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
McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart
Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.
Full Text Available coastal resources and anthropogenic infrastructure for a safer future. What is the role of remote sensing? The coastal zone connects terrestrial biophysical systems with marine systems. Some marine ecosystems cannot function without intact inland... for the development of sound integrated management solutions. To date, however, remote sensing applications usually focus on areas landward from the highwater line (?terrestrial? remote sensing), while ?marine? remote sensing does not pay attention to the shallow...
Khorram, Siamak; Koch, Frank H; van der Wiele, Cynthia F
Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns. It explains the role of this new technology in current global challenges. "Remote Sensing" will discuss remotely sensed data application payloads and platforms, along with the methodologies involving image processing techniques as applied to remotely sensed data. This title provides information on image classification techniques and image registration, data integration, and data fusion techniques. How this technology applies to natural resources and environmental concerns will also be discussed.
McCarthy, Tim; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart
Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North...
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.
Remote RemoteRemoteRemote sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing p. A Ngie, F Ahmed, K Abutaleb ...
The application of GMM to remote sensing image classification ... A . The boundary that has a Mahalanobis distance to the centre ... yields the Baye's theorem: ..... bands were extracted using the layer properties tool and visualised in MATLAB ...
Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang
Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.
Campbell, W. J.; Ramseier, R. O.; Weeks, W. F.; Gloersen, P.
Review article on remote sensing applications to glaciology. Ice parameters sensed include: ice cover vs open water, ice thickness, distribution and morphology of ice formations, vertical resolution of ice thickness, ice salinity (percolation and drainage of brine; flushing of ice body with fresh water), first-year ice and multiyear ice, ice growth rate and surface heat flux, divergence of ice packs, snow cover masking ice, behavior of ice shelves, icebergs, lake ice and river ice; time changes. Sensing techniques discussed include: satellite photographic surveys, thermal IR, passive and active microwave studies, microwave radiometry, microwave scatterometry, side-looking radar, and synthetic aperture radar. Remote sensing of large aquatic mammals and operational ice forecasting are also discussed.
A remotely sensed digital image of SPOT by its linear enhancement on a large memory, high speed, and digital electronic computer revealed from false colour composite that vegetation is expressed as red. Further processing of SPOT digital image for arithmetic banding of Normalized Differential Vegetation Index (NDVI) ...
Castella, M.; Rigo, T.; Argemi, O.; Bech, J.; Pineda, N.; Vilaclara, E.
The need for advanced visualization tools for meteorological data has lead in the last years to the development of sophisticated software packages either by observing systems manufacturers or by third-party solution providers. For example, manufacturers of remote sensing systems such as weather radars or lightning detection systems include zoom, product selection, archive access capabilities, as well as quantitative tools for data analysis, as standard features which are highly appreciated in weather surveillance or post-event case study analysis. However, the fact that each manufacturer has its own visualization system and data formats hampers the usability and integration of different data sources. In this context, Google Earth (GE) offers the possibility of combining several graphical information types in a unique visualization system which can be easily accessed by users. The Meteorological Service of Catalonia (SMC) has been evaluating the use of GE as a visualization platform for surveillance tasks in adverse weather events. First experiences are related to the integration in real-time of remote sensing data: radar, lightning, and satellite. The tool shows the animation of the combined products in the last hour, giving a good picture of the meteorological situation. One of the main advantages of this product is that is easy to be installed in many computers and does not need high computational requirements. Besides this, the capability of GE provides information about the most affected areas by heavy rain or other weather phenomena. On the opposite, the main disadvantage is that the product offers only qualitative information, and quantitative data is only available though the graphical display (i.e. trough color scales but not associated to physical values that can be accessed by users easily). The procedure developed to run in real time is divided in three parts. First of all, a crontab file launches different applications, depending on the data type
Bikesh Kumar Singh
Full Text Available There is rapid increase in image databases of remote sensing images due to image satellites with high resolution, commercial applications of remote sensing & high available bandwidth in last few years. The problem of content-based image retrieval (CBIR of remotely sensed images presents a major challenge not only because of the surprisingly increasing volume of images acquired from a wide range of sensors but also because of the complexity of images themselves. In this paper, a software system for content-based retrieval of remote sensing images using RGB and HSV color spaces is presented. Further, we also compare our results with spatiogram based content retrieval which integrates spatial information along with color histogram. Experimental results show that the integration of spatial information in color improves the image analysis of remote sensing data. In general, retrievals in HSV color space showed better performance than in RGB color space.
Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea
Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.
Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad
In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R 2 , RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that
Medler, Michael Johns
Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy
Deal, William R.; Chattopadhyay, Goutam
The operating frequency of InP integrated circuits has pushed well into the Submillimeter Wave frequency band, with amplification reported as high as 670 GHz. This paper provides an overview of current performance and potential application of InP HEMT to Submillimeter Wave radiometers for earth remote sensing.
Czaja, Wojciech; Le Moigne-Stewart, Jacqueline
In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.
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
Giorgoudis, Marios D.; Hadjimitsis, Diofantos G.; Shiftan, Yoram
The main advantage of using GIS is its ability to access and analyze spatially distributed data. The applications of GIS to transportation can be viewed as involving either on data retrieval; data integrator; or data analysis. The use of remote sensing can assist the retrieval of land use changes. Indeed, the integration of GIS and remote sensing will be used to fill the gap in the smart transport planning. A four step research is going to be done in order to try to integrate the usage of GIS and remote sensing to sustainable transport planning. The proposed research will be held in the city of Limassol, Cyprus. The data that are going to be used are data that are going to be collected through questionnaires, and other available data from the Cyprus Public Works Department and from the Remote Sensing Laboratory and Geo-Environment Research Lab of the Cyprus University of Technology. Overall, statistical analysis and market segmentation of data will be done, the land usage will be examined, and a scenario building on mode choice will be held. This paper presents an overview of the methodology that will be adopted.
greatly facilitated integrated development of land and water resources on ... areas, vulnerability/risk maps for many disasters in GIS environ- ment has been ... cornerstone for the survey and management of natural resources in the country ...
Full Text Available TO INFORM INTERGRATED COASTAL ZONE MANAGEMENT GISSA Western Cape Regional Meeting Wesley Roberts & Melanie Luck-Vogel 2 June 2010 CSIR NRE Ecosystems Earth Observation Group What is Integrated Coastal Zone Management? Integrated coastal management... D1D1 B a n d 1 Band 2 Quick theory of CVA Magnitude Direction ( ) ( )22 xaxbyaybM ?+?= Quadrant 1 (++) Accretion Quadrant 2 (-+) Quadrant 4 (+-) Quadrant 3 (--) Erosion CVA Results & Conclusions ? Change in image time series...
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
Bach, H.; Appel, F.; Schulz, W.; Merkel, U.; Ludwig, R.; Mauser, W.
