Time-series within automatically generated ROIs from wildlife cameras are well able to explain variability in forest phenology on a temperature gradient

2020 ◽  
Author(s):  
Lars Uphus ◽  
Annette Menzel
Keyword(s):  
Time Series ◽  
Temperature Gradient ◽  
Time Lapse ◽  
Relevant Information ◽  
High Temporal Resolution ◽  
Deciduous Species ◽  
Multiple Thresholds ◽  
In Situ Observations ◽  
Wildlife Cameras

<p>Using RGB camera data (e.g. webcams, wildlife cameras) has great potential to measure forest phenology over climate gradients, because of its very high temporal resolution, while at the same time being more objective and less time consuming than in situ observations. To make images useful for the purpose of measuring phenological events, such as Start of Season (SOS) and End of Season (EOS), there is need to derive Regions of Interest (ROI) objectively and (semi-)automatically. In order to answer this need, Bothmann et al. (2017) proposed a method which randomly sets a number of pinpricks in the image and calculates how greenness over time from all other pixels correlates to these different pinpricks. Subsequently, ROIs are created by discarding the pixels with low correlation, using multiple thresholds. Despite its advantage of being automated and more objective compared to prevailing expert-based ROIs, and therefore its potential applicability for phenological research using a large amount of cameras, the method has not been reproduced for this purpose so far. Therefore, we assess here how well this method is able to separate foliage of different deciduous species from evergreens and phenologically irrelevant components in time-lapse wildlife camera data and in that way how suitable it is in explaining variation in phenology over a temperature gradient. We used 73 Cuddleback wildlife cameras troughout Bavaria which were installed within nine quadrants of 6*6 kilometers spanning a temperature gradient of 2.5°C. Hourly taken images of deciduous forests in spring, summer and autumn 2019 were analysed. Half of them were facing canopy, and half of them were facing understory. We applied the principles of the method from Bothmann et al. (2017) and assigned the best matching ROI to foliage of <em>Fagus sylvatica</em> or other deciduous species. Within this ROI, mean Green Chromatic Coordinate (GCC), a greenness index, over all pixels within the ROI, was derived per time-stamp. Afterwards, a time-series was calculated on these GCC values and with a suitable combination of curve-fitting techniques, SOS and EOS were derived, expressed in Day of Year (DOY). We compared these SOS and EOS dates with weekly in situ observations of spring and autumn phenology, which were taken in the same quadrants. Despite that Bothmann's method was developed on a single tower-mounted scientific webcam which viewed on canopy from above, while we made use of wildlife cameras at 73 different locations facing either understory perpendicular or canopy from below, it was able to distinguish <em>F. sylvatica</em> and other deciduous foliage from phenologically less relevant information. Time-series derived from these ROIs were able to explain variability in phenology between understory and canopy and over the temperature gradient similarly and supplementary to in situ observations. </p>

scholarly journals Mediterranean Sea climatic indices: monitoring long term variability and climate changes

2018 ◽  
Author(s):  
Athanasia Iona ◽  
Athanasios Theodorou ◽  
Sarantis Sofianos ◽  
Sylvain Watelet ◽  
Charles Troupin ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Mediterranean Sea ◽  
Climate Changes ◽  
Salt Content ◽  
Climatic Indices ◽  
In Situ Observations ◽  
The Mediterranean

Abstract. We present a new product composed of a set of thermohaline climatic indices from 1950 to 2015 for the Mediterranean Sea such as decadal temperature and salinity anomalies, their mean values over selected depths, decadal ocean heat and salt content anomalies at selected depth layers as well as their long times series. It is produced from a new high-resolution climatology of temperature and salinity on a 1/8° regular grid based on historical high quality in situ observations. Ocean heat and salt content differences between 1980–2015 and 1950–1979 are compared for evaluation of the climate shift in the Mediterranean Sea. The spatial patterns of heat and salt content shifts demonstrate in greater detail than ever before that the climate changes differently in the several regions of the basin. Long time series of heat and salt content for the period 1950 to 2015 are also provided which indicate that in the Mediterranean Sea there is a net mean volume warming and salting since 1950 with acceleration during the last two decades. The time series also show that the ocean heat content seems to fluctuate on a cycle of about 40 years and seems to follow the Atlantic Multidecadal Oscillation climate cycle indicating that the natural large scale atmospheric variability could be superimposed on to the warming trend. This product is an observations-based estimation of the Mediterranean climatic indices. It relies solely on spatially interpolated data produced from in-situ observations averaged over decades in order to smooth the decadal variability and reveal the long term trends with more accuracy. It can provide a valuable contribution to the modellers' community, next to the satellite-based products and serve as a baseline for the evaluation of climate-change model simulations contributing thus to a better understanding of the complex response of the Mediterranean Sea to the ongoing global climate change. The product is available here: https://doi.org/10.5281/zenodo.1210100.

