GEOSPATIAL IMAGE LABELING AND FEATURE CHANGE DETECTION

1 . A computer-implemented method comprising:

receiving information indicative of a geospatial image;

applying a trained feature extraction module to detect a first target feature based on a feature specification;

mapping the first target feature against a set of labeled features within an area defined by the geospatial image;

determining that the first target feature is new, based on a threshold distance value between the first target feature and a first labeled feature; and

updating the set of labeled features with the first target feature.

2 . The method of claim 1 , wherein the feature specification defines an object type based on at least one of an object shape, an object area, or an object size.

3 . The method of claim 1 , wherein the threshold distance value is based on the feature specification and an aggressiveness parameter, wherein the aggressiveness parameter defines a variability allowance for the feature specification.

4 . The method of claim 1 , wherein the first target feature is indicative of at least one of a building, a structure, a road, or a land feature.

5 . The method of claim 1 , wherein the trained feature extraction module performs object recognition trained on at least one set of labeled features.

6 . The method of claim 1 , further comprising:

detecting, by the trained feature extraction module, a second target feature; and

merging the first and second target features based on a distance parameter and the feature specification.

7 . The method of claim 1 , wherein the mapping comprises providing a visual mapping of the first target feature relative to the set of labeled features.

8 . The method of claim 1 , wherein the threshold distance value is based on a center point distance between the first target feature and the first labeled feature.

9 . A system comprising:

one or more processors; and

a memory comprising instructions that, when executed by the one or more processors, cause the system to:

receive information indicative of a geospatial image;

apply a trained feature extraction module to detect a set of detected features;

associate an object type with a first feature in the set of detected features;

map the set of detected features against a set of known features in a labeled image;

determine a distance between the first feature and a nearest feature in the labeled image;

generate a threshold distance value based on the object type and an aggressiveness parameter;

add the first feature to the labeled image when the distance is greater than or equal to the threshold distance value; and

replace the nearest feature with the first feature when the distance is less than the threshold distance value.

10 . The system of claim 9 , wherein the trained feature extraction module detects features based on a feature specification associating the object type with one or more of a shape, an area, or a location.

11 . The system of claim 9 , wherein the object type is at least one of a building type, a structure, or a landmark.

12 . The system of claim 9 , wherein the instructions are further configured to cause the system to generate a labeled image displaying the nearest feature in a first color, and the first feature in a second color.

13 . The system of claim 9 , wherein the instructions are further configured to cause the system to convert the set of known features into a first format comprising at least one of a GeoTIFF file or a shapefile.

14 . The system of claim 9 , wherein the instructions are further configured to cause the system to update the trained feature extraction module with the first feature.

15 . The system of claim 9 , wherein the trained feature extraction module is a machine learning model trained on sets of geospatial images comprising labeled features.

16 . The system of claim 9 , wherein the aggressiveness parameter defines a variability allowance for a feature specification.

17 . A computer program product comprising:

a computer-readable storage medium; and

instructions stored on the computer-readable storage medium that, when executed by a processor, causes the processor to:

receive information indicative of a geospatial image;

apply a trained feature extraction module to detect a first target feature;

cause a display to map the first target feature against a set of labeled features within an area defined by the geospatial image;

determine that the first target feature is new, based on a threshold distance value between the first target feature and a first labeled feature, wherein the threshold distance value is based on a feature specification and a variability allowance for the feature specification; and

update the set of labeled features with the first target feature.

18 . The computer program product of claim 17 , wherein the instructions further include receiving a manual update to the set of labeled features, the manual update refining at least one of a location or a specification associated with the first target feature.

19 . The computer program product of claim 17 , wherein the trained feature extraction module performs object recognition trained on at least one set of labeled features.

20 . The computer program product of claim 17 , wherein the instructions further include labeling the first target feature as an existing feature when a distance between the first target feature and the first labeled feature is below the threshold distance value; and labeling the first target feature as a new feature when the distance between the first target feature and the first labeled feature is greater than or equal to the threshold distance value.