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

REMOTE SENSING OF ENVIRONMENT

卷:248

Article

Cheng, Yan¹  Vrieling, Anton¹  Fava, Francesco²  Meroni, Michele³  Marshall, Michael¹  Gachoki, Stella^1,4 

[1] Univ Twente, Fac Geoinformat Sci & Earth Observat, POB 217, NL-7500 AE Enschede, Netherlands

[2] Int Livestock Res Inst ILRI, POB 30709, Nairobi 00100, Kenya

[3] European Commiss, Joint Res Ctr JRC, Via E Fermi 2749, I-21027 Ispra, VA, Italy

[4] Int Ctr Insect Physiol & Ecol ICIPE, POB 30772, Nairobi 00100, Kenya

关键词: Phenology;    Multi-temporal analysis;    NDVI time series;    Sentinel-2;    PlanetScope;    Spatial resolution;    Landscape variability;    Semi-arid rangelands;    Digital repeat photography;   

DOI  :  10.1016/j.rse.2020.112004

来源: Elsevier

【 摘 要 】

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-km(2) 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 similar to 8 days for SOS50 and similar to 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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