基于三维激光扫描的校园建筑物三维建模研究

"数字校园"建设是科技发展的必然趋势,为加快这一进程,本次研究将地面三维激光扫描技术应用到大学校园。本文以Z+F IM AGER 5010c地面三维激光扫描仪采集到的吉林建筑大学基础实验楼数据为基础,运用3ds max、Auto CAD、Point Cloud等建模软件建立三维模型。同时将依据点云数据建立的实体模型与实际测量数据进行对比和精度分析,验证了地面三维激光扫描仪在建筑物三维模型建立中的精度和可靠性。     

The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century

Studies of global environmental change make extensive use of scenarios to explore how the future can evolve under a consistent set of assumptions. The recently developed Shared Socioeconomic Pathways (SSPs) create a framework for the study of climate-related scenario outcomes. Their five narratives span a wide range of worlds that vary in their challenges for climate change mitigation and adaptation. Here we provide background on the quantification that has been selected to serve as the reference, or ‘marker’, implementation for SSP2. The SSP2 narrative describes a middle-of-the-road development in the mitigation and adaptation challenges space. We explain how the narrative has been translated into quantitative assumptions in the IIASA Integrated Assessment Modelling Framework. We show that our SSP2 marker implementation occupies a central position for key metrics along the mitigation and adaptation challenge dimensions. For many dimensions the SSP2 marker implementation also reflects an extension of the historical experience, particularly in terms of carbon and energy intensity improvements in its baseline. This leads to a steady emissions increase over the 21st century, with projected end-of-century warming nearing 4 °C relative to preindustrial levels. On the other hand, SSP2 also shows that global-mean temperature increase can be limited to below 2 °C, pending stringent climate policies throughout the world. The added value of the SSP2 marker implementation for the wider scientific community is that it can serve as a starting point to further explore integrated solutions for achieving multiple societal objectives in light of the climate adaptation and mitigation challenges that society could face over the 21st century.     

Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery

Monitoring crop conditions and forecasting crop yields are both important for assessing crop production and for determining appropriate agricultural management practices; however, remote sensing is limited by the resolution, timing, and coverage of satellite images, and crop modeling is limited in its application at regional scales. To resolve these issues, the Gramineae (GRAMI)-rice model, which utilizes remote sensing data, was used in an effort to combine the complementary techniques of remote sensing and crop modeling. The model was then investigated for its capability to monitor canopy growth and estimate the grain yield of rice (Oryza sativa), at both the field and the regional scales, by using remote sensing images with high spatial resolution. The field scale investigation was performed using unmanned aerial vehicle (UAV) images, and the regional-scale investigation was performed using RapidEye satellite images. Simulated grain yields at the field scale were not significantly different (p = 0.45, p = 0.27, and p = 0.52) from the corresponding measured grain yields according to paired t-tests (α = 0.05). The model’s projections of grain yield at the regional scale represented the spatial grain yield variation of the corresponding field conditions to within ±1 standard deviation. Therefore, based on mapping the growth and grain yield of rice at both field and regional scales of interest within coverages of a UAV or the RapidEye satellite, our results demonstrate the applicability of the GRAMI-rice model to the monitoring and prediction of rice growth and grain yield at different spatial scales. In addition, the GRAMI-rice model is capable of reproducing seasonal variations in rice growth and grain yield at different spatial scales.     

Modeling the environmental susceptibility of landfill sites in California

??The proper management of solid waste (SW) is a global environmental challenge. A major issue is the proper disposal of SW while balancing a wide range of criteria and working with different spatial data. In this study, we used geographic information system as a tool to perform multi-criteria decision analysis with an analytical hierarchy process to develop an environmental impact susceptibility model (EISM) for landfills. The model was applied to the state of California, USA and results are presented herein. In particular, the EISM considers factors such as geology, pedology, geomorphology, water resources, and climate as represented by 13 associated environmental indicators. The results of the EISM indicate that more than 75% of California’s territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 25% of the state’s land, 61 landfills are located in the high and very high categories. These results are alarming because during the period from 2000 to 2015, these 61 landfills received approximately 308 million tons of SW, which corresponds to more than 57% of all SW disposed in California. The model results can be used toward mitigating the environmental impacts of these facilities.     

