What Is Digital Mapping ? Mapping Using Digital Electronics and Information Technology (IT) Tools: (Pen Tablet Portable PC’S and Digital Base Maps)

Total Page:16

File Type:pdf, Size:1020Kb

What Is Digital Mapping ? Mapping Using Digital Electronics and Information Technology (IT) Tools: (Pen Tablet Portable PC’S and Digital Base Maps) EPS 101/271 Lecture 10: Introduction to Digital Mapping Systems What are Digital Mapping Systems ? What are their educational and professional advantages ? How mapping software works: the visual user interface of GeoMapper/PenMap Digital base maps GPS devices (theory) An exciting advance with Classroom overview of many rewards, requires GeoMapper use in the field paying attention, following Lecture directions, personal Demonstration responsibility, and respect for Student use equipment – eg. UCSB What is Digital Mapping ? Mapping using digital electronics and information technology (IT) tools: (pen tablet portable PC’s and digital base maps) How different is it from Geographic Information Systems (GIS) ? GIS have 2 sources of information: - primary (newly-created data) made by digital or conventional mapping methods - secondary (digitizing old -existing data) until now GIS has largely dealt with secondary data 1 Purposes of Digital Mapping: Is the front end or data capture part of GIS systems- creating primary information Mapping- implementing the science of geology Increase overall productivity of mappers by improving: Accuracy in positioning (location) SdfSpeed of mapp ing Assisted standardization Integration of a variety of digital base maps Improved 3-D visualization & interpretation One-step “paperless” map production Educational Goals: Provide an enabling technology to advance the learning process of mapping and synthesis Reduce uncertainties and hesitancy to commit ideas to a map b ecause of diffi cu lti es i n positioning Improve mapping skills so that confidence builds as successful experiences reinforces skills Encourage insightful use of available IT data, not entertain students with mere gadgets Better preparation for professional careers 2 Educational strategy: Initiate teaching mapping using traditional paper and pencil methods Simple, fast, inexpensive- shows what is out there Digital instrumentation can interfere with learning basic geological skills and concepts Transition to digital mapping tools Use project oriented discovery learning- not show and tell Components Color pen table PC computer: Fujitsu Stylisitc 5000 Pen Tablet PC, 1.2GHz/10.4”reflective screen, 512 MB Memory 40 GB hard drive Mapping program (GeoMapper of UC Berkeley and PenMap of Strata Software, Bradford, England) Digital media Base maps: topographic, color orthophotos, epicenters EPS 118- plus gravity, magnetics, glacial geology, epicenters Real-time GPS for each student team integrated with mapping program and digital maps (not hand-held GPS) 3 Turn brightness to zero when outdoors- extend battery life and use only solar power Turn sounds off to extend battery life 4 US GlobalSat BC 337 GPS GPS http://www.usglobalsat.com/p-140-bc-337.aspx Frequency: L1, 1575.42MHz US Globalsat BC-337 GPS receiver with compact flash 20 channel AT-65 external antenna GPS accuracy depends on: Type of GPS unit The number of satellites visible to the receiver Strength of satellite signals (S/N) Geometric position of satellite in the sky (constellation) Differential corrections- require an unobstructed view of the southern sky- suggestion: put your external GPS antenna on your shoulder Face north when taking GPS readings- this automatically gives you the best chance of receiving the DGPS signals. 5 6 Satellite Geometry given as: HDOP = Horizontal dilution of precission Good GPS fix but Not differentially corrected 7 HGOP =1 is ideal Have to ppyosition yourself so that the GPS receiver is in direct line With a satellite sending down the Differential corrections- next time Orbits: ISS- International Space Station GPS- Global Positioning Systems Geosynchronous satellites Earth Revolutions around Earth each day (35,790 km) 8 Orbits http://asd-www.larc.nasa.gov/SCOOL/orbits.html What is our lat and long? http://www.lyngsat.com/tracker/g15.html httppyg://www.lyngsat.com/tracker/anikf1r.htm To find elev and azimuth Of Geostationary satellite: 9 WAAS Differential Correction: http://www.usglobalsat.com/t-what_is_waas.aspx 10 Consequence: Software has to integrate and manage these tools and support science as we practice it as a creative process without interfering with workflow The product , a geological map and data base , is a complex scientific