Claims:1. A method for agriculture field clustering and ecological forecasting based on the clustered agriculture fields, said method comprising processor implemented steps of:

a. capturing an absolute ground data representing a plurality of field measurements of a plurality of agriculture fields using a rural participatory sensing module (208);
b. capturing a plurality of weather conditions of the plurality of agriculture fields using an on-farm sensing module (210);
c. generating a feature set comprising of said absolute ground data and weather data of the plurality of agriculture fields using a feature set generation module (212);
d. adaptively clustering the plurality of agriculture fields based on the feature set to generate a cluster; wherein at least one feature out of the feature set is present in each agriculture field of the cluster using clustering module (214) ;
e. generating a generic forecasting model for ecological forecasting comprising of common features of the feature set in said cluster using a generic forecasting generation module (216);
f. selecting at least one feature out of the feature set for generating a plurality of adaptive forecasting model based for ecological forecasting on the selected feature out of the feature set using an adaptive forecasting generation module (218); and
g. recommending a plurality of control measures to a user based on said generated adaptive forecasting model using a recommendation generation module (220).

2. The method as claimed in claim 1, wherein the absolute ground data and the weather condition data is stored with a plurality of other farming data in a database (222).

3. The method as claimed in claim 2, wherein the absolute ground data further comprises of actual on field observation and incidents.

4. The method as claimed in claim 1, wherein all models including the generic model for each cluster and multiple models within each cluster will be adapted with the actual observations.

5. The method as claimed in claim 1, wherein the feature set is selected from a group comprising but not limiting to crop variety, meteorological parameters, vegetation indices, field specific activities, soil parameters, morphological parameters of watershed, crop contextual data, climatic parameters and a combination thereof.

6. A system for agriculture field clustering and adaptive ecological forecasting, said system comprising:
a processor;
a data bus coupled to said processor; and
a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for executing:

a. a rural participatory sensing module (208) configured for capturing an absolute ground data representing a plurality of field measurements of a plurality of agriculture fields;
b. an on-farm sensing module (210) configured for capturing a plurality of weather conditions of the plurality of agriculture fields;
c. feature set generation module (212) configured for generating a feature set comprising of said absolute ground data and weather data of the plurality of agriculture fields;
d. a clustering module (214) configured for adaptively clustering the plurality of agriculture fields based on the feature set to generate a cluster; wherein at least one feature out of the feature set must be common in each agriculture field of the cluster
e. generic forecasting generation module (216) configured for generating a generic forecasting model for ecological forecasting comprising of common features of the feature set in said cluster set
f. adaptive forecasting generation module (218) configured for selecting at least one feature out of the feature set for generating a plurality of adaptive forecasting model based for ecological forecasting on the selected feature out of the feature set; and
g. a recommendation generation module (220) configured for recommending a plurality of control measures to a user based on said generated adaptive forecasting model.

7. The system as claimed in claim 6, wherein the adaptive forecasting model is configured to be adaptively modified based on inclusion of new fields.

8. The system as claimed in claim 6, wherein the generic model for each cluster and multiple models within each cluster is configured to be adaptively modified based on the actual observations.

9. The system as claimed in claim 6, wherein the repository is configured to store the absolute ground data with a plurality of other farming data (224).
, Description:As Attached