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Tellus から標高データを取得する

livebooks/tellus/elevation.livemd

Ryo Wakabayashi

@RyoWakabayashi

elixir-learning

More notebooks

Tellus から標高データを取得する

Mix.install(
  [
    {:nx, "~> 0.9"},
    {:evision, "~> 0.2"},
    {:exla, "~> 0.9"},
    {:req, "~> 0.5"},
    {:kino, "~> 0.14"},
    {:kino_maplibre, "~> 0.1"},
    {:kino_vega_lite, "~> 0.1"}
  ],
  config: [nx: [default_backend: EXLA.Backend]]
)

著作権表記

Credit: ASTER GDEM is courtesy of METI and NASA

情報の設定

# Tellus のトークンを入力する
token_input = Kino.Input.password("Token")

Tellus Traveler からデータを探す

Tellus Satellite Data Traveler API を使用する

API 仕様: https://www.tellusxdp.com/docs/travelers/

データセットの選択

defmodule TellusTraveler do
  @base_path "https://www.tellusxdp.com/api/traveler/v1"
  @data_path "#{@base_path}/datasets"

  defp get_headers(token) do
    %{
      "Authorization" => "Bearer #{token}",
      "Content-Type" => "application/json"
    }
  end

  def get_datasets(token, is_order_required) do
    url = "#{@data_path}/?is_order_required=#{is_order_required}"
    headers = get_headers(token)

    url
    |> Req.get!(headers: headers)
    |> then(&amp; &amp;1.body["results"])
  end

  def get_dataset(token, dataset_id) do
    url = "#{@data_path}/#{dataset_id}/"
    headers = get_headers(token)

    url
    |> Req.get!(headers: headers)
    |> Map.get(:body)
  end

  def search(token, dataset_id, coordinates) do
    url =
      if is_list(dataset_id) do
        "#{@base_path}/data-search/"
      else
        "#{@data_path}/#{dataset_id}/data-search/"
      end

    headers = get_headers(token)

    request_body =
      %{
        intersects: %{
          type: "Polygon",
          coordinates: coordinates
        },
        query: %{},
        sortby: [
          %{
            field: "properties.start_datetime",
            direction: "asc"
          }
        ]
      }
      |> Map.merge(
        if is_list(dataset_id) do
          %{datasets: dataset_id}
        else
          %{}
        end
      )
      |> Jason.encode!()

    url
    |> Req.post!(body: request_body, headers: headers)
    |> then(&amp; &amp;1.body["features"])
  end

  def get_data_files(token, dataset_id, data_id) do
    url = "#{@data_path}/#{dataset_id}/data/#{data_id}/files/"
    headers = get_headers(token)

    url
    |> Req.get!(headers: headers)
    |> then(&amp; &amp;1.body["results"])
  end

  defp get_data_file_download_url(token, dataset_id, data_id, file_id) do
    url = "#{@data_path}/#{dataset_id}/data/#{data_id}/files/#{file_id}/download-url/"
    headers = get_headers(token)

    url
    |> Req.post!(headers: headers)
    |> then(&amp; &amp;1.body["download_url"])
  end

  def download(token, dataset_id, scene_id, dist \\ "/tmp/") do
    [dist, scene_id]
    |> Path.join()
    |> File.mkdir_p()

    token
    |> get_data_files(dataset_id, scene_id)
    |> Enum.map(fn file ->
      file_path = Path.join([dist, scene_id, file["name"]])

      unless File.exists?(file_path) do
        token
        |> get_data_file_download_url(dataset_id, scene_id, file["id"])
        |> Req.get!(into: File.stream!(file_path))
      end

      file_path
    end)
  end
end

datasets =
  token_input
  |> Kino.Input.read()
  |> TellusTraveler.get_datasets(false)

elevation_datasets =
  datasets
  |> Enum.filter(fn dataset ->
    dataset["permission"]["allow_network_type"] == "global" &amp;&amp;
      String.contains?(dataset["description"], "標高")
  end)

