# Output GeoJSON of detection algorithms¶

GeoJSON with a FeatureCollection where each Feature represents an individual detection. All features have geometry of type Polygon and properties which are specific to algorithm which this is result of.

geometry of each region is its minimum-area bounding rectangle.

Note

Minimum-area bounding rectangles can have any orientation, i.e. they are not necessarily aligned with parallels and meridians or the feature’s orientation property.

{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"properties": {
"class": "cars",
"area": 7.6,
"count": 1,
"orientation": -28.5,
"aspectRatio": 0.22,
"confidence": 0.95,
"reflectance": {
"blue": 0.0123,
"near-ir2": 0.0234,
"near-ir1": 0.01,
"yellow": 0.02,
"green": 0.09,
"red-edge": 0.12,
"coastal": 0.001,
"red": 0.123
}
},
"geometry": {
"type": "Polygon",
"coordinates": [
[
[153.12104687732085, -27.388643101636596],
[153.12137530696452, -27.389043532193686],
[153.12076821186633, -27.389436088316238],
[153.12043978372787, -27.389035658966332],
[153.12104687732085, -27.388643101636596]
]
]
}
}
]
}


## Object detection feature properties¶

• class – determines object classification; always present.
• area – area of detected object in $$m^2$$; always present.
• count – number of objects represented by the Feature; always present.
• orientation – angle between x-axis of an image and axis of a detected object given in degrees (counter-clockwise); present only if count is 1; may be unavailable.
• aspectRatio – ratio between longer side and shorter side of the minimum-area enclosing oriented rectangle; may be unavailable.
• confidence – a number between 0 and 1; may be unavailable.
• reflectance – per-band reflectance of the object. Value is JSON where keys are band names and values are reflectances; may be unavailable.

# Output JSON of segmentation algorithms¶

Output JSON contains square meters of area covered by each segmentation class.

Example:

{
"water": 1161.74,

• meanChange - Average value of the change heatmap inside the attention region.
• compactness - a float number between 0 and 1 (inclusive). It measures compactness, where 1 means the attention region has fully convex shape (e.g. circle).
• linearity - a float number between 0 and 1 (inclusive). It measurers region linearity, where 1 means the attention region has very linear (eccentric) shape (e.g. narrow straight road).