record created incrementally & interactively Mapping is not: A sequence of discrete point measurements Mapping is a continuum of activities requiring one to keep oriented, located, and continually aware of their stratigraphic, lithologic and structural environment. A digital mapping system must support this continuum and implement the routine that mappers deem convenient and essential to natural workflow 11 The visual user interface constitutes the entirety of the link between the geologist and the digital tools The link must be familiar, logical, scientifically functional, comprehensive and easy to personalize for each new area Two main alternative digital mapping systems: Full PC pen tablets running Windows getting faster, smaller and less expensive best for “data fusion” Palm units running Windows CE (data collectors) GeoMapper by Brimhall, Vanegas and Lerch (UCB) Built around the workflow activities of the scientist in the field using the visual user interface as sole control. Vilisual user interf ace h as sci iififilientific functionality providing: Definition of mapping project areas with legends Point and Click- no programming required of user Logical and self explanatory workflow mapping system without menus nor gaps that stop users None of the file transfer of palm CE units 12 GeoMapper Project Manager lets the user define the local stratigraphic column GeoMapper Legend Maker Takes < 1 hour using only point and click A hard copy of the legend can be printed Removes s serious barrier to independent digital mapping User-selected color infill Selectable pre-programmed lithology patterns patterns (Compton, 1985) 13 Button Tool bars Tool bars are arrays of buttons which can be touched by the pen stylus to bring up groups of buttons organized in a logical fashion but providing flex ibility i n sequence Saves screen space for the map and improves speed Lithology structure Formations Mineralization, alteration and sampling sites GeoMapper Color-coded frequency of use hierarchy stop light & left to right Go ahead: Open map, legend, map, sample, export Caution: Undo, erase, redraw, zoom, lost Stop- pay attention: Save, Exit Base maps, ortho-photos, GPS, laser Copyright UC Regents 1999 Mapping workflow continuum Go ahead Tool bars Samples 14 Button Tool bars bring up groups of buttons organized in a logical fashion but providing flexibility in sequence Lithology Formations Structure Mineralization Alteration Mapping on a Vector Topographic Map Outcrop lithology mapping preserves the prime data Colored formation show regional distribution 15 GPS- A Legacy of the Cold war Satellite navigation system using triangulation from 27 satellites orbiting 11,000 miles above the earth Funded and controlled by the Department of Defense (DOD) Coded satellite signals that can be processed in a ground receiver to compute position, velocity and time Method of Ranging Distance = Velocity * Time Velocity = speed of light (3x10exp 10 cm/sec) Time is the unknown Travel times are used to compute distance and are very short 0.06 secs Syy()nchronized to Universal Coordinated Time (UTC): Greenwich Mean Time plus a few seconds (suburb of London on the Thames River , Long. = 0 arbitrarily Accurate atomic clocks on each satellite 16 ISS Moon GPS Geosynchronous 16 2 1 1/30 revolutions around the Earth per day Mean diameter of Earth 12,756 km GPS satellites 20,000 km orbit circle Earth 2 times per day International Space Station in Low Earth Orbit 361-437 km above Earth (15-16 Earth orbits per day) Geosynchronous Earth orbit 35,786 km (5.5 Earth diameters) Mean diameter of Moon 3,476 km (30 days to make one Earth revolution) Mean distance Earth to Moon 384,400 km (30 times Earth's diameter) Operational Modes Now with noise turned off, autonomous GPS accuracy is about +/-5-10 m (15-30 feet) Atmospheric conditions in ionosphere and multi -pathing cause another error by bouncing off other objects before arriving at the receiver Differential Corrections Software algg()orithms called Virtual Base Stations (VBS) Calculate differential corrections that a base station would generate if it were at the receiver location 17 Mathematical requirements x, y, z, time are 4 unknowns Need 4 independent equations At least 4 satellites are needed to get a 3 dimensional location of x, y and z The more satellites the better Our GPS units required at least 4 satellites with a signal to noise ratio about 32 Satellites Visible 18 Types of base (back) maps • No base map. PenMap automatically uses Universal Transverse Mercator (UTM) in meter units. No map prep required • Raster (scanned) bit