Mapping files
The Ultimate List of GIS Formats and Geospatial File Extensions - GIS Geography
The Ultimate List of GIS Formats and Geospatial File Extensions
Including function calls in error messages — topic-error-call
Starting with rlang 1.0, abort() includes the erroring function in the message by default:
my_function <- function() {
abort("Can't do that.")
}
my_function()
#> Error in `my_function()`:
#> ! Can't do that.
This works well when abort() is called directly within the failing function. However, when the abort() call is exported to another function (which we call an "error helper"), we need to be explicit about which function abort() is throwing an error for.
This works well when abort() is called directly within the failing function. However, when the abort() call is exported to another function (which we call an "error helper"), we need to be explicit about which function abort() is throwing an error for.
There are two main kinds of error helpers:
Simple abort() wrappers. These often aim at adding classes and attributes to an error condition in a structured way:
stop_my_class <- function(message) {
abort(message, class = "my_class")
}
Input checking functions. An input checker is typically passed an input and an argument name. It throws an error if the input doesn't conform to expectations:
check_string <- function(x, arg = "x") {
if (!is_string(x)) {
cli::cli_abort("{.arg {arg}} must be a string.")
}
}
To fix this, let abort() know about the function that it is throwing the error for by passing the corresponding function environment as the call argument:
Cartographic boundary
Chapter 6 Mapping Census data with R | Analyzing US Census Data
Data from the United States Census Bureau are commonly visualized using maps, given that Census and ACS data are aggregated to enumeration units. This chapter will cover the process of map-making...
Chapter 5 Census geographic data and applications in R | Analyzing US Census Data
As discussed in previous chapters of this book, Census and ACS data are associated with geographies, which are units at which the data are aggregated. These defined geographies are represented in...
Generating Area's of Interest
A consistent tool kit for forward and reverse geocoding and defining boundaries for spatial analysis.
Reinder - Cursor for databases
2255 STONE MOUNTAIN LITHONIA RD, LITHONIA, GA 30058 | Climate Risk Report | First Street
2255 STONE MOUNTAIN LITHONIA RD, LITHONIA, GA 30058 has risk from flooding, risk from wildfire, and risk from windstorms
publiclab/leaflet-environmental-layers: Collection of different environmental map layers in an easy to use Leaflet library, similar to https://github.com/leaflet-extras/leaflet-providers#leaflet-providers
Collection of different environmental map layers in an easy to use Leaflet library, similar to https://github.com/leaflet-extras/leaflet-providers#leaflet-providers - publiclab/leaflet-environmenta...
R as an MCP server
OpenTopography API
Bdl faqs local hpis
rspatialdata
Satellite satellite
Windy: Wind map & weather forecast
Comprehensive ESF and All Hazards Dashboard
Application for viewing GEMA ESF and Hazards Dashboards
PROD - NFHL - WMA
Data from Flood Insurance Rate Maps (FIRMs) where available digitally.
USA Flood Hazard Areas
This layer displays Flood Hazard Areas from the Flood Insurance Rate Map created by the Federal Emergency Management Agency, updated by Esri annually.
FEMA Geospatial Resource Center Content Gallery
Category Gallery to view FEMA Geospatial Resource Center content by category. App linked through GRC Hub site
FEMA Geospatial Resource Center Content Gallery
Category Gallery to view FEMA Geospatial Resource Center content by category. App linked through GRC Hub site
FEMA Geospatial Resource Center Content Gallery
Category Gallery to view FEMA Geospatial Resource Center content by category. App linked through GRC Hub site
FEMA Geospatial Resource Center
FEMA GIS supports the emergency management community with world-class geospatial information, services, and technologies to prepare for, protect against, respond to, recover from and mitigate against all hazards.
MyGeodata Converter | MyGeodata Cloud
MyGeodata Converter - Convert and transform GIS/CAD data to various formats and coordinate systems, like SHP, KML, KMZ, TAB, CSV, GeoJSON, GML, DGN, DXF...
Cartographic Boundary Files - Shapefile
View the cartographic boundary files in shapefile format from 2018 and previous years.
GeoJSON and KML data for the United States
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...
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.
USEPA/elevatr: An R package for accessing elevation data
An R package for accessing elevation data
Spatial data with terra — R Spatial