Kino.DataTable.new(elevation_datasets, keys: ["name", "id", "description"])

dataset_id = "3f865d0b-6410-453f-b124-e0bf48544b45"

シーンの選択

mt_fuji_location = {138.73, 35.36}

mt_fuji_rectangle = [
  [
    [elem(mt_fuji_location, 0) - 0.001, elem(mt_fuji_location, 1) - 0.001],
    [elem(mt_fuji_location, 0) + 0.001, elem(mt_fuji_location, 1) - 0.001],
    [elem(mt_fuji_location, 0) + 0.001, elem(mt_fuji_location, 1) + 0.001],
    [elem(mt_fuji_location, 0) - 0.001, elem(mt_fuji_location, 1) + 0.001],
    [elem(mt_fuji_location, 0) - 0.001, elem(mt_fuji_location, 1) - 0.001]
  ]
]

scenes_list =
  token_input
  |> Kino.Input.read()
  |> TellusTraveler.search(dataset_id, mt_fuji_rectangle)

mt_fuji_scene_id =
  scenes_list
  |> Enum.at(0)
  |> Map.get("id")

データのダウンロード

token_input
|> Kino.Input.read()
|> TellusTraveler.download(dataset_id, mt_fuji_scene_id)

ダウンロードした画像を表示する

"/tmp/#{mt_fuji_scene_id}"
|> File.ls!()
|> Enum.filter(fn filename -> Path.extname(filename) != ".txt" end)
|> Enum.sort()
|> Enum.map(fn filename ->
  ["/tmp", mt_fuji_scene_id, filename]
  |> Path.join()
  # 色が 16bit で格納されているため、 IMREAD_ANYDEPTH と IMREAD_ANYCOLOR を指定する
  |> Evision.imread(
    flags: Evision.Constant.cv_IMREAD_ANYDEPTH() + Evision.Constant.cv_IMREAD_ANYCOLOR()
  )
  # 大きすぎるのでリサイズ
  |> Evision.resize({640, 640})
end)
|> Kino.Layout.grid(columns: 2)

mt_fuji_dem =
  "/tmp/#{mt_fuji_scene_id}"
  |> File.ls!()
  |> Enum.find(fn filename -> String.ends_with?(filename, "_dem.tif") end)
  |> then(&amp;Path.join(["/tmp", mt_fuji_scene_id, &amp;1]))
  |> Evision.imread(
    flags: Evision.Constant.cv_IMREAD_ANYDEPTH() + Evision.Constant.cv_IMREAD_ANYCOLOR()
  )
  |> Evision.Mat.to_nx(EXLA.Backend)

{mt_fuji_min_dig, mt_fuji_max_dig} = {
  mt_fuji_dem |> Nx.reduce_min() |> Nx.to_number(),
  mt_fuji_dem |> Nx.reduce_max() |> Nx.to_number()
}

mt_fuji_dem_u8 =
  mt_fuji_dem
  |> Nx.subtract(mt_fuji_min_dig)
  |> Nx.multiply(255 / (mt_fuji_max_dig - mt_fuji_min_dig))
  |> Nx.as_type(:u8)

Evision.resize(mt_fuji_dem_u8, {640, 640})

mt_fuji_dem_color = Evision.applyColorMap(src: mt_fuji_dem_u8, colormap: Evision.Constant.cv_COLORMAP_JET())

Evision.resize(mt_fuji_dem_color, {640, 640})

