GNSS remote sensing theory, methods and applications

CERN Document Server

Jin, Shuanggen; Xie, Feiqin

2014-01-01

This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. It contains detailed theory and study cases to help the reader put the material into practice.

Methods of training the graduate level and professional geologist in remote sensing technology

Science.gov (United States)

Kolm, K. E.

1981-01-01

Requirements for a basic course in remote sensing to accommodate the needs of the graduate level and professional geologist are described. The course should stress the general topics of basic remote sensing theory, the theory and data types relating to different remote sensing systems, an introduction to the basic concepts of computer image processing and analysis, the characteristics of different data types, the development of methods for geological interpretations, the integration of all scales and data types of remote sensing in a given study, the integration of other data bases (geophysical and geochemical) into a remote sensing study, and geological remote sensing applications. The laboratories should stress hands on experience to reinforce the concepts and procedures presented in the lecture. The geologist should then be encouraged to pursue a second course in computer image processing and analysis of remotely sensed data.

Evaluation of Clear-Sky Incoming Radiation Estimating Equations Typically Used in Remote Sensing Evapotranspiration Algorithms

Directory of Open Access Journals (Sweden)

Ted W. Sammis

2013-09-01

Full Text Available Net radiation is a key component of the energy balance, whose estimation accuracy has an impact on energy flux estimates from satellite data. In typical remote sensing evapotranspiration (ET algorithms, the outgoing shortwave and longwave components of net radiation are obtained from remote sensing data, while the incoming shortwave (RS and longwave (RL components are typically estimated from weather data using empirical equations. This study evaluates the accuracy of empirical equations commonly used in remote sensing ET algorithms for estimating RS and RL radiation. Evaluation is carried out through comparison of estimates and observations at five sites that represent different climatic regions from humid to arid. Results reveal (1 both RS and RL estimates from all evaluated equations well correlate with observations (R2 ≥ 0.92, (2 RS estimating equations tend to overestimate, especially at higher values, (3 RL estimating equations tend to give more biased values in arid and semi-arid regions, (4 a model that parameterizes the diffuse component of radiation using two clearness indices and a simple model that assumes a linear increase of atmospheric transmissivity with elevation give better RS estimates, and (5 mean relative absolute errors in the net radiation (Rn estimates caused by the use of RS and RL estimating equations varies from 10% to 22%. This study suggests that Rn estimates using recommended incoming radiation estimating equations could improve ET estimates.

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

International Nuclear Information System (INIS)

Martin, William G.K.; Hasekamp, Otto P.

2018-01-01

Highlights: • We demonstrate adjoint methods for atmospheric remote sensing in a two-dimensional setting. • Searchlight functions are used to handle the singularity of measurement response functions. • Adjoint methods require two radiative transfer calculations to evaluate the measurement misfit function and its derivatives with respect to all unknown parameters. • Synthetic retrieval studies show the scalability of adjoint methods to problems with thousands of measurements and unknown parameters. • Adjoint methods and the searchlight function technique are generalizable to 3D remote sensing. - Abstract: In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.

Science.gov (United States)

Zheng, Guang; Moskal, L Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.

Remote sensing image ship target detection method based on visual attention model

Science.gov (United States)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

Sensing our Environment: Remote sensing in a physics classroom

Science.gov (United States)

Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit

2017-04-01

Remote sensing is defined as data acquisition of an object, deprived physical contact. Fundamentally, most remote sensing applications are referred to as the use of satellite- or aircraft-based sensor technologies to detect and classify objects mainly on Earth or other planets. In the last years there have been efforts to bring the important subject of remote sensing into schools, however, most of these attempts focused on geography disciplines - restricting to the applications of remote sensing and to a less extent the technique itself and the physics behind it. Optical remote sensing is based on physical principles and technical devices, which are very meaningful from a theoretical point of view as well as for "hands-on" teaching. Some main subjects are radiation, atom and molecular physics, spectroscopy, as well as optics and the semiconductor technology used in modern digital cameras. Thus two objectives were outlined for this project: 1) to investigate the possibilities of using remote sensing techniques in physics teaching, and 2) to identify its impact on pupil's interest in the field of natural sciences. This joint project of the DLR_School_Lab, Oberpfaffenhofen of the German Aerospace Center (DLR) and the Earth and Planetary Image Facility (EPIF) at BGU, was conducted in 2016. Thirty teenagers (ages 16-18) participated in the project and were exposed to the cutting edge methods of earth observation. The pupils on both sides participated in the project voluntarily, knowing that at least some of the project's work had to be done in their leisure time. The pupil's project started with a day at EPIF and DLR respectively, where the project task was explained to the participants and an introduction to remote sensing of vegetation was given. This was realized in lectures and in experimental workshops. During the following two months both groups took several measurements with modern optical remote sensing systems in their home region with a special focus on flora

Remote Sensing

CERN Document Server

Khorram, Siamak; Koch, Frank H; van der Wiele, Cynthia F

2012-01-01

Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns. It explains the role of this new technology in current global challenges. "Remote Sensing" will discuss remotely sensed data application payloads and platforms, along with the methodologies involving image processing techniques as applied to remotely sensed data. This title provides information on image classification techniques and image registration, data integration, and data fusion techniques. How this technology applies to natural resources and environmental concerns will also be discussed.

Coalfire related CO2 emissions and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Gangopadhyay, P.K.

2008-06-11

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Coalfires related CO2 emissions and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Gangopadhyay, P.K.

2008-06-11

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Coalfire related CO2 emissions and remote sensing

International Nuclear Information System (INIS)

Gangopadhyay, P.K.

2008-01-01

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

Science.gov (United States)

Ben-David, Avishai; Davidson, Charles E

2012-04-23

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

Remote sensing of suspended sediment water research: principles, methods, and progress

Science.gov (United States)

Shen, Ping; Zhang, Jing

2011-12-01

In this paper, we reviewed the principle, data, methods and steps in suspended sediment research by using remote sensing, summed up some representative models and methods, and analyzes the deficiencies of existing methods. Combined with the recent progress of remote sensing theory and application in water suspended sediment research, we introduced in some data processing methods such as atmospheric correction method, adjacent effect correction, and some intelligence algorithms such as neural networks, genetic algorithms, support vector machines into the suspended sediment inversion research, combined with other geographic information, based on Bayesian theory, we improved the suspended sediment inversion precision, and aim to give references to the related researchers.

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

Science.gov (United States)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

Subsurface remote sensing

International Nuclear Information System (INIS)

Schweitzer, Jeffrey S.; Groves, Joel L.

2002-01-01

Subsurface remote sensing measurements are widely used for oil and gas exploration, for oil and gas production monitoring, and for basic studies in the earth sciences. Radiation sensors, often including small accelerator sources, are used to obtain bulk properties of the surrounding strata as well as to provide detailed elemental analyses of the rocks and fluids in rock pores. Typically, instrument packages are lowered into a borehole at the end of a long cable, that may be as long as 10 km, and two-way data and instruction telemetry allows a single radiation instrument to operate in different modes and to send the data to a surface computer. Because these boreholes are often in remote locations throughout the world, the data are frequently transmitted by satellite to various locations around the world for almost real-time analysis and incorporation with other data. The complete system approach that permits rapid and reliable data acquisition, remote analysis and transmission to those making decisions is described

Space remote sensing systems an introduction

CERN Document Server

Chen, H S

1985-01-01

Space Remote Sensing Systems: An Introduction discusses the space remote sensing system, which is a modern high-technology field developed from earth sciences, engineering, and space systems technology for environmental protection, resource monitoring, climate prediction, weather forecasting, ocean measurement, and many other applications. This book consists of 10 chapters. Chapter 1 describes the science of the atmosphere and the earth's surface. Chapter 2 discusses spaceborne radiation collector systems, while Chapter 3 focuses on space detector and CCD systems. The passive space optical rad

Remote sensing of natural phenomena

Directory of Open Access Journals (Sweden)

Miodrag D. Regodić

2014-06-01

Full Text Available There has always been a need to directly perceive and study the events whose extent is beyond people's possibilities. In order to get new data and to make observations and studying much more objective in comparison with past syntheses - a new method of examination called remote sensing has been adopted. The paper deals with the principles and elements of remote sensing, as well as with the basic aspects of using remote research in examining meteorological (weather parameters and the conditions of the atmosphere. The usage of satellite images is possible in all phases of the global and systematic research of different natural phenomena when airplane and satellite images of different characteristics are used and their analysis and interpretation is carried out by viewing and computer added procedures. Introduction Remote sensing of the Earth enables observing and studying global and local events that occur on it. Satellite images are nowadays used in geology, agriculture, forestry, geodesy, meteorology, spatial and urbanism planning, designing of infrastructure and other objects, protection from natural and technological catastrophes, etc. It it possible to use satellite images in all phases of global and systematic research of different natural phenomena. Basics of remote sensing Remote sensing is a method of the acquisition and interpretation of information about remote objects without making a physical contact with them. The term Daljinska detekcija is a literal translation of the English term Remote Sensing. In French it isTeledetection, in German - Fernerkundung, in Russian - дистанционие иследования. We also use terms such as: remote survailance, remote research, teledetection, remote methods, and distance research. The basic elements included in Remote Sensing are: object, electromagnetic energy, sensor, platform, image, analysis, interpretation and the information (data, fact. Usage of satellite remote research in

Estimating actual evapotranspiration from remote sensing imagery using R: the package 'TriangleMethod'.

Science.gov (United States)

Gampe, David; Huber García, Verena; Marzahn, Philip; Ludwig, Ralf

2017-04-01

Actual evaporation (Eta) is an essential variable to assess water availability, drought risk and food security, among others. Measurements of Eta are however limited to a small footprint, hampering a spatially explicit analysis and application and are very often not available at all. To overcome the problem of data scarcity, Eta can be assessed by various remote sensing approaches such as the Triangle Method (Jiang & Islam, 1999). Here, Eta is estimated by using the Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST). In this study, the R-package 'TriangleMethod' was compiled to efficiently perform the calculations of NDVI and processing LST to finally derive Eta from the applied data set. The package contains all necessary calculation steps and allows easy processing of a large data base of remote sensing images. By default, the parameterization for the Landsat TM and ETM+ sensors are implemented, however, the algorithms can be easily extended to additional sensors. The auxiliary variables required to estimate Eta with this method, such as elevation, solar radiation and air temperature at the overpassing time, can be processed as gridded information to allow for a better representation of the study area. The package was successfully applied in various studies in Spain, Palestine, Costa Rica and Canada.

Advances in estimation methods of vegetation water content based on optical remote sensing techniques

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

Research on active imaging information transmission technology of satellite borne quantum remote sensing

Science.gov (United States)

Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

Thermal infrared remote sensing sensors, methods, applications

CERN Document Server

Kuenzer, Claudia

2013-01-01

This book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techni

Choice of Eye-Safe Radiation Wavelength in UV and Near IR Spectral Bands for Remote Sensing

OpenAIRE

M. L. Belov; V. A. Gorodnichev; D. A. Kravtsov; A. A. Cherpakova

2016-01-01

The introduction of laser remote sensing systems carries a particular risk to the human’s sense of vision. A structure of the eye, and especially the retina, is the main critical organ as related to the laser radiation.The work uses the optical models of the atmosphere, correctly working in both the UV and the near-IR band, to select the eye-safe radiation wavelengths in the UV (0.355 m) and near-IR (~ 1.54 and ~ 2 m) spectral bands from the point of view of recorded lidar signal value to ful...

Remote sensing image fusion

CERN Document Server

Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

2015-01-01

A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

Science.gov (United States)

Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan

2016-01-01

Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...

Remote sensing of coral reefs and their physical environment

International Nuclear Information System (INIS)

Mumby, Peter J.; Skirving, William; Strong, Alan E.; Hardy, John T.; LeDrew, Ellsworth F.; Hochberg, Eric J.; Stumpf, Rick P.; David, Laura T.

2004-01-01

There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas

Remote sensing of coral reefs and their physical environment

Energy Technology Data Exchange (ETDEWEB)

Mumby, Peter J.; Skirving, William; Strong, Alan E.; Hardy, John T.; LeDrew, Ellsworth F.; Hochberg, Eric J.; Stumpf, Rick P.; David, Laura T

2004-02-01

There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas.

Current perspective on remote sensing

International Nuclear Information System (INIS)

Goodman, R.H.

1992-01-01

Surveillance and tracking of oil spills has been a feature of most spill response situations for many years. The simplest and most direct method uses visual observations from an aircraft and hand-plotting of the data on a map. This technique has proven adequate for most small spills and for responses in fair weather. As the size of the spill increases or the weather deteriorates, there is a need to augment visual aerial observations with remote sensing methods. Remote sensing and its associated systems are one of the most technically complex and sophisticated elements of an oil spill response. During the past few years, a number of initiatives have been undertaken to use contemporary electronic and computing systems to develop new and improved remote sensing systems

Mississippi Sound Remote Sensing Study

Science.gov (United States)

Atwell, B. H.

1973-01-01

The Mississippi Sound Remote Sensing Study was initiated as part of the research program of the NASA Earth Resources Laboratory. The objective of this study is development of remote sensing techniques to study near-shore marine waters. Included within this general objective are the following: (1) evaluate existing techniques and instruments used for remote measurement of parameters of interest within these waters; (2) develop methods for interpretation of state-of-the-art remote sensing data which are most meaningful to an understanding of processes taking place within near-shore waters; (3) define hardware development requirements and/or system specifications; (4) develop a system combining data from remote and surface measurements which will most efficiently assess conditions in near-shore waters; (5) conduct projects in coordination with appropriate operating agencies to demonstrate applicability of this research to environmental and economic problems.

Choice of Eye-Safe Radiation Wavelength in UV and Near IR Spectral Bands for Remote Sensing

Directory of Open Access Journals (Sweden)

M. L. Belov

2016-01-01

Full Text Available The introduction of laser remote sensing systems carries a particular risk to the human’s sense of vision. A structure of the eye, and especially the retina, is the main critical organ as related to the laser radiation.The work uses the optical models of the atmosphere, correctly working in both the UV and the near-IR band, to select the eye-safe radiation wavelengths in the UV (0.355 m and near-IR (~ 1.54 and ~ 2 m spectral bands from the point of view of recorded lidar signal value to fulfill the tasks of laser sensing the natural formations and laser aerosol sensing in the atmosphere.It is shown that the remote sensing lasers with appropriate characteristics can be selected both in the UV band (at a wavelength of 0.355 μm and in the near-IR band (at wavelengths of 1.54 ~ or ~ 2 μm.Molecular scattering has its maximum (for the selected wavelength at a wavelength of 0.355 μm in the UV band, and the minimum at the wavelengths of 1.54 and 2.09 μm in the near -IR band. The main contribution to the molecular absorption at a wavelength of 0.355 μm is made by ozone. In the near-IR spectral band the radiation is absorbed due to water vapor and carbon dioxide.Calculations show that the total effect of the molecular absorption and scattering has no influence on radiation transmission for both the wavelength of 0.355 μm in the UV band, and the wavelengths of 1.54 and 2.09 μm in the near-IR band for sensing trails ~ 1 km.One of the main factors of laser radiation attenuation in the Earth's atmosphere is radiation scattering by aerosol particles.The results of calculations at wavelengths of 0.355 μm, 1.54 μm and 2.09 μm for the several models of the atmosphere show that a choice of the most effective (in terms of the recorded signal of lidar and eye-safe radiation wavelength depends strongly on the task of sensing.To fulfill the task of laser sensing the natural formations, among the eye-safe wavelengths there is one significantly advantageous

A Remote Sensing Image Fusion Method based on adaptive dictionary learning

Science.gov (United States)

He, Tongdi; Che, Zongxi

2018-01-01

This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

Evaluation and application of passive and active optical remote sensing methods for the measurement of atmospheric aerosol properties

Energy Technology Data Exchange (ETDEWEB)

Mielonen, T.

2010-07-01

Atmospheric aerosol particles affect the atmosphere's radiation balance by scattering and absorbing sunlight. Moreover, the particles act as condensation nuclei for clouds and affect their reflectivity. In addition, aerosols have negative health effects and they reduce visibility. Aerosols are emitted into the atmosphere from both natural and anthropogenic sources. Different types of aerosols have different effects on the radiation balance, thus global monitoring and typing of aerosols is of vital importance. In this thesis, several remote sensing methods used in the measurement of atmospheric aerosols are evaluated. Remote sensing of aerosols can be done with active and passive instruments. Passive instruments measure radiation emitted by the sun and the Earth while active instruments have their own radiation source, for example a black body radiator or laser. The instruments utilized in these studies were sun photometers (PFR, Cimel), lidars (POLLYXT, CALIOP), transmissiometer (OLAF) and a spectroradiometer (MODIS). Retrieval results from spaceborne instruments (MODIS, CALIOP) were evaluated with ground based measurements (PFR, Cimel). In addition, effects of indicative aerosol model assumptions on the calculated radiative transfer were studied. Finally, aerosol particle mass at the ground level was approximated from satellite measurements and vertical profiles of aerosols measured with a lidar were analyzed. For the evaluation part, these studies show that the calculation of aerosol induced attenuation of radiation based on aerosol size distribution measurements is not a trivial task. In addition to dry aerosol size distribution, the effect of ambient relative humidity on the size distribution and the optical properties of the aerosols need to be known in order to achieve correct results from the calculations. Furthermore, the results suggest that aerosol size parameters retrieved from passive spaceborne measurements depend heavily on surgace reflectance

A change detection method for remote sensing image based on LBP and SURF feature

Science.gov (United States)

Hu, Lei; Yang, Hao; Li, Jin; Zhang, Yun

2018-04-01

Finding the change in multi-temporal remote sensing image is important in many the image application. Because of the infection of climate and illumination, the texture of the ground object is more stable relative to the gray in high-resolution remote sensing image. And the texture features of Local Binary Patterns (LBP) and Speeded Up Robust Features (SURF) are outstanding in extracting speed and illumination invariance. A method of change detection for matched remote sensing image pair is present, which compares the similarity by LBP and SURF to detect the change and unchanged of the block after blocking the image. And region growing is adopted to process the block edge zone. The experiment results show that the method can endure some illumination change and slight texture change of the ground object.

Remote sensing models and methods for image processing

CERN Document Server

Schowengerdt, Robert A

2007-01-01

Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

Scale issues in remote sensing

CERN Document Server

Weng, Qihao

2014-01-01

This book provides up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. The book is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as a supplemental reading for graduate level students.

Introduction to remote sensing

CERN Document Server

Cracknell, Arthur P

2007-01-01

Addressing the need for updated information in remote sensing, Introduction to Remote Sensing, Second Edition provides a full and authoritative introduction for scientists who need to know the scope, potential, and limitations in the field. The authors discuss the physical principles of common remote sensing systems and examine the processing, interpretation, and applications of data. This new edition features updated and expanded material, including greater coverage of applications from across earth, environmental, atmospheric, and oceanographic sciences. Illustrated with remotely sensed colo

Research on remote sensing image pixel attribute data acquisition method in AutoCAD

Science.gov (United States)

Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui

2013-07-01

The remote sensing image has been widely used in AutoCAD, but AutoCAD lack of the function of remote sensing image processing. In the paper, ObjectARX was used for the secondary development tool, combined with the Image Engine SDK to realize remote sensing image pixel attribute data acquisition in AutoCAD, which provides critical technical support for AutoCAD environment remote sensing image processing algorithms.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

Science.gov (United States)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Study on Method of Geohazard Change Detection Based on Integrating Remote Sensing and GIS

International Nuclear Information System (INIS)

Zhao, Zhenzhen; Yan, Qin; Liu, Zhengjun; Luo, Chengfeng

2014-01-01

Following a comprehensive literature review, this paper looks at analysis of geohazard using remote sensing information. This paper compares the basic types and methods of change detection, explores the basic principle of common methods and makes an respective analysis of the characteristics and shortcomings of the commonly used methods in the application of geohazard. Using the earthquake in JieGu as a case study, this paper proposes a geohazard change detection method integrating RS and GIS. When detecting the pre-earthquake and post-earthquake remote sensing images at different phases, it is crucial to set an appropriate threshold. The method adopts a self-adapting determination algorithm for threshold. We select a training region which is obtained after pixel information comparison and set a threshold value. The threshold value separates the changed pixel maximum. Then we apply the threshold value to the entire image, which could also make change detection accuracy maximum. Finally, we output the result to the GIS system to make change analysis. The experimental results show that this method of geohazard change detection based on integrating remote sensing and GIS information has higher accuracy with obvious advantages compared with the traditional methods

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery.

Science.gov (United States)

Qi, Baogui; Shi, Hao; Zhuang, Yin; Chen, He; Chen, Liang

2018-04-25

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery

Science.gov (United States)

Qi, Baogui; Zhuang, Yin; Chen, He; Chen, Liang

2018-01-01

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited. PMID:29693585

Optical remote sensing

CERN Document Server

Prasad, Saurabh; Chanussot, Jocelyn

2011-01-01

Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data: challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, patter

Remote sensing of potential and actual daily transpiration of plant canopies based on spectral reflectance and infrared thermal measurements: Concept with preliminary test

International Nuclear Information System (INIS)

Inoue, Y.; Moran, M.S.; Pinter, P.J.Jr.

1994-01-01

A new concept for estimating potential and actual values of daily transpiration rate of vegetation canopies is presented along with results of an initial test. The method is based on a physical foundation of spectral radiation balance for a vegetation canopy, the key inputs to the model being the remotely sensed spectral reflectance and the surface temperature of the plant canopy. The radiation interception or absorptance is estimated more directly from remotely sensed spectral data than it is from the leaf area index. The potential daily transpiration is defined as a linear function of the absorbed solar radiation, which can be estimated using a linear relationship between the fraction absorptance of solar radiation and the remotely sensed Soil Adjusted Vegetation Index for the canopy. The actual daily transpiration rate is estimated by combining this concept with the Jackson-Idso Crop Water Stress Index, which also can be calculated from remotely sensed plant leaf temperatures measured by infrared thermometry. An initial demonstration with data sets from an alfalfa crop and a rangeland suggests that the method may give reasonable estimates of potential and actual values of daily transpiration rate over diverse vegetation area based on simple remote sensing measurements and basic meteorological parameters

Combining the Pixel-based and Object-based Methods for Building Change Detection Using High-resolution Remote Sensing Images

Directory of Open Access Journals (Sweden)

ZHANG Zhiqiang

2018-01-01

Full Text Available Timely and accurate change detection of buildings provides important information for urban planning and management.Accompanying with the rapid development of satellite remote sensing technology,detecting building changes from high-resolution remote sensing images have received wide attention.Given that pixel-based methods of change detection often lead to low accuracy while object-based methods are complicated for uses,this research proposes a method that combines pixel-based and object-based methods for detecting building changes from high-resolution remote sensing images.First,based on the multiple features extracted from the high-resolution images,a random forest classifier is applied to detect changed building at the pixel level.Then,a segmentation method is applied to segement the post-phase remote sensing image and to get post-phase image objects.Finally,both changed building at the pixel level and post-phase image objects are fused to recognize the changed building objects.Multi-temporal QuickBird images are used as experiment data for building change detection with high-resolution remote sensing images,the results indicate that the proposed method could reduce the influence of environmental difference,such as light intensity and view angle,on building change detection,and effectively improve the accuracies of building change detection.

Benchmarking of Remote Sensing Segmentation Methods

Czech Academy of Sciences Publication Activity Database

Mikeš, Stanislav; Haindl, Michal; Scarpa, G.; Gaetano, R.

2015-01-01

Roč. 8, č. 5 (2015), s. 2240-2248 ISSN 1939-1404 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : benchmark * remote sensing segmentation * unsupervised segmentation * supervised segmentation Subject RIV: BD - Theory of Information Impact factor: 2.145, year: 2015 http://library.utia.cas.cz/separaty/2015/RO/haindl-0445995.pdf

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

Science.gov (United States)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing

Economic optimization and evolutionary programming when using remote sensing data

OpenAIRE

Shamin Roman; Alberto Gabriel Enrike; Uryngaliyeva Ayzhana; Semenov Aleksandr

2018-01-01

The article considers the issues of optimizing the use of remote sensing data. Built a mathematical model to describe the economic effect of the use of remote sensing data. It is shown that this model is incorrect optimisation task. Given a numerical method of solving this problem. Also discusses how to optimize organizational structure by using genetic algorithm based on remote sensing. The methods considered allow the use of remote sensing data in an optimal way. The proposed mathematical m...

Remote sensing and resource exploration

International Nuclear Information System (INIS)

El-Baz, F.; Hassan, M.H.A.; Cappellini, V.

