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Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (31 January 2017) | Viewed by 94404

Special Issue Editor

Prof. Dr. Jason Levy

E-Mail Website
Guest Editor
Disaster Preparedness and Emergency Management, University of Hawaii, 2540 Dole Street, Honolulu, HI 96822, USA
Interests: epidemiology and prevention of congenital anomalies; psychosis and affective psychosis; cancer epidemiology and prevention; molecular and human genome epidemiology; evidence synthesis related to public health and health services research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The current generation of remote sensors have become essential for many environmental, social, and business applications in our modern world. For example, sensors on satellites, airplanes, and unmanned aerial vehicles provide reliable, detailed, cost-effective, continuous, and synoptic coverage of natural and anthropogenic phenomena. This Special Issue examines practical issues in applied remote sensing and remote sensing decision making, such as: How to promote integrated remote sensing that takes into account a range of sensors and platforms? How to improve risk management with sensors? Can we improve remote sensing education? How to promote fully integrated, inexpensive sensor systems suitable for real world decision makers. Is it possible to truly integrate economic, social, and political factors in our decision making? What are the best models for public-private sector partnerships? What are the most practical web sensor architecture designs and field deployments for system interoperability and scalability? Any topic pertaining to real-world, integrated, and comprehensive remote sensing decision making is encouraged. This Special Issue explores the best way to make use of high-resolution satellite images and near-real-time measurements.

Prof. Dr. Jason K. Levy
Guest Editor

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Keywords

  • applied remote sensing
  • decision making
  • risk management
  • integrated sensor systems

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Published Papers (15 papers)

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Research

6608 KiB  
Article
Preliminary Study of UAS Equipped with Thermal Camera for Volcanic Geothermal Monitoring in Taiwan
by Shih-Hong Chio and Cheng-Horng Lin
Sensors 2017, 17(7), 1649; https://doi.org/10.3390/s17071649 - 18 Jul 2017
Cited by 19 | Viewed by 5979
Abstract
Thermal infrared cameras sense the temperature information of sensed scenes. With the development of UASs (Unmanned Aircraft Systems), thermal infrared cameras can now be carried on a quadcopter UAV (Unmanned Aircraft Vehicle) to appropriately collect high-resolution thermal images for volcanic geothermal monitoring in [...] Read more.
Thermal infrared cameras sense the temperature information of sensed scenes. With the development of UASs (Unmanned Aircraft Systems), thermal infrared cameras can now be carried on a quadcopter UAV (Unmanned Aircraft Vehicle) to appropriately collect high-resolution thermal images for volcanic geothermal monitoring in a local area. Therefore, the quadcopter UAS used to acquire thermal images for volcanic geothermal monitoring has been developed in Taiwan as part of this study to overcome the difficult terrain with highly variable topography and extreme environmental conditions. An XM6 thermal infrared camera was employed in this thermal image collection system. The Trimble BD970 GNSS (Global Navigation Satellite System) OEM (Original Equipment Manufacturer) board was also carried on the quadcopter UAV to gather dual-frequency GNSS observations in order to determine the flying trajectory data by using the Post-Processed Kinematic (PPK) technique; this will be used to establish the position and orientation of collected thermal images with less ground control points (GCPs). The digital surface model (DSM) and thermal orthoimages were then produced from collected thermal images. Tests conducted in the Hsiaoyukeng area of Taiwan’s Yangmingshan National Park show that the difference between produced DSM and airborne LIDAR (Light Detection and Ranging) data are about 37% between −1 m and 1 m, and 66% between −2 m and 2 m in the area surrounded by GCPs. As the accuracy of thermal orthoimages is about 1.78 m, it is deemed sufficient for volcanic geothermal monitoring. In addition, the thermal orthoimages show some phenomena not only more globally than do the traditional methods for volcanic geothermal monitoring, but they also show that the developed system can be further employed in Taiwan in the future. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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4835 KiB  
Article
Investigating Surface and Near-Surface Bushfire Fuel Attributes: A Comparison between Visual Assessments and Image-Based Point Clouds
by Christine Spits, Luke Wallace and Karin Reinke
Sensors 2017, 17(4), 910; https://doi.org/10.3390/s17040910 - 20 Apr 2017
Cited by 15 | Viewed by 5699
Abstract
Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques [...] Read more.
Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques such as image-based point clouds can offer land managers potentially more repeatable descriptions of fuel structure. This study compared the variability of estimates of surface and near-surface fuel attributes generated by eight assessment teams using the OFHAG and Fuels3D, a smartphone method utilising image-based point clouds, within three assessment plots in an Australian lowland forest. Surface fuel hazard scores derived from underpinning attributes were also assessed. Overall, this study found considerable variability between teams on most visually assessed variables, resulting in inconsistent hazard scores. Variability was observed within point cloud estimates but was, however, on average two to eight times less than that seen in visual estimates, indicating greater consistency and repeatability of this method. It is proposed that while variability within the Fuels3D method may be overcome through improved methods and equipment, inconsistencies in the OFHAG are likely due to the inherent subjectivity between assessors, which may be more difficult to overcome. This study demonstrates the capability of the Fuels3D method to efficiently and consistently collect data on fuel hazard and structure, and, as such, this method shows potential for use in fire management practices where accurate and reliable data is essential. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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24477 KiB  
Article
Prioritizing Seafloor Mapping for Washington’s Pacific Coast
by Timothy Battista, Ken Buja, John Christensen, Jennifer Hennessey and Katrina Lassiter
Sensors 2017, 17(4), 701; https://doi.org/10.3390/s17040701 - 28 Mar 2017
Cited by 3 | Viewed by 5309
Abstract
Remote sensing systems are critical tools used for characterizing the geological and ecological composition of the seafloor. However, creating comprehensive and detailed maps of ocean and coastal environments has been hindered by the high cost of operating ship- and aircraft-based sensors. While a [...] Read more.
Remote sensing systems are critical tools used for characterizing the geological and ecological composition of the seafloor. However, creating comprehensive and detailed maps of ocean and coastal environments has been hindered by the high cost of operating ship- and aircraft-based sensors. While a number of groups (e.g., academic research, government resource management, and private sector) are engaged in or would benefit from the collection of additional seafloor mapping data, disparate priorities, dauntingly large data gaps, and insufficient funding have confounded strategic planning efforts. In this study, we addressed these challenges by implementing a quantitative, spatial process to facilitate prioritizing seafloor mapping needs in Washington State. The Washington State Prioritization Tool (WASP), a custom web-based mapping tool, was developed to solicit and analyze mapping priorities from each participating group. The process resulted in the identification of several discrete, high priority mapping hotspots. As a result, several of the areas have been or will be subsequently mapped. Furthermore, information captured during the process about the intended application of the mapping data was paramount for identifying the optimum remote sensing sensors and acquisition parameters to use during subsequent mapping surveys. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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3199 KiB  
Article
Precise Orbit Solution for Swarm Using Space-Borne GPS Data and Optimized Pseudo-Stochastic Pulses
by Bingbing Zhang, Zhengtao Wang, Lv Zhou, Jiandi Feng, Yaodong Qiu and Fupeng Li
Sensors 2017, 17(3), 635; https://doi.org/10.3390/s17030635 - 20 Mar 2017
Cited by 8 | Viewed by 5290
Abstract
Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit [...] Read more.
Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospheric activity. We choose Swarm space-borne GPS data from 1–25 October 2014, and Swarm reduced-dynamic orbits are obtained. Orbit quality is assessed by GPS phase observation residuals and compared with Precise Science Orbits (PSOs) released by ESA. Results show that pseudo-stochastic pulses with a time interval of 6 min and a priori standard deviation (STD) of 10−2 mm/s in radial (R), along-track (T) and cross-track (N) directions are optimized to Swarm ZD reduced-dynamic precise orbit determination (POD). During high ionospheric activity, the mean Root Mean Square (RMS) of Swarm GPS phase residuals is at 9–11 mm, Swarm orbit solutions are also compared with Swarm PSOs released by ESA and the accuracy of Swarm orbits can reach 2–4 cm in R, T and N directions. Independent Satellite Laser Ranging (SLR) validation indicates that Swarm reduced-dynamic orbits have an accuracy of 2–4 cm. Swarm-B orbit quality is better than those of Swarm-A and Swarm-C. The Swarm orbits can be applied to the geomagnetic, geoelectric and gravity field recovery. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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3966 KiB  
Article
Study on Climate and Grassland Fire in HulunBuir, Inner Mongolia Autonomous Region, China
by Meifang Liu, Jianjun Zhao, Xiaoyi Guo, Zhengxiang Zhang, Gang Tan and Jihong Yang
Sensors 2017, 17(3), 616; https://doi.org/10.3390/s17030616 - 17 Mar 2017
Cited by 27 | Viewed by 6741
Abstract
Grassland fire is one of the most important disturbance factors of the natural ecosystem. Climate factors influence the occurrence and development of grassland fire. An analysis of the climate conditions of fire occurrence can form the basis for a study of the temporal [...] Read more.
