Creat membership Creat membership
Sign in

Forgot password?

Confirm
  • Forgot password?
    Sign Up
  • Confirm
    Sign In
Creat membership Creat membership
Sign in

Forgot password?

Confirm
  • Forgot password?
    Sign Up
  • Confirm
    Sign In
Collection
For ¥0.57 per day, unlimited downloads CREATE MEMBERSHIP Download

toTop

If you have any feedback, Please follow the official account to submit feedback.

Turn on your phone and scan

home > search >

Hybrid Model for Forecasting of Changes in Land Use and Land Cover Using Satellite Techniques

Author:
Mercedes Marquez, Adriana  Guevara, Edilberto  Rey, Demetrio  


Journal:
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING


Issue Date:
2019


Abstract(summary):

This paper proposes a hybrid model identified as krig-ging ordinary-forecasting models that contributes to predict the spatio-temporal of land use and land cover (LULC) changes using a unique predictor variable represented by the surface reflectance derived of satellite images, transformed in the principal component 1 (PC1). The tools used allow knowing the trends of spatial and temporal prediction models of PC1 semivariances and to judge the adjustment between observed and predicted variables by analyzing prediction statistics as: root-mean-squared error, mean absolute error, mean absolute percentage error, mean error, and mean percentage error. From the observation of statistics, the best spatio-temporal adjustment can be selected. The prediction of LULC changes through the PC1 prediction can be followed for different future time into the time series. The samples evaluated of PC1 prediction in the validation stage give a correlation coefficient upper to 0.8 and adjusted determination coefficient upper to 0.7; being a successful adjustment between observed and predicted values allowing to select the hybrid model proposed to forecast the PC1 variable in a future time. Likewise, an extensive time series is not required to get a good prediction, which has been obtained as a result of the test of three annual time series in different period constituted by a minimum of five years (2014-2018) and a maximum of eight years (1991-2003).


Page:
252---273


VIEW PDF

The preview is over

If you wish to continue, please create your membership or download this.

Create Membership

Similar Literature

Submit Feedback

This function is a member function, members do not limit the number of downloads