Introduction to Ag Informatics

Outline for Today

• Spatial data
• Introduction to geometry in Python
• From geometry to spatial data
• Putting spatial data to map in Django

Install Python packages

conda activate asm591
conda install pyarrow
conda install -c conda-forge geopandas
        

You can find commands in module 6 -> lab 6

Spatial Data & Geographic Information System

Tools

• ArcGIS, QGIS, Google Earth
• Google Map, MapBox
• Python

Geometry fundamental element

Geometry fundamental element

Point

Geometry fundamental element

Line

Geometry fundamental element

Polygon

Geometry in action

Geometric Object In Python

Shapely

Manipulation and analysis of geometric objects in the Cartesian plane

import shapely.geometry as geo
point = geo.Point(0, 0)
line = geo.LineString([[0, 0], [1, 0]])
line.length
polygon = geo.Polygon(((0, 0), (0, 1), (1, 1), (1, 0)))
polygon.area
          

point_a = geo.Point(0, 0)
point_b = geo.Point(10, 5)
point_a.distance(point_b)
line_a = geo.LineString([[0, 0], [10, 0]])
line_b = geo.LineString([[5, -5], [5, 5]])
line_a.intersects(line_b)
line_a.intersection(line_b)
polygon.contains(point_a)
polygon.contains(line_b)

From Geometry To GeoSpatial

GeoPandas

            import geopandas as gpd
            world_df = gpd.read_file(
                    gpd.datasets.get_path('naturalearth_lowres')
            )
        

                world_df.plot()
            

            import numpy as np
            world_df['log_gdp'] = np.log(world_df['gdp_md_est'])
            world_df.plot("log_gdp")
        

            world_df = world_df.to_crs(
                "+proj=eck4 +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs"
            )
            world_df.area
        

Open Data Source

• ArcGIS
• Opendatasoft
• Indiana Map
• US Census
• Free GIS Data

Common File types

• ShapeFile (.prj + .dbf + .shp + .shx)
• GeoJSON
• KML
• GeoDatabase

Questions?

License

• Attribution Recommendation: Introduction to Agricultural Informatics Course", Tam Bureetes, Purdue University. Available at https://github.com/ag-informatics/ag-informatics-course. Licensed by CC BY-NC-SA 4.0.

This course is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. This is a human-readable summary of (and not a substitute for) the license. Official translations of this license are available in other languages.

You are free to:

• Share — copy and redistribute the material in any medium or format
• Adapt — remix, transform, and build upon the material

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