Grassland fire is one of the most important disturbance factors of the natural ecosystem. Climate factors influence the occurrence and development of grassland fire. An analysis of the climate conditions of fire occurrence can form the basis for a study of the temporal and spatial variability of grassland fire. The purpose of this paper is to study the effects of monthly time scale climate factors on the occurrence of grassland fire in HulunBuir, located in the northeast of the Inner Mongolia Autonomous Region in China. Based on the logistic regression method, we used the moderate-resolution imaging spectroradiometer (MODIS) active fire data products named thermal anomalies/fire daily L3 Global 1km (MOD14A1 (Terra) and MYD14A1 (Aqua)) and associated climate data for HulunBuir from 2000 to 2010, and established the model of grassland fire climate index. The results showed that monthly maximum temperature, monthly sunshine hours and monthly average wind speed were all positively correlated with the fire climate index; monthly precipitation, monthly average temperature, monthly average relative humidity, monthly minimum relative humidity and the number of days with monthly precipitation greater than or equal to 5 mm were all negatively correlated with the fire climate index. We used the active fire data from 2011 to 2014 to validate the fire climate index during this time period, and the validation result was good (Pearson’s correlation coefficient was 0.578), which showed that the fire climate index model was suitable for analyzing the occurrence of grassland fire in HulunBuir. Analyses were conducted on the temporal and spatial distribution of the fire climate index from January to December in the years 2011–2014; it could be seen that from March to May and from September to October, the fire climate index was higher, and that the fire climate index of the other months is relatively low. The zones with higher fire climate index are mainly distributed in Xin Barag Youqi, Xin Barag Zuoqi, Zalantun Shi, Oroqen Zizhiqi, and Molidawa Zizhiqi; the zones with medium fire climate index are mainly distributed in Chen Barag Qi, Ewenkizu Zizhiqi, Manzhouli Shi, and Arun Qi; and the zones with lower fire climate index are mainly distributed in Genhe Shi, Ergun city, Yakeshi Shi, and Hailar Shi. The results of this study will contribute to the quantitative assessment and management of early warning and forecasting for mid-to long-term grassland fire risk in HulunBuir. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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5276 KiB  
Article
The Influence of Land Use on the Grassland Fire Occurrence in the Northeastern Inner Mongolia Autonomous Region, China
by Yiping Li, Jianjun Zhao, Xiaoyi Guo, Zhengxiang Zhang, Gang Tan and Jihong Yang
Sensors 2017, 17(3), 437; https://doi.org/10.3390/s17030437 - 23 Feb 2017
Cited by 29 | Viewed by 5853
Abstract
Grassland, as one of the most important ecosystems on Earth, experiences fires that affect the local ecology, economy and society. Notably, grassland fires occur frequently each year in northeastern China. Fire occurrence is a complex problem with multiple causes, such as natural factors, [...] Read more.