Methods to accurately assess and forecast flood discharge are mandatory to minimise the impact of hydrological hazards. However, existing rainfall-runoff models rarely accurately consider the spatial characteristics of the watershed, which is essential for a suitable and physics-based description of processes relevant for runoff formation. Spatial information with low temporal variability like elevation, slopes and land use can be mapped or extracted from remote sensing data. However, land surface param- eters of high temporal variability, like soil moisture and snow properties are hardly available and used in operational forecasts. Remote sensing methods can improve flood forecast by providing information on the actual water retention capacities in the watershed and facilitate the regionalisation of hydrological models. To prove and demonstrate this, the project 'InFerno' (Integration of remote sensing data in opera- tional water balance and flood forecast modelling) has been set up, funded by DLR (50EE0053). Within InFerno remote sensing data (optical and microwave) are thor- oughly processed to deliver spatially distributed parameters of snow properties and soil moisture. Especially during the onset of a flood this information is essential to estimate the initial conditions of the model. At the flood forecast centres of 'Baden- Württemberg' and 'Rheinland-Pfalz' (Southwest Germany) the remote sensing based maps on soil moisture and snow properties will be integrated in the continuously op- erated water balance and flood forecast model LARSIM. The concept is to transfer the developed methodology from the Neckar to the Mosel basin. The major challenges lie on the one hand in the implementation of algorithms developed for a multisensoral synergy and the creation of robust, operationally applicable remote sensing products. On the other hand, the operational flood forecast must be adapted to make full use of the new data sources. In the operational phase of the
Toll, D. L.; Doorn, B.; Searby, N. D.; Entin, J. K.; Lee, C. M.
This presentation will emphasize NASA's water research, applications, and capacity building activities using satellites and models to contribute to water issues including water availability, transboundary water, flooding and droughts for improved Integrated Water Resources Management (IWRM). NASA's free and open exchange of Earth data observations and products helps engage and improve integrated observation networks and enables national and multi-national regional water cycle research and applications that are especially useful in data sparse regions of most developing countries. NASA satellite and modeling products provide a huge volume of valuable data extending back over 50 years across a broad range of spatial (local to global) and temporal (hourly to decadal) scales and include many products that are available in near real time (see earthdata.nasa.gov). To further accomplish these objectives NASA works to actively partner with public and private groups (e.g. federal agencies, universities, NGO's, and industry) in the U.S. and international community to ensure the broadest use of its satellites and related information and products and to collaborate with regional end users who know the regions and their needs best. Key objectives of this talk will highlight NASA's Water Resources and Capacity Building Programs with their objective to discover and demonstrate innovative uses and practical benefits of NASA's advanced system technologies for improved water management in national and international applications. The event will help demonstrate the strong partnering and the use of satellite data to provide synoptic and repetitive spatial coverage helping water managers' deal with complex issues. The presentation will also demonstrate how NASA is a major contributor to water tasks and activities in GEOSS (Global Earth Observing System of Systems) and GEO (Group on Earth Observations).
Full Text Available In the Earth Observation sensor web environment, the rapid, accurate, and unified discovery of diverse remote sensing satellite sensors, and their association to yield an integrated solution for a comprehensive response to specific emergency tasks pose considerable challenges. In this study, we propose a remote sensing satellite sensor object model, based on the object-oriented paradigm and the Open Geospatial Consortium Sensor Model Language. The proposed model comprises a set of sensor resource objects. Each object consists of identification, state of resource attribute, and resource method. We implement the proposed attribute state description by applying it to different remote sensors. A real application, involving the observation of floods at the Yangtze River in China, is undertaken. Results indicate that the sensor inquirer can accurately discover qualified satellite sensors in an accurate and unified manner. By implementing the proposed union operation among the retrieved sensors, the inquirer can further determine how the selected sensors can collaboratively complete a specific observation requirement. Therefore, the proposed model provides a reliable foundation for sharing and integrating multiple remote sensing satellite sensors and their observations.
Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli
Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.
Full Text Available Development of efficient methodologies for mapping wetland vegetation is of key importance to wetland conservation. Here we propose the integration of a number of statistical techniques, in particular cluster analysis, universal kriging and error propagation modelling, to integrate observations from remote sensing and field sampling for mapping vegetation communities and estimating uncertainty. The approach results in seven vegetation communities with a known floral composition that can be mapped over large areas using remotely sensed data. The relationship between remotely sensed data and vegetation patterns, captured in four factorial axes, were described using multiple linear regression models. There were then used in a universal kriging procedure to reduce the mapping uncertainty. Cross-validation procedures and Monte Carlo simulations were used to quantify the uncertainty in the resulting map. Cross-validation showed that accuracy in classification varies according with the community type, as a result of sampling density and configuration. A map of uncertainty derived from Monte Carlo simulations revealed significant spatial variation in classification, but this had little impact on the proportion and arrangement of the communities observed. These results suggested that mapping improvement could be achieved by increasing the number of field observations of those communities with a scattered and small patch size distribution; or by including a larger number of digital images as explanatory variables in the model. Comparison of the resulting plant community map with a flood duration map, revealed that flooding duration is an important driver of vegetation zonation. This mapping approach is able to integrate field point data and high-resolution remote-sensing images, providing a new basis to map wetland vegetation and allow its future application in habitat management, conservation assessment and long-term ecological monitoring in wetland
Zhao, Zhenzhen; Yan, Qin; Liu, Zhengjun; Luo, Chengfeng
Following a comprehensive literature review, this paper looks at analysis of geohazard using remote sensing information. This paper compares the basic types and methods of change detection, explores the basic principle of common methods and makes an respective analysis of the characteristics and shortcomings of the commonly used methods in the application of geohazard. Using the earthquake in JieGu as a case study, this paper proposes a geohazard change detection method integrating RS and GIS. When detecting the pre-earthquake and post-earthquake remote sensing images at different phases, it is crucial to set an appropriate threshold. The method adopts a self-adapting determination algorithm for threshold. We select a training region which is obtained after pixel information comparison and set a threshold value. The threshold value separates the changed pixel maximum. Then we apply the threshold value to the entire image, which could also make change detection accuracy maximum. Finally, we output the result to the GIS system to make change analysis. The experimental results show that this method of geohazard change detection based on integrating remote sensing and GIS information has higher accuracy with obvious advantages compared with the traditional methods
Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.
The Integrated Remote Sensing and Visualization System (IRSV) is being designed to accommodate the needs of todays Bridge : Engineers at the state and local level from the following aspects: : Better understanding and enforcement of a complex ...
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
remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and
Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna
'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).
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...
Full Text Available Recently, many researchers have been dedicated to using convolutional neural networks (CNNs to extract global-context features (GCFs for remote-sensing scene classification. Commonly, accurate classification of scenes requires knowledge about both the global context and local objects. However, unlike the natural images in which the objects cover most of the image, objects in remote-sensing images are generally small and decentralized. Thus, it is hard for vanilla CNNs to focus on both global context and small local objects. To address this issue, this paper proposes a novel end-to-end CNN by integrating the GCFs and local-object-level features (LOFs. The proposed network includes two branches, the local object branch (LOB and global semantic branch (GSB, which are used to generate the LOFs and GCFs, respectively. Then, the concatenation of features extracted from the two branches allows our method to be more discriminative in scene classification. Three challenging benchmark remote-sensing datasets were extensively experimented on; the proposed approach outperformed the existing scene classification methods and achieved state-of-the-art results for all three datasets.
