netic radiation as a medium of interaction. Space borne remote sensing is fast emerging as a front running provider of information on natural resources in a spatial format. This article briefly discusses the physical basis of remote sensing, how information is extracted from images and various applications of remote sensing.
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Rangnath R Navalgund, after working for more than two decades at the. Space Applications. Centre (ISRO),. Ahmedabad has moved over to the National. Remote Sensing Agency,. Department of Space,. Hyderabad, as its. Director since May 2001. Definition of Indian spacebome remote sensing missions and formulation of ...
application area. RS data in conjunction with collateral data has greatly facilitated integrated development of land and water resources on watershed basis leading to sustainable develop- ment. Disaster monitoring, damage assessment and mitigation has been a main beneficiary of spaceborne remote sensing. Sequen-.
Liebel, L.; Körner, M.
In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.
Cracknell, Arthur P
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
Full Text Available In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN, can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.
Prasad, Saurabh; Chanussot, Jocelyn
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
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...
Xia, Fei; Li, HuiZhou
This paper introduces a method for fast airport detection on remote sensing images (RSIs) using Single Shot MultiBox Detector (SSD). To our knowledge, this could be the first study which introduces an end-to-end detection model into airport detection on RSIs. Based on the common low-level features between natural images and RSIs, a convolution neural network trained on large amounts of natural images was transferred to tackle the airport detection problem with limited annotated data. To deal with the specific characteristics of RSIs, some related parameters in the SSD, such as the scales and layers, were modified for more accurate and rapider detection. The experiments show that the proposed method could achieve 83.5% Average Recall at 8 FPS on RSIs with the size of 1024*1024. In contrast to Faster R-CNN, an improvement on AP and speed could be obtained.
Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. This book provides a holistic treatment that captures its multidisciplinary nature, emphasizing the physical principles of hyperspectral remote sensing.
Bai, Yingxin; Yu, Jirong; Petzar, Paul; Petros, M.; Chen, Songsheng; Trieu, Bo; Lee, Nyung; Singh, U.
Ho:YLF/LuLiF lasers have specific applications for remote sensing such as wind-speed measurement and carbon dioxide (CO2) concentration measurement in the atmosphere because the operating wavelength (around 2 m) is located in the eye-safe range and can be tuned to the characteristic lines of CO2 absorption and there is strong backward scattering signal from aerosol (Mie scattering). Experimentally, a diode pumped Ho:Tm:YLF laser has been successfully used as the transmitter of coherent differential absorption lidar for the measurement of with a repetition rate of 5 Hz and pulse energy of 75 mJ . For highly precise CO2 measurements with coherent detection technique, a laser with high repetition rate is required to averaging out the speckle effect . In addition, laser efficiency is critically important for the air/space borne lidar applications, because of the limited power supply. A diode pumped Ho:Tm:YLF laser is difficult to efficiently operate in high repetition rate due to the large heat loading and up-conversion. However, a Tm:fiber laser pumped Ho:YLF laser with low heat loading can be operated at high repetition rates efficiently . No matter whether wind-speed or carbon dioxide (CO2) concentration measurement is the goal, a Ho:YLF/LuLiF laser as the transmitter should operate in a single longitudinal mode. Injection seeding is a valid technique for a Q-switched laser to obtain single longitudinal mode operation. In this paper, we will report the new results for a single longitudinal mode, high repetition rate, Q-switched Ho:YLF laser. In order to avoid spectral hole burning and make injection seeding easier, a four mirror ring cavity is designed for single longitudinal mode, high repetition rate Q-switched Ho:YLF laser. The ramp-fire technique is chosen for injection seeding.
Eismann, Michael Theodore
..., 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...
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.
Nowell, H.; Liu, G.
With the advent of satellites, we can now observe areas of the globe that have sparse to no ground data coverage. Both active and passive satellite sensors aboard satellites including CloudSat's Cloud Profiling Radar (CPR), Aqua's Advanced Microwave Scanning Radiometer (AMSR-E) and the upcoming Global Precipitation Measurement's (GPM) Dual-Frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) study ice and snow particles. A good retrieval algorithm for these satellite sensors can only be developed when the single scattering properties of the snowflakes are accurately calculated in radiative transfer models. This becomes crucial at frequencies at and above the W-band when aggregate ice crystals become detectable by satellite radiometers. Snowflakes are often modeled as spheres or oblate spheroids to ease the complexity of calculations, despite the fact that they are typically aggregates of crystals. For improved accuracy in satellite remote sensing, it is important to model snowflakes as close to nature as possible. Several recent studies model flakes as pristine crystal types [Liu, 2008], generate aggregate flakes as fractals [Ishimoto, 2008] or via the Monte Carlo method [Maruyama and Fujioshi, 2005]. Modeling snowflakes as pristine crystals, however, has the drawback of not accurately reflecting snowflakes as most tend to be aggregates of different crystal types. Other studies where aggregates are generated tend to overlook size-density relationships of aggregate flakes or other studied statistical parameters such as aspect ratio. In an effort to improve available single-scattering properties of aggregate flakes, we developed a new method of generating flakes. Starting out with a six-bullet rosette crystal of accurate size and density, aggregate flakes are generated with two different bullet rosette crystal sizes of 200 and/or 400 microns in maximum dimension. The flakes similarly follow size-density relationships of aggregate as determined from
Campbell, James B
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
Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea
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
Belinda Arunarwati Margono
Remote sensing is an important data source for monitoring the change of forest cover, in terms of both total removal of forest cover (deforestation), and change of canopy cover, structure and forest ecosystem services that result in forest degradation. In the context of Intergovernmental Panel on Climate Change (IPCC), forest degradation monitoring requires information...
Lippitt, Christopher; Coulter, Lloyd
This book documents the state of the art in the use of remote sensing to address time-sensitive information requirements. Specifically, it brings together a group of authors who are both researchers and practitioners, who work toward or are currently using remote sensing to address time-sensitive information requirements with the goal of advancing the effective use of remote sensing to supply time-sensitive information. The book addresses the theoretical implications of time-sensitivity on the remote sensing process, assessments or descriptions of methods for expediting the delivery and improving the quality of information derived from remote sensing, and describes and analyzes time-sensitive remote sensing applications, with an emphasis on lessons learned. This book is intended for remote sensing scientists, practitioners (e.g., emergency responders or administrators of emergency response agencies), and students, but will also be of use to those seeking to understand the potential of remote sensing to addres...
The flow of water and energy fluxes at the Earth's surface and within the climate system is difficult to quantify. Recent advances in remote sensing technologies have provided scientists with a useful means to improve characterization of these complex processes. However, many challenges remain that limit our ability to optimize remote sensing data in determining evapotranspiration (ET) and energy fluxes. For example, periodic cloud cover limits the operational use of remotely sensed data from passive sensors in monitoring seasonal fluxes. Additionally, there are many remote sensing-based single-source surface energy balance (SEB) models, but no clear guidance on which one to use in a particular application. Two widely used models---surface energy balance algorithm for land (SEBAL) and mapping ET at high resolution with internalized calibration (METRIC)---need substantial human-intervention that limits their applicability in broad-scale studies. This dissertation addressed some of these challenges by proposing novel ways to optimize available resources within the SEB-based ET modeling framework. A simple regression-based Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) fusion model was developed to integrate Landsat spatial and MODIS temporal characteristics in calculating ET. The fusion model produced reliable estimates of seasonal ET at moderate spatial resolution while mitigating the impact that cloud cover can have on image availability. The dissertation also evaluated five commonly used remote sensing-based single-source SEB models and found the surface energy balance system (SEBS) may be the best overall model for use in humid subtropical climates. The study also determined that model accuracy varies with land cover type, for example, all models worked well for wet marsh conditions, but the SEBAL and simplified surface energy balance index (S-SEBI) models worked better than the alternatives for grass cover. A new automated approach based on
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.…
Paul H. Evangelista
Full Text Available In this study, we tested the Maximum Entropy model (Maxent for its application and performance in remotely sensing invasive Tamarix sp. Six Landsat 7 ETM+ satellite scenes and a suite of vegetation indices at different times of the growing season were selected for our study area along the Arkansas River in Colorado. Satellite scenes were selected for April, May, June, August, September, and October and tested in single-scene and time-series analyses. The best model was a time-series analysis fit with all spectral variables, which had an AUC = 0.96, overall accuracy = 0.90, and Kappa = 0.79. The top predictor variables were June tasselled cap wetness, September tasselled cap wetness, and October band 3. A second time-series analysis, where the variables that were highly correlated and demonstrated low predictive strengths were removed, was the second best model. The third best model was the October single-scene analysis. Our results may prove to be an effective approach for mapping Tamarix sp., which has been a challenge for resource managers. Of equal importance is the positive performance of the Maxent model in handling remotely sensed datasets.
Joseph, A.; Desa, E.
surface layer of the ocean surface and hence these techniques are unusable for measurement of subsurface circulation. The three methods of ocean circulation measurement using acoustic remote sensing techniques are the Lagrangian, Eulerian and single...
Full Text Available During the Capo Mannu Project 2011 fieldwork season, three separate sites were selected for remote sensing prospection: Su Pallosu (Beachfront and Upper Platform, Sa Rocca Tunda (Beachfront and Serra Is Araus. These areas have in common the presence of buried structures and/or ceramic deposits, and represent the favourite candidates for future excavations in the area. The level of success attained across the sites was not very high, which awkward topography and/or unusual geological circumstances hindering the usually reliant magnetometer survey method.
Remote sensing is one of the best ways to be able to monitor and see changes in the Earth. The use of satellite images in the classroom can be a practical way to help students understand the importance and use of remote sensing and Geographic Information Systems (GIS). It is essential in helping students to understand that underlying individual data points are converted to a broad spatial form. The use of actual remote sensing data makes this more understandable to the students e.g. an online map of recent earthquake events, geologic maps, satellite imagery. For change detection, images of years ten or twenty years apart of the same area can be compared and observations recorded. Satellite images of different places can be available on the Internet or from the local space agency. In groups of mixed abilities, students can observe changes in land use over time and also give possible reasons and explanations to those changes. Students should answer essential questions like, how does satellite imagery offer valuable information to different faculties e.g. military, weather, environmental departments and others. Before and after images on disasters for example, volcanoes, floods and earthquakes should be obtained and observed. Key questions would be; how can scientists use these images to predict, or to change the future outcomes over time. How to manage disasters and how the archived images can assist developers in planning land use around that area in the future. Other material that would be useful includes maps and aerial photographs of the area. A flight should be organized over the area for students to acquire aerial photographs of their own; this further enhances their understanding of the concept "remote sensing". Environmental issues such as air, water and land pollution can also be identified on satellite images. Key questions for students would include causes, effects and possible solutions to the problem. Conducting a fieldwork exercise around the area would
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....
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....
Bishop, Charlotte; Rivard, Benoit; de Souza Filho, Carlos; van der Meer, Freek
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.
Applications Branch, EROS Data Center
NCIC was established within the USGS to provide a single-point contact source for cartographic-related information, including remotely sensed data. A computerized indexing system, the Aerial Photography Summary Record System (APSRS), shows all holding for Federal agencies, with the long range goal of including data acquired on the state and local levels and (eventually) by private industry. The system directs the used to a particular agency which holds coverage over a particular unit area, based on the 7 1/2 minute USGS quadrangle system. The data will remain in the hands of the source agency.
Richards, John A.; Jia, Xiuping
Remote Sensing Digital Image Analysis provides the non-specialist with an introduction to quantitative evaluation of satellite and aircraft derived remotely retrieved data. Each chapter covers the pros and cons of digital remotely sensed data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations. Problems conclude each chapter. This fourth edition has been developed to reflect the changes that have occurred in this area over the past several years.
Written by leaders in the field, Signal Processing for Remote Sensing explores the data acquisitions segment of remote sensing. Each chapter presents a major research result or the most up to date development of a topic. The book includes a chapter by Dr. Norden Huang, inventor of the Huang-Hilbert transform who, along with and Dr. Steven Long discusses the application of the transform to remote sensing problems. It also contains a chapter by Dr. Enders A. Robinson, who has made major contributions to seismic signal processing for over half a century, on the basic problem of constructing seism
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...
Papers were presented in four subject areas: applications of remote sensing; data analysis, digital and analog; acquisition systems; and general. Abstracts of individual items from the conference were prepared separately for the data base
Full Text Available For this research, the researchers examine various existing image classification algorithms with the aim of demonstrating how these algorithms can be applied to remote sensing images. These algorithms are broadly divided into supervised...
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.
North, G. W.
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.
Hovis, W. A.
Remote sensing from aircraft has been used to determine water content in areas such as the New York Bight. Extension of the techniques developed to satellite sensing of the Chesapeake Bay will begin in 1978 with the launch of Nimbus-G. Remote sensing offers a number of interesting possibilities for investigating a reasonably large body of water, such as the Chesapeake Bay, coupled with some disadvantages. The chief advantage of remote sensing is that it offers the opportunity to cover large areas in relatively short periods of time. Low altitude satellites traveling at about 7 km/s can cover the Chesapeake Bay in about 1 minute so that the entire Bay can be studied under almost identical conditions of solar illumination.
Davis, Bruce A.; Schmidt, Nicholas; Jensen, John R.; Cowen, Dave J.; Halls, Joanne; Narumalani, Sunil; Burgess, Bryan
Utility companies are challenged to provide services to a highly dynamic customer base. With factory closures and shifts in employment becoming a routine occurrence, the utility industry must develop new techniques to maintain records and plan for expected growth. BellSouth Telecommunications, the largest of the Bell telephone companies, currently serves over 13 million residences and 2 million commercial customers. Tracking the movement of customers and scheduling the delivery of service are major tasks for BellSouth that require intensive manpower and sophisticated information management techniques. Through NASA's Commercial Remote Sensing Program Office, BellSouth is investigating the utility of remote sensing and geographic information system techniques to forecast residential development. This paper highlights the initial results of this project, which indicate a high correlation between the U.S. Bureau of Census block group statistics and statistics derived from remote sensing data.
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....
Miodrag D. Regodić
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
Kahn, Ralph A.
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.
Assem, S. van den; Bastiaanssen, W.G.M.; Claassen, T.H.L.; Feddes, R.A.; Menenti, M.; Minderhoud, P.; Nieuwenhuis, G.J.A.; Nieuwkoop, J. van; Stokkom, H.T.C. van; Stokman, N.G.M.; Thunnissen, H.A.M.; Visser, T.N.M.
In modern water management detailed information is required on processes that occur and on the state of water systems, including the way they are influenced by human activities. Remote sensing can contribute significantly to these information. For example, areal patterns of water quality parameters
White, P. G.
Remote sensing, as a tool to aid in the control of water pollution, offers a means of making rapid, economical surveys of areas that are relatively inaccessible on the ground. At the same time, it offers the only practical means of mapping pollution patterns that cover large areas. Detection of oil slicks, thermal pollution, sewage, and algae are discussed.
Champollion, N; Benveniste, J; Chen, J
This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives. Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of th...
Ustinov, Eugene A
This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented. Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians are used to solve corresponding inver...
"… a comprehensive view on and real world examples of remote sensing technologies in natural resources assessment and monitoring. … state-of-the-art knowledge in this multidisciplinary field. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available and apply their knowledge to the understanding of sampling design, the analysis of multi-source imagery, and the application of the techniques to specific problems relevant to natural resources."-Yuhong He, University of Toronto Mississauga, Ontario, Canada"The list of topics covered is so complete that I would recommend the book to anyone teaching a graduate course on vegetation analysis through digital image analysis. … I recommend this book then for anyone doing advanced digital image analysis and environmental GIS courses who want to cover topics related to applied remote sensing work involving vegetation analysis."-Charles Roberts, Florida Atlantic University, Boca Raton, USA, in Economic Bota...
Clarke, Keith C.; Scepan, Joseph; Hemphill, Jeffrey; Herold, Martin; Husak, Gregory; Kline, Karen; Knight, Kevin
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.
Pena, A.; Bay Hasager, C.; Lange, J. [Technical Univ. of Denmark. DTU Wind Energy, DTU Risoe Campus, Roskilde (Denmark) (and others
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 Risoe) during the first PhD Summer School: Remote Sensing in Wind Energy. Thus it is closely linked to the PhD Summer Schools where state-of-the-art is presented during the lecture sessions. The advantage of the report is to supplement with in-depth, article style information. Thus we strive to provide link from the lectures, field demonstrations, and hands-on exercises to theory. The report will allow alumni to trace back details after the course and benefit from the collection of information. This is the third edition of the report (first externally available), after very successful and demanded first two, and we warmly acknowledge all the contributing authors for their work in the writing of the chapters, and we also acknowledge all our 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 in Wind Energy. (Author)
Garaba, S. P.; Dierssen, H. M.
Plastic debris is becoming a nuisance in the environment and as a result there has been a dire need to synoptically detect and quantify them in the ocean and on land. We investigate the possible utility of spectral information determined from hand held, airborne and satellite remote sensing tools in the detection and identification polymer source of plastic debris. Sampled debris will be compared to our derived spectral library of typical raw polymer sources found at sea and in household waste. Additional work will be to determine ways to estimate the abundance of plastic debris in target areas. Implications of successful remote detection, tracking and quantification of plastic debris will be towards validating field observations over large areas and at repeated time intervals both on land and at sea.
Application of active and passive microwave remote sensing to the study of ocean pollution is discussed. Previous research efforts, both in the field and in the laboratory were surveyed to derive guidance for the design of a laboratory program of research. The essential issues include: choice of radar or radiometry as the observational technique; choice of laboratory or field as the research site; choice of operating frequency; tank sizes and material; techniques for wave generation and appropriate wavelength spectrum; methods for controlling and disposing of pollutants used in the research; and pollutants other than oil which could or should be studied.
Nansen, Christian; Elliott, Norman
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.
Batini, C.; Blaschke, T.; Lang, S.; Albrecht, F.; Abdulmutalib, H. M.; Barsi, Á.; Szabó, G.; Kugler, Zs.
The issue of data quality (DQ) is of growing importance in Remote Sensing (RS), due to the widespread use of digital services (incl. apps) that exploit remote sensing data. In this position paper a body of experts from the ISPRS Intercommission working group III/IVb "DQ" identifies, categorises and reasons about issues that are considered as crucial for a RS research and application agenda. This ISPRS initiative ensures to build on earlier work by other organisations such as IEEE, CEOS or GEO, in particular on the meritorious work of the Quality Assurance Framework for Earth Observation (QA4EO) which was established and endorsed by the Committee on Earth Observation Satellites (CEOS) but aims to broaden the view by including experts from computer science and particularly database science. The main activities and outcomes include: providing a taxonomy of DQ dimensions in the RS domain, achieving a global approach to DQ for heterogeneous-format RS data sets, investigate DQ dimensions in use, conceive a methodology for managing cost effective solutions on DQ in RS initiatives, and to address future challenges on RS DQ dimensions arising in the new era of the big Earth data.
Chern, Jeng-Shing; Ling, Jer; Weng, Shui-Lin
FORMOSAT-2 is Taiwan's first remote sensing satellite (RSS). It was launched on 20 May 2004 with five-year mission life and a very unique mission orbit at 891 km altitude. This orbit gives FORMOSAT-2 the daily revisit feature and the capability of imaging the Arctic and Antarctic regions due to the high enough altitude. For more than three years, FORMOSAT-2 has performed outstanding jobs and its global effectiveness is evidenced in many fields such as public education in Taiwan, Earth science and ecological niche research, preservation of the world heritages, contribution to the International Charter: space and major disasters, observation of suspected North Korea and Iranian nuclear facilities, and scientific observation of the atmospheric transient luminous events (TLEs). In order to continue the provision of earth observation images from space, the National Space Organization (NSPO) of Taiwan started to work on the second RSS from 2005. This second RSS will also be Taiwan's first indigenous satellite. Both the bus platform and remote sensing instrument (RSI) shall be designed and manufactured by NSPO and the Instrument Technology Research Center (ITRC) under the supervision of the National Applied Research Laboratories (NARL). Its onboard computer (OBC) shall use Taiwan's indigenous LEON-3 central processing unit (CPU). In order to achieve cost effective design, the commercial off the shelf (COTS) components shall be widely used. NSPO shall impose the up-screening/qualification and validation/verification processes to ensure their normal functions for proper operations in the severe space environments.
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.
Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.
Gumerman, G J; Lyons, T R
We have shown that the different spectral surveying techniques and the resultant imagery vary in their applicability to archeological prediction and exploration, but their applications are far broader than we have indicated. Their full potential, to a considerable extent, still remains unexplored. Table 1 is a chart of the more common sensor systems useful to archeological investigators. Several kinds of photography, thermal infrared imagery, and radar imagery are listed. Checks in various categories of direct and indirect utility in archeological research indicate that the different systems do provide varying degrees of input for studies in these areas. Photography and multispectral photography have the broadest applications in this field. Standard black-and-white aerial photography generally serves the purposes of archeological exploration and site analysis better than infrared scanner imagery, radar, or color photography. However, the real value of remotesensing experimentation lies in the utilization of different instruments and in the comparison and correlation of their data output. It can be stated without doubt that there is no one all-purpose remotesensing device on which the archeologist can rely that will reveal all evidence of human occupations. Remote-sensing data will not replace the traditional ground-based site survey, but, used judiciously, data gathered from aerial reconnaissance can reveal many cultural features unsuspected from the ground. The spectral properties of sites distinguishable by various types of remote sensors may perhaps be one of their most characteristic features, and yet the meaning of the differential discrimnination of features has not been determined for the most part, since such spectral properties are poorly understood at this date. The difficulty in isolating the causes of acceptable definition in certain portion of the spectrum and the lack of acceptable definition in others suggests that the evaluation of remote-sensing
Moore, H.J.; Boyce, J.M.; Schaber, G.G.; Scott, D.H.
Remote sensing and measurements of the Moon from Apollo orbiting spacecraft and Earth form a basis for extrapolation of Apollo surface data to regions of the Moon where manned and unmanned spacecraft have not been and may be used to discover target regions for future lunar exploration which will produce the highest scientific yields. Orbital remote sensing and measurements discussed include (1) relative ages and inferred absolute ages, (2) gravity, (3) magnetism, (4) chemical composition, and (5) reflection of radar waves (bistatic). Earth-based remote sensing and measurements discussed include (1) reflection of sunlight, (2) reflection and scattering of radar waves, and (3) infrared eclipse temperatures. Photographs from the Apollo missions, Lunar Orbiters, and other sources provide a fundamental source of data on the geology and topography of the Moon and a basis for comparing, correlating, and testing the remote sensing and measurements. Relative ages obtained from crater statistics and then empirically correlated with absolute ages indicate that significant lunar volcanism continued to 2.5 b.y. (billion years) ago-some 600 m.y. (million years) after the youngest volcanic rocks sampled by Apollo-and that intensive bombardment of the Moon occurred in the interval of 3.84 to 3.9 b.y. ago. Estimated fluxes of crater-producing objects during the last 50 m.y. agree fairly well with fluxes measured by the Apollo passive seismic stations. Gravity measurements obtained by observing orbiting spacecraft reveal that mare basins have mass concentrations and that the volume of material ejected from the Orientale basin is near 2 to 5 million km 3 depending on whether there has or has not been isostatic compensation, little or none of which has occurred since 3.84 b.y. ago. Isostatic compensation may have occurred in some of the old large lunar basins, but more data are needed to prove it. Steady fields of remanent magnetism were detected by the Apollo 15 and 16 subsatellites
Leachtenauer, J.; And Others
A major design objective of the Natural Resource Information System entailed the use of remote sensing data as an input to the system. Potential applications of remote sensing data were therefore reviewed and available imagery interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and…
Tiner, Ralph W; Klemas, Victor V
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...
Dons, Klaus; Grogan, Kenneth
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...
Baibatsha, A. B.
For work materials used multispectral satellite imagery Landsat (7 channels), medium spatial resolution (14,25-90 m) and a digital elevation model (data SRTM). For interpretation of satellite images and especially their infrared and thermal channels allocated buried paleovalleys pre-paleogene age. Their total length is 228 km. By manifestation of the content of remote sensing paleovalleys distinctly divided into two types, long ribbon-like read in materials and space survey highlights a network of small lakes. By the nature of the relationship established that the second type of river paleovalleys flogs first. On this basis, proposed to allocate two uneven river paleosystem. The most ancient paleovalleys first type can presumably be attributed to karst erosion, blurry chalk and carbon deposits foundation. Paleovalleys may include significant groundwater resources as drinking and industrial purposes. Also we can control the position paleovalleys zinc and bauxite mineralization area and alluvial deposits include uranium mineralization valleys infiltration type and placer gold. Direction paleovalleys choppy, but in general they have a north-east orientation, which is controlled by tectonic zones of the foundation. These zones are defined as the burial place themselves paleovalleys and position of karst cavities in areas interfacing with other structures orientation. The association of mineralization to the caverns in the beds paleovalleys could generally present conditions of formation of mineralization and carry it to the "Niagara" type. The term is obviously best reflects the mechanism of formation of these ores.
A. B. Baibatsha
Full Text Available For work materials used multispectral satellite imagery Landsat (7 channels, medium spatial resolution (14,25–90 m and a digital elevation model (data SRTM. For interpretation of satellite images and especially their infrared and thermal channels allocated buried paleovalleys pre-paleogene age. Their total length is 228 km. By manifestation of the content of remote sensing paleovalleys distinctly divided into two types, long ribbon-like read in materials and space survey highlights a network of small lakes. By the nature of the relationship established that the second type of river paleovalleys flogs first. On this basis, proposed to allocate two uneven river paleosystem. The most ancient paleovalleys first type can presumably be attributed to karst erosion, blurry chalk and carbon deposits foundation. Paleovalleys may include significant groundwater resources as drinking and industrial purposes. Also we can control the position paleovalleys zinc and bauxite mineralization area and alluvial deposits include uranium mineralization valleys infiltration type and placer gold. Direction paleovalleys choppy, but in general they have a north-east orientation, which is controlled by tectonic zones of the foundation. These zones are defined as the burial place themselves paleovalleys and position of karst cavities in areas interfacing with other structures orientation. The association of mineralization to the caverns in the beds paleovalleys could generally present conditions of formation of mineralization and carry it to the "Niagara" type. The term is obviously best reflects the mechanism of formation of these ores.
Deepak R. Mishra
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.
From the earliest need to be able to see an enemy over a hill to sending semi-autonomous platforms with advanced sensor packages out into space, humans have wanted to know more about what is around them. Issues of distance are being minimized through advances in technology to the point where remote control of a sensor is useful but sensing by way of a non-collocated sensor is better. We are not content to just sense what is physically nearby. However, it is not always practical or possible to move sensors to an area of interest; we must be able to sense at a distance. This requires not only new technologies but new approaches; our need to sense at a distance is ever changing with newer challenges. As a result, remote sensing is not limited to relocating a sensor but is expanded into possibly deducing or inferring from available information. Sensing at a distance is the heart of remote sensing. Much of the sensing technology today is focused on analysis of electromagnetic radiation and sound. While these are important and the most mature areas of sensing, this paper seeks to identify future sensing possibilities by looking beyond light and sound. By drawing a parallel to the five human senses, we can then identify the existing and some of the future possibilities. A further narrowing of the field of sensing causes us to look specifically at robotic sensing. It is here that this paper will be directed.
Including an introduction and historical overview of the field, this comprehensive synthesis of the major biophysical applications of satellite remote sensing includes in-depth discussion of satellite-sourced biophysical metrics such as leaf area index.
National Oceanic and Atmospheric Administration, Department of Commerce — The Remote Sensing Division is responsible for providing data to support the Coastal Mapping Program, Emergency Response efforts, and the Aeronautical Survey Program...
Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.
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.
Lackey, J.G.; Burson, Z.G.
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
Jin, Shuanggen; Xie, Feiqin
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.
Hyperspectral remote sensing is an emerging field with many potential applications in the observation, management, and maintenance of the global transportation infrastructure. This report describes the development of an affordable framework to captur...
López Martínez, Fernando
The IR Imaging and Remote Sensing Laboratory – LIR-UC3M of Universidad Carlos III, has developed Multi and Hyper spectral Infrared (IR) analysis techniques for gas remote sensing. Design of specific sensors for the determination of gases and their concentration are proposed. Almost all gases (CO2, CO, NO2, O3, HC o NH, …) related to industrial, environmental or military safety can be detected. Companies or centres with interest in the use of specific application sensors are required.