1989-01-01

The purpose of the Workshop was to study in depth the application of remote sensing technology to the fields of archaeology, astronomy, geography, geology, and physics. Some emphasis was placed on utilizing remote sensing methods and techniques in the search for water, mineral and land resources. The Workshop was attended by 90 people from 35 countries. The proceedings of this meeting includes 15 papers, 12 of them have a separate abstract in the INIS Database. Refs, figs and tabs

Measurement of rain intensity by means of active-passive remote sensing

Science.gov (United States)

Linkova, Anna; Khlopov, Grygoriy

2014-05-01

Measurement of rain intensity is of great interest for municipal services and agriculture, particularly because of increasing number of floods and landslides. At that monitoring of amount of liquid precipitation allows to schedule work of hydrological services to inform the relevant public authorities about violent weather in time. That is why development of remote sensing methods for monitoring of rains is quite important task. The inverse problem solution of rain remote sensing is based on the measurements of scattering or radiation characteristics of rain drops. However liquid precipitation has a difficult structure which depends on many parameters. So using only scattering or radiation characteristics obtained by active and passive sensing at a single frequency does not allow to solve the inverse problem. Therefore double frequency sensing is widely used now for precipitation monitoring. Measurement of reflected power at two frequencies allows to find two parameters of drop size distribution of rain drops. However three-parameter distributions (for example gamma distribution) are the most prevalent now as a rain model, so in this case solution of the inverse problem requires the measurement of at least three uncorrelated variables. That is why a priori statistical meteorological data obtained by contact methods are used additionally to the double frequency sensing to solve the inverse problem. In particular, authors proposed and studied the combined method of double frequency sensing of rains based on dependence of the parameters of gamma distribution on rain intensity. The numerical simulation and experimental study shown that the proposed method allows to retrieve the profile of microstructure and integral parameters of rain with accuracy less than 15%. However, the effectiveness of the proposed method essentially depends on the reliability of the used statistical data which are tend to have a strong seasonal and regional variability led to significant

Development and Testing of Physically-Based Methods for Filling Gaps in Remotely Sensed River Data

Science.gov (United States)

2011-09-30

Filling Gaps in Remotely Sensed River Data Jonathan M. Nelson US Geological Survey National Research Program Geomorphology and Sediment Transport...the research work carried out under this grant are to develop and test two methods for filling in gaps in remotely sensed river data. The first...information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215

Advanced Remote Sensing Research

Science.gov (United States)

Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna

2008-01-01

'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).

Progress in Analysis to Remote Sensed Thermal Abnormity with Fault Activity and Seismogenic Process

Directory of Open Access Journals (Sweden)

WU Lixin

2017-10-01

Full Text Available Research to the remote sensed thermal abnormity with fault activity and seismogenic process is a vital topic of the Earth observation and remote sensing application. It is presented that a systematic review on the international researches on the topic during the past 30 years, in the respects of remote sensing data applications, anomaly analysis methods, and mechanism understanding. Firstly, the outlines of remote sensing data applications are given including infrared brightness temperature, microwave brightness temperature, outgoing longwave radiation, and assimilated data from multiple earth observations. Secondly, three development phases are summarized as qualitative analysis based on visual interpretation, quantitative analysis based on image processing, and multi-parameter spatio-temporal correlation analysis. Thirdly, the theoretical hypotheses presented for the mechanism understanding are introduced including earth degassing, stress-induced heat, crustal rock battery conversion, latent heat release due to radon decay as well as multi-spheres coupling effect. Finally, three key directions of future research on this topic are proposed:anomaly recognizing by remote sensing monitoring and data analysis for typical tectonic activity areas; anomaly mechanism understanding based on earthquake-related earth system responses; spatio-temporal correlation analysis of air-based, space-based and ground-based stereoscopic observations.

Some problems on remote sensing geology for uranium prospecting

International Nuclear Information System (INIS)

Yang Tinghuai.

1988-01-01

Remote sensing is a kind of very effective method which can be used in all stages of geological prospecting. Geological prospecting with remote sensing method must be based on different genetic models of ore deposits, characteristics of geology-landscape and comprehensive analysis for geophysical and geochemical data, that is, by way of conceptual model prospecting. The prospecting results based on remote sensing geology should be assessed from three aspects such as direct, indirect and potential ones

The separation-combination method of linear structures in remote sensing image interpretation and its application

International Nuclear Information System (INIS)

Liu Linqin

1991-01-01

The separation-combination method a new kind of analysis method of linear structures in remote sensing image interpretation is introduced taking northwestern Fujian as the example, its practical application is examined. The practice shows that application results not only reflect intensities of linear structures in overall directions at different locations, but also contribute to the zonation of linear structures and display their space distribution laws. Based on analyses of linear structures, it can provide more information concerning remote sensing on studies of regional mineralization laws and the guide to ore-finding combining with mineralization

Photogrammetry and remote sensing education subjects

Science.gov (United States)

Lazaridou, Maria A.; Karagianni, Aikaterini Ch.

2017-09-01

The rapid technologic advances in the scientific areas of photogrammetry and remote sensing require continuous readjustments at the educational programs and their implementation. The teaching teamwork should deal with the challenge to offer the volume of the knowledge without preventing the understanding of principles and methods and also to introduce "new" knowledge (advances, trends) followed by evaluation and presentation of relevant applications. This is of particular importance for a Civil Engineering Faculty as this in Aristotle University of Thessaloniki, as the framework of Photogrammetry and Remote Sensing is closely connected with applications in the four educational Divisions of the Faculty. This paper refers to the above and includes subjects of organizing the courses in photogrammetry and remote sensing in the Civil Engineering Faculty of Aristotle University of Thessaloniki. A scheme of the general curriculum as well the teaching aims and methods are also presented.

REMOTE SENSING IN OCEANOGRAPHY.

Science.gov (United States)

remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and

Remote Sensing Image Registration Using Multiple Image Features

Directory of Open Access Journals (Sweden)

Kun Yang

2017-06-01

Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

Remote Sensing of Landslides—A Review

Directory of Open Access Journals (Sweden)

Chaoying Zhao

2018-02-01

Full Text Available Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers.

Remote sensing for studying atmospheric aerosols in Malaysia

Science.gov (United States)

Kanniah, Kasturi D.; Kamarul Zaman, Nurul A. F.

2015-10-01

The aerosol system is Southeast Asia is complex and the high concentrations are due to population growth, rapid urbanization and development of SEA countries. Nevertheless, only a few studies have been carried out especially at large spatial extent and on a continuous basis to study atmospheric aerosols in Malaysia. In this review paper we report the use of remote sensing data to study atmospheric aerosols in Malaysia and document gaps and recommend further studies to bridge the gaps. Satellite data have been used to study the spatial and seasonal patterns of aerosol optical depth (AOD) in Malaysia. Satellite data combined with AERONET data were used to delineate different types and sizes of aerosols and to identify the sources of aerosols in Malaysia. Most of the aerosol studies performed in Malaysia was based on station-based PM10 data that have limited spatial coverage. Thus, satellite data have been used to extrapolate and retrieve PM10 data over large areas by correlating remotely sensed AOD with ground-based PM10. Realising the critical role of aerosols on radiative forcing numerous studies have been conducted worldwide to assess the aerosol radiative forcing (ARF). Such studies are yet to be conducted in Malaysia. Although the only source of aerosol data covering large region in Malaysia is remote sensing, satellite observations are limited by cloud cover, orbital gaps of satellite track, etc. In addition, relatively less understanding is achieved on how the atmospheric aerosol interacts with the regional climate system. These gaps can be bridged by conducting more studies using integrated approach of remote sensing, AERONET and ground based measurements.

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

Science.gov (United States)

Quattrochi, Dale A.; Luvall, Jeffrey C.

1998-01-01

Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of

PARALLEL AND ADAPTIVE UNIFORM-DISTRIBUTED REGISTRATION METHOD FOR CHANG’E-1 LUNAR REMOTE SENSED IMAGERY

Directory of Open Access Journals (Sweden)

X. Ning

2012-08-01

To resolve the above-mentioned registration difficulties, a parallel and adaptive uniform-distributed registration method for CE-1 lunar remote sensed imagery is proposed in this paper. Based on 6 pairs of randomly selected images, both the standard SIFT algorithm and the parallel and adaptive uniform-distributed registration method were executed, the versatility and effectiveness were assessed. The experimental results indicate that: by applying the parallel and adaptive uniform-distributed registration method, the efficiency of CE-1 lunar remote sensed imagery registration were increased dramatically. Therefore, the proposed method in the paper could acquire uniform-distributed registration results more effectively, the registration difficulties including difficult to obtain results, time-consuming, non-uniform distribution could be successfully solved.

A stereo remote sensing feature selection method based on artificial bee colony algorithm

Science.gov (United States)

Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

2014-05-01

To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

Application of remote sensing to agricultural field trials

NARCIS (Netherlands)

Clevers, J.G.P.W.

1986-01-01

Remote sensing techniques enable quantitative information about a field trial to be obtained instantaneously and non-destructively. The aim of this study was to identify a method that can reduce inaccuracies in field trial analysis, and to identify how remote sensing can support and/or

Extraction Method for Earthquake-Collapsed Building Information Based on High-Resolution Remote Sensing

International Nuclear Information System (INIS)

Chen, Peng; Wu, Jian; Liu, Yaolin; Wang, Jing

2014-01-01

At present, the extraction of earthquake disaster information from remote sensing data relies on visual interpretation. However, this technique cannot effectively and quickly obtain precise and efficient information for earthquake relief and emergency management. Collapsed buildings in the town of Zipingpu after the Wenchuan earthquake were used as a case study to validate two kinds of rapid extraction methods for earthquake-collapsed building information based on pixel-oriented and object-oriented theories. The pixel-oriented method is based on multi-layer regional segments that embody the core layers and segments of the object-oriented method. The key idea is to mask layer by layer all image information, including that on the collapsed buildings. Compared with traditional techniques, the pixel-oriented method is innovative because it allows considerably rapid computer processing. As for the object-oriented method, a multi-scale segment algorithm was applied to build a three-layer hierarchy. By analyzing the spectrum, texture, shape, location, and context of individual object classes in different layers, the fuzzy determined rule system was established for the extraction of earthquake-collapsed building information. We compared the two sets of results using three variables: precision assessment, visual effect, and principle. Both methods can extract earthquake-collapsed building information quickly and accurately. The object-oriented method successfully overcomes the pepper salt noise caused by the spectral diversity of high-resolution remote sensing data and solves the problem of same object, different spectrums and that of same spectrum, different objects. With an overall accuracy of 90.38%, the method achieves more scientific and accurate results compared with the pixel-oriented method (76.84%). The object-oriented image analysis method can be extensively applied in the extraction of earthquake disaster information based on high-resolution remote sensing

Remote Sensing Image Classification Based on Stacked Denoising Autoencoder

Directory of Open Access Journals (Sweden)

Peng Liang

2017-12-01

Full Text Available Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised Greedy layer-wise training algorithm is used to train each layer in turn for more robust expressing, characteristics are obtained in supervised learning by Back Propagation (BP neural network, and the whole network is optimized by error back propagation. Finally, Gaofen-1 satellite (GF-1 remote sensing data are used for evaluation, and the total accuracy and kappa accuracy reach 95.7% and 0.955, respectively, which are higher than that of the Support Vector Machine and Back Propagation neural network. The experiment results show that the proposed method can effectively improve the accuracy of remote sensing image classification.

Methods for Enhancing Geological Structures in Spectral Spatial Difference－Based on Remote-Sensing Image

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

@@In this paper, some image processing methods such as directional template (mask) matching enhancement, pseudocolor or false color enhancement, K-L transform enhancement are used to enhance a geological structure, one of important ore-controlling factors, shown in the remote-sensing images.This geological structure is regarded as image anomaly in the remote-sensing image, since considerable differences, based on the spatial spectral distribution pattern, in gray values (spectral), color tones and texture, are always present between the geological structure and background. Therefore,the enhancement of the geological structure in the remotesensing image is that of the spectral spatial difference.

Remote Sensing for Wind Energy

DEFF Research Database (Denmark)

The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus......-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

Tunnel-Site Selection by Remote Sensing Techniques

Science.gov (United States)

A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave

Remote Sensing Best Paper Award 2013

OpenAIRE

Prasad Thenkabail

2013-01-01

Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for 2013. Nominations were selected by the Editor-in-Chief and selected editorial board members from among all the papers published in 2009. Reviews and research papers were evaluated separately.

Documentation of archaeological sites in northern iraq using remote sensing methods

Science.gov (United States)

Matoušková, E.; Pavelka, K.; Nováček, K.; Starková, L.

2015-08-01

The MULINEM (The Medieval Urban Landscape in Northeastern Mesopotamia) project is aiming to investigate a Late Sasanian and Islamic urban network in the land of Erbil, historic province of Hidyab (Adiabene) that is located in the northern Iraq. The research of the hierarchical urban network in a defined area belongs to approaches rarely used in the study of the Islamic urbanism. The project focuses on the cluster of urban sites of the 6th-17th centuries A.D. This paper focuses on remote sensing analysis of historical sites with special interest of FORMOSAT-2 data that have been gained through a research announcement: Free FORMOSAT-2 satellite Imagery. Documentation of two archaeological sites (Makhmúr al-Qadima and Kushaf) are introduced. FORMOSAT-2 data results have been compared to historic CORONA satellite data of mentioned historical sites purchased earlier by the University of West Bohemia. Remote sensing methods were completed using in-situ measurements.

Remote Sensing for Wind Energy

DEFF Research Database (Denmark)

Peña, Alfredo; Hasager, Charlotte Bay; Lange, Julia

The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... state-of-the-art ‘guideline’ available for people involved in Remote Sensing in Wind Energy....

Remote Sensing and Imaging Physics

Science.gov (United States)

2012-03-07

Program Manager AFOSR/RSE Air Force Research Laboratory Remote Sensing and Imaging Physics 7 March 2012 Report Documentation Page Form...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Remote Sensing And Imaging Physics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Imaging of Space Objects •Information without Imaging •Predicting the Location of Space Objects • Remote Sensing in Extreme Conditions •Propagation

Remote sensing: best practice

Energy Technology Data Exchange (ETDEWEB)

Brown, Gareth [Sgurr Energy (Canada)

2011-07-01

This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.

Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

Directory of Open Access Journals (Sweden)

Marc Cattet

2010-11-01

Full Text Available Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC. Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI, inversion algorithm, data fusion, and the integration of remote sensing (RS and geographic information system (GIS.

Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists.

Science.gov (United States)

Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc

2010-01-01

Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).

Raman lidar measurements of water vapor and aerosols during the atmospheric radiation measurement (ARM) remote clouds sensing (RCS) intensive observation period (IOP)

Energy Technology Data Exchange (ETDEWEB)

Melfi, S.H.; Starr, D.O`C.; Whiteman, D. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)] [and others

1996-04-01

The first Atmospheric Radiation Measurement (ARM) remote Cloud Study (RCS) Intensive Operations Period (IOP) was held during April 1994 at the Southern Great Plains (SGP) site. This experiment was conducted to evaluate and calibrate state-of-the-art, ground based remote sensing instruments and to use the data acquired by these instruments to validate retrieval algorithms developed under the ARM program.

Remote Sensing of Irrigated Agriculture: Opportunities and Challenges

Directory of Open Access Journals (Sweden)

Chelsea Cervantes

2010-09-01

Full Text Available Over the last several decades, remote sensing has emerged as an effective tool to monitor irrigated lands over a variety of climatic conditions and locations. The objective of this review, which summarizes the methods and the results of existing remote sensing studies, is to synthesize principle findings and assess the state of the art. We take a taxonomic approach to group studies based on location, scale, inputs, and methods, in an effort to categorize different approaches within a logical framework. We seek to evaluate the ability of remote sensing to provide synoptic and timely coverage of irrigated lands in several spectral regions. We also investigate the value of archived data that enable comparison of images through time. This overview of the studies to date indicates that remote sensing-based monitoring of irrigation is at an intermediate stage of development at local scales. For instance, there is overwhelming consensus on the efficacy of vegetation indices in identifying irrigated fields. Also, single date imagery, acquired at peak growing season, may suffice to identify irrigated lands, although to multi-date image data are necessary for improved classification and to distinguish different crop types. At local scales, the mapping of irrigated lands with remote sensing is also strongly affected by the timing of image acquisition and the number of images used. At the regional and global scales, on the other hand, remote sensing has not been fully operational, as methods that work in one place and time are not necessarily transferable to other locations and periods. Thus, at larger scales, more work is required to indentify the best spectral indices, best time periods, and best classification methods under different climatological and cultural environments. Existing studies at regional scales also establish the fact that both remote sensing and national statistical approaches require further refinement with a substantial investment of

Remote sensing in meteorology, oceanography and hydrology

Energy Technology Data Exchange (ETDEWEB)

Cracknell, A P [ed.

1981-01-01

Various aspects of remote sensing are discussed. Topics include: the EARTHNET data acquisition, processing, and distribution facility the design and implementation of a digital interactive image processing system geometrical aspects of remote sensing and space cartography remote sensing of a complex surface legal aspects of remote sensing remote sensing of pollution, dust storms, ice masses, and ocean waves and currents use of satellite images for weather forecasting. Notes on field trips and work-sheets for laboratory exercises are included.

Remote sensing of oil slicks

Digital Repository Service at National Institute of Oceanography (India)

Fondekar, S.P.; Rao, L.V.G.

the drawback of expensive conventional surveying methods. An airborne remote sensing system used for monitoring and surveillance of oil comprises different sensors such as side-looking airborne radar, synthetic aperture radar, infrared/ultraviolet line scanner...

Modeling Solar Radiation in the Forest Using Remote Sensing Data: A Review of Approaches and Opportunities

Directory of Open Access Journals (Sweden)

Alex S. Olpenda

2018-05-01

Full Text Available Solar radiation, the radiant energy from the sun, is a driving variable for numerous ecological, physiological, and other life-sustaining processes in the environment. Traditional methods to quantify solar radiation are done either directly (e.g., quantum sensors, or indirectly (e.g., hemispherical photography. This study, however, evaluates literature which utilized remote sensing (RS technologies to estimate various forms of solar radiation or components, thereof under or within forest canopies. Based on the review, light detection and ranging (LiDAR has, so far, been preferably used for modeling light under tree canopies. Laser system’s capability of generating 3D canopy structure at high spatial resolution makes it a reasonable choice as a source of spatial information about light condition in various parts of forest ecosystem. The majority of those using airborne laser system (ALS commonly adopted the volumetric-pixel (voxel method or the laser penetration index (LPI for modeling the radiation, while terrestrial laser system (TLS is preferred for canopy reconstruction and simulation. Furthermore, most of the studies focused only on global radiation, and very few on the diffuse fraction. It was also found out that most of these analyses were performed in the temperate zone, with a smaller number of studies made in tropical areas. Nonetheless, with the continuous advancement of technology and the RS datasets becoming more accessible and less expensive, these shortcomings and other difficulties of estimating the spatial variation of light in the forest are expected to diminish.

Remote Sensing Wind and Wind Shear System.

Science.gov (United States)

Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.

Remote sensing of land surface phenology

Science.gov (United States)

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

Adjoint Sensitivity Analysis of Radiative Transfer Equation: Temperature and Gas Mixing Ratio Weighting Functions for Remote Sensing of Scattering Atmospheres in Thermal IR

Science.gov (United States)

Ustinov, E.

1999-01-01

Sensitivity analysis based on using of the adjoint equation of radiative transfer is applied to the case of atmospheric remote sensing in the thermal spectral region with non-negligeable atmospheric scattering.

Radiative transfer theory for active remote sensing of a layer of small ellipsoidal scatterers. [of vegetation

Science.gov (United States)

Tsang, L.; Kubacsi, M. C.; Kong, J. A.

1981-01-01

The radiative transfer theory is applied within the Rayleigh approximation to calculate the backscattering cross section of a layer of randomly positioned and oriented small ellipsoids. The orientation of the ellipsoids is characterized by a probability density function of the Eulerian angles of rotation. The radiative transfer equations are solved by an iterative approach to first order in albedo. In the half space limit the results are identical to those obtained via the approach of Foldy's and distorted Born approximation. Numerical results of the theory are illustrated using parameters encountered in active remote sensing of vegetation layers. A distinctive characteristic is the strong depolarization shown by vertically aligned leaves.

Remote sensing for global change, climate change and atmosphere and ocean forecasting. Volume 1

International Nuclear Information System (INIS)

1992-01-01

This volume is separated in three sessions. First part is on remote sensing for global change (with global modelling, land cover change on global scale, ocean colour studies of marine biosphere, biological and hydrological interactions and large scale experiments). Second part is on remote sensing for climate change (with earth radiation and clouds, sea ice, global climate research programme). Third part is on remote sensing for atmosphere and ocean forecasting (with temperatures and humidity, winds, data assimilation, cloud imagery, sea surface temperature, ocean waves and topography). (A.B.). refs., figs., tabs

System and method for extracting physiological information from remotely detected electromagnetic radiation

NARCIS (Netherlands)

2016-01-01

The present invention relates to a device and a method for extracting physiological information indicative of at least one health symptom from remotely detected electromagnetic radiation. The device comprises an interface (20) for receiving a data stream comprising remotely detected image data

System and method for extracting physiological information from remotely detected electromagnetic radiation

NARCIS (Netherlands)

2015-01-01

The present invention relates to a device and a method for extracting physiological information indicative of at least one health symptom from remotely detected electromagnetic radiation. The device comprises an interface (20) for receiving a data stream comprising remotely detected image data

An improved optimum-path forest clustering algorithm for remote sensing image segmentation

Science.gov (United States)

Chen, Siya; Sun, Tieli; Yang, Fengqin; Sun, Hongguang; Guan, Yu

2018-03-01

Remote sensing image segmentation is a key technology for processing remote sensing images. The image segmentation results can be used for feature extraction, target identification and object description. Thus, image segmentation directly affects the subsequent processing results. This paper proposes a novel Optimum-Path Forest (OPF) clustering algorithm that can be used for remote sensing segmentation. The method utilizes the principle that the cluster centres are characterized based on their densities and the distances between the centres and samples with higher densities. A new OPF clustering algorithm probability density function is defined based on this principle and applied to remote sensing image segmentation. Experiments are conducted using five remote sensing land cover images. The experimental results illustrate that the proposed method can outperform the original OPF approach.

Remote sensing for the geobotanical and biogeochemical assessment of environmental contamination

International Nuclear Information System (INIS)

Wickham, J.; Chesley, M.; Lancaster, J.; Mouat, D.

1993-01-01

Under Contract Number DE-AC08-90NV10845, the DOE has funded the Desert Research Institute (DRI) to examine several aspects of remote sensing, specifically with respect to how its use might help support Environmental Restoration and Waste Management (ERWM) activities at DOE sites located throughout the country. This report represents partial fulfillment of DRI's obligations under that contract and includes a review of relevant literature associated with remote sensing studies and our evaluation and recommendation as to the applicability of various remote sensing techniques for DOE needs. With respect to DOE ERWM activities, remote sensing may be broadly defined as collecting information about a target without actually being in physical contact with the object. As the common platforms for remote sensing observations are aircraft and satellites, there exists the possibility to rapidly and efficiently collect information over DOE sites that would allow for the identification and monitoring of contamination related to present and past activities. As DOE sites cover areas ranging from tens to hundreds of square miles, remote sensing may provide an effective, efficient, and economical method in support of ERWM activities. For this review, remote sensing has been limited to methods that employ electromagnetic (EM) energy as the means of detecting and measuring target characteristics

Remote sensing for the geobotanical and biogeochemical assessment of environmental contamination

Energy Technology Data Exchange (ETDEWEB)

Wickham, J.; Chesley, M.; Lancaster, J.; Mouat, D.

1993-01-01

Under Contract Number DE-AC08-90NV10845, the DOE has funded the Desert Research Institute (DRI) to examine several aspects of remote sensing, specifically with respect to how its use might help support Environmental Restoration and Waste Management (ERWM) activities at DOE sites located throughout the country. This report represents partial fulfillment of DRI`s obligations under that contract and includes a review of relevant literature associated with remote sensing studies and our evaluation and recommendation as to the applicability of various remote sensing techniques for DOE needs. With respect to DOE ERWM activities, remote sensing may be broadly defined as collecting information about a target without actually being in physical contact with the object. As the common platforms for remote sensing observations are aircraft and satellites, there exists the possibility to rapidly and efficiently collect information over DOE sites that would allow for the identification and monitoring of contamination related to present and past activities. As DOE sites cover areas ranging from tens to hundreds of square miles, remote sensing may provide an effective, efficient, and economical method in support of ERWM activities. For this review, remote sensing has been limited to methods that employ electromagnetic (EM) energy as the means of detecting and measuring target characteristics.

Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks

Directory of Open Access Journals (Sweden)

Rui Guo

2018-03-01

Full Text Available Considering the classification of high spatial resolution remote sensing imagery, this paper presents a novel classification method for such imagery using deep neural networks. Deep learning methods, such as a fully convolutional network (FCN model, achieve state-of-the-art performance in natural image semantic segmentation when provided with large-scale datasets and respective labels. To use data efficiently in the training stage, we first pre-segment training images and their labels into small patches as supplements of training data using graph-based segmentation and the selective search method. Subsequently, FCN with atrous convolution is used to perform pixel-wise classification. In the testing stage, post-processing with fully connected conditional random fields (CRFs is used to refine results. Extensive experiments based on the Vaihingen dataset demonstrate that our method performs better than the reference state-of-the-art networks when applied to high-resolution remote sensing imagery classification.