Hill, Bradley; Nash, Greg; Ridd, Merrill; Hauff, Phoebe L.; Ebel, Phil
The Cuprite mining district in southwestern Nevada has become a test site for remote sensing studies with numerous airborne scanners and ground sensor data sets collected over the past fifteen years. Structurally, the Cuprite region can be divided into two areas with slightly different alteration and mineralogy. These zones lie on either side of a postulated low-angle structural discontinuity that strikes nearly parallel to US Route 95. Hydrothermal alternation at Cuprite was classified into three major zones: silicified, opalized, and argillized. These alteration types form a bulls-eye pattern east of the highway and are more linear on the west side of the highway making a striking contrast from the air and the imagery. Cuprite is therefore an ideal location for remote sensing research as it exhibits easily identified hydrothermal zoning, is relatively devoid of vegetation, and contains a distinctive spectrally diagnostic mineral suite including the ammonium feldspar buddingtonite, several types of alunite, different jarosites, illite, kaolinite, smectite, dickite, and opal. This present study brings a new dimension to these previous remote sensing and ground data sets compiled for Cuprite. The development of a higher resolution field spectrometer now provides the capability to combine extensive in-situ mineralogical data with a new geologic field survey and detailed Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) images. The various data collection methods and the refinement of the integrated techniques are discussed.
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.
Krause, Keith Stuart
The change, reduction, or extinction of species is a major issue currently facing the Earth. Efforts are underway to measure, monitor, and protect habitats that contain high species diversity. Remote sensing technology shows extreme value for monitoring species diversity by mapping ecosystems and using those land cover maps or other derived data as proxies to species number and distribution. The National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) consists of remote sensing instruments such as an imaging spectrometer, a full-waveform lidar, and a high-resolution color camera. AOP collected data over the Ordway-Swisher Biological Station (OSBS) in May 2014. A majority of the OSBS site is covered by the Sandhill ecosystem, which contains a very high diversity of vegetation species and is a native habitat for several threatened fauna species. The research presented here investigates ways to analyze the AOP data to map ecosystems at the OSBS site. The research attempts to leverage the high spatial resolution data and study the variability of the data within a ground plot scale along with integrating data from the different sensors. Mathematical features are derived from the data and brought into a decision tree classification algorithm (rpart), in order to create an ecosystem map for the site. The hyperspectral and lidar features serve as proxies for chemical, functional, and structural differences in the vegetation types for each of the ecosystems. K-folds cross validation shows a training accuracy of 91%, a validation accuracy of 78%, and a 66% accuracy using independent ground validation. The results presented here represent an important contribution to utilizing integrated hyperspectral and lidar remote sensing data for ecosystem mapping, by relating the spatial variability of the data within a ground plot scale to a collection of vegetation types that make up a given ecosystem.
Sussman, A. J.; Macleod, G.; Labak, P.; Malich, G.; Rowlands, A. P.; Craven, J.; Sweeney, J. J.; Chiappini, M.; Tuckwell, G.; Sankey, P.
The Integrated Field Exercise of 2014 (IFE14) was an event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of an on-site inspection (OSI) within the CTBT verification regime. During an OSI, up to 40 international inspectors will search an area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of a real OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams (which executed the scenario in which the exercise was played) and those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test and integrate Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, suites of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, in addition to other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection using other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials, and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of the goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.
Full Text Available For mapping, quantifying and monitoring regional and global forest health, satellite remote sensing provides fundamental data for the observation of spatial and temporal forest patterns and processes. While new remote-sensing technologies are able to detect forest data in high quality and large quantity, operational applications are still limited by deficits of in situ verification. In situ sampling data as input is required in order to add value to physical imaging remote sensing observations and possibilities to interlink the forest health assessment with biotic and abiotic factors. Numerous methods on how to link remote sensing and in situ data have been presented in the scientific literature using e.g. empirical and physical-based models. In situ data differs in type, quality and quantity between case studies. The irregular subsets of in situ data availability limit the exploitation of available satellite remote sensing data. To achieve a broad implementation of satellite remote sensing data in forest monitoring and management, a standardization of in situ data, workflows and products is essential and necessary for user acceptance. The key focus of the review is a discussion of concept and is designed to bridge gaps of understanding between forestry and remote sensing science community. Methodological approaches for in situ/remote-sensing implementation are organized and evaluated with respect to qualifying for forest monitoring. Research gaps and recommendations for standardization of remote-sensing based products are discussed. Concluding the importance of outstanding organizational work to provide a legally accepted framework for new information products in forestry are highlighted.
Lauer, D.T.; Estes, J.E.; Jensen, J.R.; Greenlee, D.D.
The developers as well as the users of remotely sensed data and geographic information system (GIS) techniques are associated with nearly all types of institutions in government, industry, and academia. Individuals in these various institutions often find the barriers to accepting remote sensing and GIS are not necessarily technical in nature, but can be attributed to the institutions themselves. Several major institutional issues that affect the technologies of remote sensing and GIS are data availability, data marketing and costs, equipment availability and costs, standards and practices, education and training, and organizational infrastructures. Not only are problems associated with these issues identified, but needs and opportunities also are discussed. -from Authors
Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin
Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a “black box” and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users. PMID:24901016
Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin
Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a "black box" and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users.
Meyer, F. J.; Webley, P.; Dehn, J.; Arko, S. A.; McAlpin, D. B.
Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing techniques have become established in operational forecasting, monitoring, and managing of volcanic hazards. Monitoring organizations, like the Alaska Volcano Observatory (AVO), are nowadays heavily relying on remote sensing data from a variety of optical and thermal sensors to provide time-critical hazard information. Despite the high utilization of these remote sensing data to detect and monitor volcanic eruptions, the presence of clouds and a dependence on solar illumination often limit their impact on decision making processes. Synthetic Aperture Radar (SAR) systems are widely believed to be superior to optical sensors in operational monitoring situations, due to the weather and illumination independence of their observations and the sensitivity of SAR to surface changes and deformation. Despite these benefits, the contributions of SAR to operational volcano monitoring have been limited in the past due to (1) high SAR data costs, (2) traditionally long data processing times, and (3) the low temporal sampling frequencies inherent to most SAR systems. In this study, we present improved data access, data processing, and data integration techniques that mitigate some of the above mentioned limitations and allow, for the first time, a meaningful integration of SAR into operational volcano monitoring systems. We will introduce a new database interface that was developed in cooperation with the Alaska Satellite Facility (ASF) and allows for rapid and seamless data access to all of ASF's SAR data holdings. We will also present processing techniques that improve the temporal frequency with which hazard-related products can be produced. These techniques take advantage of modern signal processing technology as well as new radiometric normalization schemes, both enabling the combination of
Ainullotfi, A A; Ibrahim, A L; Masron, T
This study is conducted to establish a community based flood management system that is integrated with remote sensing technique. To understand local knowledge, the demographic of the local society is obtained by using the survey approach. The local authorities are approached first to obtain information regarding the society in the study areas such as the population, the gender and the tabulation of settlement. The information about age, religion, ethnic, occupation, years of experience facing flood in the area, are recorded to understand more on how the local knowledge emerges. Then geographic data is obtained such as rainfall data, land use, land elevation, river discharge data. This information is used to establish a hydrological model of flood in the study area. Analysis were made from the survey approach to understand the pattern of society and how they react to floods while the analysis of geographic data is used to analyse the water extent and damage done by the flood. The final result of this research is to produce a flood mitigation method with a community based framework in the state of Kelantan. With the flood mitigation that involves the community's understanding towards flood also the techniques to forecast heavy rainfall and flood occurrence using remote sensing, it is hope that it could reduce the casualties and damage that might cause to the society and infrastructures in the study area
Full Text Available Traditional smallholder farming systems dominate the savanna range countries of sub-Saharan Africa and provide the foundation for the region’s food security. Despite continued expansion of smallholder farming into the surrounding savanna landscapes, food insecurity in the region persists. Central to the monitoring of food security in these countries, and to understanding the processes behind it, are reliable, high-quality datasets of cultivated land. Remote sensing has been frequently used for this purpose but distinguishing crops under certain stages of growth from savanna woodlands has remained a major challenge. Yet, crop production in dryland ecosystems is most vulnerable to seasonal climate variability, amplifying the need for high quality products showing the distribution and extent of cropland. The key objective in this analysis is the development of a classification protocol for African savanna landscapes, emphasizing the delineation of cropland. We integrate remote sensing techniques with probabilistic modeling into an innovative workflow. We present summary results for this methodology applied to a land cover classification of Zambia’s Southern Province. Five primary land cover categories are classified for the study area, producing an overall map accuracy of 88.18%. Omission error within the cropland class is 12.11% and commission error 9.76%.
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.
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...
This volume introduces several applications of remote bridge inspection technologies studied in : this Integrated Remote Sensing and Visualization (IRSV) study using ground-based LiDAR : systems. In particular, the application of terrestrial LiDAR fo...
Full Text Available A majority of secondary science teachers are found to include the topic of climate change in their courses. However, teachers informally and sporadically discuss climate change and students rarely understand the underlying scientific concepts. The project team developed an innovative pedagogical approach, in which teachers and students learn climate change concepts by analyzing National Aeronautics and Space Administration (NASA global data collected through satellites and by imitating the NASA data collection process through NASA Airborne Earth Research Observation Kites And Tethered Systems (AEROKATS, a kite-borne remote sensing system. Besides AEROKATS, other major components of this system include a web-collection of NASA and remote sensing data and related educational resources, project-based learning for teacher professional development, teacher and student field trips, iOS devices, smart field data collector apps, portable weather stations, probeware, and a virtual teacher collaboratory supported with a GIS-enabled mapping portal. Three sets of research instruments, the NASA Long-Term Experience –Educator End of Event Survey, the Teacher End of Project Survey, and the pre-and-post-Investigating Climate Change and Remote Sensing (ICCARS project student exams, are adapted to study the pedagogical impacts of the NASA AEROKATS remote sensing system. These findings confirm that climate change education is more effective when both teachers and students actively participate in authentic scientific inquiry by collecting and analyzing remote sensing data, developing hypotheses, designing experiments, sharing findings, and discussing results.
Full Text Available Rapid urbanization has resulted in great changes in rural landscapes globally. Using remote sensing data to quantify the distribution of rural settlements and their changes has received increasing attention in the past three decades, but remains a challenge. Previous studies mostly focused on the residential changes within a grid or administrative boundary, but not at the individual village level. This paper presents a new change detection approach for rural residential settlements, which can identify different types of rural settlement changes at the individual village level by integrating remote sensing and Geographic Information System (GIS analyses. Using multi-temporal Landsat TM image data, this approach classifies villages into five types: “no change”, “totally lost”, “shrinking”, “expanding”, and “merged”, in contrast to the commonly used “increase” and “decrease”. This approach was tested in the Beijing metropolitan area from 1984 to 2010. Additionally, the drivers of such changes were investigated using multinomial logistic regression models. The results revealed that: (1 36% of the villages were lost, but the total area of developed lands in existing villages increased by 34%; (2 Changes were dominated by the type of ‘expansion’ in 1984–1990 (accounted for 43.42% and 1990–2000 (56.21%. However, from 2000 to 2010, 49.73% of the villages remained unchanged; (3 Both topographical factors and distance factors had significant effects on whether the villages changed or not, but their impacts changed through time. The topographical driving factors showed decreasing effects on the loss of rural settlements, while distance factors had increasing impacts on settlement expansion and merging. This approach provides a useful tool for better understanding the changes in rural residential settlements and their associations with urbanization.
Jolliff, Brad L.; Ryder, Graham
It has been more than 25 years since Apollo 17 returned the last of the Apollo lunar samples. Since then, a vast amount of data has been obtained from the study of rocks and soils from the Apollo and Luna sample collections and, more recently, on a set of about a dozen lunar meteorites collected on Earth. Based on direct studies of the samples, many constraints have been established for the age, early differentiation, crust and mantle structure, and subsequent impact modification of the Moon. In addition, geophysical experiments at the surface, as well as remote sensing from orbit and Earth-based telescopic studies, have provided additional datasets about the Moon that constrain the nature of its surface and internal structure. Some might be tempted to say that we know all there is to know about the Moon and that it is time to move on from this simple satellite to more complex objects. However, the ongoing Lunar Prospector mission and the highly successful Clementine mission have provided important clues to the real geological complexity of the Moon, and have shown us that we still do not yet adequately understand the geologic history of Earth's companion. These missions, like Galileo during its lunar flyby, are providing global information viewed through new kinds of windows, and providing a fresh context for models of lunar origin, evolution, and resources, and perhaps even some grist for new questions and new hypotheses. The probable detection and characterization of water ice at the poles, the extreme concentration of Th and other radioactive elements in the Procellarum-Imbrium-Frigon's resurfaced areas of the nearside of the Moon, and the high-resolution gravity modeling enabled by these missions are examples of the kinds of exciting new results that must be integrated with the extant body of knowledge based on sample studies, in situ experiments, and remote-sensing missions to bring about the best possible understanding of the Moon and its history.
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
Rosen, Paul A.
This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.
Peng, Yi; Xiong, Xiong; Knadel, Maria
There is potential to use soil ·-proximal and remote sensing derived spectra concomitantly to develop soil organic carbon (SOC) models. Yet mixing spectral data from different sources and technologies to improve soil models is still in its infancy. The objective of this study was to incorporate...... soil spectral features indicative of SOC from laboratory visible near-infrared reflectance (vis-NlR) spectra and incorporate them with remote sensing (RS) images to improve predictions of top SOC in the Skjem river catchment, Denmark. The secondary objective was to improve prediction results...
Hill, Victoria J.; Matrai, Patricia A.; Olson, Elise; Suttles, S.; Steele, Mike; Codispoti, L. A.; Zimmerman, Richard C.
