高分辨率遥感影像提取道路的方法综述与思考

 介绍了高分辨率遥感影像上道路的特征、模型和道路提取的基本思想，对已有的道路提取方法进行了分析，并对道路提取问题进行思考，提出下一步的研究方向。     

遥感影像制图综合的智能化研究

本文以人工智能为基础,用计算机模拟一般制图人员对遥感图像进行制图综合的过程,用框架的知识表示方法建立了一个实验性的知识库,并设计了一个推理机。对蒙古人民共和国乌布苏淖尔地区的ＴＭ分类图进行了实验,取得了较好的效果。     

天文观测科学实践中心技术实现

天文观测科学实践中心是一个以天文观测为核心的网络实践体验中心,以网站的形式向公众提供服务。网站建设使用HTML、CSS、JavaScript和JSP/JaveBean等技术;基于B/S结构实现望远镜远程控制;采用Windows Media技术实现视频发布。建成的网站为用户提供了全新的天文观测实践体验机会,达到了传播天文知识的目的。     

基于遥感影像的建筑物空间分布方法在地震灾害损失预评估中的应用

房屋建筑数据是地震重点危险区预评估工作的基础,需基于获取到的房屋建筑信息开展人员伤亡、经济损失、救援物资需求等预评估工作。历年地震重点危险区预评估工作能够通过现场调查得到的房屋建筑信息占比极小,仅能进行抽样调查。因此,为批量完成危险区内全部房屋建筑损失估算,需基于遥感影像获取房屋建筑矢量数据,并建立数据库。为实现全国地震重点危险区预评估工作中大批量建筑物矢量化数据的快速获取,本文采用基于遥感影像的建筑物空间分布数据批量获取方法,得到地震重点危险区内建筑物空间矢量数据,结合现场抽样调查得到的建筑物属性信息,建立地震重点危险区建筑物空间分布数据库,进而为地震重点危险区灾害损失预评估工作提供数据基础。本文采用的方法可广泛应用于地震重点危险区房屋建筑信息获取工作中,可提高工作效率,降低工作成本,提升预评估工作的科学性和准确性。     

Assessing protected area’s carbon stocks and ecological structure at regional-scale using GEDI lidar

Protected areas (PAs) serve as a critical strategy for protecting natural resources, conserving biodiversity, and mitigating climate change. While there is a critical need to guide area-based conservation efforts, a systematic assessment of PA effectiveness for storing carbon stocks has not been possible due to the lack of globally consistent forest biomass data. In this study, we present a new methodology utilizing forest structural information and aboveground biomass density (AGBD) obtained from the Global Ecosystem Dynamics Investigation (GEDI) mission. We compare PAs with similar, unprotected forests obtained through statistical matching to assess differences in carbon storage and forest structure. We also assess matching outcomes for a robust and minimally biased way to quantify PA efficacy. We find that all analyzed PAs in Tanzania possess higher biomass densities than their unprotected counterfactuals (24.4% higher on average). This is also true for other forest structure metrics, including tree height, canopy cover, and plant area index (PAI). We also find that community-governed PAs are the most effective category of PAs at preserving forest structure and AGBD – often outperforming those managed by international or national entities. In addition, PAs designated under more than one entity perform better than the PAs with a single designation, especially those with multiple international designations. Finally, our findings suggest that smaller PAs may be more effective for conservation, depending on levels of connectivity. Taken together, these findings support the designation of PAs as an effective means for forest management with considerable potential to protect forest ecosystems and achieve long-term climate goals.     

Measuring land-use and land-cover change using the U.S. department of agriculture’s cropland data layer: Cautions and recommendations

Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.     

