Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2

The short revisit times afforded by recently-deployed optical satellite sensors that acquire 3–30 m resolution imagery provide new opportunities to study seasonal vegetation dynamics. Previous studies demonstrated a successful retrieval of phenology with Sentinel-2 for relatively stable annual growi...

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Autores principales: Cheng, Yan, Vrieling, Anton, Fava, Francesco P., Meroni, Michele, Marshall, Michael, Gachoki, Stella
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://hdl.handle.net/10568/129593
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author Cheng, Yan
Vrieling, Anton
Fava, Francesco P.
Meroni, Michele
Marshall, Michael
Gachoki, Stella
author_browse Cheng, Yan
Fava, Francesco P.
Gachoki, Stella
Marshall, Michael
Meroni, Michele
Vrieling, Anton
author_facet Cheng, Yan
Vrieling, Anton
Fava, Francesco P.
Meroni, Michele
Marshall, Michael
Gachoki, Stella
author_sort Cheng, Yan
collection Repository of Agricultural Research Outputs (CGSpace)
description The short revisit times afforded by recently-deployed optical satellite sensors that acquire 3–30 m resolution imagery provide new opportunities to study seasonal vegetation dynamics. Previous studies demonstrated a successful retrieval of phenology with Sentinel-2 for relatively stable annual growing seasons. In semi-arid East Africa however, vegetation responds rapidly to a concentration of rainfall over short periods and consequently is subject to strong interannual variability. Obtaining a sufficient density of cloud-free acquisitions to accurately describe these short vegetation cycles is therefore challenging. The objective of this study is to evaluate if data from two satellite constellations, i.e., PlanetScope (3 m resolution) and Sentinel-2 (10 m resolution), each independently allow for accurate mapping of vegetation phenology under these challenging conditions. The study area is a rangeland with bimodal seasonality located at the 128-km2 Kapiti Farm in Machakos County, Kenya. Using all the available PlanetScope and Sentinel-2 imagery between March 2017 and February 2019, we derived temporal NDVI profiles and fitted double hyperbolic tangent models (equivalent to commonly-used logistic functions), separately for the two rainy seasons locally referred to as the short and long rains. We estimated start- and end-of-season for the series using a 50% threshold between minimum and maximum levels of the modelled time series (SOS50/EOS50). We compared our estimates against those obtained from vegetation index series from two alternative sources, i.e. a) greenness chromatic coordinate (GCC) series obtained from digital repeat photography, and b) MODIS NDVI. We found that both PlanetScope and Sentinel-2 series resulted in acceptable retrievals of phenology (RMSD of ~8 days for SOS50 and ~15 days for EOS50 when compared against GCC series) suggesting that the sensors individually provide sufficient temporal detail. However, when applying the model to the entire study area, fewer spatial artefacts occurred in the PlanetScope results. This could be explained by the higher observation frequency of PlanetScope, which becomes critical during periods of persistent cloud cover. We further illustrated that PlanetScope series could differentiate the phenology of individual trees from grassland surroundings, whereby tree green-up was found to be both earlier and later than for grass, depending on location. The spatially-detailed phenology retrievals, as achieved in this study, are expected to help in better understanding climate and degradation impacts on rangeland vegetation, particularly for heterogeneous rangeland systems with large interannual variability in phenology and productivity.
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spelling CGSpace1295932025-12-08T09:54:28Z Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2 Cheng, Yan Vrieling, Anton Fava, Francesco P. Meroni, Michele Marshall, Michael Gachoki, Stella vegetation phenology geology The short revisit times afforded by recently-deployed optical satellite sensors that acquire 3–30 m resolution imagery provide new opportunities to study seasonal vegetation dynamics. Previous studies demonstrated a successful retrieval of phenology with Sentinel-2 for relatively stable annual growing seasons. In semi-arid East Africa however, vegetation responds rapidly to a concentration of rainfall over short periods and consequently is subject to strong interannual variability. Obtaining a sufficient density of cloud-free acquisitions to accurately describe these short vegetation cycles is therefore challenging. The objective of this study is to evaluate if data from two satellite constellations, i.e., PlanetScope (3 m resolution) and Sentinel-2 (10 m resolution), each independently allow for accurate mapping of vegetation phenology under these challenging conditions. The study area is a rangeland with bimodal seasonality located at the 128-km2 Kapiti Farm in Machakos County, Kenya. Using all the available PlanetScope and Sentinel-2 imagery between March 2017 and February 2019, we derived temporal NDVI profiles and fitted double hyperbolic tangent models (equivalent to commonly-used logistic functions), separately for the two rainy seasons locally referred to as the short and long rains. We estimated start- and end-of-season for the series using a 50% threshold between minimum and maximum levels of the modelled time series (SOS50/EOS50). We compared our estimates against those obtained from vegetation index series from two alternative sources, i.e. a) greenness chromatic coordinate (GCC) series obtained from digital repeat photography, and b) MODIS NDVI. We found that both PlanetScope and Sentinel-2 series resulted in acceptable retrievals of phenology (RMSD of ~8 days for SOS50 and ~15 days for EOS50 when compared against GCC series) suggesting that the sensors individually provide sufficient temporal detail. However, when applying the model to the entire study area, fewer spatial artefacts occurred in the PlanetScope results. This could be explained by the higher observation frequency of PlanetScope, which becomes critical during periods of persistent cloud cover. We further illustrated that PlanetScope series could differentiate the phenology of individual trees from grassland surroundings, whereby tree green-up was found to be both earlier and later than for grass, depending on location. The spatially-detailed phenology retrievals, as achieved in this study, are expected to help in better understanding climate and degradation impacts on rangeland vegetation, particularly for heterogeneous rangeland systems with large interannual variability in phenology and productivity. 2020-10 2023-03-10T14:40:40Z 2023-03-10T14:40:40Z Journal Article https://hdl.handle.net/10568/129593 en Open Access Elsevier Cheng, Yan; Vrieling, Anton; Fava, Francesco; Meroni, Michele; Marshall, Michael; Gachoki, Stella. 2020. Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2. Remote Sensing of Environment 248: 112004
spellingShingle vegetation
phenology
geology
Cheng, Yan
Vrieling, Anton
Fava, Francesco P.
Meroni, Michele
Marshall, Michael
Gachoki, Stella
Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
title Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
title_full Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
title_fullStr Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
title_full_unstemmed Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
title_short Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
title_sort phenology of short vegetation cycles in a kenyan rangeland from planetscope and sentinel 2
topic vegetation
phenology
geology
url https://hdl.handle.net/10568/129593
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