map image (*BMP) file of a topographic map, ortho-rectified air photo, satellite image. QliffQuality suffers w hen map is enlarged • Vector map of topography made from scanned map or stereo air photos in 2- D or 3-D Digital Elevation model (DEM) • •DiBothgggp()ital raster raster andgrap vectorhics (DRGsimultaneousl) y – eg. An ortho-photo and a topographic map in digital (vector) •ESRIform, Shapefile or a geophysical map all 4 types at once or any combination Topography, orthophoto, geophysics, magnetics, gravity), geography ... Mapping on a Vector Topo Map Outcrops 19 Advantages of Ortho-Images • Since they are ortho-rectified … • They serve as accurate background maps which preserve position,
Recommended publications
  • Digital Mapping & Spatial Analysis
    Digital Mapping & Spatial Analysis Zach Silvia Graduate Community of Learning Rachel Starry April 17, 2018 Andrew Tharler Workshop Agenda 1. Visualizing Spatial Data (Andrew) 2. Storytelling with Maps (Rachel) 3. Archaeological Application of GIS (Zach) CARTO ● Map, Interact, Analyze ● Example 1: Bryn Mawr dining options ● Example 2: Carpenter Carrel Project ● Example 3: Terracotta Altars from Morgantina Leaflet: A JavaScript Library http://leafletjs.com Storytelling with maps #1: OdysseyJS (CartoDB) Platform Germany’s way through the World Cup 2014 Tutorial Storytelling with maps #2: Story Maps (ArcGIS) Platform Indiana Limestone (example 1) Ancient Wonders (example 2) Mapping Spatial Data with ArcGIS - Mapping in GIS Basics - Archaeological Applications - Topographic Applications Mapping Spatial Data with ArcGIS What is GIS - Geographic Information System? A geographic information system (GIS) is a framework for gathering, managing, and analyzing data. Rooted in the science of geography, GIS integrates many types of data. It analyzes spatial location and organizes layers of information into visualizations using maps and 3D scenes. With this unique capability, GIS reveals deeper insights into spatial data, such as patterns, relationships, and situations - helping users make smarter decisions. - ESRI GIS dictionary. - ArcGIS by ESRI - industry standard, expensive, intuitive functionality, PC - Q-GIS - open source, industry standard, less than intuitive, Mac and PC - GRASS - developed by the US military, open source - AutoDESK - counterpart to AutoCAD for topography Types of Spatial Data in ArcGIS: Basics Every feature on the planet has its own unique latitude and longitude coordinates: Houses, trees, streets, archaeological finds, you! How do we collect this information? - Remote Sensing: Aerial photography, satellite imaging, LIDAR - On-site Observation: total station data, ground penetrating radar, GPS Types of Spatial Data in ArcGIS: Basics Raster vs.
    [Show full text]
  • Direct-To-Digital Mapping Methodology: a Hands-On Guidebook for Applying Google Earth
    Steven DeRoy / The Firelight Group / January 2016 Direct-To-Digital Mapping Methodology: A Hands-on Guidebook for Applying Google Earth Copyright © Steven DeRoy and the Firelight Group (www.thefirelightgroup.com) 1 | Page Table of Contents ACKNOWLEDGEMENTS 4 PURPOSE OF THIS GUIDE 4 PREPARE TO MAP 5 DOWNLOAD AND INSTALL GOOGLE EARTH 5 SET UP YOUR FILE FOLDERS ON YOUR COMPUTER 5 INTERVIEW ROOM SETTING 5 START THE INTERVIEW 5 INTERVIEW CHECK LIST 6 INTERVIEW KIT 6 SET UP GOOGLE EARTH 6 CHECK YOUR EQUIPMENT 6 INFORM THE PARTICIPANT AND MAKE THEM COMFORTABLE 6 BEFORE STARTING THE INTERVIEW 7 REMINDERS DURING THE INTERVIEW 7 INTERVIEW OVERVIEW 8 INTRODUCTIONS 8 MAPPING 8 INTERVIEW 8 STORAGE OF RESULTS 8 MAPPING NOTES 9 OVERVIEW OF GOOGLE EARTH 10 WHAT IS GOOGLE EARTH? 10 WHY USE GOOGLE EARTH? 10 HOW ARE GOOGLE EARTH AND MAPS DIFFERENT? 10 INTRODUCTION TO THE GOOGLE EARTH INTERFACE 11 NAVIGATING IN GOOGLE EARTH 11 SET UP YOUR ENVIRONMENT 12 THE “PLACES” PANEL 13 SET UP FOLDERS TO STORE YOUR DATA 13 ORGANIZE YOUR FOLDERS 14 UNDERSTANDING SCALE 14 Copyright © Steven DeRoy and the Firelight Group (www.thefirelightgroup.com) 2 | Page HOW TO MAP IN GOOGLE EARTH 16 WHAT TO RECORD FOR EACH SITE 16 ADDING POINTS (PLACEMARKS) 16 ADDING LINES (PATHS) 18 ADDING AREAS (POLYGONS) 19 EDITING MAPPED DATA 20 INTERVIEWS CONDUCTED WITH NO MAPPING DATA 20 OVERLAYING DATA FROM PAST STUDIES 21 CLOSING OFF THE INTERVIEW 22 SAVING KMZ FILES 22 COPY AND SAVE ALL DIGITAL AUDIO AND VIDEO FILES TO YOUR LAPTOP/COMPUTER 23 BACKUP YOUR FILES 23 USEFUL RESOURCES 24 Copyright © Steven DeRoy and the Firelight Group (www.thefirelightgroup.com) 3 | Page Acknowledgements Steven DeRoy, Director of the Firelight Group, produced this comprehensive guidebook.