In Situ Observations of Voiding in Metal Lines Under Passivation

1994 ◽  
Vol 338 ◽  
Author(s):  
T. Marieb ◽  
J.C. Bravman ◽  
P. Flinn ◽  
M. Madden
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Time Lapse ◽  
Still Images ◽  
In Situ Observations ◽  
Voltage Scanning ◽  
Morphology Changes ◽  
Passivated Metal ◽  
Scanning Electron

ABSTRACTMovies showing high voltage scanning electron microscope (HVSEM) in situ observations of void motion in passivated metal lines were produced. By taking pictures of the line when the void morphology changes and combining these images digitally with a technique called morphing, a time-lapse movie is constructed with the minimum amount of stored images. The sequence of still images from which a movie is constructed are shown in this paper. This sequence demonstrates that wedge voids do not cause failure in near-bamboo pure Al lines; rather the void will move until it encounters a grain which it can grow across in a slit-like manner.

scholarly journals An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4285 ◽  
Author(s):  
Shubha Sathyendranath ◽  
Robert Brewin ◽  
Carsten Brockmann ◽  
Vanda Brotas ◽  
Ben Calton ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Marine Ecosystem ◽  
Ocean Colour ◽  
Remote Sensing Reflectance ◽  
Resolution Imaging ◽  
In Situ Observations ◽  
Climate Studies ◽  
Reflectance Data

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

scholarly journals Mechanisms of Barrier Layer Formation and Erosion from In Situ Observations in the Bay of Bengal

2019 ◽  
Vol 49 (5) ◽  
pp. 1183-1200 ◽  
Author(s):  
Jenson V. George ◽  
P. N. Vinayachandran ◽  
V. Vijith ◽  
V. Thushara ◽  
Anoop A. Nayak ◽  
...  
Keyword(s):  
Time Series ◽  
Barrier Layer ◽  
Bay Of Bengal ◽  
High Salinity ◽  
Layer Structure ◽  
Surface Mixed Layer ◽  
Study Region ◽  
In Situ Observations ◽  
Differential Advection

AbstractDuring the Bay of Bengal (BoB) Boundary Layer Experiment (BoBBLE) in the southern BoB, time series of microstructure measurements were obtained at 8°N, 89°E from 4 to 14 July 2016. These observations captured events of barrier layer (BL) erosion and reformation. Initially, a three-layer structure was observed: a fresh surface mixed layer (ML) of thickness 10–20 m; a BL below of 30–40-m thickness with similar temperature but higher salinity; and a high salinity core layer, associated with the Summer Monsoon Current. Each of these three layers was in relative motion to the others, leading to regions of high shear at the interfaces. However, the destabilizing influence of the shear regions was not enough to overcome the haline stratification, and the three-layer structure was preserved. A salinity budget using in situ observations suggested that during the BL erosion, differential advection brought high salinity surface waters (34.5 psu) with weak stratification to the time series location and replaced the three-layer structure with a deep ML (~60 m). The resulting weakened stratification at the time series location then allowed atmospheric wind forcing to penetrate deeper. The turbulent kinetic energy dissipation rate and eddy diffusivity showed elevated values above 10−7 W kg−1 and 10−4 m2 s−1, respectively, in the upper 60 m. Later, the surface salinity decreased again (33.8 psu) through differential horizontal advection, stratification became stronger and elevated mixing rates were confined to the upper 20 m, and the BL reformed. A 1D model experiment suggested that in the study region, differential advection of temperature–salinity characteristics is essential for the maintenance of BL and to the extent to which mixing penetrates the water column.

scholarly journals Blending Sea Surface Temperatures from Multiple Satellites and In Situ Observations for Coastal Oceans

2009 ◽  
Vol 26 (7) ◽  
pp. 1415-1426 ◽  
Author(s):  
Yi Chao ◽  
Zhijin Li ◽  
John D. Farrara ◽  
Peter Hung
Keyword(s):  
Coastal Upwelling ◽  
Sea Surface ◽  
High Temporal Resolution ◽  
Potential Applications ◽  
Independent Observations ◽  
Ocean Flows ◽  
In Situ Observations ◽  
Continuous Fields ◽  
Mean Square Errors

