Download PDFOpen PDF in browserAutomatic Modelling of Land Use Suitability Using Deep Feedforward Networks in Leon - Silao, Guanajuato Region9 pages•Published: November 4, 2019AbstractLand use change is a global phenomenon that impacts directly to the urban growth and it should be addressed from different disciplines to minimize the potential negative effects of urbanization predicting the spatial urban growth. The urban growth dynamics might be very complicated and difficult to model, nevertheless it is necessary to understand the causes of the dynamics and the dynamics itself to build precise computational models that help to detect problems generated by urban land use change. For that reason, we propose the study of the land use suitability sub-model used by several models to make land use spatial predictions. This sub-model is implemented as a logistic regression based on linear correlations. The problem is that this model is limited to capture a variety of nonlinear relations among variables for prediction and classification purposes. We propose to use an alternative based on Deep Feedforward Networks able to deal with this problem.In Mexico, the urban growth will increase considerably the number of cities during the next decade where the Mexican population will be concentrated. That means that the generation and study of existing spatio-temporal computational frameworks for studying the Mexican urban growth is very relevant. Therefore we present an initial contribution comparing Deep Feedforward Networks with a Multi-Level Linear Logistic Regression as land suitability models applied to Mexican land use classification. We show that basic deep feedforward models outperform in allocation accuracy to linear logistic regression, and also minimizes the parameters tuned by trial and error. Keyphrases: deep feedforward network, land suitability, land use classification, multi level linear logistic regression, non linear model In: Oscar S. Siordia, José Luis Silván Cárdenas, Alejandro Molina-Villegas, Gandhi Hernandez, Pablo Lopez-Ramirez, Rodrigo Tapia-McClung, Karime González Zuccolotto and Mario Chirinos Colunga (editors). Proceedings of the 1st International Conference on Geospatial Information Sciences, vol 13, pages 96-104.
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