    [Show full text]
  • Digital Mapping Techniques ‘02— Workshop Proceedings
    cov02 5/20/03 3:19 PM Page 1 So Digital Mapping Techniques ‘02— Workshop Proceedings May 19-22, 2002 Salt Lake City, Utah Convened by the Association of American State Geologists and the United States Geological Survey Hosted by the Utah Geological Survey U.S. GEOLOGICAL SURVEY OPEN-FILE REPORT 02-370 Printed on recycled paper CONTENTS I U.S. Department of the Interior U.S. Geological Survey Digital Mapping Techniques ʻ02— Workshop Proceedings Edited by David R. Soller May 19-22, 2002 Salt Lake City, Utah Convened by the Association of American State Geologists and the United States Geological Survey Hosted by the Utah Geological Survey U.S. GEOLOGICAL SURVEY OPEN-FILE REPORT 02-370 2002 II CONTENTS CONTENTS III This report is preliminary and has not been reviewed for conformity with the U.S. Geological Survey editorial standards. Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply endorsement by the U.S. Government or State governments II CONTENTS CONTENTS III CONTENTS Introduction By David R. Soller (U.S. Geological Survey). 1 Oral Presentations The Value of Geologic Maps and the Need for Digitally Vectorized Data By James C. Cobb (Kentucky Geological Survey) . 3 Compilation of a 1:24,000-Scale Geologic Map Database, Phoenix Metropoli- tan Area By Stephen M. Richard and Tim R. Orr (Arizona Geological Survey). 7 Distributed Spatial Databases—The MIDCARB Carbon Sequestration Project By Gerald A. Weisenfluh (Kentucky Geological Survey), Nathan K. Eaton (Indiana Geological Survey), and Ken Nelson (Kansas Geological Survey) .
    [Show full text]
  • Digital Geologic Mapping Methods
    INTERNATIONAL JOURNAL OF GEOLOGY Issue 3, Volume 2, 2008 Digital geologic mapping methods: from field to 3D model M. De Donatis, S. Susini and G. Delmonaco Abstract—Classical geologic mapping is one of the main techniques software 2DMove and 3DMove by Midland Valley Exploration Ltd. used in geology where pencils, paper base map and field book are the This paper reports a case study of digital mapping carried out in traditional tools of field geologists. In this paper, we describe a new the Southern Apennines. This work is part of an ENEA project, method of digital mapping from field work to buiding three funded by the Italian Ministry of University and Research, devoted to dimensional geologic maps, including GIS maps and geologic cross- heritage sites prone to landslide risk where local-scale geologic and sections. The project consisted of detailed geologic mapping of the geomorphic mapping is fundamental in the preliminary stage of the are of Craco village (Matera - Italy). The work started in the lab by project. implementing themes for defining a cartographic base (aerial photos, topographic and geologic maps) and for field work (developing II. Study area symbols for outcrops, dip data, boundaries, faults, and landslide The study area (Fig. 1) is located in the Southern Apennines, types). Special prompts were created ad hoc for data collection. All around Craco, a small village in the Matera Province along a ridge data were located or mapped through GPS. It was possible to easily between the Bruscata and Salandrella stream. store any types of documents (digital pictures, notes, and sketches), linked to an object or a geo-referenced point.
