Maram Bhargav Reddy
Research Scholar
School of Natural Resources Management, College of Post Graduate Studies in Agriculture Sciences, CAU(I), Umiam, Meghalaya, India
Sushree Panda
Assistant Professor
School of Tribal Resource Management,
Kalinga Institute of Social Sciences Deemed to be University, Bhubaneswar, Odisha, India [email protected]
Abstract
Accurate crop discrimination is essential for agricultural monitoring, yield prediction, and sustainable resource management. This study leverages Sentinel-2 temporal profiles to analyze the phenological behavior of four economically significant crops—rice (Oryza sativa), maize (Zea mays), cotton (Gossypium hirsutum), and red gram (Cajanus cajan)—in the semi-arid Jogulamba Gadwal region of Telangana, India, during the 2020–2021 growing season. Using 12-day interval NDVI time-series data, we derived distinct growth patterns for each crop: rice exhibited rapid NDVI rise and fall (peak: 0.8–0.9 at 60–75 days), maize showed a gradual peak (0.8–0.85 at 60–80 days), cotton displayed prolonged high NDVI during boll development (0.7–0.8 for 80–110 days), and red gram had an earlier peak (0.7–0.75 at 50–70 days).
KISS International Journal of Entrepreneurship, Innovation and Sustainability (KIJEIS) 2025 Jul, Vol.1 (1): 58 – 64