Grassland, as one of the most important ecosystems on Earth, experiences fires that affect the local ecology, economy and society. Notably, grassland fires occur frequently each year in northeastern China. Fire occurrence is a complex problem with multiple causes, such as natural factors, human activities and land use. This paper investigates the disruptive effects of grassland fire in the northeastern Inner Mongolia Autonomous Region of China. In this study, we relied on thermal anomaly detection from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to identify fire occurrences, and land use data were acquired by Landsat Thematic Mapper/Enhanced Thematic Mapper (TM/ETM). We discussed the relationship between land use and the spatial distribution of grassland fires. The results showed that the impact of land use on grassland fires was significant. Spatially, approximately 80% of grassland fires were clustered within 10 km of cultivated land, and grassland fires generally occurred in areas of intense human activity. The correlation between the spatial distribution of grassland fires and the land use degree in 2000, 2005 and 2010 was high, with R2 values of 0.686, 0.716, 0.633, respectively (p < 0.01). These results highlight the importance of the relationship between land use and grassland fire occurrence in the northeastern Inner Mongolia Autonomous Region. This study provides significance for local fire management and prevention. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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10744 KiB  
Article
Online Condition Monitoring of a Rail Fastening System on High-Speed Railways Based on Wavelet Packet Analysis
by Jiahong Wei, Chong Liu, Tongqun Ren, Haixia Liu and Wenjing Zhou
Sensors 2017, 17(2), 318; https://doi.org/10.3390/s17020318 - 8 Feb 2017
Cited by 42 | Viewed by 8230
Abstract
The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in [...] Read more.
The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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17459 KiB  
Article
Evaluation of the Vegetation Coverage Resilience in Areas Damaged by the Wenchuan Earthquake Based on MODIS-EVI Data
by Xiaofu Liu, Weiguo Jiang, Jing Li and Wenjie Wang
Sensors 2017, 17(2), 259; https://doi.org/10.3390/s17020259 - 28 Jan 2017
Cited by 17 | Viewed by 4887
Abstract
The concept of resilience was integrated into post-earthquake ecological restoration assessments in 10 counties heavily impacted by the 2008 Wenchuan earthquake. Ecological resilience was defined as the time interval required for the vegetation coverage to recover to pre-earthquake levels in damaged areas. MODIS-EVI [...] Read more.
The concept of resilience was integrated into post-earthquake ecological restoration assessments in 10 counties heavily impacted by the 2008 Wenchuan earthquake. Ecological resilience was defined as the time interval required for the vegetation coverage to recover to pre-earthquake levels in damaged areas. MODIS-EVI data from May to August in 2000 to 2016 were used to calculate the ecological resilience by fitting the curve of recovery rate (RR) versus time. The following conclusions were reached: (1) An area of 424.1 km2 sustained vegetation damage. (2) The vegetation recovery was found to be linear based on the statistical analysis of the most common components of the damaged areas; consequently, linear fitting was used to estimate the resilience. (3) In terms of vegetation coverage, 44.2% of the damaged areas have already recovered. The vast majority of damaged areas are predicted to achieve vegetation recovery by 2022, but 5.3% of the damaged areas will not recover within this time period and have no resilience. (4) The management of damaged areas near roads, rivers and mining operations, especially at elevations of 2000–2500 m, slopes greater than 30°, and precipitation levels greater than 1200 mm, should be prioritized in the future. (5) The innovations of this study include the method used to extract earthquake-related vegetation damage and the prediction of vegetation succession based on resilience. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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3725 KiB  
Article
Earthquake Damage Visualization (EDV) Technique for the Rapid Detection of Earthquake-Induced Damages Using SAR Data
by Ram C. Sharma, Ryutaro Tateishi, Keitarou Hara, Hoan Thanh Nguyen, Saeid Gharechelou and Luong Viet Nguyen
Sensors 2017, 17(2), 235; https://doi.org/10.3390/s17020235 - 27 Jan 2017
Cited by 37 | Viewed by 8753
Abstract
The damage of buildings and manmade structures, where most of human activities occur, is the major cause of casualties of from earthquakes. In this paper, an improved technique, Earthquake Damage Visualization (EDV) is presented for the rapid detection of earthquake damage using the [...] Read more.