    [Show full text]
  • Digital Earth Based on Metadata Electronic Maps Standard
    DIGITAL EARTH BASED ON METADATA ELECTRONIC MAPS STANDARD Alexander Martynenko 2 build., 44, Vavilova st., Moscow, 117333, Russia, Institute of Informatics Problems, Russian Academy of Sciences, [email protected] Digital Earth was at the center of attention at 19th International Cartographic Conference (Ottawa) and 1st International Symposium on Digital Earth (Beijing) in 1999 [1, 2]. The discussion raised in the papers on the theory of Metadata Standard Systems that could be used in International and National Spatial Information Infrastructures to establish Digital Earth still continues. We highly appreciate the essential contribution made by Chinese scientists: Zhao Yongping, Huang Fang, Guo Jingjun, Feng Quan, Cui Weihong. Since 1990s the Information Society is being created in Russia. Each member of this Society will be able to obtain complete and actual information, including geoinformation, in any point of geographical space, by means of Internet. Today it is obvious that this problem could be solved in most effective way by using electronic libraries of various intent, including electronic map libraries. Completeness, methods and form of geoinformation, temporal factors of the information supply can be considered as the main criteria for evaluating quality of the electronic geoinformation resources. In the process of creating the electronic geoinformation resources, standardization in the area of geoinformation technologies plays the main role. Today, at the boundary of millennia, the Global Geoinformatic Mapping (GGM) appears as the prior direction of scientific and technical progress. Its goal is the cartographic representation of the real world and creation of the global computer model of the Earth, comprised of millions of space images and electronic maps of various subjects and scales, themes and also reference information [3, 4].
    [Show full text]
  • Ogdc)—Release 6
    State of Oregon Oregon Department of Geology and Mineral Industries Ian P. Madin, Interim State Geologist README FILE FOR OREGON GEOLOGIC DATA COMPILATION (OGDC)—RELEASE 6 by Rachel L. Smith1 and Warren P. Roe1 2015 1 Formerly with Oregon Department of Geology and Mineral Industries, 800 NE Oregon St., Ste. 965, Portland, OR 97015 Oregon Geologic Data Compilation Release 6 DISCLAIMER This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information. This publication cannot substitute for site-specific investigations by qualified practitioners. Site-specific data may give results that differ from the results shown in the publication. Spatial inaccuracies exist in this data set, and some functionalities of Oregon Geologic Data Compilation have changed from previous versions due to the transition to an Esri®-formatted geodatabase. Known issues include topology errors, small spatial data gaps, typographical errors, incomplete metadata, and other minor errors. Oregon Department of Geology and Mineral Industries | Oregon Geologic Data Compilation, release 6 Published in conformance with ORS 516.030 For additional information: Administrative Offices 800 NE Oregon Street #28, Suite 965 Portland, OR 97232 Telephone (971) 673-1555 Fax (971) 673-1562 http://www.oregongeology.org http://egov.oregon.gov/DOGAMI/ Oregon Department of Geology
    [Show full text]
  • Using Digitized Spacecraft Film and a Revised Lunar Control Network for Photogrammetric Mapping
    USING DIGITIZED SPACECRAFT FILM AND A REVISED LUNAR CONTROL NETWORK FOR PHOTOGRAMMETRIC MAPPING Mark R. Rosiek R.L. Kirk B.A. Archinal T.L. Becker L. Weller B. Redding E. Howington-Kraus D. Galuszka U.S. Geological Survey 2255 N. Gemini Dr Flagstaff AZ 86001 [email protected] ABSTRACT This paper reports on the results of photogrammetric mapping with Lunar Orbiter, Apollo panoramic and Apollo metric camera digitized photographs using modern softcopy digital mapping techniques and a revised lunar control network to establish control. We will report on the differences between Digital Elevation Models (DEMs) collected from Lunar Orbiter, Apollo panoramic and metric camera digitized photographs. Our test area is the Rima Hadley region, which includes the Apollo 15 landing site. This area is covered by multiple sources of data that can be used for comparison and evaluation of accuracy. The original Lunar Orbiter photographs reconstructed in the 1960s had limited utility for mapping due to a stair-step offset in the reconstructed photographs. These images have been re- cently digitized and digitally reconstructed to fit the reseaux and the fiducials to the camera calibration data. The Apollo imagery was previously used to produce topographic maps using different control networks. These previous networks have kilometer-size offsets between them and were also limited in size and accuracy. A revised lunar con- trol network, the Unified Lunar Control Network 2005, improves the accuracy and the density of control points and includes solved-for for elevations of the control points. We find that all the image sets studied provide useful DEMs with minimal requirement for interactive editing but varying tradeoffs between area covered and resolution.