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.
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.
This report discusses the Remote Sensing, Imaging, and Signal Engineering (RISE) trust area which has been very active in working to define new directions. Signal and image processing have always been important support for existing programs at Lawrence Livermore National Laboratory (LLNL), but now these technologies are becoming central to the formation of new programs. Exciting new applications such as high-resolution telescopes, radar remote sensing, and advanced medical imaging are allowing us to participate in the development of new programs.
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...
Bandini, Filippo; Garcia, Monica; Bauer-Gottwein, Peter
compared to other technologies: compared to field based techniques, remote sensing with UAVs is a non-destructive technique, less time consuming, ensures a reduced time between acquisition and interpretation of data and gives the possibility to access remote and unsafe areas. Compared to full...
Richards, John A
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...
Fingas, M.; Fruhwirth, M.; Gamble, L.
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
Full Text Available With the arrival of the big data era in Earth observation, the remote sensing communities have accumulated a large amount of invaluable and irreplaceable data for global monitoring. These massive remote sensing data have enabled large-area and long-term series Earth observation, and have, in particular, made standard, automated product generation more popular. However, there is more than one type of data selection for producing a certain remote sensing product; no single remote sensor can cover such a large area at one time. Therefore, we should automatically select the best data source from redundant multisource remote sensing data, or select substitute data if data is lacking, during the generation of remote sensing products. However, the current data selection strategy mainly adopts the empirical model, and has a lack of theoretical support and quantitative analysis. Hence, comprehensively considering the spectral characteristics of ground objects and spectra differences of each remote sensor, by means of spectrum simulation and correlation analysis, we propose a suitability evaluation model for product generation. The model will enable us to obtain the Production Suitability Index (PSI of each remote sensing data. In order to validate the proposed model, two typical value-added information products, NDVI and NDWI, and two similar or complementary remote sensors, Landsat-OLI and HJ1A-CCD1, were chosen, and the verification experiments were performed. Through qualitative and quantitative analysis, the experimental results were consistent with our model calculation results, and strongly proved the validity of the suitability evaluation model. The proposed production suitability evaluation model could assist with standard, automated, serialized product generation. It will play an important role in one-station, value-added information services during the big data era of Earth observation.
Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit
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
Powers, W. F.
The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.
Middleton, E. M.; Marcell, R. F.
References relevant to remote sensing of water quality were compiled, organized, and cross-referenced. The following general categories were included: (1) optical properties and measurement of water characteristics; (2) interpretation of water characteristics by remote sensing, including color, transparency, suspended or dissolved inorganic matter, biological materials, and temperature; (3) application of remote sensing for water quality monitoring; (4) application of remote sensing according to water body type; and (5) manipulation, processing and interpretation of remote sensing digital water data.
Zhang Wanliang; Liu Dechang
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)
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.
Lazaridou, Maria A.; Karagianni, Aikaterini Ch.
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.
Srivastava, Prashant K; Gupta, Manika; Islam, Tanvir
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.
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
Chen, H S
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
Meier, G.A.; Brown, Jesslyn F.
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.
Brown, R. L. (Principal Investigator)
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.
Sun, Yu-Zhang; Guo, Lan-Ping; Zhu, Wen-Quan; Huang, Lu-Qi; Gu, Xiao-He; Han, Li-Jian; Pan, Yao-Zhong
Remote sensing technology was used for investigation of the resources of Atractylodes lancea. Firstly, the general situation of Jiangshu Maoshan and A. lancea in Maoshan was introduced; Secondly, the methods of remote sensing on the resource of the wild drugs were explained. Thirdly, the TM images were interpret according to the differences of the objects reflex spectrum, and growth environments in Damao mountain, Ermao mountain and Xiaomao mountain were divided into different sub-areas according to the results of the field investigations. Finally, the resource of A. lancea in Jiangshu Maoshan was estimated.
Hasager, Charlotte Bay
the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground-based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost....... The advantages of microwave satellite remote sensing are 1) horizontal spatial coverage, 2) long data archives and 3) high spatial detail both in the coastal zone and of far-field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to 6 observations per day with near...
Sallee, Jeff; Meier, Lesley R.
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…
Luo, Qiuhua; Shao, Xiaopeng; Peng, Ligen; Wang, Yi; Wang, Lin
A new effective image super resolution (SR) algorithm which is a hybrid of multiple frame Variational Bayesian (VB) reconstruction and single frame Dictionary Learning (DL) reconstruction method is developed to reconstruct a high resolution (HR) satellite image in this article. Firstly, by employing a variational Bayesian analysis, the unknown high resolution image, the acquisition process, the motion parameters and the unknown model parameters are built together in a single mathematical model with a Bayesian formula, and then the distributions of all unknowns are jointly estimated. Without any parameter adjustment, an HR image is adaptively reconstructed from multiple frame low resolution (LR) images. Secondly, by taking the above HR image as input, a higher resolution image can be rebuilt utilizing the statistical correlation between the HR and LR images which is obtained via the DL method. The VB method effectively uses non-redundant information between LR images to recover HR satellite images. Benefit from the dictionary training of magnanimity image, the DL algorithm is able to provide more high-frequency image details, which means this hybrid of VB and DL method combines the above advantages. The experiments show that this proposed algorithm can effectively increase the image resolution of remote sensing images by 0.5times at least comparing with low resolution image.
Review: Estimating evapotranspiration using remote sensing and the Surface Energy Balance System – A South African perspective. ... It is therefore recommended that any further research using the SEBS model in South Africa should be limited to agricultural areas where accurate vegetation parameters can be obtained, ...
The purpose of this publication is to provide the reader with a basis for making an intelligent approach to the use of remote sensing in uranium exploration. It includes: A description of the various techniques; specific applications in view of exploration strategy and selection of appropriate techniques, and some examples of applications; availability and costs; a bibliography
The paper outlines recent developments in using optical remote sensing (ORS) instruments for air quality monitoring both for gaseous pollutants and airborne particulate matter (PM). The U.S. Environmental Protection Agency (EPA) has been using open-path Fourier transform infrared...
Jong, S.M. de; Jetten, V.G.; Kwast, J. van der; Addink, E.A.
The Faculty of Geosciences of Utrecht University in The Netherlands is a suc-cessful research and educational organi-sation (www.geo.uu.nl). The Faculty has four departments: Physical Geography, Earth Sciences, Human Geography & Planning and Innovation & Environmental Sciences. The remote sensing,
Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...
Remote sensing techniques hold considerable promise for the inventory and monitoring of natural resources on rangelands. A significant lack of information concerning basic spectral characteristics of range vegetation and soils has resulted in a lack of rangeland applications. The parameters of interest for range condition ...
Hasager, Charlotte Bay; Badger, Merete; Astrup, Poul
Satellite remote sensing of ocean surface winds are presented with focus on wind energy applications. The history on operational and research-based satellite ocean wind mapping is briefly described for passive microwave, scatterometer and synthetic aperture radar (SAR). Currently 6 GW installed...
Gullies are large and deep erosion depressions or channels normally occurring in drainage ways. They are spectrally heterogeneous, making them difficult to map using pixel based classification technique. The advancement of remote sensing in terms of Geographic Object Based Image Analysis (GEOBIA) provides new ...
Full Text Available With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS-based urban flood vulnerability and risk maps.
Picard, R. H; Dewan, E. M; Winick, J. R; O'Neil, R. R
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...
-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.
We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and
Bikhazi, Nicolas; Young, William F; Nguyen, Hung D
A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.
Veldkamp JG; Velde RJ van de; LBG
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
Colwell, R. N.
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.
Li, Jie; Zhu, Lingling; Cao, Fubin
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.
Dons, Klaus; Grogan, Kenneth
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...... 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...... Change (UNFCCC) and the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) methods sourcebook. These documents provide a generic framework on methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses...
Danielson, R. L.
Computer applications to instruction in any field may be divided into two broad generic classes: computer-managed instruction and computer-assisted instruction. The division is based on how frequently the computer affects the instructional process and how active a role the computer affects the instructional process and how active a role the computer takes in actually providing instruction. There are no inherent characteristics of remote sensing education to preclude the use of one or both of these techniques, depending on the computer facilities available to the instructor. The characteristics of the two classes are summarized, potential applications to remote sensing education are discussed, and the advantages and disadvantages of computer applications to the instructional process are considered.
Ahmad, T.; Hayat, M.F.; Afzal, M.; Asif, H.M.S.; Asif, K.H.
Remote Sensing Application (RSA) is important as one of the critical enabler of e-systems such as e- governments, e-commerce, and e-sciences. In this study, we argued that owning to the specialized needs of RSA such as volatility and interactive nature, a customized Software Engineering (SE) approach should be adapted for their development. Based on this argument we have also identified the shortcomings of the conventional SE approaches and the classical waterfall software development life cycle model. In this study, we have proposed a modification to the classical waterfall software development life cycle model for proposing a customized software development Framework for RSAs. We have identified four (4) different types of changes that can occur to an already developed RS application. The proposed framework was capable to incorporate all four types of changes. Remote Sensing, software engineering, functional requirements, types of changes. (author)
Fingas, Merv; Brown, Carl
Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing. Copyright © 2014 Elsevier Ltd. All rights reserved.
Gausman, H. W.
Remote sensing with infrared color aerial photography (Kodak Ektachrome Infrared Aero 8443 film) for detecting citrus tree anomalies is described. Illustrations and discussions are given for detecting nutrient toxicity symptoms, for detecting foot rot and sooty mold fungal diseases, and for distinguishing among citrus species. Also, the influence of internal leaf structure on light reflectance, transmittance, and absorptance are considered; and physiological and environmental factors that affect citrus leaf light reflectance are reviewed briefly and illustrated.
vital information for studies of deep-ocean circulation and boundary currents, the mid-ocean gyres, tsunamis and ocean currents on synoptic to global...tracks associated with four GPS satellites, colourised by reflected signal power. The picture was generated by Google Earth and GPS Visualizer. Yu et al...not from satellite plat- forms. There are no geodetic services producing GNSS remote sensing products on a continuous, synoptic basis. From the IAG’s
Mikeš, Stanislav; Haindl, Michal; Scarpa, G.; Gaetano, R.
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
Full Text Available Archaeological remote sensing is not a novel discipline. Indeed, there is already a suite of geoscientific techniques that are regularly used by practitioners in the field, according to standards and best practice guidelines. However, (i the technological development of sensors for data capture; (ii the accessibility of new remote sensing and Earth Observation data; and (iii the awareness that a combination of different techniques can lead to retrieval of diverse and complementary information to characterize landscapes and objects of archaeological value and significance, are currently three triggers stimulating advances in methodologies for data acquisition, signal processing, and the integration and fusion of extracted information. The Special Issue “Remote Sensing and Geosciences for Archaeology” therefore presents a collection of scientific contributions that provides a sample of the state-of-the-art and forefront research in this field. Site discovery, understanding of cultural landscapes, augmented knowledge of heritage, condition assessment, and conservation are the main research and practice targets that the papers published in this Special Issue aim to address.
With increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.
Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li
Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.
This report concerns the feasibility of using remotely-sensed data for long-term monitoring of uranium tailings. Decommissioning of uranium mine tailings sites may require long-term monitoring to confirm that no unanticipated release of contaminants occurs. Traditional ground-based monitoring of specific criteria of concern would be a significant expense depending on the nature and frequency of the monitoring. The objective of this study was to evaluate whether available remote-sensing data and techniques were applicable to the long-term monitoring of tailings sites. This objective was met by evaluating to what extent the data and techniques could be used to identify and discriminate information useful for monitoring tailings sites. The cost associated with obtaining and interpreting this information was also evaluated. Satellite and aircraft remote-sensing-based activities were evaluated. A monitoring programme based on annual coverage of Landsat Thematic Mapper data is recommended. Immediately prior to and for several years after decommissioning of the tailings sites, airborne multispectral and thermal infrared surveys combined with field verification data are required in order to establish a baseline for the long-term satellite-based monitoring programme. More frequent airborne surveys may be required if rapidly changing phenomena require monitoring. The use of a geographic information system is recommended for the effective storage and manipulation of data accumulated over a number of years
Adams, John B.; Gillespie, Alan R.
Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge the gap between the engineering and theoretical sides of remote-sensing and the world that we encounter when we venture outdoors. The emphasis is on the practical use of images rather than on theory and mathematical derivations. Examples are drawn from a variety of landscapes and interpretations are tested against the reality seen on the ground. The reader is led through analysis of real images (using figures and explanations); the examples are chosen to illustrate important aspects of the analytic framework. This textbook will form a valuable reference for graduate students and professionals in a variety of disciplines including ecology, forestry, geology, geography, urban planning, archeology and civil engineering. It is supplemented by a web-site hosting digital color versions of figures in the book as well as ancillary images (www.cambridge.org/9780521662214). Presents a coherent view of practical remote sensing, leading from imaging and field work to the generation of useful thematic maps Explains how to apply physical models to help interpret spectral images Supplemented by a website hosting digital colour versions of figures in the book, as well as additional colour figures
Full Text Available The present paper aims at analyzing the potentialities of noninvasive remote sensing techniques used for detecting the conservation status of infrastructures. The applied remote sensing techniques are ground-based microwave radar interferometer and InfraRed Thermography (IRT to study a particular structure planned and made in the framework of the ISTIMES project (funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme. To exploit the effectiveness of the high-resolution remote sensing techniques applied we will use the high-frequency thermal camera to measure the structures oscillations by high-frequency analysis and ground-based microwave radar interferometer to measure the dynamic displacement of several points belonging to a large structure. The paper describes the preliminary research results and discusses on the future applicability and techniques developments for integrating high-frequency time series data of the thermal imagery and ground-based microwave radar interferometer data.
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
Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent
The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal
Jackson, T.J.; Schmugge, T.J.
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
Full Text Available Looting of archaeological sites is illegal and considered a major anthropogenic threat for cultural heritage, entailing undesirable and irreversible damage at several levels, such as landscape disturbance, heritage destruction, and adverse social impact. In recent years, the employment of remote sensing technologies using ground-based and/or space-based sensors has assisted in dealing with this issue. Novel remote sensing techniques have tackled heritage destruction occurring in war-conflicted areas, as well as illicit archeological activity in vast areas of archaeological interest with limited surveillance. The damage performed by illegal activities, as well as the scarcity of reliable information are some of the major concerns that local stakeholders are facing today. This study discusses the potential use of remote sensing technologies based on the results obtained for the archaeological landscape of Ayios Mnason in Politiko village, located in Nicosia district, Cyprus. In this area, more than ten looted tombs have been recorded in the last decade, indicating small-scale, but still systematic, looting. The image analysis, including vegetation indices, fusion, automatic extraction after object-oriented classification, etc., was based on high-resolution WorldView-2 multispectral satellite imagery and RGB high-resolution aerial orthorectified images. Google Earth© images were also used to map and diachronically observe the site. The current research also discusses the potential for wider application of the presented methodology, acting as an early warning system, in an effort to establish a systematic monitoring tool for archaeological areas in Cyprus facing similar threats.
Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.
LANDSAT imagery at the scale of 1:250.000 and obtained from bands 5 and 7 as well as computer compatible tapes were used to evaluate the effectiveness of remotely sensed orbital data in inventorying forests in a 462,100 area of Brazil emcompassing the cities of Ribeirao, Altinopolis Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Santa Rita do Passa Quatro, and Santa Rosa do Viterbo. Visual interpretation of LANDSAT imagery shows that 37,766 hectares (1977) and 38,003.75 hectares (1979) were reforested areas of pine and eucalyptus species. An increment of 237.5 hectares was found during this two-year time lapse.
Parada, N. D. J. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.
The utilization of remotely sensed orbital data for forestry inventory. The study area (approximately 491,100 ha) encompasses the municipalities of Ribeirao Preto, Altinopolis, Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Sant Rita do Passa Quatro and Santa Rosa do Viterbo (Sao Paulo State). Materials used were LANDSAT data from channels 5 and 7 (scale 1:250,000) and CCT's. Visual interpretation of the imagery showed that for 1977 a total of 37,766.00 ha and for 1979 38,003.75 ha were reforested with Pinus and Eucalyptus within the area under study. The results obtained show that LANDSAT data can be used efficiently in forestry inventory studies.
Reliable, high-capacity communications in scattering media can be effectively established with some basic remote sensing techniques involving time reversal. I will formulate these problems and discuss the various mathematical approaches that can be used for analysis. It turns out that stochastic analysis plays an important role and, in some cases, gives very satisfactory results. One such result is the spectacular increase in communications capacity in a richly scattering environment. I will end with a discussion of applications and computational issues that arise in the realistic simulation of communication systems.
Siegal, B.S.; Welby, C.W.
Remote sensing techniques enhance the selection and evaluation process for nuclear power plant siting. The principal advantage is the synoptic view which improves recognition of linear features, possibly indicative of faults. The interpretation of such images, in conjunction with seismological studies, also permits delineation of seismo-tectonic provinces. In volcanic terrains, geomorphic-age boundaries can be delineated and volcanic centers identified, providing necessary guidance for field sampling and regional model derivation. The use of such techniques is considered for studies in the Philippines, Mexico, and Greece. 5 refs
Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks.
, in modern space sciences, its usage is restricted to mean detection of features at or near the earth's surface from space using electromagnetic radiation. Remote sensing is often considered as opposite of astronomy. In astronomy, we observe the space from... the entire area in one day, nor afford 100 ships stationed in such an area (one ship per 10 sq. km.). Satellite on the other hand, circle the entire earth in a couple of hours and simultaneously send all observationa to a ground receiving station for online...
Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.
A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.
Kiefer, R. W.
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.
Velsko, S.P.; Webb, M.S.; Cook, W.M.; Neuman, W.A.
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
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
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
Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen
This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface tempera...
De, Ch.; Chakraborty, B.
=UTF-8 3868 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 49, NO. 10, OCTOBER 2011 Model-Based Acoustic Remote Sensing of Seafloor Characteristics Chanchal De and Bishwajit Chakraborty, Member, IEEE Abstract—The characterization... of the estimated values of seafloor roughness spectrum parameters with the values of sediment mean grain size are compared with published information available in the literature. Index Terms—Acoustic remote sensing, backscatter model, echo envelope, inversion, mean...
Full Text Available million (UNESCO, 2009). The destructive forces of storms mainly results from the impact of: ? Waves, leading to shoreline erosion ? Wind ? Flooding. Coastal areas which are low-lying and sandy are particularly vulnerable, as can be found along most... such as shoreline erosion or flooding. Coastal remote sensing, as we define it, is bridging the gap between classic terrestrial and marine remote sensing. However, to date, coastal remote sensing competency and applications are very scarce and undeveloped...
Conradsen, K.; Nilsson, G.; Thyrsted, T.
A research project, aiming at investigation the use of remote sensing in uranium exploration, has been accomplished on data from South Greenland. During the project, analyses have been done on pure remote sensing data (Landsat MSS) and on integrated data of various types, including geochemical, aeromagnetic, radiometric and geological data in addition to the MSS data. Ratioing, factor analysis and discriminant analysis were used for enhancement of colour anomalies which correspond to oxidation zones. Some of the anomalies coincide with U and Nb mineralizations. Lineaments were mapped visually from photoprints, digitized and analysed statistically. A sinusoidal model could be applied to the general directional frequency distribution and was used to define ten classes of significant directions. Three of these directions were of major geological significance. Thus some of the major alkaline intrusions are situated at the intersections of some of the lineaments, a particular NE-SW trending lineament coincides with a geochemical boundary and pitchblende occurrences may be related to a WNW-ESE direction. The various types of data set were brought onto format of the Landsat images and collected in a data base. Representing three different types of data (Landsat MSS-band 7, aeromagnetic data and the geochemical Fe-content of stream sediments) on basis of intensity, hue and saturation revealed new features among which can be mentioned a possible indication of a subsurface continuation of one of the major alkaline intrusions. (author)
This paper presents a study for linking remotely sensed data with property tax related issues. First, it discusses the key attributes required for property taxation and evaluates the capabilities of remote sensing technology to measure these attributes accurately at parcel level. Next, it presents a detailed case study of six representative wards of different characteristics in Dehradun, India, that illustrates how measurements of several of these attributes supported by field survey can be combined to address the issues related to property taxation. Information derived for various factors quantifies the property taxation contributed by an average dwelling unit of the different income groups. Results show that the property tax calculated in different wards varies between 55% for the high-income group, 32% for the middle-income group, 12% for the low-income group and 1% for squatter units. The study concludes that higher spatial resolution satellite data and integrates social survey helps to assess the socio-economic status of the population for tax contribution purposes.
Jacobs, J. M.; Myers, D. A.; Anderson, M. C.
The application of remote sensing methods to estimate evapotranspiration has the advantage of good spatial resolution and excellent spatial coverage, but may have the disadvantage of infrequent sampling and considerable expense. The GOES satellites provide enhanced temporal resolution with hourly estimates of solar radiation and have a spatial resolution that is significantly better than that available from most ground-based pyranometer networks. As solar radiation is the primary forcing variable in wetland evapotranspiration, the opportunity to apply GOES satellite data to wetland hydrologic analyses is great. An accuracy assessment of the remote sensing product is important and the subsequent validation of the evapotranspiration estimates are a critical step for the use of this product. A wetland field experiment was conducted in the Paynes Prairie Preserve, North Central Florida during a growing season characterized by significant convective activity. Evapotranspiration and other surface energy balance components of a wet prairie community dominated by Panicum hemitomon (maiden cane), Ptilimnium capillaceum (mock bishop's weed), and Eupatorium capillifolium (dog fennel) were investigated. Incoming solar radiation derived from GOES-8 satellite observations, in combination with local meteorological measurements, were used to model evapotranspiration from a wetland. The satellite solar radiation, derived net radiation and estimated evapotranspiration estimates were compared to measured data at 30-min intervals and daily times scales.
Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.
In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.
Serafin, Robert J.; Szejwach, Gerard; Phillips, Byron B.
The potential for airborne remote sensing for atmospheric sciences research and in particular for research over the oceans is explored. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. There exists promising candidates of both active and passive types in the electromagnetic spectrum from microwave to visible wavelengths. Short-range, rapid response measurements of temperature, water vapor, winds, and turbulence are all possible using infrared radiometry and Doppler lidar velocimetry. Pulsed Doppler radar for measurements of the three-dimensional structures of winds and hydrometeors in precipitating systems has been clearly established. Pulsed Doppler lidar is less well developed in comparison to Doppler radar but promises to be an important complement to radar observations by providing wind measurements in the nonprecipitating and cloud free atmosphere. It is possible now to equip a single aircraft or several aircraft with a variety of remote sensing instruments that together form a powerful, highly mobile atmospheric observing system for measurement of fundamental meteorological variables in three dimensions on a variety of spatial scales. This capability is of major importance to the study of mesoscale systems, particularly to those over the ocean, where the deployment of surface based sensors is exceedingly difficult, if not impossible, and costly.
Corey, J.C.; Mackey, H.E. Jr.
A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.
Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund
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.
Hayden, L. B.; Johnson, D.; Baltrop, J.
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
Haller, M. C.; Catalan, P.
The wave roller has a primary influence on the balances of mass and momentum in the surf zone (e.g. Svendsen, 1984; Dally and Brown, 1995; Ruessink et al., 2001). In addition, the roller area and its angle of inclination on the wave front are important quantities governing the dissipation rates in breaking waves (e.g Madsen et al., 1997). Yet, there have been very few measurements published of individual breaking wave roller geometries in shallow water. A number of investigators have focused on observations of the initial jet-like motion at the onset of breaking before the establishment of the wave roller (e.g. Basco, 1985; Jansen, 1986), while Govender et al. (2002) provide observations of wave roller vertical cross-sections and angles of inclination for a pair of laboratory wave conditions. Nonetheless, presently very little is known about the growth, evolution, and decay of this aerated region of white water as it propagates through the surf zone; mostly due to the inherent difficulties in making the relevant observations. The present work is focused on analyzing observations of the time and space scales of individual shallow water breaking wave rollers as derived from remote sensing systems. Using a high-resolution video system in a large-scale laboratory facility, we have obtained detailed measurements of the growth and evolution of the wave breaking roller. In addition, by synchronizing the remote video with in-situ wave gages, we are able to directly relate the video intensity signal to the underlying wave shape. Results indicate that the horizontal length scale of breaking wave rollers differs significantly from the previous observations of Duncan (1981), which has been a traditional basis for roller model parameterizations. The overall approach to the video analysis is new in the sense that we concentrate on individual breaking waves, as opposed to the more commonly used time-exposure technique. In addition, a new parameter of interest, denoted Imax, is
Porter, Reid B [Los Alamos National Laboratory; Hush, Do [Los Alamos National Laboratory; Harvey, Neal [Los Alamos National Laboratory; Theile, James [Los Alamos National Laboratory
To move from data to information in almost all science and defense applications requires a human-in-the-loop to validate information products, resolve inconsistencies, and account for incomplete and potentially deceptive sources of information. This is a key motivation for visual analytics which aims to develop techniques that complement and empower human users. By contrast, the vast majority of algorithms developed in machine learning aim to replace human users in data exploitation. In this paper we describe a recently introduced machine learning problem, called rare category detection, which may be a better match to visual analytic environments. We describe a new design criteria for this problem, and present comparisons to existing techniques with both synthetic and real-world datasets. We conclude by describing an application in broad-area search of remote sensing imagery.
Lawrence, Gary W.; King, Roger; Kelley, Amber T.; Vickery, John
A method and apparatus for remote sensing of parasitic nematodes in plants, now undergoing development, is based on measurement of visible and infrared spectral reflectances of fields where the plants are growing. Initial development efforts have been concentrated on detecting reniform nematodes (Rotylenchulus reniformis) in cotton plants, because of the economic importance of cotton crops. The apparatus includes a hand-held spectroradiometer. The readings taken by the radiometer are processed to extract spectral reflectances at sixteen wavelengths between 451 and 949 nm that, taken together, have been found to be indicative of the presence of Rotylenchulus reniformis. The intensities of the spectral reflectances are used to estimate the population density of the nematodes in an area from which readings were taken.
Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.
Siegal, B.S.; Welby, C.W.
It is shown that satellite remote sensing provides timely and cost-effective information for siting and site evaluation of nuclear power plants. Side-looking airborne radar (SLAR) imagery is especially valuable in regions of prolonged cloud cover and haze, and provides additional assurance in siting and licensing. In addition, a wide range of enhancement techniques should be employed and different types of image should be color-combined to provide structural and lithologic information. Coastal water circulation can also be studied through repetitive coverage and the inherently synoptic nature of imaging satellites. Among the issues discussed are snow cover, sun angle, and cloud cover, and actual site evaluation studies in the Bataan peninsula of the Philippines and Laguna Verde, California
Rush, M.; Goldstein, J.; Hsi, B. P.; Olsen, C. B.
An urban area was studied through the use of the inventory-by-surrogate method rather than by direct interpretation of photographic imagery. Prior uses of remote sensing in urban and public research are examined. The effects of crowding, poor housing conditions, air pollution, and street conditions on public health are considered. Color infrared photography was used to categorize land use features and the grid method was used in photo interpretation analysis. The incidence of shigella and salmonella, hepatitis, meningitis, tuberculosis, myocardial infarction and veneral disease were studied, together with mortality and morbidity rates. Sample census data were randomly collected and validated. The hypothesis that land use and residential quality are associated with and act as an influence upon health and physical well-being was studied and confirmed.
Full Text Available The main objective of this article was to show an application of principal component analysis (PCA which is used in two science degrees. Particularly, PCA analysis was used to obtain information of the land cover from satellite images. Three Landsat images were selected from two areas which were located in the municipalities of Gandia and Vallat, both in the Valencia province (Spain. In the first study area, just one Landsat image of the 2005 year was used. In the second study area, two Landsat images were used taken in the 1994 and 2000 years to analyse the most significant changes in the land cover. According to the results, the second principal component of the Gandia area image allowed detecting the presence of vegetation. The same component in the Vallat area allowed detecting a forestry area affected by a forest fire. Consequently in this study we confirmed the feasibility of using PCA in remote sensing to extract land use information.
