Greenness Index from Phenocams Performs Well in Linking Climatic Factors and Monitoring Grass Phenology in a Temperate Prairie Ecosystem

doi:10.5814/j.issn.1674-764X.2019.05.003

Abstract

Abstract:

Near-surface remote sensing (e.g., digital cameras) has played an important role in capturing plant phenological metrics at either a focal or landscape scale. Exploring the relationship of the digital image-based greenness index (e.g., Gcc, green chromatic coordinate) with that derived from satellites is critical for land surface process research. Moreover, our understanding of how well Gcc time series associate with environmental variables at field stations in North American prairies remains limited. This paper investigated the response of grass Gcc to daily environmental factors in 2018, such as soil moisture (temperature), air temperature, and solar radiation. Thereafter, using a derivative-based phenology extraction method, we evaluated the correspondence between key phenological events (mainly including start, end and length of growing season, and date with maximum greenness value) derived from Gcc, MODIS and VIIRS NDVI (EVI) for the period 2015-2018. The results showed that daily Gcc was in good agreement with ground-level environmental variables. Additionally, multivariate regression analysis identified that the grass growth in the study area was mainly affected by soil temperature and solar radiation, but not by air temperature. High frequency Gcc time series can respond immediately to precipitation events. In the same year, the phenological metrics retrieved from digital cameras and multiple satellites are similar, with spring phenology having a larger relative difference. There are distinct divergences between changing rates in the greenup and senescence stages. Gcc also shows a close relationship with growing degree days (GDD) derived from air temperature. This study evaluated the performance of a digital camera for monitoring vegetation phenological metrics and related climatic factors. This research will enable multiscale modeling of plant phenology and grassland resource management of temperate prairie ecosystems.

Key words: vegetation phenology, green chromatic coordinate, vegetation indices, PhenoCam, near-surface remote sensing

ZHOU Yuke. Greenness Index from Phenocams Performs Well in Linking Climatic Factors and Monitoring Grass Phenology in a Temperate Prairie Ecosystem[J]. Journal of Resources and Ecology, 2019, 10(5): 481-493.

Figures/Tables 14

References 42

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Data name	Start date	End date	Frequency	Integrated frequency	Spatial scope
Gcc	2015-4-1	2018-9-11	30 min	Daily	Landscape scale
Modis NDVI(EVI)	2015-1-1	2018-9-11	16 day	Semimonthly	2.5 km×2.5 km
VIIRS NDVI(EVI)	2015-1-1
Air Temperature (Oakville)	2018-3-18	2018-9-11	15 min	Daily	Point
Air Temperature (Grand Forks)	2015-4-1	2018-9-11	Daily	Daily	Point
Precipitation (Oakville)	2018-3-18	2018-9-11	15 min	Daily	Point
Precipitation (Grand Forks)	2015-4-1	2018-9-11	Daily	Daily	Point
GDD (Grand Forks)	2015-4-1	2018-9-11	Daily	Daily	Point
Soil Water Content	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 2"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 4"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 8"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 20"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 40"	2018-3-18	2018-9-11	15 min	Daily	Point

Data name	Start date	End date	Frequency	Integrated frequency	Spatial scope
Gcc	2015-4-1	2018-9-11	30 min	Daily	Landscape scale
Modis NDVI(EVI)	2015-1-1	2018-9-11	16 day	Semimonthly	2.5 km×2.5 km
VIIRS NDVI(EVI)	2015-1-1
Air Temperature (Oakville)	2018-3-18	2018-9-11	15 min	Daily	Point
Air Temperature (Grand Forks)	2015-4-1	2018-9-11	Daily	Daily	Point
Precipitation (Oakville)	2018-3-18	2018-9-11	15 min	Daily	Point
Precipitation (Grand Forks)	2015-4-1	2018-9-11	Daily	Daily	Point
GDD (Grand Forks)	2015-4-1	2018-9-11	Daily	Daily	Point
Soil Water Content	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 2"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 4"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 8"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 20"	2018-3-18	2018-9-11	15 min	Daily	Point
Soil Temperature 40"	2018-3-18	2018-9-11	15 min	Daily	Point

Coefficients	Estimate	Std. error	t value	Pr (>\|t\|)
Intercept	3.132e-01	7.881e-03	39.798	< 2e-16 ***
Solar	2.527e-04	5.277e-05	4.788	4.28e-06 ***
SoilTemp4	-8.647e-03	3.546e-03	-2.439	0.0160 *
SoilTemp8	8.264e-03	4.011e-03	2.061	0.0412 *
SoilTemp20	3.756e-02	2.804e-03	13.396	< 2e-16 ***
SoilTemp40	-3.677e-02	2.066e-03	-17.801	< 2e-16 ***
Soil Water	6.107e-02	1.167e-02	5.232	6.10e-07 ***

Coefficients	Estimate	Std. error	t value	Pr (>\|t\|)
Intercept	3.132e-01	7.881e-03	39.798	< 2e-16 ***
Solar	2.527e-04	5.277e-05	4.788	4.28e-06 ***
SoilTemp4	-8.647e-03	3.546e-03	-2.439	0.0160 *
SoilTemp8	8.264e-03	4.011e-03	2.061	0.0412 *
SoilTemp20	3.756e-02	2.804e-03	13.396	< 2e-16 ***
SoilTemp40	-3.677e-02	2.066e-03	-17.801	< 2e-16 ***
Soil Water	6.107e-02	1.167e-02	5.232	6.10e-07 ***

Year	SOS	EOS		LOS		POP	MGS	RSP	RAU	PEAK		MSP	MAU
2015	151	284		133		172	0.402	0.003	-0.0014	0.426		0.398	0.350
2016	141	283		142		167	0.412	0.0036	-0.0017	0.438		0.3981	0.352
2017	132	257		125		172	0.411	0.0032	-0.0013	0.427		0.376	0.374
2018	127	210		83		167	0.438	0.005	-0.0013	0.451		0.386	0.420
Mean	137	258	120		169		0.416	0.0037	-0.0014		0.4355	0.389	0.374