Recent warming of surface waters, accompanied by reduced ice thickness and extent may have significant consequences for climate-driven changes of primary production (PP) in the Arctic Ocean (AO). However, it has been difficult to obtain a robust benchmark estimate of pan-Arctic PP necessary for evaluating change. This paper provides an estimate of pan-Arctic PP prior to significant warming from a synthetic analysis of the ARCSS-PP database of in situ measurements collected from 1954 to 2007 and estimates derived from satellite-based observations from 1998 to 2007. Vertical profiles of in situ chlorophyll a (Chl a) and PP revealed persistent subsurface peaks in biomass and PP throughout the AO during most of the summer period. This was contradictory with the commonly assumed exponential decrease in PP with depth on which prior satellite-derived estimates were based. As remotely sensed Chl a was not a good predictor of integrated water column Chl a, accurate satellite-based modeling of vertically integrated primary production (IPPsat), requires knowledge of the subsurface distribution of phytoplankton, coincident with the remotely sensed ocean color measurements. We developed an alternative approach to modeling PP from satellite observations by incorporating climatological information on the depths of the euphotic zone and the mixed layer that control the distribution of phytoplankton that significantly improved the fidelity of satellite derived PP to in situ observations. The annual IPP of the Arctic Ocean combining both in situ and satellite based estimates was calculated here to be a minimum of 466 ± 94 Tg C yr-1 and a maximum of 993 ± 94 Tg C yr-1, when corrected for subsurface production. Inflow shelf seas account for 75% of annual IPP, while the central basin and Beaufort northern sea were the regions with the lowest annual integrated productivity, due to persistently stratified, oligotrophic and ice-covered conditions. Although the expansion of summertime
Chen, R. S.; Downs, R. R.; Schumacher, J.
The interdisciplinary use of data from multiple disciplines to address both research and applied problems has received increasing attention in the sciences, but understanding remains limited on the specific modalities of data use and their impact not only in enabling new research insights but also in facilitating the application of research to societal problems. In our previous work, we used citation analysis to investigate the use of data from the NASA Socioeconomic Data and Applications Center (SEDAC) and identify the extent of interdisciplinary use, based on the subject classifications of citing journals. We also proposed and tested a taxonomy of data integration and use on a selection of peer-reviewed scientific articles that cited both remote sensing data and socioeconomic data from SEDAC. We extend both of these analyses here. We analyze the interdisciplinary use of SEDAC data over a seven-year period including the types and topical areas of application observed. We also explore the degree to which different types of data integration and use are leading to further "downstream" research and applications, and if objective measures can be developed using bibliometric methods to quantify downstream use and impact in meaningful ways. These methods include both traditional citation analysis and searches of the informal literature and online resources. Better understanding of how disparate data and information has been utilized to address new interdisciplinary problems will help the data user and provider communities improve the effectiveness and efficiency of their efforts. It should also provide justification for further investments in linking different data resources and networks across scientific fields, in methods of interdisciplinary data integration, and in application of integrated data to societal problems.
Brown, Gareth [Sgurr Energy (Canada)
This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.
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...
Weiqi Zhou; Austin Troy; Morgan. Grove
This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman's Run, in Baltimore County, Maryland, USA. Parcel lawn...
Calaudi, Rosamaria; Feudo, Teresa Lo; Calidonna, Claudia Roberta
Italian coastal sites have the advantage of favorable climatic conditions to use mixed renewable energy sources, such as solar and wind. Harbors are safe places to install wind turbines where wind conditions are almost offshore. Space-borne remote sensing can provide information to determine solar...
The application of remote sensing to the study of lakes is begun in years 80 with the lunch of the satellites of second generation. Many experiences have indicated the contribution of remote sensing for the limnology [it
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...
Hyon, Jason J.
The US National Research Council (NRC) recommended that: "The U.S. government, working in concert with the private sector, academe, the public, and its international partners, should renew its investment in Earth-observing systems and restore its leadership in Earth science and applications." in response to the NASA Earth Science Division's request to prioritize research areas, observations, and notional missions to make those objectives. In this presentation, we will discuss our approach to connect remote sensing science to decision support applications by establishing a framework to integrate direct measurements, earth system models, inventories, and other information to accurately estimate fresh water resources in global, regional, and local scales. We will discuss our demonstration projects and lessons learned from the experience. Deploying a monitoring system that offers sustained, accurate, transparent and relevant information represents a challenge and opportunity to a broad community spanning earth science, water resource accounting and public policy. An introduction to some of the scientific and technical infrastructure issues associated with monitoring systems is offered here to encourage future treatment of these topics by other contributors as a concluding remark.
Garron, J.; Trainor, S.
Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill
Campbell, W.J.; Imhoff, M.L.; Robinson, J.; Gunther, F.; Boyd, R.; Anuta, M.
The utility and cost effectiveness of incorporating digitized aircraft and satellite remote sensing data into a geographic information system for facility siting and environmental impact assessments was evaluated. This research focused on the evaluation of several types of multisource remotely sensed data representing a variety of spectral band widths and spatial resolution. High resolution aircraft photography, Landsat MSS, and 7 band Thematic Mapper Simulator (TMS) data were acquired, analyzed, and evaluated for their suitability as input to an operational geographic information system (GIS). 78 references, 59 figures, 74 tables
economic development of ex-mine sites. The aim of this research is to quantify, model and map the economic potential of the ex-mine sites for built up areas such as housing and other urban infrastructures. Land cover classes were interpreted into maps and the accuracy of the maps were validated to reference data and actual ground scenarios. The study for validation of the proposed modeling tool was carried out using the large prominent mining area in Malaysia namely the Kinta District. Results from the validation study carried out indicate that the correlation of the results obtained from this Integrated Remote Sensing and GIS tool for modeling to field data is in the range of 0.87-0.92 which is acceptable and close to reality.
