gssurgo 0.0.2

Python toolbox enabling an open source gSSURGO workflow

gssurgo

The gSSURGO data product contains multiple text format datasets referenced to a single raster grid. The raster grids are contained within file geodatabase archives and can only be extracted using ArcGIS (using the fileGDB driver).

This repo enables subsequent open source workflows with gSSURGO by extracting grids and aggregating the remaining data into a geopackage. This package enables specific queries of gSSURGO data, which are constructed in SQL, and subsequently merged with its corresponding (raster) grid.

Prereqs

• The intial tif (grid) extraction step requies the arcpy python module. This step assumes that a python executable linked to arcpy can be found at C:\Python27\ArcGIS10.3\python.exe. Edit bin/extract_gssurgo_tif to enable alternate locations.

• Remaining operations require a number of dependencies listed in environment.yml and requirements.txt. If using Anaconda, make sure you have the 64bit version. You can install an Anaconda virtual environment with:

conda env create -n gSSURGO -f environment.yml
source activate gSSURGO

Installation

# local install
# pip install -e  . 

# development install 
pip install git+git://github.com/jsta/gssurgo.git

# development upgrade
# pip install --upgrade git+git://github.com/jsta/gssurgo.git

Usage

1. Extract tif and build gpkgs

extract_gssurgo_tif 'path/to/gSSURGO_STATE.gdb/MapunitRaster_10m' 'path/to/STATE.tif'

import gssurgo
gssurgo.build_gpkg("path/to/gSSURGO_STATE.gdb", "path/to/gSSURGO_STATE.gpkg")

2. Pull specific variable and merge with corresponding tif

gssurgo.query_gpkg(src_gpkg = "path/to/gSSURGO_MI.gpkg", sql_query = 'SELECT mukey, nonirryield_r FROM mucropyld WHERE (cropname = "Corn")', src_tif = "path/to/gSSURGO_MI.tif", xmin = 925029.1, xmax = 935594, ymin = 2214590.5, ymax = 2225584, out_raster = "tests/nonirryield_r.tif")

The sql_query parameter must give a two column result of mukey and some_variable. The above example produces a tif of non irrigated corn yields clipped to the defined bounding box.

3. Visualize output

gssurgo.viz_numeric_output("tests/nonirryield_r.tif", "tests/nonirryield_r.png")