.gitignore

@@ -5,6 +5,4 @@ dist
 layers/dot-cams/*/data/states.js
 layers/survey-markers/states.js
 layers/tjx/data/chains.js
-layers/crop-history/data/counties.js
 .direnv
-venv

Makefile

@@ -1,6 +1,6 @@
 .PHONY: deploy
 deploy: build
-	rsync --archive --verbose --delete dist/ root@bert:/srv/maps.chandlerswift.com/
+	rsync --archive --verbose --delete dist/ zirconium.home.chandlerswift.com:/var/www/maps.chandlerswift.com/
 
 .PHONY: clean
 clean:

README.md

@@ -1,7 +1,5 @@
 # maps.chandlerswift.com
 
-[![XKCD 2054: "Data Pipeline"](https://imgs.xkcd.com/comics/data_pipeline_2x.png '"Is the pipeline literally running from your laptop?" "Don't be silly, my laptop disconnects far too often to host a service we rely on. It's running on my phone."')](https://xkcd.com/2054/)
-
 - [ ] My location (from whereis.chandlerswift.com)
 - [ ] Menards
 - [ ] Culver's

layers/crop-history/extract_counties.py

@@ -1,60 +0,0 @@
-#!/usr/bin/python
-
-import geopandas as gpd
-import os
-import fiona
-import sys
-import csv
-
-states_to_include = ["MN"]
-
-state_fipses_to_include = []
-county_lookup = {}
-print("Reading county census data...")
-with open('national_cousub2020.txt') as csvfile:
-    reader = csv.DictReader(csvfile, delimiter='|')
-    for row in reader:
-        if row['STATE'] in states_to_include:
-            state_fipses_to_include.append(row['STATEFP'])
-        county_lookup[row['STATEFP'] + row['COUNTYFP']] = row
-
-input_file = sys.argv[1]
-
-print("Reading input gdb...")
-gdf = gpd.read_file(input_file)
-gdf = gdf[gdf['STATEFIPS'].isin(state_fipses_to_include)]
-
-print("Reprojecting...")
-gdf = gdf.to_crs("EPSG:4326")
-
-print("Simplifying geometry...")
-gdf['geometry'] = gdf['geometry'].simplify(0.0001, preserve_topology=True)
-
-print("Calculating FULLFIPS...")
-gdf['FULLFIPS'] = gdf['STATEFIPS'].astype(str) + gdf['CNTYFIPS'].astype(str)
-
-print("Finding unique FULLFIPS...")
-counties = gdf['FULLFIPS'].unique()
-
-# TODO: Trim down which fields are included
-#
-# "CSBID", "CSBYEARS", "CSBACRES",
-# "CDL2016", "CDL2017", "CDL2018", "CDL2019", "CDL2020", "CDL2021", "CDL2022", "CDL2023",
-# "STATEFIPS", "STATEASD", "ASD", "CNTY", "CNTYFIPS",
-# "INSIDE_X", "INSIDE_Y", "Shape_Length", "Shape_Area", "FULLFIPS"
-
-for i, county in enumerate(counties, 1):
-    print(f"Processing county ({county}): {i}/{len(counties)}")
-    county_gdf = gdf[gdf['FULLFIPS'] == county]
-    output_file = f"{county}.geojson"
-    county_gdf.to_file(os.path.join("data", output_file), driver="GeoJSON", COORDINATE_PRECISION=5)
-
-with open('data/counties.js', 'w') as f:
-    for county in counties:
-        f.write(f"import county{county} from './{county}.geojson?url';\n")
-    f.write('\nexport default {\n')
-    for county in counties:
-        county_name = county_lookup[county]['COUNTYNAME']
-        state_name = county_lookup[county]['STATE']
-        f.write(f"    '{county_name}, {state_name}': county{county},\n")
-    f.write("};\n")

layers/crop-history/get_data.sh

@@ -1,17 +0,0 @@
-#!/usr/bin/env nix-shell
-#! nix-shell -i bash --pure
-#! nix-shell -p bash wget unzip python3 python3Packages.geopandas python3Packages.fiona python3Packages.pyproj
-# TODO: do I need all the python packages?
-
-set -x -euo pipefail
-
-wget -nc https://www.nass.usda.gov/Research_and_Science/Crop-Sequence-Boundaries/datasets/NationalCSB_2016-2023_rev23.zip
-wget -nc https://www2.census.gov/geo/docs/reference/codes2020/national_cousub2020.txt
-unzip -u NationalCSB_2016-2023_rev23.zip
-
-mkdir -p data
-
-# HEADS UP: this script takes something like 40GB of RAM. In theory, I could
-# probably do something clever with streaming...but I have 40 GB of RAM, so this
-# works!
-python -i extract_counties.py NationalCSB_2016-2023_rev23/CSB1623.gdb

