scholarly journals Proximal-Sensing-Powered Modelling of Energy-Water Fluxes in a Vineyard: A Spatial Resolution Analysis

2021 ◽  
Vol 13 (22) ◽  
pp. 4699
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Antonino Maltese ◽  
Giuseppe Ciraolo ◽  
Marco Mancini
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Alternative Energy ◽  
Scale Effects ◽  
Surface Flux ◽  
Low Resolution ◽  
Proximal Sensing ◽  
Resolution Analysis ◽  
Relative Errors

Spatial resolution is a key parameter in energy–water surface flux modelling. In this research, scale effects are analyzed on fluxes modelled with the FEST-EWB model, by upscaling both its inputs and outputs separately. The main questions are: (a) if high-resolution remote sensing images are necessary to accurately model a heterogeneous area; and (b) whether and to what extent low-resolution modelling provides worse/better results than the upscaled results of high-resolution modelling. The study area is an experimental vineyard field where proximal sensing images were obtained by an airborne platform and verification fluxes were measured via a flux tower. Modelled fluxes are in line with those from alternative energy-balance models, and quite accurate (NSE = 0.78) with respect to those measured in situ. Field-scale evapotranspiration has resulted in both the tested upscaling approaches (with relative error within ±30%), although fewer pixels available for low-resolution calibration may produce some differences. When working at low resolutions, the model has produced higher relative errors (20% on average), but is still within acceptable bounds. This means that the model can produce high-quality results, partially compensating for the loss in spatial heterogeneity associated with low-resolution images.

scholarly journals Super Resolution Digital Image Correlation (SR-DIC): an Alternative to Image Stitching at High Magnifications

2021 ◽  
Author(s):  
R. S. Hansen ◽  
D. W. Waldram ◽  
T. Q. Thai ◽  
R. B. Berke
Keyword(s):  
High Resolution ◽  
Digital Image Correlation ◽  
Spatial Resolution ◽  
Digital Image ◽  
Super Resolution ◽  
Image Correlation ◽  
Low Resolution ◽  
Strain Measurements ◽  
Resolution Image ◽  
High Resolution Image

Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.

Combining in situ observations and high resolution VENμS data to monitor temperate deciduous shrub and tree phenology

2020 ◽  
Author(s):  
Alison Donnelly ◽  
Rong Yu
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Carbon Budget ◽  
Vegetation Index ◽  
Return Time ◽  
Small Scale ◽  
Spatial Coverage ◽  
Temperate Deciduous

<p>Direct in situ phenological observations of co-located trees and shrubs help characterize the phenological profile of ecosystems, such as, temperate deciduous forests. Accurate determination of the start and end of the growing season is necessary to define the active carbon uptake period for use in reliable carbon budget calculations. However, due to the resource intensive nature of recording in situ phenology the spatial coverage of sampling is often limited. In recent decades, the use of freely available satellite-derived phenology products to monitor ‘green-up’ at the landscape scale have become commonplace. Although these data sets are widely available they either have (i) high temporal resolution but low spatial resolution, such as, MODIS (daily return time; 250m) or (ii) low temporal resolution but high spatial resolution, such as, Landsat (16-day return time; 30m). However, the recently (2017) launched VENμS (Vegetation and Environment monitoring on a New Micro-Satellite) satellite combines both high temporal (two-day return time) and spatial (5-10m) resolution at a local scale thus providing an opportunity for small scale comparison of a range of phenometrics. The next challenge is to determine what in situ phenophase corresponds to the satellite-derived phenology. Our study site is a temperate deciduous woodlot on the campus of the University of Wisconsin-Milwaukee, USA, where we monitored in situ phenology on a range of (5) native (N) and (3) non-native invasive (NNI) shrub species, and (6) tree species for a 3-year period (2017-2019) to determine the timing and duration of key spring (bud-open, leaf-out, full-leaf unfolded) and autumn (leaf color, leaf fall) phenophases. The monitoring campaign coincided with the 2-day return time of VENμS to enable direct comparison with the satellite data. The shrubs leafed out before the trees and the NNIs, in particular, remained green well into the autumn season when the trees were leafless. The next step will be to determine what exact in situ phenophses correspond to NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived start, peak and end of season from MODIS and VENμS data. In addition, we will determine if VENμS can detect differences in phenological profile between N and NNI shrubs at seasonal extremes. We anticipate that the high resolution VENμS data will increase the accuracy of phenological determination which could help improve carbon budget determination and inform forest management and conservation plans.</p>

