Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data fusion represents a porful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own.  focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study,  compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-ighted logistic regression (GWR), as ll as classification and regression trees (CART).  ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference beten the methods. Hover, GWR was found to perform better than the other tested methods in areas with high disagreement beten the inputs.
['M. Lesiv', 'Elena Moltchanova', 'D. Schepaschenko', 'Linda See', 'A. Shvidenko', 'Alexis J. Comber', 'Steffen Fritz']
I am writing a research paper on a idea Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map
[{"from": "human", "value": "I am writing a research paper on a idea Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data fusion represents a porful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own.  focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study,  compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-ighted logistic regression (GWR), as ll as classification and regression trees (CART).  ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference beten the methods. Hover, GWR was found to perform better than the other tested methods in areas with high disagreement beten the inputs."}]