J. P. Stals
Full Text Available Earth observation (EO data is effective in monitoring agricultural cropping activity over large areas. An example of such an application is the GeoTerraImage crop type classification for the South African Crop Estimates Committee (CEC. The satellite based classification of crop types in South Africa provides a large scale, spatial and historical record of agricultural practices in the main crop growing areas. The results from these classifications provides data for the analysis of trends over time, in order to extract valuable information that can aid decision making in the agricultural sector. Crop cultivation practices change over time as farmers adapt to demand, exchange rate and new technology. Through the use of remote sensing, grain crop types have been identified at field level since 2008, providing a historical data set of cropping activity for the three most important grain producing provinces of Mpumalanga, Freestate and North West province in South Africa. This historical information allows the analysis of farm management practices to identify changes and trends in crop rotation and irrigation practices. Analysis of crop type classification over time highlighted practices such as: frequency of cultivation of the same crop on a field, intensified cultivation on centre pivot irrigated fields with double cropping of a winter grain followed by a summer grain in the same year and increasing cultivation of certain types of crops over time such as soyabeans. All these practices can be analysed in a quantitative spatial and temporal manner through the use of the remote sensing based crop type classifications.
Mitchell, Jessica J.; Glenn, Nancy F.; Sankey, Temuulen T.; Derryberry, DeWayne R.; Germino, Matthew J.
This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R2 value of 0.72 and an R2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R2 to 0.95 (R2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.
Latchininsky, Alexandre V.
A dozen species of locusts (Orthoptera: Acrididae) are a major threat to food security worldwide. Their outbreaks occur on every continent except Antarctica, threatening the livelihood of 10% of the world's population. The locusts are infamous for their voracity, polyphagy, and capacity for long-distance migrations. Decades of research revealed very complex bio-ecology of locusts. They exist in two, inter-convertible and density-dependent states, or "phases." Despite the evident progress in understanding locust behavior, our ability to predict and manage locust outbreaks remains insufficient, as evidenced by locust plagues still occurring during the 21st century. One of the main reasons is that locusts typically inhabit remote and scarcely populated areas, and their distribution ranges often spread across continents. This creates tremendous obstacles for locust population monitoring and control. Traditional ground locust surveys are inadequate to address the enormous spatial scale of the locust problem in a limited window of time dictated by the pest's development. Remote sensing (satellite information) appears a promising tool in locust monitoring. Satellite data are increasingly used for monitoring and forecasting two locust species, the desert and the Australian plague locust. However, applications of this geospatial technology to other locust species remain rare.
Dozier J 1989a Remote sensing of snow in the visible and near-infrared wavelengths; In: Theory and Applications of. Optical Remote Sensing (ed.) Asrar G (New York: John. Wiley and Sons), pp. 527–547. Dozier J 1989b Spectral signature of alpine snow cover from the Landsat Thematic Mapper; Rem. Sens. Environ. 28.
Eisgruber, L. M.
A theoretical framwork is outlined for estimating social returns from research and application of remote sensing. The approximate dollar magnitude is given of a particular application of remote sensing, namely estimates of corn production, soybeans, and wheat. Finally, some comments are made on the limitations of this procedure and on the implications of results.
Sy, de V.; Herold, M.; Achard, F.; Asner, G.P.; Held, A.; Kellndorfer, J.; Verbesselt, J.
Remote sensing technologies can provide objective, practical and cost-effective solutions for developing and maintaining REDD+ monitoring systems. This paper reviews the potential and status of available remote sensing data sources with a focus on different forest information products and synergies
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
Raymond L. Czaplewski
Global and regional assessaents require timely information on landscape level status (e.g., areal extent of different ecosystems) and processes (e.g., changes in land use and land cover). To measure and understand these processes at the regional level, and model their impacts, remote sensing is often necessary. However, processing massive volumes of remotely sensing...
present study, Remote Sensing (RS) and Geographical Information System (GIS) techniques were used. Remotely sensed .... growing stock in Tahno range of Dehradun Forest Division. Okhandiara (2008) .... areas on an image by identifying 'training' sites of known targets and then extrapolating those spectral signatures to ...
This study examines the special advantage offered by GIS-Remote Sensing processing to survey of vegetation, a renewable natural resource in Ibadan, South-Western, Nigeria with a view to eliciting support for sound environmental policy in the future. A remotely sensed digital image of SPOT by its linear enhancement on ...
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 ...
Full Text Available at the coast is that it is in a permanent state of change. Remote sensing, whether from orbiting (space-borne) or air-borne platforms, can greatly assist in the task of monitoring coastal environments. In particular, remote sensing enables simultaneous or near...
Philip Riggan; Lynn Wolden; Bob Tissell; David Weise; J. Coen
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...
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 ...
The principal objective of this study is to identify, demarcate and map agricultural land use categories of Tehran province on basis of remote sensing survey technique. In this research, Landsat ETM images of July 2006 were used to expose the use of remote sensing technique in order to produce current land use map of the ...
Warren B. Cohen; Samuel N. Goward
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...
Weinstein, R. H.
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.
... intrusive having remanent magnetization corresponding to upper normal and reverse polarity (29N and 29R) of the Deccan basalt magnetostratigrahy. Analysis of remote sensing and geological data also reveals the predominance of ENE–WSW structural faults. Integration of remote sensing, geological and potential field ...
Seebach, Lucia Maria
the need for harmonised forest information can be satisfied using remote sensing methods. In conclusion, the study showed that it is possible to derive harmonised forest information of high spatial detail in Europe with remote sensing. The study also highlighted the imperative provision of accuracy...
Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun
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...
Fujikawa, S.; Uchida, K.; Tanaka, S.; Jingo, H. [Dowa Engineering Co. Ltd., Tokyo (Japan); Hato, M. [Earth Remote Sensing Data Analysis Center, Tokyo (Japan)
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.
Harper, Warren W.; Schultz, John F.
Spectroscopic chemical sensing research at Pacific Northwest National Laboratory (PNNL) is focused on developing advanced sensors for detecting the production of nuclear, chemical, or biological weapons; use of chemical weapons; or the presence of explosives, firearms, narcotics, or other contraband of significance to homeland security in airports, cargo terminals, public buildings, or other sensitive locations. For most of these missions, the signature chemicals are expected to occur in very low concentrations, and in mixture with ambient air or airborne waste streams that contain large numbers of other species that may interfere with spectroscopic detection, or be mistaken for signatures of illicit activity. PNNL’s emphasis is therefore on developing remote and sampling sensors with extreme sensitivity, and resistance to interferents, or selectivity. PNNL’s research activities include: 1. Identification of signature chemicals and quantification of their spectral characteristics, 2. Identification and development of laser and other technologies that enable breakthroughs in sensitivity and selectivity, 3. Development of promising sensing techniques through experimentation and modeling the physical phenomenology and practical engineering limitations affecting their performance, and 4. Development and testing of data collection methods and analysis algorithms. Close coordination of all aspects of the research is important to ensure that all parts are focused on productive avenues of investigation. Close coordination of experimental development and numerical modeling is particularly important because the theoretical component provides understanding and predictive capability, while the experiments validate calculations and ensure that all phenomena and engineering limitations are considered.
Full Text Available In order to assess the extent of the decline of mangrove ecosystems, extensive mapping and monitoring programs are needed. To monitor the change in large-scale coverage of mangrove areas over certain periods of time, remote sensing technology offers many advantages compared to conventional field monitoring. The main benefit of using remote sensing is related to its speed and continuity in collecting space images of a broad area of the Earth’s surface. With the specific application on mangrove studies, remote sensing enables spatial and spectral information to be collected from the mangrove forests environment mostly located in inaccessible areas, where ground measurements become difficult and expensive. This review of the literature emphasizes the application of remote sensing in change detection and mapping of mangrove ecosystems. Key words : mangroves, remote sensing, mapping, field monitoring, continuity
Zhang, Hong; Shen, Jinxiang; Ma, Yanmei
Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.
Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan
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...
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
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
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
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
Full Text Available Land cover classification has been widely investigated in remote sensing for agricultural, ecological and hydrological applications. Landsat images with multispectral bands are commonly used to study the numerous classification methods in order to improve the classification accuracy. Thermal remote sensing provides valuable information to investigate the effectiveness of the thermal bands in extracting land cover patterns. k-NN and Random Forest algorithms were applied to both the single Landsat 8 image and the time series Landsat 4/5 images for the Attert catchment in the Grand Duchy of Luxembourg, trained and validated by the ground-truth reference data considering the three level classification scheme from COoRdination of INformation on the Environment (CORINE using the 10-fold cross validation method. The accuracy assessment showed that compared to the visible and near infrared (VIS/NIR bands, the time series of thermal images alone can produce comparatively reliable land cover maps with the best overall accuracy of 98.7% to 99.1% for Level 1 classification and 93.9% to 96.3% for the Level 2 classification. In addition, the combination with the thermal band improves the overall accuracy by 5% and 6% for the single Landsat 8 image in Level 2 and Level 3 category and provides the best classified results with all seven bands for the time series of Landsat TM images.
Full Text Available Unmanned Aerial Vehicles (UAVs have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1 mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2 power supply and control parts; (3 onboard application components. This platform covers five degrees of freedom (DOFs: horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail’s repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies.
Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong
Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1) mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2) power supply and control parts; (3) onboard application components. This platform covers five degrees of freedom (DOFs): horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail's repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies.
Brown, Molly E.
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
Smith, James A.
Remote sensing has proved a fruitful tool for understanding the distribution and functioning of plant communities at multiple scales and to understand their coupling to bioclimatic and anthropogenic factors. But a similar approach to understanding the distribution and abundance of bird species as well as many other animal organisms is lacking. The increasing need for such understanding is evident with the recent examples of threats to human health via avian vector transmission and the increasing emphasis on global conservation biology. From experimental observations we know that species richness tends to track biological or environmental gradients. In this paper, we explore the fundamental idea that thermal and water-relation environments of birds, as estimated from satellite data and biophysical models, can define the constraints on their Occurrences and richness. We develop individual bird energy budget models and use these models to define the climate space niche of birds. Using satellite data assimilation products to drive our models, we disperse a distribution of virtual or actual bird species across the landscape in accordance to the limits expressed by their climate space niche. Here, we focus on the North American summer breeding season and give two examples to illustrate our approach. The first is a tundra loving bird, e.g. corresponding to the Culidris genus, and a second genus example, Myiurchus, that corresponds to arid or semi-arid regions. We define these birds in terms of their basic physiology and morphological characteristics, construct avian energetic simulations to predict their allowable metabolic ranges and climate space limits.
I utilized state the art remote sensing and GIS (Geographical Information System) techniques to study large scale biological, physical and ecological processes of coastal, nearshore, and offshore waters of Lake Michigan and Lake Superior. These processes ranged from chlorophyll alpha and primary production time series analysies in Lake Michigan to coastal stamp sand threats on Buffalo Reef in Lake Superior. I used SeaWiFS (Sea-viewing Wide Field-of-view Sensor) satellite imagery to trace various biological, chemical and optical water properties of Lake Michigan during the past decade and to investigate the collapse of early spring primary production. Using spatial analysis techniques, I was able to connect these changes to some important biological processes of the lake (quagga mussels filtration). In a separate study on Lake Superior, using LiDAR (Light Detection and Ranging) and aerial photos, we examined natural coastal erosion in Grand Traverse Bay, Michigan, and discussed a variety of geological features that influence general sediment accumulation patterns and interactions with migrating tailings from legacy mining. These sediments are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.
Pena, Alfredo; Hasager, Charlotte Bay; Gryning, Sven-Erik; Courtney, Michael; Antoniou, Ioannis; Mikkelsen, Torben; Soerensen, Paul
Ground-based remote sensing instruments can observe winds at different levels in the atmosphere where the wind characteristics change with height: the range of heights where modern turbine rotors are operating. A six-month wind assessment campaign has been made with a LiDAR (Light Detection And Ranging) and a SoDAR (Sound Detection and Ranging) on the transformer/platform of the world's largest offshore wind farm located at the West coast of Denmark to evaluate their ability to observe offshore winds. The high homogeneity and low turbulence levels registered allow the comparison of LiDAR and SoDAR with measurements from cups on masts surrounding the wind farm showing good agreement for both the mean wind speed and the longitudinal component of turbulence. An extension of mean wind speed profiles from cup measurements on masts with LiDAR observations results in a good match for the free sectors at different wind speeds. The log-linear profile is fitted to the extended profiles (averaged over all stabilities and roughness lengths) and the deviations are small. Extended profiles of turbulence intensity are also shown for different wind speeds up to 161 m. Friction velocities and roughness lengths calculated from the fitted log-linear profile are compared with the Charnock model which seems to overestimate the sea roughness for the free sectors
Full Text Available Hyperspectral remote sensing imagery contains much more information in the spectral domain than does multispectral imagery. The consecutive and abundant spectral signals provide a great potential for classification and anomaly detection. In this study, two real hyperspectral data sets were used for anomaly detection. One data set was an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS data covering the post-attack World Trade Center (WTC and anomalies are fire spots. The other data set called SpecTIR contained fabric panels as anomalies compared to their background. Existing anomaly detection algorithms including the Reed–Xiaoli detector (RXD, the blocked adaptive computation efficient outlier nominator (BACON, the random selection based anomaly detector (RSAD, the weighted-RXD (W-RXD, and the probabilistic anomaly detector (PAD are reviewed here. The RXD generally sets strict assumptions to the background, which cannot be met in many scenarios, while BACON, RSAD, and W-RXD employ strategies to optimize the estimation of background information. The PAD firstly estimates both background information and anomaly information and then uses the information to conduct anomaly detection. Here, the BACON, RSAD, W-RXD, and PAD outperformed the RXD in terms of detection accuracy, and W-RXD and PAD required less time than BACON and RSAD.
Morey, Mark; O'Neill, Mary; Hahn, Mark; DiBenedetto, John
There is a need for stable test standards for many remote sensing applications that can be used both in the laboratory and in rugged test environments. Ideally these standards would be stable over time such that the same standard could be used from year to year for comparison of system performance. While ink-jet and spray gun methods can disperse controlled doses of dissolved analytes, methods to maintain particle size spectral variations are lacking. In addition, standards that are environmentally robust and stable over time are limited. As part of the recent Lighthouse work toward a Hyperspectral Imagery (HSI) proximal handheld sensor, Special Technologies Laboratory (STL) was tasked to do preliminary work toward a rugged, transportable, waterproof target board. This involved developing test standards using minerals of known particle sizes that have spectrally relevant features. Mineral powders were dispersed in binders that did not change their spectral characteristics. These standards were packaged such that they could be transported and used repeatedly. This paper discusses the methodology for developing this preliminary set of targets. Target sizes were limited to the proximal case, and further work is required to finalize the optimum binder and examine other possible appropriate minerals.
Fingas, Merv; Brown, Carl E
The technical aspects of oil spill remote sensing are examined and the practical uses and drawbacks of each technology are given with a focus on unfolding technology. The use of visible techniques is ubiquitous, but limited to certain observational conditions and simple applications. Infrared cameras offer some potential as oil spill sensors but have several limitations. Both techniques, although limited in capability, are widely used because of their increasing economy. The laser fluorosensor uniquely detects oil on substrates that include shoreline, water, soil, plants, ice, and snow. New commercial units have come out in the last few years. Radar detects calm areas on water and thus oil on water, because oil will reduce capillary waves on a water surface given moderate winds. Radar provides a unique option for wide area surveillance, all day or night and rainy/cloudy weather. Satellite-carried radars with their frequent overpass and high spatial resolution make these day-night and all-weather sensors essential for delineating both large spills and monitoring ship and platform oil discharges. Most strategic oil spill mapping is now being carried out using radar. Slick thickness measurements have been sought for many years. The operative technique at this time is the passive microwave. New techniques for calibration and verification have made these instruments more reliable.
Schowengerdt, Robert A
This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, s
Full Text Available Remotely sensed land surface temperature (LST downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK, downscaling cokriging (DSCK, kriging with external drift (KED and area-to-point regression kriging (ATPRK, are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.
Brost, Randolph; Perkins, David Nikolaus
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.
Full Text Available Since the remote sensing data of MODIS has some advantages of short detection period, wide coverage and open access, it is suitable for large-scale, dynamic agricultural remote sensing monitoring. According to the application requirements of winter wheat acreage extracting in Huang- Huai region, this article analyzes the features of MODIS data and phenological characteristics of crops. Three kinds of MODIS data and five remote sensing indices are used in winter wheat acreage monitoring. The results show that the five-day synthetic MODIS data product has a better extraction accuracy, and the indices of NDVI and NDWI are better for crop monitoring in early phase of winter wheat.
This volume debuts the new scope of Remote Sensing, which was first defined as the analysis of data collected by sensors that were not in physical contact with the objects under investigation (using cameras, scanners, and radar systems operating from spaceborne or airborne platforms). A wider characterization is now possible: Remote Sensing can be any non-destructive approach to viewing the buried and nominally invisible evidence of past activity. Spaceborne and airborne sensors, now supplemented by laser scanning, are united using ground-based geophysical instruments and undersea remote sensing, as well as other non-invasive techniques such as surface collection or field-walking survey. Now, any method that enables observation of evidence on or beneath the surface of the earth, without impact on the surviving stratigraphy, is legitimately within the realm of Remote Sensing. The new interfaces and senses engaged in Remote Sensing appear throughout the book. On a philosophical level, this is about the landscap...
Husak, G. J.; Funk, C. C.; Verdin, J. P.; Rowland, J.; Budde, M. E.
The Famine Early Warning Systems Network (FEWS NET) is a U.S. Agency for International Development (USAID) supported project designed to monitor and anticipate food insecurity in the developing world, primarily Africa, Central America, the Caribbean and Central Asia. This is done through a network of partners involving U.S. government agencies, universities, country representatives, and partner institutions. This presentation will focus on the remotely sensed data used in FEWS NET activities and capacity building efforts designed to expand and enhance the use of FEWS NET tools and techniques. Remotely sensed data are of particular value in the developing world, where ground data networks and data reporting are limited. FEWS NET uses satellite based rainfall and vegetation greenness measures to monitor and assess food production conditions. Satellite rainfall estimates also drive crop models which are used in determining yield potential. Recent FEWS NET products also include estimates of actual evapotranspiration. Efforts are currently underway to assimilate these products into a single tool which would indicate areas experiencing abnormal conditions with implications for food production. FEWS NET is also involved in a number of capacity building activities. Two primary examples are the development of software and training of institutional partners in basic GIS and remote sensing. Software designed to incorporate rainfall station data with existing satellite-derived rainfall estimates gives users the ability to enhance satellite rainfall estimates or long-term means, resulting in gridded fields of rainfall that better reflect ground conditions. Further, this software includes a crop water balance model driven by the improved rainfall estimates. Finally, crop parameters, such as the planting date or length of growing period, can be adjusted by users to tailor the crop model to actual conditions. Training workshops in the use of this software, as well as basic GIS and
My presentation will begin with the discussion of the Intercomparison of three-dimensional (3D) Radiative Codes (13RC) project that has been started in 1997. I will highlight the question of how well the atmospheric science community can solve the 3D radiative transfer equation. Initially I3RC was focused only on algorithm intercomparison; now it has acquired a broader identity providing new insights and creating new community resources for 3D radiative transfer calculations. Then I will switch to satellite remote sensing. Almost all radiative transfer calculations for satellite remote sensing are one-dimensional (1D) assuming (i) no variability inside a satellite pixel and (ii) no radiative interactions between pixels. The assumptions behind the 1D approach will be checked using cloud and aerosol data measured by the MODerate Resolution Imaging Spectroradiometer (MODIS) on board of two NASA satellites TERRA and AQUA. In the discussion, I will use both analysis technique: statistical analysis over large areas and time intervals, and single scene analysis to validate how well the 1D radiative transfer equation describes radiative regime in cloudy atmospheres.
Walter, Steven J.
Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid, and precipitation, emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band because communication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of water vapor-induced propagation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity wave experiments, and radio science missions. During 1993, WVRs provided data for propagation model development, supported planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily
.... This effort is cooperatively conducted with the professional researchers at the Remote Sensing GIS Center of the US Army Cold Regions Research and Engineering Laboratory in Hanover, New Hampshire...
Prashad, L.; Christensen, P. R.; Anwar, S.; Dickenshied, S.; Engle, E.; Noss, D.
The ASU 100 Cities Project and the ASU Mars Space Flight Facility (MSFF) present JEarth, a set of analytical Geographic Information System (GIS) tools for viewing and processing Earth-based remote sensing imagery and vectors, including high-resolution and hyperspectral imagery such as TIMS and MASTER. JEarth is useful for a wide range of researchers and practitioners who need to access, view, and analyze remote sensing imagery. JEarth stems from existing MSFF applications: the Java application JMars (Java Mission-planning and Analysis for Remote Sensing) for viewing and analyzing remote sensing imagery and THMPROC, a web-based, interactive tool for processing imagery to create band combinations, stretches, and other imagery products. JEarth users can run the application on their desktops by installing Java-based open source software on Windows, Mac, or Linux operating systems.
He, Qiang; Chu, Chee-Hung Henry
Remote sensing is widely used to assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, the data collection of aerial digital images is constrained with bad weather, muzzy atmosphere, and unstable camera or camcorder. As a result, remote sensing imagery is shown as lowcontrast, blurred, and dark from time to time. Here, we introduce a new method integrating image local statistics and image natural characteristics to enhance remote sensing imagery. This method computes the adaptive histogram equalization to each distinct region of the input image and then redistributes the lightness values of the image. The natural characteristic of image is applied to adjust the restoration contrast. The experiments on real data show the effectiveness of the algorithm.
Schaepman-Strub, G.; Schaepman, M.E.; Painter, T.H.; Dangel, S.; Martonchik, J.
The remote sensing community puts major efforts into calibration and validation of sensors, measurements, and derived products to quantify and reduce uncertainties. Given recent advances in instrument design, radiometric calibration, atmospheric correction, algorithm development, product
Gerstl, S.A.W.; Borel, C.C.
In this paper we describe the progress made in the last three years on developing the radiosity method for remote sensing applications. The research covered canopy modeling, volumetric scattering and atmospheric corrections for future analysis of EOS imaging spectrometer data.
Singh, R.P.; Kumar, V.; Srivastav, S.K.
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
National Aeronautics and Space Administration — The proposed innovation is Spark-RS, an open source software project that enables GPU-accelerated remote sensing workflows in an Apache Spark distributed computing...
Increasingly, optical datasets from estuarine and coastal systems are becoming available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data ...
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.
Kunte, P.D.; Wagle, B.G.
Satellite remote sensing data pertaining to two areas, one each on east and west coasts of India has been utilized to study suspended sediment dynamics within the near-shore region. For this purpose, thematic mapper image and second principal...
Kunte, P.D.; Wagle, B.G.
Remote sensing data has been used for mapping coastal vegetation along the Goa Coast, India. The study envisages the use of digital image processing techniques for delineating geomorphic features and associated vegetation, including mangrove, along...
DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using. WEKA, open source ...
Blending the most fundamental Remote-Sensing principles (RS) with the most functional spatial knowledge (GIS) with the objective of the determination of the accident-prone palms and points (case study: Tehran-Hamadan Highway on Saveh Superhighway)
DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source ...
Strauss, Karl F.
This method enables sensing and quantization of analog strain gauges. By manufacturing a piezoelectric sensor stack in parallel (physical) with a piezoelectric actuator stack, the capacitance of the sensor stack varies in exact proportion to the exertion applied by the actuator stack. This, in turn, varies the output frequency of the local sensor oscillator. The output, F(sub out), is fed to a phase detector, which is driven by a stable reference, F(sub ref). The output of the phase detector is a square waveform, D(sub out), whose duty cycle, t(sub W), varies in exact proportion according to whether F(sub out) is higher or lower than F(sub ref). In this design, should F(sub out) be precisely equal to F(sub ref), then the waveform has an exact 50/50 duty cycle. The waveform, D(sub out), is of generally very low frequency suitable for safe transmission over long distances without corruption. The active portion of the waveform, t(sub W), gates a remotely located counter, which is driven by a stable oscillator (source) of such frequency as to give sufficient digitization of t(sub W) to the resolution required by the application. The advantage to this scheme is that it negates the most-common, present method of sending either very low level signals (viz. direct output from the sensors) across great distances (anything over one-half meter) or the need to transmit widely varying higher frequencies over significant distances thereby eliminating interference [both in terms of beat frequency generation and in-situ EMI (electromagnetic interference)] caused by ineffective shielding. It also results in a significant reduction in shielding mass.
Maynard, Nancy G.; Vicente, G. A.
In response to the need for improved observations of environmental factors to better understand the links between human health and the environment, NASA has established a new program to significantly improve the utilization of NASA's diverse array of data, information, and observations of the Earth for health applications. This initiative, lead by Goddard Space Flight Center (GSFC) has the following goals: (1) To encourage interdisciplinary research on the relationships between environmental parameters (e.g., rainfall, vegetation) and health, (2) Develop practical early warning systems, (3) Create a unique system for the exchange of Earth science and health data, (4) Provide an investigator field support system for customers and partners, (5) Facilitate a system for observation, identification, and surveillance of parameters relevant to environment and health issues. The NASA Environment and Health Program is conducting several interdisciplinary projects to examine applications of remote sensing data and information to a variety of health issues, including studies on malaria, Rift Valley Fever, St. Louis Encephalitis, Dengue Fever, Ebola, African Dust and health, meningitis, asthma, and filariasis. In addition, the NASA program is creating a user-friendly data system to help provide the public health community with easy and timely access to space-based environmental data for epidemiological studies. This NASA data system is being designed to bring land, atmosphere, water and ocean satellite data/products to users not familiar with satellite data/products, but who are knowledgeable in the Geographic Information Systems (GIS) environment. This paper discusses the most recent results of the interdisciplinary environment-health research projects and provides an analysis of the usefulness of the satellite data to epidemiological studies. In addition, there will be a summary of presently-available NASA Earth science data and a description of how it may be obtained.
Fylaktos, Asimakis; Yfantidou, Anastasia
Natural hazards like earthquakes can result to enormous property damage, and human casualties in mountainous areas. Italy has always been exposed to numerous earthquakes, mostly concentrated in central and southern regions. Last year, two seismic events near Norcia (central Italy) have occurred, which led to substantial loss of life and extensive damage to properties, infrastructure and cultural heritage. This research utilizes remote sensing products and GIS software, to provide a database of information. We used both SAR images of Sentinel 1A and optical imagery of Landsat 8 to examine the differences of topography with the aid of the multi temporal monitoring technique. This technique suits for the observation of any surface deformation. This database is a cluster of information regarding the consequences of the earthquakes in groups, such as property and infrastructure damage, regional rifts, cultivation loss, landslides and surface deformations amongst others, all mapped on GIS software. Relevant organizations can implement these data in order to calculate the financial impact of these types of earthquakes. In the future, we can enrich this database including more regions and enhance the variety of its applications. For instance, we could predict the future impacts of any type of earthquake in several areas, and design a preliminarily model of emergency for immediate evacuation and quick recovery response. It is important to know how the surface moves, in particular geographical regions like Italy, Cyprus and Greece, where earthquakes are so frequent. We are not able to predict earthquakes, but using data from this research, we may assess the damage that could be caused in the future.
Perry, Eileen M.; Rupp, Richard; Davenport, Joan; Leal, Juliano; Pierce, Francis J.; Schulthess, Urs
Fresh market fruit crops such as apples have not employed precision agriculture tools, partially due to the labor intensive nature of the cropping systems. In this paper we describe new research in the development of precision agriculture tools for tree fruit, including the ability to track spatially variable orchard data before harvest through to the packing plant. Remote sensing is a key component of this system, and remote sensing products are being evaluated for their usefulness in guiding orchard management.
Estes, J. E.; Sailer, C. T. (Principal Investigator); Tinney, L. R.
The current status of artificial intelligence AI technology is discussed along with imagery data management, database interrogation, and decision making. Techniques adapted from the field of artificial intelligence (AI) have significant, wide ranging impacts upon computer-assisted remote sensing analysis. AI based techniques offer a powerful and fundamentally different approach to many remote sensing tasks. In addition to computer assisted analysis, AI techniques can also aid onboard spacecraft data processing and analysis and database access and query.
