17 results on '"Roosjen, Peter"'
Search Results
2. Improved estimation of leaf area index and leaf chlorophyll content of a potato crop using multi-angle spectral data – potential of unmanned aerial vehicle imagery
- Author
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Roosjen, Peter P.J., Brede, Benjamin, Suomalainen, Juha M., Bartholomeus, Harm M., Kooistra, Lammert, and Clevers, Jan G.P.W.
- Published
- 2018
- Full Text
- View/download PDF
3. Detection and quantification of broadleaf weeds in turfgrass using close-range multispectral imagery with pixel- and object-based classification.
- Author
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Hahn, Daniel S., Roosjen, Peter, Morales, Alejandro, Nijp, Jelmer, Beck, Leslie, Velasco Cruz, Ciro, and Leinauer, Bernd
- Subjects
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TURFGRASSES , *GROUND vegetation cover , *WEEDS , *GROUND cover plants , *HIGH resolution imaging , *GRISELINIA littoralis - Abstract
The current practice used to evaluate broadleaf weed cover in turfgrass is visual assessment, which is time consuming and often leads to inconsistencies among evaluators. In this study, we investigated the effectiveness of constructing Random Forest models (RF), either pixel-, object-based (OBIA) or a combination of both to detect and quantify broadleaf weed cover. High resolution multispectral images were captured of 136 turfgrass plots, seeded with five species of Festuca L. and overseeded with either clover (Trifolium repens L.), daisy (Bellis perennis L.), yarrow (Achillea millefolium L.), or a mixture of all three weeds. Ground measurements of vegetation cover and bare soil were taken with a point quadrat and digital image analysis. Weeds were detected with 99% accuracy by OBIA, followed by the combined approach (98%) and Pixel-based approach (93%). Accuracy at distinguishing among weed species was somewhat lower (89%, 81% and 90%, respectively), with yarrow contributing most to the decrease in accuracy. The predictions based on ground measurements were further compared to field measurements. For both soil and weed classification, models that used shape features (OBIA and combined) resulted in better agreement with field measurements compared to Pixel- based classifications. Our study suggests that broadleaf weed cover comprised of species such as clover and daisy can be accurately quantified with high resolution multispectral images; however, quantifying yarrow cover remains challenging. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
4. AAPM : autmoated airborne pest monitoring
- Author
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Fahrentrapp, Johannes, Kooistra, Lammert, Green, David R., Roosjen, Peter, and Gregory, Billy
- Subjects
630: Landwirtschaft - Published
- 2019
5. Automated airborne pest monitoring of drosophila suzukii in crops and natural habitats
- Author
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Fahrentrapp, Johannes, Roosjen, Peter, Kooistra, Lammer, Gregory, Billy J., and Green, David R.
- Subjects
630: Landwirtschaft - Published
- 2019
6. Automated airborne pest monitoring of drosophila suzukii in crops and natural habitats
- Author
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Roosjen, Peter, Lammert, Kooistra, Fahrentrapp, Johannes, and Green, David R.
- Subjects
630: Landwirtschaft - Abstract
Drosophila suzukii has become a serious pest in Europe attacking many soft-skinned crops such as several berry species and grapevines since its spread in 2008 to Spain and Italy. An efficient and accurate monitoring system to identify the presence of Drosophila suzukii in crops and their surroundings is essential for the prevention of damage to economically valuable fruit crops. Existing methods for monitoring Drosophila suzukii are costly, time and labor intensive, prone to errors, and typically conducted at a low spatial resolution. To overcome current monitoring limitations, we are developing a novel system consisting of sticky traps which are monitored by means of Unmanned Aerial Vehicles (UAVs) and an image processing pipeline that automatically identifies and counts the number of Drosophila suzukii per trap location. To this end, we are currently collecting high resolution RGB imagery of Drosophila suzukii flies in sticky traps taken from both a static position (tripod) and from a UAV, which are then used as input to train deep learning models. Preliminary results show that a large part of the of Drosophila suzukii flies that are caught in the sticky traps can be correctly identified by the trained deep learning models. In the future, an autonomously flying UAV platform will be programmed to capture imagery of the sticky traps under field conditions. The collected imagery will be transferred directly to cloud-based storage for subsequent processing and analysis to identify the presence and count of Drosophila suzukii in near real time. This data will be used as input to a decision support system (DSS) to provide valuable information for farmers.