標高をグラフ化する

display_elevation_at_x = fn dem, x_index, width, max_y ->
  plot_data =
    dem[[x_index]]
    |> Nx.to_flat_list()
    |> Enum.with_index()
    |> Enum.map(fn {elevation, index} ->
      %{
        elevation: elevation,
        index: index
      }
    end)

  x_scale = %{"domain" => [0, 3601]}
  y_scale = %{"domain" => [-500, max_y]}

  VegaLite.new(width: width)
  |> VegaLite.data_from_values(plot_data)
  |> VegaLite.mark(:area)
  |> VegaLite.encode_field(:x, "index", type: :quantitative, scale: x_scale)
  |> VegaLite.encode_field(:y, "elevation", type: :quantitative, scale: y_scale)
end

display_elevation_at_x.(mt_fuji_dem, 0, 700, 4000)

max_index = mt_fuji_dem |> Nx.argmax() |> Nx.to_number()

max_x_index = div(max_index, 3601)
max_y_index = max_index - max_x_index * 3601

{max_x_index, max_y_index}

mt_fuji_dem[[max_x_index, max_y_index]]

display_elevation_at_x.(mt_fuji_dem, max_x_index, 700, 4000)

グラフをアニメーションにする

x_scale = %{"domain" => [0, 3601]}
y_scale = %{"domain" => [-500, 4000]}

widget =
  VegaLite.new(width: 700)
  |> VegaLite.mark(:area)
  |> VegaLite.encode_field(:x, "index", type: :quantitative, scale: x_scale)
  |> VegaLite.encode_field(:y, "elevation", type: :quantitative, scale: y_scale)
  |> Kino.VegaLite.new()

animate = fn dem, x_index ->
  plot_data =
    dem[[x_index]]
    |> Nx.to_flat_list()
    |> Enum.with_index()
    |> Enum.map(fn {elevation, y_index} ->
      %{
        elevation: elevation,
        index: y_index
      }
    end)

  Kino.VegaLite.clear(widget)
  Kino.VegaLite.push_many(widget, plot_data)
end

0..3600//20
|> Enum.map(fn x_index ->
  animate.(mt_fuji_dem, x_index)
  Process.sleep(100)
end)

富士山と大分市を比較する

get_scene_id = fn location ->
  rectangle = [
    [
      [elem(location, 0) - 0.001, elem(location, 1) - 0.001],
      [elem(location, 0) + 0.001, elem(location, 1) - 0.001],
      [elem(location, 0) + 0.001, elem(location, 1) + 0.001],
      [elem(location, 0) - 0.001, elem(location, 1) + 0.001],
      [elem(location, 0) - 0.001, elem(location, 1) - 0.001]
    ]
  ]

  scenes_list =
    token_input
    |> Kino.Input.read()
    |> TellusTraveler.search(dataset_id, rectangle)

  scenes_list
  |> Enum.at(0)
  |> Map.get("id")
end

oita_location = {131.64, 33.20}

oita_scene_id = get_scene_id.(oita_location)

token_input
|> Kino.Input.read()
|> TellusTraveler.download(dataset_id, oita_scene_id)

oita_dem =
  "/tmp/#{oita_scene_id}"
  |> File.ls!()
  |> Enum.find(fn filename -> String.ends_with?(filename, "_dem.tif") end)
  |> then(&amp;Path.join(["/tmp", oita_scene_id, &amp;1]))
  |> Evision.imread(
    flags: Evision.Constant.cv_IMREAD_ANYDEPTH() + Evision.Constant.cv_IMREAD_ANYCOLOR()
  )
  |> Evision.Mat.to_nx(EXLA.Backend)

oita_dem_u8 =
  oita_dem
  |> Nx.subtract(mt_fuji_min_dig)
  |> Nx.multiply(255 / (mt_fuji_max_dig - mt_fuji_min_dig))
  |> Nx.as_type(:u8)

oita_dem_color = Evision.applyColorMap(src: oita_dem_u8, colormap: Evision.Constant.cv_COLORMAP_JET())

[mt_fuji_dem_color, oita_dem_color]
|> Kino.Layout.grid(columns: 2)

oita_max_index = oita_dem |> Nx.argmax() |> Nx.to_number()
oita_max_x_index = div(oita_max_index, 3601)

[
  display_elevation_at_x.(mt_fuji_dem, max_x_index, 300, 4000),
  display_elevation_at_x.(oita_dem, oita_max_x_index, 300, 4000)
]
|> Kino.Layout.grid(columns: 2)

