Using Deep learning and GIS applications to Extract Features from Remote Sensing Data

Section: Article
Issue
Vol. 22 No. 2 (2025): Volume 22 Issue 2
Published
Nov 30, 2025
Pages
17-25

Abstract

In recent years, artificial intelligence (AI) has advanced quickly, equal or perhaps even outperforming human accuracy in tasks like picture recognition, reading comprehension, and text translation.  Large-scale opportunities that were not previously available are now had been created by the confluence of AI and GIS with remote sensing data processing. The motivation of current study is to incorporate deep learning models that implemented through ArcGIS Pro tools particularly convolutional neural networks (CNNs), identifying complex patterns and features in high-resolution image. An automated Deep Learning model type Mask R-CNN had applied to extract model for training objects. The overall accuracy metric improved the performance of the current work accurately with less error when calculating RMSE criteria.

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Author

Faten Azeez Mustafa

Image Processing Dept., Remote Sensing Center, University of Mosul , Mosul ,Iraq

Identifiers

https://doi.org/10.33899/iqjoss.v22i2.54069
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How to Cite

Mustafa , F. A. . (2025). Using Deep learning and GIS applications to Extract Features from Remote Sensing Data. IRAQI JOURNAL OF STATISTICAL SCIENCES, 22(2), 17–25. https://doi.org/10.33899/iqjoss.v22i2.54069