Remote Sensing and the Earth.

Science.gov (United States)

Brosius, Craig A.; And Others

This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

Remote Sensing Training for Middle School through the Center of Excellence in Remote Sensing Education

Science.gov (United States)

Hayden, L. B.; Johnson, D.; Baltrop, J.

2012-12-01

Remote sensing has steadily become an integral part of multiple disciplines, research, and education. Remote sensing can be defined as the process of acquiring information about an object or area of interest without physical contact. As remote sensing becomes a necessity in solving real world problems and scientific questions an important question to consider is why remote sensing training is significant to education and is it relevant to training students in this discipline. What has been discovered is the interest in Science, Technology, Engineering and Mathematics (STEM) fields, specifically remote sensing, has declined in our youth. The Center of Excellence in Remote Sensing Education and Research (CERSER) continuously strives to provide education and research opportunities on ice sheet, coastal, ocean, and marine science. One of those continued outreach efforts are Center for Remote Sensing of Ice Sheets (CReSIS) Middle School Program. Sponsored by the National Science Foundation CReSIS Middle School Program offers hands on experience for middle school students. CERSER and NSF offer students the opportunity to study and learn about remote sensing and its vital role in today's society as it relate to climate change and real world problems. The CReSIS Middle School Program is an annual two-week effort that offers middle school students experience with remote sensing and its applications. Specifically, participants received training with Global Positioning Systems (GPS) where the students learned the tools, mechanisms, and applications of a Garmin 60 GPS. As a part of the program the students were required to complete a fieldwork assignment where several longitude and latitude points were given throughout campus. The students had to then enter the longitude and latitude points into the Garmin 60 GPS, navigate their way to each location while also accurately reading the GPS to make sure travel was in the right direction. Upon completion of GPS training the

Radar Remote Sensing

Science.gov (United States)

Rosen, Paul A.

2012-01-01

This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.

Study on edge-extraction of remote sensing image

International Nuclear Information System (INIS)

Wen Jianguang; Xiao Qing; Xu Huiping

2005-01-01

Image edge-extraction is an important step in image processing and recognition, and also a hot spot in science study. In this paper, based on primary methods of the remote sensing image edge-extraction, authors, for the first time, have proposed several elements which should be considered before processing. Then, the qualities of several methods in remote sensing image edge-extraction are systematically summarized. At last, taking Near Nasca area (Peru) as an example the edge-extraction of Magmatic Range is analysed. (authors)

CYBERNETIC BASIS AND SYSTEM PRACTICE OF REMOTE SENSING AND SPATIAL INFORMATION SCIENCE

Directory of Open Access Journals (Sweden)

X. Tan

2017-09-01

Full Text Available Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science

Science.gov (United States)

Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.

2017-09-01

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

Science.gov (United States)

Giardino, Marco J.; Haley, Bryan S.

2005-01-01

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously

Remote sensing for water quality

International Nuclear Information System (INIS)

Giardino, Claudia

2006-01-01

The application of remote sensing to the study of lakes is begun in years 80 with the lunch of the satellites of second generation. Many experiences have indicated the contribution of remote sensing for the limnology [it

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

Science.gov (United States)

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Water column correction for coral reef studies by remote sensing.

Science.gov (United States)

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-09-11

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

Introductory remote sensing principles and concepts principles and concepts

CERN Document Server

Gibson, Paul

2013-01-01

Introduction to Remote Sensing Principles and Concepts provides a comprehensive student introduction to both the theory and application of remote sensing. This textbook* introduces the field of remote sensing and traces its historical development and evolution* presents detailed explanations of core remote sensing principles and concepts providing the theory required for a clear understanding of remotely sensed images.* describes important remote sensing platforms - including Landsat, SPOT and NOAA * examines and illustrates many of the applications of remotely sensed images in various fields.

An Orthogonal Learning Differential Evolution Algorithm for Remote Sensing Image Registration

Directory of Open Access Journals (Sweden)

Wenping Ma

2014-01-01

Full Text Available We introduce an area-based method for remote sensing image registration. We use orthogonal learning differential evolution algorithm to optimize the similarity metric between the reference image and the target image. Many local and global methods have been used to achieve the optimal similarity metric in the last few years. Because remote sensing images are usually influenced by large distortions and high noise, local methods will fail in some cases. For this reason, global methods are often required. The orthogonal learning (OL strategy is efficient when searching in complex problem spaces. In addition, it can discover more useful information via orthogonal experimental design (OED. Differential evolution (DE is a heuristic algorithm. It has shown to be efficient in solving the remote sensing image registration problem. So orthogonal learning differential evolution algorithm (OLDE is efficient for many optimization problems. The OLDE method uses the OL strategy to guide the DE algorithm to discover more useful information. Experiments show that the OLDE method is more robust and efficient for registering remote sensing images.

The potential of remote sensing technology for the detection and ...

African Journals Online (AJOL)

Internationally, a number of studies have successfully used remote sensing technology to monitor forest damage. Remote sensing technology allows for instantaneous methods of assessments whereby ground assessments would be impossible on a regular basis. This paper provides an overview of how advances in ...

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images

Directory of Open Access Journals (Sweden)

Bin Hou

2016-08-01

Full Text Available Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD methods have been developed to solve them by utilizing remote sensing (RS images. The advent of high resolution (HR remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC segmentation. Then, saliency and morphological building index (MBI extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF. Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.

Impact of the Sun on Remote Sensing of Sea Surface Salinity from Space

National Research Council Canada - National Science Library

Le Vine, David M; Abraham, Saji; Wentz, F; Lagerloef, G. S

2005-01-01

... to monitor soil moisture and sea surface salinity. Radiation from the sun can impact passive remote sensing systems in several ways, including line-of-sight radiation that comes directly from the sun and enters through antenna side lobes...

Remote Sensing and Reflectance Profiling in Entomology.

Science.gov (United States)

Nansen, Christian; Elliott, Norman

2016-01-01

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

Operational remote sensing of aerosols over land to account for directional effects

International Nuclear Information System (INIS)

Ramon, Didier; Santer, Richard

2001-01-01

The assumption that the ground is a Lambertian reflector is commonly adopted in operational atmospheric corrections of spaceborne sensors. Through a simple modeling of directional effects in radiative transfer following the second simulation of the satellite signal in the solar spectrum (6S) approach, we propose an operational method to account for the departure from Lambertian behavior of a reflector covered by a scattering medium. This method relies on the computation of coupling terms between the reflecting and the scattering media and is able to deal with a two-layer atmosphere. We focus on the difficult problem of aerosol remote sensing over land. One popular sensing method relies on observations over dense dark vegetation, for which the surface reflectance is low and quite well defined in the blue and in the red. Therefore a study was made for three cases: (1) dark vegetation covered by atmospheric aerosols, (2) atmospheric aerosols covered by molecules, and finally (3) dark vegetation covered by atmospheric aerosols covered by molecules. Comparisons of top-of-the-atmosphere reflectances computed with our modeling and reference computations made with the successive-order-of-scattering code show the robustness of the modeling in the blue and in the red for aerosol optical thicknesses as great as 0.6 and solar zenith angles as large as 60 deg. . The model begins to fail only in the blue for large solar zenith angles. The benefits expected for aerosol remote sensing over land are evaluated with an aerosol retrieval scheme developed for the Medium-Resolution Imaging Spectrometer. The main result is a better constraint on the aerosol model with inclusion of directional effects and a weaker effect on the optical thickness of the retrieval aerosol. The directional scheme is then applied to the aerosol remote-sensing problem in actual Indian Remote Sensing Satellite P3/Modular Optoelectronic Scanner images over land and shows significant improvement compared with a

Photogrammetry - Remote Sensing and Geoinformation

Science.gov (United States)

Lazaridou, M. A.; Patmio, E. N.

2012-07-01

Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS) is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc), and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers) in the Lab. of Photogrammetry - Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.

Remote Sensing of shallow sea floor for digital earth environment

International Nuclear Information System (INIS)

Yahya, N N; Hashim, M; Ahmad, S

2014-01-01

Understanding the sea floor biodiversity requires spatial information that can be acquired from remote sensing satellite data. Species volume, spatial patterns and species coverage are some of the information that can be derived. Current approaches for mapping sea bottom type have evolved from field observation, visual interpretation from aerial photography, mapping from remote sensing satellite data along with field survey and hydrograhic chart. Remote sensing offers most versatile technique to map sea bottom type up to a certain scale. This paper reviews the technical characteristics of signal and light interference within marine features, space and remote sensing satellite. In addition, related image processing techniques that are applicable to remote sensing satellite data for sea bottom type digital mapping is also presented. The sea bottom type can be differentiated by classification method using appropriate spectral bands of satellite data. In order to verify the existence of particular sea bottom type, field observations need to be carried out with proper technique and equipment

Image Fusion Technologies In Commercial Remote Sensing Packages

OpenAIRE

Al-Wassai, Firouz Abdullah; Kalyankar, N. V.

2013-01-01

Several remote sensing software packages are used to the explicit purpose of analyzing and visualizing remotely sensed data, with the developing of remote sensing sensor technologies from last ten years. Accord-ing to literature, the remote sensing is still the lack of software tools for effective information extraction from remote sensing data. So, this paper provides a state-of-art of multi-sensor image fusion technologies as well as review on the quality evaluation of the single image or f...

Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR: Chapter 1

Science.gov (United States)

Panda, Sudhanshu S.; Rao, Mahesh N.; Thenkabail, Prasad S.; Fitzerald, James E.

2015-01-01

The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.

Remote sensing applications for the dam industry

Energy Technology Data Exchange (ETDEWEB)

Pryse-Phillips, A.; Woolgar, R. [Hatch Ltd., St. John' s, NL (Canada); Puestow, T.; Warren, S. [Memorial Univ. of Newfoundland, St. John' s, NL (Canada). C-Core; Rogers, K. [Nalcor Energy, St. John' s, NL (Canada); Khan, A. [Government of Newfoundland and Labrador, St. Johns, NL (Canada)

2009-07-01

There has been an increase in the earth observation missions providing satellite imagery for operational monitoring applications. This technique has been found to be especially useful for the surveillance of large, remote areas, which is challenging to achieve in a cost-effective manner by conventional field-based or aerial means. This paper discussed the utility of satellite-based monitoring for different applications relevant to hydrology and water resources management. Emphasis was placed on the monitoring of river ice covers in near, real-time and water resources management. The paper first outlined river ice monitoring using remote sensing on the Lower Churchill River. The benefits of remote sensing over traditional survey methods for the dam industry was then outlined. Satellite image acquisition and interpretation for the Churchill River was then presented. Several images were offered. Watershed physiographic characterization using remote sensing was also described. It was concluded that satellite imagery proved to be a useful tool to develop physiographic characteristics when conducting rainfall-runoff modelling. 3 refs., 1 tab., 11 figs.

Remote Sensing Digital Image Analysis An Introduction

CERN Document Server

Richards, John A

2013-01-01

Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

Multiscale and Multitemporal Urban Remote Sensing

Science.gov (United States)

Mesev, V.

2012-07-01

The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.

Accurate estimation of motion blur parameters in noisy remote sensing image

Science.gov (United States)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

Research on Horizontal Accuracy Method of High Spatial Resolution Remotely Sensed Orthophoto Image

Science.gov (United States)

Xu, Y. M.; Zhang, J. X.; Yu, F.; Dong, S.

2018-04-01

At present, in the inspection and acceptance of high spatial resolution remotly sensed orthophoto image, the horizontal accuracy detection is testing and evaluating the accuracy of images, which mostly based on a set of testing points with the same accuracy and reliability. However, it is difficult to get a set of testing points with the same accuracy and reliability in the areas where the field measurement is difficult and the reference data with high accuracy is not enough. So it is difficult to test and evaluate the horizontal accuracy of the orthophoto image. The uncertainty of the horizontal accuracy has become a bottleneck for the application of satellite borne high-resolution remote sensing image and the scope of service expansion. Therefore, this paper proposes a new method to test the horizontal accuracy of orthophoto image. This method using the testing points with different accuracy and reliability. These points' source is high accuracy reference data and field measurement. The new method solves the horizontal accuracy detection of the orthophoto image in the difficult areas and provides the basis for providing reliable orthophoto images to the users.

Remote Sensing for Wind Energy

DEFF Research Database (Denmark)

The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to add more topics in future editions and to update as necessary, to provide a truly state-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

Remote Sensing for Wind Energy

DEFF Research Database (Denmark)

Peña, Alfredo; Hasager, Charlotte Bay; Badger, Merete

The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art ‘guideline’ available for people involved in Remote Sensing...

Water Column Correction for Coral Reef Studies by Remote Sensing

Directory of Open Access Journals (Sweden)

Maria Laura Zoffoli

2014-09-01

Full Text Available Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

Water Column Correction for Coral Reef Studies by Remote Sensing

Science.gov (United States)

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-01-01

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application. PMID:25215941

A DATA FIELD METHOD FOR URBAN REMOTELY SENSED IMAGERY CLASSIFICATION CONSIDERING SPATIAL CORRELATION

Directory of Open Access Journals (Sweden)

Y. Zhang

2016-06-01

Full Text Available Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and model spatial information of local pixels. The original data field method can represent the spatial interactions of neighbourhood pixels effectively. However, its focus on measuring the grey level change between the central pixel and the neighbourhood pixels results in exaggerating the contribution of the central pixel to the whole local window. Besides, Geary’s C has also been proven to well characterise and qualify the spatial correlation between each pixel and its neighbourhood pixels. But the extracted object is badly delineated with the distracting salt-and-pepper effect of isolated misclassified pixels. To correct this defect, we introduce the data field method for filtering and noise limitation. Moreover, the original data field method is enhanced by considering each pixel in the window as the central pixel to compute statistical characteristics between it and its neighbourhood pixels. The last step employs a support vector machine (SVM for the classification of multi-features (e.g. the spectral feature and spatial correlation feature. In order to validate the effectiveness of the developed method, experiments are conducted on different remotely sensed images containing multiple complex object classes inside. The results show that the developed method outperforms the traditional method in terms of classification accuracies.

A fast infrared radiative transfer model based on the adding-doubling method for hyperspectral remote-sensing applications

International Nuclear Information System (INIS)

Zhang Zhibo; Yang Ping; Kattawar, George; Huang, H.-L.; Greenwald, Thomas; Li Jun; Baum, Bryan A.; Zhou, Daniel K.; Hu Yongxiang

2007-01-01

A fast infrared radiative transfer (RT) model is developed on the basis of the adding-doubling principle, hereafter referred to as FIRTM-AD, to facilitate the forward RT simulations involved in hyperspectral remote-sensing applications under cloudy-sky conditions. A pre-computed look-up table (LUT) of the bidirectional reflection and transmission functions and emissivities of ice clouds in conjunction with efficient interpolation schemes is used in FIRTM-AD to alleviate the computational burden of the doubling process. FIRTM-AD is applicable to a variety of cloud conditions, including vertically inhomogeneous or multilayered clouds. In particular, this RT model is suitable for the computation of high-spectral-resolution radiance and brightness temperature (BT) spectra at both the top-of-atmosphere and surface, and thus is useful for satellite and ground-based hyperspectral sensors. In terms of computer CPU time, FIRTM-AD is approximately 100-250 times faster than the well-known discrete-ordinate (DISORT) RT model for the same conditions. The errors of FIRTM-AD, specified as root-mean-square (RMS) BT differences with respect to their DISORT counterparts, are generally smaller than 0.1 K

Assessment of the accuracy of the conventional ray-tracing technique: Implications in remote sensing and radiative transfer involving ice clouds

International Nuclear Information System (INIS)

Bi, Lei; Yang, Ping; Liu, Chao; Yi, Bingqi; Baum, Bryan A.; Diedenhoven, Bastiaan van; Iwabuchi, Hironobu

2014-01-01

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TM+IGOM are considered as a benchmark because the II-TM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TM+IGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 μm) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical

Remote sensing, airborne radiometric survey and aeromagnetic survey data processing and analysis

International Nuclear Information System (INIS)

Dong Xiuzhen; Liu Dechang; Ye Fawang; Xuan Yanxiu

2009-01-01

Taking remote sensing data, airborne radiometric data and aero magnetic survey data as an example, the authors elaborate about basic thinking of remote sensing data processing methods, spectral feature analysis and adopted processing methods, also explore the remote sensing data combining with the processing of airborne radiometric survey and aero magnetic survey data, and analyze geological significance of processed image. It is not only useful for geological environment research and uranium prospecting in the study area, but also reference to applications in another area. (authors)

Remote Sensing of Aboveground Biomass in Tropical Secondary Forests: A Review

Directory of Open Access Journals (Sweden)

J. M. Barbosa

2014-01-01

Full Text Available Tropical landscapes are, in general, a mosaic of pasture, agriculture, and forest undergoing various stages of succession. Forest succession is comprised of continuous structural changes over time and results in increases in aboveground biomass (AGB. New remote sensing methods, including sensors, image processing, statistical methods, and uncertainty evaluations, are constantly being developed to estimate biophysical forest changes. We review 318 peer-reviewed studies related to the use of remotely sensed AGB estimations in tropical forest succession studies and summarize their geographic distribution, sensors and methods used, and their most frequent ecological inferences. Remotely sensed AGB is broadly used in forest management studies, conservation status evaluations, carbon source and sink investigations, and for studies of the relationships between environmental conditions and forest structure. Uncertainties in AGB estimations were found to be heterogeneous with biases related to sensor type, processing methodology, ground truthing availability, and forest characteristics. Remotely sensed AGB of successional forests is more reliable for the study of spatial patterns of forest succession and over large time scales than that of individual stands. Remote sensing of temporal patterns in biomass requires further study, in particular, as it is critical for understanding forest regrowth at scales useful for regional or global analyses.

Potential of remote sensing of cirrus optical thickness by airborne spectral radiance measurements at different sideward viewing angles

OpenAIRE

Wolf, Kevin; Ehrlich, André; Hüneke, Tilman; Pfeilsticker, Klaus; Werner, Frank; Wirth, Martin; Wendisch, Manfred

2017-01-01

Spectral radiance measurements collected in nadir and sideward viewing directions by two airborne passive solar remote sensing instruments, the Spectral Modular Airborne Radiation measurement sysTem (SMART) and the Differential Optical Absorption Spectrometer (mini-DOAS), are used to compare the remote sensing results of cirrus optical thickness τ. The comparison is based on a sensitivity study using radiative transfer simulations (RTS) and on data obtained during three airb...

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

Science.gov (United States)

Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

2018-01-15

In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Best practices in Remote Sensing for REDD+

DEFF Research Database (Denmark)

Dons, Klaus; Grogan, Kenneth

2012-01-01

due to steep terrain, • phenological gradients across natural, agricultural and forestry ecosystems including plantations and • the need to serve the REDD-specific context of deforestation and forest degradation across spatial and temporal scales make remote sensing based approaches particularly...... be expected from remote sensing imagery and the provided information shall help to better anticipate problems that will be encountered when acquiring, analyzing and interpreting remote sensing data. Beyond remote sensing, it may be a good point of departure for a large group of scientists with a diverse...... and governance, and deforestation and forest degradation processes. The second part summarizes the available literature on remote sensing based good practices for REDD. It largely draws from the documents of the Intergovernmental Panel on Climate Change (IPCC), the United Nations Framework Convention on Climate...

In Situ/Remote Sensing Integration to Assess Forest Health—A Review

Directory of Open Access Journals (Sweden)

Marion Pause

2016-06-01

Full Text Available For mapping, quantifying and monitoring regional and global forest health, satellite remote sensing provides fundamental data for the observation of spatial and temporal forest patterns and processes. While new remote-sensing technologies are able to detect forest data in high quality and large quantity, operational applications are still limited by deficits of in situ verification. In situ sampling data as input is required in order to add value to physical imaging remote sensing observations and possibilities to interlink the forest health assessment with biotic and abiotic factors. Numerous methods on how to link remote sensing and in situ data have been presented in the scientific literature using e.g. empirical and physical-based models. In situ data differs in type, quality and quantity between case studies. The irregular subsets of in situ data availability limit the exploitation of available satellite remote sensing data. To achieve a broad implementation of satellite remote sensing data in forest monitoring and management, a standardization of in situ data, workflows and products is essential and necessary for user acceptance. The key focus of the review is a discussion of concept and is designed to bridge gaps of understanding between forestry and remote sensing science community. Methodological approaches for in situ/remote-sensing implementation are organized and evaluated with respect to qualifying for forest monitoring. Research gaps and recommendations for standardization of remote-sensing based products are discussed. Concluding the importance of outstanding organizational work to provide a legally accepted framework for new information products in forestry are highlighted.

Ten ways remote sensing can contribute to conservation

Science.gov (United States)

Rose, Robert A.; Byler, Dirck; Eastman, J. Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A.; Laporte, Nadine; Leidner, Allison K.; Leimgruber, Peter; Morisette, Jeffrey T.; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C.; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

2014-01-01

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to

Ten ways remote sensing can contribute to conservation.

Science.gov (United States)

Rose, Robert A; Byler, Dirck; Eastman, J Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A; Laporte, Nadine; Leidner, Allison; Leimgruber, Peter; Morisette, Jeffrey; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

2015-04-01

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to

Remote sensing for oil spill detection and response

International Nuclear Information System (INIS)

Engelhardt, F.R.

1999-01-01

This paper focuses on the use of remote sensing for marine oil spill detection and response. The surveillance and monitoring of discharges, and the main elements of effective surveillance are discussed. Tactical emergency response and the requirements for selecting a suitable remote sensing approach, airborne remote sensing systems, and the integration of satellite and airborne imaging are examined. Specifications of satellite surveillance systems potentially usable for oil spill detection, and specifications of airborne remote sensing systems suitable for oil spill detection, monitoring and supplemental actions are tabulated, and a schema of integrated satellite-airborne remote sensing (ISARS) is presented. (UK)

TWO METHODS FOR REMOTE ESTIMATION OF COMPLETE URBAN SURFACE TEMPERATURE

Directory of Open Access Journals (Sweden)

L. Jiang

2017-09-01

Full Text Available Complete urban surface temperature (TC is a key parameter for evaluating the energy exchange between the urban surface and atmosphere. At the present stage, the estimation of TC still needs detailed 3D structure information of the urban surface, however, it is often difficult to obtain the geometric structure and composition of the corresponding temperature of urban surface, so that there is still lack of concise and efficient method for estimating the TC by remote sensing. Based on the four typical urban surface scale models, combined with the Envi-met model, thermal radiant directionality forward modeling and kernel model, we analyzed a complete day and night cycle hourly component temperature and radiation temperature in each direction of two seasons of summer and winter, and calculated hemispherical integral temperature and TC. The conclusion is obtained by examining the relationship of directional radiation temperature, hemispherical integral temperature and TC: (1 There is an optimal angle of radiation temperature approaching the TC in a single observation direction when viewing zenith angle is 45–60°, the viewing azimuth near the vertical surface of the sun main plane, the average absolute difference is about 1.1 K in the daytime. (2 There are several (3–5 times directional temperatures of different view angle, under the situation of using the thermal radiation directionality kernel model can more accurately calculate the hemispherical integral temperature close to TC, the mean absolute error is about 1.0 K in the daytime. This study proposed simple and effective strategies for estimating TC by remote sensing, which are expected to improve the quantitative level of remote sensing of urban thermal environment.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

Directory of Open Access Journals (Sweden)

Guizhou Wang

2013-01-01

Full Text Available This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine. Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy.

Satellite Remote Sensing: Aerosol Measurements

Science.gov (United States)

Kahn, Ralph A.

2013-01-01

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

Remote sensing of growing conditions of rice plants by landsat MSS data and color IR aerial photograph

International Nuclear Information System (INIS)

Miyama, K.; Sato, H.

1985-01-01

Remote sensing is the technique of deriving information about an object or a phenomenon on the ground without actually coming in contact with it. The quantity measured in remote sensing systems is the electromagnetic energy which is reflected or radiated from the object of interest. Therefore, the remote sensing data rare usually collected by the remote-senser on board the airplane or the satellite. This technique is very useful for the measurement or investigation of earth surface conditions, for example, in the field of agriculture, geology, environment, etc., and the practical application of this technique is expected

Remote sensing of growing conditions of rice plants by landsat MSS data and color IR aerial photograph

Energy Technology Data Exchange (ETDEWEB)

Miyama, K.; Sato, H. [Hokkaido National Agricultural Experiment Station, Sapporo (Japan)

1985-12-15

Remote sensing is the technique of deriving information about an object or a phenomenon on the ground without actually coming in contact with it. The quantity measured in remote sensing systems is the electromagnetic energy which is reflected or radiated from the object of interest. Therefore, the remote sensing data rare usually collected by the remote-senser on board the airplane or the satellite. This technique is very useful for the measurement or investigation of earth surface conditions, for example, in the field of agriculture, geology, environment, etc., and the practical application of this technique is expected.