Abstract A two-dimensional variational data assimilation (2DVAR) method for blending sea surface temperature (SST) data from multiple observing platforms is presented. This method produces continuous fields and has the capability of blending multiple satellite and in situ observations. In addition, it allows specification of inhomogeneous and anisotropic background correlations, which are common features of coastal ocean flows. High-resolution (6 km in space and 6 h in time) blended SST fields for August 2003 are produced for a region off the California coast to demonstrate and evaluate the methodology. A comparison of these fields with independent observations showed root-mean-square errors of less than 1°C, comparable to the errors in conventional SST observations. The blended SST fields also clearly reveal the finescale spatial and temporal structures associated with coastal upwelling, demonstrating their utility in the analysis of finescale flows. With the high temporal resolution, the blended SST fields are also used to describe the diurnal cycle. Potential applications of this SST blending methodology in other coastal regions are discussed.

scholarly journals Orientation selective grain sublimation-deposition in snow under temperature gradient metamorphism observed with Diffraction Contrast Tomography

2021 ◽  
Author(s):  
Rémi Granger ◽  
Frédéric Flin ◽  
Wolfgang Ludwig ◽  
Ismail Hammad ◽  
Christian Geindreau
Keyword(s):  
Temperature Gradient ◽  
Horizontal Plane ◽  
Time Lapse ◽  
Snow Sample ◽  
Crystalline Orientation ◽  
Diffraction Contrast ◽  
Crystallographic Facets ◽  
Over Time ◽  
Material Fluxes

Abstract. In this study on temperature gradient metamorphism in snow, we investigate the hypothesis that there exists a favorable crystalline orientation relative to the temperature gradient, giving rise to a faster formation of crystallographic facets. We applied in-situ time-lapse Diffraction Contrast Tomography on a snow sample with a density of 476 kg m−3 subject to a temperature gradient of 52 °C m−1 at mean temperatures in the range between −4.1 °C and −2.1 °C for three days. The orientations of about 900 grains along with their microstructural evolution are followed over time. Faceted crystals appear during the evolution and from the analysis of the material fluxes, we indeed observe higher sublimation-deposition rate for grains with their c-axis in the horizontal plane at the beginning of the metamorphism. This remains the case up to the end of the experiment for what concerns sublimation while the differences vanish for deposition. That latter observation is explained in terms of geometrical interactions between grains.

scholarly journals SEA-LEVEL PRESSURE TRENDS IN THE SOUTHERN OCEAN AND ANTARCTICA FROM REANALYSIS AND IN SITU DATA

2021 ◽  
Vol 49 (4) ◽  
pp. 63-85
Author(s):  
P. Yu. Romanov ◽  
N. A. Romanova
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Reanalysis Data ◽  
Environmental Research ◽  
Sea Level Pressure ◽  
Mean Values ◽  
Level Pressure ◽  
High Latitude Region ◽  
In Situ Observations

Trends in the mean sea-level pressure (SLP) in Antarctica in the last four decades (1980– 2020) have been examined using in situ observations and reanalysis data. The analysis involved time series of monthly mean, season-mean and yearly-mean values of the SLP derived from four reanalysis datasets, NCEP/NCAR, ERA5, JRA55, MERRA2, and from surface observations acquired from the Reference Antarctic Data for Environmental Research (READER) dataset. With this data we have evaluated the trends, characterized their seasonal peculiarities and variation across the high-latitude region of the Southern Hemisphere. The results of the analysis confirmed the dominance of decreasing trends in the annual mean SLP in Antarctica. Larger negative trends were found in the Western Antarctica with the most pronounced pressure drop in the South Pacific. The long-term decrease in the annual mean SLP in Antarctica was due to strong negative pressure trends in the austral summer and fall season whereas in winter and in spring the trends turn to mixed and mostly positive. The comparison of multiyear time series of SLP reanalysis data with in situ observations at Antarctic stations revealed a considerable overestimate of negative SLP trends in the NCEP/NCAR dataset. Among the four examined reanalysis datasets, ERA5 provided the best agreement with the station data on the annual mean and monthly mean SLP trend values.

scholarly journals Mediterranean Sea climatic indices: monitoring long-term variability and climate changes

2018 ◽  
Vol 10 (4) ◽  
pp. 1829-1842 ◽  
Author(s):  
Athanasia Iona ◽  
Athanasios Theodorou ◽  
Sarantis Sofianos ◽  
Sylvain Watelet ◽  
Charles Troupin ◽  
...  
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Climate Changes ◽  
Salt Content ◽  
Climatic Indices ◽  
Long Time ◽  
In Situ Observations ◽  
The Mediterranean

