A multiple-frame approach of crop yield estimation from satellite remotely sensed data

TL;DR

This paper presents a multiple-frame estimation method combining satellite remote sensing data and crop sampling to improve wheat yield accuracy in Haryana, India, demonstrating higher efficiency than single-frame approaches.

Contribution

It introduces a novel multiple-frame estimator integrating satellite data and crop sampling for crop yield estimation, enhancing precision over traditional single-frame methods.

Findings

Multiple-frame estimators show higher relative efficiency.

Combining WiFS and LISS-III data improves yield estimates.

Method applied to wheat yield in Haryana, India.

Abstract

Many studies have recently explored the information from the satellite-remotely sensed data (SRSD) for estimating the crop production statistics. The value of this information depends on the aerial and spatial resolutions of SRSD. The SRSD with fine spatial resolution is costly and the aerial coverage is less. Use of multiple frames of SRSD in the estimation process of crop production can increase the precision. We propose an estimator for the average yield of wheat for the state of Haryana, India. This estimator uses the information from the Wide Field Sensor (WiFS) and the Linear Imaging Self Scanner (LISS-III) data from the Indian Remote Sensing satellite (IRS-1D) and the crop cutting experiment data collected by probability sampling design from a list frame of villages. We find that the relative efficiencies of the multiple-frame estimators are high in comparison to the single frame estimators.