结合模平方的双树复小波变形监测数据滤波

针对变形监测数据的去噪问题,该文在分析离散小波变换去噪不足的基础上,提出了一种基于模平方的双树复小波变形监测数据滤波方法。该方法利用双树复小波变换的完全重构、近似平移不变性和较好的方向选择性等特点,通过最小尺度空间的小波系数得到噪声强度,并结合模平方处理法确定各层的阈值,经重构阈值处理后的各层小波系数即得到去噪后的信号;经算例,并与传统离散小波变换对比分析。结果表明:双树复小波变换的分解效果优于传统离散小波变换,能较好地表现出细节部分的频率信息,使变形信号的周期性变化特征更为明显。该方法去噪更彻底,进一步提高了消噪的精度和可靠性,可作为变形监测数据降噪处理的新方法。     

《遥感学报》20年:从热点到前沿

为反映《遥感学报》及中国遥感学科近20年的发展趋势,针对《遥感学报》在1997年—2015年期间出版的所有1804篇论文进行了统计分析,给出了国内高校及研究机构的发文量排名和受国家自然科学基金资助的发文情况,并对比了常设栏目和专题栏目的论文发文量及被引用情况。通过比较4个时间段内论文关键词的共现关系,反映出随着新的卫星载荷不断发射,观测技术由单一观测变为多源卫星观测,遥感定量反演模型由简单变得更为复杂,遥感技术应用也由最初的测绘、国土调查等单一应用逐渐变为多学科交叉应用,特别是在近年来国内外社会热点的驱动下,遥感技术已开始在灾害应急、全球变化、大气污染、粮食安全等领域发挥出越来越重要的作用。此外,无论是在当前遥感学科发展还是国家需求的现状下,都迫切需要建立国家级的遥感应用综合信息系统,以提高对环境和资源的宏观调控能力,为中国经济和社会可持续发展战略、布局和趋势预测,为资源管理、环境保护、防灾减灾以及实现资源环境、经济、社会的宏观调控,提供科学的数据和决策支持。     

盾构施工参数与沉降变形关系模型构建

针对盾构施工参数变化对施工引起的地表变形的重要影响,该文构建了盾构施工参数与地表沉降变形关系模型。以北京市某地铁盾构区间施工过程中的实测数据为基础,分析了不同盾构施工参数与地表沉降变形的关联度和相关性,得到不同参数对沉降变形贡献值的大小;之后,利用多元回归模型方法建立主要影响参数与地表变形的关系模型,并进行模型的合理性检验;最后,利用该模型得到的沉降量与实测数据进行对比分析,结果显示符合性较好。     

县域经济发展水平评价及时空格局演变——以河北省为例

针对河北省县域经济发展特点和时空变化规律的问题,该文将GIS技术与定量分析方法相结合,选取2000年和2010年的15个能够反映河北省县域经济发展状况的指标,采用熵值法系统地测算了河北省136个县的经济发展水平,并利用空间自相关分析法分析了河北省县域经济发展空间格局的演变特征。研究结果表明:河北省县域经济发展依然存在明显的南北差异,并已形成"一线+两点"的经济空间格局;2000—2010年,Moran指数不断下降,高-高集聚区和低-低集聚区的县域数量与土地面积不断减少,河北省县域经济集聚效应减弱,经济发展渐趋均衡。     

Landsat 8陆地成像仪影像的缨帽变换推导

针对Landsat 8陆地成像仪影像,该文提出了一种缨帽变换系数的推算方法。利用准同步的Landsat ETM+影像缨帽变换结果为目标值,采用普鲁克算法对不同地理分布下的陆地成像仪影像样本点的主成分轴分别进行旋转,得到相应的初始变换系数;通过广义普鲁克分析对所得初始变换系数进行平均化,并以格拉姆-施密特算法保持其正交性,最终得到基于陆地成像仪大气表观反射率数据的缨帽变换系数。验证结果表明,与现有陆地成像仪变换系数相比,该文提出的缨帽变换精度相对较高,误差较小,变换后的不同地物覆盖类型具有更好的可分性。     

