02-AREAS

02-AREAS

Chapter 9 Making maps with R | Geocomputation with R
Chapter 9 Making maps with R | Geocomputation with R
Prerequisites This chapter requires the following packages that we have already been using: library(sf) library(terra) library(dplyr) library(spData) library(spDataLarge) The main package used in...
·r.geocompx.org·
Chapter 9 Making maps with R | Geocomputation with R
Understanding Your Topographic Map Maker
Understanding Your Topographic Map Maker
The first-ever topographic maps were said to have been formed by the British in the late 18th century, and soon after, the US followed suit. Back then, the US had a department called the “Topographical Bureau of the Army,” which used these maps to plan tactical strategies during the War of 1812. However, even when the war ended, our interest in topography remained.
The term “topography” comes from a combination of two Greek words: “topo,” which means place, and “graphia,” which means writing. It is used to describe the study of a region’s forms and features, primarily to show their relative positions and elevations. Topography could refer to the forms and features themselves or a depiction of them (such as a map).
Unlike traditional maps which only represent the land horizontally, one made with a topographic map maker will represent the land vertically as well. These maps, also referred to as topo maps, show the form and elevation of an area, including the location and shape of hills, valleys, mountains, streams, and other natural or human-made features.
Contour Lines
Contour lines are the primary way in which topographic maps depict elevation. These imaginary lines connect points of equal elevation in order to present three-dimensional information on a two-dimensional map. This allows the viewer to visualize the height and shape of mountains, the depth of canyons, and the location of flat plains.  To determine the exact elevation of a location, you’ll need to know the contour interval – the difference in elevation between two contour lines. This will vary depending on the map, but regardless, you can calculate them yourself fairly easily. First, find the bolded contour lines that contain a number. These are the index contours, and the number is the elevation at the line.  Then, count the number of contour lines between each index contour, and divide the difference in elevation by that number. For instance, if you had one index contour with an elevation of 7,800 five contour lines apart from another index with an elevation of 8,000, the contour interval would be 40 ( (8,000 - 7,800) / 5 = 40 ).
The contour lines produced by your topographic map maker are often used to determine the slope or steepness of an area. The lines will be spaced farther apart when the slope is gentle, and closer together when the slope is steep. This is because, in steep areas, the elevation will increase at a greater frequency, so the lines will appear closer together. A completely flat meadow will have no contour lines, while a vertical cliff will have contour lines that are stacked on top of one another.
Features
You can also use contour lines to identify features of the land.  Peaks and Depressions: The innermost ring at the center of several other rings will typically represent a peak, but in some cases, it could represent a depression. Valleys: A valley is a type of depression in which water could flow down (if water is present), and they can be identified by their V or U shaped contour lines that point towards higher elevation (the peak). Cliffs: When two or more lines join together to form a single line, they represent a cliff. However, if the change in elevation isn’t great enough to call for another contour line, the cliff may not appear on the map. Ridges: A ridge is a chain of mountains or hills that create a continuous summit for an extended distance. These can be identified by V or U shaped contours that point towards lower elevation.  Saddles: A saddle is a low spot between two higher points of elevation, and on a topographic map, they appear as hourglass shaped contour lines.
·id.land·
Understanding Your Topographic Map Maker
Urban Analytics in R | Nikhil Kaza
Urban Analytics in R | Nikhil Kaza
Course Description & Objectives This course is about different techniques used in assembling, managing, analysing and predicting using heterogeneous data sets in urban environments. These datasets are inherently messy and incomplete.
·nkaza.github.io·
Urban Analytics in R | Nikhil Kaza
moudey/Shell | DeepWiki
moudey/Shell | DeepWiki
This document provides a high-level introduction to the Nilesoft Shell repository, which implements a Windows File Explorer context menu extender. It covers the core system architecture, key component
·deepwiki.com·
moudey/Shell | DeepWiki
Fips
Fips
·transition.fcc.gov·
Fips
Flood Data Viewers and Geospatial Data
Flood Data Viewers and Geospatial Data
The National Flood Hazard Layer (NFHL) is a geospatial database that contains current effective flood hazard data. FEMA provides the flood hazard data to support the National Flood Insurance Program. You can use the information to better understand your level of flood risk and type of flooding.
·fema.gov·
Flood Data Viewers and Geospatial Data
An R Interface for Downloading, Reading, and Handling IPUMS Data
An R Interface for Downloading, Reading, and Handling IPUMS Data
An easy way to work with census, survey, and geographic data provided by IPUMS in R. Generate and download data through the IPUMS API and load IPUMS files into R with their associated metadata to make analysis easier. IPUMS data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from the IPUMS website .
·tech.popdata.org·
An R Interface for Downloading, Reading, and Handling IPUMS Data
ChartDB – Database schema diagrams visualizer
ChartDB – Database schema diagrams visualizer
Free and open-source database-diagram editor. Visualise and design your schema with a single query, then export clean DDL scripts.
·chartdb.io·
ChartDB – Database schema diagrams visualizer
Esri Geoportal Server | Open-Source Metadata Management
Esri Geoportal Server | Open-Source Metadata Management
Esri Geoportal Server is a free, open-source, stand-alone metadata catalog management app that enables discovery and use of geospatial resources such as datasets, raster data & web services.
·esri.com·
Esri Geoportal Server | Open-Source Metadata Management
Building a Large Geospatial Model to Achieve Spatial Intelligence
Building a Large Geospatial Model to Achieve Spatial Intelligence
At Niantic, we are pioneering the concept of a Large Geospatial Model that will use large-scale machine learning to understand a scene and connect it to millions of other scenes globally.
·nianticlabs.com·
Building a Large Geospatial Model to Achieve Spatial Intelligence
Klarety
Klarety
Empower geospatial data, deploy AI, automate satellite analysis - unveil insights, unify action
·klarety.ai·
Klarety
Julius AI | Your AI Data Analyst
Julius AI | Your AI Data Analyst
Julius is a powerful AI data analyst that helps you analyze and visualize your data. Chat with your data, create graphs, build forecasting models, and more.
·julius.ai·
Julius AI | Your AI Data Analyst