Field-scale Assessment of Sugarcane for Mill-level Production Forecasting using Indian Satellite Data

• Published in: Journal of the Indian Society of Remote Sensing Vol. 50; no. 2; pp. 313 - 329
• Main Authors: Kumar, Mukesh, Das, Ayan, Chaudhari, K. N., Dutta, Sujay, Dakhore, K. K., Bhattacharya, B. K.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.02.2022; Springer Nature B.V
• Subjects: Crop production; Crop yield; Discrimination; Earth and Environmental Science; Earth Sciences; Economic forecasting; Enumeration; Estimation; Factories; Forecasting; Global positioning systems; GPS; Indian spacecraft; Industrial plants; Mills; Remote Sensing/Photogrammetry; Research Article; Sugar industry; Sugarcane; Satellite Remote Sensing; Crushable Cane Yield; Micro-Scale; Ratoon; Mill-Level Production Forecasting
• ISSN: 0255-660X; 0974-3006
• DOI: 10.1007/s12524-021-01442-2

Estimating sugarcane ( Saccharum officinarum L. ) production at micro-scale prior to harvest is required for fixing of Fair and Remunerative Price (FRP) payable by sugar factories, levy price of sugar and its supply for public distribution systems and regulating supply of free-sale sugar. This may also help the sugar mill owners to plan for crushing the expected cane biomass, estimate the production of sugar in each mill and look for opportunities to sell or buy from nearest sugar mills if expected production is more or less than factory’s crushable capacity. A pilot-scale study was carried out in four sugar mills of Gujarat and Maharashtra states during 2017–2019 period. Multi-date multispectral data from LISS IV, LISS III of Resourcesat-2&2A, GPS and mobile-based ground truth data and Crop Cutting Experiment data (CCE) were used. Crop discrimination in the form of fresh and ratoon, field-scale crop health assessment, yield-model development and mill-level crop acreage and production estimation were carried out. LISS IV data along with error-free GPS-based polygons could lead to discrimination with 95% accuracy and between 88–91% with mobile-based point locations. The mill-level production was found to have less than 10% deviation from reported production. The field-scale assessment and enumeration could lead to mill-level crushable cane production forecast 2 months before harvest. Future efforts are needed to utilize agro-met products and SAR-based metrics to improve the production forecasting.