AN OPTIMIZED ARTIFICIAL NEURAL NETWORK FOR THE CLASSIFICATION OF URBAN ENVIRONMENT COMFORT USING LANDSAT-8 REMOTE SENSING DATA IN GREATER JAKARTA AREA, INDONESIA

Nurwita Mustika Sari, Dony Kushardono, Mukhoriyah, Kustiyo, Masita Dwi Mandini Manessa

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The development of computer vision technology as a type of artificial intelligence is increasing rapidly in various fields. This method uses deep learning methods based on artificial neural networks, a well-performed algorithm in multi-parameter analysis. One of the development of computer vision models and algorithms is for a thematic digital image classification, such as environmental analysis. Remote sensing based digital image classification is one of the reliable tools for environmental quality analysis. This study aims to perform neural network optimization for the analysis of the urban environment comfort based on satellite data. The input data used are 4 types of geobiophysical indexes as urban environmental comfort parameters derived from cloud-free annual mosaics Landsat-8 remote sensing satellite data. The results obtained in this study indicate that the 1 hidden layer neural network architecture with 16 neurons for the classification of urban environmental comfort and 10 other land cover classes is quite good. The result of the classification using this optimized artificial neural network shows that the distribution of classes is very uncomfortable which dominates the Greater Jakarta area and its surroundings. For other classes in the study area, some are uncomfortable and rather comfortable. By using this method, we obtained a fast classification training time of 18 seconds for 145 iterations to achieve an RMS Error of 0.01, and has a fairly high classification accuracy overall 89% with a Kappa coefficient of 0.88, while the 2 hidden layer neural network architecture does not succeed in achieving convergence.

Original languageEnglish
Pages (from-to)743-755
Number of pages13
JournalJournal of Applied Engineering and Technological Science
Volume4
Issue number2
DOIs
Publication statusPublished - 2023

Keywords

  • Artificial Intelligence
  • Digital classification
  • Landsat-8
  • Neural Network optimization
  • Urban Environment Comfort

Fingerprint

Dive into the research topics of 'AN OPTIMIZED ARTIFICIAL NEURAL NETWORK FOR THE CLASSIFICATION OF URBAN ENVIRONMENT COMFORT USING LANDSAT-8 REMOTE SENSING DATA IN GREATER JAKARTA AREA, INDONESIA'. Together they form a unique fingerprint.

Cite this