The data layers response comes in a GeoTIFF file. You can use your own tooling to get the data you are interested in. For example, imagine you have a GeoTIFF image showing temperature values across a region. Using TypeScript, you can map low temperatures to blue colors and high temperatures to red to create a colorful image that's instantly understandable for visualizing temperature patterns.
This TypeScript code is designed to take special image files called GeoTIFFs and display them on a website using an HTML canvas (like a digital picture frame). The code uses the following components:
- GeoTIFF images: GeoTIFFs can store multiple layers of image data, making them useful for maps or scientific analysis.
- RGB Images: These are the types of images we're most familiar with (like photos). Every pixel has red, green, and blue values that determine the color.
- Palettes: These are like paint sets. They contain a list of predefined colors that can be used to color images.
This page shows how to get the pixel data values (the information stored in individual pixels of a digital image, including color values and other attributes) and calculates the latitude and longitude from the GeoTIFF and stores it in a TypeScript object.
The following code snippet shows the type definition where we store the data of interest in this example. Fields and type of data is a "type" in TypeScript. For this specific example, we chose to allow type checking, reducing type errors and adding reliability to your code, making it easier to maintain. Define a type to store that data in order to return multiple values like the pixel values and the lat/long bounding box.
export interface GeoTiff {
width: number;
height: number;
rasters: Array<number>[];
bounds: Bounds;
}
Core functions
The code has several functions that work together:
renderRGB: Takes an RGB GeoTIFF image and optionally a mask (for transparency), creates a website canvas element, loops through each pixel of the GeoTIFF, and colors the corresponding pixel on the canvas.renderPalette: Takes a GeoTIFF with a single layer of data and a color palette, maps the GeoTIFF data values to the colors in the palette, creates a new RGB image using the palette colors, and callsrenderRGBto display the image on the canvas.
/**
* Renders an RGB GeoTiff image into an HTML canvas.
*
* The GeoTiff image must include 3 rasters (bands) which
* correspond to [Red, Green, Blue] in that order.
*
* @param {GeoTiff} rgb GeoTiff with RGB values of the image.
* @param {GeoTiff} mask Optional mask for transparency, defaults to opaque.
* @return {HTMLCanvasElement} Canvas element with the rendered image.
*/
export function renderRGB(rgb: GeoTiff, mask?: GeoTiff): HTMLCanvasElement {
// Create an HTML canvas to draw the image.
// https://www.w3schools.com/tags/canvas_createimagedata.asp
const canvas = document.createElement('canvas');
// Set the canvas size to the mask size if it's available,
// otherwise set it to the RGB data layer size.
canvas.width = mask ? mask.width : rgb.width;
canvas.height = mask ? mask.height : rgb.height;
// Since the mask size can be different than the RGB data layer size,
// we calculate the "delta" between the RGB layer size and the canvas/mask
// size. For example, if the RGB layer size is the same as the canvas size,
// the delta is 1. If the RGB layer size is smaller than the canvas size,
// the delta would be greater than 1.
// This is used to translate the index from the canvas to the RGB layer.
const dw = rgb.width / canvas.width;
const dh = rgb.height / canvas.height;
// Get the canvas image data buffer.
const ctx = canvas.getContext('2d')!;
const img = ctx.getImageData(0, 0, canvas.width, canvas.height);
// Fill in every pixel in the canvas with the corresponding RGB layer value.
// Since Javascript doesn't support multidimensional arrays or tensors,
// everything is stored in flat arrays and we have to keep track of the
// indices for each row and column ourselves.
for (let y = 0; y < canvas.height; y++) {
for (let x = 0; x < canvas.width; x++) {
// RGB index keeps track of the RGB layer position.
// This is multiplied by the deltas since it might be a different
// size than the image size.
const rgbIdx = Math.floor(y * dh) * rgb.width + Math.floor(x * dw);
// Mask index keeps track of the mask layer position.
const maskIdx = y * canvas.width + x;
// Image index keeps track of the canvas image position.
// HTML canvas expects a flat array with consecutive RGBA values.
// Each value in the image buffer must be between 0 and 255.
// The Alpha value is the transparency of that pixel,
// if a mask was not provided, we default to 255 which is opaque.
const imgIdx = y * canvas.width * 4 + x * 4;
img.data[imgIdx + 0] = rgb.rasters[0][rgbIdx]; // Red
img.data[imgIdx + 1] = rgb.rasters[1][rgbIdx]; // Green
img.data[imgIdx + 2] = rgb.rasters[2][rgbIdx]; // Blue
img.data[imgIdx + 3] = mask // Alpha
? mask.rasters[0][maskIdx] * 255
: 255;
}
}
// Draw the image data buffer into the canvas context.
ctx.putImageData(img, 0, 0);
return canvas;
}
Helper Functions
The code also includes several helper functions that enable additional functionality:
createPalette: Creates a list of colors to be used for coloring images based on a list of hexadecimal color codes.colorToRGB: Converts a color code like "#FF00FF" into its red, green, and blue components.normalize,lerp,clamp: Mathematical helper functions for image processing.