Remote sensing of forest insect disturbances: Current state and future directions.

Science.gov (United States)

Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

2017-08-01

Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

Science.gov (United States)

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

Remote sensing for agriculture, ecosystems, and hydrology

International Nuclear Information System (INIS)

Engman, E.T.

1998-01-01

This volume contains the proceedings of SPIE's remote sensing symposium which was held September 22--24, 1998, in Barcelona, Spain. Topics of discussion include the following: calibration techniques for soil moisture measurements; remote sensing of grasslands and biomass estimation of meadows; evaluation of agricultural disasters; monitoring of industrial and natural radioactive elements; and remote sensing of vegetation and of forest fires

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

Science.gov (United States)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

Remote Sensing of Environmental Pollution

Science.gov (United States)

North, G. W.

1971-01-01

Environmental pollution is a problem of international scope and concern. It can be subdivided into problems relating to water, air, or land pollution. Many of the problems in these three categories lend themselves to study and possible solution by remote sensing. Through the use of remote sensing systems and techniques, it is possible to detect and monitor, and in some cases, identify, measure, and study the effects of various environmental pollutants. As a guide for making decisions regarding the use of remote sensors for pollution studies, a special five-dimensional sensor/applications matrix has been designed. The matrix defines an environmental goal, ranks the various remote sensing objectives in terms of their ability to assist in solving environmental problems, lists the environmental problems, ranks the sensors that can be used for collecting data on each problem, and finally ranks the sensor platform options that are currently available.

Commercial future: making remote sensing a media event

Science.gov (United States)

Lurie, Ian

1999-12-01

The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.

USDOE Remote Sensing Laboratory multisensor surveys

International Nuclear Information System (INIS)

Tinney, L.; Christel, L.; Clark, H.; Mackey, H.

1996-01-01

The United States Department of Energy (USDOE) maintains a Remote Sensing Laboratory (RSL) to support nuclear related programs of the US Government. The mission of the organization includes both emergency response and routine environmental assessments of nuclear facilities. The unique suite of equipment used by RSL for multisensor surveys of nuclear facilities include gamma radiation sensors, mapping quality aerial cameras, video cameras, thermal imagers, and multispectral scanners. Results for RSL multisensor surveys that have been conducted at the Savannah River Site (SRS) located in South Carolina are presented

Forest biodiversity and its assessment by remote sensing

International Nuclear Information System (INIS)

Innes, J.L.; Koch, B.

1998-01-01

Several international conventions and agreements have stressed the importance of the assessment of forest biodiversity. However, the methods by which such assessments can be made remain unclear. Remote sensing represents an important tool for looking at ecosystem diversity and various structural aspects of individual ecosystems. It provides a means to make assessments across several different spatial scales, and is also critical for assessments of changes in ecosystem pattern over time. Many different forms of remote sensing are available. While lately the emphasis on laser scanner and synthetic aperture radar data has increased, most work to date has used photographs and digital optical imagery, primarily from airborne and spaceborne platforms. These provide the opportunity to assess different phenomena from the landscape to the stand scale. Remote sensing provides the most efficient tool available for determining landscape-scale elements of forest biodiversity, such as the relative proportion of matrix and patches and their physical arrangement. At intermediate scales, remote sensing provides an ideal tool for evaluating the presence of corridors and the nature of edges. At the stand scale, remote sensing technologies are likely to deliver an increasing amount of information about the structural attributes of forest stands, such as the nature of the canopy surface, the presence of layering within the canopy and presence of (very) coarse woody debris on the forest floor. Given the rate of development in the technology, even greater usage is likely in the future. (author)

Remote Sensing Best Paper Award for the Year 2014

OpenAIRE

Prasad Thenkabail

2014-01-01

Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for the year 2014.

Basic Remote Sensing Investigations for Beach Reconnaissance.

Science.gov (United States)

Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in

Developing status of satellite remote sensing and its application

International Nuclear Information System (INIS)

Zhang Wanliang; Liu Dechang

2005-01-01

This paper has discussed the latest development of satellite remote sensing in sensor resolutions, satellite motion models, load forms, data processing and its application. The authors consider that sensor resolutions of satellite remote sensing have increased largely. Valid integration of multisensors is a new idea and technology of satellite remote sensing in the 21st century, and post-remote sensing application technology is the important part of deeply applying remote sensing information and has great practical significance. (authors)

Towards operational environmental applications using terrestrial remote sensing

NARCIS (Netherlands)

Veldkamp JG; Velde RJ van de; LBG

1996-01-01

Dit rapport beschrijft de resultaten van het Beleidscommissie Remote Sensing (BCRS) project 'Verankering van toepassingen van terrestrische remote sensing bij RIVM'. Het had ten eerste tot doel te voldoen aan de voorwaarden, zoals gesteld in de inventarisatie van remote sensing als

Low-cost microwave radiometry for remote sensing of soil moisture

Science.gov (United States)

Chikando, Eric Ndjoukwe

2007-12-01

Remote sensing is now widely regarded as a dominant means of studying the Earth and its surrounding atmosphere. This science is based on blackbody theory, which states that all objects emit broadband electromagnetic radiation proportional to their temperature. This thermal emission is detectable by radiometers---highly sensitive receivers capable of measuring extremely low power radiation across a continuum of frequencies. In the particular case of a soil surface, one important parameter affecting the emitted radiation is the amount of water content or, soil moisture. A high degree of precision is required when estimating soil moisture in order to yield accurate forecasting of precipitations and short-term climate variability such as storms and hurricanes. Rapid progress within the remote sensing community in tackling current limitations necessitates an awareness of the general public towards the benefits of the science. Information about remote sensing instrumentation and techniques remain inaccessible to many higher-education institutions due to the high cost of instrumentation and the current general inaccessibility of the science. In an effort to draw more talent within the field, more affordable and reliable scientific instrumentation are needed. This dissertation introduces the first low-cost handheld microwave instrumentation fully capable of surface soil moisture studies. The framework of this research is two-fold. First, the development of a low-cost handheld microwave radiometer using the well-known Dicke configuration is examined. The instrument features a super-heterodyne architecture and is designed following a microwave integrated circuit (MIC) system approach. Validation of the instrument is performed by applying it to various soil targets and comparing measurement results to gravimetric technique measured data; a proven scientific method for determining volumetric soil moisture content. Second, the development of a fully functional receiver RF front

Hyperspectral remote sensing application for monitoring and preservation of plant ecosystems

Science.gov (United States)

Krezhova, Dora; Maneva, Svetla; Zdravev, Tomas; Petrov, Nikolay; Stoev, Antoniy

Remote sensing technologies have advanced significantly at last decade and have improved the capability to gather information about Earth’s resources and environment. They have many applications in Earth observation, such as mapping and updating land-use and cover, weather forecasting, biodiversity determination, etc. Hyperspectral remote sensing offers unique opportunities in the environmental monitoring and sustainable use of natural resources. Remote sensing sensors on space-based platforms, aircrafts, or on ground, are capable of providing detailed spectral, spatial and temporal information on terrestrial ecosystems. Ground-based sensors are used to record detailed information about the land surface and to create a data base for better characterizing the objects which are being imaged by the other sensors. In this paper some applications of two hyperspectral remote sensing techniques, leaf reflectance and chlorophyll fluorescence, for monitoring and assessment of the effects of adverse environmental conditions on plant ecosystems are presented. The effect of stress factors such as enhanced UV-radiation, acid rain, salinity, viral infections applied to some young plants (potato, pea, tobacco) and trees (plums, apples, paulownia) as well as of some growth regulators were investigated. Hyperspectral reflectance and fluorescence data were collected by means of a portable fiber-optics spectrometer in the visible and near infrared spectral ranges (450-850 nm and 600-900 nm), respectively. The differences between the reflectance data of healthy (control) and injured (stressed) plants were assessed by means of statistical (Student’s t-criterion), first derivative, and cluster analysis and calculation of some vegetation indices in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (690-720 nm) and near infrared (720-780 nm). Fluorescence spectra were analyzed at five characteristic wavelengths located at the

Remote sensing of wetlands applications and advances

CERN Document Server

Tiner, Ralph W; Klemas, Victor V

2015-01-01

Effectively Manage Wetland Resources Using the Best Available Remote Sensing Techniques Utilizing top scientists in the wetland classification and mapping field, Remote Sensing of Wetlands: Applications and Advances covers the rapidly changing landscape of wetlands and describes the latest advances in remote sensing that have taken place over the past 30 years for use in mapping wetlands. Factoring in the impact of climate change, as well as a growing demand on wetlands for agriculture, aquaculture, forestry, and development, this text considers the challenges that wetlands pose for remote sensing and provides a thorough introduction on the use of remotely sensed data for wetland detection. Taking advantage of the experiences of more than 50 contributing authors, the book describes a variety of techniques for mapping and classifying wetlands in a multitude of environments ranging from tropical to arctic wetlands including coral reefs and submerged aquatic vegetation. The authors discuss the advantages and di...

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

Science.gov (United States)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

Remote sensing of wet lands in irrigated areas

Science.gov (United States)

Ham, H. H.

1972-01-01

The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

Introduction to remote sensing

CERN Document Server

Campbell, James B

2012-01-01

A leading text for undergraduate- and graduate-level courses, this book introduces widely used forms of remote sensing imagery and their applications in plant sciences, hydrology, earth sciences, and land use analysis. The text provides comprehensive coverage of principal topics and serves as a framework for organizing the vast amount of remote sensing information available on the Web. Including case studies and review questions, the book's four sections and 21 chapters are carefully designed as independent units that instructors can select from as needed for their courses. Illustrations in

Environmental monitoring by means of remote sensing

International Nuclear Information System (INIS)

Theilen-Willige, B.

1993-01-01

Aircraft and satellite aerial photographs represent indispensible tools for environmental observation today. They contribute to a systematic inventory of important environmental parameters such as climate, vegetation or surface water. Their great importance lies in the continuous monitoring of large regions so that changes in environmental conditions are quickly detected. This book provides an overview of the capabilities of remote sensing in environmental monitoring and in the recognition of environmental problems as well as of the usefulness of remote sensing data for environmental planning. Also addressed is the role of remote sensing in the monitoring of natural hazards such as earthquakes and volcano eruptions as well as problems of remote sensing technology transfer to developing countries. (orig.) [de

Estimation of the under-surface temperature pattern by dynamic remote sensing

Energy Technology Data Exchange (ETDEWEB)

Inamura, M [Univ. of Tokyo; Tao, R; Katsuma, T; Toyota, H

1977-10-01

There are three basic classifications of remote sensing: passive RS, which involves measurement of reflected solar radiation; active RS, which involves the use of microwaves or laser radar; and infrared scanning. These methods make possible the determination of an object's surface temperature, its effective emissivity, and its effective reflectivity. The surface temperature, in effect, contains information concerning the structure below the surface. Fundamental experiments were conducted to extract sub-surface information by means of 'dynamic remote sensing.' Aluminum objects were embedded in a container filled with sand, and the container was heated from below. First, the spatial transfer function of the medium (sand) was determined, the surface temperature pattern was filtered, and the subsurface temperature pattern was calculated, allowing the subsurface forms of the aluminum objects to be estimated. The relationship between the thermal input (bottom temperature) and the thermal output (surface temperature) was expressed in terms of electrical circuit analogs, and the heat capacity and thermal conductivity of the sample were calculated, permitting estimation of its composition. This technique will be useful for groundwater and mineral exploration and for nondestructive testing.

Preface: Remote Sensing in Coastal Environments

Directory of Open Access Journals (Sweden)

Deepak R. Mishra

2016-08-01

Full Text Available The Special Issue (SI on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology in the coastal zone. This preface provides a brief summary of each article published in the SI.

Remote sensing approach to structural modelling

International Nuclear Information System (INIS)

El Ghawaby, M.A.

1989-01-01

Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs

Unmanned aerial systems for photogrammetry and remote sensing: A review

Science.gov (United States)

Colomina, I.; Molina, P.

2014-06-01

We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

Educational activities of remote sensing archaeology (Conference Presentation)

Science.gov (United States)

Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasilki; Themistocleous, Kyriacos; Cuca, Branka; Nisantzi, Argyro; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter

2016-10-01

Remote sensing science is increasingly being used to support archaeological and cultural heritage research in various ways. Satellite sensors either passive or active are currently used in a systematic basis to detect buried archaeological remains and to systematic monitor tangible heritage. In addition, airborne and low altitude systems are being used for documentation purposes. Ground surveys using remote sensing tools such as spectroradiometers and ground penetrating radars can detect variations of vegetation and soil respectively, which are linked to the presence of underground archaeological features. Education activities and training of remote sensing archaeology to young people is characterized of highly importance. Specific remote sensing tools relevant for archaeological research can be developed including web tools, small libraries, interactive learning games etc. These tools can be then combined and aligned with archaeology and cultural heritage. This can be achieved by presenting historical and pre-historical records, excavated sites or even artifacts under a "remote sensing" approach. Using such non-form educational approach, the students can be involved, ask, read, and seek to learn more about remote sensing and of course to learn about history. The paper aims to present a modern didactical concept and some examples of practical implementation of remote sensing archaeology in secondary schools in Cyprus. The idea was built upon an ongoing project (ATHENA) focused on the sue of remote sensing for archaeological research in Cyprus. Through H2020 ATHENA project, the Remote Sensing Science and Geo-Environment Research Laboratory at the Cyprus University of Technology (CUT), with the support of the National Research Council of Italy (CNR) and the German Aerospace Centre (DLR) aims to enhance its performance in all these new technologies.

A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features

Directory of Open Access Journals (Sweden)

LEI Xiaoqi

2016-02-01

Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.

Feasibility Study on Fiber-optic Radiation Sensor for Remote Gamma-ray Spectroscopy

International Nuclear Information System (INIS)

Jeon, Hyesu; Jang, Kyoung Won; Shin, Sang Hun and others

2014-01-01

In this study, we fabricated a fiber-optic radiation sensor using an optical fiber and various scintillators. To select an adequate inorganic scintillator for the sensing probe of fiber-optic radiation sensor, 5 types of scintillators were evaluated. The spectra of gamma-rays emitted from a Na-22 radiation source were measured by using the manufactured sensors. As a result, the BGO was suitable for the sensing probe of fiber-optic radiation sensor due to its high scintillation output and exact photoelectric peak for the gamma-ray energy. The basic principle of radiation detection is to detect the signals caused by interactions between radiations and materials. There are various types of radiation detectors depending on types of radiation to be detected and physical quantities to be measured. As one of the radiation detectors, a fiber-optic radiation sensor using a scintillator and an optical fiber has two advantages such as no space restraint and remote sensing. Moreover, in nuclear environments, this kind of sensor has immunities for electromagnetic field, temperature, and pressure. Thus, the fiber-optic radiation sensor can be used in various fields including nondestructive inspection, radioactive waste management, nuclear safety, radiodiagnosis and radiation therapy. As a fundamental study of the fiber-optic radiation sensor for remote gamma-ray spectroscopy, in this study, we fabricated a fiber-optic radiation sensor using an optical fiber and various scintillators. To select an adequate inorganic scintillator for the sensing probe of fiber-optic radiation sensor, 5 types of scintillators were evaluated. The spectra of gamma-rays emitted from a Na-22 radiation source were measured by using the manufactured sensors

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

Science.gov (United States)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data

A Space-Time Periodic Task Model for Recommendation of Remote Sensing Images

Directory of Open Access Journals (Sweden)

Xiuhong Zhang

2018-01-01

Full Text Available With the rapid development of remote sensing technology, the quantity and variety of remote sensing images are growing so quickly that proactive and personalized access to data has become an inevitable trend. One of the active approaches is remote sensing image recommendation, which can offer related image products to users according to their preference. Although multiple studies on remote sensing retrieval and recommendation have been performed, most of these studies model the user profiles only from the perspective of spatial area or image features. In this paper, we propose a spatiotemporal recommendation method for remote sensing data based on the probabilistic latent topic model, which is named the Space-Time Periodic Task model (STPT. User retrieval behaviors of remote sensing images are represented as mixtures of latent tasks, which act as links between users and images. Each task is associated with the joint probability distribution of space, time and image characteristics. Meanwhile, the von Mises distribution is introduced to fit the distribution of tasks over time. Then, we adopt Gibbs sampling to learn the random variables and parameters and present the inference algorithm for our model. Experiments show that the proposed STPT model can improve the capability and efficiency of remote sensing image data services.

LWIR Microgrid Polarimeter for Remote Sensing Studies

Science.gov (United States)

2010-02-28

Polarimeter for Remote Sensing Studies 5b. GRANT NUMBER FA9550-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1. Scott Tyo 5e. TASK...and tested at the University of Arizona, and preliminary images are shown in this final report. 15. SUBJECT TERMS Remote Sensing , polarimetry 16...7.0 LWIR Microgrid Polarimeter for Remote Sensing Studies J. Scott Tyo College of Optical Sciences University of Arizona Tucson, AZ, 85721 tyo

Hyperspectral remote sensing

National Research Council Canada - National Science Library

Eismann, Michael Theodore

2012-01-01

..., and hyperspectral data processing. While there are many resources that suitably cover these areas individually and focus on specific aspects of the hyperspectral remote sensing field, this book provides a holistic treatment...

Cybernetic group method of data handling (GMDH) statistical learning for hyperspectral remote sensing inverse problems in coastal ocean optics

Science.gov (United States)

Filippi, Anthony Matthew

For complex systems, sufficient a priori knowledge is often lacking about the mathematical or empirical relationship between cause and effect or between inputs and outputs of a given system. Automated machine learning may offer a useful solution in such cases. Coastal marine optical environments represent such a case, as the optical remote sensing inverse problem remains largely unsolved. A self-organizing, cybernetic mathematical modeling approach known as the group method of data handling (GMDH), a type of statistical learning network (SLN), was used to generate explicit spectral inversion models for optically shallow coastal waters. Optically shallow water light fields represent a particularly difficult challenge in oceanographic remote sensing. Several algorithm-input data treatment combinations were utilized in multiple experiments to automatically generate inverse solutions for various inherent optical property (IOP), bottom optical property (BOP), constituent concentration, and bottom depth estimations. The objective was to identify the optimal remote-sensing reflectance Rrs(lambda) inversion algorithm. The GMDH also has the potential of inductive discovery of physical hydro-optical laws. Simulated data were used to develop generalized, quasi-universal relationships. The Hydrolight numerical forward model, based on radiative transfer theory, was used to compute simulated above-water remote-sensing reflectance Rrs(lambda) psuedodata, matching the spectral channels and resolution of the experimental Naval Research Laboratory Ocean PHILLS (Portable Hyperspectral Imager for Low-Light Spectroscopy) sensor. The input-output pairs were for GMDH and artificial neural network (ANN) model development, the latter of which was used as a baseline, or control, algorithm. Both types of models were applied to in situ and aircraft data. Also, in situ spectroradiometer-derived Rrs(lambda) were used as input to an optimization-based inversion procedure. Target variables

Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

Science.gov (United States)

Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

2017-01-01

Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

Remote sensing of the Canadian Arctic: Modelling biophysical variables

Science.gov (United States)

Liu, Nanfeng

It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic

PHOTOGRAMMETRY – REMOTE SENSING AND GEOINFORMATION

Directory of Open Access Journals (Sweden)

M. A. Lazaridou

2012-07-01

Full Text Available Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc, and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers in the Lab. of Photogrammetry – Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

Science.gov (United States)

Martin, William G. K.; Hasekamp, Otto P.

2018-01-01

In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote

Discussion on the application potential of thermal infrared remote sensing technology in uranium deposits exploration

International Nuclear Information System (INIS)

Wang Junhu; Zhang Jielin; Liu Dechang

2011-01-01

With the continual development of new thermal infrared sensors and thermal radiation theory, the technology of thermal infrared remote sensing has shown great potential for applications in resources exploration, especially in the field of uranium exploration. The paper makes a systemic summary of the theoretical basis and research status of the thermal infrared remote sensing applications in resources exploration from the surface temperature, thermal inertia and thermal infrared spectrum. What's more, the research objective and the research content of thermal infrared remote sensing in the uranium deposits exploration applications are discussed in detail. Besides, based on the thermal infrared ASTER data, the paper applies this technology to the granite-type uranium deposits in South China and achieves good result. Above all, the practice proves that the thermal infrared remote sensing technology has a good application prospects and particular value in the field of uranium prospecting and will play an important role in the prospecting target of the uranium deposits. (authors)

On the division of contribution of the atmosphere and ocean in the radiation of the earth for the tasks of remote sensing and climate

Science.gov (United States)

Sushkevich, T. A.; Strelkov, S. A.; Maksakova, S. V.

2017-11-01

We are talking about the national achievements of the world level in theory of radiation transfer in the system atmosphere-oceans and about the modern scientific potential developing in Russia, which adequately provides a methodological basis for theoretical and computational studies of radiation processes and radiation fields in the natural environments with the use of supercomputers and massively parallel processing for problems of remote sensing and the climate of Earth. A model of the radiation field in system "clouds cover the atmosphere-ocean" to the separation of the contributions of clouds, atmosphere and ocean.

Optical Remote Sensing of Glacier Characteristics: A Review with Focus on the Himalaya

Science.gov (United States)

Racoviteanu, Adina E.; Williams, Mark W.; Barry, Roger G.

2008-01-01

The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya. PMID:27879883

Oil spill remote sensing sensors and aircraft

International Nuclear Information System (INIS)

Fingas, M.; Fruhwirth, M.; Gamble, L.

1992-01-01

The most common form of remote sensing as applied to oil spills is aerial remote sensing. The technology of aerial remote sensing, mainly from aircraft, is reviewed along with aircraft-mounted remote sensors and aircraft modifications. The characteristics, advantages, and limitations of optical techniques, infrared and ultraviolet sensors, fluorosensors, microwave and radar sensors, and slick thickness sensors are discussed. Special attention is paid to remote sensing of oil under difficult circumstances, such as oil in water or oil on ice. An infrared camera is the first sensor recommended for oil spill work, as it is the cheapest and most applicable device, and is the only type of equipment that can be bought off-the-shelf. The second sensor recommended is an ultraviolet and visible-spectrum device. The laser fluorosensor offers the only potential for discriminating between oiled and un-oiled weeds or shoreline, and for positively identifying oil pollution on ice and in a variety of other situations. However, such an instrument is large and expensive. Radar, although low in priority for purchase, offers the only potential for large-area searches and foul-weather remote sensing. Most other sensors are experimental or do not offer good potential for oil detection or mapping. 48 refs., 8 tabs

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

Directory of Open Access Journals (Sweden)

Linyi Li

2017-01-01

Full Text Available In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

Science.gov (United States)

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Operational Use of Remote Sensing within USDA

Science.gov (United States)

Bethel, Glenn R.

2007-01-01

A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.

Multi-source remote sensing data management system

International Nuclear Information System (INIS)

Qin Kai; Zhao Yingjun; Lu Donghua; Zhang Donghui; Wu Wenhuan

2014-01-01

In this thesis, the author explored multi-source management problems of remote sensing data. The main idea is to use the mosaic dataset model, and the ways of an integreted display of image and its interpretation. Based on ArcGIS and IMINT feature knowledge platform, the author used the C# and other programming tools for development work, so as to design and implement multi-source remote sensing data management system function module which is able to simply, conveniently and efficiently manage multi-source remote sensing data. (authors)

Remote Sensing Monitoring Methods for Detecting Invasive Weed Coverage in Delta Waterways and Bay Marshlands

Science.gov (United States)

Potter, Christopher

2018-01-01

This presentation is part of the Independent Science Board of the State of California Delta Stewardship Council brown bag seminar series on the "How the Delta is Monitored", followed with a panel discussion. Various remote sensing approaches for aquatic vegetation will be reviewed. Key research and application issues with remote sensing monitoring in the Delta will be addressed.

A temporal and spatial scaling method for quantifying daily photosynthesis using remote sensing data

Energy Technology Data Exchange (ETDEWEB)

Liu, J.; Chen, W.; Sarich, M. [Intermap Technologies Ltd., Nepean, ON (Canada); Cihlar, J. [Canada Centre for Remote Sensing, Ottawa, ON (Canada); Goulden, M. [California Univ., Irvine, CA (United States)

1998-06-01

Remote sensing to monitor the behaviour of terrestrial ecosystems over large areas was discussed. For this type of application the boreal ecosystem productivity simulator (BEPS) was developed, with the subsequent incorporation of the more advanced photosynthetic model. The new model improves the methodology through analytical spatial and temporal integration of canopy photosynthesis processes, and is suitable for regional remote sensing applications at moderate resolutions of 250 to 1000 m. 10 refs., 1 tab., 3 figs.