Abstract. We present a new product composed of a set of thermohaline climatic indices from 1950 to 2015 for the Mediterranean Sea such as decadal temperature and salinity anomalies, their mean values over selected depths, decadal ocean heat and salt content anomalies at selected depth layers as well as their long time series. It is produced from a new high-resolution climatology of temperature and salinity on a 1∕8∘ regular grid based on historical high-quality in situ observations. Ocean heat and salt content differences between 1980–2015 and 1950–1979 are compared for evaluation of the climate shift in the Mediterranean Sea. The two successive periods are chosen according to the standard WMO climate normals. The spatial patterns of heat and salt content shifts demonstrate that the climate changes differently in the several regions of the basin. Long time series of heat and salt content for the period 1950 to 2015 are also provided which indicate that in the Mediterranean Sea there is a net mean volume warming and salinification since 1950 that has accelerated during the last two decades. The time series also show that the ocean heat content seems to fluctuate on a cycle of about 40 years and seems to follow the Atlantic Multidecadal Oscillation climate cycle, indicating that the natural large-scale atmospheric variability could be superimposed onto the warming trend. This product is an observation-based estimation of the Mediterranean climatic indices. It relies solely on spatially interpolated data produced from in situ observations averaged over decades in order to smooth the decadal variability and reveal the long-term trends. It can provide a valuable contribution to the modellers' community, next to the satellite-based products, and serve as a baseline for the evaluation of climate-change model simulations, thus contributing to a better understanding of the complex response of the Mediterranean Sea to the ongoing global climate change. The product is available in netCDF at the following sources: annual and seasonal T∕S anomalies (https://doi.org/10.5281/zenodo.1408832), annual and seasonal T∕S vertical averaged anomalies (https://doi.org/10.5281/zenodo.1408929), annual and seasonal areal density of OHC/OSC anomalies (https://doi.org/10.5281/zenodo.1408877), annual and seasonal linear trends of T∕S, OHC/OSC anomalies (https://doi.org/10.5281/zenodo.1408917), annual and seasonal time series of T∕S, OHC/OSC anomalies (https://doi.org/10.5281/zenodo.1411398), and differences of two 30-year averages of annual and seasonal T∕S, OHC/OSC anomalies (https://doi.org/10.5281/zenodo.1408903).

scholarly journals Snow on the Ross Ice Shelf: comparison of reanalyses and observations from automatic weather stations

2013 ◽  
Vol 7 (5) ◽  
pp. 1399-1410 ◽  
Author(s):  
L. Cohen ◽  
S. Dean
Keyword(s):  
Statistical Evaluation ◽  
Snow Accumulation ◽  
High Temporal Resolution ◽  
Ice Shelf ◽  
Ross Ice Shelf ◽  
In Situ Observations ◽  
Weather Stations ◽  
Event Based ◽  
Precipitation Events

Abstract. Snow accumulation measurements from automatic weather stations (AWS) around the Ross Ice Shelf (RIS), Antarctica, are used to provide a new set of ground-based observations which are compared to precipitation from the ECMWF ERA-Interim and NCEP/NCAR Reanalysis-2 datasets. The high temporal resolution of the AWS snow accumulation measurements allow for an event-based comparison of reanalyses precipitation to the in situ observations. Snow accumulation records from nine AWS provide multiple years of accumulation data between 2008 and 2012 over a relatively large, homogeneous region of Antarctica, and also provide the basis for a statistical evaluation of accumulation and precipitation events. The complex effects of wind on snow accumulation (which can both limit and enhance accumulation) complicate the use of the accumulation measurements, but this analysis shows that they can provide a valuable source of ground-based observations for comparisons to modelled precipitation on synoptic timescales. The analysis shows that ERA-Interim reproduces more precipitation events than NCEP-2, and these events correspond to an average 8.2% more precipitation. Significant correlations between reanalyses and AWS event sizes are seen at several stations and show that ERA-Interim consistently produces larger precipitation events than NCEP-2.

scholarly journals Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014–2016

2017 ◽  
Author(s):  
Mikko Peltoniemi ◽  
Mika Aurela ◽  
Kristin Böttcher ◽  
Pasi Kolari ◽  
John Loehr ◽  
...  
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Low Cost ◽  
Time Lapse ◽  
Observation Time ◽  
Data Repository ◽  
High Temporal Resolution ◽  
Digital Surveillance ◽  
Spatial Coverage ◽  
The Status

Abstract. In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. Networked cameras can provide information about snow cover and vegetation status with a broad spatial coverage and high temporal resolution, and serve as ground truths to earth observations, and be useful for gap-filling of cloudy areas in earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen-science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images (see, https://doi.org/10.5281/zenodo.777952) in the permanent data repository (https://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series from cameras are consisted of half-hourly images collected between 2014 and 2016. Additionally, we present example colour index time series derived from image time series from two contrasting sites.

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