    [Show full text]
  • Digital Soil Mapping and GIS-Based Land Evaluation for Rice Suitability in Kilombero Valley, Tanzania
    Digital Soil Mapping and GIS-based Land Evaluation for Rice Suitability in Kilombero Valley, Tanzania DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Boniface Hussein John Massawe, M.S. Graduate Program in Environment and Natural Resources The Ohio State University 2015 Dissertation Committee: Dr. Brian Slater, Advisor Dr. Warren Dick Dr. Laura Lindsey i Copyrighted by Boniface Hussein John Massawe 2015 ii Abstract A GIS-based multi-criteria land evaluation was performed in Kilombero Valley, Tanzania in order to avail decision makers and farmers with evidence based decision support tool for improved and sustainable rice production in this important region for agricultural investment. Five most important criteria for rice production in the area were identified through literature search and discussion with local agronomists and farmers. The identified criteria were 1) soil properties, 2) surface water resources, 3) accessibility, 4) distance to markets, and 5) topography. Spatial information for these criteria for the study area was generated. To generate spatial soil information, field survey and lab analysis was conducted using base map generated from a legacy soil map and 30 m Digital Elevation Model (DEM). OSACA, a k-means based clustering application was used to perform distance metric numerical classification of soil profiles. The profiles were classified into 13 clusters. The clusters were demonstrated to be different from each other through comparison of modeled continuous vertical variability of selected attributes of modal soil cluster centroids by using equal area spline functions. Two decision tree based algorithms, J48 and Random Forest (RF) were applied to construct models to spatially predict the soil clusters using environmental correlates derived from 30 m DEM, 5 m RapidEye satellite ii image and legacy soil map using the scorpan digital soil mapping framework.
    [Show full text]
  • Digital Mapping of Peatlands
    Earth-Science Reviews 196 (2019) 102870 Contents lists available at ScienceDirect Earth-Science Reviews journal homepage: www.elsevier.com/locate/earscirev Digital mapping of peatlands – A critical review T ⁎ Budiman Minasnya, , Örjan Berglundb, John Connollyc, Carolyn Hedleyd, Folkert de Vriese, Alessandro Gimonaf, Bas Kempeng, Darren Kiddh, Harry Liljai, Brendan Malonea,p, Alex McBratneya, Pierre Roudierd,q, Sharon O'Rourkej, Rudiyantok, José Padariana, Laura Poggiof,g, Alexandre ten Catenl, Daniel Thompsonm, Clint Tuven, Wirastuti Widyatmantio a School of Life & Environmental Science, Sydney Institute of Agriculture, the University of Sydney, Australia b Swedish University of Agricultural Sciences, Department of Soil and Environment, Uppsala, Sweden c School of History & Geography, Dublin City University, Ireland d Manaaki Whenua - Landcare Research, Palmerston North, New Zealand e Wageningen Environmental Research, PO Box 47, Wageningen, the Netherlands f The James Hutton Institute, Scotland, United Kingdom g ISRIC – World Soil Information, PO Box 353, Wageningen, the Netherlands h Department of Primary Industries, Parks, Water, and Environment, Tasmania, Australia i Luke, Natural Resources Institute, Finland j School of Biosystems & Food Engineering, University College Dublin, Ireland k Faculty of Fisheries and Food Security, Universiti Malaysia Terengganu, Malaysia l Universidade Federal de Santa Catarina, Brazil m Natural Resources Canada, Canada n Natural Resources Conservation Service, United States Department of Agriculture, USA o Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia p CSIRO Agriculture and Food, Black Mountain ACT, Australia q Te Pūnaha Matatini, The University of Auckland, Private Bag 92019, Auckland 1010, New Zealand ABSTRACT Peatlands offer a series of ecosystem services including carbon storage, biomass production, and climate regulation.
