fsa-lfp-eligibility

scaleSequential = (await import("https://cdn.jsdelivr.net/npm/d3@7/+esm")).scaleSequential

// a format for dates
formatDate = d3.utcFormat("%b %d, %Y")  // e.g., "Apr 18, 2025"

// counties

//counties_file = await d3.json("https://cdn.jsdelivr.net/npm/us-atlas@3/counties-10m.json");
us = await d3.json("https://sustainable-fsa.github.io/fsa-counties-dd17/fsa-counties-dd17.topojson");
//us = await d3.json("assets/fsa-counties-dd17-albers.topojson");
counties = topojson.feature(us, us.objects.counties)

// states, but just the boundaries between them
//states_file = FileAttachment("assets/fsa_states.topojson").json()
states = topojson.mesh(us, us.objects.states, (a, b) => a !== b)

// normal grazing period data, simplified
data = FileAttachment("assets/fsa-lfp-eligibility-simple.csv").csv({typed: true})

// Load color palettes
color =
new Map([
["1 Month", "#FFFF54"], 
["2 Month", "#F3AE3D"],
["3 Month", "#6D4E16"],
["4 Month", "#EA3323"],
["5 Month", "#7316A2"],
["Eligible", "#EA3323"]
])

variable = "payment_type"

filtered = data.filter(d => d.year === year && d.type === type && d.disaster === disaster)

// Create a lookup table keyed by `id`
valueById = Object.fromEntries(filtered.map(d => [String(d.id).padStart(5, "0"), d[variable]]))

// Merge values into counties.features
countiesFiltered = {
  // Build lookup from filtered CSV: id → full row
  const rowById = Object.fromEntries(
        filtered.map(d => [String(d.id).padStart(5, "0"), d])
  );

  // Rebuild counties with joined properties
  return {
    type: "FeatureCollection",
    features: counties.features.map(f => {
      const id = String(f.id);
      const row = rowById[id];

      return {
        ...f,
        value: row ? row[variable] : null,
        properties: {
          id: f.id,
          ...f.properties,
          ...(row ?? {}),
          value: row ? row[variable] : null  // explicitly add value for coloring
        }
      };
    })
  };
}

FSA Livestock Forage Disaster Program Eligibility

viewof disaster = Inputs.radio(
["Drought", "Fire"],
{
label: "Disaster",
value: "Drought"
}
)

viewof year = Inputs.range(
d3.extent(data, d => d.year),
{
step: 1, 
label: "Year",
value: 2024
}
)

viewof type = {
  const options = disaster === "Fire"
    ? ["Rangeland"]
    : [...new Set(data.map(d => d.type))].sort();
  return Inputs.select(options, { label: "Type" });
}

Plot.plot({
projection: {
    type: "albers",
    domain: counties
  },
grid: true,
color: (disaster === "Drought" ? 
{
    domain: ["1 Month", "2 Month", "3 Month", "4 Month", "5 Month"], 
    range: ["#FFFF54", "#F3AE3D", "#6D4E16", "#EA3323", "#7316A2"],
    unknown: "#ccc",
    legend: true
  } : 
  {
    domain: ["Eligible"], 
    range: ["#EA3323"],
    unknown: "#ccc",
    legend: true
  }),
marks: [
Plot.geo(countiesFiltered, {
      fill: "value"
    }),

Plot.dot(
  countiesFiltered.features.map(f => {
    const [x, y] = d3.geoCentroid(f);
    return {
      ...f.properties,
      x,
      y
    };
  }),
  {
    x: "x",
    y: "y",
    r: 3,
    fill: "transparent",
    stroke: "none",
    tip: true,
    title: d => `${d.county} County, ${d.state}
FIPS: ${String(d.id).padStart(5, "0")}
Program Year: ${year}
Crop Type: ${type}
Disaster: ${d.disaster ? d.disaster : "None"}
Drought Qualifier: ${d.qualifier ? d.qualifier : "None"}
Start Date: ${d.disaster_start_date ? formatDate(d.disaster_start_date) : "None"}
`
  }
),

Plot.geo(states, {stroke: "white"}),
]
})