Focused Plenoptic Camera and Spatial Resolution Improving Technology

2013 ◽  
Vol 710 ◽  
pp. 419-423
Author(s):  
Juan Ning Zhao ◽  
Xiao Na Dong ◽  
Suo Chao Yuan
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Traditional Approach ◽  
Microlens Array ◽  
Low Resolution ◽  
New Approach ◽  
Plenoptic Camera ◽  
High Resolution Images

The focused plenoptic cameras based on the rays resampling of microlens array on the image formed by main lens, captures radiation on sensor includes the 4D radiance information.Because of both spatial and angular information are recorded on the sensor of fixed pixels number, when rendering image with fixed view there are limited pixels from sub_image are adopted, this results in disappointingly low resolution of the result image. Our approach presents a new approach to rendering an image with higher spatial resolution than the traditional approach, allowing us to render high resolution images that meet the high requirements.

scholarly journals Lunar Image Fusion using Wavelet Transform

2013 ◽  
pp. 211-215
Author(s):  
Dr.Vani. K ◽  
Anto. A. Micheal
Keyword(s):  
High Resolution ◽  
Image Fusion ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Lunar Surface ◽  
High Spatial Resolution ◽  
Multispectral Image ◽  
High Spectral Resolution ◽  
Low Resolution ◽  
Mineral Mapping

This paper is an attempt to combine high resolution panchromatic lunar image with low resolution multispectral lunar image to produce a composite image using wavelet approach. There are many sensors that provide us image data about the lunar surface. The spatial resolution and spectral resolution is unique for each sensor, thereby resulting in limitation in extraction of information about the lunar surface. The high resolution panchromatic lunar image has high spatial resolution but low spectral resolution; the low resolution multispectral image has low spatial resolution but high spectral resolution. Extracting features such as craters, crater morphology, rilles and regolith surfaces with a low spatial resolution in multispectral image may not yield satisfactory results. A sensor which has high spatial resolution can provide better information when fused with the high spectral resolution. These fused image results pertain to enhanced crater mapping and mineral mapping in lunar surface. Since fusion using wavelet preserve spectral content needed for mineral mapping, image fusion has been done using wavelet approach.

scholarly journals 394 HIGH-AND-LOW RESOLUTION ANALYSIS OF GROWTH IN SNAPDRAGON (Antirrhinum majus cv. Giant Tetra) AND ZINNIA (Zinnia elegens cv. Pompom)

HortScience ◽  
1994 ◽  
Vol 29 (5) ◽  
pp. 487e-487
Author(s):  
Will Neily ◽  
Peter R. Hicklenton ◽  
David N. Kristie
Keyword(s):  
High Resolution ◽  
Plant Height ◽  
Developmental Stages ◽  
Stem Elongation ◽  
Growth Cycle ◽  
Low Resolution ◽  
Flower Bud ◽  
Expansion Stage ◽  
Resolution Analysis ◽  
Stage 1