- Published
- 2018
7. AAPM : automated airborne pest monitoring
- Author
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Fahrentrapp, Johannes, Roosjen, Peter, Kooistra, Lammert, Gregory, Billy J., and Green, David R.
- Subjects
630: Landwirtschaft - Abstract
www.aapmproject.eu/
- Published
- 2018
8. Improved estimation of leaf area index and leaf chlorophyll content of a potato crop using multi-angle spectral data - potential of unmanned aerial vehicle imagery
- Author
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Roosjen, Peter, P.J., Brede, Benjamin, Suomalainen, Juha, M., Bartholomeus, Harm, M., Kooistra, Lammert, Clevers, Jan, G.P.W., National Land Survey of Finland, and Maanmittauslaitos
- Subjects
multi-angular reflectance ,reflectance anisotropy ,leaf area index ,PROSAIL ,unmanned aerial vehicle ,Leaf chlorophyll content ,model inversion - Abstract
In addition to single-angle reflectance data, multi-angular observations can be used as an additional information source for the retrieval of properties of an observed target surface. In this paper, we studied the potential of multi-angular reflectance data for the improvement of leaf area index (LAI) and leaf chlorophyll content (LCC) estimation by numerical inversion of the PROSAIL model. The potential for improvement of LAI and LCC was evaluated for both measured data and simulated data. The measured data was collected on 19 July 2016 by a frame-camera mounted on an unmanned aerial vehicle (UAV) over a potato field, where eight experimental plots of 30 × 30 m were designed with different fertilization levels. Dozens of viewing angles, covering the hemisphere up to around 30° from nadir, were obtained by a large forward and sideways overlap of collected images. Simultaneously to the UAV flight, in situ measurements of LAI and LCC were performed. Inversion of the PROSAIL model was done based on nadir data and based on multi-angular data collected by the UAV. Inversion based on the multi-angular data performed slightly better than inversion based on nadir data, indicated by the decrease in RMSE from 0.70 to 0.65 m2/m2 for the estimation of LAI, and from 17.35 to 17.29 μg/cm2 for the estimation of LCC, when nadir data were used and when multi-angular data were used, respectively. In addition to inversions based on measured data, we simulated several datasets at different multi-angular configurations and compared the accuracy of the inversions of these datasets with the inversion based on data simulated at nadir position. In general, the results based on simulated (synthetic) data indicated that when more viewing angles, more well distributed viewing angles, and viewing angles up to larger zenith angles were available for inversion, the most accurate estimations were obtained. Interestingly, when using spectra simulated at multi-angular sampling configurations as were captured by the UAV platform (view zenith angles up to 30°), already a huge improvement could be obtained when compared to solely using spectra simulated at nadir position. The results of this study show that the estimation of LAI and LCC by numerical inversion of the PROSAIL model can be improved when multi-angular observations are introduced. However, for the potato crop, PROSAIL inversion for measured data only showed moderate accuracy and slight improvements.