Study on fractal characteristics of remote sensing image in the typical volcanic uranium metallogenic areas

International Nuclear Information System (INIS)

Pan Wei; Ni Guoqiang; Li Hanbo

2010-01-01

Computing Methods of fractal dimension and multifractal spectrum about the remote sensing image are briefly introduced. The fractal method is used to study the characteristics of remote sensing images in Xiangshan and Yuhuashan volcanic uranium metallogenic areas in southern China. The research results indicate that the Xiangshan basin in which lots of volcanic uranium deposits occur,is of bigger fractal dimension based on remote sensing image texture than that of the Yuhuashan basin in which two uranium ore occurrences exist, and the multifractal spectrum in the Xiangshan basin obviously leans to less singularity index than in the Yuhuashan basin. The relation of the fractal dimension and multifractal singularity of remote sensing image to uranium metallogeny are discussed. The fractal dimension and multifractal singularity index of remote sensing image may be used to predict the volcanic uranium metallogenic areas. (authors)

Navigation and Remote Sensing Payloads and Methods of the Sarvant Unmanned Aerial System

Science.gov (United States)

Molina, P.; Fortuny, P.; Colomina, I.; Remy, M.; Macedo, K. A. C.; Zúnigo, Y. R. C.; Vaz, E.; Luebeck, D.; Moreira, J.; Blázquez, M.

2013-08-01

In a large number of scenarios and missions, the technical, operational and economical advantages of UAS-based photogrammetry and remote sensing over traditional airborne and satellite platforms are apparent. Airborne Synthetic Aperture Radar (SAR) or combined optical/SAR operation in remote areas might be a case of a typical "dull, dirty, dangerous" mission suitable for unmanned operation - in harsh environments such as for example rain forest areas in Brazil, topographic mapping of small to medium sparsely inhabited remote areas with UAS-based photogrammetry and remote sensing seems to be a reasonable paradigm. An example of such a system is the SARVANT platform, a fixed-wing aerial vehicle with a six-meter wingspan and a maximumtake- of-weight of 140 kilograms, able to carry a fifty-kilogram payload. SARVANT includes a multi-band (X and P) interferometric SAR payload, as the P-band enables the topographic mapping of densely tree-covered areas, providing terrain profile information. Moreover, the combination of X- and P-band measurements can be used to extract biomass estimations. Finally, long-term plan entails to incorporate surveying capabilities also at optical bands and deliver real-time imagery to a control station. This paper focuses on the remote-sensing concept in SARVANT, composed by the aforementioned SAR sensor and envisioning a double optical camera configuration to cover the visible and the near-infrared spectrum. The flexibility on the optical payload election, ranging from professional, medium-format cameras to mass-market, small-format cameras, is discussed as a driver in the SARVANT development. The paper also focuses on the navigation and orientation payloads, including the sensors (IMU and GNSS), the measurement acquisition system and the proposed navigation and orientation methods. The latter includes the Fast AT procedure, which performs close to traditional Integrated Sensor Orientation (ISO) and better than Direct Sensor Orientation (Di

Prospecting for coal in China with remote sensing

Energy Technology Data Exchange (ETDEWEB)

Ke-long Tan; Yu-qing Wan; Sun-xin Sun; Gui-bao Bao; Jing-shui Kuang [Aerophotogrammetry and Remote Sensing Center of China Coal, Xi' an (China)

2008-12-15

In China it is important to explore coal prospecting by taking advantage of modern remote sensing and geographic information system technologies. Given a theoretical basis for coal prospecting by remote sensing, the methodologies and existing problems are demonstrated systematically by summarizing past practices of coal prospecting with remote sensing. A new theory of coal prospecting with remote sensing is proposed. In uncovered areas, coal resources can be prospected by direct interpretation. In coal bearing strata of developed areas covered by thin Quaternary strata or vegetation, prospecting for coal can be carried out by indirect interpretation of geomorphology and vegetation. For deeply buried underground deposits, coal prospecting can rely on tectonic structures, interpretation and analysis of new tectonic clues and regularity of coal formation and preservation controlled by tectonic structures. By applying newly hyper-spectral, multi-polarization, multi-angle, multi-temporal and multi-resolution remote sensing data and carrying out integrated analysis of geographic attributes, ground attributes, geophysical exploration results, geochemical exploration results, geological drilling results and remote sensing data by GIS tools, coal geology resources and mineralogical regularities can be explored and coal resource information can be acquired with some confidence. 12 refs., 4 figs., 3 tabs.

Kite Aerial Photography as a Tool for Remote Sensing

Science.gov (United States)

Sallee, Jeff; Meier, Lesley R.

2010-01-01

As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

Physics teaching by infrared remote sensing of vegetation

Science.gov (United States)

Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

2018-05-01

Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.

National Satellite Land Remote Sensing Data Archive

Science.gov (United States)

Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

2013-01-01

The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

Remote sensing research in geographic education: An alternative view

Science.gov (United States)

Wilson, H.; Cary, T. K.; Goward, S. N.

1981-01-01

It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

Evaluation of Different Methods for Soil Classifications by Using Geographic Information Systems and Remote Sensing

Directory of Open Access Journals (Sweden)

S. H Sanaeinejad

2012-12-01

Full Text Available Soil salinity is an important factor that affects plant growth and reduces production of plantat different growth stages Remote sensing technology and GIS have a great potential for monitoring dynamic soil processes such as salinity. In the present study the efficiency of remote sensing technology and its integration with GIS was examined to estimate soil salinity for Neyshabour basin. Different classification methods for soil salinity were also investigated. We used 6 bands of LandSat ETM+ for this study. Classification results obtained from applying mathematical models for the images were compared with different band combinations results. The area of saline and non saline soil classes were identified in the study area based on the both methods and also based on the combination of the two methods. The results showed that the best method for soil classification was using of the two methods in the first stage to separate two classes of saline and non saline soils and then classifying the non saline soils in the second stage. As the variation in the numerical values of the image for different soil salinity in the study area was small, it was concluded that there is a limit potential of LandSat ETM+ images for identifying and classification of soil salinity in such an area.

METHOD OF GROUP OBJECTS FORMING FOR SPACE-BASED REMOTE SENSING OF THE EARTH

Directory of Open Access Journals (Sweden)

A. N. Grigoriev

2015-07-01

Full Text Available Subject of Research. Research findings of the specific application of space-based optical-electronic and radar means for the Earth remote sensing are considered. The subject matter of the study is the current planning of objects survey on the underlying surface in order to increase the effectiveness of sensing system due to the rational use of its resources. Method. New concept of a group object, stochastic swath and stochastic length of the route is introduced. The overview of models for single, group objects and their parameters is given. The criterion for the existence of the group object based on two single objects is formulated. The method for group objects formation while current survey planning has been developed and its description is presented. The method comprises several processing stages for data about objects with the calculation of new parameters, the stochastic characteristics of space means and validates the spatial size of the object value of the stochastic swath and stochastic length of the route. The strict mathematical description of techniques for model creation of a group object based on data about a single object and onboard special complex facilities in difficult conditions of registration of spatial data is given. Main Results. The developed method is implemented on the basis of modern geographic information system in the form of a software tool layout with advanced tools of processing and analysis of spatial data in vector format. Experimental studies of the forming method for the group of objects were carried out on a different real object environment using the parameters of modern national systems of the Earth remote sensing detailed observation Canopus-B and Resurs-P. Practical Relevance. The proposed models and method are focused on practical implementation using vector spatial data models and modern geoinformation technologies. Practical value lies in the reduction in the amount of consumable resources by means of

Hydrologic Remote Sensing and Land Surface Data Assimilation

Directory of Open Access Journals (Sweden)

Hamid Moradkhani

2008-05-01

Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

History and future of remote sensing technology and education

Science.gov (United States)

Colwell, R. N.

1980-01-01

A historical overview of the discovery and development of photography, related sciences, and remote sensing technology is presented. The role of education to date in the development of remote sensing is discussed. The probable future and potential of remote sensing and training is described.

Remote Sensing of Mangrove Ecosystems: A Review

Directory of Open Access Journals (Sweden)

Stefan Dech

2011-04-01

Full Text Available Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high- and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove

[Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing].

Science.gov (United States)

Wang, Li-Wen; Wei, Ya-Xing

2013-10-01

Nitrogen is the necessary element in life activity of vegetation, which takes important function in biosynthesis of protein, nucleic acid, chlorophyll, and enzyme etc, and plays a key role in vegetation photosynthesis. The technology about inversion of vegetation nitrogen concentration by hyperspectral remote sensing has been the research hotspot since the 70s of last century. With the development of hyperspectral remote sensing technology in recent years, the advantage of spectral bands subdivision in a certain spectral region provides the powerful technology measure for correlative spectral characteristic research on vegetation nitrogen. In the present paper, combined with the newest research production about monitoring vegetation nitrogen concentration by hyperspectral remote sensing published in main geography science literature in recent several years, the principle and correlated problem about monitoring vegetation nitrogen concentration by hyperspectral remote sensing were introduced. From four aspects including vegetation nitrogen spectral index, vegetation nitrogen content inversion based on chlorophyll index, regression model, and eliminating influence factors to inversion of vegetation nitrogen concentration, main technology methods about inversion of vegetation nitrogen concentration by hyperspectral remote sensing were detailedly introduced. Correlative research conclusions were summarized and analyzed, and research development trend was discussed.

Remote sensing for vineyard management

Science.gov (United States)

Philipson, W. R.; Erb, T. L.; Fernandez, D.; Mcleester, J. N.

1980-01-01

Cornell's Remote Sensing Program has been involved in a continuing investigation to assess the value of remote sensing for vineyard management. Program staff members have conducted a series of site and crop analysis studies. These include: (1) panchromatic aerial photography for planning artificial drainage in a new vineyard; (2) color infrared aerial photography for assessing crop vigor/health; and (3) color infrared aerial photography and aircraft multispectral scanner data for evaluating yield related factors. These studies and their findings are reviewed.

Researching on the process of remote sensing video imagery

Science.gov (United States)

Wang, He-rao; Zheng, Xin-qi; Sun, Yi-bo; Jia, Zong-ren; Wang, He-zhan

Unmanned air vehicle remotely-sensed imagery on the low-altitude has the advantages of higher revolution, easy-shooting, real-time accessing, etc. It's been widely used in mapping , target identification, and other fields in recent years. However, because of conditional limitation, the video images are unstable, the targets move fast, and the shooting background is complex, etc., thus it is difficult to process the video images in this situation. In other fields, especially in the field of computer vision, the researches on video images are more extensive., which is very helpful for processing the remotely-sensed imagery on the low-altitude. Based on this, this paper analyzes and summarizes amounts of video image processing achievement in different fields, including research purposes, data sources, and the pros and cons of technology. Meantime, this paper explores the technology methods more suitable for low-altitude video image processing of remote sensing.

SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

Science.gov (United States)

The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was

Noise estimation for remote sensing image data analysis

Science.gov (United States)

Du, Qian

2004-01-01

Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

Science.gov (United States)

Musick, H. Brad

1993-01-01

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Hyperspectral remote sensing for light pollution monitoring

Directory of Open Access Journals (Sweden)

P. Marcoionni

2006-06-01

Full Text Available industries. In this paper we introduce the results from a remote sensing campaign performed in September 2001 at night time. For the first time nocturnal light pollution was measured at high spatial and spectral resolution using two airborne hyperspectral sensors, namely the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS and the Visible InfraRed Scanner (VIRS-200. These imagers, generally employed for day-time Earth remote sensing, were flown over the Tuscany coast (Italy on board of a Casa 212/200 airplane from an altitude of 1.5-2.0 km. We describe the experimental activities which preceded the remote sensing campaign, the optimization of sensor configuration, and the images as far acquired. The obtained results point out the novelty of the performed measurements and highlight the need to employ advanced remote sensing techniques as a spectroscopic tool for light pollution monitoring.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

Science.gov (United States)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at

Use of microwave remote sensing in salinity estimation

International Nuclear Information System (INIS)

Singh, R.P.; Kumar, V.; Srivastav, S.K.

1990-01-01

Soil-moisture interaction and the consequent liberation of ions causes the salinity of waters. The salinity of river, lake, ocean and ground water changes due to seepage and surface runoff. We have studied the feasibility of using microwave remote sensing for the estimation of salinity by carrying out numerical calculations to study the microwave remote sensing responses of various models representative of river, lake and ocean water. The results show the dependence of microwave remote sensing responses on the salinity and surface temperature of water. The results presented in this paper will be useful in the selection of microwave sensor parameters and in the accurate estimation of salinity from microwave remote sensing data

Remote sensing of environmental pollution on teesside

NARCIS (Netherlands)

van Genderen, J.L.

1974-01-01

A preliminary reconnaissance is being carried out to study the methods and procedures most useful for the detection of vegetation stress resulting from the various forms of environmental pollution, in the industrial area of Teesside, NE England, by means of a multiband remote sensing programme.

Online catalog access and distribution of remotely sensed information

Science.gov (United States)

Lutton, Stephen M.

1997-09-01

Remote sensing is providing voluminous data and value added information products. Electronic sensors, communication electronics, computer software, hardware, and network communications technology have matured to the point where a distributed infrastructure for remotely sensed information is a reality. The amount of remotely sensed data and information is making distributed infrastructure almost a necessity. This infrastructure provides data collection, archiving, cataloging, browsing, processing, and viewing for applications from scientific research to economic, legal, and national security decision making. The remote sensing field is entering a new exciting stage of commercial growth and expansion into the mainstream of government and business decision making. This paper overviews this new distributed infrastructure and then focuses on describing a software system for on-line catalog access and distribution of remotely sensed information.

Review of research on remote sensing with digital map. Remote sensing to suchi chizu no ketsugo ni yoru kenkyu no shokai

Energy Technology Data Exchange (ETDEWEB)

Tanaka, S; Sugimura, T [Remote Sensing Technology Center of Japan, Tokyo (Japan)

1990-12-05

This paper describes the relationship between remote sensing and digital map. The relation between remote sensing and digital map is roughly classified into two kinds. One of them is utilization of remote sensing and digital map in combination to analyze phenomena, and the other is normalization of remote sensing data by use of digital map. For examples of utilizing remote sensing and digital map, there are the creation of a perspective image of ground scene from Landsat MSS data by use of a mesh type digital map of the orthogonal co-ordinates, and the creation of an image of the enviromental research along roads from satilite data by use of a vector type digital map. Furthermore, this paper introduces a procedure of correcting geographical strains by use of a digital map and converting a radar image to corrected plane image, and the use of a digital map in the global scale for the analysis of floods and other purposes. 20 refs., 5 figs., 1 tab.

Information operator approach and iterative regularization methods for atmospheric remote sensing

International Nuclear Information System (INIS)

Doicu, A.; Hilgers, S.; Bargen, A. von; Rozanov, A.; Eichmann, K.-U.; Savigny, C. von; Burrows, J.P.

2007-01-01

In this study, we present the main features of the information operator approach for solving linear inverse problems arising in atmospheric remote sensing. This method is superior to the stochastic version of the Tikhonov regularization (or the optimal estimation method) due to its capability to filter out the noise-dominated components of the solution generated by an inappropriate choice of the regularization parameter. We extend this approach to iterative methods for nonlinear ill-posed problems and derive the truncated versions of the Gauss-Newton and Levenberg-Marquardt methods. Although the paper mostly focuses on discussing the mathematical details of the inverse method, retrieval results have been provided, which exemplify the performances of the methods. These results correspond to the NO 2 retrieval from SCIAMACHY limb scatter measurements and have been obtained by using the retrieval processors developed at the German Aerospace Center Oberpfaffenhofen and Institute of Environmental Physics of the University of Bremen

Remote sensing in operational range management programs in Western Canada

Science.gov (United States)

Thompson, M. D.

1977-01-01

A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.

Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

Directory of Open Access Journals (Sweden)

TAO Feixiang

2015-08-01

Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

Optical Remote Sensing Laboratory

Data.gov (United States)

Federal Laboratory Consortium — The Optical Remote Sensing Laboratory deploys rugged, cutting-edge electro-optical instrumentation for the collection of various event signatures, with expertise in...

Development of a mobile robot for remote radiation measurement

International Nuclear Information System (INIS)

Sarkar, Ushnish; Saini, Surendra Singh; Swaroop, Tumapala Teja; Sreejith, P.; Kumar, Ravinder; Ray, Debasish Datta

2016-01-01

Remote measurement of radiation using mobile robots is recommended in nuclear installations. For this purpose various robots have been developed that carry a radiation sensor. However since the robot has to go very near to the source of radiation, the life of the robot's components is compromised due to high level of absorbed dose. It was earlier managed to increase the life expectancy of remote radiation measurement robots by allowing the sensor to be placed on an extendable telescopic assembly; analogous to a health physicist taking measurements using a Teletector. The first prototype developed had stair climbing capabilities but it was found to be over dimensioned for various potential applications. A significant use of such robots is in taking measurements at nuclear reprocessing facilities having narrow cluttered pathways. This required development of a new version of the robot capable of negotiating the narrow pathways of such facilities. This paper describes the different aspects of the development of the mobile robot system with flexible radiation sensing capabilities

Current NASA Earth Remote Sensing Observations

Science.gov (United States)

Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin;

Geological remote sensing signatures of terrestrial impact craters

International Nuclear Information System (INIS)

Garvin, J.B.; Schnetzler, C.; Grieve, R.A.F.

1988-01-01

Geological remote sensing techniques can be used to investigate structural, depositional, and shock metamorphic effects associated with hypervelocity impact structures, some of which may be linked to global Earth system catastrophies. Although detailed laboratory and field investigations are necessary to establish conclusive evidence of an impact origin for suspected crater landforms, the synoptic perspective provided by various remote sensing systems can often serve as a pathfinder to key deposits which can then be targetted for intensive field study. In addition, remote sensing imagery can be used as a tool in the search for impact and other catastrophic explosion landforms on the basis of localized disruption and anomaly patterns. In order to reconstruct original dimensions of large, complex impact features in isolated, inaccessible regions, remote sensing imagery can be used to make preliminary estimates in the absence of field geophysical surveys. The experienced gained from two decades of planetary remote sensing of impact craters on the terrestrial planets, as well as the techniques developed for recognizing stages of degradation and initial crater morphology, can now be applied to the problem of discovering and studying eroded impact landforms on Earth. Preliminary results of remote sensing analyses of a set of terrestrial impact features in various states of degradation, geologic settings, and for a broad range of diameters and hence energies of formation are summarized. The intention is to develop a database of remote sensing signatures for catastrophic impact landforms which can then be used in EOS-era global surveys as the basis for locating the possibly hundreds of missing impact structures

Accuracy Dimensions in Remote Sensing

Science.gov (United States)

Barsi, Á.; Kugler, Zs.; László, I.; Szabó, Gy.; Abdulmutalib, H. M.

2018-04-01

The technological developments in remote sensing (RS) during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS), which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users' needs. The present paper gives the theoretic overview of the issue, besides selected, practice

ACCURACY DIMENSIONS IN REMOTE SENSING

Directory of Open Access Journals (Sweden)

Á. Barsi

2018-04-01

Full Text Available The technological developments in remote sensing (RS during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS, which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users’ needs. The present paper gives the theoretic overview of the issue, besides

Optical/Infrared Signatures for Space-Based Remote Sensing

National Research Council Canada - National Science Library

Picard, R. H; Dewan, E. M; Winick, J. R; O'Neil, R. R

2007-01-01

This report describes work carried out under the Air Force Research Laboratory's basic research task in optical remote-sensing signatures, entitled Optical / Infrared Signatures for Space-Based Remote Sensing...

New advance in the research of post-remote sensing application technology. Series of 'proposition and consideration of post-remote sensing application technology'

International Nuclear Information System (INIS)

Liu Dechang; Ye Fawang

2005-01-01

Based on deep consideration in post-remote sensing application technology, this article pays more attention to its technological meaning. The application idea of post-remote sensing application technology to uranium exploration is also discussed. The proposition and research on new concept of post-remote sensing application technology is an important search and of important theoretical and practical significance to uranium exploration. (authors)

An Overview on Data Mining of Nighttime Light Remote Sensing

Directory of Open Access Journals (Sweden)

LI Deren

2015-06-01

Full Text Available When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future

Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States

Science.gov (United States)

Reitz, Meredith; Senay, Gabriel; Sanford, Ward E.

2017-01-01

Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.

Comprehensive, integrated, remote sensing at DOE sites

International Nuclear Information System (INIS)

Lackey, J.G.; Burson, Z.G.

1985-01-01

The Department of Energy has established a program called Comprehensive, Integrated Remote Sensing (CIRS). The overall objective of the program is to provide a state-of-the-art data base of remotely sensed data for all users of such information at large DOE sites. The primary types of remote sensing provided, at present, consist of the following: large format aerial photography, video from aerial platforms, multispectral scanning, and airborne nuclear radiometric surveys. Implementation of the CIRS Program by EG and G Energy Measurements, Inc. began with field operations at the Savannah River Plant in 1982 and is continuing at that DOE site at a level of effort of about $1.5 m per year. Integrated remote sensing studies were subsequently extended to the West Valley Demonstration Project in this summer and fall of 1984. It is expected that the Program will eventually be extended to cover all large DOE sites on a continuing basis

Polarimetric Remote Sensing of Atmospheric Particulate Pollutants

Science.gov (United States)

Li, Z.; Zhang, Y.; Hong, J.

2018-04-01

Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF), whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

Overview of the Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08): A field experiment evaluating methods for quantifying ET at multiple scales

Science.gov (United States)

Evett, Steven R.; Kustas, William P.; Gowda, Prasanna H.; Anderson, Martha C.; Prueger, John H.; Howell, Terry A.

2012-12-01

In 2008, scientists from seven federal and state institutions worked together to investigate temporal and spatial variations of evapotranspiration (ET) and surface energy balance in a semi-arid irrigated and dryland agricultural region of the Southern High Plains in the Texas Panhandle. This Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08) involved determination of micrometeorological fluxes (surface energy balance) in four weighing lysimeter fields (each 4.7 ha) containing irrigated and dryland cotton and in nearby bare soil, wheat stubble and rangeland fields using nine eddy covariance stations, three large aperture scintillometers, and three Bowen ratio systems. In coordination with satellite overpasses, flux and remote sensing aircraft flew transects over the surrounding fields and region encompassing an area contributing fluxes from 10 to 30 km upwind of the USDA-ARS lysimeter site. Tethered balloon soundings were conducted over the irrigated fields to investigate the effect of advection on local boundary layer development. Local ET was measured using four large weighing lysimeters, while field scale estimates were made by soil water balance with a network of neutron probe profile water sites and from the stationary flux systems. Aircraft and satellite imagery were obtained at different spatial and temporal resolutions. Plot-scale experiments dealt with row orientation and crop height effects on spatial and temporal patterns of soil surface temperature, soil water content, soil heat flux, evaporation from soil in the interrow, plant transpiration and canopy and soil radiation fluxes. The BEAREX08 field experiment was unique in its assessment of ET fluxes over a broad range in spatial scales; comparing direct and indirect methods at local scales with remote sensing based methods and models using aircraft and satellite imagery at local to regional scales, and comparing mass balance-based ET ground truth with eddy covariance

Preface to: Pan Ocean Remote Sensing Conference (PORSEC)

Digital Repository Service at National Institute of Oceanography (India)

Desa, E.; Brown, R.; Shenoi, S.S.C.; Joseph, G.

Conference (PORSEC), earlier known as the Paci c Ocean Remote Sensing Conference (PORSEC), was formed in 1992 to provide a venue for international cooperation in the increasingly important area of remote sensing of the ocean. Many countries that border... and ocean dynamics, and modeling with satellite sensor (mainly microwave) data. Some of the presentations are of regional interest, while others will nd an audience beyond the satellite remote sensing community. These rst results through their simple...

Remote Sensing: Physics And Environmental Applications

International Nuclear Information System (INIS)

EI Raey, M.

2007-01-01

Full text: Basic principles of remote sensing of environment are outlined emphasizing inherent physical and target properties leading to proper identification and classification. Basic processing techniques are discussed. Applications of remote sensing techniques in various aspects of environmental monitoring and assessment is surveyed with emphasis on aspects of main concern to developing communities such as planning, sea level impacts, mine detection and earthquake prediction are all outlined and discussed

Freeware for GIS and Remote Sensing

OpenAIRE

Lena Halounová

2007-01-01

Education in remote sensing and GIS is based on software utilization. The software needs to be installed in computer rooms with a certain number of licenses. The commercial software equipment is therefore financially demanding and not only for universities, but especially for students. Internet research brings a long list of free software of various capabilities. The paper shows a present state of GIS, image processing and remote sensing free software.