The damage of buildings and manmade structures, where most of human activities occur, is the major cause of casualties of from earthquakes. In this paper, an improved technique, Earthquake Damage Visualization (EDV) is presented for the rapid detection of earthquake damage using the Synthetic Aperture Radar (SAR) data. The EDV is based on the pre-seismic and co-seismic coherence change method. The normalized difference between the pre-seismic and co-seismic coherences, and vice versa, are used to calculate the forward (from pre-seismic to co-seismic) and backward (from co-seismic to pre-seismic) change parameters, respectively. The backward change parameter is added to visualize the retrospective changes caused by factors other than the earthquake. The third change-free parameter uses the average values of the pre-seismic and co-seismic coherence maps. These three change parameters were ultimately merged into the EDV as an RGB (Red, Green, and Blue) composite imagery. The EDV could visualize the earthquake damage efficiently using Horizontal transmit and Horizontal receive (HH), and Horizontal transmit and Vertical receive (HV) polarizations data from the Advanced Land Observing Satellite-2 (ALOS-2). Its performance was evaluated in the Kathmandu Valley, which was hit severely by the 2015 Nepal Earthquake. The cross-validation results showed that the EDV is more sensitive to the damaged buildings than the existing method. The EDV could be used for building damage detection in other earthquakes as well. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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3997 KiB  
Article
Geometric Positioning for Satellite Imagery without Ground Control Points by Exploiting Repeated Observation
by Zhenling Ma, Xiaoliang Wu, Li Yan and Zhenliang Xu
Sensors 2017, 17(2), 240; https://doi.org/10.3390/s17020240 - 26 Jan 2017
Cited by 11 | Viewed by 5647
Abstract
With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important [...] Read more.
With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important means to acquire geospatial information. This paper explores geometric processing using satellite imagery without ground control points (GCPs). The outcome of spatial triangulation is introduced for geo-positioning as repeated observation. Results from combining block adjustment with non-oriented new images indicate the feasibility of geometric positioning with the repeated observation. GCPs are a must when high accuracy is demanded in conventional block adjustment; the accuracy of direct georeferencing with repeated observation without GCPs is superior to conventional forward intersection and even approximate to conventional block adjustment with GCPs. The conclusion is drawn that taking the existing oriented imagery as repeated observation enhances the effective utilization of previous spatial triangulation achievement, which makes the breakthrough for repeated observation to improve accuracy by increasing the base-height ratio and redundant observation. Georeferencing tests using data from multiple sensors and platforms with the repeated observation will be carried out in the follow-up research. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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4142 KiB  
Article
Combining CHAMP and Swarm Satellite Data to Invert the Lithospheric Magnetic Field in the Tibetan Plateau
by Yaodong Qiu, Zhengtao Wang, Weiping Jiang, Bingbing Zhang, Fupeng Li and Fei Guo
Sensors 2017, 17(2), 238; https://doi.org/10.3390/s17020238 - 26 Jan 2017
Cited by 12 | Viewed by 6327
Abstract
CHAMP and Swarm satellite magnetic data are combined to establish the lithospheric magnetic field over the Tibetan Plateau at satellite altitude by using zonal revised spherical cap harmonic analysis (R-SCHA). These data are integrated with geological structures data to analyze the relationship between [...] Read more.
CHAMP and Swarm satellite magnetic data are combined to establish the lithospheric magnetic field over the Tibetan Plateau at satellite altitude by using zonal revised spherical cap harmonic analysis (R-SCHA). These data are integrated with geological structures data to analyze the relationship between magnetic anomaly signals and large-scale geological tectonic over the Tibetan Plateau and to explore the active tectonic region based on the angle of the magnetic anomaly. Results show that the model fitting error is small for a layer 250–500 km high, and the RMSE of the horizontal and radial geomagnetic components is better than 0.3 nT. The proposed model can accurately describe medium- to long-scale lithospheric magnetic anomalies. Analysis indicates that a negative magnetic anomaly in the Tibetan Plateau significantly differs with a positive magnetic anomaly in the surrounding area, and the boundary of the positive and negative regions is generally consistent with the geological tectonic boundary in the plateau region. Significant differences exist between the basement structures of the hinterland of the plateau and the surrounding area. The magnetic anomaly in the Central and Western Tibetan Plateau shows an east–west trend, which is identical to the direction of the geological structures. The magnetic anomaly in the eastern part is arc-shaped and extends along the northeast direction. Its direction is significantly different from the trend of the geological structures. The strongest negative anomaly is located in the Himalaya block, with a central strength of up to −9 nT at a height of 300 km. The presence of a strong negative anomaly implies that the Curie isotherm in this area is relatively shallow and deep geological tectonic activity may exist. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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3705 KiB  
Article
Emission Flux Measurement Error with a Mobile DOAS System and Application to NOx Flux Observations
by Fengcheng Wu, Ang Li, Pinhua Xie, Hao Chen, Zhaokun Hu, Qiong Zhang, Jianguo Liu and Wenqing Liu
Sensors 2017, 17(2), 231; https://doi.org/10.3390/s17020231 - 25 Jan 2017
Cited by 19 | Viewed by 5650
Abstract
Mobile differential optical absorption spectroscopy (mobile DOAS) is an optical remote sensing method that can rapidly measure trace gas emission flux from air pollution sources (such as power plants, industrial areas, and cities) in real time. Generally, mobile DOAS is influenced by wind, [...] Read more.