富士山とエベレストを比較する

mt_everest_location = {86.92, 27.99}

mt_everest_scene_id = get_scene_id.(mt_everest_location)

token_input
|> Kino.Input.read()
|> TellusTraveler.download(dataset_id, mt_everest_scene_id)

mt_everest_dem =
  "/tmp/#{mt_everest_scene_id}"
  |> File.ls!()
  |> Enum.find(fn filename -> String.ends_with?(filename, "_dem.tif") end)
  |> then(&amp;Path.join(["/tmp", mt_everest_scene_id, &amp;1]))
  |> Evision.imread(
    flags: Evision.Constant.cv_IMREAD_ANYDEPTH() + Evision.Constant.cv_IMREAD_ANYCOLOR()
  )
  |> Evision.Mat.to_nx(EXLA.Backend)

{mt_everest_min_dig, mt_everest_max_dig} = {
  mt_everest_dem |> Nx.reduce_min() |> Nx.to_number(),
  mt_everest_dem |> Nx.reduce_max() |> Nx.to_number()
}

min_dig = Enum.min([mt_fuji_min_dig, mt_everest_min_dig])
max_dig = Enum.max([mt_fuji_max_dig, mt_everest_max_dig])

{min_dig, max_dig}

get_heatmap = fn dem, min_dig, max_dig ->
  dem
  |> Nx.subtract(min_dig)
  |> Nx.multiply(256 / (max_dig - min_dig))
  |> Nx.as_type(:u8)
  |> then(&amp;[src: &amp;1, colormap: Evision.Constant.cv_COLORMAP_JET()])
  |> Evision.applyColorMap()
end

[
  get_heatmap.(mt_everest_dem, min_dig, max_dig),
  get_heatmap.(mt_fuji_dem, min_dig, max_dig),
  get_heatmap.(oita_dem, min_dig, max_dig)
]
|> Kino.Layout.grid(columns: 3)

mt_everest_max_x_index =
  mt_everest_dem
  |> Nx.argmax()
  |> Nx.to_number()
  |> div(3601)

[
  display_elevation_at_x.(mt_everest_dem, mt_everest_max_x_index, 200, 9000),
  display_elevation_at_x.(mt_fuji_dem, max_x_index, 200, 9000),
  display_elevation_at_x.(oita_dem, oita_max_x_index, 200, 9000)
]
|> Kino.Layout.grid(columns: 3)

海面上昇シミュレーション

alpha =
  Nx.logical_and(Nx.greater(oita_dem, 0), Nx.less_equal(oita_dem, 10))
  |> Nx.select(255, 0)
  |> Nx.new_axis(-1)

alpha
|> Nx.as_type(:u8)
|> Evision.Mat.from_nx_2d()
|> Evision.resize({640, 640})

bgra =
  [0, 0, 255]
  |> Nx.tensor()
  |> Nx.tile([3601, 3601, 1])
  |> then(&amp;Nx.concatenate([&amp;1, alpha], axis: 2))
  |> Nx.as_type(:u8)
  |> Evision.Mat.from_nx_2d()

Evision.resize(bgra, {640, 640})

get_data_url = fn mat ->
  Evision.imencode(".png", mat)
  |> Base.encode64()
  |> then(&amp;"data:image/png;base64,#{&amp;1}")
end

center = {131.5, 33.5}

coordinates = [
  [131 - 1 / 3600 / 2, 34 - 9 / 3600 / 2],
  [132 + 1 / 3600 / 2, 34 - 9 / 3600 / 2],
  [132 + 1 / 3600 / 2, 33 - 11 / 3600 / 2],
  [131 - 1 / 3600 / 2, 33 - 11 / 3600 / 2]
]

img_base64 = get_data_url.(bgra)

MapLibre.new(center: center, zoom: 8, style: :terrain)
|> MapLibre.add_source("image", type: :image, url: img_base64, coordinates: coordinates)
|> MapLibre.add_layer(
  id: "overlay",
  source: "image",
  type: :raster,
  paint: %{"raster-opacity" => 0.5}
)

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