Gonzalez, R. C, and R. E. Woods . 2002. Digital Image Processing . 2nd ed. Upper Saddle River, NJ: Prentice Hall. Grady, L. 2006. Random Walks for Image ...remotely sensed images that are in panchromatic or true-color formats. Image - processing techniques, in- cluding Hough transforms, machine learning, and...in the GIS analysis. This paper introduces image - processing techniques and tools that may help detect some of these features in remotely sensed
Gonzalez, R. C, and R. E. Woods . 2002. Digital Image Processing . 2nd ed. Upper Saddle River, NJ: Prentice Hall. Grady, L. 2006. Random Walks for Image ...remotely sensed images that are in panchromatic or true-color formats. Image - processing techniques, in- cluding Hough transforms, machine learning, and...in the GIS analysis. This paper introduces image - processing techniques and tools that may help detect some of these features in remotely sensed
Murtha, P. A.
The development, current status, and organization of the University of British Columbia's interdisciplinary graduate program in remote sensing are described. Specialized programs are tailored to meet student's needs and interest and can range from the theoretical development of technology (sensor development, modelling, and computer analysis) to specialized application of remote sensing in resource analysis such as the determination of vegetation damage, land classification, and land use. The courses and faculty members are listed.
van Brug, Hedser; Visser, Huib
This paper describes one of the issues that are facing the remote sensing community in the not so far future; scientists ask for certain requirement that cannot be fulfilled either due to cost issues or technological issues. The paper starts with giving a short and quick historical overview of the development of spectrometer based remote sensing systems. Next, the likely end of the spectrometers will be explained, followed by a possible alternative.
Rosenqvist, Ake; Imhoff, Marc; Milne, Anthony; Dobson, Craig
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
Swain, P. H.
An overview is given of the current state of automatic image pattern recognition as applied to remote sensing of the earth's resources. The framework for the discussion is provided by four important aspects of the remote sensing problem: scene information content, characterization of scene information, information extraction methods, and the net value of extractable information. Outstanding problems are surveyed, as are the prospects for future developments. The effect of increasingly complex data bases and the rapidly evolving digital computer technology are highlighted.
Serafin, R. J.; Szejwach, G.; Phillips, B. B.
This paper explores the potential for airborne remote sensing for atmospheric sciences research. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. Promising candidates include Doppler radar and lidar, infrared short range radiometry, and microwave radiometry.
Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong
Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major pa...
Johannsen, Chris J.
The primary agricultural objective of this research is to determine what soil and crop information can be verified from remotely sensed images during the growing season. Specifically: (1) Elements of crop stress due to drought, weeds, disease and nutrient deficiencies will be documented with ground truth over specific agricultural sites and (2) Use of remote sensing with GPS and GIS technology for providing a safe and environmentally friendly application of fertilizers and chemicals will be documented.
Soil Moisture Retrievals for Forecasting Rainfall-Runoff Partitioning ," Geophysical Research Letters, 32(18):L 18401 [doi: 10.1029/2005GL023543...Influences on the Remote Estimation of Evapotranspiration Using Multiple Satellite Sensors," Remote Sensing of Envi- ronment, 105(4):271-285. Milfred, C
Nielsen, Rasmus; Thorndahl, Søren Liedtke
This study contributes with extensive research of applying low-cost remotely sensed monitoring stations to an urban environment. Design requirements are scrutinized, including applications for remote data access, hardware design, and monitoring network design. A network of 9 monitoring stations m...
Roerink, G.J.; Wit, de A.J.W.; Pelgrum, H.; Mücher, C.A.
This report presents the results of the EU project "Carbon and water fluxes of Mediterranean forests and impacts of land use/cover changes". The objectives of the project can be summarized as follows: (I) surface energy balance mapping using remote sensing, (ii) carbon uptake mapping using remote
Full Text Available Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1 scale issue; (2 transportability issue; (3 data availability; and (4 uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.
Li, Zhaoqin; Xu, Dandan; Guo, Xulin
Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.
Jiang, Hongxu; Yang, Kai; Liu, Tingshan; Zhang, Yongfei
The measurement of visual quality is of fundamental importance to remote sensing image compression, especially for image quality assessment and compression algorithm optimization. We exploit the distortion features of optical remote sensing image compression and propose a full-reference image quality metric based on multilevel distortions (MLD), which assesses image quality by calculating distortions of three levels (such as pixel-level, contexture-level, and content-level) between original images and compressed images. Based on this, a multiscale MLD (MMLD) algorithm is designed and it outperforms the other current methods in our testing. In order to validate the performance of our algorithm, a special remote sensing image compression distortion (RICD) database is constructed, involving 250 remote sensing images compressed with different algorithms and various distortions. Experimental results on RICD and Laboratory for Image and Video Engineering databases show that the proposed MMLD algorithm has better consistency with subjective perception values than current state-of-the-art methods in remote sensing image compression assessment, and the objective assessment results can show the distortion features and visual quality of compressed image well. It is suitable to be the evaluation criteria for optical remote sensing image compression.
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.
Li, Zhaoqin; Xu, Dandan; Guo, Xulin
Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges. PMID:25386759
Stoyanov, D. V.; Dreischuh, T. N.
The lidars of picosecond resolution are an attractive tool for remote probing of some highly dynamic objects like sea subsurface waters, small-scale turbulences in the atmosphere, etc. The picosecond lasers are suitable illuminating sources, but the main restrictions are due to the lack of proper receiving methods, combining the both high temporal and amplitude resolution, good sensitivity, short integration time, and wide dynamic range. The methods for short pulse measurements are not suitable for picosecond lidars, operating at low level, with highly dynamic signals. The streak-cameras are of high cost, lower sensitivity, and lower dynamic range (approximately 10(exp 3)). Because of the background, the single quantum regime in photomultipliers (PMT) is ineffective. The sampling of highly dynamic optical signals with resolution less than or equal to 1ns is a serious problem, limiting the application of the high speed PMT-MCP (microchannel plate) in the picosecond lidar systems. The goal of this work is to describe the use of a new photodetection technique which combines the picosecond resolution with the high amplitude resolution, dynamic range, and sensitivity.
Lobitz, Brad; Johnson, Lee; Hlavka, Chris; Armstrong, Roy; Bell, Cindy
High spatial resolution airborne imagery was acquired in California's Napa Valley in 1993 and 1994 as part of the Grapevine Remote sensing Analysis of Phylloxera Early Stress (GRAPES) project. Investigators from NASA, the University of California, the California State University, and Robert Mondavi Winery examined the application of airborne digital imaging technology to vineyard management, with emphasis on detecting the phylloxera infestation in California vineyards. Because the root louse causes vine stress that leads to grapevine death in three to five years, the infested areas must be replanted with resistant rootstock. Early detection of infestation and changing cultural practices can compensate for vine damage. Vineyard managers need improved information to decide where and when to replant fields or sections of fields to minimize crop financial losses. Annual relative changes in leaf area due to phylloxera infestation were determined by using information obtained from computing Normalized Difference Vegetation Index (NDVI) images. Two other methods of monitoring vineyards through imagery were also investigated: optical sensing of the Red Edge Inflection Point (REIP), and thermal sensing. These did not convey the stress patterns as well as the NDVI imagery and require specialized sensor configurations. NDVI-derived products are recommended for monitoring phylloxera infestations.
Doyle, S. E.
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.
Colomina, Ismael; Molina, Pere
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...
Academy of Natural Sciences, Philadelphia, PA.
This publication identifies some of the general concepts of remote sensing and explains the image collection process and computer-generated reconstruction of the data. Monitoring the ecological collapse in coral reefs, weather phenomena like El Nino/La Nina, and U.S. Space Shuttle-based sensing projects are some of the areas for which remote…
I was asked if I could help a local elementary school to set up and operate a weather satellite receiving station. Since I am myself studying Space Engineering at the Luleå University of Technology, I accepted the task. With two fellow students I set out to investigate the receiving station. To be honest, we did not know much about satellite receiving systems ourselves, since we had only taken general engineering classes so far, but stimulated by our interest in the subject and the challenge to solve a task different from ordinary assignments, we quickly learned how to set up the equipment. After a while we could receive quite decent pictures from the NOAA polar orbiting weather satellites. The pupils, focusing on grades 5-6, did not have much previous knowledge in physics and technology, and - quite naturally - did not know much about space and satellites. At their age it is probably difficult to understand the services satellites provide us with high up in the sky, watching the earth and the weather. On the other hand, this was part of the challenge we accepted. It was intriguing to observe how the pupils adapted to the situation, initially perhaps uneasy with it, but then enthusiastic about learning how to operate the equipment. They could see what happened if they did something differently. They could compare the actual weather outside the window and the weather images on the screen in front of them. The efforts invested in understanding the system were rewarded by the results achieved. The pupils will be able to use this system in many areas in their education. As it turned out, it was easy to operate when it was once properly set up. Through this system, the students are exposed to ,,hands-on'' education and experience with meteorology, remote sensing, geography and many other areas and applications. It is our hope that we may contribute to make these young pupils aware of the vast knowledge available to them through their efforts at school, to make them
Haque, Saad Ul
The two main global issues related to water are its declining quality and quantity. Population growth, industrialization, increase in agriculture land and urbanization are the main causes upon which the inland water bodies are confronted with the increasing water demand. The quality of surface water has also been degraded in many countries over the past few decades due to the inputs of nutrients and sediments especially in the lakes and reservoirs. Since water is essential for not only meeting the human needs but also to maintain natural ecosystem health and integrity, there are efforts worldwide to assess and restore quality of surface waters. Remote sensing techniques provide a tool for continuous water quality information in order to identify and minimize sources of pollutants that are harmful for human and aquatic life. The proposed methodology is focused on assessing quality of water at selected lakes in Pakistan (Sindh); namely, HUBDAM, KEENJHAR LAKE, HALEEJI and HADEERO. These lakes are drinking water sources for several major cities of Pakistan including Karachi. Satellite imagery of Landsat 7 (ETM+) is used to identify the variation in water quality of these lakes in terms of their optical properties. All bands of Landsat 7 (ETM+) image are analyzed to select only those that may be correlated with some water quality parameters (e.g. suspended solids, chlorophyll a). The Optimum Index Factor (OIF) developed by Chavez et al. (1982) is used for selection of the optimum combination of bands. The OIF is calculated by dividing the sum of standard deviations of any three bands with the sum of their respective correlation coefficients (absolute values). It is assumed that the band with the higher standard deviation contains the higher amount of 'information' than other bands. Therefore, OIF values are ranked and three bands with the highest OIF are selected for the visual interpretation. A color composite image is created using these three bands. The water quality
Full Text Available Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC. The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation. Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs.
Garvin, J. B.; Schnetzler, C.; Grieve, R. A. F.
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. In addition, refinement of initial dimensions of extremely recent structures such as Zhamanshin and Bosumtwi is an important objective in order to permit re-evaluation of global Earth system responses associated with these types of events.
Garvin, J.B.; Schnetzler, C.; Grieve, R.A.F.
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
Sun, J.; Xiang, H.
Problems exist in remote sensing dynamic monitoring of mining are expounded, general idea of building remote sensing dynamic monitoring information system is presented, and timely release of service-oriented remote sensing monitoring results is established. Mobile device-based data verification subsystem is developed using mobile GIS, remote sensing dynamic monitoring information system of mining is constructed, and "timely release, fast handling and timely feedback" rapid response mechanism of remote sensing dynamic monitoring is implemented.
Günther, K.P.; Dahn, H.G.; Lüdeker, W.
In November 1989 the EUREKA project LASFLEUR (EU 380) started as an European research effort to investigate the future application of far-field laser-induced plant fluorescence for synoptic, airborne environmental monitoring of vegetation. This report includes a brief introduction in a theoretically approach for the laser-induced fluorescence signals of leaves and their spectral and radiometric behaviour. In addition, a detailed description of the design and realization of the second generation of the far-field fluorescence lidar (DLidaR-2) is given with special regard to the optical and electronical setup, followed by a short explanation of the data processing. The main objectives of the far field measurements are to demonstrate the link between laser-induced fluorescence data and plant physiology and to show the reliability of remote single shot lidar measurements. The data sets include the typical daily cycles of the fluorescence for different global irradiation. As expected from biophysical models, the remotely sensed chlorophyll fluorescence is highly correlated with the carbon fixation rate, while the fluorescence ratio F685 / F730 is only dependent on the chlorophyll concentration. Drought stress measurement of evergreen oaks Quercus pubescens confirm the findings of healthy plants with regard to the fluorescence ratio F685 / F730 while the fluorescence signals of stressed plants show a different behavior than nonstressed plants. Additionally, the corresponding physiological data (porometer and PAM data) are presented. (author)
Innes, J.L.; Koch, B.
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)
Daniel A. Griffith
Full Text Available Virtually all remotely sensed data contain spatial autocorrelation, which impacts upon their statistical features of uncertainty through variance inflation, and the compounding of duplicate information. Estimating the nature and degree of this spatial autocorrelation, which is usually positive and very strong, has been hindered by computational intensity associated with the massive number of pixels in realistically-sized remotely-sensed images, a situation that more recently has changed. Recent advances in spatial statistical estimation theory support the extraction of information and the distilling of knowledge from remotely-sensed images in a way that accounts for latent spatial autocorrelation. This paper summarizes an effective methodological approach to achieve this end, illustrating results with a 2002 remotely sensed-image of the Florida Everglades, and simulation experiments. Specifically, uncertainty of spatial autocorrelation parameter in a spatial autoregressive model is modeled with a beta-beta mixture approach and is further investigated with three different sampling strategies: coterminous sampling, random sub-region sampling, and increasing domain sub-regions. The results suggest that uncertainty associated with remotely-sensed data should be cast in consideration of spatial autocorrelation. It emphasizes that one remaining challenge is to better quantify the spatial variability of spatial autocorrelation estimates across geographic landscapes.
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.
Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton
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
Griffith, J.A.; Egbert, S.L.
Remote sensing education is increasingly in demand across academic and professional disciplines. Meanwhile, Internet technology and the World Wide Web (WWW) are being more frequently employed as teaching tools in remote sensing and other disciplines. The current wealth of information on the Internet and World Wide Web must be distilled, nonetheless, to be useful in remote sensing education. An extensive literature base is developing on the WWW as a tool in education and in teaching remote sensing. This literature reveals benefits and limitations of the WWW, and can guide its implementation. Among the most beneficial aspects of the Web are increased access to remote sensing expertise regardless of geographic location, increased access to current material, and access to extensive archives of satellite imagery and aerial photography. As with other teaching innovations, using the WWW/Internet may well mean more work, not less, for teachers, at least at the stage of early adoption. Also, information posted on Web sites is not always accurate. Development stages of this technology range from on-line posting of syllabi and lecture notes to on-line laboratory exercises and animated landscape flyovers and on-line image processing. The advantages of WWW/Internet technology may likely outweigh the costs of implementing it as a teaching tool.
Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton
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.
Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling
In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.
Prasad S. Thenkabail
Full Text Available Remote Sensing, an open access journal (http://www.mdpi.com/journal/remotesensing has grown at rapid pace since its first publication five years ago, and has acquired a strong reputation. It is a “pathfinder” being the first open access journal in remote sensing. For those academics who were used to waiting a year or two for their peer-reviewed scientific work to be reviewed, revised, edited, and published, Remote Sensing offers a publication time frame that is unheard of (in most cases, less than four months. However, we do this after multiple peer-reviews, multiple revisions, much editorial scrutiny and decision-making, and professional editing by an editorial office before a paper is published online in our tight time frame, bringing a paradigm shift in scientific publication. As a result, there has been a swift increase in submissions of higher and higher quality manuscripts from the best authors and institutes working on Remote Sensing, Geographic Information Systems (GIS, Global Navigation Satellite System (GNSS, GIScience, and all related geospatial science and technologies from around the world. The purpose of this editorial is to update everyone interested in Remote Sensing on the progress made over the last year, and provide an outline of our vision for the immediate future. [...
Dercas, Nicholas; Dalezios, Nicolas
Drought is a multi-faceted issue and requires a multi-faceted assessment. Droughts may have the origin on precipitation deficits, which sequentially and by considering different time and space scales may impact soil moisture, plant wilting, stream flow, wildfire, ground water levels, famine and social impacts. There is a need to monitor drought even at a global scale. Key variables for monitoring drought include climate data, soil moisture, stream flow, ground water, reservoir and lake levels, snow pack, short-medium-long range forecasts, vegetation health and fire danger. However, there is no single definition of drought and there are different drought indicators and indices even for each drought type. There are already four operational global drought risk monitoring systems, namely the U.S. Drought Monitor, the European Drought Observatory (EDO), the African and the Australian systems, respectively. These systems require further research to improve the level of accuracy, the time and space scales, to consider all types of drought and to achieve operational efficiency, eventually. This paper attempts to contribute to the above mentioned objectives. Based on a similar general methodology, the multi-indicator approach is considered. This has resulted from previous research in the Mediterranean region, an agriculturally vulnerable region, using several drought indices separately, namely RDI and VHI. The proposed scheme attempts to consider different space scaling based on agroclimatic zoning through remotely sensed techniques and several indices. Needless to say, the agroclimatic potential of agricultural areas has to be assessed in order to achieve sustainable and efficient use of natural resources in combination with production maximization. Similarly, the time scale is also considered by addressing drought-related impacts affected by precipitation deficits on time scales ranging from a few days to a few months, such as non-irrigated agriculture, topsoil moisture
Full Text Available Global maps of total-column carbon dioxide (CO2 mole fraction (in units of parts per million are important tools for climate research since they provide insights into the spatial distribution of carbon intake and emissions as well as their seasonal and annual evolutions. Currently, two main remote sensing instruments for total-column CO2 are the Orbiting Carbon Observatory-2 (OCO-2 and the Greenhouse gases Observing SATellite (GOSAT, both of which produce estimates of CO2 concentration, called profiles, at 20 different pressure levels. Operationally, each profile estimate is then convolved into a single estimate of column-averaged CO2 using a linear pressure weighting function. This total-column CO2 is then used for subsequent analyses such as Level 3 map generation and colocation for validation. In principle, total-column CO2 in these applications may be more efficiently estimated by making optimal estimates of the vector-valued CO2 profiles and applying the pressure weighting function afterwards. These estimates will be more efficient if there is multivariate dependence between CO2 values in the profile. In this article, we describe a methodology that uses a modified Spatial Random Effects model to account for the multivariate nature of the data fusion of OCO-2 and GOSAT. We show that multivariate fusion of the profiles has improved mean squared error relative to scalar fusion of the column-averaged CO2 values from OCO-2 and GOSAT. The computations scale linearly with the number of data points, making it suitable for the typically massive remote sensing datasets. Furthermore, the methodology properly accounts for differences in instrument footprint, measurement-error characteristics, and data coverages.
Bhattarai, Nishan; Shaw, Stephen B.; Quackenbush, Lindi J.; Im, Jungho; Niraula, Rewati
In the last two decades, a number of single-source surface energy balance (SEB) models have been proposed for mapping evapotranspiration (ET); however, there is no clear guidance on which models are preferable under different conditions. In this paper, we tested five models-Surface Energy Balance Algorithm for Land (SEBAL), Mapping ET at high Resolution with Internalized Calibration (METRIC), Simplified Surface Energy Balance Index (S-SEBI), Surface Energy Balance System (SEBS), and operational Simplified Surface Energy Balance (SSEBop)-to identify the single-source SEB models most appropriate for use in the humid southeastern United States. ET predictions from these models were compared with measured ET at four sites (marsh, grass, and citrus surfaces) for 149 cloud-free Landsat image acquisition days between 2000 and 2010. The overall model evaluation statistics showed that SEBS generally outperformed the other models in terms of estimating daily ET from different land covers (e.g., the root mean squared error (RMSE) was 0.74 mm day-1). SSEBop was consistently the worst performing model and overestimated ET at all sites (RMSE = 1.67 mm day-1), while the other models typically fell in between SSEBop and SEBS. However, for short grass conditions, SEBAL, METRIC, and S-SEBI appear to work much better than SEBS. Overall, our study suggests that SEBS may be the best SEB model in humid regions, although it may require modifications to work better over short vegetation.
De Klerk, HM
Full Text Available Traditionally, to map environmental features using remote sensing, practitioners will use training data to develop models on various satellite data sets using a number of classification approaches and use test data to select a single ‘best performer...
Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...
Dou, Aixia; Wang, Xiaoqing; Ding, Xiang; Du, Zecheng
On the basis of the study on the enhancement methods of remote sensing images obtained after several earthquakes, the paper designed a new and optimized image enhancement model which was implemented by combining different single methods. The patterns of elementary model units and combined types of model were defined. Based on the enhancement model database, the algorithm of combinatorial model was brought out via C++ programming. The combined model was tested by processing the aerial remote sensing images obtained after 1976 Tangshan earthquake. It was proved that the definition and implementation of combined enhancement model can efficiently improve the ability and flexibility of image enhancement algorithm.
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.
Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong
Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.
Zhang, Xiangrong; Pan, Xian; Hou, Biao; Jiao, Licheng
This paper presents a new method based on Semantic Structure Tree (SST) for remote sensing image segmentation, in which, the semantic image analysis is used to construct the SST of the image. The leaves of the SST represent the semantics of the image and serve as human semantic understanding of the image. The root of the tree is the whole image. The SST uses grammar rules to construct a hierarchy structure of the image and gives a complete high-level semantics contents description of the image. Experimental results show that the tree can give efficient description of the semantic content of the remote sensing image, and can be well used in remote sensing image segmentation.
Menk, Frederick W
Written by a researcher at the forefront of the field, this first comprehensive account of magnetoseismology conveys the physics behind these movements and waves, and explains how to detect and investigate them. Along the way, it describes the principles as applied to remote sensing of near-Earth space and related remote sensing techniques, while also comparing and intercalibrating magnetoseismology with other techniques. The example applications include advanced data analysis techniques that may find wider used in areas ranging from geophysics to medical imaging, and remote sensing using radar systems that are of relevance to defense surveillance systems. As a result, the book not only reviews the status quo, but also anticipates new developments. With many figures and illustrations, some in full color, plus additional computational codes for analysis and evaluation. Aimed at graduate readers, the text assumes knowledge of electromagnetism and physical processes at degree level, but introductory chapters wil...
Prados, Don; Mohamed, Mohamed A.; Johnson, Michael; Cao, Changyong; Gasser, Jerry
This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.
Space Infrastructure is a space system that provides communication, navigation and remote sensing service for broad users. China National Space Remote Sensing Infrastructure includes remote sensing satellites, ground system and related systems. According to the principle of multiple-function on one satellite, multiple satellites in one constellation and collaboration between constellations, series of land observation, ocean observation and atmosphere observation satellites have been suggested to have high, middle and low resolution and fly on different orbits and with different means of payloads to achieve a high ability for global synthetically observation. With such an infrastructure, we can carry out the research on climate change, geophysics global surveying and mapping, water resources management, safety and emergency management, and so on. I This paper gives a detailed introduction about the planning of this infrastructure and its application in different area, especially the international cooperation potential in the so called One Belt and One Road space information corridor.
Sarah A. Lewis; Peter R. Robichaud; William J. Elliot; Bruce E. Frazier; Joan Q. Wu
Forest fires may induce changes in soil organic properties that often lead to water repellent conditions within the soil profile that decrease soil infiltration capacity. The remote detection of water repellent soils after forest fires would lead to quicker and more accurate assessment of erosion potential. An airborne hyperspectral image was acquired over the Hayman...
Markowicz, K. M.; Ritter, C.; Lisok, J.; Makuch, P.; Stachlewska, I. S.; Cappelletti, D.; Mazzola, M.; Chilinski, M. T.
This work presents a methodology for obtaining vertical profiles of aerosol single scattering properties based on a combination of different measurement techniques. The presented data were obtained under the iAREA (Impact of absorbing aerosols on radiative forcing in the European Arctic) campaigns conducted in Ny-Ålesund (Spitsbergen) during the spring seasons of 2015-2017. The retrieval uses in-situ observations of black carbon concentration and absorption coefficient measured by a micro-aethalometer AE-51 mounted onboard a tethered balloon, as well as remote sensing data obtained from sun photometer and lidar measurements. From a combination of the balloon-borne in-situ and the lidar data, we derived profiles of single scattering albedo (SSA) as well as absorption, extinction, and aerosol number concentration. Results have been obtained in an altitude range from about 400 m up to 1600 m a.s.l. and for cases with increased aerosol load during the Arctic haze seasons of 2015 and 2016. The main results consist of the observation of increasing values of equivalent black carbon (EBC) and absorption coefficient with altitude, and the opposite trend for aerosol concentration for particles larger than 0.3 μm. SSA was retrieved with the use of lidar Raman and Klett algorithms for both 532 and 880 nm wavelengths. In most profiles, SSA shows relatively high temporal and altitude variability. Vertical variability of SSA computed from both methods is consistent; however, some discrepancy is related to Raman retrieval uncertainty and absorption coefficient estimation from AE-51. Typically, very low EBC concentration in Ny-Ålesund leads to large error in the absorbing coefficient. However, SSA uncertainty for both Raman and Klett algorithms seems to be reasonable, e.g. SSA of 0.98 and 0.95 relate to an error of ±0.01 and ± 0.025, respectively.
Full Text Available Airplane detection in remote sensing images remains a challenging problem due to the complexity of backgrounds. In recent years, with the development of deep learning, object detection has also obtained great breakthroughs. For object detection tasks in natural images, such as the PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning VOC (Visual Object Classes Challenge, the major trend of current development is to use a large amount of labeled classification data to pre-train the deep neural network as a base network, and then use a small amount of annotated detection data to fine-tune the network for detection. In this paper, we use object detection technology based on deep learning for airplane detection in remote sensing images. In addition to using some characteristics of remote sensing images, some new data augmentation techniques have been proposed. We also use transfer learning and adopt a single deep convolutional neural network and limited training samples to implement end-to-end trainable airplane detection. Classification and positioning are no longer divided into multistage tasks; end-to-end detection attempts to combine them for optimization, which ensures an optimal solution for the final stage. In our experiment, we use remote sensing images of airports collected from Google Earth. The experimental results show that the proposed algorithm is highly accurate and meaningful for remote sensing object detection.
Gurnett, Donald A.
A coordinated Cluster/Regatta mission provides unique opportunities for remote sensing studies of terrestrial radio emissions. The scientific questions that can be addressed by remote radio measurements from Cluster and Regatta are described and the technical issues involved are discussed. The radio emission of primary interest is Auroral Kilometric Radiation (AKR) which is a powerful radio emission generated over the Earth's auroral zones at frequencies from 100 to 500 kHz.
Steven G. Ackleson
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.
Elsheikha, Diael-Deen Mohamed
Remote sensing is being used in agriculture for crop management. Ground based remote sensing data acquisition system was used for collection of high spatial and temporal resolution data for irrigated broccoli crop. The system was composed of a small cart that ran back and forth on a rail system that was mounted on a linear move irrigation system. The cart was equipped with a sensor that had 4 discrete wavelengths; 550 nm, 660 nm, 720 nm, and 810 nm, and an infrared thermometer, all had 10 nm bandwidth. A global positioning system was used to indicate the cart position. The study consisted of two parts; the first was to evaluate remotely sensed reflectance and indices in broccoli during the growing season, and determine whether remotely sensed indices or standard deviation of indices can distinguish between nitrogen and water stress in broccoli, and the second part of the study was to evaluate remotely sensed indices and standard deviation of remotely sensed indices in broccoli during daily changes in solar zenith angle. Results indicated that nitrogen was detected using Ratio Vegetation index, RVI, Normalized Difference Vegetation Index, NDVI, Canopy Chlorophyll Concentration Index, CCCI, and also using the reflectance in the Near-Infrared, NIR, bands. The Red reflectance band capability of showing stress was not as clear as the previous indices and bands reflectance. The Canopy Chlorophyll Concentration Index, CCCI, was the most successful index. The Crop Water Stress Index was able to detect water stress but it was highly affected by the solar zenith angle change along the day.
Slonecker, E. Terrence; Fisher, Gary B.; Marr, David A.; Milheim, Lesley E.; Roig-Silva, Coral M.
"Remote sensing” is a general 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 U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.
