Open Access

ARTICLE

Spatial Variability Assessment on Staple Crop Yields in Hisar District of Haryana, India Using GIS and Remote Sensing

Sanghati Banerjee¹, Om Pal², Tauseef Ahmad³, Shruti Kanga⁴, Suraj Kumar Singh^1,*, Bhartendu Sajan¹

1 Centre for Climate Change & Water Research, Suresh Gyan Vihar University, Jaipur, 302017, India
2 Haryana Space Applications Centre (HARSAC), Hisar, 125004, India
3 Department of Geography, SakaryaUniversity, Sakarya, 08390, Turkey
4 Department of Geography, School of Environment and Earth Sciences, Central University of Punjab, Bathinda, 151401, India

* Corresponding Author: Suraj Kumar Singh. Email:

(This article belongs to the Special Issue: Geospatial Data Quality: Unraveling the Essentials)

Revue Internationale de Géomatique 2025, 34, 71-88. https://doi.org/10.32604/rig.2025.057963

Received 01 September 2024; Accepted 10 January 2025; Issue published 24 February 2025

Abstract

Agriculture is a primary activity in many countries, with wheat being a major cereal crop in India. Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dynamics, pricing, and trade. This study focuses on estimating wheat acreage and yield in Barwala block, Hisar district, Haryana, for the 2019–2020 Rabi season using remote sensing techniques. Multi-temporal satellite data capturing phenological stages of wheat (Seedling to Ripening) were processed using supervised classification with a maximum likelihood classifier in ERDAS Imagine. Wheat crop acreage was determined by overlaying ground truth points on the classified data. The estimated acreage showed a relative deviation of −1.07% compared to statistics from the Department of Agriculture (DoA), Haryana. Yield assessment employed a Semi-Physical model based on the Modified Monteith Model. Key parameters included Photosynthetically Active Radiation (PAR), fraction of PAR absorbed by wheat (fAPAR), light use efficiency, and water stress derived from the Land Surface Water Index (LSWI) using Sentinel-2 NIR and SWIR-1 bands. Net Primary Productivity (NPP) was computed for the wheat growth period, and grain yield was estimated using a harvest index obtained from literature. The estimated yield had a relative deviation of 9.3% from DoA data. The study demonstrates the potential of multi-temporal satellite imagery for accurate block-level wheat acreage and yield estimation, providing a valuable tool for agricultural planning and policy-making.

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Keywords

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