| 1. |
- Braun, Andreas, et al.
(author)
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Above-ground biomass estimates based on active and passive microwave sensor imagery in low-biomass savanna ecosystems
- 2018
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In: Journal of Applied Remote Sensing. - 1931-3195. ; 12:4
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Journal article (peer-reviewed)abstract
- Although many studies exist on the estimation and monitoring of above-ground biomass (AGB) of forest ecosystems by methods of remote sensing, very little research has been carried out for ecosystems of low primary production, such as grasslands, steppes, or savannas. Our study intends to approach this gap and investigates the correlation between space-borne radar information and AGB at the scale of 10 tons per hectare and below. Additionally, we introduce the integration of passive brightness temperature as an additional covariate for biomass estimation, based on the hypothesis that it contains information complementary to microwave backscatter of the active sensors. Our findings show that large-scale estimates of AGB can be conducted for grasslands and savannas at high accuracy (R-2 up to 0.52). Additionally, we found that the integration of passive radar can increase the quality of AGB estimates in terms of explained variance for selected cases. We hope that these indications are a starting point for more integrated approaches toward biomass estimations based on Earth observation methods.
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| 2. |
- Gebru, Alem, et al.
(author)
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Investigation of atmospheric insect wing-beat frequencies and iridescence features using a multispectral kHz remote detection system
- 2014
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In: Journal of Applied Remote Sensing. - 1931-3195. ; 8
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Journal article (peer-reviewed)abstract
- Quantitative investigation of insect activity in their natural habitat is a challenging task for entomologists. It is difficult to address questions such as flight direction, predation strength, and overall activities using the current techniques such as traps and sweep nets. A multispectral kHz remote detection system using sunlight as an illumination source is presented. We explore the possibilities of remote optical classification of insects based on their wing-beat frequencies and iridescence features. It is shown that the wing-beat frequency of the fast insect events can be resolved by implementing high-sampling frequency. The iridescence features generated from the change of color in two channels (visible and near-infrared) during wing-beat cycle are presented. We show that the shape of the wing-beat trajectory is different for different insects. The flight direction of an atmospheric insect is also determined using a silicon quadrant detector. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
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| 3. |
- Gebru, Alem, et al.
(author)
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Probing insect backscatter cross section and melanization using kHz optical remote detection system
- 2017
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In: Journal of Applied Remote Sensing. - 1931-3195. ; 11:1
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Journal article (peer-reviewed)abstract
- A kHz optical remote sensing system is implemented to determine insect melanization features. This is done by measuring the backscatter signal in the visible and near-infrared (VISNIR) and short-wave infrared (SWIR) in situ. It is shown that backscatter cross section in the SWIR is insensitive to melanization and absolute melanization can be derived from the ratio of backscatter cross section of different bands (SWIR/VIS-NIR). We have shown that reflectance from insect is stronger in the SWIR as compared to NIR and VIS. This reveals that melanization plays a big role to determine backscatter cross section. One can use this feature as a tool to improve insect species and age classification. To support the findings, we illustrated melanization feature using three different insects [dead, dried specimens of snow white moth (Spilosoma genus), fox moth (Macrothylacia), and leather beetle (Odontotaenius genus)]. It is shown that reflectance from the leather beetle in the VIS and NIR is more affected by melanization as compared with snow white moth.
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| 4. |
- Hommersom, Annelies, et al.
(author)
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Intercomparison in the field between the new WISP-3 and other radiometers (TriOS Ramses, ASD FieldSpec, and TACCS)
- 2012
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In: Journal of Applied Remote Sensing. - 1931-3195. ; 6
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Journal article (peer-reviewed)abstract
- Optical close-range instruments can be applied to derive water quality parameters for monitoring purposes and for validation of optical satellite data. In situ radiometers are often difficult to deploy, especially from a small boat or a remote location. The water insight spectrometer (WISP-3) is a new hand-held radiometer for monitoring water quality, which automatically performs measurements with three radiometers (L-sky, L-u, E-d) and does not need to be connected with cables and electrical power during measurements. The instrument is described and its performance is assessed by an intercomparison to well-known radiometers, under real fieldwork conditions using a small boat and with sometimes windy and cloudy weather. Root mean squared percentage errors relative to those of the TriOS system were generally between 20% and 30% for remote sensing reflection, which was comparable to those of the other instruments included in this study. From this assessment, it can be stated that for the tested conditions, the WISP-3 can be used to obtain reflection spectra with accuracies in the same range as well-known instruments. When tuned with suitable regional algorithms, it can be used for quick scans for water quality monitoring of Chl, SPM, and aCDOM.