    [Show full text]
  • Using Google's Cloud-Based Platform for Digital Soil Mapping
    Computers & Geosciences 83 (2015) 80–88 Contents lists available at ScienceDirect Computers & Geosciences journal homepage: www.elsevier.com/locate/cageo Case study Using Google's cloud-based platform for digital soil mapping J. Padarian n, B. Minasny, A.B. McBratney Faculty of Agriculture and Environment, Department of Environmental Sciences, The University of Sydney, New South Wales, Australia article info abstract Article history: A digital soil mapping exercise over a large extent and at a high resolution is a computationally expensive Received 2 January 2015 procedure. It may take days or weeks to obtain the final maps and to visually evaluate the prediction Received in revised form models when using a desktop workstation. To increase the speed of time-consuming procedures, the use 29 June 2015 of supercomputers is a common practice. GoogleTM has developed a product specifically designed for Accepted 30 June 2015 mapping purposes (Earth Engine), allowing users to take advantage of its computing power and the Available online 10 July 2015 mobility of a cloud-based solution. In this work, we explore the feasibility of using this platform for Keywords: digital soil mapping by presenting two soil mapping examples over the contiguous United States. We also Supercomputing discuss the advantages and limitations of this platform at its current development stage, and potential DSM improvements towards a fully functional cloud-based soil mapping platform. Cloud computing & 2015 Elsevier Ltd. All rights reserved. GlobalSoilMap Google Earth Engine 1. Introduction space). The so-called Scorpan factors can usually be represented in a digital form, usually as raster data. The mapping is achieved by Current soil mapping heavily depends on the use of technology building a spatial soil prediction function which relates observed and computers, starting with the use of computer-based geo- soil variables with Scorpan factors.
    [Show full text]
  • Improving the Visualization of Geospatial Data Using Google's
    Improving the Visualization of Geospatial Data Using Google’s KML THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Ebenezer Attua Odoi Jr Graduate Program in Geodetic Science and Surveying The Ohio State University 2012 Master's Examination Committee: Prof. Alan Saalfeld, Advisor Prof. Ralph Von Frese, Committee Member Copyright by Ebenezer Attua Odoi Jr 2012 Abstract The Geospatial community continues to search for effective tools that produce visualizations of the nature of the earth and its features. With the aid of geobrowsers like Google Maps and Google Earth, geoscientists can now tell their ‘tales’ in ways that nonscientists can grasp and respond to in terms of awareness, policy formulation, application development and integration in ventures that usher human existence forward. This thesis explores diverse visualization techniques using Google’s Keyhole Markup Language (KML) that will benefit the viewing of geological data. In the process the thesis will show the potential of geobrowsers and KML as a unified programming language. Though there has been a proliferation of digital map viewers like geobrowsers being developed, thematic mapping capabilities, unfortunately, has been left out. The thesis will explore how KML can be used to achieve thematic mapping, though KML itself was not specifically designed for this application. Current possibilities for making proportional symbol maps, chart maps, choropleth maps and animated maps with KML will be presented. The innovation of the thesis is the conversion of a database table into a thematic map, using proportional symbols to represent the data.
    [Show full text]
  • Mobile Mapping Mobile Mapping Mediamatters
    media Mobile Mapping matters Space, Cartography and the Digital Amsterdam University clancy wilmott Press Mobile Mapping MediaMatters MediaMatters is an international book series published by Amsterdam University Press on current debates about media technology and its extended practices (cultural, social, political, spatial, aesthetic, artistic). The series focuses on critical analysis and theory, exploring the entanglements of materiality and performativity in ‘old’ and ‘new’ media and seeks contributions that engage with today’s (digital) media culture. For more information about the series see: www.aup.nl Mobile Mapping Space, Cartography and the Digital Clancy Wilmott Amsterdam University Press The publication of this book is made possible by a grant from the European Research Council (ERC) under the European Community’s 7th Framework program (FP7/2007-2013)/ ERC Grant Number: 283464 Cover illustration: Clancy Wilmott Cover design: Suzan Beijer Lay-out: Crius Group, Hulshout isbn 978 94 6298 453 0 e-isbn 978 90 4853 521 7 doi 10.5117/9789462984530 nur 670 © C. Wilmott / Amsterdam University Press B.V., Amsterdam 2020 All rights reserved. Without limiting the rights under copyright reserved above, no part of this book may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form or by any means (electronic, mechanical, photocopying, recording or otherwise) without the written permission of both the copyright owner and the author of the book. Every effort has been made to obtain permission to use all copyrighted illustrations reproduced in this book. Nonetheless, whosoever believes to have rights to this material is advised to contact the publisher. Table of Contents Acknowledgements 7 Part 1 – Maps, Mappers, Mapping 1.
    [Show full text]