- Published
- 2018
9. Deep learning for automated detection of Drosophila suzukii: potential for UAV‐based monitoring.
- Author
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Roosjen, Peter PJ, Kellenberger, Benjamin, Kooistra, Lammert, Green, David R, and Fahrentrapp, Johannes
- Subjects
DROSOPHILA suzukii ,DEEP learning ,CONVOLUTIONAL neural networks ,INTEGRATED pest control ,INSECT traps ,PEST control - Abstract
BACKGROUND The fruit fly Drosophila suzukii, or spotted wing drosophila (SWD), is a serious pest worldwide, attacking many soft‐skinned fruits. An efficient monitoring system that identifies and counts SWD in crops and their surroundings is therefore essential for integrated pest management (IPM) strategies. Existing methods, such as catching flies in liquid bait traps and counting them manually, are costly, time‐consuming and labour‐intensive. To overcome these limitations, we studied insect trap monitoring using image‐based object detection with deep learning. RESULTS: Based on an image database with 4753 annotated SWD flies, we trained a ResNet‐18‐based deep convolutional neural network to detect and count SWD, including sex prediction and discrimination. The results show that SWD can be detected with an area under the precision recall curve (AUC) of 0.506 (female) and 0.603 (male) in digital images taken from a static position. For images collected using an unmanned aerial vehicle (UAV), the algorithm detected SWD individuals with an AUC of 0.086 (female) and 0.284 (male). The lower AUC for the aerial imagery was due to lower image quality caused by stabilisation manoeuvres of the UAV during image collection. CONCLUSION: Our results indicate that it is possible to monitor SWD using deep learning and object detection. Moreover, the results demonstrate the potential of UAVs to monitor insect traps, which could be valuable in the development of autonomous insect monitoring systems and IPM. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
10. Measuring and modeling the effect of surface moisture on the spectral reflectance of coastal beach sand
- Author
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Nolet, Corjan, Poortinga, Ate, Roosjen, Peter, Bartholomeus, Harm, Ruessink, Gerben, Proceskunde, Coastal dynamics, Fluvial systems and Global change, Proceskunde, and Coastal dynamics, Fluvial systems and Global change
- Subjects
Absorption of water ,Optical Phenomena ,Spectrophotometry, Infrared ,Pedology ,lcsh:Medicine ,Geographical Regions ,spectral reflectance ,light scattering ,Soil ,remote sensing ,soil physics ,Spectrum Analysis Techniques ,Hydraulic conductivity ,Laboratory of Geo-information Science and Remote Sensing ,moisture ,water absorption ,Geoinformatics ,drying ,lcsh:Science ,Water content ,soil-water-content ,Coastal Regions ,Physics ,Multidisciplinary ,Remote Sensing Imagery ,Moisture ,Geography ,Electromagnetic Radiation ,article ,Absorption Spectroscopy ,PE&RC ,Wavelength ,Optical Equipment ,Erosion ,Physical Sciences ,Engineering and Technology ,light ,seashore ,Research Article ,Computer and Information Sciences ,spectroscopy ,porosity ,Surface Properties ,Oceans and Seas ,entrainment ,penetration ,Mineralogy ,Soil Science ,Equipment ,Research and Analysis Methods ,Pore water pressure ,Surface Water ,wet ,wind ,Laboratorium voor Geo-informatiekunde en Remote Sensing ,controlled study ,procedures ,Porosity ,aeolian sediment transport ,variability ,Soil physics ,Ecology and Environmental Sciences ,lcsh:R ,Water ,Geomorphology ,15. Life on land ,Models, Theoretical ,Bodemfysica en Landbeheer ,sand moisture ,optics ,laser ,Soil Physics and Land Management ,Regional Geography ,waveform ,Earth Sciences ,lcsh:Q ,Hydrology ,soil moisture ,hydraulic permeability ,mathematical model - Abstract
Surface moisture is an important supply limiting factor for aeolian sand transport, which is the primary driver of coastal dune development. As such, it is critical to account for the control of surface moisture on available sand for dune building. Optical remote sensing has the potential to measure surface moisture at a high spatio-temporal resolution. It is based on the principle that wet sand appears darker than dry sand: it is less reflective. The goals of this study are (1) to measure and model reflectance under controlled laboratory conditions as function of wavelength (l) and surface moisture (h) over the optical domain of 350-2500 nm, and (2) to explore the implications of our laboratory findings for accurately mapping the distribution of surface moisture under natural conditions. A laboratory spectroscopy experiment was conducted to measure spectral reflectance (1 nm interval) under different surface moisture conditions using beach sand. A non-linear increase of reflectance upon drying was observed over the full range of wavelengths. Two models were developed and tested. The first model is grounded in optics and describes the proportional contribution of scattering and absorption of light by pore water in an unsaturated sand matrix. The second model is grounded in soil physics and links the hydraulic behaviour of pore water in an unsaturated sand matrix to its optical properties. The optical model performed well for volumetric moisture content h v 24% (R2 w 0.97), but underestimated reflectance for h between 24-30% (R2 w 0.92), most notable around the 1940 nm water absorption peak. The soil-physical model performed very well (R2 w 0.99) but is limited to 4% w h v 24%. Results from a field experiment show that a short-wave infrared terrestrial laser scanner (l = 1550 nm) can accurately relate surface moisture to reflectance (standard error 2.6%), demonstrating its potential to derive spatially extensive surface moisture maps of a natural coastal beach.
