Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Remote Sensing on 03/07/2018 available online: http://www.tandfonline.com/10.1080/01431161.2018.1479797
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Major trends in the land surface phenology (LSP) of Africa, controlling for land cover change
AU - Adole, Tracy
AU - Dash, Jadunandan
AU - Atkinson, Peter Michael
N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Remote Sensing on 03/07/2018 available online: http://www.tandfonline.com/10.1080/01431161.2018.1479797
PY - 2018
Y1 - 2018
N2 - Monitoring land surface phenology (LSP) trends is important in understanding how both climatic and non-climatic factors influence vegetation growth and dynamics. Controlling for land-cover changes in these analyses has been undertaken only rarely, especially in poorly studied regions like Africa. Using regression models and controlling for land-cover changes, this study estimated LSP trends for Africa from the enhanced vegetation index (EVI) derived from 500 m surface reflectance Moderate-Resolution Imaging Spectroradiometer (MOD09A1), for the period from 2001 to 2015. Overall end of season showed slightly more pixels with significant trends (12.9% of pixels) than start of season (11.56% of pixels) and length of season (LOS) (5.72% of pixels), leading generally to more ‘longer season’ LOS trends. Importantly, LSP trends that were not affected by land-cover changes were distinguished from those that were influenced by land-cover changes such as to map LSP changes that have occurred within stable land-cover classes and which might, therefore, be reasonably associated with climate changes through time. As expected, greater slope magnitudes were observed more frequently for pixels with land-cover changes compared to those without, indicating the importance of controlling for land cover. Consequently, we suggest that future analyses of LSP trends should control for land-cover changes such as to isolate LSP trends that are solely climate-driven and/or those influenced by other anthropogenic activities or a combination of both.
AB - Monitoring land surface phenology (LSP) trends is important in understanding how both climatic and non-climatic factors influence vegetation growth and dynamics. Controlling for land-cover changes in these analyses has been undertaken only rarely, especially in poorly studied regions like Africa. Using regression models and controlling for land-cover changes, this study estimated LSP trends for Africa from the enhanced vegetation index (EVI) derived from 500 m surface reflectance Moderate-Resolution Imaging Spectroradiometer (MOD09A1), for the period from 2001 to 2015. Overall end of season showed slightly more pixels with significant trends (12.9% of pixels) than start of season (11.56% of pixels) and length of season (LOS) (5.72% of pixels), leading generally to more ‘longer season’ LOS trends. Importantly, LSP trends that were not affected by land-cover changes were distinguished from those that were influenced by land-cover changes such as to map LSP changes that have occurred within stable land-cover classes and which might, therefore, be reasonably associated with climate changes through time. As expected, greater slope magnitudes were observed more frequently for pixels with land-cover changes compared to those without, indicating the importance of controlling for land cover. Consequently, we suggest that future analyses of LSP trends should control for land-cover changes such as to isolate LSP trends that are solely climate-driven and/or those influenced by other anthropogenic activities or a combination of both.
U2 - 10.1080/01431161.2018.1479797
DO - 10.1080/01431161.2018.1479797
M3 - Journal article
VL - 39
SP - 8060
EP - 8075
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
SN - 0143-1161
IS - 22
ER -