Latitudinal gradient of spruce forest understory and tundra phenology in Alaska as observed from satellite and ground-based data

Kobayashi, Hideki; Yunus, Ali P.; Nagai, Shin; Sugiura, Komei; Kim, Yongwon; Dam, Brie Van; Nagano, Hirohiko; Zona, Donatella; Harazono, Yoshinobu; Bret‐Harte, M. Syndonia; Ichii, Kazuhito; Ikawa, Hiroki; Iwata, Hiroyasu; Oechel, Walter C.; Ueyama, Masahito; Suzuki, Rikie

doi:10.1016/j.rse.2016.02.020

Cited by 52 publications

(36 citation statements)

References 62 publications

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“…We were able to predict SOS within seven days and EOS within 10 days with ground cameras with similar results being reported in Baumann et al () and Nijland et al (). The better results for SOS compared to EOS may be related to the SOS signal being stronger than the EOS signal (Nijland et al, ) and may also relate to lower solar elevation and sun angle at EOS and there being a stronger signal from conifer species as sun cannot penetrate to the understorey (Kobayashi et al, ). The correlation between DRIVE and ground camera data across 17 forested and non‐forested sites with varying species composition displays its ability to capture spatial patterns in vegetation across our study area beyond simple elevation trends.…”

Section: Discussionmentioning

confidence: 99%

“…It also allows objective capture of vegetation phases that can be analyzed visually by users or by automatic algorithms. Networks of cameras can be established on a seasonal (Nijland et al, ) or permanent basis (The Phenocam Network) (Richardson et al, ) and have been shown to be useful for tracking green‐up and senescence of key vegetative food species (Bater et al, ; Laskin, ; Nijland et al, ). Despite its high temporal resolution and accuracy, time‐lapse photography still lacks the spatially explicit information to measure vegetation cycles continuously in space and time.…”

Section: Introductionmentioning

confidence: 99%

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Detecting changes in understorey and canopy vegetation cycles in West Central Alberta using a fusion of Landsat and MODIS

McClelland

Coops

Berman

et al. 2019

Applied Vegetation Science

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Aims To model regional vegetation cycles through data fusion methods for creating a 30‐m daily vegetation product from 2000 to 2018 and to analyze annual vegetation trends over this time period. Location The Yellowhead Bear Management Area, a 31,180‐km2 area in west central Alberta, Canada. Methods In this paper, we use Dynamic Time Warping (DTW) as a data fusion technique to combine Landsat 5, 7 and 8 satellite data and Moderate Resolution Image Spectroradiometer (MODIS) Aqua and Terra imagery, to quantify daily vegetation using Enhanced Vegetation Index at a 30‐m resolution, for the years 2000–2018. We validated this approach, entitled DRIVE (Daily Remote Inference of VEgetation), using imagery acquired from a network of ground cameras. Results When DRIVE was compared to start and end of season dates (SOS and EOS respectively) derived from ground cameras, correlations were r = 0.73 at SOS and r = 0.85 at EOS with a mean absolute error of 7.17 days at SOS and 10.76 days at EOS. Results showed that DRIVE accurately increased spatial and temporal resolution of remote‐sensing data. We demonstrated that SOS is advancing at a maximum rate of 0.78 days per year temporally over the 18‐year time period for varying elevation gradients and land cover classes over the region. Conclusions With DRIVE, we demonstrate the utility of DTW in quantifying vegetation cycles over a large heterogeneous region and determining how changing climate is affecting regional vegetation. DRIVE may prove to be an important method to determine how carbon sequestration is varying within fine‐scale individual plant communities in response to changing climate and likely will be beneficial to wildlife movement and habitat selection studies examining the varying response of wildlife species to changing vegetation cycles under shifting climatic conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detecting changes in understorey and canopy vegetation cycles in West Central Alberta using a fusion of Landsat and MODIS

McClelland

Coops

Berman

et al. 2019

Applied Vegetation Science

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“…, Kobayashi et al. ). Phenological metrics derived via color indices from camera images have been compared in prior studies to in situ observations in a few sites (Keenan et al.…”

Section: Introductionmentioning

confidence: 98%

Species‐specific spring and autumn leaf phenology captured by time‐lapse digital cameras

2018

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Plant leaf phenology is typically observed either via ground‐based visual observations on individuals or via remote sensing of land surface vegetation. To integrate phenological information from both data sources, collected at different spatial scales using different observational protocols, digital cameras were deployed spanning canopy areas with enough spatial resolution to identify temporal changes in individual deciduous tree species with continuous observations. Comparisons of phenology between camera photography and in situ observations have been reported in prior studies; however, it is still unclear that how these camera images relate to field observations at individual and species levels, and how the metrics from those images provide comparable species‐specific phenological responses to environmental variation. We set a suite of digital time‐lapse cameras to acquire continuous photographs of deciduous tree canopies and conducted ground‐based visual observations in Connecticut, USA, from 2012 to 2014. Comparisons between image‐derived dates and observed phenological dates showed that both green and red color indices could be matched to ground observations, and red color indices showed good performance in matching autumn phenology across our group of eight tree species that dominate the southern New England forests. Linear mixed‐effects models were applied to investigate the relationships between climatic/weather conditions and the timing of peak and of intensity of red color in fall foliage for each species. Model results suggested that temperature, precipitation, drought stress in autumn, and heat stress in summer are all important factors to the timing of peak fall foliage color and that higher minimum temperatures (or lower cold degree‐day accumulation) in the autumn are linked to higher intensity of red coloration at least in sugar maples. This study improves our understanding of temporal and spatial variation in the phenology of deciduous trees captured by digital cameras. As well, this provides insights into relating species‐specific information on phenology from visual observations in the field to near‐surface remote sensing and points to the need for further research on autumn phenology using the change in redness of tree canopies.

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“…A1). However, in these more western areas, vegetation changes to rather erect dwarf shrubs and graminoids (Walker et al, 2005, their We speculate that possible explanations for this might be an increasing effect of low SZA late in the growing season (Kobayashi et al, 2016) affecting low NDVI in particularly sparse vegetation heavily. NDVI might also be strongly decreased by standing surface water (Gamon et al, 2013) from snow melt or intermittent precipitation that has not yet drained or evaporated until later in the growing season.…”

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confidence: 87%

Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis

Walther¹,

Guanter²,

Heim³

et al. 2018

Preprint

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Abstract. High latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of climate sensitive tundra. Spaceborne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land cover classes. A particularly late peak of NDVI in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness/growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models.

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Latitudinal gradient of spruce forest understory and tundra phenology in Alaska as observed from satellite and ground-based data

Cited by 52 publications

References 62 publications

Detecting changes in understorey and canopy vegetation cycles in West Central Alberta using a fusion of Landsat and MODIS

Detecting changes in understorey and canopy vegetation cycles in West Central Alberta using a fusion of Landsat and MODIS

Species‐specific spring and autumn leaf phenology captured by time‐lapse digital cameras

Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis

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