Schowengerdt, Robert A
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
Wen Jianguang; Xiao Qing; Xu Huiping
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)
Microwave and millimeter-wave remote sensing techniques are fast becoming a necessity in many aspects of security as detection and classification of objects or intruders becomes more difficult. This groundbreaking resource offers you expert guidance in this burgeoning area. It provides you with a thorough treatment of the principles of microwave and millimeter-wave remote sensing for security applications, as well as practical coverage of the design of radiometer, radar, and imaging systems. You learn how to design active and passive sensors for intruder detection, concealed object detection,
Lowry, James D., Jr.
This project focuses on the adaptation of human populations to their environments from prehistoric times to the present. It emphasizes interdisciplinary research to develop ecological baselines through the use of remotely sensed imagery, in situ field work, and the modeling of human population dynamics. It utilizes cultural and biological data from dated archaeological sites to assess the subsistence and settlement patterns of human societies in response to changing climatic and environmental conditions. The utilization of remote sensing techniques in archaeology is relatively new, exciting, and opens many doors.
Full Text Available A new methodology for the generation of flood hazard maps is presented fusing remote sensing and volunteered geographical data. Water pixels are identified utilizing a machine learning classification of two Landsat remote sensing scenes, acquired before and during the flooding event as well as a digital elevation model paired with river gage data. A statistical model computes the probability of flooded areas as a function of the number of adjacent pixels classified as water. Volunteered data obtained through Google news, videos and photos are added to modify the contour regions. It is shown that even a small amount of volunteered ground data can dramatically improve results.
The subject of this volume is remote sensing for environmental monitoring and resource management. This session is divided in eight parts. First part is on general topics, methodology and meteorology. Second part is on geology, environment and land cover. Third part is on disaster monitoring. Fourth part is on operational status of remote sensing. Fifth part is on coastal zones and inland waters. Sixth and seventh parts are on forestry and agriculture. Eighth part is on instrumentation and systems. (A.B.). refs., figs., tabs
-15 m. The older dunes are marked by very dark tone. These dunes extend to about 1 to 2 kIn inland. Remote sensing data can be used as an effective tool for identitying coastal geomorphic features. Above data proves that the coastal geomorphological...-Type text/plain; charset=UTF-8 :;. RmOTE 5mBIN(; AND AERIAL PHOTOGRAPHY FOR COASTAL GIDMORPHOLOGY By B. G. Wagle National Institute of Oceanography Dona Paula, Goa -~o:;DOL,. • : " In this lecture I will discuss the use ofRemote~. Sensing data...
Molthan, Andrew; Bell, Jordan; Case, Jonathan; Cole, Tony; Elmer, Nicholas; McGrath, Kevin; Schultz, Lori; Zavodsky, Brad
NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.
Le Vine, D. M.; Johnson, J. T.; Piepmeier, J.
Passive microwave remote sensing of the Earth from space provides information essential for understanding the Earth's environment and its evolution. Parameters such as soil moisture, sea surface temperature and salinity, and profiles of atmospheric temperature and humidity are measured at frequencies determined by the physics (e.g. sensitivity to changes in desired parameters) and by the availability of suitable spectrum free from interference. Interference from manmade sources (radio frequency interference) is an impediment that in many cases limits the potential for accurate measurements from space. A review is presented here of the frequencies employed in passive microwave remote sensing of the Earth from space and the associated experience with RFI.
Campbell, W. J.
The application of remote sensors for obtaining geophysical information of the Arctic regions is discussed. Two significant requirements are to acquire sequential, synoptic imagery of the Arctic Ocean during all weather and seasons and to measure the strains in the sea ice canopy and the heterogeneous character of the air and water stresses acting on the canopy. The acquisition of geophysical data by side looking radar and microwave sensors in military aircraft is described.
Tofani, Veronica; Agostini, Andrea; Segoni, Samuele; Catani, Filippo; Casagli, Nicola
The existing remote sensing techniques and their actual application in Europe for landslide detection, mapping and monitoring have been investigated. Data and information necessary to evaluate the subjects have been collected through a questionnaire, designed using a Google form, which was disseminated among end-users and researchers involved in landslide. In total, 49 answers were collected, coming from 17 European countries and from different kinds of institutions (universities, research institutes, public institutes and private companies). The spatial distribution of the answers is consistent with the distribution of landslides in Europe, the significance of landslides impact on society and the estimated landslide susceptibility in the various countries. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data followed by aerial photos and meteorological sensors. Since subsampling the answers according to the different typology of institutions it is not noticeable a clear gap between research institutes and end users, it is possible to infer that in landslide remote sensing the research is advancing at the same pace as its day-to-day application. Apart from optical and radar imagery, other techniques are less widespread and some of them are not so well established, notwithstanding their performances are increasing at a fast rate as scientific and technological improvements are accomplished. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000 - 1:25000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. Concerning landslide monitoring, the results of the questionnaire stressed that the best
Curran, Robert J. (Editor); Smith, James A. (Editor); Watson, Ken (Editor)
The papers presented in this volume address the technical aspects of earth and atmospheric remote sensing. Topics discussed include spaceborne and ground-based applications of laser remote sensing, advanced applications of lasers in remote sensing, laser ranging applications, data analysis and systems for biospheric processes, measurements for biospheric processes, and remote sensing for geology and geophysics. Papers are presented on a space-qualified laser transmitter for lidar applications, solid state lasers for planetary exploration, automated band selection for multispectral meteorological applications, aerospace remote sensing of natural water organics, and remote sensing of volcanic ash hazards to aircraft.
Piti's Tepungan Bay and Tumon Bay, two of five marine preserves in Guam, have not been mapped to a level of detail sufficient to support proposed management strategies. This project addresses this gap by providing high resolution maps to promote sustainable, responsible use of the area while protecting natural resources. Dr. Chirayath, a research scientist at the NASA Ames Laboratory, developed a theoretical model and algorithm called 'Fluid Lensing'. Fluid lensing removes optical distortions caused by moving water, improving the clarity of the images taken of the corals below the surface. We will also be using MiDAR, a next-generation remote sensing instrument that provides real-time multispectral video using an array of LED emitters coupled with NASA's FluidCam Imaging System, which may assist Guam's coral reef response team in understanding the severity and magnitude of coral bleaching events. This project will produce a 3D orthorectified model of the shallow water coral reef ecosystems in Tumon Bay and Piti marine preserves. These 3D models may be printed, creating a tactile diorama and increasing understanding of coral reefs among various audiences, including key decision makers. More importantly, the final data products can enable accurate and quantitative health assessment capabilities for coral reef ecosystems.
Chávez, Jason Defibaugh y; Tullis, Jason
Coverage and frequency of remotely sensed forest structural information would benefit from single orbital platforms designed to collect sufficient data. We evaluated forest structural information content using single-date Hyperion hyperspectral imagery collected over full-canopy oak-hickory forests in the Ozark National Forest, Arkansas, USA. Hyperion spectral derivatives were used to develop machine learning regression tree rule sets for predicting forest neighborhood percentile heights gene...
This paper, presented in poster form addresses the use of radar remote sensing in coastal zone management. Current and future applications in The Netherlands are highlighted with an outlook to technology and models that are involved. Applications include monitoring of the environment, oil spills,
Remote sensing techniques and products have recently been developed for the estimation of water balance variables. The objective of this study was to test the reliability of LandSAF (Land Surface Analyses Satellite Applications Facility) evapotranspiration (ET) and SPOT-Vegetation Normalised Difference Water Index ...
van Vliet REC; van der Meulen A; Swart DPJ
Windlidar is een remote sensing techniek voor het bepalen van wind- velden. Het systeem is gebaseerd op het herkennen van aerosol struc- turen in de atmosfeer met behulp van correlatie technieken. Afmetingen en levensduur vormen de belangrijkste parameters in deze techniek. Het verticale
Full Text Available such as partial least squares (PLS) and ridge regression were used to predict grass biomass in the Kruger National Park and the surrounding areas. The results indicated that both the environmental and remote sensing indicators had potential to predict grass...
A spatial variable nitrogen (N) rate trial and remote sensing of cotton crop was conducted during 2003 at Paul Good Farms, Mississippi, USA. The N rate trial consisted of three, 8-row transects at the east and west side of the field that were selected to represent variable soil and elevation feature...
MATLAB is a programming language just like C, C++, and python. In this research, a computer program implemented in MATLAB is used to experiment the. Gaussian mixture model algorithm. Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test ...
These conventional multi-class classifiers/algorithms are usually written in programming languages such as C, C++, and python. The objective of this research is to experiment the use of a binary classifier/algorithm for multi-class remote sensing task, implemented in MATLAB. MATLAB is a programming language just like C ...
Kerekes, John Paul; Landgrebe, David A.
Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.
Gregory P. Asner
Full Text Available Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions.
Starting in 2000, experiments have been conducted at the Jornada Experimental Range near Las Cruces, NM to evaluate the utility of Unmanned Aerial Vehicles (UAVs) for applications on arid rangelands. When compared to all types of remote sensing research ongoing at Jornada and other locations, UAVs h...
Yu, Anthony W.
There are currently three operational lidar systems orbiting the Earth, the Moon and the planet Mercury gathering scientific data and images to form a better understanding of our Earth and solar system. In this paper we will present an overview of the spacebome laser programs and offer insights into future spacebome lasers for remote sensing applications.
and soil erosion which is very critical especially in. Southern Tunisia. This necessitates mapping of wind erosion and sand encroachment evolution to help decision makers to undertake better management plans against desertification and to adapt sustainable land use policies. Remote sensing and GIS technologies are ...
Hu, Youjian; Zhang, Xiaohua
Image fusion plays an important role in improving high resolution remote sensing images, as many Earth observation satellites provide both high-resolution panchromatic and multispectral images. To date, many image fusion techniques have been developed. Existing traditional image fusion techniques such as the intensity-hue-saturation (IHS) transform, wavelet transform and principal components analysis(PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as IKONOS and Quick Bird. However, the available algorithms can hardly meet a satisfactory fusion requirement for high resolution remote sensing images. Among the existing fusion algorithms, the IHS technique is the most widely used one technique. But the color distortion of this technique is often obvious, especially when high resolution multispectral images are fused with its panchromatic images. This study presents a new fusion approach that integrates both IHS and histogram match techniques to reduce the color distortion of high resolution remote sensing fusion results. Different high resolution remote sensing images have been fused with this new approach. The result proves that the concept of the proposed improved IHS is promising, and it does significantly improve the fusion quality compared to conventional IHS transform fusion techniques.
Water erosion creates negative impacts on agricultural production, infrastructure, and water quality across the world. Regional-scale water erosion assessment is important, but limited by data availability and quality. Satellite remote sensing can contribute through providing spatial data to such
Myers, V. I.
The role of research in the educational setting is discussed. Curriculum developments for integrating teaching and research are described. Remote sensing technology is used as an example of bridging the gap between research and application. Recommendations are presented for strengthing research groups.
Foster, K. E.; Mackey, P. F.; Bonham, C. D.
Remote sensing techniques were applied to the lower Pantano Wash area to acquire data for planning an ecological balance between the expanding Tucson metropolitan area and its environment. The types and distribution of vegetation are discussed along with the hydrologic aspects of the Wash.
Colomina, I.; Molina, P.
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.
This thesis describes an investigation into the applications of radar remote sensing in forestry. During a four-year period (1982-1985), an extensive set of radar data was acquired at four test sites with forest plantations in The Netherlands: the Roggebotzand and Horsterwold sites at
Landsat Remote Sensing Data as an Alternative Approach for Geological Mapping in Tanzania: A Case Study in the Rungwe Volcanic Province, ... Tanzania Journal of Science ... The use of Landsat data in this area has revealed the need of effective use of these data in geological mapping programs in Tanzania. Landsat ...
The effects of climate change are severe in developing countries like Ethiopia where agriculture is the dominant economy. The Remote Sensing and GIS based analysis of climate change impact is crucial to help Ethiopia benefit the most from the technology. This study aims at assessing changes and variations in climatic ...
In this study, Gangotri glacier was monitored using Indian Remote Sensing (IRS) LISS-III sensor data in combination with field collected snow-meteorological data for a period of seven years (2001–2008). An overall decreasing trend in the areal extent of seasonal snow cover area (SCA) was observed. An upward shifting ...
Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen
This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature. PMID:24464232
Full Text Available This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature.
Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen
This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature.
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
the spatial and temporal coverage required for global change studies, particularly monitoring of atmospheric aerosols. Remote sensing of aerosols from satellites over the land and ocean is essen- tial to obtain the global aerosol budget to estimate the contributions of anthropogenic emissions to the aerosol budget and to ...
Spatial Analysis of Political Capital Citation Using Remote Sensing and GIS; A Case Study of Lokoja. ... The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader). If you would like more information about how to print, save, ...
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
The available measurements are, in fact, insuffi- cient to satisfy the increasing needs by the scientific community, of estimations of atmospheric aerosol content and type on global basis. Surface-based. Keywords. Land aerosols; spectral signatures; remote sensing; IRS-P3 MOS data. Proc. Indian Acad. Sci. (Earth Planet.
“How can remote sensing address information needs and gaps in water quality and quantity management?” was a workshop convened during the biennial National Water Quality Monitoring Conference 2014, held in Cincinnati, OH. The focus of this workshop was to provide an o...
Lin, Daoyu; Fu, Kun; Wang, Yang; Xu, Guangluan; Sun, Xian
With the development of deep learning, supervised learning has frequently been adopted to classify remotely sensed images using convolutional networks (CNNs). However, due to the limited amount of labeled data available, supervised learning is often difficult to carry out. Therefore, we proposed an unsupervised model called multiple-layer feature-matching generative adversarial networks (MARTA GANs) to learn a representation using only unlabeled data. MARTA GANs consists of both a generative model $G$ and a discriminative model $D$. We treat $D$ as a feature extractor. To fit the complex properties of remote sensing data, we use a fusion layer to merge the mid-level and global features. $G$ can produce numerous images that are similar to the training data; therefore, $D$ can learn better representations of remotely sensed images using the training data provided by $G$. The classification results on two widely used remote sensing image databases show that the proposed method significantly improves the classification performance compared with other state-of-the-art methods.
(GIS) have been observed to have potential scientific value for the study of population-environment interaction. This paper provides an account of how. Remote Sensing, GIS, census (mainly population and agricultural) and socioeconomic ..... Caldwell, J. C., 1965, 'Extended Family Obligations and Education: A study of an.
4, No. 2, June 2015. 174. Remote sensing and geochemistry techniques for the assessment of coal mining pollution, Emalahleni (Witbank), Mpumalanga. ... Department of Environmental Affairs declared this air pollution hotspot as Highveld Priority ..... metal pollution in the urban stream sediments and its tributaries.
... this study suggested that the more the input data and the adopted techniques, the higher and more reliable are the resultant lineaments. Moreover, SPOT DEM proved to be the most efficient among the input optical datasets. Keywords: Remote Sensing, Lineaments, Hydrogeology, Image Processing, Edge Enhancement ...
Dulk, den J.A.
This thesis describes research done to ascertain the possibilities and limitations of the use of remote sensing observations for agriculture. The topic is defined in Chapter 1. In Chapter 2 the possible applicability of certain existing models for this study is examined. Three models are
This chapter provides an overview of methods used for the extraction of biophysical vegetation variables from remote sensing imagery. It starts with the description of the main spectral regions in the optical window of the electromagnetic spectrum based on typical spectral signatures of land
Sathe, P.V.; Saran, A.K.
of surface reflected light in the context of using it for remote sensing of sea state. We propose the design for an instrument that will view the wind-roughened sea surface over a period of time and compute the fraction of plane polarised light received by it...
Multispectral imagery has been used as the data source for water and land observational remote sensing from airborne and satellite systems since the early 1960s. Over the past two decades, advances in sensor technology have made it possible for the collection of several hundred spectral bands. This is commonly ...
This review provides an overview of the use of remote sensing data, the development of spectral reflectance indices for detecting plant water stress, and the usefulness of field measurements for ground-truthing purposes. Reliable measurements of plant water stress over large areas are often required for management ...
Van Wambeke, L.; Sanderson, D.J.; Dolan, J.M.
The First European Workshop on 'Remote sensing in mineral exploration' organized by the Commission of the European Communities in February 1985 took stock of the results obtained within the European Community on the application of remote sensing techniques in exploration. The papers presented in this publication are essentially based on data obtained with the first generation of satellites and some airborne experiments. Important progress in data processing and interpretation has been made in the EEC since 1979 and is continuing to be made. The main aim is to provide the EC mining industry with a new tool for exploration. Significant results have already been obtained with the EEC playing an important role in the promotion of this relatively new technique. The main R and D trend is towards an integration of multidata sets (remote sensing, geochemical, geophysical and other data) to improve the methodology for delineating new targets in exploration. Another general trend is the participation of mining companies in remote sensing experiments. Further improvement for exploration is expected in the near future with the thematic mapper and the spot imageries as well as new airborne sensors
Wessels, Konrad J
Full Text Available This study used remotely-sensed phenology data derived from Advanced Very High Resolution Radiometer (AVHRR), in a fully supervised decision-tree classification based on the new biome map of South Africa. The objectives were: (i) to investigate...
Alistair M. S. Smith; Crystal A. Kolden; Wade T. Tinkham; Alan F. Talhelm; John D. Marshall; Andrew T. Hudak; Luigi Boschetti; Michael J. Falkowski; Jonathan A. Greenberg; John W. Anderson; Andrew Kliskey; Lilian Alessa; Robert F. Keefe; James R. Gosz
Climate change is altering the species composition, structure, and function of vegetation in natural terrestrial ecosystems. These changes can also impact the essential ecosystem goods and services derived from these ecosystems. Following disturbances, remote-sensing datasets have been used to monitor the disturbance and describe antecedent conditions as a means of...
Mapping of Landscape Cover Using Remote Sensing and GIS in Chandoli. National Park, India. Ekwal Imam. Department of Biology, College of Natural and Computational Sciences, P.O. Box 3044,. Mekelle University, Mekelle, Tigray, Ethiopia (firstname.lastname@example.org). ABSTRACT. Humankind to fulfill its needs has put ...
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 ...
Remote sensing-based fire frequency mapping in a savannah rangeland. Samuel Kusangaya1 and Vhusomuzi .B. Sithole2. 1Centre for Water Resources Research, University of KwaZulu Natal, Scottsville,. Pietermaritzburg 3209, South Africa. Email: email@example.com. 2Department of Geosciences, Nelson Mandela ...
Abstract. Gullies are large and deep erosion depressions or channels normally occurring in drainage ways. They are spectrally heterogeneous, making them difficult to map using pixel based classification technique. The advancement of remote sensing in terms of Geographic Object Based Image Analysis. (GEOBIA) ...
This study aimed at exploring different remote sensing (RS) techniques for quantitatively measuring vegetation and bare soil fractions in dune ecosystems along the Kenyan coast. The accurate measurements of field samples are required by Kenya Wildlife for environmental monitoring. The current methodology for ...
No. 3, November 2016. 285. Remote sensing object-oriented approaches coupled with ecological informatics to map invasive plant species. Sanjay Gairolaa*, Şerban Procheşa, Michael Gebreslasiea, and Duccio Rocchinib. aSchool of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Westville.
Abstract. The usefulness of remote sensing to discriminate Seriphium plumosum from grass using a field spectrometer data was investigated in this study. Analysis focused on wavelength regions that showed potential of discriminating S. plumosum from grass which were determined from global pair spectral comparison ...
The usefulness of remote sensing to discriminate Seriphium plumosum from grass using a field spectrometer data was investigated in this study. Analysis focused on wavelength regions that showed potential of discriminating S. plumosum from grass which were determined from global pair spectral comparison between S.
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.
LANDSAT REMOTE SENSING DATA AS AN ALTERNATIVE APPROACH. FOR GEOLOGICAL MAPPING IN TANZANIA: A CASE STUDY IN THE. RUNGWE VOLCANIC PROVINCE, SOUTH-WESTERN TANZANIA. EE Mshiu. Geology Department, University of Dar es Salaam,. P. O. Box 35052, Dar es Salaam.
Key words: remote sensing, geographic information system (GIS), aerial photographs, shoreline change. Data from aerial photographs taken in 1981, 1992 and 2002 of the Kunduchi shoreline off the Dar es Salaam coast were integrated in a geographic information system (GIS) to determine shoreline change in that locality.
The susceptibility of slopes in open pit coal mines to various modes of failure (i.e. plane, wedge, circular and toppling failure) could be envisaged by virtue of processing and analysis of pertinent satellite data. The aim of the present study was to integrate thematic maps generated using remote sensing image processing ...
Despite the enormous capital required to fund remote sensing initiatives, governments worldwide are increasingly adopting earth observation technologies to optimise operational efficiency and societal benefit. However, the value of information derived from earth observation will increase substantially if augmented by ...
Lokoja, the Kogi state capital, is located at the Niger-Benue confluence. Hazards erupt when human activities in the confluence area are not properly managed. This article uses the Remote Sensing and GIS technique to assess the flood vulnerability zones of the town using the bench mark minimum and maximum water ...
Applications of sampling theory together with the technical developments in the field of remote sensing have opened new paths in forest inventory. This paper presents an overview of ongoing research in the field of automatic feature extraction and pattern recognition, which may provide options towards a fully automated ...
Jul 8, 2013 ... Remote sensing-based evapotranspiration (ET) algorithms developed in recent years are well suited for estimating evapo- transpiration and its spatial trends over time. In this paper the application of energy balance methods in South Africa is reviewed, showing that the Surface Energy Balance Algorithm ...
Aliyu et al.
Remote sensing offers a synoptic capability of covering large areas in real time and can cost effectively explore prospective geothermal sites not easily detectable using conventional survey methods, thus can aid in the prefeasibility stages of geothermal exploration. In this paper, we evaluate the techniques and approaches ...
Aug 31, 2017 ... a variety of investigations, such as mineral and energy resources, environmental characterizations, groundwater and geohazard studies. The integra- tion of geological, remote-sensing, and geophysical. **Deceased. data aids in the detection and geological interpretation of the structural features and has ...
glaciers to estimate recession rates using snout monitoring, remote sensing and geomorphological evidences. Most of these studies related to glacier retreat in Himalaya are attributed to climatic varia- tions or global warming (Bhutiyani 1999; Kulkarni et al. 2002a, 2005; Kulkarni 2007; Bhutiyani et al. 2008; Hasnain 2008).
Rayma A. Cooley; Peter T. Wolter; Brian R. Sturtevant
Spatially explicit modeling of recovering forest structure within two years following wildfire disturbance has not been attempted, yet such knowledge is critical for determining successional pathways. We used remote sensing and field data, along with digital climate and terrain data, to model and map early-seral aspen structure and vegetation species richness following...
Monitoring huge and dynamic floodplains such as the Kafue Flats in Zambia is critical to its sustainable use. This requires among other things accurate, past and current geo-referenced flood maps. The aim of this study was, therefore, to use remotely sensed data to generate flood maps for Kafue Flats. Flood maps were ...
This paper analyzed the spatial and temporal pattern of urban decay in different parts of a traditional organic city through data extracted from satellite remote sensing images. It analyzed temporal differences in urban quality in the city using uniform parameter of urban blight measurement. It presented a classification scheme ...
Cox, Helen; Kelly, Kimberle; Yetter, Laura
This curriculum and instruction paper describes initial implementation and evaluation of remote-sensing exercises designed to promote post-secondary climate literacy in the geosciences. Tutorials developed by the first author engaged students in the analysis of climate change data obtained from NASA satellite missions, including the LANDSAT,…
Precision weed management, an application of precision agriculture, accounts for within-field variability of weed infestation and herbicide damage. Unmanned aerial vehicles (UAVs) provide a unique platform for remote sensing of field crops. They are more efficient and flexible than manned agricultur...
+). An indirect remote sensing (RS) approach has been suggested to map the infrastructure used for degradation rather than the actual change in forest canopy cover. This offers a way to delineate intact forest land and to model and estimate emissions from forest degradation in the non‐intact forest land – thereby...
Kaspersen, Per Skougaard; Drews, Martin
This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...
... Remote Sensing satellite (IRS-P3) launched by the Indian Space Research Organization (ISRO) in March 1996, 13 channel multi-spectral data in the range of 408 to 1010nm at high radiometric resolution, precision, and with narrow spectral bands have been available for a variety of land, atmospheric and oceanic studies ...
Louis R. Iverson; Robin Lambert Graham; Elizabeth A. Cook; Elizabeth A. Cook
Since the launch of the first civilian earth-observing satellite in 1972, satellite remote sensing has provided increasingly sophisticated information on the structure and function of forested ecosystems. Forest classification and mapping, common uses of satellite data, have improved over the years as a result of more discriminating sensors, better classification...
Application of remote sensing technique in biomass change detection: a case study of Bromley and Chihota, Zimbabwe. ... There are various field methods used worldwide to determine density of forest resources but have several limitations because of the nature of factors influencing biomass change. These include ...
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.
Epps, J. W.
Current references were surveyed for the application of remote sensing to traffic and transportation studies. The major problems are presented that concern traffic engineers and transportation managers, and the literature references that discuss remote sensing applications are summarized.
National Aeronautics and Space Administration — MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Multispectral remote sensing images have...
Omar A. Alcover Firpi
Full Text Available A review of Google Earth Engine for archaeological remote sensing using satellite data. GEE is a freely accessible software option for processing remotely sensed data, part of the larger Google suite of products.
Lou, Dong; Zhiu, Bingjian; Zhu, Yingbo
...+, SPOT, ESR- 2SAR and NOAA-AVHRR remote sensing data as well as other general data. TM/ETM+ and SPOT remote sensing images were used to obtain the information about port conditions, shoreline types and storage fields...
Andersen, Jens; Dybkjær, Gorm Ibsen; Jensen, Karsten Høgh
distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration......distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration...
Andersen, J.; Sandholt, Inge; Jensen, Karsten Høgh
Remote Sensing, hydrological modelling, dryness index, surface temperature, vegetation index, Africa, Senegal, soil moisture......Remote Sensing, hydrological modelling, dryness index, surface temperature, vegetation index, Africa, Senegal, soil moisture...
Hidalgo, J. U.
The applicability of remote sensing to transportation and traffic analysis, urban quality, and land use problems is discussed. Other topics discussed include preliminary user analysis, potential uses, traffic study by remote sensing, and urban condition analysis using ERTS.
Under the U.S. Department of Transportation (DOT) Commercial Remote Sensing and Spatial : Information (CRS&SI) Technology Initiative 2 of the Transportation Infrastructure Construction : and Condition Assessment, an intelligent Remote Sensing and GIS...
Under U.S. Department of Transportation (DOT) Commercial Remote Sensing and : Spatial Information (CRS&SI) Technology Initiative 2 of the Transportation : Infrastructure Construction and Condition Assessment, an intelligent Remote Sensing and : GIS-b...
Application and processing of remotely sensed data are discussed. Areas of application include: pollution monitoring, water quality, land use, marine resources, ocean surface properties, and agriculture. Image processing and scene analysis are described along with automated photointerpretation and classification techniques. Data from infrared and multispectral band scanners onboard LANDSAT satellites are emphasized.
The launch of the Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009 marked a milestone in remote sensing for it was the first time a radiometer capable of acquiring wide field of view images at every single snapshot, a unique feature of the synthetic aperture technique, made it to space. The technology behind such an achievement was developed, thanks to the effort of a community of researchers and engineers in different groups around the world. It was only because of their joint work that SMOS finally became a reality. The fact that the European Space Agency, together with CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnológico e Industrial), managed to get the project through should be considered a merit and a reward for that entire community. This paper is an invited historical review that, within a very limited number of pages, tries to provide insight into some of the developments which, one way or another, are imprinted in the name of SMOS.
Climate change will have a significant influence on vegetation health and growth. Predictions of higher mean summer temperatures and prolonged summer draughts may pose a threat to agriculture areas and forest canopies. Rising canopy temperatures can be an indicator of plant stress because of the closure of stomata and a decrease in the transpiration rate. Thermal cameras are available for decades, but still often used for single image analysis, only in oblique view manner or with visual evaluations of video sequences. Therefore remote sensing using a thermal camera can be an important data source to understand transpiration processes. Photogrammetric workflows allow to process thermal images similar to RGB data. But low spatial resolution of thermal cameras, significant optical distortion and typically low contrast require an adapted workflow. Temperature distribution in forest canopies is typically completely unknown and less distinct than for urban or industrial areas, where metal constructions and surfaces yield high contrast and sharp edge information. The aim of this paper is to investigate the influence of interior camera orientation, tie point matching and ground control points on the resulting accuracy of bundle adjustment and dense cloud generation with a typically used photogrammetric workflow for UAVbased thermal imagery in natural environments.