- Published
- 2014
11. Mapping Reflectance Anisotropy of a Potato Canopy Using Aerial Images Acquired with an Unmanned Aerial Vehicle.
- Author
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Roosjen, Peter P. J., Suomalainen, Juha M., Bartholomeus, Harm M., Kooistra, Lammert, and Clevers, Jan G. P. W.
- Subjects
- *
POTATO yields , *AGRICULTURE , *DRONE aircraft , *IMAGE processing , *DISTRIBUTION (Probability theory) , *DATA analysis - Abstract
Viewing and illumination geometry has a strong influence on optical measurements of natural surfaces due to their anisotropic reflectance properties. Typically, cameras on-board unmanned aerial vehicles (UAVs) are affected by this because of their relatively large field of view (FOV) and thus large range of viewing angles. In this study, we investigated the magnitude of reflectance anisotropy effects in the 500–900 nm range, captured by a frame camera mounted on a UAV during a standard mapping flight. After orthorectification and georeferencing of the images collected by the camera, we calculated the viewing geometry of all observations of each georeferenced ground pixel, forming a dataset with multi-angular observations. We performed UAV flights on two days during the summer of 2016 over an experimental potato field where different zones in the field received different nitrogen fertilization treatments. These fertilization levels caused variation in potato plant growth and thereby differences in structural properties such as leaf area index (LAI) and canopy cover. We fitted the Rahman–Pinty–Verstraete (RPV) model through the multi-angular observations of each ground pixel to quantify, interpret, and visualize the anisotropy patterns in our study area. The Q parameter of the RPV model, which controls the proportion of forward and backward scattering, showed strong correlation with canopy cover, where in general an increase in canopy cover resulted in a reduction of backward scattering intensity, indicating that reflectance anisotropy contains information on canopy structure. In this paper, we demonstrated that anisotropy data can be extracted from measurements using a frame camera, collected during a typical UAV mapping flight. Future research will focus on how to use the anisotropy signal as a source of information for estimation of physical vegetation properties. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
12. Hyperspectral Reflectance Anisotropy Measurements Using a Pushbroom Spectrometer on an Unmanned Aerial Vehicle--Results for Barley, Winter Wheat, and Potato.
- Author
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Roosjen, Peter P. J., Suomalainen, Juha M., Bartholomeus, Harm M., and Clevers, Jan G. P. W.
- Subjects
- *
REFLECTANCE measurement , *ANISOTROPY , *SPECTROMETERS , *DRONE aircraft , *GONIOMETERS , *BARLEY , *WINTER wheat - Abstract
Reflectance anisotropy is a signal that contains information on the optical and structural properties of a surface and can be studied by performing multi-angular reflectance measurements that are often done using cumbersome goniometric measurements. In this paper we describe an innovative and fast method where we use a hyperspectral pushbroom spectrometer mounted on a multirotor unmanned aerial vehicle (UAV) to perform such multi-angular measurements. By hovering the UAV above a surface while rotating it around its vertical axis, we were able to sample the reflectance anisotropy within the field of view of the spectrometer, covering all view azimuth directions up to a 30° view zenith angle. We used this method to study the reflectance anisotropy of barley, potato, and winter wheat at different growth stages. The reflectance anisotropy patterns of the crops were interpreted by analysis of the parameters obtained by fitting of the Rahman-Pinty-Verstraete (RPV) model at a 5-nm interval in the 450-915 nm range. To demonstrate the results of our method, we firstly present measurements of barley and winter wheat at two different growth stages. On the first measuring day, barley and winter wheat had structurally comparable canopies and displayed similar anisotropic reflectance patterns. On the second measuring day the anisotropy of crops differed significantly due to the crop-specific development of grain heads in the top layer of their canopies. Secondly, we show how the anisotropy is reduced for a potato canopy when it grows from an open row structure to a closed canopy. In this case, especially the backward scattering intensity was strongly diminished due to the decrease in shadowing effects that were caused by the potato rows that were still present on the first measuring day. The results of this study indicate that the presented method is capable of retrieving anisotropic reflectance characteristics of vegetation canopies and that it is a feasible alternative for field goniometer measurements. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
13. West Nile Virus: High Transmission Rate in North-Western European Mosquitoes Indicates Its Epidemic Potential and Warrants Increased Surveillance.