Assessing reference evapotranspiration at regional scale based on remote sensing,weather forecast and GIS tools

Reference evapotranspiration (ET_o) is a key component in efficient water management, especially in arid and semi-arid environments. However, accurate ET_o assessment at the regional scale is complicated by the limited number of weather stations and the strict requirements in terms of their location and surrounding physical conditions for the collection of valid weather data. In an attempt to overcome this limitation, new approaches based on the use of remote sensing techniques and weather forecast tools have been proposed.Use of the Land Surface Analysis Satellite Application Facility (LSA SAF) tool and Geographic Information Systems (GIS) have allowed the design and development of innovative approaches for ET_o assessment, which are especially useful for areas lacking available weather data from weather stations. Thus, by identifying the best-performing interpolation approaches (such as the Thin Plate Splines, TPS) and by developing new approaches (such as the use of data from the most similar weather station, TS, or spatially distributed correction factors, CITS), errors as low as 1.1% were achieved for ET_o assessment. Spatial and temporal analyses reveal that the generated errors were smaller during spring and summer as well as in homogenous topographic areas.The proposed approaches not only enabled accurate calculations of seasonal and daily ET_o values, but also contributed to the development of a useful methodology for evaluating the optimum number of weather stations to be integrated into a weather station network and the appropriateness of their locations. In addition to ET_o, other variables included in weather forecast datasets (such as temperature or rainfall) could be evaluated using the same innovative methodology proposed in this study.     

Assessment of land degradation in Mediterranean forests and grazing lands using a landscape unit approach and the normalized difference vegetation index

Land managers need sound, evidence-based information about land degradation patterns and about the effectiveness of their management responses. Obtaining such information is particularly difficult in Mediterranean grazing lands and forests, where a long history of anthropogenic pressure, high topographical and climatic variability, and frequent disturbances combine to create a highly diverse and unstable environment.Our study aimed at designing a methodology to provide land managers in three data-scarce drylands in Spain, Greece, and Cyprus with spatially explicit, up-to-date information on the state of their land, the pressures driving land degradation, and the effectiveness of their management efforts using remotely sensed NDVI data. To translate NDVI values into a land degradation assessment, we analysed the variance of the annual average NDVI within different landscape units, which we identified based on land cover, aspect, and slope steepness parameters. After calibrating and validating the land degradation mapping methodology using field observations, we related the obtained land degradation patterns with spatial information about grazing and wildfire, as well as controlled grazing and afforestation practices.Our methodology proved useful to assess land degradation and management measures in dry, semi-natural ecosystems. It also provided insights into the role of landscape in modulating land degradation. Results indicate that grazing is a significant cause of land degradation even in partially abandoned areas; repeated fires have a negative impact; slope steepness increases the land's sensitivity to grazing; north- and east-facing slopes are less sensitive to fire in the long term than south- and west-facing slopes; and the effectiveness of responses to land degradation is substantially affected by land cover and topography.The methodology presented can be used to overcome the lack of spatially explicit information on the state of the land in drylands of the Mediterranean and beyond, or as a basis for more in-depth studies to plan restoration interventions.     

论地球空间信息科学的形成

从分析地球空间信息科学与全球变化监测和社会可持续发展的关系出发,回顾了地球空间信息科学产生的背景,提出地球空间信息科学的定义及内涵,概括了学科当前的发展状况,提出了现阶段学科研究的主要内容,最后,展望了地球空间信息科学的发展。     

The application of satellite differential SAR interferometry-derived ground displacements in hydrogeology

The application of satellite differential synthetic aperture radar (SAR) interferometry, principally coherent (InSAR) and to a lesser extent, persistent-scatterer (PSI) techniques to hydrogeologic studies has improved capabilities to map, monitor, analyze, and simulate groundwater flow, aquifer-system compaction and land subsidence. A number of investigations over the previous decade show how the spatially detailed images of ground displacements measured with InSAR have advanced hydrogeologic understanding, especially when a time series of images is used in conjunction with histories of changes in water levels and management practices. Important advances include: (1) identifying structural or lithostratigraphic boundaries (e.g. faults or transitional facies) of groundwater flow and deformation; (2) defining the material and hydraulic heterogeneity of deforming aquifer-systems; (3) estimating system properties (e.g. storage coefficients and hydraulic conductivities); and (4) constraining numerical models of groundwater flow, aquifer-system compaction, and land subsidence. As a component of an integrated approach to hydrogeologic monitoring and characterization of unconsolidated alluvial groundwater basins differential SAR interferometry contributes unique information that can facilitate improved management of groundwater resources. Future satellite SAR missions specifically designed for differential interferometry will enhance these contributions.