2018
DOI: 10.5194/isprs-archives-xlii-1-79-2018
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Honey Crop Estimation From Space: Detection of Large Flowering Events in Western Australian Forests

Abstract: <p><strong>Abstract.</strong> Recent studies have shown that in the spectral space there is often a better spectral separation between leaves and flowers and even between flowers of different species than between leaves of different species. In this study we assess the ability of satellite remotely sensed data to detect the flowering of Red Gum trees (<i>Corymbia calophylla</i>) in Western Australia, the state’s largest annual honey crop. Spectroradiometer measurements of flowers,… Show more

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Cited by 2 publications
(3 citation statements)
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“…The flowering index data for collection sites was based on satellite images using Sentinel-3 satellite remote sensing platform. To develop a reliable temporal curve, a moving average of the maximum calculated marri flowering index by the ratio of Band 6 to Band 1 (MFI; according to Campbell and Fearns [ 43 ]) over a 14-day period was used. This is similar to the maximum window approach commonly used to calculate other vegetation indices, such as the 16-day Normalised Difference Vegetation Index (NDVI) product produced by NASA [ 44 ].…”
Section: Methodsmentioning
confidence: 99%
“…The flowering index data for collection sites was based on satellite images using Sentinel-3 satellite remote sensing platform. To develop a reliable temporal curve, a moving average of the maximum calculated marri flowering index by the ratio of Band 6 to Band 1 (MFI; according to Campbell and Fearns [ 43 ]) over a 14-day period was used. This is similar to the maximum window approach commonly used to calculate other vegetation indices, such as the 16-day Normalised Difference Vegetation Index (NDVI) product produced by NASA [ 44 ].…”
Section: Methodsmentioning
confidence: 99%
“…While the model does not produce the lowest errors, it is nonetheless a reliable predictor (particularly for 'good years' versus non-good years). The lower accuracy of the prediction is offset by the lead time to the honey flow; with honey flow generally starting in late January to early February [32], having a strong indicator of an upcoming good harvest by the end of November gives apiarists approximately two months to prepare for the predicted conditions. The models with the lowest errors are highlighted in green.…”
Section: 6%mentioning
confidence: 97%
“…The Marri Flowering Index (MFI), developed by Campbell and Fearns [32], was designed for direct detection of marri flowers from MODIS data, based on an analysis of spectroradiometer surveys of this particular species. While the MFI has proven to be an effective index for classifying the marri honey harvest weight for some apiary sites with a high proportion of canopy cover [32], it appears to be less reliable across multiple apiary sites and years [9].…”
Section: Satellite-derived Datamentioning
confidence: 99%