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Application of Google Earth Engine NDVI Trend to Study Yield of Sugarcane Crop Using Sentinel 2 Data
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Author(s): Malathi Narra (Department of Civil Engineering, Velagapudi Ramakrishna Siddhartha Engineering College (Deemed to be University),, India), Harsha Vardhan Reddy (Department of Civil Engineering, Velagapudi Ramakrishna Siddhartha Engineering College (Deemed to be University),, India), Vinay Kumar Gaddam (Department of Civil Engineering, Velagapudi Ramakrishna Siddhartha Engineering College (Deemed to be University),, India), Shashidhar Raju Nandhuri (Department of Civil Engineering, Velagapudi Ramakrishna Siddhartha Engineering College (Deemed to be University),, India), Tejaswini Vallepu (Department of Civil Engineering, Velagapudi Ramakrishna Siddhartha Engineering College (Deemed to be University),, India)and Sai Sumath (Department of Civil Engineering, Velagapudi Ramakrishna Siddhartha Engineering College (Deemed to be University),, India)
Copyright: 2025
Pages: 34
Source title:
Navigating Usability and User Experience in a Multi-Platform World
Source Author(s)/Editor(s): Anacleto Correia (CINAV, Naval Academy, Portugal)
DOI: 10.4018/979-8-3693-2337-3.ch011
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Abstract
Increasing global food demand and the effects of climate change further indicate a need for proper ways of monitoring crop health. This chapter has demonstrated the importance of normalized difference vegetation index (NDVI) as a non-invasive means of monitoring crop health. A review of the literature indicates that NDVI is useful in determining crop stress, diseases, and performance, especially if considered on a long-term basis. This study is based on sugarcane in Vuyyuru Village, Andhra Pradesh, considering NDVI to analyze crop health for the five-year period of 2018-2022. In this chapter, pre-processing Sentinel satellite imagery through atmospheric correction and image registration was carried out to ensure that data accuracy is ensured. The computation of NDVI values each year involves assessing any patterns or variations that are found in crop health spatially. The work sets out to enhance the understanding of the dynamics in crop health through time, thus giving valued insights for any future agricultural management.
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