机载激光雷达技术和摄影测量匹配技术在DEM生产中的应用

机载激光雷达技术和摄影测量匹配技术是国内制作DEM最为常见的两种技术,本文对这两种技术的作业流程及优缺点进行了详细论述,并在实验中将这两种技术组合应用,最终证明这两种技术如果能恰当地组合使用,可在DEM生产中显著提高生产效率.     

模拟退火机制下优化离散粒子群的端元提取算法

针对离散粒子群优化(Discrete Particle Swarm Optimization,DPSO)端元提取算法初始种群质量差、收敛性能低且易于陷入局部最优,本文将模拟退火算法引入到DPSO的不同阶段,模拟退火算法能以一定的概率接受和舍弃新状态,使种群内粒子渐趋有序、达到平衡,收敛到全局最优,有效避免了搜索陷入局部最优。因此,该算法不仅保持了DPSO的全局组合优化特点,克服了初始种群质量差、易陷入局部最优等缺点,而且还提高了收敛速度和端元提取精度。     

基于遥感影像的城市用地变化监测方法研究

利用遥感技术进行动态变化监测是地理国情监测的重点研究内容之一,动态监测技术方法较多,笔者在对已有方法探讨的基础上,基于World View-2及资源三号遥感影像,提出了一种城市用地变化信息检测的多波段主成分分析方法。该方法通过线性变换生成互不相关的波段组合,对多波段主成分分析后的影像采用直方图统计法进行阈值分割,再经过滤波处理,去除干扰信息。研究结果表明,采用该方法提取两期遥感影像上的变化信息,可以实现动态变化监测。     

基于多源多时相遥感数据的秋季菜田监测与分析——以北京市大兴区为例

根据北方蔬菜种植生育期特点,选择7~8月份的高分1号(GF1)融合影像、10月份的16 m宽覆盖的GF1影像以及8月份Rapid Eye融合影像,结合耕地本底数据开展提取秋季菜田信息的技术流程研究,并对2013年和2014年大兴区秋季菜田进行了动态监测,同时结合气象等数据分析其时空分布规律和变化原因。     

浅谈高原高寒地区遥感影像判读技巧

以西藏怒江流域高原高寒地区为背景,对利用高分辨率遥感影像进行判读时经常遇到的几方面问题,运用实例分析的方法,给出了解决问题的思路,为以后的工作和类似区域遥感影像的判读提供了参考依据。     

多源遥感影像管理与服务平台的设计与实现

针对遥感影像管理与共享服务,在分析不同来源遥感影像数据资源特点基础上,提出了适合多源、海量遥感影像数据管理的"文件+数据库"的存储和管理方式,采用镶嵌数据集进行遥感影像数据管理,并进行服务发布;同时提出了多源遥感影像管理与服务平台的总体构架体系,包括海量遥感影像管理平台和多源遥感影像网络化服务平台的设计与实现。     

高精度遥感影像的空间投影几何精校正

几何校正为影像预处理工作做了技术准备。其精度直接影响着后续工作的质量。目前,高精度遥感影像因其空间分辨率较高、数据产品格式复杂,在实际应用中对其进行几何精校正(包括正射校正)还存在许多问题。在地面控制点(Ground Control Point,GCP)分布不均或数量不足的情况下,运用空间投影加密控制点的方法,能有效解决此类问题。本文以Quick Bird遥感卫星影像为例,阐述了该方法的可行性。     

Detection of foreclosure-related landscape management changes using Landsat

The volume of properties affected by foreclosure over the past decade suggests the potential for dramatic change in vegetation cover due to changes in management. Yet, the specific pathology of each foreclosure, the temporal asynchrony among foreclosures, and differences in the area available for vegetation growth across properties presents challenges to observing and measuring change. This paper develops and tests a difference in deviations approach that compares the parcel NDVI to a neighborhood norm before and after foreclosure. The difference in deviations approach addresses the challenges of separating parcel-level change corresponding to foreclosure and identifies changes on both small and large parcels. The method relies on a time series of Landsat Normalized Difference Vegetation Index (NDVI) data, individual home foreclosure records and property tax assessment data for Maricopa County, Arizona from 2002 to 2012. To establish the level of difference associated with observable landscape change, we use a probit regression model, coding Google Earth images for properties across the range of observed deviations of difference. The basic assumption underlying the approach is that if foreclosure coincides with a change in management, it will lead to changes in vegetation structure and thus, NDVI values. We estimate that 13% of home foreclosures in Maricopa County over the period from 2002 to 2012 resulted in declines in vegetation whereas 6.5% resulted in vegetation increases. Future uses of this method for understanding landscape management in residential landscapes are discussed.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

Crossing-over between land cover and land use: Exploring spatially varying relationships in two large US metropolitan areas

Difficulties in identifying actual uses of land space from remote sensing-based land cover products often result in lost opportunities to enhance the capacity of applied research on human settlements. In an attempt to address these difficulties, this study investigates how land cover and land use are interrelated with each other and what determines the relationship patterns by analyzing detailed land use and land cover data for two large US metropolitan areas – the five-county Los Angeles and six-county Chicago regions – where a broad spectrum of human settlements, ranging from urban cores to less-urbanized edges, coexist. The analysis shows that the land cover-land use relationship substantially varies not only across regions but across neighborhoods within each region. Through multivariate regression, it is also found that the intraregional variation is highly associated with the neighborhood's stage of urbanization, median housing age, and other development characteristics, suggesting that the relationship pattern can largely be shaped by the history and evolution of urban design/development.