scholarly journals Vehicle Emission Detection in Data-Driven Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zheng He ◽  
Gang Ye ◽  
Hui Jiang ◽  
Youming Fu
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Remote Sensing Data ◽  
Vehicle Emission ◽  
Fuel Type ◽  
Essential Information ◽  
Sensing Technology ◽  
Main Component ◽  
Emission Detection ◽  
Remote Sensing Methods

Environmental protection is a fundamental policy in many countries, where the vehicle emission pollution turns to be outstanding as a main component of pollutions in environmental monitoring. Remote sensing technology has been widely used on vehicle emission detection recently and this is mainly due to the fast speed, reality, and large scale of the detection data retrieved from remote sensing methods. In the remote sensing process, the information about the fuel type and registration time of new cars and nonlocal registered vehicles usually cannot be accessed, leading to the failure in assessing vehicle pollution situations directly by analyzing emission pollutants. To handle this problem, this paper adopts data mining methods to analyze the remote sensing data to predict fuel type and registration time. This paper takes full use of decision tree, random forest, AdaBoost, XgBoost, and their fusion models to successfully make precise prediction for these two essential information and further employ them to an essential application: vehicle emission evaluation.

scholarly journals Monitoring Cyanobacteria Bloom in Dianchi Lake Based on Ground-Based Multispectral Remote-Sensing Imaging: Preliminary Results

2021 ◽  
Vol 13 (19) ◽  
pp. 3970
Author(s):  
Huan Zhao ◽  
Junsheng Li ◽  
Xiang Yan ◽  
Shengzhong Fang ◽  
Yichen Du ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Cyanobacterial Bloom ◽  
Remote Sensing Data ◽  
Cyanobacterial Blooms ◽  
Dynamic Monitoring ◽  
Dianchi Lake ◽  
Sensing Technology ◽  
Multispectral Remote Sensing ◽  
Early Warnings

Some lakes in China have undergone serious eutrophication, with cyanobacterial blooms occurring frequently. Dynamic monitoring of cyanobacterial blooms is important. At present, the traditional lake-survey-based cyanobacterial bloom monitoring is spatiotemporally limited and requires considerable human and material resources. Although satellite remote sensing can rapidly monitor large-scale cyanobacterial blooms, clouds and other factors often mean that effective images cannot be obtained. It is also difficult to use this method to dynamically monitor and manage aquatic environments and provide early warnings of cyanobacterial blooms in lakes and reservoirs. In contrast, ground-based remote sensing can operate under cloud cover and thus act as a new technical method to dynamically monitor cyanobacterial blooms. In this study, ground-based remote-sensing technology was applied to multitemporal, multidirectional, and multiscene monitoring of cyanobacterial blooms in Dianchi Lake via an area array multispectral camera mounted on a rotatable cloud platform at a fixed station. Results indicate that ground-based imaging remote sensing can accurately reflect the spatiotemporal distribution characteristics of cyanobacterial blooms and provide timely and accurate data for salvage treatment and early warnings. Thus, ground-based multispectral remote-sensing data can operationalize the dynamic monitoring of cyanobacterial blooms. The methods and results from this study can provide references for monitoring such blooms in other lakes.

scholarly journals STUDY ON VORTEX CURRENT IN STRAIT WITH REMOTE-SENSING

1980 ◽  
Vol 1 (17) ◽  
pp. 157 ◽  
Author(s):  
Sotoaki Onishi ◽  
Tsukasa Nishimura
Keyword(s):  
Water Pollution ◽  
Remote Sensing ◽  
Boundary Conditions ◽  
Mathematical Models ◽  
Large Scale ◽  
Sea Water ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Sensing Technology ◽  
Pollution Problem

With rapid increases of industrial activity in present time, water pollution in the coastal environment has "become an urgent problem to cope with. This problem is especially serious in enclosed bays or inland seas. Hydrodynamic character of the strait connecting the inland sea to the open ocean must be understood well in order to analyse the diffusion of pollutants in the Inland sea, because its character determine boundary conditions in the mathematical models of the water pollution problem. So far however, it is seemed that the main efforts exerted by coastal engineers have concentrated mainly on the development of mathematical models, lacking satisfactory knowledge of the boundary conditions through field measurements. One reason of this state is resulted from the fact that the relating phenomena in the field are of too large scale, in general, to perform the field measurements. Connecting with this point, the authors present in this paper, that remote-sensing technology is very useful to get information of the hydrodynaniical phenomena occurring in the water body around the strait. To show the above, the authors selected as an object of the study , Naruto Strait in the Seto Inland Sea, which is world famous for the existence of rapid tidal currents and dynamic vortices. Remote-sensing data both from the airplanes and from a space satellite Landsat are analysed with the aid of theoretical considerations and hydraulic mo-del tests to disclose the behavior of the vortices of various scales and the roles of them in the sea water mixing phenomena at the strait.