Chen, Fulong; Jiang, Aihui; Ishwaran, Natarajan
Angkor, in the northern province of Siem Reap, Cambodia, is one of the most important world heritage sites of Southeast Asia. Seasonal flood and ground sinking are two representative hazards in Angkor site. Synthetic Aperture Radar (SAR) remote sensing has played an important role for the Angkor site monitoring and management. In this study, 46 scenes of TerraSAR data acquired in the span of February, 2011 to December, 2013 were used for the time series analysis and hazard evaluation; that is, two-fold classification for flood area extracting and Multi-Temporal SAR Interferometry (MT-InSAR) for ground subsidence monitoring. For the flood investigation, the original Single Look Complex (SLC) TerraSAR-X data were transferred into amplitude images. Water features in dry and flood seasons were firstly extracted using a proposed mixed-threshold approach based on the backscattering; and then for the correlation analysis between water features and the precipitation in seasonally and annually. Using the MT-InSAR method, the ground subsidence was derived with values ranging from -50 to +12 mm/yr in the observation period of February, 2011 to June, 2013. It is clear that the displacement on the Angkor site was evident, implying the necessity of continuous monitoring.
The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and
Thongkongoum, W.; Boonduang, S.; Limsuwan, P.
Heart rate monitoring via optically remote noncontact technique was reported in this research. A green laser (5 mW, 532±10 nm) was projected onto the left carotid artery. The reflected laser light on the screen carried the deviation of the interference patterns. The interference patterns were recorded by the digital camera. The recorded videos of the interference patterns were frame by frame analysed by 2 standard digital image processing (DIP) techniques, block matching (BM) and optical flow (OF) techniques. The region of interest (ROI) pixels within the interference patterns were analysed for periodically changes of the interference patterns due to the heart pumping action. Both results of BM and OF techniques were compared with the reference medical heart rate monitoring device by which a contact measurement using pulse transit technique. The results obtained from BM technique was 74.67 bpm (beats per minute) and OF technique was 75.95 bpm. Those results when compared with the reference value of 75.43±1 bpm, the errors were found to be 1.01% and 0.69%, respectively.
Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui
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.
Remote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across a range of spatial and temporal scales. However, the translation of remote sensing signals into meaningful descriptors of vegetation function and traits is still associated with large uncertainties due to complex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in the treatment of confounding factors in spectrum-trait relations. This editorial provides (1) a background on major advances in the remote sensing of vegetation, (2) a detailed timeline and description of relevant historical and planned satellite missions, and (3) an outline of remaining challenges, upcoming opportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Special Issue papers here that focus on novel approaches for exploiting current and future advancements in remote sensor technologies. The described enhancements in spectral, spatial and temporal resolution and radiometric performance provide exciting opportunities to significantly advance the ability to accurately monitor and model the state and function of vegetation canopies at multiple scales on a timely basis.
, National Forest Inventory (NFI) data can be used for estimating availability of forest resources, but often limitations in sampling designs do not allow for accurate estimation of the local availabilities and conditions of, for example, timber volume, tree species composition, or forest structure. Remote...... 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...
Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...
Stephane P. Flasse; Simon N. Trigg; Pietro N. Ceccato; Anita H. Perryman; Andrew T. Hudak; Mark W. Thompson; Bruce H. Brockett; Moussa Drame; Tim Ntabeni; Philip E. Frost; Tobias Landmann; Johan L. le Roux
In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then...
... Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems AGENCY: National Oceanic and.... Abstract NOAA has established requirements for the licensing of private operators of remote-sensing space... Land Remote- Sensing Policy Act of 1992 and with the national security and international obligations of...
... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...
... Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems AGENCY: National Oceanic and... for the licensing of private operators of remote-sensing space systems. The information in applications and subsequent reports is needed to ensure compliance with the Land Remote- Sensing Policy Act of...
Bolton, W.; Lapp, M.; Vitko, J. Jr. [Sandia National Labs., Livermore, CA (United States); Phipps, G. [Sandia National Labs., Albuquerque, NM (United States)
This report documents the results of a Laboratory Directed Research and Development (LDRD) program to explore how best to utilize Sandia`s defense-related sensing expertise to meet the Department of Energy`s (DOE) ever-growing needs for environmental monitoring. In particular, we focused on two pressing DOE environmental needs: (1) reducing the uncertainties in global warming predictions, and (2) characterizing atmospheric effluents from a variety of sources. During the course of the study we formulated a concept for using unmanned aerospace vehicles (UAVs) for making key 0798 climate measurements; designed a highly accurate, compact, cloud radiometer to be flown on those UAVs; and established the feasibility of differential absorption Lidar (DIAL) to measure atmospheric effluents from waste sites, manufacturing processes, and potential treaty violations. These concepts have had major impact since first being formulated in this ,study. The DOE has adopted, and DoD`s Strategic Environmental Research Program has funded, much of the UAV work. And the ultraviolet DIAL techniques have already fed into a major DOE non- proliferation program.
John D. Hedley
Full Text Available Coral reefs are in decline worldwide and monitoring activities are important for assessing the impact of disturbance on reefs and tracking subsequent recovery or decline. Monitoring by field surveys provides accurate data but at highly localised scales and so is not cost-effective for reef scale monitoring at frequent time points. Remote sensing from satellites is an alternative and complementary approach. While remote sensing cannot provide the level of detail and accuracy at a single point than a field survey, the statistical power for inferring large scale patterns benefits in having complete areal coverage. This review considers the state of the art of coral reef remote sensing for the diverse range of objectives relevant for management, ranging from the composition of the reef: physical extent, benthic cover, bathymetry, rugosity; to environmental parameters: sea surface temperature, exposure, light, carbonate chemistry. In addition to updating previous reviews, here we also consider the capability to go beyond basic maps of habitats or environmental variables, to discuss concepts highly relevant to stakeholders, policy makers and public communication: such as biodiversity, environmental threat and ecosystem services. A clear conclusion of the review is that advances in both sensor technology and processing algorithms continue to drive forward remote sensing capability for coral reef mapping, particularly with respect to spatial resolution of maps, and synthesis across multiple data products. Both trends can be expected to continue.
Yi, Dingrong; Kong, Linghua
Multispectral imaging is a powerful tool in remote sensing applications. Recently a micro-arrayed narrow-band optical mosaic filter was invented and successfully fabricated to reduce the size and cost of multispectral imaging devices in order to meet the requirements for low- or mid- altitude remote sensing. Such a filter with four narrow bands is integrated with an off-shelf CCD camera, resulting in an economic and light-weight multispectral imaging camera with the capacity of producing multiple images at different center wavelengths with a single shot. The multispectral imaging camera is then integrated with a wireless transmitter and battery to produce a remote sensing multispectral imaging system. The design and some preliminary results of a prototyped multispectral imaging system with the potential for remote sensing applications with a weight of only 200 grams are reported. The prototyped multispectral imaging system eliminates the image registration procedure required by traditional multispectral imaging technologies. In addition, it has other advantages such as low cost, being light weight and compact in design.
Full Text Available Influenced by the growing popularity of smart phones and the rapid development of open science, remote sensing is being developed and applied more by general public than by trained professionals. This trend is mainly embodied in the democratized data collection, democratized data processing and democratized data usage. This paper discusses and analyzes the three aforementioned characteristics, introduces some recent representative work and progress. It also lists numerous international open data processing tools, including photogrammetry processing, laser scanning processing, machine learning, and spatial information management. In addition, the article makes a detailed description of the benefits of open data, and lists a number of global data programs and experimental data sets for scientific research. At the end of this paper, it is pointed out that the democratization of remote sensing will not only produce great economic benefits, but also bring about great social benefits, and finally change the landscape of industry and the life style of people.
Smith, J.A.; Schmugge, T.J.; Ballard, J.R. Jr.
Land Surface Temperature (LST) is an important parameter in understanding global environmental change because it controls many of the underlying processes in the energy budget at the surface and heat and water transport between the surface and the atmosphere. The measurement of LST at a variety of spatial and temporal scales and extension to global coverage requires remote sensing means to achieve these goals. Land surface temperature and emissivity products are currently being derived from satellite and aircraft remote sensing data using a variety of techniques to correct for atmospheric effects. Implicit in the commonly employed approaches is the assumption of isotropy in directional thermal infrared exitance. The theoretical analyses indicate angular variations in apparent infrared temperature will typically yield land surface temperature errors ranging from 1 to 4 C unless corrective measures are applied
Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasiliki; Themistocleous, Kyriakos; Cuca, Branka; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter
The Cultural Heritage (CH) sector, especially those of monuments and sites has always been facing a number of challenges from environmental pressure, pollution, human intervention from tourism to destruction by terrorism.Within this context, CH professionals are seeking to improve currently used methodologies, in order to better understand, protect and valorise the common European past and common identity. "ATHENA" H2020-TWINN-2015 project will seek to improve and expand the capabilities of the Cyprus University of Technology, involving professionals dealing with remote sensing technologies for supporting CH sector from the National Research Center of Italy (CNR) and German Aerospace Centre (DLR). The ATHENA centre will be devoted to the development, introduction and systematic use of advanced remote sensing science and technologies in the field of archaeology, built cultural heritage, their multi-temporal analysis and interpretation and the distant monitoring of their natural and anthropogenic environment in the area of Eastern Mediterranean.
Distributed calibrating snow models using remotely sensed snow cover information Hongyi Li1, Tao Che1, Xin Li1, Jian Wang11. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China For improving the simulation accuracy of snow model, remotely sensed snow cover data are used to calibrate spatial parameters of snow model. A physically based snow model is developed and snow parameters including snow surface roughness, new snow density and critical threshold temperature distinguishing snowfall from precipitation, are spatially calibrated in this study. The study region, Babaohe basin, located in northwestern China, have seasonal snow cover and with complex terrain. The results indicates that the spatially calibration of snow model parameters make the simulation results more reasonable, and the simulated snow accumulation days, plot-scale snow depth are more better than lumped calibration.
M. L. Jarman
Full Text Available The kinds of imagery, types of data and general relationships between scale of study, scale of mapping and scale of remote sensing products that are appropriate to the South African situation for visual and digital analysis are presented. The type of remote sensing product and processing, the type of field exercise appropriate to each, and the purpose of producing maps at each scale are discussed. Lack of repetitive imagery to date has not allowed for the full investigation of monitoring potential and careful planning at national level is needed to ensure availability of imagery for monitoring purposes. Map production processes which are rapid and accurate should be utilized. An integrated approach to vegetation mapping and surveying, which incorporates the best features of both visual and digital processing, is recommended for use.
Morris-Jones, D. R.; Kiefer, R. W.
A variety of remote sensing data sources and interpretation techniques has been tested in a 6136 hectare watershed with agricultural, forest and urban land cover to determine the relative utility of alternative aerial photographic data sources for gathering the desired land use/land cover data. The principal photographic data sources are high altitude 9 x 9 inch color infrared photos at 1:120,000 and 1:60,000 and multi-date medium altitude color and color infrared photos at 1:60,000. Principal data for estimating soil erosion potential include precipitation, soil, slope, crop, crop practice, and land use/land cover data derived from topographic maps, soil maps, and remote sensing. A computer-based geographic information system organized on a one-hectare grid cell basis is used to store and quantify the information collected using different data sources and interpretation techniques. Research results are compared with traditional Universal Soil Loss Equation field survey methods.
Simonsen, S. B.; Stenseng, Lars; Sørensen, Louise Sandberg
A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction...... of firn compaction to correct ICESat measurements and assessing the present mass loss of the Greenland ice sheet. Validation of the model against the radar data gives good results and confidence in using the model to answer important questions. Questions such as; how large is the firn compaction...... correction relative to the changes in the elevation of the surface observed with remote sensing altimetry? What model time resolution is necessary to resolved the observed layering? What model refinements are necessary to give better estimates of the surface mass balance of the Greenland ice sheet from...
Verkerke, Joshua L.; Williams, David J.; Thoma, Eben
Monitoring for leak hazards is an important consideration in the deployment of carbon dioxide geologic sequestration. Failure to detect and correct leaks may invalidate any potential emissions benefits intended by such projects. Presented is a review of remote sensing methods primed to serve a central role in any monitoring program due to their minimally invasive nature and potential for large area coverage in a limited timeframe or in real-time as a continuous monitoring program. Methods investigated were divided into those capable of indirect detection of carbon dioxide leakage, such as monitoring for vegetative stress and ground surface deformation, and those that directly detect gaseous and atmospheric compounds, by means of such tools as Open-Path Fourier Transform Infrared or Tunable Diode Lasers. Both direct and indirect methods present viable means of detecting a leak event, though ultimately, a robust approach will incorporate multiple monitoring tools that may include both direct and indirect remote sensing methods.
Stefanov, William L.
This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.
In a few days several map products based on the aforementioned analysis were delivered to end users: a review of the different types and purposes of this products will be provided and discussed. An assessment of the thematic accuracy of remotely sensed based products will be carried out on the basis of a review of the several available studies focused on this issue, including the main outcomes of a validation based on a comparison with in-situ data performed by the authors.
Villmann, Thomas; Schleif, Frank-Michael; Merenyi, E.; Strickert, M.; Hammer, Barbara
We propose an extension of the self-organizing map for supervised fuzzy classification learning, whereby uncertain (fuzzy) class information is also allowed for training data. The method is able to detect class similarities, which can be used for data vizualization. Applying a special functional metric, derived from of the L_p norms, we show the application of the method for classification and visualization of hyper-spectral data in satellite image remote sensing image analysis.
Bai, Junhua; Li, Jing; Li, Shaokun
International audience; PDC (Plant Density of Cotton) was an essential parameter for estimating the cotton yield and developing the zone-management measurements. This paper proposed a new method to retrieve PDC from the satellite remote sensing data. The thirteen fields of Xinjiang Production and Construction Corps (XPCC) (total 630 hm2) were selected as the study area, where the sowing date, emergence date, and PDC were investigated. Based on the investigation data the linear models to estim...
Akçay, Hüseyin Gökhan
Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent Univiversity, 2007. Thesis (Master's) -- Bilkent University, 2007. Includes bibliographical references leaves 68-76 Automatic content extraction and classification of remotely sensed images have become highly desired goals by the advances in satellite technology and computing power. The usual choice for the level of processing image data has been pixelbased analysis. Howev...
Kanniah, Kasturi D.; Kamarul Zaman, Nurul A. F.
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.
Posselt, W.; Holota, K.; Tittel, H. O.; Rost, M.; Harnisch, B.
The feasibility of a compact Fourier-Transform-Imaging-Spectrometer (FTIS) for small satellite remote sensing missions is currently being studied under ESA contract. Compared to classical hyperspectral imagers using dispersive spectrometers the major advantages of the FTIS is the compact optics module and the tolerable higher detector temperature, thus easing the instrument thermal design. The feasibility of this instrument concept will be demonstrated by breadboarding.
Carbonneau, P.; Dugdale, S. J.
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
Sterckx, S.; Debruyn, W.; Kempeneers, P.
On the 16th of June 2003 a CASI (Compact Airborne Spectrographic Imager) hyperspectral airborne remote sensing campaign took place above the Southern North Sea, just offshore of Oostende. In coincidence with the airborne overpasses seaborne measurements of water leaving reflectance and water quality parameters were performed. In addition near-simultaneous satellite imagery are available. This paper deals with the analysis of the airborne data. The CASI data have been atmospherically corrected...
Bartholomeus, Harm; Keesstra, Saskia; Kooistra, Lammert; Suomalainen, Juha; Mucher, Sander; Kramer, Henk; Franke, Jappe
To support environmental management there is an increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems. In 2012, different groups within Wageningen University and Research Centre have established an Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold: a) To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments; b) To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community; and c) To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment. The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics (EI) of Alterra. The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angles for characterization of BRDF and flexibility in use of camera's and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested. In the last years we developed and implemented different camera systems (e.g. a hyperspectral pushbroom system, and multispectral frame cameras) which we operated in projects all
In recent years, there has been much discussion about U.S. commercial remoteUnder the Act, the Secretary of Commerce sensing policies and how effectively theylicenses the operations of private U.S. address U.S. national security, foreignremote sensing satellite systems, in policy, commercial, and public interests.consultation with the Secretaries of Defense, This paper will provide an overview of U.S.State, and Interior. PDD-23 provided further commercial remote sensing laws,details concerning the operation of advanced regulations, and policies, and describe recentsystems, as well as criteria for the export of NOAA initiatives. It will also addressturnkey systems and/or components. In July related foreign practices, and the overall2000, pursuant to the authority delegated to legal context for trade and investment in thisit by the Secretary of Commerce, NOAA critical industry.iss ued new regulations for the industry. Licensing and Regulationsatellite systems. NOAA's program is The 1992 Land Remote Sensing Policy Act ("the Act"), and the 1994 policy on Foreign Access to Remote Sensing Space Capabilities (known as Presidential Decision Directive-23, or PDD-23) put into place an ambitious legal and policy framework for the U.S. Government's licensing of privately-owned, high-resolution satellite systems. Previously, capabilities afforded national security and observes the international obligations of the United States; maintain positive control of spacecraft operations; maintain a tasking record in conjunction with other record-keeping requirements; provide U.S. Government access to and use of data when required for national security or foreign policy purposes; provide for U.S. Government review of all significant foreign agreements; obtain U.S. Government approval for any encryption devices used; make available unenhanced data to a "sensed state" as soon as such data are available and on reasonable cost terms and conditions; make available unenhanced data as requested
Full Text Available Change detection (CD of any surface using multitemporal remote sensing images is an important research topic since up-to-date information about earth surface is of great value. Abrupt changes are occurring in different earth surfaces due to natural disasters or man-made activities which cause damage to that place. Therefore, it is necessary to observe the changes for taking necessary steps to recover the subsequent damage. This paper is concerned with this issue and analyzes statistical similarity measure to perform CD using remote sensing images of the same scene taken at two different dates. A variation of normalized mutual information (NMI as a similarity measure has been developed here using sliding window of different sizes. In sliding window approach, pixels’ local neighborhood plays a significant role in computing the similarity compared to the whole image. Thus the insignificant global characteristics containing noise and sparse samples can be avoided when evaluating the probability density function. Therefore, NMI with different window sizes is proposed here to identify changes using multitemporal data. Experiments have been carried out using two separate multitemporal remote sensing images captured one year apart and one month apart, respectively. Experimental analysis reveals that the proposed technique can detect up to 97.71% of changes which outperforms the traditional approaches.
Full Text Available Central Portugal is well known for the existence of Sn-W and Au-Ag mineral occurrences primarily associated with hydrothermal processes. Despite the economic and strategic importance of such occurrences, the detailed geology of this particular region is poorly known and there is an obvious absence of geological mapping at an adequate scale. Remote sensing techniques were used in order to increase current geological knowledge of the Góis–Castanheira de Pêra area (600 km2 and to guide future exploration stages by targeting and prioritising potential locations. Digital image processing algorithms, such as Red, Green, Blue (RGB colour composites, digital spatial filters, band ratios and Principal Components Analysis, were applied to Landsat 8 imagery and elevation data. Lineaments were extracted relying on geological photointerpretation criteria, allowing the identification of new geological–structural elements. Fieldwork was carried out in order to validate the remote sensing interpretations. Integration of remote sensing data with other information sources led to the definition of locations possibly suitable for hosting Sn-W and Au-Ag mineral occurrences. These areas were ranked according to their mineral potential. Targeting the most promising locations resulted in a reduction to less than 10% of the original study area (50.5 km2.
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.
Glackin, David L.; Dodd, Joseph K.
Present large space-based remote sensing systems, and those planned for the next two decades, remain dichotomous and custom-built. An integrated architecture might reduce total cost without limiting system performance. An example of such an architecture, developed at The Aerospace Corporation, explores the feasibility of reducing overall space systems costs by forming a 'super-system' which will provide environmental, earth resources and theater surveillance information to a variety of users. The concept involves integration of programs, sharing of common spacecraft bus designs and launch vehicles, use of modular components and subsystems, integration of command and control and data capture functions, and establishment of an integrated program office. Smart functional modules that are easily tested and replaced are used wherever possible in the space segment. Data is disseminated to systems such as NASA's EOSDIS, and data processing is performed at established centers of expertise. This concept is advanced for potential application as a follow-on to currently budgeted and planned space-based remote sensing systems. We hope that this work will serve to engender discussion that may be of assistance in leading to multinational remote sensing systems with greater cost effectiveness at no loss of utility to the end user.
The use of autonomous proling oats for observational estimates of radiometric quantities in the ocean is explored, and the use of this platform for validation of satellite-based estimates of remote sensing reectance in the ocean is examined. This effort includes comparing quantities estimated from oat and satellite data at nominal wavelengths of 412, 443, 488, and 555 nm, and examining sources and magnitudes of uncertainty in the oat estimates. This study had 65 occurrences of coincident high-quality observations from oats and MODIS Aqua and 15 occurrences of coincident high-quality observations oats and Visible Infrared Imaging Radi-ometer Suite (VIIRS). The oat estimates of remote sensing reectance are similar to the satellite estimates, with disagreement of a few percent in most wavelengths. The variability of the oatsatellite comparisons is similar to the variability of in situsatellite comparisons using a validation dataset from the Marine Optical Buoy (MOBY). This, combined with the agreement of oat-based and satellite-based quantities, suggests that oats are likely a good platform for validation of satellite-based estimates of remote sensing reectance.
The significance of accurate evapotranspiration (ET) need not be overstated because of the current prolonged drought, water scarcity, increasing population, and climate change in many parts of the world. The remote sensing based ET calculation methods had been taken as one of the reliable tools for estimating ET at larger temporal and spatial resolution. The linearity between temperature difference (DT) and surface temperature (Ts) from the thermal band of the satellite is utilized in many operational evapotranspiration (ET) models (SEBAL/METRIC) invoking the anchor pixel concept. In these models, the surface-air temperature difference in anchor pixels (dThot/cold) are calculated based on known the sensible heat flux (H) from the surface energy balance method. We explored the inherent differences while inverting the aerodynamic equation of H with the actual surface-air temperature (dTact) to dThot/cold. The results showed that this formulation possibly underestimates H with smaller dT slope, which overall overestimates the ET. The major finding and innovative aspect of this study are to present the two inconsistent behaviors of the identical process of energy transformation, which had been utilized by remote sensing based evapotranspiration models. This study will help to understand the uncertainty in H calculations in these models, explore the limitations of this methodology (dThot, cold), and warrant further discussion of this application in remote sensing and micrometeorology community.
Beyrich, F. [BTU Cottbus, LS Umweltmeteorologie, Cottbus (Germany)
Remote sensing systems can be considered today as a real alternative to classical soundings with respect to the MH (mixing height) determination. They have the basic advantage to allow continuous monitoring of the ABL (atmospheric boundary layer). Some technical issues which limit their operational use at present should be solved in the near future (frequency allocation, eye safety, costs). Taking into account specific operating conditions and the formulated-above requirements of a sounding system to be used for MH determination it becomes obvious that none of the available systems meets all of them, i.e., the `Mixing height-meter` does not exist. Therefore, reliable MH determination under a wide variety of conditions can be achieved only by integrating different instruments into a complex sounding system. The S-profiles provide a suitable data base for MH estimation from all types of remote sensing instruments. The criteria to deduce MH-values from these profiles should consider the structure type and the evolution stage of the ABL as well as the shape of the profiles. A certain kind of harmonization concerning these criteria should be achieved. MH values derived automatically from remote sensing data appear to be not yet reliable enough for direct operational use, they should be in any case critically examined by a trained analyst. Contemporary mathematical methods (wavelet transforms, fuzzy logics) are supposed to allow considerable progress in this field in the near future. (au) 19 refs.
Giardino, Marco J.
During its long history of developing and deploying remote sensing instruments, NASA has provided a scientific data that have benefitted a variety of scientific applications among them archaeology. Multispectral and hyperspectral instrument mounted on orbiting and suborbital platforms have provided new and important information for the discovery, delineation and analysis of archaeological sites worldwide. Since the early 1970s, several of the ten NASA centers have collaborated with archaeologists to refine and validate the use of active and passive remote sensing for archeological use. The Stennis Space Center (SSC), located in Mississippi USA has been the NASA leader in archeological research. Together with colleagues from Goddard Space Flight Center (GSFC), Marshall Space Flight Center (MSFC), and the Jet Propulsion Laboratory (JPL), SSC scientists have provided the archaeological community with useful images and sophisticated processing that have pushed the technological frontiers of archaeological research and applications. Successful projects include identifying prehistoric roads in Chaco canyon, identifying sites from the Lewis and Clark Corps of Discovery exploration and assessing prehistoric settlement patterns in southeast Louisiana. The Scientific Data Purchase (SDP) stimulated commercial companies to collect archaeological data. At present, NASA formally solicits "space archaeology" proposals through its Earth Science Directorate and continues to assist archaeologists and cultural resource managers in doing their work more efficiently and effectively. This paper focuses on passive remote sensing and does not consider the significant contributions made by NASA active sensors. Hyperspectral data offers new opportunities for future archeological discoveries.
Oh, Sunjong; Jung, Youngdo; Kim, Seonggi; Kim, SungJoon; Hu, Xinghao; Lim, Hyuneui; Kim, CheolGi
Mechanoreceptors in a fingertip convert external tactile stimulations into electrical signals, which are transmitted by the nervous system through synaptic transmitters and then perceived by the brain with high accuracy and reliability. Inspired by the human synapse system, this paper reports a robust tactile sensing system consisting of a remote touch tip and a magnetic synapse. External pressure on the remote touch tip is transferred in the form of air pressure to the magnetic synapse, where its variation is converted into electrical signals. The developed system has high sensitivity and a wide dynamic range. The remote sensing system demonstrated tactile capabilities over wide pressure range with a minimum detectable pressure of 6 Pa. In addition, it could measure tactile stimulation up to 1,000 Hz without distortion and hysteresis, owing to the separation of the touching and sensing parts. The excellent performance of the system in terms of surface texture discrimination, heartbeat measurement from the human wrist, and satisfactory detection quality in water indicates that it has considerable potential for various mechanosensory applications in different environments.
Full Text Available This paper describes the evolution of recent work on using crowdsourced analysis of remote sensing imagery, particularly high-resolution aerial imagery, to provide rapid, reliable assessments of damage caused by earthquakes and potentially other disasters. The initial effort examined online imagery taken after the 2008 Wenchuan, China, earthquake. A more recent response to the 2010 Haiti earthquake led to the formation of an international consortium: the Global Earth Observation Catastrophe Assessment Network (GEO-CAN. The success of GEO-CAN in contributing to the official damage assessments made by the Government of Haiti, the United Nations, and the World Bank led to further development of a web-based interface. A current initiative in Christchurch, New Zealand, is underway where remote sensing experts are analyzing satellite imagery, geotechnical engineers are marking liquefaction areas, and structural engineers are identifying building damage. The current site includes online training to improve the accuracy of the assessments and make it possible for even novice users to contribute to the crowdsourced solution. The paper discusses lessons learned from these initiatives and presents a way forward for using crowdsourced remote sensing as a tool for rapid assessment of damage caused by natural disasters around the world.