Stem elongation rates (SER) in snapdragon end zinnia were recorded in 3 DIF regimes (+5, -5, and 0; Daily average: 18C) using both high resolution (linear transducers), and low resolution techniques. Three developmental stages were chosen for study: Stage 1 was vegetative growth, preceding the formation of a flower bud. Stage 2 was the period from bud formation to preliminary expansion. Stage 3 was the period just before anthesis. Low resolution measurements showed a decrease in snapdragon height in response to a negative DIF. A negative DIF was less effective in reducing zinnia height especially after the third developmental stage. Final plant height for both species was not affected by placing plants in the 3 DIF regimes for 1 week during the growth cycle. Snapdragon and zinnia displayed unique diurnal SER patterns. Snapdragon showed a large peak in SER at the start of the dark period followed by a gradual decline. SER increased again during the light period. Most growth in vegetative zinnias occurred around the light/dark transition. This peak growth tended to shift to the night period as buds were formed and flowering proceeded. High resolution measurements revealed a reduction in SER for both species at negative DIP; greatest decreases occurred during the night. DIF exerts an influence on diurnal SER in both snapdragon and zinnia, despite well defined differences in SER patterns. Negative DIF suppresses the SER of both species at all 3 developmental stages, but must be applied consistently in order to produce significant differences in final plant height.

scholarly journals High-resolution inventory to capture glacier disintegration in the Austrian Silvretta

2021 ◽  
Author(s):  
Andrea Fischer ◽  
Bernd Seiser ◽  
Kay Helfricht ◽  
Martin Stocker-Waldhuber
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Ice Age ◽  
Surface Elevation ◽  
Glacier Changes ◽  
Wide Range ◽  
Elevation Data ◽  
Glacier Ice ◽  
Geodetic Mass Balance

Abstract. Eastern Alpine glaciers have been receding since the LIA maximum, but the majority of glacier margins could be delineated unambiguously for the last Austrian glacier inventories. Even debris-covered termini, changes in slope, colour or the position of englacial streams enabled at least an in situ survey of glacier outlines. Today the outlines of totally debris-covered glacier ice are fuzzy and raise the theoretical discussion if these glaciogenic features are still glaciers and should be part of the respective inventory – or part of an inventory of transient cryogenic landforms. A new high-resolution glacier inventory (area and surface elevation) was compiled for the years 2017 and 2018 to quantify glacier changes for the Austrian Silvretta region in full. Glacier outlines were mapped manually, based on orthophotos and elevation models and patterns of volume change of 1 to 0.5 m spatial resolution. The vertical accuracy of the DEMs generated from 6 to 8 LiDAR points per m2 is in the order of centimetres. calculated in relation to the previous inventories dating from 2004/2006 (LiDAR), 2002, 1969 (photogrammetry) and to the Little Ice Age maximum extent (moraines). Between 2004/06 and 2017/2018, the 46 glaciers of the Austrian Silvretta lost −29 ± 4 % of their area and now cover 13.1 ± 0.4 km2. This is only 32 ± 2 % of their LIA extent of 40.9 ± 4.1 km2. The area change rate increased from −0.6 %/year (1969–2002) to −2.4 %/year (2004/06–2017/18). The annual geodetic mass balance showed a loss increasing from −0.2 ± 0.1 m w.e./year (1969–2002) to –0.8 m ±0.1 w.e./year (2004/06–2017/18) with an interim peak in 2002–2004/06 at −1.5 ± 0.7 m w.e./year. Identifying the glacier outlines offers a wide range of possible interpretations of former glaciers that have evolved into small and now totally debris-covered cryogenic geomorphological structures. Only the patterns and amounts of volume changes allow us to estimate the area of the buried glacier remnants. To keep track of the buried ice and its fate, and to distinguish increasing debris cover from ice loss, we recommend inventory repeat frequencies of three to five years and surface elevation data with a spatial resolution of one metre.

scholarly journals Sensitivity of ensemble Lagrangian reconstructions to assimilated wind time step resolution

2009 ◽  
Vol 9 (2) ◽  
pp. 8619-8633
Author(s):  
I. Pisso ◽  
V. Marécal ◽  
B. Legras ◽  
G. Berthet
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Time Resolution ◽  
Wind Fields ◽  
Time Step ◽  
Coarse Resolution ◽  
Temporal And Spatial ◽  
Atmospheric Tracers

Abstract. The aim of this study is to define the optimal temporal and spatial resolution required for accurate offline diffusive Lagrangian reconstructions of high resolution in-situ tracers measurements based on meteorological wind fields and on coarse resolution 3-D tracer distributions. Increasing the time resolution of the advecting winds from three to one hour intervals has a modest impact on diffusive reconstructions in the case studied. This result is discussed in terms of the effect on the geometry of transported clouds of points in order to set out a method to assess the effect of meteorological flow on the transport of atmospheric tracers.

