I have some GPS point of wheat cropland, using these GPS points I want to find NDVI values of wheat crops for three months i.e. January, February, and March. Based on these NDVI values i want to classify Wheat crops using Decision tree method. Please provide me the detailed way to perform decision tree method.
Dear Avinash,
I have extensively used decision tree method during my doctoral research. Check these two papers in my profile:
1) Landscape control of nitrous oxide emissions during the transition from conservation reserve program to perennial grasses for bioenergy
2) Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models
I believe you have NDVI as a response variable and you want to predict that with lat-long and possibly other variables. I have used "rpart" function in R to construct the tree. I would be happy to help you with that. Before that, I need to know more about what exactly you want to do and the data structure.
I hope it was helpful.
Best,
Debasish
Dear Debasish
Thanks for your warm response. Actually, i have some NDVI value of particular crops (i.e wheat, gram , mustard) extracted with the help of GPS point (GPS point was taken during field visit). Now i want to classify various crops with the help of these NDVI value of specific crop.
Regards with respect
Avinash
I want to use these value in decision tree method to classify various crop.
Hi Avinash,
If you are familiar with R statistical software, you can try something like this:
#install the required packages
library(rpart)
set.seed(500) # Use the same seed to get the same forest output
# Make the tree
tree=rpart(NDVI~Crop, data=data, method="anova", control=rpart.control(minsplit=10))
#plot the tree
plot(tree, margin=0.1, uniform=T, main="")
text(tree, use.n=T, cex=0.9)
summary(tree)
This should make a tree classifying the crops based on their respective NDVI values. You can also include other independent variables if you have measurements available.
Let me know if this works.
Good luck!
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