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Land use and land cover detection system using an intelligent framework

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Abstract

Remote Sensing is an interesting topic for many applications to recognize the complete land resource through satellite images. However, the key drawback behind this remote sensing paradigm is analyzing the feature. Because the presence of noisy content has maximized the risk of identifying the features present in the satellite images. So, the current article has planned to invent the novel Vulture-based Convolutional Land behavior Prediction (VbCLBP) by extracting the land features from the satellite images and collecting the land resource information by tracking land-use area. Moreover, the resources such as water, forest, crop, barren and urban regions are considered. The region obtained to track the estimated resources is the Andhra Pradesh-Chittoor location. Here, satellite images from the year 2017 to 2021 were utilized. Furthermore, the planned method is elaborated in the Google-Earth-Engine platform, written in java language. Also, the proficient measure of the developed novel VbCLBP was estimated with some significant metrics like kappa score and accuracy.

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Authors and Affiliations

  1. Department of Electronics and Communications Engineering, Sri Venkateswara University College of Engineering (SVUCE), Tirupati, Andhra Pradesh, 517502, India

    S. Rohini & S. Narayana Reddy

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  1. S. Rohini
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  2. S. Narayana Reddy
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Correspondence to S. Rohini.

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Rohini, S., Reddy, S.N. Land use and land cover detection system using an intelligent framework. Int. j. inf. tecnol. 15, 1661–1677 (2023). https://doi.org/10.1007/s41870-023-01200-2

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