arcgis-imagery
Skill0 starsChanged 7 months agoMITView on GitHub
Work with raster and imagery data using ImageryLayer, ImageryTileLayer, pixel filtering, raster functions, multidimensional data, and oriented imagery. Use for satellite imagery, elevation data, and scientific raster datasets.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- geoai-latam/SKILL_JS5_ARCGIStheir own version, first seen Nov 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- geoai-latam/SKILL_JS5_ARCGIS★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository47 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/arcgis-ai-components/AGENTS.mdAGENTS.md
- skills/arcgis-authentication/AGENTS.mdAGENTS.md
- skills/arcgis-charts/AGENTS.mdAGENTS.md
- skills/arcgis-coding-components/AGENTS.mdAGENTS.md
- skills/arcgis-core-maps/AGENTS.mdAGENTS.md
- skills/arcgis-editing/AGENTS.mdAGENTS.md
- skills/arcgis-embeddable-maps/AGENTS.mdAGENTS.md
- skills/arcgis-interaction/AGENTS.mdAGENTS.md
- skills/arcgis-layers/AGENTS.mdAGENTS.md
- skills/arcgis-starter-app/AGENTS.mdAGENTS.md
- skills/arcgis-visualization/AGENTS.mdAGENTS.md
- skills/arcgis-widgets-ui/AGENTS.mdAGENTS.md
- arcgis-3d-layersSkill
- arcgis-advanced-layersSkill
- arcgis-ai-componentsSkill
- arcgis-arcadeSkill
- arcgis-authenticationSkill
- arcgis-chartsSkill
- arcgis-cim-symbolsSkill
- arcgis-coding-componentsSkill
- arcgis-coordinates-projectionSkill
- arcgis-core-mapsSkill
- arcgis-core-utilitiesSkill
- arcgis-custom-renderingSkill
- arcgis-editingSkill
- arcgis-embeddable-mapsSkill
- arcgis-feature-effectsSkill
- arcgis-geometry-operationsSkill
- arcgis-interactionSkill
- arcgis-knowledge-graphsSkill
- arcgis-layersSkill
- arcgis-map-toolsSkill
- arcgis-performanceSkill
- arcgis-popup-templatesSkill
- arcgis-portal-contentSkill
- arcgis-rest-servicesSkill
- arcgis-scene-environmentSkill
- arcgis-smart-mappingSkill
- arcgis-spatial-analysisSkill
- arcgis-starter-appSkill
- arcgis-tables-formsSkill
- arcgis-time-animationSkill
- arcgis-utility-networksSkill
- arcgis-visualizationSkill
- arcgis-widgets-advancedSkill
- arcgis-widgets-uiSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Use this skill for raster imagery, pixel-level operations, raster functions, multidimensional data, and oriented imagery viewers.
- Very specific: line 423
Memory with large images: Use ImageryTileLayer for large datasets.
- Very specific: line 427
Redraw after filter changes: Call imageryLayer.redraw() after modifying external variables used in pixelFilter.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
ArcGIS Imagery
Use this skill for raster imagery, pixel-level operations, raster functions, multidimensional data, and oriented imagery viewers.
Import Patterns
ESM (npm)
import ImageryLayer from "@arcgis/core/layers/ImageryLayer.js";
import ImageryTileLayer from "@arcgis/core/layers/ImageryTileLayer.js";
import OrientedImageryLayer from "@arcgis/core/layers/OrientedImageryLayer.js";
import RasterFunction from "@arcgis/core/layers/support/RasterFunction.js";
import MosaicRule from "@arcgis/core/layers/support/MosaicRule.js";
import DimensionalDefinition from "@arcgis/core/layers/support/DimensionalDefinition.js";
import MultidimensionalSubset from "@arcgis/core/layers/support/MultidimensionalSubset.js";CDN (dynamic import)
const ImageryLayer = await $arcgis.import(
"@arcgis/core/layers/ImageryLayer.js",
);
const ImageryTileLayer = await $arcgis.import(
"@arcgis/core/layers/ImageryTileLayer.js",
);
const RasterFunction = await $arcgis.import(
"@arcgis/core/layers/support/RasterFunction.js",
);ImageryLayer
ImageryLayer connects to ArcGIS Image Services for dynamic raster data.