Smart 3D数据的三维模型重建

针对Smart 3D生成的实景三维模型是一个三角网集合,并不能直接应用于数字城市建设、土地利用管理与城市规划的问题,该文提出了Smart 3D数据三维模型重建的方法:研究了基于分割过滤方法,提取高精度数字高程模型;基于参数化建模、纹理重建方法构建了建筑物三维模型。利用敦化市的倾斜影像进行了实验。实验结果表明:三维重建模型精度高、效果好、提高了自动化的程度,实现了城市建筑物模型的单体化。     

Crossing Boundaries in a Collaborative Modeling Workspace

There is substantial literature on the importance of bridging across disciplinary and science–management boundaries. One of the ways commonly suggested to cross boundaries is for participants from both sides of the boundary to jointly produce information (i.e., knowledge co-production). But simply providing tools or bringing people together in the same room is not sufficient. Here we present a case study documenting the mechanisms by which managers and scientists collaborated to incorporate climate change projections into Colorado’s State Wildlife Action Plan. A critical component of the project was the use of a collaborative modeling and visualization workspace: the U.S. Geological Survey’s Resource for Advanced Modeling (RAM). Using video analysis and pre/post surveys from this case study, we examine how the RAM facilitated cognitive and social processes that co-produced a more salient and credible end product. This case provides practical suggestions to scientists and practitioners who want to implement actionable science.     

空间相互作用模型中的目的地竞争效应 ——基于中国城市间铁路客流数据的实证研究

目的地竞争模型是空间相互作用领域的重要进展之一,但其有效性尚未得到一致认可,且缺乏基于中国的实证依据。基于中国2010年城市间铁路客流数据,采用目的地竞争模型进行实证分析,并与传统空间相互作用模型相比较,以检验目的地竞争模型在实际应用中的有效性。结果表明：① 空间结构对中国城市间铁路客流存在显著影响,目的地之间存在较强的竞争效应;② 目的地竞争模型的引入显著地减弱了距离衰减参数的空间自相关程度,较大程度上改善了传统空间相互作用模型的距离衰减参数标定偏误问题;③ 既有研究中在区域尺度下对传统空间相互作用模型（即重力模型）参数的标定及实证分析可能会存在偏误,目的地竞争模型这一改进模型具备应用价值。     

人海关系地域系统的构成及其研究重点探讨

在全球化和人类活动向海洋扩张的背景下,作为总体性人地关系一个组成部分的人海关系正变得日益复杂和重要,亟需对其进行基础性的理论解读,以整合和指导具体研究的展开。人海关系地域系统包括人类、海洋和陆地3个基本组成部分。其中,人类具有自然和社会2种基本属性,受人类活动影响的海洋和陆地具有自然、社会和关系3种基本属性。人类与海洋、人类与陆地和海洋与陆地之间的互动构成了人海关系地域系统中最基本的相互关系,其不同组合和演变塑造出了具体、多样的人海关系地域系统。当前人海关系地域系统的研究重点包括海洋观、海洋的开发与保护、国际海洋关系、陆海统筹和海洋社会5个方面。     

当代生态经济的综合研究综述

可持续发展战略的规划设计需要生态经济学的综合研究思想。在总结国内外关于生态经济综合研究资料的基础上,系统总结了一门新兴学科——生态经济学的研究历程、研究内容和方法。生态经济学的综合研究,关键是将人类社会经济系统视为生态系统的一个子系统,认为人类社会的发展依赖于生态系统的支持。其研究是在微观层次上对经济系统和生态系统进行有机结合的具体尝试。从发展与环境之间关系的讨论入手,系统地分析总结了生态经济学与经济学、生态学以及其它学科之间的关系和作用,西方生态经济学早期和当代的研究状况和我国生态经济学的研究状况及进展,最后从可持续发展的定量衡量和生态经济模型的建立两方面介绍了目前流行的生态经济学研究方法。     

THE UNDERSTANDING OF ENSO CYCLE MECHANISM AND ENSO POTENTIAL PREDICTION ABILITY*

In recent years,the dynamic coupled models of ocean-atmosphere and statistical models have been used in routine operation for issuing long-lead forecasts.The dynamic coupled models consist of models with varying degrees of complexity,ranging from simplified coupled models of the shallow water to coupled general circulation models.During the period of 1980-1992,some models performed considerably better than the persistence forecast on predicting typical indices of ENSO for lead time of 6 to 12 months.It seems that ENSO is predictable at least one year in advance.However.nearly all the models have lost their skill of forecasting sea surface temperature(SST)changes in the eastern equatorial Pacific since 1992.It is a challenge not only to the dynamic models but also to the understanding of the ENSO cycle mechanism.This paper examines multiple time-space scales of the ocean-atmosphere interactions and potential prediction ability of ENSO event by using data analysis and model study.