- Author
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Fros, Jelke J., Geertsema, Corinne, Vogels, Chantal B., Roosjen, Peter P., Failloux, Anna-Bella, Vlak, Just M., Koenraadt, Constantianus J., Takken, Willem, and Pijlman, Gorben P.
- Subjects
WEST Nile virus ,MOSQUITOES ,EPIDEMICS ,CULEX pipiens - Abstract
Background: West Nile virus (WNV) is a highly pathogenic flavivirus transmitted by Culex spp. mosquitoes. In North America (NA), lineage 1 WNV caused the largest outbreak of neuroinvasive disease to date, while a novel pathogenic lineage 2 strain circulates in southern Europe. To estimate WNV lineage 2 epidemic potential it is paramount to know if mosquitoes from currently WNV-free areas can support further spread of this epidemic. Methodology/Principal Findings: We assessed WNV vector competence of Culex pipiens mosquitoes originating from north-western Europe (NWE) in direct comparison with those from NA. We exposed mosquitoes to infectious blood meals of lineage 1 or 2 WNV and determined the infection and transmission rates. We explored reasons for vector competence differences by comparing intrathoracic injection versus blood meal infection, and we investigated the influence of temperature. We found that NWE mosquitoes are highly competent for both WNV lineages, with transmission rates up to 25%. Compared to NA mosquitoes, transmission rates for lineage 2 WNV were significantly elevated in NWE mosquitoes due to better virus dissemination from the midgut and a shorter extrinsic incubation time. WNV infection rates further increased with temperature increase. Conclusions/Significance: Our study provides experimental evidence to indicate markedly different risk levels between both continents for lineage 2 WNV transmission and suggests a degree of genotype-genotype specificity in the interaction between virus and vector. Our experiments with varying temperatures explain the current localized WNV activity in southern Europe, yet imply further epidemic spread throughout NWE during periods with favourable climatic conditions. This emphasizes the need for intensified surveillance of virus activity in current WNV disease-free regions and warrants increased awareness in clinics throughout Europe. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF
14. A Laboratory Goniometer System for Measuring Reflectance and Emittance Anisotropy.
- Author
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Roosjen, Peter P. J., Clevers, Jan G. P. W., Bartholomeus, Harm M., Schaepman, Michael E., Schaepman-Strub, Gabriela, Jalink, Henk, der Schoor, Rob van, and de Jong, Arjan
- Subjects
- *
GONIOMETERS , *ANISOTROPY , *REMOTE sensing , *MOUNTING of cameras , *PLANT canopies , *REFLECTANCE spectroscopy - Abstract
In this paper, a laboratory goniometer system for performing multi-angular measurements under controlled illumination conditions is described. A commercially available robotic arm enables the acquisition of a large number of measurements over the full hemisphere within a short time span making it much faster than other goniometers. In addition, the presented set-up enables assessment of anisotropic reflectance and emittance behaviour of soils, leaves and small canopies. Mounting a spectrometer enables acquisition of either hemispherical measurements or measurements in the horizontal plane. Mounting a thermal camera allows directional observations of the thermal emittance. This paper also presents three showcases of these different measurement set-ups in order to illustrate its possibilities. Finally, suggestions for applying this instrument and for future research directions are given, including linking the measured reflectance anisotropy with physically-based anisotropy models on the one hand and combining them with field goniometry measurements for joint analysis with remote sensing data on the other hand. The speed and flexibility of the system offer a large added value to the existing pool of laboratory goniometers. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
15. REFLECTANCE ANISOTROPY MEASUREMENTS USING A PUSHBROOM SPECTROMETER MOUNTED ON UAV AND A LABORATORY GONIOMETER -- PRELIMINARY RESULTS.
