E3S Web Conf.
Volume 232, 2021International Conference on Agribusiness and Rural Development (IConARD 2020)
|Number of page(s)||15|
|Published online||25 January 2021|
Rice Crop Phenology Model to Monitor Rice Planting and Harvesting Time using Remote Sensing Approach
Department of Geography, Faculty of Mathematics and Natural Sciences, University of Indonesia, 16424, Jawa Barat, Indonesia
* Corresponding author: firstname.lastname@example.org
Rice is one of the most significant food commodity products in Indonesia. The production of rice in 2019 reached 49.8 million tons. On a global scale, rice is consumed by half of the human population around the world. This study will support the development of sustainable natural resources management, which is an important thing to the realization of the Sustainable Development Goals in zero poverty and zero hunger. Remote sensing is a useful instrument to monitor natural resources. This study used Sentinel-2 imageries to extract rice phenology using vegetation indices (NDVI and NDWI), then acquired the planting and harvesting time using the temporal analysis. The NDVI value is showing a parabolic curve regarding the planting stage of the rice. The value of NDVI is high in the transplanting stage but decreases in the harvesting phase. Besides that, in the seedling and transplanting stage, NDWI has a higher value than NDVI. However, in tillering until the harvesting phase, NDWI has a similar characteristic but lower value than NDVI. Based on the spatial and temporal distribution of rice planting and harvesting date, it is known that climate is not a resistant factor, especially the irrigated rice field. Nevertheless, in the rainfed rice field, the planting time depends on climate conditions.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.