Basic ImageryLayer
const imageryLayer = new ImageryLayer({
url: "https://sampleserver6.arcgisonline.com/arcgis/rest/services/ScientificData/SeaTemperature/ImageServer",
});
map.add(imageryLayer);ImageryLayer with Popup
const imageryLayer = new ImageryLayer({
url: "...",
popupTemplate: {
title: "Raster Value",
content: "{Raster.ServicePixelValue}",
},
});Key ImageryLayer Properties
| Property | Type | Description |
url | string | ImageServer REST endpoint |
format | string | Output format ("jpgpng", "tiff", etc.) |
bandIds | number[] | Which bands to display |
rasterFunction | RasterFunction | Server-side processing |
mosaicRule | MosaicRule | Raster combination rules |
pixelFilter | Function | Client-side pixel processing |
renderingRule | object | Client-side rendering rules (JSON) |
ImageryTileLayer
ImageryTileLayer provides fast tiled access to imagery, including Cloud-Optimized GeoTIFF (COG).
Basic ImageryTileLayer
const imageryTileLayer = new ImageryTileLayer({
url: "https://tiledimageservices.arcgis.com/...",
});
map.add(imageryTileLayer);Cloud Optimized GeoTIFF (COG)
const imageryTileLayer = new ImageryTileLayer({
url: "https://example.com/image.tif",
title: "COG Layer",
});Raster Functions
Apply Raster Function
// Hillshade
const hillshadeFunction = new RasterFunction({
functionName: "Hillshade",
functionArguments: {
azimuth: 315,
altitude: 45,
zFactor: 1,
},
});
imageryLayer.rasterFunction = hillshadeFunction;Common Raster Functions
// Stretch
const stretchFunction = new RasterFunction({
functionName: "Stretch",
functionArguments: {
stretchType: 3,
numberOfStandardDeviations: 2,
},
});
// Colormap
const colormapFunction = new RasterFunction({
functionName: "Colormap",
functionArguments: {
colormap: [
[1, 255, 0, 0],
[2, 0, 255, 0],
[3, 0, 0, 255],
],
},
});
// NDVI
const ndviFunction = new RasterFunction({
functionName: "NDVI",
functionArguments: {
visibleBandID: 3,
infraredBandID: 4,
},
});RasterFunction Properties
| Property | Type | Description |
functionName | string | Name of the raster function |
functionArguments | object | Parameters for the function |
outputType | string | Output pixel type |
Common function names: Hillshade, Stretch, Colormap, NDVI, GVITINDEX, SAVI, Pansharpening, Convolution, MLClassify
Mosaic Rules
const mosaicRule = new MosaicRule({
mosaicMethod: "center", // "center", "northwest", "nadir", "lock-raster", "by-attribute"
mosaicOperator: "first", // "first", "last", "min", "max", "mean", "sum", "blend"
lockRasterIds: [1, 2, 3], // Lock to specific rasters
multidimensionalDefinition: [], // For multidimensional data
});
imageryLayer.mosaicRule = mosaicRule;Multidimensional Data
DimensionalDefinition
// Define dimensions (depth, time, etc.)
const dimInfo = [];
// Depth dimension
dimInfo.push(
new DimensionalDefinition({
dimensionName: "StdZ",
values: [0],
isSlice: true,
}),
);
// Time dimension
dimInfo.push(
new DimensionalDefinition({
dimensionName: "StdTime",
values: [1396828800000],
isSlice: true,
}),
);
const mosaicRule = new MosaicRule({
multidimensionalDefinition: dimInfo,
});
const layer = new ImageryLayer({
url: "...",
mosaicRule: mosaicRule,
});Accessing Multidimensional Info
await imageryLayer.load();
const dimensions = imageryLayer.multidimensionalInfo.dimensions;
dimensions.forEach((dim) => {
console.log("Dimension:", dim.name);
console.log("Values:", dim.values);
console.log("Unit:", dim.unit);
});ImageryTileLayer Multidimensional
const layer = new ImageryTileLayer({
url: "...",
multidimensionalSubset: {
dimensions: [
{
name: "StdTime",
values: [
/* epoch ms */
],
},
{
name: "StdZ",
values: [
/* depth values */
],
},
],
},
multidimensionalDefinition: [
new DimensionalDefinition({
dimensionName: "StdTime",
values: [1609459200000],
}),
],
});Common dimension names: StdTime, StdZ, StdPlev, StdDepth
Pixel Filtering
Custom Pixel Filter
const imageryLayer = new ImageryLayer({
url: "...",
pixelFilter: processPixels,
});
function processPixels(pixelData) {
if (!pixelData || !pixelData.pixelBlock) return;
const pixelBlock = pixelData.pixelBlock;
const pixels = pixelBlock.pixels;
let mask = pixelBlock.mask;
const numPixels = pixelBlock.width * pixelBlock.height;
const minVal = pixelBlock.statistics[0].minValue;