- Author
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Suomalainen, Juha, Roosjen, Peter, Bartholomeus, Harm, and Clevers, Jan
- Subjects
ANISOTROPY ,GONIOMETERS ,AERIAL surveys - Abstract
During 2014--2015 we have developed a new method to measure reflectance factor anisotropy using a PUSHBROOM spectrometer mounted on a multicopter UAV. In this paper/presentation we describe the acquisition method and show the preliminary results of the experiment. To validate the measurements the same targets have also been measured with a laboratory goniometer system. The first experiments over sugar beet fields in 2014 show similar trends in both UAV and laboratory anisotropy data, but also some differences caused by differences in sampling and diffuse illumination. In 2015 a more extensive study on wheat, barley and potato fields were performed. The measurements were repeated on three days over the growth of the crops allowing linking the development of the crops to the anisotropy signals. On each day the anisotropy measurement was repeated 4--5 times with different solar zenith angles ranging from 60° to 40° allowing analysis how the solar angle affects the anisotropy. The first results of these experiments will be presented in this conference. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF
16. Streptococcus salivarius MS-oral-D6 promotes gingival re-epithelialization in vitro through a secreted serine protease.
- Author
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Fernandez-Gutierrez MM, Roosjen PPJ, Ultee E, Agelink M, Vervoort JJM, Keijser B, Wells JM, and Kleerebezem M
- Subjects
- Cytokines biosynthesis, Humans, Inflammation Mediators metabolism, Models, Biological, Mouth microbiology, Gingiva microbiology, Gingiva physiology, Re-Epithelialization, Serine Proteases biosynthesis, Streptococcus salivarius physiology, Wound Healing
- Abstract
Gingival re-epithelialization represents an essential phase of oral wound healing in which epithelial integrity is re-establish. We developed an automated high-throughput re-epithelialization kinetic model, using the gingival epithelial cell line Ca9-22. The model was employed to screen 39 lactic acid bacteria, predominantly including oral isolates, for their capacity to accelerate gingival re-epithelialization. This screen identified several strains of Streptococcus salivarius that stimulated re-epithelialization. Further analysis revealed that S. salivarius strain MS-oral-D6 significantly promoted re-epithelialization through a secreted proteinaceous compound and subsequent experiments identified a secreted serine protease as the most likely candidate to be involved in re-epithelialization stimulation. The identification of bacteria or their products that stimulate gingival wound repair may inspire novel strategies for the maintenance of oral health.
- Published
- 2017
- Full Text
- View/download PDF
17. Measuring and modeling the effect of surface moisture on the spectral reflectance of coastal beach sand.
- Author
-
Nolet C, Poortinga A, Roosjen P, Bartholomeus H, and Ruessink G
- Subjects
- Soil chemistry, Spectrophotometry, Infrared, Surface Properties, Models, Theoretical, Oceans and Seas, Optical Phenomena, Water chemistry
- Abstract
Surface moisture is an important supply limiting factor for aeolian sand transport, which is the primary driver of coastal dune development. As such, it is critical to account for the control of surface moisture on available sand for dune building. Optical remote sensing has the potential to measure surface moisture at a high spatio-temporal resolution. It is based on the principle that wet sand appears darker than dry sand: it is less reflective. The goals of this study are (1) to measure and model reflectance under controlled laboratory conditions as function of wavelength (λ) and surface moisture (θ) over the optical domain of 350-2500 nm, and (2) to explore the implications of our laboratory findings for accurately mapping the distribution of surface moisture under natural conditions. A laboratory spectroscopy experiment was conducted to measure spectral reflectance (1 nm interval) under different surface moisture conditions using beach sand. A non-linear increase of reflectance upon drying was observed over the full range of wavelengths. Two models were developed and tested. The first model is grounded in optics and describes the proportional contribution of scattering and absorption of light by pore water in an unsaturated sand matrix. The second model is grounded in soil physics and links the hydraulic behaviour of pore water in an unsaturated sand matrix to its optical properties. The optical model performed well for volumetric moisture content θ < 24% (R2 > 0.97), but underestimated reflectance for θ between 24-30% (R2 > 0.92), most notable around the 1940 nm water absorption peak. The soil-physical model performed very well (R2 > 0.99) but is limited to 4% > θ < 24%. Results from a field experiment show that a short-wave infrared terrestrial laser scanner (λ = 1550 nm) can accurately relate surface moisture to reflectance (standard error 2.6%), demonstrating its potential to derive spatially extensive surface moisture maps of a natural coastal beach.
- Published
- 2014
- Full Text
- View/download PDF
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