5):731-739

遥感技术已广泛应用于红树林资源调查与动态监测中,但仍然存在遥感数据获取困难、数据预处理工作量大、监测时间长而周期过大等问题,影响了学者对红树林演变过程的精细刻画与理解。本文基于Google Earth Engine（GEE）云遥感数据处理平台,选取Landsat系列卫星数据,生成长时间序列年际极少云影像集（云量少于5%）,利用3个红外波段反射率（NIR、SWIR1、SWIR2）和3个特征指数（NDVI、NDWI、NDMI）建立阈值规则集,实现对实验区越南玉显县红树林、红树林-虾塘、不透水面-裸地、水体4种目标地物的专家知识决策树分类和土地覆盖的制图,并基于分类结果监测该区域1993-2017年的红树林年际动态变化。结果表明：GEE平台可满足多云多雨地区红树林的长时间序列年际变化监测需求;本文阈值分类方法可以有效提取红树林及红树林-虾塘,实验区有86%年份的影像分类精度达到80%以上;年际变化监测可精细刻画实验区红树林面积先增后减再增的变化过程,也能准确反映红树林与红树林-虾塘养殖系统面积之间的负相关关系。红树林年际动态监测结果可以降低红树林演变分析的不确定性,并能更精细地量化红树林与其他土地覆盖类型的转化过程,从而评估经济发展、政策等因素对红树林演变的影响。  相似文献   

基于PCA方法的GPS台站时间序列分析     

张晶  王小亚  胡小工 《大地测量与地球动力学》2019,39(6):613-619

基于10 a以上的全球GPS台站数据，利用主成分分析法及其他数据处理方法，对台站时间序列进行预处理和结果分析，研究其中的非线性周期规律，探讨时间序列的主要影响机制。结果表明，主成分分析法可以将台站残差时空矩阵分解成若干正交成分，GPS台站时间序列的东西方向具有线性漂移趋势，全球大部分GPS台站都存在非线性周期规律，周年项和半周年周期占据主导地位。  相似文献   

Drifting runoff periodicity during the 20th century due to changing surface water volume     

Anders Wörman  Göran Lindström  Anna Åkesson  Joakim Riml 《水文研究》2010,24(26):3772-3784

Fourier and wavelet analyses were used to reveal the dominant trends and coherence of a more than one‐century‐long time series of precipitation and discharge in several watersheds in Sweden, two of which were subjected to hydropower and intensive agriculture. During the 20th century, there was a gradual, significant drift of the dominant discharge periodicity in agricultural watersheds. This study shows that the steepness of the Fourier spectrum of runoff from the May to October period each year increased gradually during the century, which suggests a more predictable intra‐annual runoff pattern (more apart from white‐noise). In the agricultural watershed, the coherence spectrum of precipitation and runoff is generally high with a consistent white‐noise relationship for precipitation during the 20th century, indicating that precipitation is not controlling the drift of the discharge spectrum. In the hydropower regulated watershed, there was a sudden decrease of the discharge spectrum slope when regulation commenced in the 1920s. This study develops a new theory in which the runoff spectrum is related to the hydraulic and hydro‐morphological characteristics of the watershed. Using this theory, we explain the changes in runoff spectra in the two watersheds by the anthropogenic change in surface water volume and, hence, changes in kinematic wave celerity and water transit times. The reduced water volume in the agricultural watershed would also contribute to decreasing evaporation, which could explain a slightly increasing mean discharge during the 20th century despite the fact that precipitation was statistically constant in the area. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

利用时序InSAR监测兰州市中心城区地面沉降     

张剑  柯宝贵  刘同木  曹炳强 《测绘科学》2021,46(1):99-107,161

针对兰州市中心城区的地面沉降问题,该文采用PS-SBAS和PS-InSAR技术,利用2016-01-20—2019-02-21时间段内的39景Sentinel-1A/B降轨数据,使用缓冲区分析技术对兰州市中心城区轨道交通线和铁路线周边100m区域做了沉降影响分析,监测结果表明:基于Sentinel-1A/B数据和时序InSAR技术,可以准确监测城市地表的沉降和轨道交通线的沉降时空规律;沉降区域主要集中在研究区东南部的方家泉村、和平镇和猪咀岭村;软土地基下地铁的施工会导致沉降现象的发生,兰州轨道交通线和铁路线的沉降主要发生在城区东南方向;在监测时段内,使用两种时序InSAR技术监测的同名点在沉降趋势和累计沉降量上保持了良好的一致性和吻合性,但PS-InSAR的时序变化曲线较PS-SBAS更为平缓。  相似文献   

顾及有色噪声影响的甘肃境内CMONOC基准站坐标时间序列分析          下载免费PDF全文

刘双童  徐鉴民  高志钰  陈晨  杨树文 《全球定位系统》2021,46(1):43-49

针对甘肃省境内19个CMONOC基准站坐标时间序列结果,采用极大似然估计法（MLE）探讨了各基准站的最优噪声模型,确定了基准站的速度场,并分析了甘肃省地壳运动状况. 研究结果表明:甘肃省境内CMONOC基准站各坐标分量噪声特性存在较大的差异,“白噪声+闪烁噪声（WN+FN）”为最优噪声模型,能够更好地描述基准站坐标时间序列3分量上的噪声特性,且估算的速率不确定度是仅考虑WN时的4~15倍. 甘肃省CMONOC基准站在ITRF14框架下水平方向运动的平均速率为34.54 mm/a,运动方向为SEE 98.07°;相对于欧亚板块的水平方向运动的平均速率为6.49 mm/a,运动方向为NEE 79.23?°.   相似文献   

基于时序InSAR技术监测大桥历史形变     

陈艳青  赵景堂 《测绘工程》2021,30(2):50-54,59

2019-06-14,河源市源城区东江大桥第三跨第二桥墩以及第四跨第三桥墩出现了垮塌,此次事故造成了人员伤亡和重大经济损失。为了分析此次灾害事故发生发展的成因,本研究获取了Sentinel-1A雷达卫星2018年12月至2019年6月的历史影像数据,基于时序InSAR技术手段处理得到了该监测时间段内的历史形变信息。研究成果显示该桥梁在此数据获取时间段处于相对稳固状态,并无明显的形变特征趋势。通过对事发桥梁进行实地观测,结合了各类研究资料推断该桥梁垮塌的成因机理为突发因素,例如物体撞击或者水流的冲刷造成。文中研究成果可以为今后桥梁类基础设施的监测预警工作提供应用实践。  相似文献   

雷达遥感滑坡隐患识别与形变监测     

廖明生  董杰  李梦华  敖萌  张路  史绪国 《遥感学报》2021,25(1):332-341

滑坡是全球发生最为频繁、造成损失最严重的自然灾害之一,滑坡表面形变测量对于滑坡的早期识别、监测和预警具有重要意义。雷达遥感具有非接触式大范围空间连续覆盖和高精度形变测量等优势,在滑坡地质灾害领域中取得了广泛的应用。本文概述武汉大学干涉雷达遥感团队近几年在利用雷达遥感监测滑坡形变方面的研究内容,包括：雷达遥感在滑坡形变监测中的可行性和适用性分析、大范围滑坡隐患识别、复杂山区滑坡形变测量、大梯度滑坡形变测量、滑坡三维形变提取等。  相似文献