Mapping the spatial distribution of shade provision of street trees in Boston using Google Street View panoramas

Street trees provide shade and increase human thermal comfort during hot summer. In this study, we investigated the spatial distribution of shade provision of street trees in Boston, Massachusetts. The sky view factor (SVF), which influences the solar radiation to the ground and affects human thermal comfort, was used to indicate the contribution of street trees on shade provision. Google Street View (GSV) panoramas were used to calculate the photographic method based SVF (SVF_P), with the consideration of all kinds of obstructions within street canyons. A building height model was used to calculate the simulation based SVF (SVFs), with consideration of obstruction of building blocks only. Considering the fact that street trees and building blocks are the two major obstructions of radiation within street canyons, therefore, the difference between the two SVF estimation results can be considered as the shade provision of street trees. The results show that street trees help to decrease the SVF by 24.61% in Boston, Massachusetts. The shading level varies spatially in the study area. Generally, the southwestern area has much higher shading level than the north and the east. We further explored the shading variation among different socioeconomic groups in the study area. Result shows that Hispanics tend to live in neighborhoods with lower shading level. This study can help to provide a reference for future urban greening projects for global climate change adaption.     

Google Earth和GPS在林业司法鉴定中的应用

涉林案件中,常见现场地表被剥离,而林业司法鉴定中需要确定被毁坏林地类型及面积.Google Earth影像往往是若干年前的卫星影像,保留着未破坏前的现场影像,故可利用手持GPS机定位现场边界,根据地理坐标准确定位出Goosle Earth影像,利用StitchMaps软件下栽保存,在GIS软件中,勾绘各地类边界、测算面...     

基于Google Earth Engine平台的关中冬小麦面积时空变化监测

以关中地区为研究区,基于Google Earth Engine(GEE)平台,根据冬小麦生育期内归一化植被指数(NDVI)时序曲线和物候特征,采用NDVI重构增幅算法和光谱突变斜率,构建了关中地区冬小麦提取模型并实现了冬小麦种植面积的提取。用农业统计面积验证提取结果表明:在市级和县级尺度上,决定系数R~2分别为0.82和0.62,一致性指标d分别为0.95和0.84,提取结果与实地调查数据的空间一致性精度为93.4%。结果显示:关中地区冬小麦主要分布在中部关中平原,冬小麦种植面积在2011—2017年呈下降趋势,减少了83.22×10~3 hm~2(8.47%)。综合考虑冬小麦NDVI时序曲线的"峰""谷"特征,具有一定的普适性,可为大面积连续年份冬小麦种植面积时空监测提供参考。     

基于GEE的山东省近30年农业大棚时空动态变化研究

针对精确获取大尺度空间范围内农业大棚的分布情况并进行长时间的序列动态监测存在数据量大、计算效率低、精度不高等问题,利用Google Earth Engine(GEE)云平台能够实现快速存取、实时处理海量卫星数据,基于多时相Landsat影像进行农业大棚时序光谱特征和纹理特征的自动提取,采用随机森林算法实现山东省农业大棚的遥感分类,从而生成了山东省近30年农业大棚的空间分布和时空动态变化图。结果表明,本文分类流程具有较高的分类精度,其平均总体精度达到91.63%,Kappa系数均值为0.8642。经分析,山东省农业大棚从1990年的6.67 km^2增加到2018年的9919.40 km^2,增长速度为354.03 km^2/a。     

基于Google Earth Engine平台的大湄公河次区域2001—2019年植被NPP时空变化分析

为探明大湄公河次区域植被净初级生产力(NPP)时空变化特征,基于Google Earth Engine(GEE)云计算平台,利用MOD17A3HGF NPP时序数据,采用线性趋势分析方法,分析了2001—2019年大湄公河次区域植被NPP的时空变化特征。结果显示:(1)2001—2019年间大湄公河次区域植被NPP总体较高,植被NPP年均值整体上变化趋势不显著,变化波动较大,且与年均温度有显著的负相关性;(2)大湄公河次区域植被NPP年均值具有较明显的空间分异性规律,大体呈中部高,南、西南部略低的状态,与其主要河流流域有着重要的联系;(3)植被NPP变化趋势呈现基本不变、轻微改善的特征,改善区域主要位于中国云南省与广西,轻微退化区域主要位于老挝中部和缅甸北部;(4)GEE云平台解决了本地平台数据下载与存储不便等问题,整个大湄公河次区域植被NPP时空变化的数据处理在10 min内完成,GEE云平台在大范围、长时间尺度的研究中体现出了强大的优势。     

Google Earth Engine平台支持下的南流江流域生态环境质量动态监测

为探究南流江流域2000—2019年生态环境质量的时空变化,利用Google Earth Engine（GEE）平台对2000—2019年南流江流域Landsat影像进行优化重构,并耦合植被绿度、湿度、地表温度、土壤干度等生态环境指标,构建遥感生态指数（RSEI）模型对南流江流域生态环境质量进行监测和评价。结果表明：2000—2019年南流江流域生态环境质量呈现逐年好转的态势,RSEI均值从2000年的0.543 4增长至2019年的0.636 4;南流江流域生态环境质量面积变化主要以中等生态风险等级向良生态等级转移为主,其中流域上游的中生态等级面积占比减少29.90个百分点,下游的良生态等级面积占比增加28.11个百分点。研究表明,使用GEE平台重构年度无云影像,可以对常年多云覆盖区的生态环境质量进行长时序的监测和评价。     

Google Earth应用于基建项目管理系统的研究与实现

Google Earth是Google公司开发的一款虚拟地球仪软件,它把卫星照片、航空照相和GIS布置在一个三维地球模型上,通过Google Earth插件及其JavaScript API可以将Google Earth三维地球模型嵌入网页中,同其他网页信息整合形成具有一定查询功能和3D展示功能的业务管理系统。本研究探讨了如何将Google Earth三维地球模型引入基建项目管理系统,实现基于B/S结构的三维实景基建项目管理系统,直观展示基建项目建设总体布局,并实现管理过程中各类信息的交互查询和显示。     

Where Is Agricultural Economics and AgriBusiness Research Information Published and Indexed? A Comparison of Coverage in Web of Knowledge,CAB Abstracts,EconLit, and Google Scholar

ABSTRACT

Identifying the best source of information to satisfy the needs of local clientele has always been the challenge facing collection development and instruction librarians. In order to provide users with the best possible access tool and source for comprehensive information, it is important that librarians be aware of the most productive sources of information in a field. This paper identifies where the bulk of agricultural economics research is published and indexed. It also ascertains whether Google Scholar is as productive in covering this information as CAB Abstracts and EconLit. The cited reference counts for the top 50 cited sources in Web of Knowledge and Google Scholar are also compared. The scatter of the journal literature in this field, based on the Library of Congress Subject Headings, is also provided. The study identified a broad range of article scattering in areas where agricultural economics and agribusiness materials are published. On the cited reference count, Google Scholar was as productive as the Web of Knowledge. Google Scholar is a free source of very useful information for cited references and other subject searches in the area of agricultural economics and could be used to complement traditional databases.     

Google Earth在公路设计中的应用

Google Earth(三维卫星地球图片)从发布开始就广泛应用于各相关领域,特别是公路勘察设计领域,现提出一种新的设计方法供同行参考:Google Earth与autocad联合在公路设计中的应用。     

将搜索进行到底--搜索引擎GOOGLE研究

Google作为世界上最有影响的搜索引擎，把用户检索的资料准确无误地反馈过来。本文探讨了其优越性和特色功能，并简要介绍搜索技巧。