Spherical Quadrilateral to Map Scale Conversion

1989 ◽  
Vol 16 (1) ◽  
pp. 54-54 ◽  
Author(s):  
W. Tobler
Keyword(s):  
Map Scale

scholarly journals Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

2019 ◽  
Vol 11 (14) ◽  
pp. 1675 ◽  
Author(s):  
Tomás ◽  
Pagán ◽  
Navarro ◽  
Cano ◽  
Pastor ◽  
...  
Keyword(s):  
Regional Scale ◽  
Central Italy ◽  
Geographical Information ◽  
External Information ◽  
Automatic Identification ◽  
Persistent Scatterer Interferometry ◽  
Active Deformation ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Map Scale

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5,000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale.

Elements of Map-Scale Structure

1999 ◽  
pp. 1-32
Author(s):  
Richard H. Groshong
Keyword(s):  
Scale Structure ◽  
Map Scale

scholarly journals Orienteering in Geography Education in Japanese High School

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Taketo Kobayashi
Keyword(s):  
High School ◽  
Learning Effect ◽  
Geography Education ◽  
School Education ◽  
Learning System ◽  
Map Learning ◽  
The Core ◽  
Learning Outdoors ◽  
Good Learning ◽  
Map Scale

<p><strong>Abstract.</strong> Orienteering, a map activity, has been described as effective in learning geography in school education. When dealing with orienteering in school education, it is learning outdoors different from ordinary classroom lessons. Also, the environment surrounding school education differs from country to country. From this, it is important to show the practice of orienteering in school education in each country. In this research, I described the practice of orienteering in geography education of Japanese high schools in the following three viewpoints. The three viewpoints are the significance of orienteering in geography education, learning system of orienteering in geography education, examples of orienteering in geography education at school. The main points are as follows. <ol> <li>The skills given by orienteering are the basis of map learning and field learning in geography education.</li> <li>Learning system of orienteering is related to the map learning and field learning perspective, such as related to the map-scale linked with place.</li> <li>Orienteering practice in regular geography class at school grounds is the core, and good learning effect can be obtained. After this, orienteering can be expanded in a wide variety of directions.</li> </ol></p>

scholarly journals Supplemental Material: Quantifying shortening across the central Appalachian fold-thrust belt, Virginia and West Virginia, USA: Reconciling grain-, outcrop-, and map-scale shortening

2020 ◽  
Author(s):  
D. Lammie ◽  
et al.
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
Thickness Variation ◽  
Sample Mean ◽  
Appalachian Plateau ◽  
Scale Layer ◽  
Vertical Bars ◽  
Map Scale ◽  
Great Valley ◽  
Western Limb

Plate 1. (A and B) Balanced (A) and restored (B) cross section A-A' extending from the eastern Great Valley westward to the Burning Spring anticline (Fig. 1). Total deformed length (274 km) and undeformed restored length (346 km) are measured from a pin line east of the extent of documented map-scale shortening on the Appalachian Plateau, resulting in 78 km (23%) total shortening. (C) As shown, shortening in Upper Devonian through Permian rocks assumes 10% layer-parallel shortening (LPS) in the Appalachian Plateau and across the Appalachian front (to thick vertical bar) and 25% LPS in the Valley and Ridge (region between thick vertical bars). Shortening in the Great Valley requires 35% LPS, compared to the >50% LPS measured in that region (Wright and Platt, 1982). Cross sections drawn with no vertical exaggeration; Circled numbers—duplex numbers; Fm–Formation; Gp—Group. Plate 2. Geologic cross section divided into 16 sequentially numbered intervals (circled numbers above the cross section) spanning from the western limb of the Burning Springs anticline eastward to the Great Valley. Locations of each of the 40 samples used to constrain grain-scale layer-parallel shortening (LPS) are shown as small white dots projected into the line of section; calculated LPS (as a percentage) are shown above each sample. Mean LPS values for each interval are summarized in Table 2. (A) Cross section constructed to minimize the amount of unit thickness variation in the Reedsville-Martinsburg Formations. Balancing this section requires 10% outcrop-scale shortening between the Elkins Valley anticline and the boundary between the Valley and Ridge and Great Valley. (B) Cross section constructed to minimize contributions from outcrop-scale shortening. Balancing this section requires 5% outcrop-scale shortening between the Elkins Valley anticline and the boundary between the Valley and Ridge and Great Valley. Cross sections drawn with no vertical exaggeration; circled numbers—duplex numbers; Fm—Formation; Gp—Group.

scholarly journals ACCELERATION OF TOPOGRAPHIC MAP PRODUCTION USING SEMI-AUTOMATIC DTM FROM DSM RADAR DATA

2016 ◽  
Vol XLI-B7 ◽  
pp. 47-54
Author(s):  
Aldino Rizaldy ◽  
Ratna Mayasari
Keyword(s):  
Conventional Method ◽  
Point Cloud ◽  
Radar Data ◽  
Stereo Image ◽  
Human Operator ◽  
Topographic Map ◽  
Tropical Area ◽  
Check Points ◽  
Map Scale ◽  
Government Institution

Badan Informasi Geospasial (BIG) is government institution in Indonesia which is responsible to provide Topographic Map at several map scale. For medium map scale, e.g. 1:25.000 or 1:50.000, DSM from Radar data is very good solution since Radar is able to penetrate cloud that usually covering tropical area in Indonesia. DSM Radar is produced using Radargrammetry and Interferrometry technique. The conventional method of DTM production is using “stereo-mate”, the stereo image created from DSM Radar and ORRI (Ortho Rectified Radar Image), and human operator will digitizing masspoint and breakline manually using digital stereoplotter workstation. This technique is accurate but very costly and time consuming, also needs large resource of human operator. Since DSMs are already generated, it is possible to filter DSM to DTM using several techniques. This paper will study the possibility of DSM to DTM filtering using technique that usually used in point cloud LIDAR filtering. Accuracy of this method will also be calculated using enough numbers of check points. If the accuracy meets the requirement, this method is very potential to accelerate the production of Topographic Map in Indonesia.

scholarly journals COMPARISON OF SEMI AUTOMATIC DTM FROM IMAGE MATCHING WITH DTM FROM LIDAR

2016 ◽  
Vol XLI-B3 ◽  
pp. 373-380
Author(s):  
Aji Rahmayudi ◽  
Aldino Rizaldy
Keyword(s):  
Image Matching ◽  
Point Cloud ◽  
Statistical Data ◽  
Aerial Images ◽  
Mountainous Terrain ◽  
Topographic Map ◽  
Matching Algorithm ◽  
Time Calculation ◽  
Accuracy Difference ◽  
Map Scale

Nowadays DTM LIDAR was used extensively for generating contour line in Topographic Map. This method is very superior compared to traditionally stereomodel compilation from aerial images that consume large resource of human operator and very time consuming. Since the improvement of computer vision and digital image processing, it is possible to generate point cloud DSM from aerial images using image matching algorithm. It is also possible to classify point cloud DSM to DTM using the same technique with LIDAR classification and producing DTM which is comparable to DTM LIDAR. This research will study the accuracy difference of both DTMs and the result of DTM in several different condition including urban area and forest area, flat terrain and mountainous terrain, also time calculation for mass production Topographic Map. From statistical data, both methods are able to produce 1:5.000 Topographic Map scale.

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