Identification of Empty Land Based on Google Earth Using Convolutional Neural Network Algorithm

Authors

  • Islam Nur Alam Computer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia https://orcid.org/0000-0001-5320-5534
  • Renaldy Fredyan Computer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia
  • Ghinaa Zain Nabiilah Computer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia
  • Samsul Arifin Statistics Department, School of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia

Keywords:

CNN, Google Earth, Vacant Land Classification

Abstract

The development of digital image technology has experienced rapid development, both in terms of the development of models and algorithms used as well as the quality and results of the management process carried out. Utilization of digital image management can be used in classifying the condition of vacant land in certain areas. A high level of urbanization causes an increase in population growth and uneven development in certain areas. Advanced technology has resulted in a vast constellation of satellites and aerial platforms. In general, many remote sensing images with an excellent spatial resolution (VFSR) are commercially available to the general public, like google earth. This platform provides much information regarding spatial conditions. So, data available on the platform allows it to be used as a medium for analyzing and classifying the availability of vacant land in certain areas. To support good regional and city planning and overcome problems due to high levels of urbanization, a model that can automatically classify vacant land in certain areas is needed using data that is openly available on Google Earth. Thus, this study experimented by classifying vacant land based on images from google earth using the Deep Learning model, namely Convolutional Neural Network (CNN). The CNN method is used because of its superiority in classifying images. The experiment results have an optimal for image classification using the CNN algorithm.

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System Design and Implementation

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Published

17.02.2023

How to Cite

Nur Alam, I. . ., Fredyan, R. ., Zain Nabiilah, G. ., & Arifin, S. . (2023). Identification of Empty Land Based on Google Earth Using Convolutional Neural Network Algorithm. International Journal of Intelligent Systems and Applications in Engineering, 11(2), 582–587. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2714

Issue

Vol. 11 No. 2 (2023)

Section

Research Article

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