Robert Paul Breckenridge
Creeping environmental changes are impacting some of the largest remaining intact parcels of sagebrush steppe ecosystems in the western United States, creating major problems for land managers. The Idaho National Laboratory (INL), located in southeastern Idaho, is part of the sagebrush steppe ecosystem, one of the largest ecosystems on the continent. Scientists at the INL and the University of Idaho have integrated existing field and remotely sensed data with geographic information systems technology to analyze how recent fires on the INL have influenced the current distribution of terrestrial vegetation. Three vegetation mapping and classification systems were used to evaluate the changes in vegetation caused by fires between 1994 and 2003. Approximately 24% of the sagebrush steppe community on the INL was altered by fire, mostly over a 5-year period. There were notable differences between methods, especially for juniper woodland and grasslands. The Anderson system (Anderson et al. 1996) was superior for representing the landscape because it includes playa/bare ground/disturbed area and sagebrush steppe on lava as vegetation categories. This study found that assessing existing data sets is useful for quantifying fire impacts and should be helpful in future fire and land use planning. The evaluation identified that data from remote sensing technologies is not currently of sufficient quality to assess the percentage of cover. To fill this need, an approach was designed using both helicopter and fixed wing unmanned aerial vehicles (UAVs) and image processing software to evaluate six cover types on field plots located on the INL. The helicopter UAV provided the best system compared against field sampling, but is more dangerous and has spatial coverage limitations. It was reasonably accurate for dead shrubs and was very good in assessing percentage of bare ground, litter and grasses; accuracy for litter and shrubs is questionable. The fixed wing system proved to be
Calaudi, Rosamaria; Lo Feudo, Teresa; Calidonna, Claudia Roberta; Sempreviva, Anna Maria
Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from Remote Sensing can provide detailed information for analysis for sources of renewable energy and to determine the potential energy and socially acceptability of suggested location. Coastal sites of Southern Italy have the advantage of favorable climatic conditions to use renewable energy, such us cloud free days and local breeze phenomena. Many ports are located where they have opportunities for exploitation of renewable energy, by using existing port area and by taking advantage of their coastal locations. Policies of European-Committee and Global-Navigation-PIANC for a better use of energy and an efficient supply from renewable sources are also focused on the construction of port facilities in zero emissions. Using data from Remote Sensing, can reduce the financial resources currently required for finding and assessing suitable areas, we defined an integrated methodology for potential wind and solar energy in harbor areas. In this study we compared the hourly solar power energy using MSG-SEVIRI (Meteosat Second Generation Spinning Enhanced Visible and Infrared) data products DSSF (Down-welling Surface Short-wave-Flux), and PV-Plant measurements with Nominal Power Peak of 19,85 kWp. The PV Plant is situated at a coastal site in Calabrian region, located near Vibo Valentia harbor area. We estimate potential energy by using input solar radiation of Satellite data, with same characteristics of the PV-plant. The RMSE and BIAS for hourly averaged solar electrical reproducibility are estimated including clear and sky conditions. Comparison between energy reproducibility by using DSSF product and PV-plant measurements, made over the period October 2013-June 2014, showed a good agreement in our costal site and generally overestimate (RMSE(35W/m2) and BIAS(4W/m2)) electrical reproducibility from a PV-plant. For wind resource
Cho, Moses A
Full Text Available The study demonstrates that the integration of remote sensing and in situ data could be important in providing more accurate estimates of E. grandis state in KwaZulu Natal, South Africa compared to remote sensing models. Such modelling effort would...
de Sherbinin, A. M.; Yetman, G.; MacManus, K.; Vinay, S.
The diversity of data on human settlements, infrastructure, and population continues to grow rapidly, with recent releases of data products based on a range of different remote sensing data sources as well as census and administrative data. We report here on recent improvements in data from the NASA Socioeconomic Data and Applications Center (SEDAC) and partner organizations, aimed at supporting both interdisciplinary research and real-world applications. The fourth version of SEDAC's Gridded Population of the World (GPWv4) now includes variables for age categories, gender, and urban/rural location, and has also been integrated with the Global Human Settlements (GHS) data developed by the Joint Research Centre of the European Commission to produce a GHS-POP grid for the years 1975, 1990, 2000 and 2015. Through a collaboration between Facebook's Connectivity Lab and the Center for International Earth Science Information Network (CIESIN), High Resolution Settlement Layer (HRSL) data derived from 50-cm DigitalGlobe imagery are now available for selected developing countries at 30-m resolution. SEDAC is also developing interactive mapping and analysis tools to facilitate visualization and access to these often large and complex data products. For example, SEDAC has collaborated with scientists from NASA's Goddard Space Flight Center to release the Global Man-made Impervious Surfaces & Settlement Extents from Landsat data at 30-m resolution through an innovative map interface. We also summarize recent progress in developing an international data collective that is bringing together both data developers and data users from the public and private sectors to collaborate on expanding data access and use, improving data quality and documentation, facilitating data intercomparison and integration, and sharing of resources and capabilities.
Trifonov, Yu V
Description of data devices for deriving multi-spectral measuring television measurement data of middle and high resolution through use of second generation Meteor-type satellites. Options for developing a permanent and active remote sensing system in USSR are discussed. It is noted that the present experiment is an important step in that direction. Design and structural data for this particular device and its application in the experiment are covered.
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)
Kontoes, C.; Papoutsis, I.; Michail, D.; Herekakis, Th.; Koubarakis, M.; Kyzirakos, K.; Karpathiotakis, M.; Nikolaou, C.; Sioutis, M.; Garbis, G.; Vassos, S.; Keramitsoglou, I.; Kersten, M.; Manegold, S.; Pirk, H.
In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers, including land use/land cover, administrative boundaries, road and rail network, points of interest, and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters and that have activated Emergency Support Services at a European level in the framework of the operational GMES projects SAFER and LinkER. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA's in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integration of state-of-the-art Information Technologies that have become available in the framework of the TELEIOS (EC/ICT) project. TELEIOS aims at the development of fully automatic processing chains reliant on a) the effective storing and management of the large amount of EO and GIS data, b) the post-processing refinement of the fire products using semantics, and c) the creation of thematic maps and added-value services. The first objective is achieved with the use of advanced Array Database technologies, such
Hari, G. R. V.
With the usage of metadata as a reference for spatial data query, remote sensing images and other spatial datasets have been linked to their related semantic information. In the current catalogue systems, like those or satellite data provides, or clearinghouses, each remote sensing image is maintained as an independent entity. There is a very limited possibility to know the linkage of one image to another, even if one image has actually been derived from the other. It is an advantage for many purposes if the linkage among remote sensing image or other spatial data can be maintained or at least reconstructed. This research will explore how an image is linked to its related information, and how an image can be linked to another images. By exploring links among remote sensing images, a query of remote sensing data collection can be extended, for example, to find the answer of the query: 'which images are used to create certain dataset?', or 'which images have been created from a concrete dataset?', or 'is there a relationship between image A and image B based on their processing steps?'. By building links among spatial datasets in a collection based on their creation process, a further possibility of spatial data organization can be supported. The applicability and compatibility of the proposed method with the current platform is also considered. The proposed method can be implemented using the same standard and protocol and using the same metadata file as used by the existing system. This approach makes it also possible to be implemented in many countries which use the same infrastructure. To prove this purpose, we develop a prototype based on open source platform, including PostgreSQL, Apache Webserver, Mapserver WebGIS, and PHP programming environment. The output of this research leads to an improvement of spatial data handling, where an adjacency list is used to maintain spatial dataset history link. This improvement can enhance the query of spatial data in a
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.…
Brook, John; Yates, Kimberly; Halley, Robert
anthropogenic causes (Brown, 1988). Models of coral reef ecosystems, parameterized by process measurements and scaled in time-space using remote sensing, have the potential to address pressing research questions that are central to devising valid management strategies (Grigg el al., 1984; Hatcher, 1997b). To attain this goal, ecosystem-level models that integrate studies of physical and chemical forcing with observed biological and geological responses are required. This interdisciplinary approach to understanding reef biogeochemical dynamics can allow investigations that integrate the scales of time and space (Hatcher, 1997a), thereby enabling prediction of coral reef change (Andréfouët and Payri, 2001). In turn, prediction of holistic ecosystem function within various environmental focusing scenarios has substantial promise in mitigating future disturbance. Indeed, management of coral reefs at the ecosystem level has been suggested as the only meaningful approach to preserving coral reefs (Bohnsack and Ault, 1996; Christensen et al., 1996).