利用端元光谱内插的青海植被覆盖度估算研究

针对利用像元二分模型估算植被覆盖度的精度不高的问题,该文基于OSAVI,提出了选定模型参数(OSAVIs和OSAVIv)的方法,并将该方法应用于青海省植被覆盖度估算。该方法通过高分辨率影像在研究区内选取纯裸地和纯植被样点,并将纯裸地样点的OSAVI作为纯裸地样点像元的OSAVIs,将纯植被样点的OSAVI作为纯植被样点像元的OSAVIv,利用样点像元的OSAVIs和OSAVIv值,通过普通克里金内插法,求得研究区每个像元对应的OSAVIs和OSAVIv。经精度验证结果表明:此方法较常规的参数选取方法,RMSE由0.170降至0.156,MAE由0.137降至0.124。经进一步分析表明,此方法对边缘验证点和非边缘验证点的估算精度都有所提高,由于配准误差和周围地表漫反射的影响,边缘验证点的估算精度低于对非边缘验证点的估算精度。     

一种曲线拟合圆心坐标算法及精度分析

针对在工程应用中,经常需要根据某些圆形物体上的离散点求取其圆心坐标,而采用何种算法简单易行,其精度又与哪些因素有关的相关研究较少的问题,该文提出一种利用曲线拟合求取圆心坐标的简洁算法,并编程实现。然后采用模拟仿真结合统计分析的方法评估了该算法在不同条件下的拟合精度,得出测点误差越大,拟合精度越低;测点个数越多,分布越均匀,拟合精度越高;圆半径对拟合精度影响甚小等结论。在某工程项目中使用该算法得到的结果精度较高,验证了其有效可行,且与采用其他方法得到的坐标值较为接近,说明了该算法的可靠性高。     

Multiple statistical approaches for the discrimination of mangrove species of Rhizophoraceae using transformed field and laboratory hyperspectral data

This study aims at discriminating eight mangrove species of Rhizophoraceae family of Indian east coast using field and laboratory spectra in spectral range (350–2500 nm). Parametric and non-parametric statistical analyses were applied on spectral data in four spectral modes: (i) reflectance (ii) continuum removed, (iii) additive inverse and (iv) continuum removed additive inverse. We introduced continuum removal of inverse spectra to utilize the advantage of continuum removal in reflectance region. Non-parametric test gave better separability than parametric test. Principal component analysis and stepwise discriminant analysis were applied for feature reduction and to identify optimal wavelengths for species discrimination. To quantify the separability, Jeffries–Matusita distance measure was derived. Green (550 nm), red edge (680–720 nm) and water absorption region (1470 and 1850 nm) were found to be optimal wavelengths for species discrimination. The continuum removal of additive inverse spectra gave better separability than the continuum removed spectra.     

Identifying geospatial services across heterogeneous taxonomies

Geospatial services with different functions are assembled together to solve complex problems. Different taxonomies are developed to categorize these services into classes. As differences in granularity and semantics exist among these taxonomies, the identification of services across different taxonomies has become a challenge. In this paper, an approach to identify geospatial services across heterogeneous taxonomies is proposed. Using formal concept analysis, existing heterogeneous taxonomies are decomposed into semantic factors and their various combinations. With these semantic factors, a super taxonomy is established to integrate the original heterogeneous taxonomies. Finally, with the super taxonomy as a cross-referencing system, geospatial services with classes in original taxonomies are identifiable across taxonomies. Experiments in service registries and a social media-based spatial-temporal analysis project are presented to illustrate the effectiveness of this approach.     

A hybrid approach to modeling territorial control in violent armed conflicts

Territorial control is central to the understanding of violent armed conflicts, yet reliable and valid measures of this concept do not exist. We argue that geospatial analysis provides an important perspective to measure the concept. In particular, measuring territorial control can be seen as an application of calculating service areas around points of control. The modeling challenge is acute for areas with limited road infrastructure, where no complete network is available to perform the analysis, and movements largely occur off road. We present a new geospatial approach that applies network analysis on a hybrid transportation network with both actual road data and hexagon‐fishnet‐based artificial road data representing on‐road and off‐road movements, respectively. Movement speed or restriction can be readily adjusted using various input data. Simulating off‐road movement with hexagon‐fishnet‐based artificial road data has a number of advantages including scalability to small or large study areas and flexibility to allow all‐directional travel. We apply this method to measuring territorial control of armed groups in Sub‐Saharan Africa where inferior transport infrastructure is the norm. Based on the Uppsala Conflict Data Program's (UCDP) Georeferenced Event Data (GED) as well as spatial data on terrain, population locations, and limited transportation networks, we enhance the delineation of the specific areas directly controlled by each warring party during civil wars within a given travel time.