Abstract
The physical cover that present on the earth's surface is referred as land cover. It includes forests, water bodies, grass, asphalt, bare ground etc. The data acquisition of the land cover is mostly done by remote sensing. The acquired data is then categorized into different land covers, by the process of land cover classification. The selection of land cover classification method and its complexity depends upon the landscape under consideration. Various researches are going on the field of land cover classification as its application is spreading in to various areas like disaster management, urban planning, management in various fields like ecology, wild life and so on. This paper presents a review on various recent approaches for land cover classification which includes the statistical, machine learning and deep learning methods and its efficiency in classifying different terrains.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 4th International Conference on Microelectronics, Signals and Systems, ICMSS 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781665448857 |
| DOIs | |
| Publication status | Published - 2021 |
| Event | 4th International Conference on Microelectronics, Signals and Systems, ICMSS 2021 - Kollam, India Duration: 18-11-2021 → 19-11-2021 |
Publication series
| Name | Proceedings of the 4th International Conference on Microelectronics, Signals and Systems, ICMSS 2021 |
|---|
Conference
| Conference | 4th International Conference on Microelectronics, Signals and Systems, ICMSS 2021 |
|---|---|
| Country/Territory | India |
| City | Kollam |
| Period | 18-11-21 → 19-11-21 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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SDG 15 Life on Land
All Science Journal Classification (ASJC) codes
- Control and Optimization
- Signal Processing
- Information Systems
- Information Systems and Management
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
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