The Importance of Minimally Invasive Remote Sensing Methods in Huron-Wendat Archaeology

2021 ◽  
pp. 1-12
Author(s):  
Gary Warrick ◽  
Bonnie Glencross ◽  
Louis Lesage
Keyword(s):  
Remote Sensing ◽  
Minimally Invasive ◽  
Soil Chemistry ◽  
Large Scale ◽  
Archaeological Sites ◽  
Archaeological Excavation ◽  
Metal Detector ◽  
Essential Information ◽  
Land Disturbance ◽  
Remote Sensing Methods

Abstract The Huron-Wendat have had their ancestors’ villages and burial sites investigated archaeologically for over 170 years. Past and ongoing land disturbance and invasive archaeological excavation have erased dozens of Huron-Wendat village sites in Ontario, hindering Huron-Wendat duty to care for their ancestors. Consequently, over the last 20 years, in addition to large-scale repatriation of ancestral remains, the Huron-Wendat have requested that archaeologists make every effort to avoid any further excavation of ancestral sites. This poses a new challenge for archaeologists about how to learn about the Huron-Wendat past with minimal disturbance to ancestral sites. Honoring the cultural responsibilities of the Huron-Wendat, the authors have employed minimally invasive remote sensing methods of investigation on Ahatsistari, a forested early seventeenth-century Huron-Wendat village site in Simcoe County, Ontario. Remote sensing methods (e.g., magnetic susceptibility survey, high-resolution soil chemistry sampling, and metal detector survey) have revealed village limits and the possible location and orientation of longhouses, providing essential information in support of the Huron-Wendat imperative to find, assess, and preserve as many of their archaeological sites as possible. This is to protect the ancestors, learn from the ancestors, and preserve ancestral sites and related landscapes for future generations.

scholarly journals Using integrated remote sensing methods in the Nagyerdő Natura 2000 area

2014 ◽  
pp. 19-24
Author(s):  
Éva Bozsik ◽  
Tünde Fórián ◽  
Balázs Deák ◽  
Péter Riczu ◽  
János Fehér ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Monitoring System ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Natura 2000 ◽  
Airborne Lidar ◽  
Sensing Technology ◽  
Data Collecting ◽  
Collecting Methods ◽  
Remote Sensing Methods

The more widely use of GIS, remote sensing technology provides appropriate data acquisition and data processing tools to build several national and international biodiversity monitoring system of environmental protection and natur conservation. The ChangeHabitats 2 is a similar international project, which uses airborne hyperspectral and airborne laser scanning (airborne LiDAR) sources beyond traditional data collection methods to build a monitoring system of Natura 2000 habitats. The goal of our research, on one hand, was to separate the most typical species of trees which can be found in the largest coverage in the research plots of Debreceni Nagyerdő Nature Reserve from field and airborne remote sensing data, use image classification that based on spectral and geometry (height) characteristics of the trees. On the other hand our goal was to evaluate the efficient use of the integration of mobilGIS, airborne hyperspectral and airborne LiDAR data collecting methods to complement or substitut of the traditional, field data collecting methods. We used ArcGIS 10.2 and Exelis 5.0 GIS software for data evaluation, in which the mosaicing, the selection of plots and the spectral image processing were carried out.

Identification of Potentially Unmanageable Ice Features

2017 ◽  
Author(s):  
Svetlana Shafrova ◽  
Dmitri Matskevitch ◽  
Curtis Holub ◽  
Ted Kokkinis
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Near Field ◽  
Remote Sensing Data ◽  
Data Interpretation ◽  
Dual Frequency ◽  
Sensing Technology ◽  
Field Reconnaissance ◽  
Remote Sensing Systems ◽  
Remote Sensing Methods

Satellite remote sensing technology plays an important role in ice monitoring and characterization in support of ice management operations for Arctic floating drilling that previously have been described by industry to include three stages: (1) far-field reconnaissance for potentially unmanageable ice features (2) mid-field verification of ice breakability and (3) near-field ice floe size reduction. The paper discusses the application of satellite remote sensing methods for identification of Potentially Unmanageable Ice Features (PUIF) as well as challenges associated with satellite data interpretation and feature tracking. Examples of PUIF identification using both publicly and commercially available satellite imagery and other remote sensing data collected during the Oden Arctic Technology Research Cruise 2015 (OATRC 2015) are presented and the challenges with the PUIF detection and monitoring are discussed. In addition, airborne remote sensing systems for PUIF identification, both existing (such as Electromagnetic Induction (EMI)) and under development (such as dual frequency radar, multi-band synthetic aperture radar), are discussed and their capabilities contrasted and compared to satellite-based methods. Furthermore, potential ways of optimally combining airborne and satellite remote sensing are proposed.