The Integrated Remote Sensing and Visualization System (IRSV) is being designed to accommodate the needs of todays Bridge Engineers at the : state and local level from several aspects that were documented in Volume One, Summary Report. The followi...
The Integrated Remote Sensing and Visualization System (IRSV) was developed in Phase One of this project in order to : accommodate the needs of todays Bridge Engineers at the state and local level. Overall goals of this project are: : Better u...
Abdelrahim, Mohamed Mahmoud Hosny
times as much as the IKONOS GEOCARTERRA(TM) products. The developed IISP is a step closer towards the direct and active involvement of high-resolution remote sensing imagery in querying the real world and performing exploratory types of spatial analysis. (Abstract shortened by UMI.)
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....
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....
Program Manager AFOSR/RSE Air Force Research Laboratory Remote Sensing and Imaging Physics 7 March 2012 Report Documentation Page Form...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Remote Sensing And Imaging Physics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Imaging of Space Objects •Information without Imaging •Predicting the Location of Space Objects • Remote Sensing in Extreme Conditions •Propagation
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.
Akbar, M. S.; Sarker, M. H.; Sattar, M. A.; Sarwar, G. M.; Rahman, S. M. M.; Rahman, M. M.; Khan, Z. U.
Cultivation of shrimp mostly in unplanned way has been considered as one of the major environmental disasters of Shamnagar. Villagers surrounding the rivers are mainly involved with fish (shrimp) cultivation. So, fertile agriculture land has been converted to shrimp cultivation. Conversion of agriculture land to other usage is a common but acute problem for land resources of the country like Bangladesh. Conventional methods for collecting this information are relatively costly and time consuming. Contrarily, Remote Sensing satellite observation with its unique capability to provide cost-effective support in compiling the latest information about the natural resource. Remote sensing, in conjunction with GIS, has been widely applied and been recognized as a powerful and effective tool in detecting land use and land cover changes. RapidEye, Landsat8 images were used to identify land use and land cover of the area during the period 2008 and 2015. Google images were used to identify the micro-level land use features of the same period. Multi-spectral classifications using unsupervised and supervised classification were done and results have been compared based on the field investigation. The study reveals that during the period 2008 to 2015 agricultural practice has been reduced from 35 % to 21 % and shrimp cultivation area increased from 38 % to 50 %. Due to the impact of high salinity and salt water intrusion caused by natural disaster, agricultural activities is reduced and farmers have been converted to other practices, as a result shrimp farming is gaining popularity in the area.
Schweitzer, Jeffrey S.; Groves, Joel L.
Subsurface remote sensing measurements are widely used for oil and gas exploration, for oil and gas production monitoring, and for basic studies in the earth sciences. Radiation sensors, often including small accelerator sources, are used to obtain bulk properties of the surrounding strata as well as to provide detailed elemental analyses of the rocks and fluids in rock pores. Typically, instrument packages are lowered into a borehole at the end of a long cable, that may be as long as 10 km, and two-way data and instruction telemetry allows a single radiation instrument to operate in different modes and to send the data to a surface computer. Because these boreholes are often in remote locations throughout the world, the data are frequently transmitted by satellite to various locations around the world for almost real-time analysis and incorporation with other data. The complete system approach that permits rapid and reliable data acquisition, remote analysis and transmission to those making decisions is described
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.
Soliman, A.; Soltani, K.; Yin, J.; Subramaniam, B.; Liu, Y.; Padmanabhan, A.; Riteau, P.; Keahey, K.; Wang, S. W.
Urban ecosystems are unique earth environments because both their physical and social components contribute to the overall dynamics of the system. Up-to-date, remote sensing data (e.g. optical and LiDAR) allowed researchers to monitor the development of impervious surfaces however, it was not adequate to detect associated social dynamics. Geo-located social media (e.g. Twitter) provides a data source to detect population dynamics and understand the interaction of people with their physical environment. Although, integrating social media with remote sensing data has been hindered by large volumes of data and the lack of models for integrating remote sensing products with unstructured social media data. In this research work, we leveraged the NSF chameleon cloud computing platform to provide virtual clusters and elastic auto-scaling of resources that are needed for the synthesis of landuse and geo-located Twitter data. In this context, data synthesis was used to address research questions related to population dynamics in major metropolitan areas. We provide an overview of a cloud computing workflow comprised of a set of coupled scalable synthesis modules for: a) preprocessing data, which includes storage and query of heterogeneous data streams, b) spatial data integration, which matches geo-located Twitter data with user defined landuse maps based on a conceptual model of human mobility and c) visualization of urban mobility patterns. Our results demonstrate the flexibility to connect data, synthesis methods and computing resources using cloud computing, which would be otherwise very difficult for untrained scientists to setup and control. Furthermore, we demonstrate the capabilities of CyberGIS-based workflow using the case study of comparing commuting distances across major US cities from 2013 through the present. We demonstrate how our workflow will support discoveries in urban ecological studies as well as linking human and physical dimensions in environmental
Löwe, Peter; Wächter, Joachim
The Boxing Day Tsunami killed 240,000 people and inundated the affected shorelines with waves reaching heights up to 30m. Tsunami Early Warning Capabilities have improved in the meantime by continuing development of modular Tsunami Early Warning Systems (TEWS). However, recent tsunami events, like the Chile 2010 and the Honshu 2011 tsunami demonstrate that the key challenge for TEWS research still lies in the timely issuing of reliable early warning messages to areas at risk, but also to other stakeholders professionally involved in the unfolding event. Until now remote sensing products for Tsunami events, including crisis maps and change detection products, are exclusively linked to those phases of the disaster life cycle, which follow after the early warning stage: Response, recovery and mitigation. The International Charter for Space and Major Disasters has been initiated by the European Space Agency (ESA) and the Centre National d'Etudes Spatiales (CNES) in 1999. It coordinates a voluntary group of governmental space agencies and industry partners, to provide rapid crisis imaging and mapping to disaster and relief organisations to mitigate the effects of disasters on human life, property and the environment. The efficiency of this approach has been demonstrated in the field of Tsunami early warning by Charter activations following the Boxing Day Tsunami 2004, the Chile Tsunami 2010 and the Honshu Tsunami 2011. Traditional single-satellite operations allow at best bimonthly repeat rates over a given Area of Interest (AOI). This allows a lot of time for image acquisition campaign planning between imaging windows for the same AOI. The advent of constellations of identical remote sensing satellites in the early 21st century resulted both in daily AOI revisit capabilities and drastically reduced time frames for acquisition planning. However, the image acquisition planning for optical remote sensing satellite constellations is constrained by orbital and communication
Cetin, H.; Levandowsk, D.W.
