scholarly journals GPR-Based Automatic Identification of Root Zones of Influence Using HDBSCAN

2021 ◽  
Vol 13 (6) ◽  
pp. 1227
Author(s):  
Xihong Cui ◽  
Zhenxian Quan ◽  
Xuehong Chen ◽  
Zheng Zhang ◽  
Junxiong Zhou ◽  
...  
Keyword(s):  
Plant Communities ◽  
Root Zone ◽  
Spatial Clustering ◽  
Spatial Competition ◽  
Automatic Identification ◽  
Near Surface ◽  
Coarse Root ◽  
Zone Of Influence ◽  
Actual Growth ◽  
Ground Penetrating

The belowground root zone of influence (ZOI) is fundamental to the study of the root–root and root–soil interaction mechanisms of plants and is vital for understanding changes in plant community compositions and ecosystem processes. However, traditional root research methods have a limited capacity to measure the actual ZOIs within plant communities without destroying them in the process. This study has developed a new approach to determining the ZOIs within natural plant communities. First, ground-penetrating radar (GPR), a non-invasive near-surface geophysical tool, was used to obtain a dataset of the actual spatial distribution of the coarse root system in a shrub quadrat. Second, the root dataset was automatically clustered and analyzed using the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm to determine the ZOIs of different plants. Finally, the shape, size, and other characteristics of each ZOI were extracted based on the clustering results. The proposed method was validated using GPR-obtained root data collected in two field shrub plots and one simulation on a dataset from existing literature. The results show that the shrubs within the studied community exhibited either segregated and aggregated ZOIs, and the two types of ZOIs were distinctly in terms of shape and size, demonstrating the complexity of root growth in response to changes in the surrounding environment. The ZOIs extracted based on GPR survey data were highly consistent with the actual growth pattern of shrub roots and can thus be used to reveal the spatial competition strategies of plant roots responding to changes in the soil environment and the influence of neighboring plants.

Non-invasive estimation of root zone soil moisture from coarse root reflections in ground-penetrating radar images

2019 ◽  
Vol 436 (1-2) ◽  
pp. 623-639 ◽  
Author(s):  
Xinbo Liu ◽  
Xihong Cui ◽  
Li Guo ◽  
Jin Chen ◽  
Wentao Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Ground Penetrating Radar ◽  
Root Zone ◽  
Coarse Root ◽  
Radar Images ◽  
Non Invasive ◽  
Ground Penetrating

Imaging the internal structure of trunks via multiscale phase inversion of ground-penetrating radar data

2021 ◽  
pp. 1-53
Author(s):  
Lei Fu ◽  
Lanbo Liu
Keyword(s):  
Dielectric Constant ◽  
Internal Structure ◽  
Ground Penetrating Radar ◽  
Phase Inversion ◽  
Multiscale Approach ◽  
White Oak ◽  
Near Surface ◽  
Oak Tree ◽  
Ground Penetrating ◽  
Constant Distribution

Ground-penetrating radar (GPR) is a geophysical technique widely used in near-surface non-invasive detecting. It has the ability to obtaining a high-resolution internal structure of living trunks. Full wave inversion (FWI) has been widely used to reconstruct the dielectric constant and conductivity distribution for cross-well application. However, in some cases, the amplitude information is not reliable due to the antenna coupling, radiation pattern and other effects. We present a multiscale phase inversion (MPI) method, which largely matches the phase information by normalizing the magnitude spectrum; in addition, a natural multiscale approach by integrating the input data with different times is implemented to partly mitigate the local minimal problem. Two synthetic GPR datasets generated from a healthy oak tree trunk and from a decayed trunk are tested by MPI and FWI. Field GPR dataset consisting of 30 common shot GPR data are acquired on a standing white oak tree (Quercus alba); the MPI and FWI methods are used to reconstruct the dielectric constant distribution of the tree cross-section. Results indicate that MPI has more tolerance to the starting model, noise level and source wavelet. It can provide a more accurate image of the dielectric constant distribution compared to the conventional FWI.

Comparison of different infiltration schemes in the regional climate model REMO

2021 ◽  
Author(s):  
Daniel Abel ◽  
Katrin Ziegler ◽  
Felix Pollinger ◽  
Heiko Paeth
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Root Zone ◽  
Regional Climate ◽  
Climate Projections ◽  
Soil Hydrology ◽  
Spatiotemporal Resolution ◽  
Development Fund ◽  
Near Surface

<p>The European Regional Development Fund-Project BigData@Geo aims to create highly resolved climate projections for the model region of Lower Franconia in Bavaria, Germany. These projections are analyzed and made available to local stakeholders of agriculture, forestry, and viniculture as well as general public. Since regional climate models’ spatiotemporal resolution often is too coarse to deal with such local issues, the regional climate model REMO is improved within the frame of the project in cooperation with the Climate Service Center Germany (GERICS).</p><p>Accurate and highly resolved climate projections require realistic modeling of soil hydrology. Thus, REMO’s original bucket scheme is replaced by a 5-layer soil scheme. It allows for the representation of water below the root zone. Evaporation is possible solely from the top layer instead of the entire bucket and water can flow vertically between the layers. Consequently, the properties and processes change significantly compared to the bucket scheme. Both, the bucket and the 5-layer scheme, use the improved Arno scheme to separate throughfall into infiltration and surface runoff.</p><p>In this study, we examine if this scheme is suitable for use with the improved soil hydrology or if other schemes lead to better results. For this, we (1) modify the improved Arno scheme and further introduce the infiltration equations of (2) Philip as well as (3) Green and Ampt. First results of the comparison of these four different schemes and their influence on soil moisture and near-surface atmospheric variables are presented.</p>

Processing Ground Penetrating Radar Data To Improve Resolution Of Near-Surface Targets

