Multi source geographic information system (GIS) web based data visualization and interaction for vegetation management

1. A system comprising:

a vegetation management module to receive image data from an image source;

a memory for storing program instructions;

a vegetation management processor, coupled to the memory, and in communication with the vegetation module, and operative to execute program instructions to:

receive first image data and second image data for an area of interest;

overlay the first image data over the second image data to generate an overlaid image;

receive feeder attribute data for at least one feeder in the overlaid image, the feeder attribute data including at least a number of customers affected in the area of interest by outage of the at least one feeder;

generate a risk score for the at least one feeder based in part on the received feeder attribute data; and

generate a visualization based on the at least one feeder and the generated risk score.

2. The system of claim 1 , further comprising program instructions to:

identify at least one feeder in the overlaid image that includes vegetation in a buffer zone for that feeder, wherein the identification of the at least one feeder is prior to receipt of the feeder attribute data.

3. The system of claim 2 , further comprising program instructions to:

determine whether the vegetation in the buffer zone for the identified at least one feeder exceeds a threshold value.

4. The system of claim 1 , wherein the first image data is satellite image data and the second image data is geographic information system (GIS) data, and the second image data is received from a utility company.

5. The system of claim 1 , wherein the risk score predicts a risk of utility outage of the feeder.

6. The system of claim 1 , further comprising program instructions to:

generate at least one geospatial cluster including two or more feeders.

7. The system of claim 6 , wherein the feeders in the geospatial cluster include: 1. a same or similar risk score, and 2. are located in a same geographic location.

8. The system of claim 1 , further comprising program instructions to:

generate a trim schedule for at least one feeder based on the generated risk score.

9. The system of claim 8 , wherein the trim schedule includes a hot spot trim of the at least one feeder.

10. The system of claim 1 , wherein the feeder attribute data is at least one of weather data, prior outage data, last trimming date data, next trimming date data, vegetation modelling analytics.

11. The system of claim 1 , wherein the risk score is generated by a risk score model trained via a machine learning technique.

12. The system of claim 1 , wherein the visualization is at least one of a map, a graph and a table.

13. A method comprising:

receiving first image data and second image data for an area of interest;

overlaying the first image data over the second image data to generate an overlaid image;

receiving feeder attribute data for at least one feeder in the overlaid image, the feeder attribute data including at least a number of customers affected in the area of interest by outage of the at least one feeder;

generating a risk score for the at least one feeder based in part on the received feeder attribute data;

generating a visualization based on the at least one feeder and the generated risk score; and

generating a trim schedule for at least one feeder based on the generated risk score.

14. The method of claim 13 , further comprising:

identifying at least one feeder in the overlaid image that includes vegetation in a buffer zone for that feeder, wherein the identification of the at least one feeder is prior to receipt of the feeder attribute data.

15. The method of claim 13 , further comprising:

determining whether the vegetation in the buffer zone for the identified at least one feeder exceeds a threshold value.

16. The method of claim 13 , wherein the first image data is satellite image data and the second image data is geographic information system (GIS) data, and the second image data is received from a utility company.

17. The method of claim 13 , wherein the risk score predicts a risk of utility outage of the feeder.

18. The method of claim 13 , further comprising:

generating at least one geospatial cluster including two or more feeders, wherein the feeders in the geospatial cluster include: 1. a same or similar risk score, and 2. are located in a same geographic location.

19. A non-transitory, computer-readable medium storing instructions that, when executed by a computer processor, cause the computer processor to perform a method comprising:

receiving first image data and second image data for an area of interest;

overlaying the first image data over the second image data to generate an overlaid image;

receiving feeder attribute data for at least one feeder in the overlaid image, the feeder attribute data including at least a number of customers affected in the area of interest by outage of the at least one feeder;

generating a risk score for the at least one feeder based in part on the received feeder attribute data;

generating a visualization based on the at least one feeder and the generated risk score; and

generating a trim schedule for at least one feeder based on the generated risk score.

20. The medium of claim 19 , further comprising:

generating at least one geospatial cluster including two or more feeders, wherein the feeders in the geospatial cluster include: 1. a same or similar risk score, and 2. are located in a same geographic location.