Portable remote sensing image processing system; Kahangata remote sensing gazo shori system

Energy Technology Data Exchange (ETDEWEB)

Fujikawa, S; Uchida, K; Tanaka, S; Jingo, H [Dowa Engineering Co. Ltd., Tokyo (Japan); Hato, M [Earth Remote Sensing Data Analysis Center, Tokyo (Japan)

1997-10-22

Recently, geological analysis using remote sensing data has been put into practice due to data with high spectral resolution and high spatial resolution. There has been a remarkable increase in both software and hardware of personal computer. Software is independent of hardware due to Windows. It has become easy to develop softwares. Under such situation, a portable remote sensing image processing system coping with Window 95 has been developed. Using this system, basic image processing can be conducted, and present location can be displayed on the image in real time by linking with GPS. Accordingly, it is not required to bring printed images for the field works of image processing. This system can be used instead of topographic maps for overseas surveys. Microsoft Visual C++ ver. 2.0 is used for the software. 1 fig.

Remote sensing terminology: past experience and recent needs

Science.gov (United States)

Kancheva, Rumiana

2013-10-01

Terminology is a key issue for a better understanding among people using various languages. Terminology accuracy is essential during all phases of international cooperation. It is crucial to keep up with the latest quantitative and qualitative developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have wide and ever extending applications in various domains of human activity. The importance of the correct use of remote sensing terms refers not only to people working in this field but also to experts in many disciplines who handle remote sensing data and information products. The paper is devoted to terminology issues that refer to all aspects of remote sensing research and application areas. The attention is drawn on the recent needs and peculiarities of compiling specialized dictionaries in the subject area of remote sensing. Details are presented about the work in progress on the preparation of an English-Bulgarian dictionary of remote sensing terms focusing on Earth observations and geoinformation science. Our belief is that the elaboration of bilingual and multilingual dictionaries and glossaries in this spreading, most technically advanced and promising field of human expertise is of great practical importance. Any interest in cooperation and initiating of suchlike collaborative multilingual projects is welcome and highly appreciated.

Airplane detection in remote sensing images using convolutional neural networks

Science.gov (United States)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Spectral reflectance of carbonate sediments and application to remote sensing classification of benthic habitats

Science.gov (United States)

Louchard, Eric Michael

Remote sensing is a valuable tool in marine research that has advanced to the point that images from shallow waters can be used to identify different seafloor types and create maps of benthic habitats. A major goal of this dissertation is to examine differences in spectral reflectance and create new methods of analyzing shallow water remote sensing data to identify different seafloor types quickly and accurately. Carbonate sediments were used as a model system as they presented a relatively uniform, smooth surface for measurement and are a major bottom type in tropical coral reef systems. Experimental results found that sediment reflectance varied in shape and magnitude depending on pigment content, but only varied in magnitude with variations in grain size and shape. Derivative analysis of the reflectance spectra identified wavelength regions that correlate to chlorophyll a and chlorophyllide a as well as accessory pigments, indicating differences in microbial community structure. Derivative peak height also correlated to pigment content in the sediments. In remote sensing data, chlorophyll a, chlorophyllide a, and some xanthophylls were identified in derivative spectra and could be quantified from second derivative peak height. Most accessory pigments were attenuated by the water column, however, and could not be used to quantify pigments in sediments from remote sensing images. Radiative transfer modeling of remote sensing reflectance showed that there was sufficient spectral variation to separate major sediment types, such as ooid shoals and sediment with microbial layers, from different densities of seagrass and pavement bottom communities. Both supervised classification with a spectral library and unsupervised classification with principal component analysis were used to create maps of seafloor type. The results of the experiments were promising; classified seafloor types correlated with ground truth observations taken from underwater video and were

Proceedings of the eighth thematic conference on geologic remote sensing

International Nuclear Information System (INIS)

Balmer, M.L.; Lange, F.F.; Levi, C.G.

1991-01-01

These proceedings contain papers presented at the Eighth Thematic Conference on Geologic Remote Sensing. This meeting was held April 29-May 2, 1991, in Denver, Colorado, USA. The conference was organized by the Environmental Research Institute of Michigan, in Cooperation with an international program committee composed primarily of geologic remote sensing specialists. The meeting was convened to discuss state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing as well as research and development activities aimed at increasing the future capabilities of this technology. The presentations in these volumes address the following topics: Spectral Geology; U.S. and International Hydrocarbon Exploration; Radar and Thermal Infrared Remote Sensing; Engineering Geology and Hydrogeology; Minerals Exploration; Remote Sensing for Marine and Environmental Applications; Image Processing and Analysis; Geobotanical Remote Sensing; Data Integration and Geographic Information Systems

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

Science.gov (United States)

Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

2014-11-01

The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product

INTERACTIVE CHANGE DETECTION USING HIGH RESOLUTION REMOTE SENSING IMAGES BASED ON ACTIVE LEARNING WITH GAUSSIAN PROCESSES

Directory of Open Access Journals (Sweden)

H. Ru

2016-06-01

Full Text Available Although there have been many studies for change detection, the effective and efficient use of high resolution remote sensing images is still a problem. Conventional supervised methods need lots of annotations to classify the land cover categories and detect their changes. Besides, the training set in supervised methods often has lots of redundant samples without any essential information. In this study, we present a method for interactive change detection using high resolution remote sensing images with active learning to overcome the shortages of existing remote sensing image change detection techniques. In our method, there is no annotation of actual land cover category at the beginning. First, we find a certain number of the most representative objects in unsupervised way. Then, we can detect the change areas from multi-temporal high resolution remote sensing images by active learning with Gaussian processes in an interactive way gradually until the detection results do not change notably. The artificial labelling can be reduced substantially, and a desirable detection result can be obtained in a few iterations. The experiments on Geo-Eye1 and WorldView2 remote sensing images demonstrate the effectiveness and efficiency of our proposed method.

Autonomous Coral Reef Survey in Support of Remote Sensing

Directory of Open Access Journals (Sweden)

Steven G. Ackleson

2017-10-01

Full Text Available An autonomous surface vehicle instrumented with optical and acoustical sensors was deployed in Kane'ohe Bay, HI, U.S.A., to provide high-resolution, in situ observations of coral reef reflectance with minimal human presence. The data represented a wide range in bottom type, water depth, and illumination and supported more thorough investigations of remote sensing methods for identifying and mapping shallow reef features. The in situ data were used to compute spectral bottom reflectance and remote sensing reflectance, Rrs,λ, as a function of water depth and benthic features. The signals were used to distinguish between live coral and uncolonized sediment within the depth range of the measurements (2.5–5 m. In situRrs, λ were found to compare well with remotely sensed measurements from an imaging spectrometer, the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS, deployed on an aircraft at high altitude. Cloud cover and in situ sensor orientation were found to have minimal impact on in situRrs, λ, suggesting that valid reflectance data may be collected using autonomous surveys even when atmospheric conditions are not favorable for remote sensing operations. The use of reflectance in the red and near infrared portions of the spectrum, expressed as the red edge height, REHλ, was investigated for detecting live aquatic vegetative biomass, including coral symbionts and turf algae. The REHλ signal from live coral was detected in Kane'ohe Bay to a depth of approximately 4 m with in situ measurements. A remote sensing algorithm based on the REHλ signal was defined and applied to AVIRIS imagery of the entire bay and was found to reveal areas of shallow, dense coral and algal cover. The peak wavelength of REHλ decreased with increasing water depth, indicating that a more complete examination of the red edge signal may potentially yield a remote sensing approach to simultaneously estimate vegetative biomass and bathymetry in shallow water.

Remote Sensing Image in the Application of Agricultural Tourism Planning

Directory of Open Access Journals (Sweden)

Guojing Fan

2013-06-01

Full Text Available This paper introduces the processing technology of high resolution remote sensing image, the specific making process of tourism map and different remote sensing data in the key application of tourism planning and so on. Remote sensing extracts agricultural tourism planning information, improving the scientificalness and operability of agricultural tourism planning. Therefore remote sensing image in the application of agricultural tourism planning will be the inevitable trend of tourism development.

Coastal remote sensing – towards integrated coastal research and management

CSIR Research Space (South Africa)

Lück-Vogel, Melanie

2012-10-01

Full Text Available coastal resources and anthropogenic infrastructure for a safer future. What is the role of remote sensing? The coastal zone connects terrestrial biophysical systems with marine systems. Some marine ecosystems cannot function without intact inland... for the development of sound integrated management solutions. To date, however, remote sensing applications usually focus on areas landward from the highwater line (?terrestrial? remote sensing), while ?marine? remote sensing does not pay attention to the shallow...

Forest structural assessment using remote sensing technologies: an ...

African Journals Online (AJOL)

-Natal and MONDI Business Paper have recently embarked on a remote sensing cooperative. The primary focus of this cooperative is to explore the potential benefits associated with using remote sensing for forestry-related activities.

Study on the construction of multi-dimensional Remote Sensing feature space for hydrological drought

International Nuclear Information System (INIS)

Xiang, Daxiang; Tan, Debao; Wen, Xiongfei; Shen, Shaohong; Li, Zhe; Cui, Yuanlai

2014-01-01

Hydrological drought refers to an abnormal water shortage caused by precipitation and surface water shortages or a groundwater imbalance. Hydrological drought is reflected in a drop of surface water, decrease of vegetation productivity, increase of temperature difference between day and night and so on. Remote sensing permits the observation of surface water, vegetation, temperature and other information from a macro perspective. This paper analyzes the correlation relationship and differentiation of both remote sensing and surface measured indicators, after the selection and extraction a series of representative remote sensing characteristic parameters according to the spectral characterization of surface features in remote sensing imagery, such as vegetation index, surface temperature and surface water from HJ-1A/B CCD/IRS data. Finally, multi-dimensional remote sensing features such as hydrological drought are built on a intelligent collaborative model. Further, for the Dong-ting lake area, two drought events are analyzed for verification of multi-dimensional features using remote sensing data with different phases and field observation data. The experiments results proved that multi-dimensional features are a good method for hydrological drought

Digitise this! A quick and easy remote sensing method to monitor the daily extent of dredge plumes.

Directory of Open Access Journals (Sweden)

Richard D Evans

Full Text Available Technological advancements in remote sensing and GIS have improved natural resource managers' abilities to monitor large-scale disturbances. In a time where many processes are heading towards automation, this study has regressed to simple techniques to bridge a gap found in the advancement of technology. The near-daily monitoring of dredge plume extent is common practice using Moderate Resolution Imaging Spectroradiometer (MODIS imagery and associated algorithms to predict the total suspended solids (TSS concentration in the surface waters originating from floods and dredge plumes. Unfortunately, these methods cannot determine the difference between dredge plume and benthic features in shallow, clear water. This case study at Barrow Island, Western Australia, uses hand digitising to demonstrate the ability of human interpretation to determine this difference with a level of confidence and compares the method to contemporary TSS methods. Hand digitising was quick, cheap and required very little training of staff to complete. Results of ANOSIM R statistics show remote sensing derived TSS provided similar spatial results if they were thresholded to at least 3 mg L(-1. However, remote sensing derived TSS consistently provided false-positive readings of shallow benthic features as Plume with a threshold up to TSS of 6 mg L(-1, and began providing false-negatives (excluding actual plume at a threshold as low as 4 mg L(-1. Semi-automated processes that estimate plume concentration and distinguish between plumes and shallow benthic features without the arbitrary nature of human interpretation would be preferred as a plume monitoring method. However, at this stage, the hand digitising method is very useful and is more accurate at determining plume boundaries over shallow benthic features and is accessible to all levels of management with basic training.

Remote Sensing Information Science Research

Science.gov (United States)

Clarke, Keith C.; Scepan, Joseph; Hemphill, Jeffrey; Herold, Martin; Husak, Gregory; Kline, Karen; Knight, Kevin

2002-01-01

This document is the final report summarizing research conducted by the Remote Sensing Research Unit, Department of Geography, University of California, Santa Barbara under National Aeronautics and Space Administration Research Grant NAG5-10457. This document describes work performed during the period of 1 March 2001 thorough 30 September 2002. This report includes a survey of research proposed and performed within RSRU and the UCSB Geography Department during the past 25 years. A broad suite of RSRU research conducted under NAG5-10457 is also described under themes of Applied Research Activities and Information Science Research. This research includes: 1. NASA ESA Research Grant Performance Metrics Reporting. 2. Global Data Set Thematic Accuracy Analysis. 3. ISCGM/Global Map Project Support. 4. Cooperative International Activities. 5. User Model Study of Global Environmental Data Sets. 6. Global Spatial Data Infrastructure. 7. CIESIN Collaboration. 8. On the Value of Coordinating Landsat Operations. 10. The California Marine Protected Areas Database: Compilation and Accuracy Issues. 11. Assessing Landslide Hazard Over a 130-Year Period for La Conchita, California Remote Sensing and Spatial Metrics for Applied Urban Area Analysis, including: (1) IKONOS Data Processing for Urban Analysis. (2) Image Segmentation and Object Oriented Classification. (3) Spectral Properties of Urban Materials. (4) Spatial Scale in Urban Mapping. (5) Variable Scale Spatial and Temporal Urban Growth Signatures. (6) Interpretation and Verification of SLEUTH Modeling Results. (7) Spatial Land Cover Pattern Analysis for Representing Urban Land Use and Socioeconomic Structures. 12. Colorado River Flood Plain Remote Sensing Study Support. 13. African Rainfall Modeling and Assessment. 14. Remote Sensing and GIS Integration.

Freeware for GIS and Remote Sensing

Directory of Open Access Journals (Sweden)

Lena Halounová

2007-12-01

Full Text Available Education in remote sensing and GIS is based on software utilization. The software needs to be installed in computer rooms with a certain number of licenses. The commercial software equipment is therefore financially demanding and not only for universities, but especially for students. Internet research brings a long list of free software of various capabilities. The paper shows a present state of GIS, image processing and remote sensing free software.

Remote Sensing Image Registration with Line Segments and Their Intersections

Directory of Open Access Journals (Sweden)

Chengjin Lyu

2017-05-01

Full Text Available Image registration is a basic but essential step for remote sensing image processing, and finding stable features in multitemporal images is one of the most considerable challenges in the field. The main shape contours of artificial objects (e.g., roads, buildings, farmlands, and airports can be generally described as a group of line segments, which are stable features, even in images with evident background changes (e.g., images taken before and after a disaster. In this study, a registration method that uses line segments and their intersections is proposed for multitemporal remote sensing images. First, line segments are extracted in image pyramids to unify the scales of the reference image and the test image. Then, a line descriptor based on the gradient distribution of local areas is constructed, and the segments are matched in image pyramids. Lastly, triplets of intersections of matching lines are selected to estimate affine transformation between two images. Additional corresponding intersections are provided based on the estimated transformation, and an iterative process is adopted to remove outliers. The performance of the proposed method is tested on a variety of optical remote sensing image pairs, including synthetic and real data. Compared with existing methods, our method can provide more accurate registration results, even in images with significant background changes.

Remote sensing programs and courses in engineering and water resources

Science.gov (United States)

Kiefer, R. W.

1981-01-01

The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.

Ground-based Polarization Remote Sensing of Atmospheric Aerosols and the Correlation between Polarization Degree and PM2.5

International Nuclear Information System (INIS)

Cheng, Chen; Zhengqiang, Li; Weizhen, Hou; Yisong, Xie; Donghui, Li; Kaitao, Li; Ying, Zhang

2014-01-01

The ground-based polarization remote sensing adds the polarization dimension information to traditional intensity detection, which provides a new method to detect atmospheric aerosols properties. In this paper, the polarization measurements achieved by a new multi-wavelength sun photometer, CE318-DP, are used for the ground-based remote sensing of atmospheric aerosols. In addition, a polarized vector radiative transfer model is introduced to simulate the DOLP (Degree Of Linear Polarization) under different sky conditions. At last, the correlative analysis between mass density of PM 2.5 and multi-wavelength and multi-angular DOLP is carried out. The result shows that DOLP has a high correlation with mass density of PM 2.5 , R 2 >0.85. As a consequence, this work provides a new method to estimate the mass density of PM 2.5 by using the comprehensive network of ground-based sun photometer

The role of satellite remote sensing in structured ecosystem risk assessments.

Science.gov (United States)

Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

2018-04-01

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

Satellite Remote Sensing for Coastal Management: A Review of Successful Applications.

Science.gov (United States)

McCarthy, Matthew J; Colna, Kaitlyn E; El-Mezayen, Mahmoud M; Laureano-Rosario, Abdiel E; Méndez-Lázaro, Pablo; Otis, Daniel B; Toro-Farmer, Gerardo; Vega-Rodriguez, Maria; Muller-Karger, Frank E

2017-08-01

Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.

Satellite Remote Sensing for Coastal Management: A Review of Successful Applications

Science.gov (United States)

McCarthy, Matthew J.; Colna, Kaitlyn E.; El-Mezayen, Mahmoud M.; Laureano-Rosario, Abdiel E.; Méndez-Lázaro, Pablo; Otis, Daniel B.; Toro-Farmer, Gerardo; Vega-Rodriguez, Maria; Muller-Karger, Frank E.

2017-08-01

Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.

Project THEMIS: A Center for Remote Sensing.

Science.gov (United States)

This report summarizes the technical work accomplished under Project THEMIS, A Center for Remote Sensing at the University of Kansas during the...period 16 September 1967 through 15 September 1973. The highlights of the four major areas forming the remote sensing system are presented. A detailed description of the latest radar spectrometer results is presented.

Remote sensing and eLearning 2.0 for school education

Science.gov (United States)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2010-10-01

The "Remote Sensing in Schools" project aims at improving the integration of "Satellite remote sensing" into school teaching. Therefore, it is the project's overall objective to teach students in primary and secondary schools the basics and fields of application of remote sensing. Existing results show that many teachers are interested in remote sensing and at same time motivated to integrate it into their teaching. Despite the good intention, in the end, the implementation often fails due to the complexity and poor set-up of the information provided. Therefore, a comprehensive and well-structured learning platform on the topic of remote sensing is developed. The platform shall allow a structured introduction to the topic.

Remote Sensing of the Heliospheric Solar Wind using Radio ...

Indian Academy of Sciences (India)

tribpo

Astr. (2000) 21, 439–444. Remote Sensing of the Heliospheric Solar Wind using Radio. Astronomy Methods and Numerical Simulations. S. Ananthakrishnan, National Center for Radio Astrophysics, Tata Institute of. Fundamental Research, Pune, India. Abstract. The ground-based radio astronomy method of interplanetary.

POLARIMETRIC REMOTE SENSING OF ATMOSPHERIC PARTICULATE POLLUTANTS

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Z. Li

2018-04-01

Full Text Available Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF, whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

An overview of remote sensing of chlorophyll fluorescence

Science.gov (United States)

Xing, Xiao-Gang; Zhao, Dong-Zhi; Liu, Yu-Guang; Yang, Jian-Hong; Xiu, Peng; Wang, Lin

2007-03-01

Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyl l - a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.

Remote sensing techniques and their urgency for snow and glacier mapping in Himalayas

Energy Technology Data Exchange (ETDEWEB)

Das, M C; Chattopadhyay, S N; Murty, A S

1979-01-01

The mighty Himalayas are great repositories of snow and ice. The river system of Indus, the Ganges and Brahmaputra owe their perennial flow to these large snow and ice masses. The demand for systematic exploitation of water resources of these great mountain ranges calls for a thorough inventory of these water-holding bodies. Rough and difficult terrain, inclement weather and very inaccessible altitudes stood in the way for better understanding of these vast sources of life giving water. In this paper, the urgency for snow and glacier mapping of this Himalayan region is highlighted in the light of the fast evolving techniques of remote sensing. Aerospace photography, use of radars and infrared sensing methods microwave sensing, and application of gamma radiation with the help of satellites, are examined for their present status and future potential for application in this ice and snow capped, top of the world.

Application of remote sensing methods and GIS in erosive process investigations

Directory of Open Access Journals (Sweden)

Mustafić Sanja

2007-01-01

Full Text Available Modern geomorphologic investigations of condition and change of the intensity of erosive process should be based on application of remote sensing methods which are based on processing of aerial and satellite photographs. Using of these methods is very important because it enables good possibilities for realizing regional relations of the investigated phenomenon, as well as the estimate of spatial and temporal variability of all physical-geographical and anthropogenic factors influencing given process. Realizing process of land erosion, on the whole, is only possible by creating universal data base, as well as by using of appropriate software, more exactly by establishing uniform information system. Geographical information system, as the most effective one, the most complex and the most integral system of information about the space enables unification as well as analytical and synthetically processing of all data.

Review of Remote Sensing Needs and Applications in Africa

Science.gov (United States)

Brown, Molly E.

2007-01-01

Remote sensing data has had an important role in identifying and responding to inter-annual variations in the African environment during the past three decades. As a largely agricultural region with diverse but generally limited government capacity to acquire and distribute ground observations of rainfall, temperature and other parameters, remote sensing is sometimes the only reliable measure of crop growing conditions in Africa. Thus, developing and maintaining the technical and scientific capacity to analyze and utilize satellite remote sensing data in Africa is critical to augmenting the continent's local weather/climate observation networks as well as its agricultural and natural resource development and management. The report Review of Remote Sensing Needs and Applications in Africa' has as its central goal to recommend to the US Agency for International Development an appropriate approach to support sustainable remote sensing applications at African regional remote sensing centers. The report focuses on "RS applications" to refer to the acquisition, maintenance and archiving, dissemination, distribution, analysis, and interpretation of remote sensing data, as well as the integration of interpreted data with other spatial data products. The report focuses on three primary remote sensing centers: (1) The AGRHYMET Regional Center in Niamey, Niger, created in 1974, is a specialized institute of the Permanent Interstate Committee for Drought Control in the Sahel (CILSS), with particular specialization in science and techniques applied to agricultural development, rural development, and natural resource management. (2) The Regional Centre for Maiming of Resources for Development (RCMRD) in Nairobi, Kenya, established in 1975 under the auspices of the United Nations Economic Commission for Africa and the Organization of African Unity (now the African Union), is an intergovernmental organization, with 15 member states from eastern and southern Africa. (3) The

Diverse Planning for UAV Control and Remote Sensing

Directory of Open Access Journals (Sweden)

Jan Tožička

2016-12-01

Full Text Available Unmanned aerial vehicles (UAVs are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

Tracking diurnal changes of photosynthesis and evapotranspiration using fluorescence, gas exchange and hyperspectral remote sensing measurements

Science.gov (United States)

Wang, S.; Zhang, L.; Guanter, L.; Huang, C.

2017-12-01

Photosynthesis and evapotranspiration (ET) are the two most important activities of vegetation and make a great contribution to carbon, water and energy exchanges. Remote sensing provides opportunities for monitoring these processes across time and space. This study focuses on tracking diurnal changes of photosynthesis and evapotranspiration over soybean using multiple measurement techniques. Diurnal changes of both remote sensing-based indicators, including active and passive chlorophyll fluorescence and biophysical-related parameters, including photosynthesis rate (photo) and leaf stomatal conductance (cond), were observed. Results showed that both leaf-level steady-state fluorescence (Fs) and canopy-level solar-induced chlorophyll fluorescence were linearly correlated to photosynthetically active radiation (PAR) during the daytime. A double-peak diurnal change curve was observed for leaf-level photo and cond but not for Fs or SIF. Photo and cond showed a strong nonlinear (second-order) correlation, indicating that photosynthesis, which might be remotely sensed by SIF, has the opportunity to track short-term changes of ET. Results presented in this report will be helpful for better understanding the relationship between remote-sensing-based indices and vegetation's biophysical processes.

Illumination invariant feature point matching for high-resolution planetary remote sensing images

Science.gov (United States)

Wu, Bo; Zeng, Hai; Hu, Han

2018-03-01

Despite its success with regular close-range and remote-sensing images, the scale-invariant feature transform (SIFT) algorithm is essentially not invariant to illumination differences due to the use of gradients for feature description. In planetary remote sensing imagery, which normally lacks sufficient textural information, salient regions are generally triggered by the shadow effects of keypoints, reducing the matching performance of classical SIFT. Based on the observation of dual peaks in a histogram of the dominant orientations of SIFT keypoints, this paper proposes an illumination-invariant SIFT matching method for high-resolution planetary remote sensing images. First, as the peaks in the orientation histogram are generally aligned closely with the sub-solar azimuth angle at the time of image collection, an adaptive suppression Gaussian function is tuned to level the histogram and thereby alleviate the differences in illumination caused by a changing solar angle. Next, the suppression function is incorporated into the original SIFT procedure for obtaining feature descriptors, which are used for initial image matching. Finally, as the distribution of feature descriptors changes after anisotropic suppression, and the ratio check used for matching and outlier removal in classical SIFT may produce inferior results, this paper proposes an improved matching procedure based on cross-checking and template image matching. The experimental results for several high-resolution remote sensing images from both the Moon and Mars, with illumination differences of 20°-180°, reveal that the proposed method retrieves about 40%-60% more matches than the classical SIFT method. The proposed method is of significance for matching or co-registration of planetary remote sensing images for their synergistic use in various applications. It also has the potential to be useful for flyby and rover images by integrating with the affine invariant feature detectors.

Information Extraction of Tourist Geological Resources Based on 3d Visualization Remote Sensing Image

Science.gov (United States)

Wang, X.