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| 5. |
- Jansson, Samuel, et al.
(author)
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Exploitation of an atmospheric lidar network node in single-shot mode for the classification of aerofauna
- 2017
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In: Journal of Applied Remote Sensing. - 1931-3195. ; 11:3
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Journal article (peer-reviewed)abstract
- The migration of aerofauna is a seasonal phenomenon of global scale, engaging billions of individuals in long-distance movements every year. Multiband lidar systems are commonly employed for the monitoring of aerosols and atmospheric gases, and a number of systems are operated regularly across Europe in the framework of the European Aerosol Lidar Network (EARLINET). This work examines the feasibility of utilizing EARLINET for the monitoring and classification of migratory fauna based on their pigmentation. An EARLINET Raman lidar system in Athens transmits laser pulses in three bands. By installing a four-channel digital oscilloscope on the system, the backscattered light from single-laser shots is measured. Roughly 100 h of data were gathered in the summer of 2013. The data were examined for aerofauna observations, and a total of 1735 observations interpreted as airborne organisms intercepting the laser beam were found during the study period in July to August 2013. The properties of the observations were analyzed spectrally and intercompared. A spectral multimodality that could be related to different observed species is shown. The system used in this pilot study is located in Athens, Greece. It is concluded that monitoring aerial migration using it and other similar systems is feasible with minor modifications, and that in-flight species classification could be possible.
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| 6. |
- Kutser, Tiit, et al.
(author)
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Variations in colored dissolved organic matter between boreal lakes studied by satellite remote sensing
- 2009
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In: Journal of Applied Remote Sensing. - : SPIE-Intl Soc Optical Eng. - 1931-3195. ; 3, s. 033538-
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Journal article (peer-reviewed)abstract
- Therehave been major improvements in our understanding of the roleof lakes and impoundments in global carbon cycle. Estimating thetrue role of lakes as sentinels, regulators and integrators ofclimate change requires analyzing carbon content of vast number oflakes. This is not realistic without using remote sensing methods.There are no satellite sensors at the moment that providefull global coverage and at the same time have spatialand radiometric resolutions suitable for lake color dissolved organic matter(CDOM) mapping. Therefore, the global study has to be performedusing more sensitive sensors to create regional lake CDOM statisticsfor as many sites as possible and extrapolating the resultson global lake map that can be created from lesssensitive sensor data with full global coverage (Landsat). As afirst step towards the global lake carbon mapping we showthat the Advanced Land Imager (ALI) allows to study regionalvariations in lake CDOM content and consequently estimate closely correlatedDOC (dissolved organic carbon) and CO2 saturation values. The resultsshow also that there may be regional differences in lakeCDOM content even if the study sites are geographically relativelyclose to each other and occupying zones with similar landcover and annual runoff. In one occasion the difference canbe explained with human impact that has caused acidification oflakes but the other occasion needs further studies.
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| 7. |
- Mason, David C., et al.
(author)
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Floodwater detection in urban areas using Sentinel-1 and WorldDEM data
- 2021
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In: Journal of Applied Remote Sensing. - : SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS. - 1931-3195. ; 15:3
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Journal article (peer-reviewed)abstract
- Remote sensing using synthetic aperture radar (SAR) is an important tool for emergency flood incident management. At present, operational services are mainly aimed at flood mapping in rural areas, as mapping in urban areas is hampered by the complicated backscattering mechanisms occurring there. A method for detecting flooding at high resolution in urban areas that may contain dense housing is presented. This largely uses remotely sensed data sets that are readily available on a global basis, including open-access Sentinel-1 SAR data, the WorldDEM digital surface model (DSM), and open-accessWorld Settlement Footprint data to identify urban areas. The method is a change detection technique that locally estimates flood levels in urban areas. It searches for increased SAR backscatter in the post-flood image due to double scattering between water (rather than unflooded ground) and adjacent buildings, and reduced SAR backscatter in areas away from high slopes. Areas of urban flooding are detected by comparing an interpolated flood level surface to the DSM. The method was tested on two flood events that occurred in the UK during the storms of Winter 2019-2020. High urban flood detection accuracies were achieved for the event in moderate density housing. The accuracy was reduced for the event in dense housing, when street widths became comparable to the DSM resolution, though it would still be useful for incident management. The method has potential for operational use for detecting urban flooding in near real-time on a global basis. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.
