terraGIS – a web GIS for delivery of digital soil maps in cotton‐growing areas of Australia

Effective management of soil requires the spatial distribution of its various physical, chemical and hydrological properties. This is because properties, for example clay content, determine the ability of soil to hold cations and retain water. However, data acquisition is labour intensive and time‐consuming. To add value to the limited soil data, remote sensing (e.g. airborne gamma‐ray spectrometry) and proximal sensing, such as electromagnetic (EM) induction, are being used as ancillary data. Here, we provide examples of developing Digital Soil Maps (DSM) of soil physical, chemical and hydrological properties, for seven cotton‐growing areas of southeastern Australia, by coupling soil data with remote and proximal sensed ancillary data. A greater challenge is how to get these DSM to a stakeholder in a way that is useful for practical soil use and management. This study describes how we facilitate access to the DSMs, using a simple‐to‐use web GIS platform, called terraGIS. The platform is underpinned by Google Maps API, which is an open‐source development environment for building spatially enabled Internet applications. In conclusion, we consider that terraGIS and the supporting information, available on the sister web page ( http://www.terragis.bees.unsw.edu.au/ ), allow easy access to explanation of DSM of soil properties, which are relevant to cotton growers, farm managers, consultants, extension staff, researchers, state and federal government agency personnel and policy analysts. Future work should be aimed at developing error budget maps to identify where additional soil and/or ancillary data is required to improve the accuracy of the DSMs.     

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。     

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.     

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GEE的东南亚主产区橡胶林分布遥感提取

为遥感监测全球橡胶主产区橡胶的长势,选取橡胶产量最大的泰国、马来西亚、印度尼西亚三国,开展基于Google Earth Engine（GEE）的橡胶林分布遥感提取研究。通过目视解译选择典型样本区,根据Landsat 7多波段光谱特征、MODIS NDVI反映的植被物候特征建立分类回归树CART分类模型提取橡胶林分布。精度评价显示模型总体分类精度为95.8%,Kappa系数为0.94,生产者精度达到94.8%,用户精度为88.2%,达到较高水平。模型提取结果显示：橡胶林在泰国中部、南部半岛,马来半岛的东部和南部地区,苏门答腊岛分布较为集中,而泰国北部、加里曼丹岛及其他岛屿橡胶林相对稀疏。     

森林防火指挥系统、ArcGIS和Google Earth结合在新一轮退耕还林工程中的应用

在永平县新一轮退耕还林工程作业设计和管理中,利用森林防火指挥系统、ArcGIS10.2和Google Earth的功能优势互补、取长补短,完成工程地块定位、落实勾绘、面积求算、编辑成图等工作。结果表明以上3种软件(系统)结合易学易用、工作效率高、成本低、结果准确、在无地形图识图能力的情况下也能进行工程小班、地块空间位置定位识别、管理。文章简述了地块勾绘,数据格式转换,创建自定义地理(坐标)变换,投影变换,设计小班、地块数据编辑成图的方法和步骤,以期在同类工程中得到应用。     

密山至兴凯湖旅游公路冬季土方施工

本文叙述了冬季土方施工的方法、步骤和要点。     

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...     

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。     

土方机械落物保护结构动态仿真及试验

简述了土方机械落物保护结构的特点及性能要求,建立了落物保护结构受瞬态冲击响应的有限元结构动力学方程并提出了求解算法。以某装载机落物保护结构为例,建立了落物保护结构的非线性有限元模型,讨论了有限元网格划分及载荷施加方法,分析了落物保护结构的主要设计参数对冲击点最大位移及落锤速度和加速度的影响,并给出了更合理的结构。在试验台上对该装载机落物保护结构进行了落物冲击试验,试验结果和仿真结果吻合较好。落物保护结构的动态仿真为结构的设计提供了依据。