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

Abstract

Many studies have recently explored information from satellite-remotely sensed data (SRSD) for estimating crop production statistics. The value of this information depends on the aerial and spatial resolutions of SRSD. SRSD with fine spatial resolution is costly and 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 information from Wide Field Sensor (WiFS) and Linear Imaging Self Scanner (LISS-III) data from the Indian Remote Sensing (IRS-1D) satellite and crop-cutting experiment data collected by probability sampling design from a list frame of villages. We find that relative efficiencies of multiple-frame estimators are high in comparison to single-frame estimators.

Using HJ-CCD image and PLS algorithm to estimate the yield of field-grown winter wheat

“…The data sources of the earth observation satellites were chiefly low spatial resolution MODIS, national oceanic and atmospheric administration (NOAA)/AVHRR images 23,28 , medium spatial resolution India remote-sensing satellite (IRS-P6), enhanced thematic mapper (ETM), thematic mapper (TM) images, and high spatial resolution Quickbird, SPOT, IKONOS, ALOS foreign images [29][30][31] . However, these data sources were expensive, which limited their use in small and medium research units and production management departments 32,33 .Therefore, it was of great significance to promote the application of image data obtained by satellites developed by China in remote sensing of agricultural conditions. On September 6, 2008, China successfully launched satellites A and B (abbreviated as HJ-CCD) of the "Environment and Disaster Monitoring and Forecasting Small Satellite Constellation System" with independent intellectual property rights.…”