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| 8. |
- Mason, David C., et al.
(author)
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Robust algorithm for detecting floodwater in urban areas using synthetic aperture radar images
- 2018
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In: Journal of Applied Remote Sensing. - : SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS. - 1931-3195. ; 12:4
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Journal article (peer-reviewed)abstract
- Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. High-resolution synthetic aperture radar (SAR) sensors are able to detect flood extents in urban areas during both day- and night-time. If obtained in near real time, these flood extents can be used for emergency flood relief management or as observations for assimilation into flood forecasting models. A method for detecting flooding in urban areas using near real-time SAR data is developed and extensively tested under a variety of scenarios involving different flood events and different images. The method uses an SAR simulator in conjunction with LiDAR data of the urban area to predict areas of radar shadow and layover in the image caused by buildings and taller vegetation. Of the urban water pixels visible to the SAR, the flood detection accuracy averaged over the test examples is 83%, with a false alarm rate of 9%. The results indicate that flooding can be detected in the urban area to reasonable accuracy but that this accuracy is limited partly by the SAR's poor visibility of the urban ground surface due to shadow and layover. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.
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| 9. |
- Mason, David C., et al.
(author)
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Toward improved urban flood detection using Sentinel-1 : dependence of the ratio of post- to preflood double scattering cross sections on building orientation
- 2023
-
In: Journal of Applied Remote Sensing. - : SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS. - 1931-3195. ; 17:1
-
Journal article (peer-reviewed)abstract
- High-resolution synthetic aperture radar (SAR) sensors are now commonly used for flood detection. Automated detection tends to be limited to rural areas owing to the complicated backscattering mechanisms occurring in urban areas. Flooding can be identified in urban areas by searching for increased SAR backscatter in a postflood image due to double scattering between water and adjacent buildings, compared with a preflood image where double scattering is between unflooded ground and buildings. For co-polarized data, if f is the angle between the building wall and the satellite direction of travel, double scattering is strongest for f = 0 deg and falls off as f increases. Theoretical studies estimating the ratio of flooded-to-unflooded double scatterer (DS) radar cross section (RCS) using X-band SAR data, found that the ratio was high at f = 0 deg but only small at f > 10 deg. Ostensibly, this implies that few DSs might be detected in an urban area. However, experiments on real images have called into question the veracity of the modeling. We describe an empirical study to examine the relationship between the flooded-to-unflooded DS RCS ratio and f in Sentinel-1 (S-1) C-band data. We use high-resolution light detection and ranging and aerial photographs so that f can be measured accurately and is based on S-1 images from flood events that occurred in the United Kingdom during the storms of winter 2019 to 2020. Results indicate that vertical-vertical polarization is better than vertical-horizontal at distinguishing flooded from unflooded DS; that the theoretical model used underestimates the number of DS with high RCS ratios in the f range 10 deg to 30 deg; and that sufficient DS ground heights can be determined to estimate an accurate local average flood level, although in high density housing there are less of these due to the presence of adjacent buildings.
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| 10. |
- Pal, Mahendra K., et al.
(author)
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Noise reduction and destriping using local spatial statistics and quadratic regression from Hyperion images
- 2020
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In: Journal of Applied Remote Sensing. - : SPIE - The International Society for Optics and Photonics. - 1931-3195. ; 14:1
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Journal article (peer-reviewed)abstract
- Hyperion images from Earth Observing-1 (EO-1) are being used in natural resources assessment and management. The evaluation and verification of Hyperion images for the above applications are validating the EO-1 mission. However, the presence of random and striping noises in Hyperion images affect the accuracy of the results. Therefore, reduction of random noise and stripes from Hyperion images becomes indispensable for the evaluation of the results in natural resources assessment and in optimum use of the data. Thus, a collective approach for correcting pixels with no-data values and removing random noise and stripes from Hyperion radiance images is developed. In the developed method, first, no-data valued pixels are identified and corrected using a local median filter. Minimum noise fraction transformation is then used to reduce random noise from noise-dominated bands. Further, spatial statistical techniques are used to reduce random noise from the rest of the bands. Finally, a local quadratic regression by a least squares method is used to correct bad columns and global stripes, and a local-spatial-statistics-based algorithm is used to detect and correct local stripes. The effectiveness and efficiency of the algorithm is demonstrated by application to two Hyperion images: one from the Udaipur area, western India, and another from the Luleå area, northern Sweden. The results show that the algorithm reduces random and striping noise without introducing unwanted effects and alterations in the original normal data values in the images.
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