Exploring 16 years changing dynamics for land use/land cover in Pearl City (Thoothukudi) with spatial technology

Comparison between Object-based Method and Deep Learning Method for Extracting Road Features Using Submeter-grade High-resolution Satellite Imagery

“…16, the quality analysis involved using the confusion matrix to calculate the recall and accuracy of the road features extracted using the developed object-based spatial feature extraction software, the commercial software, and the deep-learning-based module using Eqs. (1) and (2). The quality analysis was conducted with the confusion matrix using the extracted road features and the ground truth.…”

“…The area of the target region selected for this study is approximately 6.167 km 2 . The top left corner of the region is at 531054.370m(N), 281930.629m(E) and the bottom right corner is at 528257.670m(N), 284172.949m(E), using the GRS80 TM coordinate system.…”

“…(1) LU and land cover (LC) changes over a certain period are essential to understand the development of human activities within a region to define the impact of anthropogenic and natural activities. (2) Remote sensing technology, which is similar to LU classification and spatial feature extraction technologies, provides information about the environment on a regional or global scale using time-series data, as well as real-time data. (3,4) Various image classification technologies associated with LU classification and spatial feature extraction have been developed.…”