const maxVal = pixelBlock.statistics[0].maxValue;
const factor = 255 / (maxVal - minVal);
const band = pixels[0];
const rBand = new Uint8Array(numPixels);
const gBand = new Uint8Array(numPixels);
const bBand = new Uint8Array(numPixels);
if (!mask) {
mask = new Uint8Array(numPixels);
mask.fill(1);
pixelBlock.mask = mask;
}
for (let i = 0; i < numPixels; i++) {
if (mask[i] === 0) continue;
const normalized = (band[i] - minVal) * factor;
rBand[i] = normalized;
gBand[i] = 0;
bBand[i] = 255 - normalized;
}
pixelData.pixelBlock.pixels = [rBand, gBand, bBand];
pixelData.pixelBlock.statistics = null;
pixelData.pixelBlock.pixelType = "u8";
}Masking Pixels by Value
let minThreshold = 0;
let maxThreshold = 100;
function maskPixels(pixelData) {
if (!pixelData || !pixelData.pixelBlock) return;
const pixelBlock = pixelData.pixelBlock;
const pixels = pixelBlock.pixels[0];
let mask = pixelBlock.mask;
if (!mask) {
mask = new Uint8Array(pixels.length);
mask.fill(1);
pixelBlock.mask = mask;
}
for (let i = 0; i < pixels.length; i++) {
mask[i] = pixels[i] >= minThreshold && pixels[i] <= maxThreshold ? 1 : 0;
}
}
// Update thresholds and redraw
function updateThresholds(min, max) {
minThreshold = min;
maxThreshold = max;
imageryLayer.redraw();
}PixelBlock Structure
| Property | Type | Description |
pixels | TypedArray[] | One array per band |
mask | Uint8Array | 0 = transparent, 1 = opaque |
statistics | object[] | { minValue, maxValue } per band |
width | number | Pixel block width |
height | number | Pixel block height |
pixelType | string | "u8", "u16", "u32", "s16", "s32", "f32", "f64" |
Band Combinations
// Select specific bands
imageryLayer.bandIds = [4, 3, 2]; // NIR, Red, Green (False color)
// Common band combinations
// Natural color: [1, 2, 3] (R, G, B)
// False color: [4, 3, 2] (NIR, R, G)
// SWIR: [7, 5, 4] (SWIR, NIR, R)Identify (Query Pixel Values)
view.on("click", async (event) => {
const result = await imageryLayer.identify({
geometry: event.mapPoint,
returnGeometry: false,
returnCatalogItems: true,
});
console.log("Pixel value:", result.value);
console.log("Catalog items:", result.catalogItems);
});Raster Statistics
await imageryLayer.load();
const stats = imageryLayer.serviceRasterInfo.statistics;
console.log("Min:", stats[0].min);
console.log("Max:", stats[0].max);
console.log("Mean:", stats[0].avg);
console.log("StdDev:", stats[0].stddev);Oriented Imagery
OrientedImageryLayer
const oiLayer = new OrientedImageryLayer({
url: "https://services.arcgis.com/.../FeatureServer/0",
});
map.add(oiLayer);OrientedImageryViewer Widget
import OrientedImageryViewer from "@arcgis/core/widgets/OrientedImageryViewer.js";
const oiViewer = new OrientedImageryViewer({
view: view,
});
view.ui.add(oiViewer, "top-right");Imagery Components
| Component | Purpose |
arcgis-oriented-imagery-viewer | View and navigate oriented imagery |
arcgis-video-player | Play video feeds from video services |
Common Pitfalls
- Pixel filter performance: Complex pixel filters run on every render — optimize loops and minimize allocations.
- Band array indices: Band IDs are 1-based in services but 0-based in
bandIdsarrays. - Coordinate systems: Imagery may need reprojection to match the view's spatial reference.
- Memory with large images: Use
ImageryTileLayerfor large datasets; it tiles automatically. - Pixel type conversion: Be careful when changing
pixelTypein pixel filters — mismatches cause artifacts. - Redraw after filter changes: Call
imageryLayer.redraw()after modifying external variables used inpixelFilter.
Reference Samples
layers-imagerylayer— Basic ImageryLayerlayers-imagery-pixelvalues— Querying pixel valueslayers-imagery-rasterfunction— Raster function processinglayers-imagery-multidimensional— Multidimensional imagerylayers-imagerytilelayer— ImageryTileLayerlayers-imagerytilelayer-cog— Cloud-Optimized GeoTIFFlayers-imagery-renderer— Imagery rendererslayers-imagery-clientside— Client-side imagery processinglayers-orientedimagerylayer— Oriented imagery
Related Skills
arcgis-time-animation— Time-aware imagery animationarcgis-layers— Common layer patternsarcgis-smart-mapping— Auto-generated renderersarcgis-custom-rendering— Custom tile layer rendering
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