scholarly journals New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture

2020 ◽  
Vol 12 (7) ◽  
pp. 1119 ◽  
Author(s):  
Jovan Kovačević ◽  
Željko Cvijetinović ◽  
Nikola Stančić ◽  
Nenad Brodić ◽  
Dragan Mihajlović
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Random Forest ◽  
Spatial Resolution ◽  
Surface Soil ◽  
Initial Step ◽  
Surface Soil Moisture ◽  
In Situ Data ◽  
Random Forest Models

ESA CCI SM products have provided remotely-sensed surface soil moisture (SSM) content with the best spatial and temporal coverage thus far, although its output spatial resolution of 25 km is too coarse for many regional and local applications. The downscaling methodology presented in this paper improves ESA CCI SM spatial resolution to 1 km using two-step approach. The first step is used as a data engineering tool and its output is used as an input for the Random forest model in the second step. In addition to improvements in terms of spatial resolution, the approach also considers the problem of data gaps. The filling of these gaps is the initial step of the procedure, which in the end produces a continuous product in both temporal and spatial domains. The methodology uses combined active and passive ESA CCI SM products in addition to in situ soil moisture observations and the set of auxiliary downscaling predictors. The research tested several variants of Random forest models to determine the best combination of ESA CCI SM products. The conclusion is that synergic use of all ESA CCI SM products together with the auxiliary datasets in the downscaling procedure provides better results than using just one type of ESA CCI SM product alone. The methodology was applied for obtaining SSM maps for the area of California, USA during 2016. The accuracy of tested models was validated using five-fold cross-validation against in situ data and the best variation of model achieved RMSE, R2 and MAE of 0.0518 m3/m3, 0.7312 and 0.0374 m3/m3, respectively. The methodology proved to be useful for generating high-resolution SSM products, although additional improvements are necessary.

scholarly journals High resolution <i>in situ</i> measurements of phytoplankton photosynthesis and abundance in the Dutch North Sea

2018 ◽  
Author(s):  
Hedy M. Aardema ◽  
Machteld Rijkeboer ◽  
Alain Lefebvre ◽  
Arnold Veen ◽  
Jacco C. Kromkamp
Keyword(s):  
High Resolution ◽  
Spatial Heterogeneity ◽  
Spatial Patterns ◽  
North Sea ◽  
Phytoplankton Biomass ◽  
Spatial Clustering ◽  
Low Resolution ◽  
Phytoplankton Communities ◽  
Phytoplankton Photosynthesis

Abstract. Marine waters can be highly heterogeneous both on a spatial and temporal scale, yet monitoring is currently mainly limited to low-resolution methods. This study explores the use of two high-resolution methods to study phytoplankton dynamics; Fast Repetition Rate fluorometry (FRRf) to study phytoplankton photosynthesis and scanning flowcytometry (FCM) to study phytoplankton biomass and composition. Measurements were conducted during four cruises on the Dutch North Sea in April, May, June, and August of 2017. Both FRRf and FCM data show spatial heterogeneity with monthly variation. Automated unsupervised Hidden Markov Model (uHMM) spatial clustering resulted in the identification of regions with distinct phytoplankton communities. Manual adjustments were necessary to optimize visualization of some distinct phytoplankton communities. Stepwise multiple linear regression (n = 61) revealed that photophysiology (alpha), phytoplankton biomass (total red fluorescence) and abiotic predictors (Turbidity, DIN, time of the day and temperature) determined integrated water column gross primary productivity. Apart from spatial heterogeneity, the diurnal trend is a significant predictor exposing clear trends with other photophysiological parameters. Consequently, spatial patterns are difficult as temporal and spatial patterns occur simultaneously. Nevertheless, high-resolution monitoring is a very useful supplement in addition to regular low-resolution monitoring.

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