![]() ![]() Thus, if the data are not rectangular (i.e. Notice that the spatial extent represents the rectangular area that the data cover. The spatial extent of vector data which you will learn next week. Image Source: National Ecological Observatory Network (NEON). ![]() points OR an image that is rotated in some way) the spatial extent covers portions of the dataset where there are no data. The spatial extent of a raster or spatial object is the geographic area that the raster data covers. Next, you’ll learn about spatial extent of your raster data. While the horizontal units often match the vertical units of a raster they don’t always! Be sure the check the metadata of your data to figure out the vertical units! Spatial Extent Important: You are working with lidar data which has a Z or vertical value as well. For example, if you wish to know the units of the EPSG code above, you can do the following: This can be used with rasterio in order to determine the metadata for a given EPSG code. +proj=utm +zone=18 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 Converting EPSG to Proj4 in PythonĪ python package for this class called ‘earthpy’ contains a dictionary that will help you convert EPSG codes into a Proj4 string. However on the website you can also view the proj4 string which will tell you a bit more about the horizontal units that the data are in. This means that the projection information is represented by a single number. The CRS format, returned by python, is in a EPSG format. The UTM zones across the continental United States. In this case you are using UTM zone 13 North.ĭigging deeper you can view the proj 4 string which tells us that the horizontal units of this project are in meters ( m). Next, you can look that EPSG code up on the spatial website to figure out what CRS it refers to and the associated units. The CRS EPSG code for your lidar_dem object is 32613. crs # Assign crs to m圜RS object - this is just an example of how you would do that You can view the CRS string associated with your Python object using the crs() method.Ī_crs = lidar_dem. View Raster Coordinate Reference System (CRS) in Python Thus, it’s important when working with spatial data in a program like Python to identify the coordinate reference system applied to the data and retain it throughout data processing and analysis. For this week, just remember that data from the same location but saved in different coordinate references systems will not line up in any GIS or other program. You will discuss Coordinate Reference systems in more detail in next weeks class. Corey, What Makes Spatial Data Line Up On A Map? These differences are a direct result of the calculations used to "flatten" the data onto a 2-dimensional map. Notice the differences in shape associated with each different projection. Maps of the United States in different projections. It also tells Python what mathematical method should be used to “flatten” or project the raster in geographic space. The Coordinate Reference System or CRS of a spatial object tells Python where the raster is located in geographic space. On this page, you will learn about three important spatial attributes associated with raster data that in this lesson: Access spatial metadata of a raster dataset in Python. ![]()
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