LAI Retrieval Based on PROSPECT-SAILH Model from Multi-Angular Data of WiDAS Imaging System

2012 ◽  
Vol 518-523 ◽  
pp. 5697-5703
Author(s):  
Zhao Yan Liu ◽  
Ling Ling Ma ◽  
Ling Li Tang ◽  
Yong Gang Qian
Keyword(s):  
Remote Sensing ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Canopy Reflectance ◽  
Area Index ◽  
Sensing Data ◽  
Spectral Bands ◽  
Sensing Technology ◽  
Leaf Optical Properties ◽  
Angular Data

The aim of this study is to assess the capability of estimating Leaf Area Index (LAI) from high spatial resolution multi-angular Vis-NIR remote sensing data of WiDAS (Wide-Angle Infrared Dual-mode Line/Area Array Scanner) imaging system by inverting the coupled radiative transfer models PROSPECT-SAILH. Based on simulations from SAILH canopy reflectance model and PROSPECT leaf optical properties model, a Look-up Table (LUT) which describes the relationship between multi-angular canopy reflectance and LAI has been produced. Then the LAI can be retrieved from LUT by directly matching canopy reflectance of six view directions and four spectral bands with LAI. The inversion results are validated by field data, and by comparing the retrieval results of single-angular remote sensing data with multi-angular remote sensing data, we can found that the view angle takes the obvious impact on the LAI retrieval of single-angular data and that high accurate LAI can be obtained from the high resolution multi-angular remote sensing technology.

LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes

2019 ◽  
Vol 221 ◽  
pp. 695-706 ◽  
Author(s):  
Jianbo Qi ◽  
Donghui Xie ◽  
Tiangang Yin ◽  
Guangjian Yan ◽  
Jean-Philippe Gastellu-Etchegorry ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Remote Sensing Data ◽  
Image Simulation ◽  
Simulation Framework ◽  
Sensing Data

scholarly journals Forest areas remote monitoring within the limits of transport objects impact

2021 ◽  
pp. 109-118
Author(s):  
Dmytro Liashenko ◽  
◽  
Dmytro Pavliuk ◽  
Vadym Belenok ◽  
Vitalii Babii ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Remote Monitoring ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Remote Sensing Data ◽  
Transport Infrastructure ◽  
Nature Management ◽  
Collecting Methods ◽  
Remote Sensing Methods

The article studies the issues of using remote sensing data for the tasks of ensuring sustainable nature management in the territories within the influence of transport infrastructure objects. Peculiarities of remote monitoring for tasks of transport networks design and in the process of their operation are determined. The paper analyzes the development of modern remote sensing methods (satellite imagery, the use of mobile sensors installed on cars or aircraft). A brief overview of spatial data collecting methods for the tasks of managing the development of territories within the influence of transport infrastructure (roads, railways, etc.) has made. The article considers the experience of using remote sensing technologies to monitor changes in the parameters of forest cover in the Transcarpathian region (Ukraine) in areas near to highways, by use Landsat imagery.

scholarly journals Automatic calibration of a large-scale sediment model using suspended sediment concentration, water quality, and remote sensing data

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Hugo de Oliveira Fagundes ◽  
Fernando Mainardi Fan ◽  
Rodrigo Cauduro Dias de Paiva
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Suspended Sediment ◽  
Large Scale ◽  
Suspended Sediment Concentration ◽  
Remote Sensing Data ◽  
Sediment Concentration ◽  
Spatial Discretization ◽  
Calibration And Validation ◽  
Sediment Model

ABSTRACT Calibration and validation are two important steps in the application of sediment models requiring observed data. This study aims to investigate the potential use of suspended sediment concentration (SSC), water quality and remote sensing data to calibrate and validate a large-scale sediment model. Observed data from across 108 stations located in the Doce River basin was used for the period between 1997-2010. Ten calibration and validation experiments using the MOCOM-UA optimization algorithm coupled with the MGB-SED model were carried out, which, over the same period of time, resulted in 37 calibration and 111 validation tests. The experiments were performed by modifying metrics, spatial discretization, observed data and parameters of the MOCOM-UA algorithm. Results generally demonstrated that the values of correlation presented slight variations and were superior in the calibration step. Additionally, increasing spatial discretization or establishing a background concentration for the model allowed for improved results. In a station with high quantity of SSC data, calibration improved the ENS coefficient from -0.44 to 0.44. The experiments showed that the spectral surface reflectance, total suspended solids and turbidity data have the potential to enhance the performance of sediment models.

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