1993 ◽  
Author(s):  
Kevin Gerlitz ◽  
Michael D. Knoll ◽  
Guy M. Cross ◽  
Robert D. Luzitano ◽  
Rosemary Knight
Keyword(s):  
Ground Penetrating Radar ◽  
Radar Data ◽  
Near Surface ◽  
Ground Penetrating

scholarly journals The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales

2015 ◽  
Vol 19 (12) ◽  
pp. 4831-4844 ◽  
Author(s):  
C. Draper ◽  
R. Reichle
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Surface Soil ◽  
Root Zone ◽  
Surface Model ◽  
Surface Soil Moisture ◽  
Near Surface ◽  
In Situ Observations ◽  
The Impact

Abstract. A 9 year record of Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) soil moisture retrievals are assimilated into the Catchment land surface model at four locations in the US. The assimilation is evaluated using the unbiased mean square error (ubMSE) relative to watershed-scale in situ observations, with the ubMSE separated into contributions from the subseasonal (SMshort), mean seasonal (SMseas), and inter-annual (SMlong) soil moisture dynamics. For near-surface soil moisture, the average ubMSE for Catchment without assimilation was (1.8 × 10−3 m3 m−3)2, of which 19 % was in SMlong, 26 % in SMseas, and 55 % in SMshort. The AMSR-E assimilation significantly reduced the total ubMSE at every site, with an average reduction of 33 %. Of this ubMSE reduction, 37 % occurred in SMlong, 24 % in SMseas, and 38 % in SMshort. For root-zone soil moisture, in situ observations were available at one site only, and the near-surface and root-zone results were very similar at this site. These results suggest that, in addition to the well-reported improvements in SMshort, assimilating a sufficiently long soil moisture data record can also improve the model representation of important long-term events, such as droughts. The improved agreement between the modeled and in situ SMseas is harder to interpret, given that mean seasonal cycle errors are systematic, and systematic errors are not typically targeted by (bias-blind) data assimilation. Finally, the use of 1-year subsets of the AMSR-E and Catchment soil moisture for estimating the observation-bias correction (rescaling) parameters is investigated. It is concluded that when only 1 year of data are available, the associated uncertainty in the rescaling parameters should not greatly reduce the average benefit gained from data assimilation, although locally and in extreme years there is a risk of increased errors.

scholarly journals Investigating the Performance of Bi-Static GPR Antennas for Near-Surface Object Detection

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 170 ◽  
Author(s):  
Xianyang Gao ◽  
Frank J. W. Podd ◽  
Wouter Van Verre ◽  
David J. Daniels ◽  
Anthony J. Peyton
Keyword(s):  
Ground Penetrating Radar ◽  
Input Impedance ◽  
Test Site ◽  
Late Time ◽  
Near Surface ◽  
Object Depth ◽  
Ground Penetrating ◽  
Antenna Input ◽  
Surface Object ◽  
Bow Tie

Antennas are an important component in ground penetrating radar (GPR) systems. Although there has been much research reported on the design of individual antennas, there is less research reported on the design of the geometry of bi-static antennas. This paper considers the effects of key parameters in the setup of a GPR head consisting of a bi-static bow-tie pair to show the effect of these parameters on the GPR performance. The parameters investigated are the antenna separation, antenna height above the soil, and antenna input impedance. The investigation of the parameters was performed by simulation and measurements. It was found when the bi-static antennas were separated by 7 cm to 9 cm and were operated close to the soil (2 cm to 4 cm), the reflected signal from a near-surface object is relatively unaffected by height variation and object depth. An antenna input impedance of 250 Ω was chosen to feed the antennas to reduce the late-time ringing. Using these results, a new GPR system was designed and then evaluated at a test site near Benkovac, Croatia.

Surveying Batavia’s Graveyard: Geophysical controlled experiments and subsurface imaging of archaeological sites on an Indian Ocean coral island

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. B147-B163 ◽  
Author(s):  
Jeffrey Shragge ◽  
David Lumley ◽  
Nader Issa ◽  
Tom Hoskin ◽  
Alistair Paterson ◽  
...  
Keyword(s):  
Sea Water ◽  
Controlled Experiments ◽  
Near Surface ◽  
Survey Techniques ◽  
Geophysical Surveys ◽  
Archaeological Materials ◽  
Coral Island ◽  
Water Saturated ◽  
Ground Penetrating ◽  
Geophysical Anomalies

We conducted geophysical surveys on Beacon Island in the Houtman Abrolhos archipelago offshore Western Australia, to investigate areas of archaeological interest related to the 1629 Batavia shipwreck, mutiny, and massacre. We used three complementary near-surface geophysical survey techniques (total magnetic intensity, electromagnetic induction mapping, and ground-penetrating radar) to identify anomalous target zones for archaeological excavation. Interpreting near-surface geophysical anomalies is often complex and nonunique, although it can be significantly improved by achieving a better understanding of site-specific factors including background conditions, natural variability, detectability limits, and the geophysical response to, and spatial resolution of, buried targets. These factors were not well-understood for Beacon Island nor indeed for the Australian coastal environment. We have evaluated the results of controlled experiments in which we bury known targets at representative depths and analyze the geophysical responses in terms of an ability to detect and resolve targets from natural background variability. The maximum depth of detectability of calibration targets on Beacon Island is limited to approximately 0.5 m due to significant variations in background physical properties between a thin ([Formula: see text]) and highly unconsolidated dry sand, shell, and coral layer of variable thickness overlying a sea-water-saturated sandy half-space. Our controlled measurements have implications for calibrating and quantifying the interpretation of geophysical anomalies in areas of archaeological interest, particularly in coastal and sandy-coral island environments. Our geophysical analyzes contributed to the discovery of archaeological materials and five historical burials associated with the 1629 Batavia shipwreck.

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