/**
* Renders a single value GeoTiff image into an HTML canvas.
*
* The GeoTiff image must include 1 raster (band) which contains
* the values we want to display.
*
* @param {GeoTiff} data GeoTiff with the values of interest.
* @param {GeoTiff} mask Optional mask for transparency, defaults to opaque.
* @param {string[]} colors Hex color palette, defaults to ['000000', 'ffffff'].
* @param {number} min Minimum value of the data range, defaults to 0.
* @param {number} max Maximum value of the data range, defaults to 1.
* @param {number} index Raster index for the data, defaults to 0.
* @return {HTMLCanvasElement} Canvas element with the rendered image.
*/
export function renderPalette({
data,
mask,
colors,
min,
max,
index,
}: {
data: GeoTiff;
mask?: GeoTiff;
colors?: string[];
min?: number;
max?: number;
index?: number;
}): HTMLCanvasElement {
// First create a palette from a list of hex colors.
const palette = createPalette(colors ?? ['000000', 'ffffff']);
// Normalize each value of our raster/band of interest into indices,
// such that they always map into a value within the palette.
const indices = data.rasters[index ?? 0]
.map((x) => normalize(x, max ?? 1, min ?? 0))
.map((x) => Math.round(x * (palette.length - 1)));
return renderRGB(
{
...data,
// Map each index into the corresponding RGB values.
rasters: [
indices.map((i: number) => palette[i].r),
indices.map((i: number) => palette[i].g),
indices.map((i: number) => palette[i].b),
],
},
mask,
);
}
/**
* Creates an {r, g, b} color palette from a hex list of colors.
*
* Each {r, g, b} value is a number between 0 and 255.
* The created palette is always of size 256, regardless of the number of
* hex colors passed in. Inbetween values are interpolated.
*
* @param {string[]} hexColors List of hex colors for the palette.
* @return {{r, g, b}[]} RGB values for the color palette.
*/
export function createPalette(hexColors: string[]): { r: number; g: number; b: number }[] {
// Map each hex color into an RGB value.
const rgb = hexColors.map(colorToRGB);
// Create a palette with 256 colors derived from our rgb colors.
const size = 256;
const step = (rgb.length - 1) / (size - 1);
return Array(size)
.fill(0)
.map((_, i) => {
// Get the lower and upper indices for each color.
const index = i * step;
const lower = Math.floor(index);
const upper = Math.ceil(index);
// Interpolate between the colors to get the shades.
return {
r: lerp(rgb[lower].r, rgb[upper].r, index - lower),
g: lerp(rgb[lower].g, rgb[upper].g, index - lower),
b: lerp(rgb[lower].b, rgb[upper].b, index - lower),
};
});
}
/**
* Convert a hex color into an {r, g, b} color.
*
* @param {string} color Hex color like 0099FF or #0099FF.
* @return {{r, g, b}} RGB values for that color.
*/
export function colorToRGB(color: string): { r: number; g: number; b: number } {
const hex = color.startsWith('#') ? color.slice(1) : color;
return {
r: parseInt(hex.substring(0, 2), 16),
g: parseInt(hex.substring(2, 4), 16),
b: parseInt(hex.substring(4, 6), 16),
};
}
/**
* Normalizes a number to a given data range.
*
* @param {number} x Value of interest.
* @param {number} max Maximum value in data range, defaults to 1.
* @param {number} min Minimum value in data range, defaults to 0.
* @return {number} Normalized value.
*/
export function normalize(x: number, max: number = 1, min: number = 0): number {
const y = (x - min) / (max - min);
return clamp(y, 0, 1);
}
/**
* Calculates the linear interpolation for a value within a range.
*
* @param {number} x Lower value in the range, when `t` is 0.
* @param {number} y Upper value in the range, when `t` is 1.
* @param {number} t "Time" between 0 and 1.
* @return {number} Inbetween value for that "time".
*/
export function lerp(x: number, y: number, t: number): number {
return x + t * (y - x);
}
/**
* Clamps a value to always be within a range.
*
* @param {number} x Value to clamp.
* @param {number} min Minimum value in the range.
* @param {number} max Maximum value in the range.
* @return {number} Clamped value.
*/
export function clamp(x: number, min: number, max: number): number {
return Math.min(Math.max(x, min), max);
}