2018-04-01

Tourism geological resources are of high value in admiration, scientific research and universal education, which need to be protected and rationally utilized. In the past, most of the remote sensing investigations of tourism geological resources used two-dimensional remote sensing interpretation method, which made it difficult for some geological heritages to be interpreted and led to the omission of some information. This aim of this paper is to assess the value of a method using the three-dimensional visual remote sensing image to extract information of geological heritages. skyline software system is applied to fuse the 0.36 m aerial images and 5m interval DEM to establish the digital earth model. Based on the three-dimensional shape, color tone, shadow, texture and other image features, the distribution of tourism geological resources in Shandong Province and the location of geological heritage sites were obtained, such as geological structure, DaiGu landform, granite landform, Volcanic landform, sandy landform, Waterscapes, etc. The results show that using this method for remote sensing interpretation is highly recognizable, making the interpretation more accurate and comprehensive.

The Potential and Uptake of Remote Sensing in Insurance: A Review

Directory of Open Access Journals (Sweden)

Jan de Leeuw

2014-11-01

Full Text Available Global insurance markets are vast and diverse, and may offer many opportunities for remote sensing. To date, however, few operational applications of remote sensing for insurance exist. Papers claiming potential application of remote sensing typically stress the technical possibilities, without considering its contribution to customer value for the insured or to the profitability of the insurance industry. Based on a systematic search of available literature, this review investigates the potential and actual support of remote sensing to the insurance industry. The review reveals that research on remote sensing in classical claim-based insurance described in the literature revolve around crop damage and flood and fire risk assessment. Surprisingly, the use of remote sensing in claim-based insurance appears to be instigated by government rather than the insurance industry. In contrast, insurance companies are offering various index insurance products that are based on remote sensing. For example, remotely sensed index insurance for rangelands and livestock are operational, while various applications in crop index insurance are being considered or under development. The paper discusses these differences and concludes that there is particular scope for application of remote sensing by the insurance industry in index insurance because (1 indices can be constructed that correlate well with what is insured; (2 these indices can be delivered at low cost; and (3 it opens up new markets that are not served by claim-based insurance. The paper finally suggests that limited adoption of remote sensing in insurance results from a lack of mutual understanding and calls for greater cooperation between the insurance industry and the remote sensing community.

Electro-Optical Sensing Apparatus and Method for Characterizing Free-Space Electromagnetic Radiation

Science.gov (United States)

Zhang, Xi-Cheng; Libelo, Louis Francis; Wu, Qi

1999-09-14

Apparatus and methods for characterizing free-space electromagnetic energy, and in particular, apparatus/method suitable for real-time two-dimensional far-infrared imaging applications are presented. The sensing technique is based on a non-linear coupling between a low-frequency electric field and a laser beam in an electro-optic crystal. In addition to a practical counter-propagating sensing technique, a co-linear approach is described which provides longer radiated field--optical beam interaction length, thereby making imaging applications practical.

Remote sensing applications in environmental research

CERN Document Server

Srivastava, Prashant K; Gupta, Manika; Islam, Tanvir

2014-01-01

Remote Sensing Applications in Environmental Research is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in today's sciences, weather and natural disaster prediction. This highly interdisciplinary reference work brings together diverse studies on remote sensing and GIS, from a theoretical background to its applications, represented through various case studies and the findings of new models. The book offers a comprehensive range of contributions by well-known scientists from around the world and opens a new window for students in presenting interdisciplinary and methodological resources on the latest research. It explores various key aspects and offers state-of-the-art research in a simplified form, describing remote sensing and GIS studies for those who are new to the field, as well as for established researchers.

APPLICATION OF CONVOLUTIONAL NEURAL NETWORK IN CLASSIFICATION OF HIGH RESOLUTION AGRICULTURAL REMOTE SENSING IMAGES

Directory of Open Access Journals (Sweden)

C. Yao

2017-09-01

Full Text Available With the rapid development of Precision Agriculture (PA promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN. For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

ESA remote-sensing programme - Present activities and future plans

Energy Technology Data Exchange (ETDEWEB)

Plevin, J [ESA, Directorate of Planning and Future Programmes, Paris, France; Pryke, I [ESA, Directorate of Applications Programmes, Toulouse, France

1979-02-01

The present activities and future missions of the ESA program of spaceborne remote sensing of earth resources and environment are discussed. Program objectives have been determined to be the satisfaction of European regional needs by agricultural, land use, water resources, coastal and polar surveys, and meeting the requirements of developing nations in the areas of agricultural production, mineral exploration and disaster warning and assessment. The Earthnet system of data processing centers presently is used for the distribution of remote sensing data acquired by NASA satellites. Remote sensing experiments to be flown aboard Spacelab are the Metric Camera, to test high resolution mapping capabilities of a large format camera, and the Microwave Remote-Sensing Experiment, which operates as a two-frequency scatterometer, a synthetic aperture radar and a passive microwave radiometer. Studies carried out on the definition of future remote sensing satellite systems are described, including studies of system concepts for land applications and coastal monitoring satellites.

Remote sensing by satellite - Technical and operational implications for international cooperation

Science.gov (United States)

Doyle, S. E.

1976-01-01

International cooperation in the U.S. Space Program is discussed and related to the NASA program for remote sensing of the earth. Satellite remote sensing techniques are considered along with the selection of the best sensors and wavelength bands. The technology of remote sensing satellites is considered with emphasis on the Landsat system configuration. Future aspects of remote sensing satellites are considered.

RSComPro: An Open Communication Protocol for Remote Sensing Systems

DEFF Research Database (Denmark)

Vasiljevic, Nikola; Trujillo, Juan-José

The remote sensing protocol (RSComPro) is a communication protocol, which has been developed for controlling multiple remote sensing systems simultaneously through a UDP/IP and TPC/IP network. This protocol is meant to be open to the remote sensing community. The scope is the implementation of so...

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

International Nuclear Information System (INIS)

Rodriguez, Jenna; Ustin, Susan; Sandoval-Solis, Samuel; O'Geen, Anthony Toby

2016-01-01

Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate post-earthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management. - Highlights: • Remote sensing to improve agricultural disaster management • Introduce post-earthquake agrohydrologic remote sensing (PEARS) framework • Apply PEARS framework to 2010 Maule Earthquake in Central Chile

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, Jenna, E-mail: jmmartin@ucdavis.edu; Ustin, Susan; Sandoval-Solis, Samuel; O' Geen, Anthony Toby

2016-09-15

Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate post-earthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management. - Highlights: • Remote sensing to improve agricultural disaster management • Introduce post-earthquake agrohydrologic remote sensing (PEARS) framework • Apply PEARS framework to 2010 Maule Earthquake in Central Chile.

Remote Sensing and the Kyoto Protocol: A Workshop Summary

Science.gov (United States)

Rosenqvist, Ake; Imhoff, Marc; Milne, Anthony; Dobson, Craig

2000-01-01

The Kyoto Protocol to the United Nations Framework Convention on Climate Change contains quantified, legally binding commitments to limit or reduce greenhouse gas emissions to 1990 levels and allows carbon emissions to be balanced by carbon sinks represented by vegetation. The issue of using vegetation cover as an emission offset raises a debate about the adequacy of current remote sensing systems and data archives to both assess carbon stocks/sinks at 1990 levels, and monitor the current and future global status of those stocks. These concerns and the potential ratification of the Protocol among participating countries is stimulating policy debates and underscoring a need for the exchange of information between the international legal community and the remote sensing community. On October 20-22 1999, two working groups of the International Society for Photogrammetry and Remote Sensing (ISPRS) joined with the University of Michigan (Michigan, USA) to convene discussions on how remote sensing technology could contribute to the information requirements raised by implementation of, and compliance with, the Kyoto Protocol. The meeting originated as a joint effort between the Global Monitoring Working Group and the Radar Applications Working Group in Commission VII of the ISPRS, co-sponsored by the University of Michigan. Tile meeting was attended by representatives from national government agencies and international organizations and academic institutions. Some of the key themes addressed were: (1) legal aspects of transnational remote sensing in the context of the Kyoto Protocol; (2) a review of the current and future and remote sensing technologies that could be applied to the Kyoto Protocol; (3) identification of areas where additional research is needed in order to advance and align remote sensing technology with the requirements and expectations of the Protocol; and 94) the bureaucratic and research management approaches needed to align the remote sensing

Remote sensing for wind power potential: a prospector's handbook

Energy Technology Data Exchange (ETDEWEB)

Wade, J.E.; Maule, P.A.; Bodvarsson, G.; Rosenfeld, C.L.; Woolley, S.G.; McClenahan, M.R.

1983-02-01

Remote sensing can aid in identifying and locating indicators of wind power potential from the terrestrial, marine, and atmospheric environments (i.e.: wind-deformed trees, white caps, and areas of thermal flux). It is not considered as a tool for determining wind power potential. A wide variety of remotely sensed evidence is described in terms of the scale at which evidence of wind power can be identified, and the appropriate remote sensors for finding such evidence. Remote sensing can be used for regional area prospecting using small-scale imagery. The information from such small-scale imagery is most often qualitative, and if it is transitory, examination of a number of images to verify presistence of the feature may be required. However, this evidence will allow rapid screening of a large area. Medium-scale imagery provides a better picture of the evidence obtained from small-scale imagery. At this level it is best to use existing imagery. Criteria relating to land use, accessibility, and proximity of candidate sites to nearby transmission lines can also be effectively evaluated from medium-scale imagery. Large-scale imagery provides the most quantitative evidence of the strength of wind. Wind-deformed trees can be identified at a large number of sites using only a few hours in locally chartered aircraft. A handheld 35mm camera can adequately document any evidence of wind. Three case studies that employ remote sensing prospecting techniques are described. Based on remotely sensed evidence, the wind power potential in three geographically and climatically diverse areas of the United States is estimated, and the estimates are compared to actual wind data in those regions. In addition, the cost of each survey is discussed. The results indicate that remote sensing for wind power potential is a quick, cost effective, and fairly reliable method for screening large areas for wind power potential.

Assessing forest resources in Denmark using wall-to-wall remote sensing data

DEFF Research Database (Denmark)

Schumacher, Johannes

then be applied to estimate resources on both small and large scales. Numerous studies have investigated the possibilities of using remote sensing data for forest monitoring at plot or single tree levels. However, experience of estimating these properties for larger areas, for example regional or country...... assessments, is lacking. In this thesis wall-to-wall remote sensing data (from aerial images, airborne LiDAR, and space-borne SAR) were combined with ground reference data (from NFI plots and tree species experiments) to build and evaluate models estimating properties such as basal area, timber volume......, the thesis extends the application of remote sensing methods to estimate important variables with relevance to water catchment management....

Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data

Directory of Open Access Journals (Sweden)

Wei Tu

2018-01-01

Full Text Available Portraying urban functional zones provides useful insights into understanding complex urban systems and establishing rational urban planning. Although several studies have confirmed the efficacy of remote sensing imagery in urban studies, coupling remote sensing and new human sensing data like mobile phone positioning data to identify urban functional zones has still not been investigated. In this study, a new framework integrating remote sensing imagery and mobile phone positioning data was developed to analyze urban functional zones with landscape and human activity metrics. Landscapes metrics were calculated based on land cover from remote sensing images. Human activities were extracted from massive mobile phone positioning data. By integrating them, urban functional zones (urban center, sub-center, suburbs, urban buffer, transit region and ecological area were identified by a hierarchical clustering. Finally, gradient analysis in three typical transects was conducted to investigate the pattern of landscapes and human activities. Taking Shenzhen, China, as an example, the conducted experiment shows that the pattern of landscapes and human activities in the urban functional zones in Shenzhen does not totally conform to the classical urban theories. It demonstrates that the fusion of remote sensing imagery and human sensing data can characterize the complex urban spatial structure in Shenzhen well. Urban functional zones have the potential to act as bridges between the urban structure, human activity and urban planning policy, providing scientific support for rational urban planning and sustainable urban development policymaking.

Advancements in Modelling of Land Surface Energy Fluxes with Remote Sensing at Different Spatial Scales

DEFF Research Database (Denmark)

Guzinski, Radoslaw

uxes, such as sensible heat ux, ground heat ux and net radiation, are also necessary. While it is possible to measure those uxes with ground-based instruments at local scales, at region scales they usually need to be modelled or estimated with the help of satellite remote sensing data. Even though...... to increase the spatial resolution of the reliable DTD-modelled fluxes from 1 km to 30 m. Furthermore, synergies between remote sensing based models and distributed hydrological models were studied with the aim of improving spatial performance of the hydrological models through incorporation of remote sensing...... of this study was to look at, and improve, various approaches for modelling the land-surface energy uxes at different spatial scales. The work was done using physically-based Two-Source Energy Balance (TSEB) approach as well as semi-empirical \\Triangle" approach. The TSEB-based approach was the main focus...

Training Small Networks for Scene Classification of Remote Sensing Images via Knowledge Distillation

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Guanzhou Chen

2018-05-01

Full Text Available Scene classification, aiming to identify the land-cover categories of remotely sensed image patches, is now a fundamental task in the remote sensing image analysis field. Deep-learning-model-based algorithms are widely applied in scene classification and achieve remarkable performance, but these high-level methods are computationally expensive and time-consuming. Consequently in this paper, we introduce a knowledge distillation framework, currently a mainstream model compression method, into remote sensing scene classification to improve the performance of smaller and shallower network models. Our knowledge distillation training method makes the high-temperature softmax output of a small and shallow student model match the large and deep teacher model. In our experiments, we evaluate knowledge distillation training method for remote sensing scene classification on four public datasets: AID dataset, UCMerced dataset, NWPU-RESISC dataset, and EuroSAT dataset. Results show that our proposed training method was effective and increased overall accuracy (3% in AID experiments, 5% in UCMerced experiments, 1% in NWPU-RESISC and EuroSAT experiments for small and shallow models. We further explored the performance of the student model on small and unbalanced datasets. Our findings indicate that knowledge distillation can improve the performance of small network models on datasets with lower spatial resolution images, numerous categories, as well as fewer training samples.

Remote sensing observation used in offshore wind energy

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun

2008-01-01

Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind...

Remote sensing education in NASA's technology transfer program

Science.gov (United States)

Weinstein, R. H.

1981-01-01

Remote sensing is a principal focus of NASA's technology transfer program activity with major attention to remote sensing education the Regional Program and the University Applications Program. Relevant activities over the past five years are reviewed and perspective on future directions is presented.

Remote Sensing Terminology in a Global and Knowledge-Based World

Science.gov (United States)

Kancheva, Rumiana

The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy

Retrieval operators of remote sensing applications

International Nuclear Information System (INIS)

Ahmad, T.; Shah, A.

2014-01-01

A set of operators of remote sensing applications have been proposed to fulfill most of the Functional Requirements (FR). These operators capture the functions of the applications, which can be considered as the services provided by the applications. In general, a good application meets maximum FR from user. In this paper, we have defined a remote sensing application by a set, having all images created at dissimilar time instances, and each image is categorized into set of different layers. (author)

River Sediment Monitoring Using Remote Sensing and GIS (case Study Karaj Watershed)

Science.gov (United States)

Shafaie, M.; Ghodosi, H.; Mostofi, K. H.

2015-12-01

Whereas the tank volume and dehydrating digits from kinds of tanks are depended on repository sludge, so calculating the sediments is so important in tank planning and hydraulic structures. We are worry a lot about soil erosion in the basin area leading to deposit in rivers and lakes. It holds two reasons: firstly, because the surface soil of drainage would lose its fertility and secondly, the capacity of the tank decreases also it causes the decrease of water quality in downstream. Several studies have shown that we can estimate the rate of suspension sediments through remote sensing techniques. Whereas using remote sensing methods in contrast to the traditional and current techniques is faster and more accurate then they can be used as the effective techniques. The intent of this study has already been to estimate the rate of sediments in Karaj watershed through remote sensing and satellite images then comparing the gained results to the sediments data to use them in gauge-hydraulic station. We mean to recognize the remote sensing methods in calculating sediment and use them to determine the rate of river sediments so that identifying their accuracies. According to the results gained of the shown relations at this article, the amount of annual suspended sedimentary in KARAJ watershed have been 320490 Tones and in hydrologic method is about 350764 Tones .

RIVER SEDIMENT MONITORING USING REMOTE SENSING AND GIS (CASE STUDY KARAJ WATERSHED

Directory of Open Access Journals (Sweden)

M. Shafaie

2015-12-01

Full Text Available Whereas the tank volume and dehydrating digits from kinds of tanks are depended on repository sludge, so calculating the sediments is so important in tank planning and hydraulic structures. We are worry a lot about soil erosion in the basin area leading to deposit in rivers and lakes. It holds two reasons: firstly, because the surface soil of drainage would lose its fertility and secondly, the capacity of the tank decreases also it causes the decrease of water quality in downstream. Several studies have shown that we can estimate the rate of suspension sediments through remote sensing techniques. Whereas using remote sensing methods in contrast to the traditional and current techniques is faster and more accurate then they can be used as the effective techniques. The intent of this study has already been to estimate the rate of sediments in Karaj watershed through remote sensing and satellite images then comparing the gained results to the sediments data to use them in gauge-hydraulic station. We mean to recognize the remote sensing methods in calculating sediment and use them to determine the rate of river sediments so that identifying their accuracies. According to the results gained of the shown relations at this article, the amount of annual suspended sedimentary in KARAJ watershed have been 320490 Tones and in hydrologic method is about 350764 Tones .

Reduction of Topographic Effect for Curve Number Estimated from Remotely Sensed Imagery

Science.gov (United States)

Zhang, Wen-Yan; Lin, Chao-Yuan

2016-04-01

The Soil Conservation Service Curve Number (SCS-CN) method is commonly used in hydrology to estimate direct runoff volume. The CN is the empirical parameter which corresponding to land use/land cover, hydrologic soil group and antecedent soil moisture condition. In large watersheds with complex topography, satellite remote sensing is the appropriate approach to acquire the land use change information. However, the topographic effect have been usually found in the remotely sensed imageries and resulted in land use classification. This research selected summer and winter scenes of Landsat-5 TM during 2008 to classified land use in Chen-You-Lan Watershed, Taiwan. The b-correction, the empirical topographic correction method, was applied to Landsat-5 TM data. Land use were categorized using K-mean classification into 4 groups i.e. forest, grassland, agriculture and river. Accuracy assessment of image classification was performed with national land use map. The results showed that after topographic correction, the overall accuracy of classification was increased from 68.0% to 74.5%. The average CN estimated from remotely sensed imagery decreased from 48.69 to 45.35 where the average CN estimated from national LULC map was 44.11. Therefore, the topographic correction method was recommended to normalize the topographic effect from the satellite remote sensing data before estimating the CN.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

Science.gov (United States)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Remote Sensing Information Gateway

Science.gov (United States)

Remote Sensing Information Gateway, a tool that allows scientists, researchers and decision makers to access a variety of multi-terabyte, environmental datasets and to subset the data and obtain only needed variables, greatly improving the download time.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

Science.gov (United States)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of

Remote sensing of coal mine pollution in the upper Potomac River basin

Science.gov (United States)

1974-01-01

A survey of remote sensing data pertinent to locating and monitoring sources of pollution resulting from surface and shaft mining operations was conducted in order to determine the various methods by which ERTS and aircraft remote sensing data can be used as a replacement for, or a supplement to traditional methods of monitoring coal mine pollution of the upper Potomac Basin. The gathering and analysis of representative samples of the raw and processed data obtained during the survey are described, along with plans to demonstrate and optimize the data collection processes.

Use of Remote Sensing for Decision Support in Africa

Science.gov (United States)

Policelli, Frederick S.

2007-01-01

Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.

Uniform competency-based local feature extraction for remote sensing images

Science.gov (United States)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Passive microwave remote sensing of soil moisture

International Nuclear Information System (INIS)

Jackson, T.J.; Schmugge, T.J.

1986-01-01

Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive microwave soil moisture sensors currently considered for space operation are in the range 10–20 km. The most useful frequency range for soil moisture sensing is 1–5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations

Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

Science.gov (United States)

Hu, Z.; Xu, L.; Yu, B.

2018-04-01

A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

SOIL MOISTURE RETRIEVAL USING CONVOLUTIONAL NEURAL NETWORKS: APPLICATION TO PASSIVE MICROWAVE REMOTE SENSING

Directory of Open Access Journals (Sweden)

Z. Hu

2018-04-01

Full Text Available A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN. Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR for soil moisture retrieval.

Remotely Sensed, catchment scale, estimations of flow resistance

Science.gov (United States)

Carbonneau, P.; Dugdale, S. J.

2009-12-01

Despite a decade of progress in the field of fluvial remote sensing, there are few published works using this new technology to advance and explore fundamental ideas and theories in fluvial geomorphology. This paper will apply remote sensing methods in order to re-visit a classic concept in fluvial geomorphology: flow resistance. Classic flow resistance equations such as those of Strickler and Keulegan typically use channel slope, channel depth or hydraulic radius and some measure channel roughness usually equated to the 50th or 84th percentile of the bed material size distribution. In this classic literature, empirical equations such as power laws are usually calibrated and validated with a maximum of a few hundred data points. In contrast, fluvial remote sensing methods are now capable of delivering millions of high resolution data points in continuous, catchment scale, surveys. On the river Tromie in Scotland, a full dataset or river characteristics is now available. Based on low altitude imagery and NextMap topographic data, this dataset has a continuous sampling of channel width at a resolution of 3cm, of depth and median grain size at a resolution of 1m, and of slope at a resolution of 5m. This entire data set is systematic and continuous for the entire 20km length of the river. When combined with discharge at the time of data acquisition, this new dataset offers the opportunity to re-examine flow resistance equations with a 2-4 orders of magnitude increase in calibration data. This paper will therefore re-examine the classic approaches of Strickler and Keulagan along with other more recent flow resistance equations. Ultimately, accurate predictions of flow resistance from remotely sensed parameters could lead to acceptable predictions of velocity. Such a usage of classic equations to predict velocity could allow lotic habitat models to account for microhabitat velocity at catchment scales without the recourse to advanced and computationally intensive

Multi- and hyperspectral geologic remote sensing: A review

Science.gov (United States)

van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie

2012-02-01

Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region allowed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc.). The step toward quantitative and validated (subpixel) surface mineralogic mapping was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectra and to unravel mixed pixel spectra to pure endmember spectra to derive subpixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) data continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly

Integration of Remote Sensing Data In Operational Flood Forecast In Southwest Germany

Science.gov (United States)

Bach, H.; Appel, F.; Schulz, W.; Merkel, U.; Ludwig, R.; Mauser, W.

Methods to accurately assess and forecast flood discharge are mandatory to minimise the impact of hydrological hazards. However, existing rainfall-runoff models rarely accurately consider the spatial characteristics of the watershed, which is essential for a suitable and physics-based description of processes relevant for runoff formation. Spatial information with low temporal variability like elevation, slopes and land use can be mapped or extracted from remote sensing data. However, land surface param- eters of high temporal variability, like soil moisture and snow properties are hardly available and used in operational forecasts. Remote sensing methods can improve flood forecast by providing information on the actual water retention capacities in the watershed and facilitate the regionalisation of hydrological models. To prove and demonstrate this, the project 'InFerno' (Integration of remote sensing data in opera- tional water balance and flood forecast modelling) has been set up, funded by DLR (50EE0053). Within InFerno remote sensing data (optical and microwave) are thor- oughly processed to deliver spatially distributed parameters of snow properties and soil moisture. Especially during the onset of a flood this information is essential to estimate the initial conditions of the model. At the flood forecast centres of 'Baden- Württemberg' and 'Rheinland-Pfalz' (Southwest Germany) the remote sensing based maps on soil moisture and snow properties will be integrated in the continuously op- erated water balance and flood forecast model LARSIM. The concept is to transfer the developed methodology from the Neckar to the Mosel basin. The major challenges lie on the one hand in the implementation of algorithms developed for a multisensoral synergy and the creation of robust, operationally applicable remote sensing products. On the other hand, the operational flood forecast must be adapted to make full use of the new data sources. In the operational phase of the

Opportunities for Increasing Societal Value of Remote Sensing Data ...

African Journals Online (AJOL)

Opportunities for Increasing Societal Value of Remote Sensing Data in South Africa's Strategic Development Priorities: A Review. ... Despite the enormous capital required to fund remote sensing initiatives, governments ... HOW TO USE AJOL.

Assessing the accuracy of remote sensing techniques in vegetation ...

African Journals Online (AJOL)

Assessing the accuracy of remote sensing techniques in vegetation fractions estimation. ... This study aimed at exploring different remote sensing (RS) techniques for quantitatively measuring vegetation and bare soil ... HOW TO USE AJOL.