A strong remote sensing regime is a necessary component of any contemporary national or international energy policy. Energy is essential to the functioning of modem industrial society, and as such it is the responsibility of governments to produce sound national energy policies in order to ensure stable economic growth, ecologically responsible use of energy resources and the health and safety of citizens. Comprehensive, accurate and timely remote sensing data can aid decision making on energy matters in several areas. This paper looks at the benefits that can be realized in resource exploration, weather forecasting and environmental monitoring. Improvements in the technology of remote sensing platforms would be of great value to buyers of energy, sellers of energy and the environment. Furthermore, the utility of such information could be enhanced by efforts of government agencies to communicate it more effectively to the end-user. National energy policies should thus include investments not only in satellite system hardware to collect data, but also in the services required to interpret and distribute the data. (author)
Lili Somantri, Nandi
The new remote sensing material included in the subjects of geography in the curriculum of 1994. For geography teachers generation of 90s and over who in college do not get the material remote sensing, for teaching is a tough matter. Most teachers only give a theoretical matter, and do not carry out practical reasons in the lack of facilities and infrastructure of computer laboratories. Therefore, in this paper studies the importance about the method or manner of teaching remote sensing material in schools. The purpose of this paper is 1) to explain the position of remote sensing material in the study of geography, 2) analyze the Geography Curriculum 2013 Subjects related to remote sensing material, 3) describes a method of teaching remote sensing material in schools. The method used in this paper is a descriptive analytical study supported by the literature. The conclusion of this paper that the position of remote sensing in the study of geography is a method or a way to obtain spatial data earth's surface. In the 2013 curriculum remote sensing material has been applied to the study of land use and transportation. Remote sensing methods of teaching must go through a practicum, which starts from the introduction of the theory of remote sensing, data extraction phase of remote sensing imagery to produce maps, both visually and digitally, field surveys, interpretation of test accuracy, and improved maps.
Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang
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.
Kolm, K. E.
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.
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.
Tožička, Jan; Komenda, Antonín
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.
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.
Sekatski, P.; Skotiniotis, M.; Dür, W.
We consider quantum metrology with arbitrary prior knowledge of the parameter. We demonstrate that a single sensing two-level system can act as a virtual multilevel system that offers increased sensitivity in a Bayesian single-shot metrology scenario, and that allows one to estimate (arbitrary) large parameter values by avoiding phase wraps. This is achieved by making use of additional degrees of freedom or auxiliary systems not participating in the sensing process. The joint system is manipulated by intermediate control operations in such a way that an effective Hamiltonian, with an arbitrary spectrum, is generated that mimics the spectrum of a multisystem interacting with the field. We show how to use additional internal degrees of freedom of a single trapped ion to achieve a high-sensitivity magnetic field sensor for fields with arbitrary prior knowledge.
Acker, James; Riebeek, Holli; Ledley, Tamara Shapiro; Herring, David; Lloyd, Steven
"Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on
Giardino, Marco J.
NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through
Driscoll, J. M.; Hay, L.; Van Beusekom, A. E.
Watershed models in Alaska are critical for understanding snow- and glacier-dominated hydrologic processes in a changing climate. The highly diverse, frozen, and remote landscapes in Alaska present a host of new challenges for broad-scale hydrologic model development, including a notable absence of field-measured streamflow data. Without this commonly-used data for model calibration, alternative methods need to be developed in order to model hydrologic processes Alaska. Calibration methods that use remotely-sensed data in multi-objective, step-wise procedures were developed in this study. A calibration method using snow covered area (SCA) measured by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) was developed for a daily, deterministic, physically-based watershed model. The model selected for this study was the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS), and focused on a 62,500-sqkm test basin in southeastern Alaska from 2000 to 2014. Watershed model calibration to SCA ensures model processes adequately estimate transitional model states during snowmelt, a dominant hydrologic process in the basin. Gridded SCA data measuring fractional coverage were spatially aggregated to hydrologic response units within the basin. Model results were aggregated to eleven subbasins for calibration, comparison, and evaluation. Calibration of the subbasin watersheds to intermediate snowmelt process states, such as daily SCA, will likely also improve model estimates of solar radiation, potential evapotranspiration, annual water balance, and components of daily runoff. In Alaska where snow and glacier-fed systems are abundant, observed data are often scarce; therefore the development of calibration methods with remotely-sensed data are critical for improvement of watershed models which can then be used to estimate response to climate change. This study provides a method using remotely-sensed snow cover data to overcome field-measured data
Full Text Available Agricultural drought is a natural hazard that can be characterized by shortage of water supply. In the scope of this paper, we synthesized the importance of agricultural drought and methods commonly employed to monitor agricultural drought conditions. These include: (i in-situ based methods, (ii optical remote sensing methods, (iii thermal remote sensing methods, (iv microwave remote sensing methods, (v combined remote sensing methods, and (vi synergy between in-situ and remote sensing based methods. The in-situ indices can provide accurate results at the point of measurements; however, unable to provide spatial dynamics over large area. This can potentially be addressed by using remote sensing based methods because remote sensing platforms have the ability to view large area at a near continuous fashion. The remote sensing derived agricultural drought related indicators primarily depend on the characteristics of reflected/emitted energy from the earth surface, thus the results can be relatively less accurate in comparison to the in-situ derived outcomes. Despite a significant amount of research and development has been accomplished in particular to the area of remote sensing of agricultural drought, still there are several challenges. Those include: monitoring relatively small area, filling gaps in the data, developing consistent historical dataset, developing remote sensing-based agricultural drought forecasting system, integrating the recently launched and upcoming remote sensors, and developing standard validation schema, among others.
Marshall, M. T.
Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of
Watts, C. T.
With the help of satellites, the Earth's environment can be monitored from a distance. Earth observing satellites and sensors collect data and survey patterns that supply important information about the environment relating to its affect on human health. Combined with ground data, such patterns and remote sensing data can be essential to public health applications. Remote sensing technology is providing information that can help predict factors that affect human health, such as disease, drought, famine, and floods. A number of public health concerns that affect Earth's human population are part of the current National Aeronautics and Space Administration (NASA) Earth Science Applications Plan to provide remotely gathered data to public health decision-makers to aid in forming and implementing policy to protect human health and preserve well-being. These areas of concern are: air quality; water quality; weather and climate change; infectious, zoonotic, and vector-borne disease; sunshine; food resource security; and health risks associated with the built environment. Collaborations within the Earth Science Applications Plan join local, state, national, or global organizations and agencies as partners. These partnerships engage in projects that strive to understand the connection between the environment and health. The important outcome is to put this understanding to use through enhancement of decision support tools that aid policy and management decisions on environmental health risks. Future plans will further employ developed models in formats that are compatible and accessible to all public health organizations.
Dewit, M.; Williams-Jones, G.; Stead, D.; Kremsater, R.; So, M.; Francioni, M.
Remote sensing methods are widely used in geological applications today. The physical properties of rock such as composition, texture and structure have previously been difficult to accurately quantify through remote sensing, however, new research in the fields of terrestrial LiDAR and infrared thermography has proven useful in the differentiation of lithology in sedimentary outcrops. This study focuses on the application of these methods, in conjunction with digital photogrammetry, to a number of volcanic rock masses in the Garibaldi Volcanic Belt (GVB) and Chilcotin Group (CG) of British Columbia. The GVB is a chain of volcanoes and related features extending through southwestern British Columbia and is the northern extension of the Cascade Volcanic Arc. The CG is an assemblage of Neogene-aged lavas covering nearly 36,500 km2 in central British Columbia. We integrate infrared chronothermography, which enables the characterization of temporal change in the thermal signature, laser waveform attributes such as amplitude and intensity, and digital photogrammetry, in order to distinguish between a range of rock types, lithologies and structures. This data is compared to laboratory experiments on field samples and ground-truth information collected by classical geological and geotechnical methods. Our research clearly shows that it is possible to remotely map, in 3D, otherwise inaccessible volcanic rock masses.
Liu, Yang; Picard, Sean; Williamson, Carey
Heavner, M.; Loveland, R.
The Melt Area Detection Index (MADI), a remote sensing algorithm to discriminate between dry and wet snow, has been previously developed and applied to the western portion of the Greenland ice sheet for the years 2000-2006, using Moderate Resolution Imaging Radiospectrometer (MODIS) data (Chylek et al, 2007). We extend that work both spatially and temporally by taking advantage of newly available data, and developing algorithms that facilitate the sensing of cloud cover and the automated inference of wet snow regions. The automated methods allow the development of a composite melt area data product with 0.25 km^2 spatial resolution and approximately two week temporal resolution. We discuss melt area dynamics that are inferred from this high resolution composite melt area. Chylek, P., M. McCabe, M. K. Dubey, and J. Dozier (2007), Remote sensing of Greenland ice sheet using multispectral near-infrared and visible radiances, J. Geophys. Res., 112, D24S20, doi:10.1029/2007JD008742.
Li, Fei; Zhao, Ying; Zheng, Jiajia; Luo, Juhua; Zhang, Xiaoqiang
The quantification of grassland grazing intensity (GI) and its detailed spatial distribution are important for grassland management and ecological protection. Remote sensing has great potential in these areas, but its use is still limited. This study analyzed the impacts of grazing on biophysical properties of vegetation and suggested using biomass to quantify GI because of its stability and interpretability. In comparison to a single spectral index, such as the red edge index (REI), combining REI and a cellulose absorption ratio index calculated from hyperspectral data performs better for biomass estimation. Further, an auxiliary spectral index, called the grazing monitoring index (GMI), was developed based on differences in spectral reflectance in the infrared range. Experiments in a grazing area of the Inner Mongolia grassland indicated that GMI can identify GI, with three range intervals (GMI blocks in the experimental grazing area. Overall, our study provides inspiration and ideas for using satellite remote sensing for evaluating plant production, standing biomass, and livestock impacts.
In the past 20+ years, NASA Goddard Space Flight Center (GSFC) has successfully developed and flown lidars for mapping of Mars, the Earth, Mercury and the Moon. As laser and electro-optics technologies expand and mature, more sophisticated instruments that once were thought to be too complicated for space are being considered and developed. We will present progress on several new, space-based laser instruments that are being developed at GSFC. These include lidars for remote sensing of carbon dioxide and methane on Earth for carbon cycle and global climate change; sodium resonance fluorescence lidar to measure environmental parameters of the middle and upper atmosphere on Earth and Mars and a wind lidar for Mars orbit; in situ laser instruments include remote and in-situ measurements of the magnetic fields; and a time-of-flight mass spectrometer to study the diversity and structure of nonvolatile organics in solid samples on missions to outer planetary satellites and small bodies.
van Diedenhoven, Bastiaan
Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally
Full Text Available The accurate estimation of deposits adhering on insulators is critical to prevent pollution flashovers which cause huge costs worldwide. The traditional evaluation method of insulator contaminations (IC is based sparse manual in-situ measurements, resulting in insufficient spatial representativeness and poor timeliness. Filling that gap, we proposed a novel evaluation framework of IC based on remote sensing and data mining. Varieties of products derived from satellite data, such as aerosol optical depth (AOD, digital elevation model (DEM, land use and land cover and normalized difference vegetation index were obtained to estimate the severity of IC along with the necessary field investigation inventory (pollution sources, ambient atmosphere and meteorological data. Rough set theory was utilized to minimize input sets under the prerequisite that the resultant set is equivalent to the full sets in terms of the decision ability to distinguish severity levels of IC. We found that AOD, the strength of pollution source and the precipitation are the top 3 decisive factors to estimate insulator contaminations. On that basis, different classification algorithm such as mahalanobis minimum distance, support vector machine (SVM and maximum likelihood method were utilized to estimate severity levels of IC. 10-fold cross-validation was carried out to evaluate the performances of different methods. SVM yielded the best overall accuracy among three algorithms. An overall accuracy of more than 70% was witnessed, suggesting a promising application of remote sensing in power maintenance. To our knowledge, this is the first trial to introduce remote sensing and relevant data analysis technique into the estimation of electrical insulator contaminations.
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 surfaceÃ¢Â€Â“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
Merritt, D. N.; Skarke, A. D.; Silwal, S.; Dash, P.
The Mississippi Sound is a semi-enclosed estuary between the coast of Mississippi and a chain of offshore barrier islands with relatively shallow water depths and high marine biodiversity that is wildly utilized for commercial fishing and public recreation. The discharge of sediment-laden rivers into the Mississippi Sound and the adjacent Northern Gulf of Mexico creates turbid plumes that can extend hundreds of square kilometers along the coast and persist for multiple days. The concentration of suspended sediment in these coastal waters is an important parameter in the calculation of regional sediment budgets as well as analysis of water-quality factors such as primary productivity, nutrient dynamics, and the transport of pollutants as well as pathogens. The spectral resolution, sampling frequency, and regional scale spatial domain associated with satellite based sensors makes remote sensing an ideal tool to monitor suspended sediment dynamics in the Northern Gulf of Mexico. Accordingly, the presented research evaluates the validity of published models that relate remote sensing reflectance with suspended sediment concentrations (SSC), for similar environmental settings, with 51 in situ observations of SSC from the Mississippi Sound. Additionally, regression analysis is used to correlate additional in situ observations of SSC in Mississippi Sound with coincident observations of visible and near-infrared band reflectance collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Aqua satellite, in order to develop a site-specific empirical predictive model for SSC. Finally, specific parameters of the sampled suspended sediment such as grain size and mineralogy are analyzed in order to quantify their respective contributions to total remotely sensed reflectance.
Li, X.; Wang, R.; Yang, A.; Vojnovic, I.
With the decline of manufacturing industries, many Rust Belt cities, which enjoyed prosperity in the past, are now suffering from financial stress, population decrease and urban poverty. As a consequence, urban neighborhoods deteriorate. Houses are abandoned and left to decay. Neighborhood vacancy brings on many problems. Governments and agencies try to survey the vacancy level by going through neighborhoods and record the condition of each structure, or by buying information of active mailing addresses to get approximate neighborhood vacancy rate. But these methods are expensive and time consuming. Remote sensing provides a quick and comparatively cost-efficient way to access spatial information on social and demographical attributes of urban area. In our study, we use remote sensing to detect a major aspect of neighborhood deterioration, the vacancy levels of neighborhoods in Detroit city. We compared different neighborhoods using Landsat 8 images in 2013. We calculated NDVI that indicates the greenness of neighborhoods with the image in July 2013. Then we used thermal infrared information from image in February to detect human activities. In winter, abandoned houses will not consume so much energy and therefore neighborhoods with more abandoned houses will have smaller urban heat island effect. Controlling for the differences in terms of the greenness obtained from summer time image, we used thermal infrared from winter image to determine the temperatures of urban surface. We find that hotter areas are better maintained and have lower house vacancy rates. We also compared the changes over time for neighborhoods using Landsat 7 images from 2003 to 2013. The results show that deteriorated neighborhoods have increased NDVI in summer and get colder in winter due to abandonment of houses. Our results show the potential application of remote sensing as an easily accessed and efficient way to obtain data about social conditions in cities. We used the neighborhood
Matikainen, Leena; Lehtomäki, Matti; Ahokas, Eero; Hyyppä, Juha; Karjalainen, Mika; Jaakkola, Anttoni; Kukko, Antero; Heinonen, Tero
To secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments
Babu, Dinesh Kumar; Kaufmann, Christof; Schmidt, Marco; Dhams, Thorsten; Conrad, Christopher
High spatial and temporal resolution data is vital for crop monitoring and phenology change detection. Due to the lack of satellite architecture and frequent cloud cover issues, availability of daily high spatial data is still far from reality. Remote sensing time series generation of high spatial and temporal data by data fusion seems to be a practical alternative. However, it is not an easy process, since it involves multiple steps and also requires multiple tools. In this paper, a framework of Geo Information System (GIS) based tool is presented for semi-autonomous time series generation. This tool will eliminate the difficulties by automating all the steps and enable the users to generate synthetic time series data with ease. Firstly, all the steps required for the time series generation process are identified and grouped into blocks based on their functionalities. Later two main frameworks are created, one to perform all the pre-processing steps on various satellite data and the other one to perform data fusion to generate time series. The two frameworks can be used individually to perform specific tasks or they could be combined to perform both the processes in one go. This tool can handle most of the known geo data formats currently available which makes it a generic tool for time series generation of various remote sensing satellite data. This tool is developed as a common platform with good interface which provides lot of functionalities to enable further development of more remote sensing applications. A detailed description on the capabilities and the advantages of the frameworks are given in this paper.
Joyce, K. E.; White, B.
Enduring a traditional lecture is the tertiary education equivalent of a long, slow, jog. There are certainly some educational benefits if the student is able to maintain concentration, but they are just as likely to get caught napping and fall off the back end of the treadmill. Alternatively, a pre-choreographed interactive workshop style class requires students to continually engage with the materials. Appropriately timed breaks or intervals allow students to recover briefly before being increasingly challenged throughout the class. Using an introductory remote sensing class at Charles Darwin University, this case study presents a transition from the traditional stand and deliver style lecture to an active student-led learning experience. The class is taught at undergraduate and postgraduate levels, with both on-campus as well as online distance learning students. Based on the concept that active engagement in learning materials promotes 'stickiness' of subject matter, the remote sensing class was re-designed to encourage an active style of learning. Critically, class content was reviewed to identify the key learning outcomes for the students. This resulted in a necessary sacrifice of topic range for depth of understanding. Graduates of the class reported high levels of enthusiasm for the materials, and the style in which the class was taught. This paper details a number of techniques that were used to engage students in active and problem based learning throughout the semester. It suggests a number of freely available tools that academics in remote sensing and related fields can readily incorporate into their teaching portfolios. Moreover, it shows how simple it can be to provide a far more enjoyable and effective learning experience for students than the one dimensional lecture.
Piermattei, Viviana; Madonia, Alice; Bonamano, Simone; Consalvi, Natalizia; Caligiore, Aurelio; Falcone, Daniela; Puri, Pio; Sarti, Fabio; Spaccavento, Giovanni; Lucarini, Diego; Pacci, Giacomo; Amitrano, Luigi; Iacullo, Salvatore; D'Andrea, Salvatore; Marcelli, Marco
The development of low-cost instrumentation plays a key role in marine environmental studies and represents one of the most innovative aspects of marine research. The availability of low-cost technologies allows the realization of extended observatory networks for the study of marine phenomena through an integrated approach merging observations, remote sensing and operational oceanography. Marine services and practical applications critically depends on the availability of large amount of data collected with sufficiently dense spatial and temporal sampling. This issue directly influences the robustness both of ocean forecasting models and remote sensing observations through data assimilation and validation processes, particularly in the biological domain. For this reason it is necessary the development of cheap, small and integrated smart sensors, which could be functional both for satellite data validation and forecasting models data assimilation as well as to support early warning systems for environmental pollution control and prevention. This is particularly true in coastal areas, which are subjected to multiple anthropic pressures. Moreover, coastal waters can be classified like case 2 waters, where the optical properties of inorganic suspended matter and chromophoric dissolved organic matter must be considered and separated by the chlorophyll a contribution. Due to the high costs of mooring systems, research vessels, measure platforms and instrumentation a big effort was dedicated to the design, development and realization of a new low cost mini-FerryBox system: Spectra. Thanks to the modularity and user-friendly employment of the system, Spectra allows to acquire continuous in situ measures of temperature, conductivity, turbidity, chlorophyll a and chromophoric dissolved organic matter (CDOM) fluorescences from voluntary vessels, even by non specialized operators (Marcelli et al., 2014; 2016). This work shows the preliminary application of this technology to
Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing
Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.
Geli, H. M. E.; Hain, C.; Anderson, M. C.; Senay, G. B.
Recent research findings on modeling actual evapotranspiration (ET) using remote sensing data and methods have proven the ability of these methods to address wide range of hydrological and water resources issues including river basin water balance for improved water resources management, drought monitoring, drought impact and socioeconomic responses, agricultural water management, optimization of land-use for water conservations, water allocation agreement among others. However, there is still a critical need to identify appropriate type of ET information that can address each of these issues. The current trend of increasing demand for water due to population growth coupled with variable and limited water supply due to drought especially in arid and semiarid regions with limited water supply have highlighted the need for such information. To properly address these issues different spatial and temporal resolutions of ET information will need to be used. For example, agricultural water management applications require ET information at field (30-m) and daily time scales while for river basin hydrologic analysis relatively coarser spatial and temporal scales can be adequate for such regional applications. The objective of this analysis is to evaluate the potential of using an integrated ET information that can be used to address some of these issues collectively. This analysis will highlight efforts to address some of the issues that are applicable to New Mexico including assessment of statewide water budget as well as drought impact and socioeconomic responses which all require ET information but at different spatial and temporal scales. This analysis will provide an evaluation of four remote sensing based ET models including ALEXI, DisALEXI, SSEBop, and SEBAL3.0. The models will be compared with ground-based observations from eddy covariance towers and water balance calculations. Remote sensing data from Landsat, MODIS, and VIIRS sensors will be used to provide ET
Lam, Nina; Emerson, Charles; Quattrochi, Dale
The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of
Hick, P.P.; Russell, W.G.R.
This report concentrates on some of the aspects of spectral analysis and shows that: spectral bands, existing in currently available remote sensing systems, may not be optimal for the delineation of salinity; that volunteer vegetation indicated the impact of increasing salinity; and that minor amounts of soluble salts in surface soils will modify spectra. The usefulness of portable field spectroradiometers and airborne scanning systems are also assessed for the discrimination of areas of land in the early stages of the effects of salinization. 9 refs., 3 tabs., 6 figs
Geoscience applications of active microwave remote sensing systems are examined. Major application areas for the system include: (1) exploration of petroleum, mineral, and ground water resources, (2) mapping surface and structural features, (3) terrain analysis, both morphometric and genetic, (4) application in civil works, and (5) application in the areas of earthquake prediction and crustal movements. Although the success of radar surveys has not been widely publicized, they have been used as a prime reconnaissance data base for mineral exploration and land-use evaluation in areas where photography cannot be obtained.
Vanderbilt, V. C.; Daughtry, C. S.
Discrimination of a few plants scattered among many plants is a goal common to detection of agricultural weeds, invasive plant species and illegal Cannabis clandestinely grown outdoors, the subject of this research. Remote sensing technology provides an automated, computer based, land cover classification capability that holds promise for improving upon the existing approaches to Cannabis detection. In this research, we investigated whether hyperspectral reflectance of recently harvested, fully turgid Cannabis leaves and buds depends upon the concentration of the psychoactive ingredient Tetrahydrocannabinol (THC) that, if present at sufficient concentration, presumably would allow species-specific identification of Cannabis.
Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.
The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and
Paul C. Doraiswamy
Full Text Available Unlike traditional ground-based methodology, remote sensing allows for the rapid estimation of crop residue cover (fR. While the Cellulose Absorption Index (CAI is ideal for fR estimation, a new index, the Shortwave Infrared Normalized Difference Residue Index (SINDRI, utilizing ASTER bands 6 and 7, is proposed for future multispectral sensors and would be less costly to implement. SINDRI performed almost as well as CAI and better than other indices at five locations in the USA on multiple dates. A minimal upgrade from one broad band to two narrow bands would provide fR data for carbon cycle modeling and tillage verification.
+). An indirect remote sensing (RS) approach has been suggested to map the infrastructure used for degradation rather than the actual change in forest canopy cover. This offers a way to delineate intact forest land and to model and estimate emissions from forest degradation in the non‐intact forest land – thereby......Our global climate system is changing and there is now broad agreement among climate scientists that changes are most likely human induced and primarily caused by CO2 emissions to the atmosphere. One important source of carbon emissions is forest disturbance by various anthropogenic activities...
Queisser, Manuel; Burton, Mike
An accurate quantification of CO2 flux from both natural and anthropogenic sources is of great interest in various areas of the Earth, environmental and atmospheric sciences. As emitted excess CO2 quickly dilutes into the 400 ppm ambient CO2 concentration and degassing often occurs diffusively, measuring CO2 fluxes is challenging. Therefore, fluxes are usually derived from grids of in-situ measurements, which are labour intensive measurements. Other than a safe measurement distance, remote sensing offers quick, spatially integrated and thus a more thorough measurement of gas fluxes. Active remote sensing combines these merits with operation independent of sunlight or clear sky conditions. Due to their weight and size, active remote sensing platforms for CO2, such as LIDAR, cannot easily be applied in the field or transported overseas. Moreover, their complexity requires a rather lengthy setup procedure to be undertaken by skilled personal. To meet the need for a rugged, practical CO2 remote sensing technique to scan volcanic plumes, we have developed the CO2 LIDAR. It measures 1-D column densities of CO2 with sufficient sensitivity to reveal the contribution of magmatic CO2. The CO2 LIDAR has been mounted inside a small aircraft and used to measure atmospheric column CO2 concentrations between the aircraft and the ground. It was further employed on the ground, measuring CO2 emissions from mud volcanism. During the measurement campaign the CO2 LIDAR demonstrated reliability, portability, quick set-up time (10 to 15 min) and platform independence. This new technique opens the possibility of rapid, comprehensive surveys of point source, open-vent CO2 emissions, as well as emissions from more diffuse sources such as lakes and fumarole fields. Currently, within the proof-of-concept ERC project CarbSens, a further reduction in size, weight and operational complexity is underway with the goal to commercialize the platform. Areas of potential applications include fugitive
Shariff, Abdul Rashid Mohamed
IGRSM This proceedings consists of the peer-reviewed papers from the 7th IGRSM International Conference and Exhibition on Remote Sensing & GIS (IGRSM 2014), which was held on 21-22 April 2014 at Berjaya Times Square Hotel, Kuala Lumpur, Malaysia. The conference, with the theme Geospatial Innovation for Nation Building was aimed at disseminating knowledge, and sharing expertise and experiences in geospatial sciences in all aspects of applications. It also aimed to build linkages between local and international professionals in this field with industries. Highlights of the conference included: Officiation by Y B Datuk Dr Abu Bakar bin Mohamad Diah, Deputy Minister of Minister of Science, Technology & Innovation Keynote presentations by: Associate Professor Dr Francis Harvey, Chair of the Geographic Information Science Commission at the International Geographical Union (IGU) and Director of U-Spatial, University of Minnesota, US: The Next Age of Discovery and a Future in a Post-GIS World. Professor Dr Naoshi Kondo, Bio-Sensing Engineering, University of Kyoto, Japan: Mobile Fruit Grading Machine for Precision Agriculture. Datuk Ir Hj Ahmad Jamalluddin bin Shaaban, Director-General, National Hydraulic Research Institute of Malaysia (NAHRIM), Malaysia: Remote Sensing & GIS in Climate Change Analyses. Oral and poster presentations from 69 speakers, from both Malaysia (35) and abroad (34), covering areas of water resources management, urban sprawl & social mobility, agriculture, land use/cover mapping, infrastructure planning, disaster management, technology trends, environmental monitoring, atmospheric/temperature monitoring, and space applications for the environment. Post-conference workshops on: Space Applications for Environment (SAFE), which was be organised by the Japan Aerospace Exploration Agency (JAXA) Global Positioning System (GPS) Receiver Evaluation Using GPS Simulation, which was be organised by the Science & Technology Research Institute for Defence
Remote Sensing is a scientific discipline of non-contact monitoring. It includes a range of technologies that span from aerial photography to advanced spectral imaging and analytical methods. This Session is designed to demonstrate contemporary practical applications of remote ...
Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping
Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.
Liu Dechang; Zhao Yingjun; Ye Fawang
The paper reviewes the innovative process of remote sensing for the uranium geology in Beijing Research Institute of Uranium Geology (BRIUG), discusses the science and technology progress of uranium geology due to remote sensing technique, and the way how to keep sustainable development of the remote sensing for uranium geology so as to play an important role in the uranium geology in the future. (authors)
Estes, J. E.; Smith, T.; Star, J. L.
Research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. The focus is on remote sensing and application for the Earth Observing System (Eos) and Space Station, including associated polar and co-orbiting platforms. The remote sensing research activities are being expanded, integrated, and extended into the areas of global science, georeferenced information systems, machine assissted information extraction from image data, and artificial intelligence. The accomplishments in these areas are examined.
The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed
Cavalli, Rosa Maria; Laneve, Giovanni; Fusilli, Lorenzo; Pignatti, Stefano; Santini, Federico
This paper aims to assess the suitability of remote sensing for enhancing the management of water body resources and for providing an inexpensive way to gather, on a wide area, weed infestation extent and optical parameter linked to the water body status. Remotely sensed satellite images and ancillary ground true data were used to produce land cover maps, trough classification techniques, and water compounds maps, applying radiative transfer models. The study proposed within the framework of the cooperation between Italian Foreign Affair Ministry (through the University of Rome) and Kenyan Authorities has been carried out on the Kenyan part of the Lake Victoria. This lake is one of the largest freshwater bodies of the world where, over the last few years environmental challenges and human impact have perturbed the ecological balance affecting the biodiversity. The objective of this research study is to define the thematic products, retrievable from satellite images, like weed abundance maps and water compound concentrations. These products, if provided with an appropriate time frequency, are useful to identify the preconditions for the occurrence of hazard events like abnormal macrophyte proliferation and to develop an up-to-date decision support system devoted to an apprised territory, environment and resource management.
McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.
Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS.
McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.
Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS
IACOB I. CIPRIAN
Full Text Available Fractal Dimension of Urban Expansion Based on Remote Sensing Images: In Cluj-Napoca city the process of urbanization has been accelerated during the years and implication of local authorities reflects a relevant planning policy. A good urban planning framework should take into account the society demands and also it should satisfy the natural conditions of local environment. The expansion of antropic areas it can be approached by implication of 5D variables (time as a sequence of stages, space: with x, y, z and magnitude of phenomena into the process, which will allow us to analyse and extract the roughness of city shape. Thus, to improve the decision factor we take a different approach in this paper, looking at geometry and scale composition. Using the remote sensing (RS and GIS techniques we manage to extract a sequence of built-up areas (from 1980 to 2012 and used the result as an input for modelling the spatialtemporal changes of urban expansion and fractal theory to analysed the geometric features. Taking the time as a parameter we can observe behaviour and changes in urban landscape, this condition have been known as self-organized – a condition which in first stage the system was without any turbulence (before the antropic factor and during the time tend to approach chaotic behaviour (entropy state without causing an disequilibrium in the main system.
Many agricultural applications require spatially distributed information on growth-related crop characteristics that could be supplied through aircraft or satellite remote sensing. A study was conducted to develop and test a methodology for estimating plant canopy ground cover for cotton (Gossypium hirsutum L.) from scene reflectance. Previous studies indicated that a relatively simple relationship between ground cover and scene reflectance could be developed based on linear mixture modeling. Theoretical analysis indicated that the effects of shadows in the scene could be compensated for by averaging the results obtained using scene reflectance in the red and near-infrared wavelengths. The methodology was tested using field data collected over several years from cotton test plots in Texas and California. Results of the study appear to verify the utility of this approach. Since the methodology relies on information that can be obtained solely through remote sensing, it would be particularly useful in applications where other field information, such as plant size, row spacing, and row orientation, is unavailable
Research has centered around: (1) completion of a study on the use of remote sensing techniques as an aid to multiple use management; (2) determination of the information transfer at various image resolution levels for wildland areas; and (3) determination of the value of small scale multiband, multidate photography for the analysis of vegetation resources. In addition, a substantial effort was made to upgrade the automatic image classification and spectral signature acquisition capabilities of the laboratory. It was found that: (1) Remote sensing techniques should be useful in multiple use management to provide a first-cut analysis of an area. (2) Imagery with 400-500 feet ground resolvable distance (GRD), such as that expected from ERTS-1, should allow discriminations to be made between woody vegetation, grassland, and water bodies with approximately 80% accuracy. (3) Barley and wheat acreages in Maricopa County, Arizona could be estimated with acceptable accuracies using small scale multiband, multidate photography. Sampling errors for acreages of wheat, barley, small grains (wheat and barley combined), and all cropland were 13%, 11%, 8% and 3% respectively.
Solaimani, Karim; Habibnejad-Roshan, Mahmud
Iran's most obvious hydroclimatic problems are compounded of the disadvantages of scanty and highly seasonal precipitation and a surface configuration which tends to concentrate moisture on the periphery of the country, leaving its vast heart an area of irreconcilable sterility. Most of the central Iran has arid conditions with dry and hot summer months, when streams with and the land is parched. Nowhere in Iran is there an annual surplus of water, and significant seasonal surpluses occur in only the wishbone of high mountains that encloses the central plateau on the north and west. In most parts (about 80 percent of the total of country) the nature of human activity depends upon the availability of surface water that can be tapped by wells and qantas. Runoff is episodic and occurs only because the precipitation, meagre as it is momentarily exceeds the infiltration capability of the surface. Such precipitation is not of course capricious in terms of quantity, location and distribution in time. For more accurate investigation, remote sensing data was used to overcome the large area. Finally for arid basins, combined data from remote sensing (Cosmos and Aerial photographs) data and topography maps provided significant results.
Zhao, Jianhu; Zhou, Fengnian; Zhang, Hongmei; Li, Juanjuan
In large-scope marine investigation, the traditional bathymetric measurement can not meet the requirement of rapid data acquisition with lower cost of financial and material resources, while remote sensing (RS) technology provides a perfect way in the work. RS can not only provide quickly and efficiently the information of underwater topography with respect to the traditional method, but also present corresponding underwater topography with different-period RS images. In this paper, we depict in detail the procedures and some key techniques in acquiring underwater topography by remote sensing inversion technology based on self-organization feature mapping (SOFM). Firstly, we introduce some basic theories about the acquisition of underwater topography by the RS inversion technology. Besides, we discuss the data acquisition and preparation in the work. Moreover, we implement correlation analysis and find out the sensitive bands used for building RS inversion model. In virtue of SOFM, we construct the mapping relation between water depth and the reflectivity of sensitive band in the studied area, and test the it in two experimental water areas. The model achieves satisfying accuracy and can meet the requirement of given bathymetric scale. Finally the mapping relation is used for the water depth inversion in the studied water area. We also use the water depth from the model to draw the underwater topographic map in the water area.
Policelli, Frederick S.
The United Nations University (UNU) estimates that floods presently impacts greater than 520 million people per year worldwide, resulting in up to 25,000 annual deaths, extensive homelessness, disaster-induced disease, crop and livestock damage, famine, and other serious harm. Meanwhile, aid agencies such as the International Federation of Red Cross and Red Crescent Societies (IFRC) are increasingly seeking better information concerning flood hazards in order to plan for and help mitigate the effects of damaging floods. There is fertile ground to continue development of better remote sensing and modeling techniques to help manage flood related disasters. Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid flood mapping and distribution, and e) validation of flood forecasting and detection products.
Full Text Available This paper aims to introduce the main types and sources of remotely sensed data that are freely available and have cryospheric applications. We describe aerial and satellite photography, satellite-borne visible, near-infrared and thermal infrared sensors, synthetic aperture radar, passive microwave imagers and active microwave scatterometers. We consider the availability and practical utility of archival data, dating back in some cases to the 1920s for aerial photography and the 1960s for satellite imagery, the data that are being collected today and the prospects for future data collection; in all cases, with a focus on data that are openly accessible. Derived data products are increasingly available, and we give examples of such products of particular value in polar and cryospheric research. We also discuss the availability and applicability of free and, where possible, open-source software tools for reading and processing remotely sensed data. The paper concludes with a discussion of open data access within polar and cryospheric sciences, considering trends in data discoverability, access, sharing and use.
Full Text Available The classes in fuzzy classification schemes are defined as fuzzy sets, partitioning the feature space through fuzzy rules, defined by fuzzy membership functions. Applying fuzzy classification schemes in remote sensing allows each pixel or segment to be an incomplete member of more than one class simultaneously, i.e., one that does not fully meet all of the classification criteria for any one of the classes and is member of more than one class simultaneously. This can lead to fuzzy, ambiguous and uncertain class assignation, which is unacceptable for many applications, indicating the need for a reliable defuzzification method. Defuzzification in remote sensing has to date, been performed by “crisp-assigning” each fuzzy-classified pixel or segment to the class for which it best fulfills the fuzzy classification rules, regardless of its classification fuzziness, uncertainty or ambiguity (maximum method. The defuzzification of an uncertain or ambiguous fuzzy classification leads to a more or less reliable crisp classification. In this paper the most common parameters for expressing classification uncertainty, fuzziness and ambiguity are analysed and discussed in terms of their ability to express the reliability of a crisp classification. This is done by means of a typical practical example from Object Based Image Analysis (OBIA.
Morales-Alvarez, Pablo; Perez-Suay, Adrian; Molina, Rafael; Camps-Valls, Gustau
Current remote sensing image classification problems have to deal with an unprecedented amount of heterogeneous and complex data sources. Upcoming missions will soon provide large data streams that will make land cover/use classification difficult. Machine learning classifiers can help at this, and many methods are currently available. A popular kernel classifier is the Gaussian process classifier (GPC), since it approaches the classification problem with a solid probabilistic treatment, thus yielding confidence intervals for the predictions as well as very competitive results to state-of-the-art neural networks and support vector machines. However, its computational cost is prohibitive for large scale applications, and constitutes the main obstacle precluding wide adoption. This paper tackles this problem by introducing two novel efficient methodologies for Gaussian Process (GP) classification. We first include the standard random Fourier features approximation into GPC, which largely decreases its computational cost and permits large scale remote sensing image classification. In addition, we propose a model which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones within a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery and infrared sounding data. Excellent empirical results support the proposal in both computational cost and accuracy.
Ben Ticha, M.B.
Wind energy is a component of an energy policy contributing to a sustainable development. Last years, offshore wind parks have been installed offshore. These parks benefit from higher wind speeds and lower turbulence than onshore. To sit a wind park, it is necessary to have a mapping of wind resource. These maps are needed at high spatial resolution to show wind energy resource variations at the scale of a wind park. Wind resource mapping is achieved through the description of the spatial variations of statistical parameters characterizing wind climatology. For a precise estimation of these statistical parameters, high temporal resolution wind speed and direction measurements are needed. However, presently, there is no data source allying high spatial resolution and high temporal resolution. We propose a data fusion method taking advantage of the high spatial resolution of some remote sensing instruments (synthetic aperture radars) and the high temporal resolution of other remote sensing instruments (scatterometers). The data fusion method is applied to a case study and the results quality is assessed. The results show the pertinence of data fusion for the mapping of wind energy resource offshore. (author)
Karagianni, Aikaterini Ch.; Lazaridou, Maria A.
Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.
Full Text Available The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.
Pohl, C.; Moellmann, J.; Fries, K.
The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.
Agnes Jane Soto Gómez
Full Text Available This study used remotely sensed maps of nightlights to investigate the etiology of increasing disaster losses from hydrometeorological hazards in a data-scarce area. We explored trends in the probability of occurrence of hazardous events (extreme rainfall and exposure of the local population as components of risk. The temporal variation of the spatial distribution of exposure to hydrometeorological hazards was studied using nightlight satellite imagery as a proxy. Temporal (yearly and spatial (1 km resolution make them more useful than official census data. Additionally, satellite nightlights can track informal (unofficial human settlements. The study focused on the Samala River catchment in Guatemala. The analyses of disasters, using DesInventar Disaster Information Management System data, showed that fatalities caused by hydrometeorological events have increased. Such an increase in disaster losses can be explained by trends in both: (i catchment conditions that tend to lead to more frequent hydrometeorological extremes (more frequent occurrence of days with wet conditions; and (ii increasing human exposure to hazardous events (as observed by amount and intensity of nightlights in areas close to rivers. Our study shows the value of remote sensing data and provides a framework to explore the dynamics of disaster risk when ground data are spatially and temporally limited.
Purkis, Sam J.
Carbonate precipitation has been a common life strategy for marine organisms for 3.7 billion years, as, therefore, has their construction of reefs. As favored by modern corals, reef-forming organisms have typically adopted a niche in warm, shallow, well-lit, tropical marine waters, where they are capable of building vast carbonate edifices. Because fossil reefs form water aquifers and hydrocarbon reservoirs, considerable effort has been dedicated to understanding their anatomy and morphology. Remote sensing has a particular role to play here. Interpretation of satellite images has done much to reveal the grand spatial and temporal tapestry of tropical reefs. Comparative sedimentology, whereby modern environments are contrasted with the rock record to improve interpretation, has been particularly transformed by observations made from orbit. Satellite mapping has also become a keystone technology to quantify the coral reef crisis—it can be deployed not only directly to quantify the distribution of coral communities, but also indirectly to establish a climatology for their physical environment. This article reviews the application of remote sensing to tropical coralgal reefs in order to communicate how this fast-growing technology might be central to addressing the coral reef crisis and to look ahead at future developments in the science.
Full Text Available Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.
Xu, Dandan; Guo, Xulin
Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.
Gabor Gyula Julius Szakács
Full Text Available The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI measured in the field (LAIfield and derived by satellite (LAIsatellite as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+ sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804 and LAIsatellite (R² = 0.9812 was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.
Ardanuy, Philip E.; Powell, Dylan C.; Marley, Stephen
In modern horror fiction, zombies are generally undead corpses brought back from the dead by supernatural or scientific means, and are rarely under anyone's direct control. They typically have very limited intelligence, and hunger for the flesh of the living . Typical spectroradiometric or hyperspectral instruments providess calibrated radiances for a number of remote sensing algorithms. The algorithms typically must meet specified latency and availability requirements while yielding products at the required quality. These systems, whether research, operational, or a hybrid, are typically cost constrained. Complexity of the algorithms can be high, and may evolve and mature over time as sensor characterization changes, product validation occurs, and areas of scientific basis improvement are identified and completed. This suggests the need for a systems engineering process for algorithm maintenance that is agile, cost efficient, repeatable, and predictable. Experience on remote sensing science data systems suggests the benefits of "plug-n-play" concepts of operation. The concept, while intuitively simple, can be challenging to implement in practice. The use of zombie algorithms-empty shells that outwardly resemble the form, fit, and function of a "complete" algorithm without the implemented theoretical basis-provides the ground systems advantages equivalent to those obtained by integrating sensor engineering models onto the spacecraft bus. Combined with a mature, repeatable process for incorporating the theoretical basis, or scientific core, into the "head" of the zombie algorithm, along with associated scripting and registration, provides an easy "on ramp" for the rapid and low-risk integration of scientific applications into operational systems.
Full Text Available Image registration is an important operation in many remote sensing applications and it, besides other tasks, involves the identification of corresponding control points in the images. As manual identification of control points may be time-consuming and tiring, several automatic techniques have been developed. This paper describes a system for automatic registration and mosaic of remote sensing images under development at The National Institute for Space Research (INPE and at The University of California, Santa Barbara (UCSB. The user can provide information to the system in order to speed up the registration process as well as to avoid mismatched control points. Based on statistical procedure, the system gives an indication of the registration quality. This allows users to stop the processing, to modify the registration parameters or to continue the processing. Extensive system tests have been performed with different types of data (optical, radar, multi-sensor, high-resolution images and video sequences in order to check the system performance. An online demo system is available on the internet ( which contains several examples that can be carried out using web browser.
Tang, Chia-Hsi; Coull, Brent A.; Schwartz, Joel; Lyapustin, Alexei I.; Di, Qian; Koutrakis, Petros
Information regarding the magnitude and distribution of PM(sub 2.5) emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially-resolved emission inventories for PM(sub 2.5). This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeast United States during the period of 2002-2013 using high- resolution 1 km x 1 km Aerosol Optical Depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R(sup2) = 0.66 approx. 0.71, CV = 17.7 approx. 20%). Predicted emissions are found to correlate with land use parameters suggesting that our method can capture emissions from land use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively.
Purkis, Sam J
Carbonate precipitation has been a common life strategy for marine organisms for 3.7 billion years, as, therefore, has their construction of reefs. As favored by modern corals, reef-forming organisms have typically adopted a niche in warm, shallow, well-lit, tropical marine waters, where they are capable of building vast carbonate edifices. Because fossil reefs form water aquifers and hydrocarbon reservoirs, considerable effort has been dedicated to understanding their anatomy and morphology. Remote sensing has a particular role to play here. Interpretation of satellite images has done much to reveal the grand spatial and temporal tapestry of tropical reefs. Comparative sedimentology, whereby modern environments are contrasted with the rock record to improve interpretation, has been particularly transformed by observations made from orbit. Satellite mapping has also become a keystone technology to quantify the coral reef crisis-it can be deployed not only directly to quantify the distribution of coral communities, but also indirectly to establish a climatology for their physical environment. This article reviews the application of remote sensing to tropical coralgal reefs in order to communicate how this fast-growing technology might be central to addressing the coral reef crisis and to look ahead at future developments in the science.
Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.
Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.
M. V. Tinin
Full Text Available We have used numerical simulation to study the effects of ionospheric irregularities on accuracy of global navigation satellite system (GNSS measurements, using ionosphere-free (in atmospheric research and geometry-free (in ionospheric research dual-frequency phase combinations. It is known that elimination of these effects from multifrequency GNSS measurements is handi-capped by diffraction effects during signal propagation through turbulent ionospheric plasma with the inner scale being smaller than the Fresnel radius. We demonstrated the possibility of reducing the residual ionospheric error in dual-frequency GNSS remote sensing in ionosphere-free combination by Fresnel inversion. The inversion parameter, the distance to the virtual screen, may be selected from the minimum of amplitude fluctuations. This suggests the possibility of improving the accuracy of GNSS remote sensing in meteorology. In the study of ionospheric disturbances with the aid of geometry-free combination, the Fresnel inversion eliminates only the third-order error. To eliminate the random TEC component which, like the measured average TEC, is the first-order correction, we should use temporal filtering (averaging.
Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering carbon cycling and climate. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the nighttime light remote sensing data, extended this method to the global domain by developing a computational method (parameterization) to estimate the key parameters in the cluster-based method, and built a consistent 20-year global urban map series to evaluate the time-reactive nature of global urbanization (e.g. 2000 in Fig. 1). Supported by urban maps derived from nightlights remote sensing data and socio-economic drivers, we developed an integrated modeling framework to project future urban expansion by integrating a top-down macro-scale statistical model with a bottom-up urban growth model. With the models calibrated and validated using historical data, we explored urban growth at the grid level (1-km) over the next two decades under a number of socio-economic scenarios. The derived spatiotemporal information of historical and potential future urbanization will be of great value with practical implications for developing adaptation and risk management measures for urban infrastructure, transportation, energy, and water systems when considered together with other factors such as climate variability and change, and high impact weather events.
Sandlerskiy, Robert; Puzachenko, Yurii
key words: ecosystem thermodynamic, energy balance, exergy, Transformation of matter and energy in plant associations and their relationship with other parts of the ecosystem are being determined by the physiological processes in plants. Accordingly, to identify general patterns of ecosystem energy transformation, assessment of an energy balance components reflecting the nature of physiological processes: photosynthesis, transpiration (of which carbon balance is evaluated), water and minerals exchange, is required. Assessment of the main energy variables for ecosystems is possible on the basis of information-thermodynamic approach in which the ecosystem - is an open system, producing yield for self-maintenance on its structure through the conversion of solar energy. In doing so, the distribution of energy absorbed by balance components depends on the structure of the system that determines the nonequilibrium energy conversion. In the information-thermodynamic approach essential component in the transformation of solar energy is exergy - the maximum work that a thermodynamic system may commit during its transition from the current state to the state of equilibrium with the environment. Exergy sometimes called system yield, it is the function of the distance between the current state of the system and thermodynamic equilibrium. Relating to ecosystems, exergy - part of absorbed solar energy, spend on biological productivity and evapotranspiration (exergy of solar radiation). The rest goes into the bound energy - energy transition in the heat flow and entropy, and in increment of internal energy - system energy accumulation wich in its turn spend on maintenance of intercomponent and interspecific interactions, local cycles. Get estimation of energy balance for the entire set of ecosystems based on ground-based measurements is virtually impossible. Such assessments are possible on the basis of remote sensing data, which show the energetic state of the Earth's surface at
Smolka, Anselm; Siebert, Andreas
The insurance sector is faced with two issues regarding earthquake risk: the estimation of rarely occurring losses from large events and the assessment of the average annual net loss. For this purpose, knowledge is needed of actual event losses, of the distribution of exposed values, and of their vulnerability to earthquakes. To what extent can remote sensing help the insurance industry fulfil these tasks, and what are its limitations? In consequence of more regular and high-resolution satellite coverage, we have seen earth observation and remote sensing methods develop over the past years to a stage where they appear to offer great potential for addressing some shortcomings of the data underlying risk assessment. These include lack of statistical representativeness and lack of topicality. Here, remote sensing can help in the following areas: • Inventories of exposed objects (pre- and post-disaster) • Projection of small-scale ground-based vulnerability classification surveys to a full inventory • Post-event loss assessment But especially from an insurance point of view, challenges remain. The strength of airborne remote sensing techniques lies in outlining heavily damaged areas where damage is caused by easily discernible structural failure, i.e. total or partial building collapse. Examples are the Haiti earthquake (with minimal insured loss) and the tsunami-stricken areas in the Tohoku district of Japan. What counts for insurers, however, is the sum of monetary losses. The Chile, the Christchurch and the Tohoku earthquakes each caused insured losses in the two-digit billion dollar range. By far the greatest proportion of these insured losses were due to non-structural damage to buildings, machinery and equipment. Even with the Tohoku event, no more than 30% of the total material damage was caused by the tsunami according to preliminary surveys, and this figure includes damage due to earthquake shock which was unrecognisable after the passage of the tsunami
Gillison, Andrew N; Asner, Gregory P; Fernandes, Erick C M; Mafalacusser, Jacinto; Banze, Aurélio; Izidine, Samira; da Fonseca, Ambrósio R; Pacate, Hermenegildo
Sustainable biodiversity and land management require a cost-effective means of forecasting landscape response to environmental change. Conventional species-based, regional biodiversity assessments are rarely adequate for policy planning and decision making. We show how new ground and remotely-sensed survey methods can be coordinated to help elucidate and predict relationships between biodiversity, land use and soil properties along complex biophysical gradients that typify many similar landscapes worldwide. In the lower Zambezi valley, Mozambique we used environmental, gradient-directed transects (gradsects) to sample vascular plant species, plant functional types, vegetation structure, soil properties and land-use characteristics. Soil fertility indices were derived using novel multidimensional scaling of soil properties. To facilitate spatial analysis, we applied a probabilistic remote sensing approach, analyzing Landsat 7 satellite imagery to map photosynthetically active and inactive vegetation and bare soil along each gradsect. Despite the relatively low sample number, we found highly significant correlations between single and combined sets of specific plant, soil and remotely sensed variables that permitted testable spatial projections of biodiversity and soil fertility across the regional land-use mosaic. This integrative and rapid approach provides a low-cost, high-return and readily transferable methodology that permits the ready identification of testable biodiversity indicators for adaptive management of biodiversity and potential agricultural productivity. Copyright © 2016 Elsevier Ltd. All rights reserved.
Vasiljevic, N.; Lea, G.; Courtney, M. [Technical Univ. of Denmark. DTU Wind Energy, DTU Risoe Campus, Roskilde (Denmark); Schneemann, J.; Trabucchi, D.; Trujillo, J.-J.; Unguran, R.; Villa, J.-P. [Univ. of Oldenburg, ForWind, Oldenburg (Germany)
The following document establishes the Remote Sensing Communication Protocol (RSComPro) to be implemented by remote sensing systems (RS system) connecting to a network coordinated by a single Master system. The implementation of the RSComPro enables a full subordination of a RS system to a Master system. The last has as main task to control and synchronize measurement activities by all RS systems in the network. In this respect the RSComPro specifies data flow rules and formal characteristics of exchanged messages. The first version of this protocol is the outcome of the collective work between DTU Wind Energy and ForWind University of Oldenburg. It has been developed in initially for application in wind measurement by means of WindScanners (synchronized multiple lidar systems). However, it could be extended to be applied on any other type of scanning remote sensing system. Its implementation has been tested initially on systems of type WLS200S from the company Leosphere at both institutes. The objective of this protocol is to define: 1) Basic details of the software running on the RS system and the Master system; 2) Basic details of the network model; 3) Specification of handshaking process; 4) Basic details of error handling; 5) Specification of message format and syntax. (Author)
Full Text Available Remote sensing provides rich sources of data for the monitoring of land surface dynamics. However, single-sensor systems are constrained from providing spatially high-resolution images with high revisit frequency due to the inherent sensor design limitation. To obtain images high in both spatial and temporal resolutions, a number of image fusion algorithms, such as spatial and temporal adaptive reflectance fusion model (STARFM and enhanced STARFM (ESTARFM, have been recently developed. To capitalize on information available in a fusion process, we propose a Bayesian data fusion approach that incorporates the temporal correlation information in the image time series and casts the fusion problem as an estimation problem in which the fused image is obtained by the Maximum A Posterior (MAP estimator. The proposed approach provides a formal framework for the fusion of remotely sensed images with a rigorous statistical basis; it imposes no requirements on the number of input image pairs; and it is suitable for heterogeneous landscapes. The approach is empirically tested with both simulated and real-life acquired Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS images. Experimental results demonstrate that the proposed method outperforms STARFM and ESTARFM, especially for heterogeneous landscapes. It produces surface reflectances highly correlated with those of the reference Landsat images. It gives spatio-temporal fusion of remotely sensed images a solid theoretical and empirical foundation that may be extended to solve more complicated image fusion problems.
National Aeronautics and Space Administration — Remotely sensed Earth Science datasets are characterized by their complexity and size, which results in difficulty in effectively disseminating this information to...
Gao, F.; Anderson, M. C.
Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate
Fiorucci, Federica; Giordan, Daniele; Santangelo, Michele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto
Landslides leave discernible signs on the land surface, most of which can be captured in remote sensing images. Trained geomorphologists analyse remote sensing images and map landslides through heuristic interpretation of photographic and morphological characteristics. Despite a wide use of remote sensing images for landslide mapping, no attempt to evaluate how the image characteristics influence landslide identification and mapping exists. This paper presents an experiment to determine the effects of optical image characteristics, such as spatial resolution, spectral content and image type (monoscopic or stereoscopic), on landslide mapping. We considered eight maps of the same landslide in central Italy: (i) six maps obtained through expert heuristic visual interpretation of remote sensing images, (ii) one map through a reconnaissance field survey, and (iii) one map obtained through a real-time kinematic (RTK) differential global positioning system (dGPS) survey, which served as a benchmark. The eight maps were compared pairwise and to a benchmark. The mismatch between each map pair was quantified by the error index, E. Results show that the map closest to the benchmark delineation of the landslide was obtained using the higher resolution image, where the landslide signature was primarily photographical (in the landslide source and transport area). Conversely, where the landslide signature was mainly morphological (in the landslide deposit) the best mapping result was obtained using the stereoscopic images. Albeit conducted on a single landslide, the experiment results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.
Full Text Available sensing in savannah ecosystems is that these areas are characterised by heterogeneity in edaphic, topographic and climatic factors. The objective is to test the utility of integrating environmental variables and in situ hyperspectral remote sensing...
Shuxin, Li; Zhilong, Zhang; Biao, Li
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.
Kim, Edward J.; Cline, Don; Davis, Bert; Hildebrand, Peter H. (Technical Monitor)
The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. The CLPX Plan has been developed through the efforts of over 60 interested scientists that have participated in the NASA Cold Land Processes Working Group (CLPWG). This group is charged with the task of assessing, planning and implementing the required background science, technology, and application infrastructure to support successful land surface hydrology remote sensing space missions. A major product of the experiment will be a comprehensive, legacy data set that will energize many aspects of cold land processes research. The CLPX will focus on developing the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment will particularly emphasize developing a strong synergism between process
Full Text Available The disposal of the solid wastes in landfill sites should be properly monitored by analyzing samples from soil, water, and landfill gases within the landfill site. Nevertheless, ground monitoring systems require intensive efforts and cost. Furthermore, ground monitoring may be difficult to be achieved in large geographic extent. Remote sensing technology has been introduced for waste disposal management and monitoring effects of the landfill sites on the environment. In this paper, two case studies are presented in the Trail Road landfill, Ottawa, Canada and the Al-Jleeb landfill, Al-Farwanyah, Kuwait to evaluate the use of multi-temporal remote sensing images to monitor the landfill sites. The work objectives are: 1 to study the usability of multi-temporal Landsat images for landfill site monitoring by studying the land surface temperature (LST in the Trail Road landfill, 2 to investigate the relationship between the LST and the amount of the landfill gas emitted in the Trail Road landfill, and 3 to use the multi-temporal LST images to detect the suspicious dumping areas within the Al-Jleeb landfill site. Free archive of multi-temporal Landsat images are obtained from the USGS EarthExplorer. The Landsat images are then atmospherically corrected and the LST images are derived from the thermal band of the corrected Landsat images. In the Trail Road landfill, the results reveal that the LST of the landfill site is always higher than the air temperature by 10°C in average as well as the surroundings. A correlation is also observed between the recorded emitted methane (CH4 from the ground monitoring stations and the LST derived from the Landsat images. Based on the findings in the Al-Jleeb landfill, five locations are identified as suspicious dumping areas by overlaying the highest LST contours generated from the multi-temporal LST images. The study demonstrates that the use of multi-temporal remote sensing images can provide supplementary