layers/crop-history/index.js

@@ -1,111 +0,0 @@
-import VectorLayer from 'ol/layer/Vector';
-import {Vector as VectorSource} from 'ol/source.js';
-import GeoJSON from 'ol/format/GeoJSON.js';
-
-import {Style} from 'ol/style.js';
-
-import counties from './data/counties.js';
-
-// from https://www.nass.usda.gov/Research_and_Science/Crop-Sequence-Boundaries/metadata_Crop-Sequence-Boundaries-2023.htm
-const crops = {
-    "1": "Corn",
-    "2": "Cotton",
-    "3": "Rice",
-    "4": "Sorghum",
-    "5": "Soybeans",
-    "6": "Sunflower",
-    "10": "Peanuts",
-    "11": "Tobacco",
-    "12": "Sweet Corn",
-    "13": "Pop or Orn Corn",
-    "14": "Mint",
-    "21": "Barley",
-    "22": "Durum Wheat",
-    "23": "Spring Wheat",
-    "24": "Winter Wheat",
-    "25": "Other Small Grains",
-    "26": "Dbl Crop WinWht/Soybeans",
-    "27": "Rye",
-    "28": "Oats",
-    "29": "Millet",
-    "30": "Speltz",
-    "31": "Canola",
-    "32": "Flaxseed",
-    "33": "Safflower",
-    "34": "Rape Seed",
-    "35": "Mustard",
-    "36": "Alfalfa",
-    "37": "Other Hay/Non Alfalfa",
-    "38": "Camelina",
-    "39": "Buckwheat",
-    "41": "Sugarbeets",
-    "42": "Dry Beans",
-    "43": "Potatoes",
-    "44": "Other Crops",
-    "45": "Sugarcane",
-    "46": "Sweet Potatoes",
-    "47": "Misc Vegs & Fruits",
-    "48": "Watermelons",
-    "49": "Onions",
-    "50": "Cucumbers",
-    "51": "Chick Peas",
-    "52": "Lentils",
-    "53": "Peas",
-    "54": "Tomatoes",
-    "55": "Caneberries",
-    "56": "Hops",
-    "57": "Herbs",
-    "58": "Clover/Wildflowers",
-    "59": "Sod/Grass Seed",
-    "60": "Switchgrass",
-}
-
-const category = {
-    name: "County Crop History",
-    details: `<a href="https://www.nass.usda.gov/Research_and_Science/Crop-Sequence-Boundaries/index.php">https://www.nass.usda.gov/Research_and_Science/Crop-Sequence-Boundaries/index.php</a>`,
-    layers: [],
-};
-
-for (let [county, url] of Object.entries(counties)) {
-    const geojsonSource = new VectorSource({
-        url: url,
-        format: new GeoJSON,
-    });
-
-    geojsonSource.on('featuresloadend', function(event) {
-        event.features.forEach(feature => {
-            for (let year = 2016; year <= 2023; year++) {
-                const cropid = feature.get(`CDL${year}`);
-                
-                // Check if the value exists in the key, then replace it
-                if (cropid in crops) {
-                    feature.set(String(year), crops[cropid]);
-                } else {
-                    feature.set(String(year), cropid);
-                }
-                feature.unset(`CDL${year}`);
-            }
-        });
-    });
-    const vectorLayer = new VectorLayer({
-        source: geojsonSource,
-    });
-
-    category.layers.push({
-        name: county,
-        layer: vectorLayer,
-    });
-}
-
-category.layers.sort(function (a, b) {
-    const a_state = a.name.substr(a.length - 2);
-    const b_state = a.name.substr(b.length - 2);
-    // Sort by state...
-    if (a_state != b_state) {
-        return a_state > b_state ? 1 : -1;
-    }
-    // ...then by county
-    return a.name > b.name ? 1 : -1;
-});
-
-export default category;

layers/index.js

@@ -20,7 +20,6 @@ import dot_cams from './dot-cams/index.js';
 import survey_markers from './survey-markers/index.js';
 import tjx from './tjx/index.js';
 import minnesotaAdventureTrails from './minnesota-adventure-trails/index.js';
-import cropHistory from './crop-history/index.js';
 
 const layerCategories = [
     { // Base maps
@@ -104,7 +103,6 @@ const layerCategories = [
     cellular,
     light_pollution,
     tjx,
-    cropHistory,
 ];
 
 export default layerCategories;