Tree health monitoring: perspectives from the visible and near infrared remote sensing

Directory of Open Access Journals (Sweden)

Gonthier P

2012-05-01

Full Text Available Based on a comprehensive literature analysis, we present a critical review of those optical remote sensing techniques operating with the visible (VIS and near infrared (NIR bands for the assessment of health in forest trees. Physical, biological and physio-pathological issues of VIS-NIR reflectance of leaves are described pointing out that a decrease of NIR reflectance is highly influenced by stress conditions on tree caused by abiotic and biotic factors. In many cases the NIR spectral band is more sensitive than the VIS one, allowing to detect plant stress long before the appearance of visible symptoms. A description of the main remote sensing methods is provided, including radiometric measurements and multispectral imaging approaches. False colour infrared (FCIR images collection and their photointerpretation and processing are shown as they represent the most relevant means to acquire information of canopy from its reflectance properties. The amount and the quality of the obtainable data depend on: (i field conditions; (ii the type of the adopted instrument (camera, radiometer; (iii the recording system position (ground platforms, aircraft, satellite; (iv the format of the data (analogical, digitalised or digital; and (v the photointerpretation technique. Results from literature are discussed stressing the limits of remote sensing methods. Remote sensing in VIS and NIR spectral bands is generally a powerful classification tool to detect and score tree stress. Nevertheless, it is not a diagnostic tool in that it does not provide information on the cause of stress. Moreover, the method should be adequately tested at single tree level for many important pathogens, in particular root rot, butt rot and stem rot fungi. In perspective, new high spatial resolution satellite images and their GIS software elaboration might be suitable to improve remote sensing analysis.

A Multi-Temporal Remote Sensing Approach to Freshwater Turtle Conservation

Science.gov (United States)

Mui, Amy B.

Freshwater turtles are a globally declining taxa, and estimates of population status are not available for many species. Primary causes of decline stem from widespread habitat loss and degradation, and obtaining spatially-explicit information on remaining habitat across a relevant spatial scale has proven challenging. The discipline of remote sensing science has been employed widely in studies of biodiversity conservation, but it has not been utilized as frequently for cryptic, and less vagile species such as turtles, despite their vulnerable status. The work presented in this thesis investigates how multi-temporal remote sensing imagery can contribute key information for building spatially-explicit and temporally dynamic models of habitat and connectivity for the threatened, Blanding's turtle (Emydoidea blandingii) in southern Ontario, Canada. I began with outlining a methodological approach for delineating freshwater wetlands from high spatial resolution remote sensing imagery, using a geographic object-based image analysis (GEOBIA) approach. This method was applied to three different landscapes in southern Ontario, and across two biologically relevant seasons during the active (non-hibernating) period of Blanding's turtles. Next, relevant environmental variables associated with turtle presence were extracted from remote sensing imagery, and a boosted regression tree model was developed to predict the probability of occurrence of this species. Finally, I analysed the movement potential for Blanding's turtles in a disturbed landscape using a combination of approaches. Results indicate that (1) a parsimonious GEOBIA approach to land cover mapping, incorporating texture, spectral indices, and topographic information can map heterogeneous land cover with high accuracy, (2) remote-sensing derived environmental variables can be used to build habitat models with strong predictive power, and (3) connectivity potential is best estimated using a variety of approaches

Remote sensing application research of mineralization prospect of uranium-polymetal deposits in west side of Daxinganling

International Nuclear Information System (INIS)

Luo Fusheng; Cui Zhenkui; Fang Maolong; Wang Guojuan; Yao Hua

1998-12-01

The key of mineral exploration by remote sensing method is the extraction and identification of mineralization-related geologic information from remote sensing data under the guidance of mineralization theory. Remote sensing research of deposits is combined with the analysis of regional geology setting, so as to give full play to the advantage of remote sensing technology. According to the geologic features of the covered area, different kinds of satellite data are, at first, selected and processed with different methods and therefore mineralization-related geologic information is effectively extracted. Then regional geologic setting is discussed and main mineralization-controlled factors, such as uranium-occurred volcanic basins, mineralization-controlled faults and granite bodies, Mesozoic volcanic rock series, volcanic framework, are identified. On the basis of the former study, the remote sensing image models of different kinds of deposits have been established. Finally, multi-source information integration technique has been applied to the assessment of favorable mineralization areas. This research shows that it is feasible to extract and identify mineralization-related information from remote sensing images in complicated and covered areas, and that the study area is favorable for uranium and polymetal deposit explorations because of its favorable geologic setting and mineralization conditions

Mapping Water Use and Drought with Satellite Remote Sensing

OpenAIRE

Anderson, Martha

2014-01-01

Mapping water use and drought with satellite remote sensing. Martha C. Anderson, Bill Kustas, Feng Gao, Kate Semmens. USDA-Agricultural Research Service Hydrology and Remote Sensing Laboratory, Beltsville, MD. Chris Hain NOAA-NESDIS

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

Science.gov (United States)

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-04-26

With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction.

Development of a NDI system using the magneto-optical method. 2. Remote sensing using the novel magneto-optical inspection system

International Nuclear Information System (INIS)

Lee, Jinyi; Shoji, Tetsuo

1999-01-01

A new remote sensing system using the magneto-optical method is developed for inspection of flaws introduced during service operation where routine inspection is difficult because of difficult inaccessibility to the components. Among the advantages of non-destructive inspection (NDI) based on the magneto-optical sensor are: real time inspection, elimination of electrical noise and high spatial resolution. Remote sensing of flaws is achieved using the basic principles of Faraday effect, optical permeability, and diffraction of a laser by the domain walls. This paper describes a novel remote NDI system using the principles of optics and LMF. The main characteristic of the system is that image data and LMF information can be obtained simultaneously. It is possible to carry out remote and high speed inspection of cracks from the intensity of reflected light, and to estimate the size of a crack effectively with their diverse data. The advantages of this NDI system are demonstrated using two specimens. (author)

Development of airborne remote sensing data assimilation system

International Nuclear Information System (INIS)

Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

2014-01-01

In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

Validating the Remotely Sensed Geography of Crime: A Review of Emerging Issues

Directory of Open Access Journals (Sweden)

Alice B. Kelly

2014-12-01

Full Text Available This paper explores the existing literature on the active detection of crimes using remote sensing technologies. The paper reviews sixty-one studies that use remote sensing to actively detect crime. Considering the serious consequences of misidentifying crimes or sites of crimes (e.g., opening that place and its residents up to potentially needless intrusion, intimidation, surveillance or violence, the authors were surprised to find a lack of rigorous validation of the remote sensing methods utilized in these studies. In some cases, validation was not mentioned, while in others, validation was severely hampered by security issues, rough terrain and weather conditions. The paper also considers the potential hazards of the use of Google Earth to identify crimes and criminals. The paper concludes by considering alternate, “second order” validation techniques that could add vital context and understanding to remotely sensed images in a law enforcement context. With this discussion, the authors seek to initiate a discussion on other potential “second order” validation techniques, as well as on the exponential growth of surveillance in our everyday lives.

Popularization of remote sensing education and general course construction in undergraduate education

International Nuclear Information System (INIS)

Wang, Jing'ai; Sheng, Zhongyao; Yu, Han

2014-01-01

The construction of a course focused on remote sensing is important because it cultivates college students' geographic abilities and popularizes remote sensing technology. Using internet datasets, this article compares data from general undergraduate courses at almost 100 universities located in the United States and China with 3 years of experimental teaching data from the general undergraduate ''Remote sensing Region'' course at Beijing Normal University. The comparison focuses on curricular concepts, course content, website construction and the popularity of the remote sensing topic. Our research shows that the ''remote sensing region'' course can promote the geographic abilities of college students by popularizing remote sensing observation technology. The course can improve the overall quality of college students by breaking major barriers, and it can promote global and national consciousness by presenting material with global and regional relevancy. Remote sensing imaging has become known as the third most intuitive geographic language after text and maps. The general remote sensing course have the three following developmental qualities: interdisciplinarity, popularization and internationalization

Remote sensing and change detection in rangelands | Palmer ...

African Journals Online (AJOL)

To most land managers, remote sensing has remained illusive, seldom allowing the manager to use it to its full potential. In contrast, the policy maker, backed by GIS laboratories and remote sensing specialists, is confronted by plausible scenarios of degradation and transformation. After intervening, he is seldom active long ...

Solid state frequency conversion technology for remote sensing

International Nuclear Information System (INIS)

Velsko, S.P.; Webb, M.S.; Cook, W.M.; Neuman, W.A.

1994-07-01

Long range remote sensing from airborne or other highly mobile platforms will require high average power tunable radiation from very compact and efficient laser systems. The solid state laser pumped optical parametric oscillator (OPO) has emerged as a leading candidate for such high average power, widely tunable sources. In contrast to laboratory systems, efficiency and simplicity can be the decisive issues which determine the practicality of a particular airborne remote sensing application. The recent advent of diode laser pumped solid state lasers has produced high average power OPO pump sources which are themselves both compact and efficient. However, parametric oscillator technology which can efficiently convert the average powers provided by these pump sources remains to be demonstrated. In addition to the average power requirement, many airborne long range sensing tasks will require a high degree of frequency multiplexing to disentangle data from multiple chemical species. A key advantage in system simplicity can be obtained, for example, if a single OPO can produce easily controlled multispectral output. In this paper the authors address several topics pertaining to the conversion efficiency, power handling, and multispectral capabilities of OPOs which they are currently investigating. In Section 2, single pulse conversion efficiency issues are addressed, while average power effects are treated in Section 3. Section 4 is concerned with multispectral performance of a single OPO. The last section contains a short summary and some concluding remarks

High-Resolution Remotely Sensed Small Target Detection by Imitating Fly Visual Perception Mechanism

Directory of Open Access Journals (Sweden)

Fengchen Huang

2012-01-01

Full Text Available The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

Science.gov (United States)

Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

2012-01-01

The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

Potential for using remote sensing to estimate carbon fluxes across northern peatlands - A review.

Science.gov (United States)

Lees, K J; Quaife, T; Artz, R R E; Khomik, M; Clark, J M

2018-02-15

Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Use of Openly Available Satellite Images for Remote Sensing Education

Science.gov (United States)

Wang, C.-K.

2011-09-01

With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.

Investigation of Arctic mixed-phase clouds by combining airborne remote sensing and in situ observations during VERDI, RACEPAC and ACLOUD

Science.gov (United States)

Ehrlich, André; Bierwirth, Eike; Borrmann, Stephan; Crewell, Susanne; Herber, Andreas; Hoor, Peter; Jourdan, Olivier; Krämer, Martina; Lüpkes, Christof; Mertes, Stephan; Neuber, Roland; Petzold, Andreas; Schnaiter, Martin; Schneider, Johannes; Weigel, Ralf; Weinzierl, Bernadett; Wendisch, Manfred

2016-04-01

To improve our understanding of Arctic mixed-phase clouds a series of airborne research campaigns has been initiated by a collaboration of German research institutes. Clouds in areas dominated by a close sea-ice cover were observed during the research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) and the Radiation-Aerosol-Cloud Experiment in the Arctic Circle (RACEPAC, April/May 2014) which both were based in Inuvik, Canada. The aircraft (Polar 5 & 6, Basler BT-67) operated by the Alfred Wegener Institute for Polar and Marine Research, Germany did cover a wide area above the Canadian Beaufort with in total 149 flight hours (62h during VERDI, 87h during RACEPAC). For May/June 2017 a third campaign ACLOUD (Arctic Clouds - Characterization of Ice, aerosol Particles and Energy fluxes) with base in Svalbard is planned within the Transregional Collaborative Research Centre TR 172 ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3 to investigate Arctic clouds in the transition zone between open ocean and sea ice. The aim of all campaigns is to combine remote sensing and in-situ cloud, aerosol and trace gas measurements to investigate interactions between radiation, cloud and aerosol particles. While during VERDI remote sensing and in-situ measurements were performed by one aircraft subsequently, for RACEPAC and ACLOUD two identical aircraft are coordinated at different altitudes to horizontally collocate both remote sensing and in-situ measurements. The campaign showed that in this way radiative and microphysical processes in the clouds can by studied more reliably and remote sensing methods can be validated efficiently. Here we will illustrate the scientific strategy of the projects including the progress in instrumentation. Differences in the general synoptic and sea ice situation and related changes in cloud properties at the different locations and seasons will be

Searches over graphs representing geospatial-temporal remote sensing data

Science.gov (United States)

Brost, Randolph; Perkins, David Nikolaus

2018-03-06

Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

Landsat's role in ecological applications of remote sensing.

Science.gov (United States)

Warren B. Cohen; Samuel N. Goward

2004-01-01

Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by landsat sensors have played the most pivotal role in spatial and temporal scaling. Modern terrestrial ecology relies on...

Integrated remotely sensed datasets for disaster management

Science.gov (United States)

McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

2008-10-01

Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

Science.gov (United States)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

The mass remote sensing image data management based on Oracle InterMedia

Science.gov (United States)

Zhao, Xi'an; Shi, Shaowei

2013-07-01

With the development of remote sensing technology, getting the image data more and more, how to apply and manage the mass image data safely and efficiently has become an urgent problem to be solved. According to the methods and characteristics of the mass remote sensing image data management and application, this paper puts forward to a new method that takes Oracle Call Interface and Oracle InterMedia to store the image data, and then takes this component to realize the system function modules. Finally, it successfully takes the VC and Oracle InterMedia component to realize the image data storage and management.

Geological and economic factors governing the use of remote sensing techniques in uranium exploration

International Nuclear Information System (INIS)

Waeber, L.; Kaiser, D.

1984-01-01

Remote sensing is an important method to be used in the first stage of an exploration program, depending on the type of uranium deposits. The benefit of the method is: coverage of large areas; quick selection of prospective areas; shortening of exploration time in the first stage; reduction of exploration risk and relatively low price. It is obvious that remote sensing is an inexpensive and time saving method for target definition. It will never substitute the other methods, but in combination with them it will have an essential place within the exploration scheme. (orig./PW)

A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

Science.gov (United States)

S. Healey; P. Patterson; S. Urbanski

2014-01-01

Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

Mapping migratory bird prevalence using remote sensing data fusion.

Science.gov (United States)

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data

Directory of Open Access Journals (Sweden)

Yuanxin Jia

2018-03-01

Full Text Available Land use is of great importance for urban planning, environmental monitoring, and transportation management. Several methods have been proposed to obtain land use maps of urban areas, and these can be classified into two categories: remote sensing methods and social sensing methods. However, remote sensing and social sensing approaches have specific disadvantages regarding the description of social and physical features, respectively. Therefore, an appropriate fusion strategy is vital for large-area land use mapping. To address this issue, we propose an efficient land use mapping method that combines remote sensing imagery (RSI and mobile phone positioning data (MPPD for large areas. We implemented this method in two steps. First, a support vector machine was adopted to classify the RSI and MPPD. Then, the two classification results were fused using a decision fusion strategy to generate the land use map. The proposed method was applied to a case study of the central area of Beijing. The experimental results show that the proposed method improved classification accuracy compared with that achieved using MPPD alone, validating the efficacy of this new approach for identifying land use. Based on the land use map and MPPD data, activity density in key zones during daytime and nighttime was analyzed to illustrate the volume and variation of people working and living across different regions.

REMOTE SENSING FOR ENVIRONMENTAL COMPLIANCE MONITORING

Science.gov (United States)

I. Remote Sensing Basics A. The electromagnetic spectrum demonstrates what we can see both in the visible and beyond the visible part of the spectrum through the use of various types of sensors. B. Resolution refers to what a remote sensor can see and how often. 1. Sp...

Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

Science.gov (United States)

Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.

1993-01-01

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

Remote Sensing and Cropping Practices: A Review

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Agnès Bégué

2018-01-01

Full Text Available For agronomic, environmental, and economic reasons, the need for spatialized information about agricultural practices is expected to rapidly increase. In this context, we reviewed the literature on remote sensing for mapping cropping practices. The reviewed studies were grouped into three categories of practices: crop succession (crop rotation and fallowing, cropping pattern (single tree crop planting pattern, sequential cropping, and intercropping/agroforestry, and cropping techniques (irrigation, soil tillage, harvest and post-harvest practices, crop varieties, and agro-ecological infrastructures. We observed that the majority of the studies were exploratory investigations, tested on a local scale with a high dependence on ground data, and used only one type of remote sensing sensor. Furthermore, to be correctly implemented, most of the methods relied heavily on local knowledge on the management practices, the environment, and the biological material. These limitations point to future research directions, such as the use of land stratification, multi-sensor data combination, and expert knowledge-driven methods. Finally, the new spatial technologies, and particularly the Sentinel constellation, are expected to improve the monitoring of cropping practices in the challenging context of food security and better management of agro-environmental issues.

Geological remote sensing

Science.gov (United States)

Bishop, Charlotte; Rivard, Benoit; de Souza Filho, Carlos; van der Meer, Freek

2018-02-01

Geology is defined as the 'study of the planet Earth - the materials of which it is made, the processes that act on these materials, the products formed, and the history of the planet and its life forms since its origin' (Bates and Jackson, 1976). Remote sensing has seen a number of variable definitions such as those by Sabins and Lillesand and Kiefer in their respective textbooks (Sabins, 1996; Lillesand and Kiefer, 2000). Floyd Sabins (Sabins, 1996) defined it as 'the science of acquiring, processing and interpreting images that record the interaction between electromagnetic energy and matter' while Lillesand and Kiefer (Lillesand and Kiefer, 2000) defined it as 'the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation'. Thus Geological Remote Sensing can be considered the study of, not just Earth given the breadth of work undertaken in planetary science, geological features and surfaces and their interaction with the electromagnetic spectrum using technology that is not in direct contact with the features of interest.

A method for geological hazard extraction using high-resolution remote sensing

International Nuclear Information System (INIS)

Wang, Q J; Chen, Y; Bi, J T; Lin, Q Z; Li, M X

2014-01-01

Taking Yingxiu, the epicentre of the Wenchuan earthquake, as the study area, a method for geological disaster extraction using high-resolution remote sensing imagery was proposed in this study. A high-resolution Digital Elevation Model (DEM) was used to create mask imagery to remove interfering factors such as buildings and water at low altitudes. Then, the mask imagery was diced into several small parts to reduce the large images' inconsistency, and they were used as the sources to be classified. After that, vector conversion was done on the classified imagery in ArcGIS. Finally, to ensure accuracy, other interfering factors such as buildings at high altitudes, bare land, and land covered by little vegetation were removed manually. Because the method can extract geological hazards in a short time, it is of great importance for decision-makers and rescuers who need to know the degree of damage in the disaster area, especially within 72 hours after an earthquake. Therefore, the method will play an important role in decision making, rescue, and disaster response planning

International Conference on Remote Sensing Applications for Archaeological Research and World Heritage Conservation

Science.gov (United States)

2002-01-01

. Archaeology through Space: Experience in Indian Subcontinent. The creation of a GIS Archaeological Site Location Catalogue in Yucatan: A Tool to preserve its Cultural Heritage. Mapping the Ancient Anasazi Roads of Southeast Utah. Remote Sensing and GIS Technology for Identification of Conservation and Heritage sites in Urban Planning. Mapping Angkor: For a new appraisal of the Angkor region. Angkor and radar imaging: seeing a vast pre-industrial low-density, dispersed urban complex. Technical and methodological aspects of archaeological CRM integrating high resolution satellite imagery. The contribution of satellite imagery to archaeological survey: an example from western Syria. The use of satellite images, digital elevation models and ground truth for the monitoring of land degradation in the "Cinque Terre" National park. Remote Sensing and GIS Applications for Protection and Conservation of World Heritage Site on the coast - Case Study of Tamil Nadu Coast, India. Multispectral high resolution satellite imagery in combination with "traditional" remote sensing and ground survey methods to the study of archaeological landscapes. The case study of Tuscany. Use of Remotely-Sensed Imagery in Cultural Landscape. Characterisation at Fort Hood, Texas. Heritage Learning and Data Collection: Biodiversity & Heritage Conservation through Collaborative Monitoring & Research. A collaborative project by UNESCO's WHC (World Heritage Center) & The GLOBE Program (Global Learning and Observations to Benefit the Environment). Practical Remote Sensing Activities in an Interdisciplinary Master-Level Space Course.

Remote sensing fire and fuels in southern California

Science.gov (United States)

Philip Riggan; Lynn Wolden; Bob Tissell; David Weise; J. Coen

2011-01-01

Airborne remote sensing at infrared wavelengths has the potential to quantify large-fire properties related to energy release or intensity, residence time, fuel-consumption rate, rate of spread, and soil heating. Remote sensing at a high temporal rate can track fire-line outbreaks and acceleration and spotting ahead of a fire front. Yet infrared imagers and imaging...

Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters

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Yongyang Xu

2018-01-01

Full Text Available Very high resolution (VHR remote sensing imagery has been used for land cover classification, and it tends to a transition from land-use classification to pixel-level semantic segmentation. Inspired by the recent success of deep learning and the filter method in computer vision, this work provides a segmentation model, which designs an image segmentation neural network based on the deep residual networks and uses a guided filter to extract buildings in remote sensing imagery. Our method includes the following steps: first, the VHR remote sensing imagery is preprocessed and some hand-crafted features are calculated. Second, a designed deep network architecture is trained with the urban district remote sensing image to extract buildings at the pixel level. Third, a guided filter is employed to optimize the classification map produced by deep learning; at the same time, some salt-and-pepper noise is removed. Experimental results based on the Vaihingen and Potsdam datasets demonstrate that our method, which benefits from neural networks and guided filtering, achieves a higher overall accuracy when compared with other machine learning and deep learning methods. The method proposed shows outstanding performance in terms of the building extraction from diversified objects in the urban district.

Remote sensing of glacier- and permafrost-related hazards in high mountains: an overview

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A. Kääb

2005-01-01

Full Text Available Process interactions and chain reactions, the present shift of cryospheric hazard zones due to atmospheric warming, and the potential far reach of glacier disasters make it necessary to apply modern remote sensing techniques for the assessment of glacier and permafrost hazards in high-mountains. Typically, related hazard source areas are situated in remote regions, often difficult to access for physical and/or political reasons. In this contribution we provide an overview of air- and spaceborne remote sensing methods suitable for glacier and permafrost hazard assessment and disaster management. A number of image classification and change detection techniques support high-mountain hazard studies. Digital terrain models (DTMs, derived from optical stereo data, synthetic aperture radar or laserscanning, represent one of the most important data sets for investigating high-mountain processes. Fusion of satellite stereo-derived DTMs with the DTM from the Shuttle Radar Topography Mission (SRTM is a promising way to combine the advantages of both technologies. Large changes in terrain volume such as from avalanche deposits can indeed be measured even by repeat satellite DTMs. Multitemporal data can be used to derive surface displacements on glaciers, permafrost and landslides. Combining DTMs, results from spectral image classification, and multitemporal data from change detection and displacement measurements significantly improves the detection of hazard potentials. Modelling of hazardous processes based on geographic information systems (GIS complements the remote sensing analyses towards an integrated assessment of glacier and permafrost hazards in mountains. Major present limitations in the application of remote sensing to glacier and permafrost hazards in mountains are, on the one hand, of technical nature (e.g. combination and fusion of different methods and data; improved understanding of microwave backscatter. On the other hand, better

Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method

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Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.

2005-01-01

The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.

Monitoring water quality by remote sensing

Science.gov (United States)

Brown, R. L. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A limited study was conducted to determine the applicability of remote sensing for evaluating water quality conditions in the San Francisco Bay and delta. Considerable supporting data were available for the study area from other than overflight sources, but short-term temporal and spatial variability precluded their use. The study results were not sufficient to shed much light on the subject, but it did appear that, with the present state of the art in image analysis and the large amount of ground truth needed, remote sensing has only limited application in monitoring water quality.

Remote Sensing in Human Health: A 10-Year Bibliometric Analysis

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João Viana

2017-11-01

Full Text Available A mixed methods bibliometric analysis was performed to ascertain the characteristic of scientific literature published in a 10-year period (2007–2016 regarding the application of remote sensing data in human health. A search was performed on the Scopus database, followed by manual revision using synthesis studies’ techniques, requiring the authors to sort through more than 8000 medical concepts to create the query, and to manually select relevant papers from over 2000 documents. From the initial 2752 papers identified, 520 articles were selected for analysis, showing that the United States ranked first, with a total of 250 (48.1% of the total documents, followed by France and the United Kingdom, with 67 (12.9% of the total and 54 (10.4% of the total documents, respectively. When considering authorship, the top three authors were Vounatsou P (22 articles, Utzinger J (19 articles, and Vignolles C (13 articles. Regarding disease-specific keywords, malaria, dengue, and schistosomiasis were the most frequent keywords, occurring 142, 34, and 24 times, respectively. For some infectious diseases and other highly pathogenic or emerging infectious diseases, remote sensing has become a very powerful instrument. Also, several studies relate different environmental factors retrieved by remote sensing data with other diseases, such as asthma exacerbations. Health-related remote sensing publications are increasing and this paper highlights the importance of these related technologies toward better information and, ideally, better provision of healthcare. On the other hand, this paper provides an overall picture of the state of the research regarding the application of remote sensing data in human health and identifies the most active stakeholders e.g., authors and institutions in the field, informing possible new collaboration research groups.