Using AVHRR-Based Vegetation Health Indices For Estimation Of Potato Yield In Bangladesh

Rahman, Asif

doi:10.4172/2165-784x.1000111

J Civil Environment Engg

2012

DOI: 10.4172/2165-784x.1000111

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Using AVHRR-Based Vegetation Health Indices For Estimation Of Potato Yield In Bangladesh

Asif Rahman¹

Abstract: We developed a model correlating Advanced Very High Resolution Radiometer (AVHRR)-based Temperature Condition Index (TCI) and Vegetation Condition Index (VCI) with potato yield in Bangladesh. Weekly TCI and VCI Indices for 1993-2005 along with official potato yield statistics were used for model development. We found a strong correlation between inter annual variation in potato yield and TCI and VCI during the critical period of potato growth (vegetative phase and tuber initiation), mid-December to mid-January… Show more

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Cited by 6 publications

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A Systematic Review of Vegetation Indices for Potato Growth Monitoring and Tuber Yield Prediction from Remote Sensing

Mukiibi,

Machakaire,

Franke

et al. 2024

Potato Res.

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Crop intelligence and yield prediction of potato (Solanum tuberosum L.) are important to farmers and the processing industry. Remote sensing can provide timely information on growth status and accurate yield predictions during the growing season. However, there is limited documentation on the most suitable vegetation indices (VIs) and optimal growth stages for acquiring remote sensing imagery of potato. To address this knowledge gap, a systematic review was conducted. Original scientific manuscripts published between 2000 and 2022 were identified using various databases. The findings indicate that satellite imagery is the most widely used source of remote sensing data for tuber yield prediction, whereas unmanned aerial vehicle systems (UAVs) and handheld sensors are more frequently applied for growth monitoring. The normalized difference vegetation index (NDVI), red-edge chlorophyll index (CIred-edge), green chlorophyll index (CIgreen), and optimized soil-adjusted vegetation index (OSAVI) are the most frequently used VIs for the growth and yield estimation of potato. The tuber initiation stage was found to be the most appropriate stage for remote sensing data acquisition. This review will assist potato farmers, agronomists and researchers in selecting the most suitable VIs for monitoring specific growth variables and selecting the optimal timing during the growing season to obtain remote sensing images.

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A Systematic Review of Vegetation Indices for Potato Growth Monitoring and Tuber Yield Prediction from Remote Sensing

Mukiibi,

Machakaire,

Franke

et al. 2024

Potato Res.

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A review of remote sensing for potato traits characterization in precision agriculture

Sun

Zhou

et al. 2022

Front. Plant Sci.

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Potato is one of the most significant food crops globally due to its essential role in the human diet. The growing demand for potato, coupled with severe environmental losses caused by extensive farming activities, implies the need for better crop protection and management practices. Precision agriculture is being well recognized as the solution as it deals with the management of spatial and temporal variability to improve agricultural returns and reduce environmental impact. As the initial step in precision agriculture, the traditional methods of crop and field characterization require a large input in labor, time, and cost. Recent developments in remote sensing technologies have facilitated the process of monitoring crops and quantifying field variations. Successful applications have been witnessed in the area of precision potato farming. Thus, this review reports the current knowledge on the applications of remote sensing technologies in precision potato trait characterization. We reviewed the commonly used imaging sensors and remote sensing platforms with the comparisons of their strengths and limitations and summarized the main applications of the remote sensing technologies in potato. As a result, this review could update potato agronomists and farmers with the latest approaches and research outcomes, as well as provide a selective list for those who have the intentions to apply remote sensing technologies to characterize potato traits for precision agriculture.

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An Ongoing Blended Long-Term Vegetation Health Product for Monitoring Global Food Security

2020

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Remotely observing global vegetation from space has endured for nearly 50 years. Many datasets have been developed to monitor vegetation status. Tailored to specifically monitor global food security concerning drought and crop yield, a suite of datasets based on vegetation health concepts and Advanced Very High Resolution Radiometer (AVHRR) observation was developed in the 1980s and utilized throughout the world. Nowadays, satellites based imaging radiometers have evolved into the Visible Infrared Imaging Radiometer Suite (VIIRS) era. With proper algorithm development, the blended version of the data suite, composed of the AVHRR dataset from 1981 to 2012 and VIIRS dataset from 2013 and afterwards, has bridged the long-term AVHRR observation and high-quality VIIRS data. This paper explains the blended version of the data suite.

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Using AVHRR-Based Vegetation Health Indices For Estimation Of Potato Yield In Bangladesh

Cited by 6 publications

References 6 publications

A Systematic Review of Vegetation Indices for Potato Growth Monitoring and Tuber Yield Prediction from Remote Sensing

A Systematic Review of Vegetation Indices for Potato Growth Monitoring and Tuber Yield Prediction from Remote Sensing

A review of remote sensing for potato traits characterization in precision agriculture

An Ongoing Blended Long-Term Vegetation Health Product for Monitoring Global Food Security

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