Mobile differential optical absorption spectroscopy (mobile DOAS) is an optical remote sensing method that can rapidly measure trace gas emission flux from air pollution sources (such as power plants, industrial areas, and cities) in real time. Generally, mobile DOAS is influenced by wind, drive velocity, and other factors, especially in the usage of wind field when the emission flux in a mobile DOAS system is observed. This paper presents a detailed error analysis and NOx emission with mobile DOAS system from a power plant in Shijiazhuang city, China. Comparison of the SO2 emission flux from mobile DOAS observations with continuous emission monitoring system (CEMS) under different drive speeds and wind fields revealed that the optimal drive velocity is 30–40 km/h, and the wind field at plume height is selected when mobile DOAS observations are performed. In addition, the total errors of SO2 and NO2 emissions with mobile DOAS measurements are 32% and 30%, respectively, combined with the analysis of the uncertainties of column density, wind field, and drive velocity. Furthermore, the NOx emission of 0.15 ± 0.06 kg/s from the power plant is estimated, which is in good agreement with that from CEMS observations of 0.17 ± 0.07 kg/s. This study has significantly contributed to the measurement of the mobile DOAS system on emission from air pollution sources, thus improving estimation accuracy. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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5191 KiB  
Article
A Modified Magnetic Gradient Contraction Based Method for Ferromagnetic Target Localization
by Chen Wang, Xiaojuan Zhang, Xiaodong Qu, Xiao Pan, Guangyou Fang and Luzhao Chen
Sensors 2016, 16(12), 2168; https://doi.org/10.3390/s16122168 - 17 Dec 2016
Cited by 35 | Viewed by 5854
Abstract
The Scalar Triangulation and Ranging (STAR) method, which is based upon the unique properties of magnetic gradient contraction, is a high real-time ferromagnetic target localization method. Only one measurement point is required in the STAR method and it is not sensitive to changes [...] Read more.
The Scalar Triangulation and Ranging (STAR) method, which is based upon the unique properties of magnetic gradient contraction, is a high real-time ferromagnetic target localization method. Only one measurement point is required in the STAR method and it is not sensitive to changes in sensing platform orientation. However, the localization accuracy of the method is limited by the asphericity errors and the inaccurate value of position leads to larger errors in the estimation of magnetic moment. To improve the localization accuracy, a modified STAR method is proposed. In the proposed method, the asphericity errors of the traditional STAR method are compensated with an iterative algorithm. The proposed method has a fast convergence rate which meets the requirement of high real-time localization. Simulations and field experiments have been done to evaluate the performance of the proposed method. The results indicate that target parameters estimated by the modified STAR method are more accurate than the traditional STAR method. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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5620 KiB  
Article
Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront
by Jingkun Gao, Bin Deng, Yuliang Qin, Hongqiang Wang and Xiang Li
Sensors 2016, 16(12), 2120; https://doi.org/10.3390/s16122120 - 14 Dec 2016
Cited by 12 | Viewed by 5131
Abstract
An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast [...] Read more.
An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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Article
Detection of Multiple Stationary Humans Using UWB MIMO Radar
by Fulai Liang, Fugui Qi, Qiang An, Hao Lv, Fuming Chen, Zhao Li and Jianqi Wang
Sensors 2016, 16(11), 1922; https://doi.org/10.3390/s16111922 - 16 Nov 2016
Cited by 37 | Viewed by 8027
Abstract
Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. [...] Read more.
Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls. Full article
(This article belongs to the Special Issue Advances in Applied Remote Sensing and Decision Making: Transforming Hazard Assessment and Environmental Management)
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