What technique should I use to develop the model so that I can predict the response of Landsat data out of range?

If I have the time series data of Landsat from 2013 to 2022, what method should I use so that I can predict the response of landsat out of this range?

Such as If i want to predict the response in 1945 or 2025, what technique should I use?

Answer 1

[Vatsal]

Hi,

I understand that you want to predict the response of Landsat beyond the available data range. To predict the response of Landsat beyond the available data range (2013 to 2022), you can utilize the time series forecasting methods.

Here are some methods to forecast the Landsat response beyond the currently available data range:

- ARIMA (AutoRegressive Integrated Moving Average): This method models the relationship between observations in a time series and can be used for predicting future values.

You can find more information here: https://in.mathworks.com/help/econ/arima.html

- SARIMA (Seasonal ARIMA): Useful for data with seasonal patterns, SARIMA extends ARIMA to handle seasonal components in the data.

You can find more information here: https://in.mathworks.com/help/econ/specify-regression-model-with-sarima-errors.html

- LSTM (Long Short-Term Memory) Neural Networks: A type of recurrent neural network (RNN) capable of learning patterns in sequential data like time series.

You can find more information here: https://in.mathworks.com/help/deeplearning/ref/nnet.cnn.layer.lstmlayer.html

I hope this helps!