The mineral belts of Lincoln County were studied using geophysical and remote sensing data. Digital Thematic Mapper (TM) data was processed in a new normalization technique that discriminates hydrothermal alteration from the other cover types in the area. This technique is robust, appears to be scene independent, and resulted in the discovery of previously unknown areas of hydrothermal alteration. Lineament analysis was carried out using a variety of filters on the TM data. Gamma-ray, as well as aeromagnetic and gravity data were used, along with the TM data, to identify the specific attributes of known mineral deposits in order to outline other potential target areas. In this paper color pseudo-three-dimensional plot of gamma-ray data is used to identify areas that have high Potassium and Thorium counts and are also characterized by significant K/Th ratio values
M. S. Akbar
Full Text Available Cultivation of shrimp mostly in unplanned way has been considered as one of the major environmental disasters of Shamnagar. Villagers surrounding the rivers are mainly involved with fish (shrimp cultivation. So, fertile agriculture land has been converted to shrimp cultivation. Conversion of agriculture land to other usage is a common but acute problem for land resources of the country like Bangladesh. Conventional methods for collecting this information are relatively costly and time consuming. Contrarily, Remote Sensing satellite observation with its unique capability to provide cost-effective support in compiling the latest information about the natural resource. Remote sensing, in conjunction with GIS, has been widely applied and been recognized as a powerful and effective tool in detecting land use and land cover changes. RapidEye, Landsat8 images were used to identify land use and land cover of the area during the period 2008 and 2015. Google images were used to identify the micro-level land use features of the same period. Multi-spectral classifications using unsupervised and supervised classification were done and results have been compared based on the field investigation. The study reveals that during the period 2008 to 2015 agricultural practice has been reduced from 35 % to 21 % and shrimp cultivation area increased from 38 % to 50 %. Due to the impact of high salinity and salt water intrusion caused by natural disaster, agricultural activities is reduced and farmers have been converted to other practices, as a result shrimp farming is gaining popularity in the area.
Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.
Full Text Available This research examines the integration and potential uses of linkages between climate dynamics, savanna vegetation and landscape level processes within a highly vulnerable region, both in terms of climate variability and social systems. We explore the combined applications of two time-series methodologies: (1 climate signals detected in tree ring growth, from published literature, chronologies from the International Tree-Ring Data Bank, and minimal preliminary field data; and (2 new primary production (NPP data of vegetation cover over time derived from remotely sensed analyses. Both time-series are related to the regional patterns of precipitation, the principle driver of plant growth in the area. The approach is temporally and spatially multiscalar and examines the relationships between vegetation cover, type and amount, and precipitation shifts. We review literature linking dendrochronology, climate, and remotely sensed imagery, and, in addition, provide unique preliminary analyses from a dry study site located on the outer limit of the Okavango Delta. The work demonstrates integration across the different data sources, to provide a more holistic view of landscape level processes occurring in the last 30-50 years. These results corroborate the water-limited nature of the region and the dominance of precipitation in controlling vegetation growth. We present this integrative analysis of vegetation and climate change, as a prospective approach to facilitate the development of long-term climate/vegetation change records across multiple scales.
Bernardes, S.; Madden, M.; Jordan, T.; Knight, A.; Aragon, A.
Hurricane impacts often include the total or partial removal of vegetation due to strong winds (e.g., uprooted trees and broken trunks and limbs). Those impacts can usually be quickly assessed following hurricanes, by using established field and remote sensing methods. Conversely, impacts on vegetation health may present challenges for identification and assessment, as they are disconnected in time from the hurricane event and may be less evident. For instance, hurricanes may promote drastic increases in salinity of water available to roots and may increase exposure of aerial parts to salt spray. Derived stress conditions can negatively impact biological processes and may lead to plant decline and death. Large areas along the coast of the United States have been affected by hurricanes and show such damage (vegetation browning). Those areas may continue to be impacted, as climate projections indicate that hurricanes may become more frequent and intense, resulting from the warming of ocean waters. This work uses remote sensing tools and techniques to record and assess impacts resulting from recent hurricanes at Sapelo Island, a barrier island off the coast of the State of Georgia, United States. Analyses included change detection at the island using time series of co-registered Sentinel 2 and Landsat images. A field campaign was conducted in September 2017, which included flying three UAVs over the island and collecting high-overlap 20-megapixel RGB images at two spatial resolutions (1 and 2 inches/pixel). A five-band MicaSense RedEdge camera, a downwelling radiation sensor and calibration panel were used to collect calibrated multispectral images of multiple vegetation types, including healthy vegetation and vegetation affected by browning. Drone images covering over 600 acres were then analyzed for vegetation status and damage, with emphasis to vegetation removal and browning resulting from salinity alterations and salt spray. Results from images acquired by drones
Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 4 : web-based bridge information database--visualization analytics and distributed sensing.
This report introduces the design and implementation of a Web-based bridge information visual analytics system. This : project integrates Internet, multiple databases, remote sensing, and other visualization technologies. The result : combines a GIS ...
The Mediterranean region is affected by water scarcity. Some countries as Tunisia reached the limit of 550 m3/year/capita due overexploitation of low water resources for irrigation, domestic uses and industry. A lot of programs aim to evaluate strategies to improve water consumption at regional level. In central Tunisia, on the Merguellil catchment, we develop integrated water resources modelisations based on social investigations, ground observations and remote sensing data. The main objective is to close the water budget at regional level and to estimate irrigation and water pumping to test scenarios with endusers. Our works benefit from French, bilateral and European projects (ANR, MISTRALS/SICMed, FP6, FP7…), GMES/GEOLAND-ESA) and also network projects as JECAM and AERONET, where the Merguellil site is a reference. This site has specific characteristics associating irrigated and rainfed crops mixing cereals, market gardening and orchards and will be proposed as a new environmental observing system connected to the OMERE, TENSIFT and OSR systems respectively in Tunisia, Morocco and France. We show here an original and large set of ground and remote sensing data mainly acquired from 2008 to present to be used for calibration/validation of water budget processes and integrated models for present and scenarios: - Ground data: meteorological stations, water budget at local scale: fluxes tower, soil fluxes, soil and surface temperature, soil moisture, drainage, flow, water level in lakes, aquifer, vegetation parameters on selected fieds/month (LAI, height, biomass, yield), land cover: 3 times/year, bare soil roughness, irrigation and pumping estimations, soil texture. - Remote sensing data: remote sensing products from multi-platform (MODIS, SPOT, LANDSAT, ASTER, PLEIADES, ASAR, COSMO-SkyMed, TerraSAR X…), multi-wavelength (solar, micro-wave and thermal) and multi-resolution (0.5 meters to 1 km). Ground observations are used (1) to calibrate soil
This paper focuses on the use of remote sensing for marine oil spill detection and response. The surveillance and monitoring of discharges, and the main elements of effective surveillance are discussed. Tactical emergency response and the requirements for selecting a suitable remote sensing approach, airborne remote sensing systems, and the integration of satellite and airborne imaging are examined. Specifications of satellite surveillance systems potentially usable for oil spill detection, and specifications of airborne remote sensing systems suitable for oil spill detection, monitoring and supplemental actions are tabulated, and a schema of integrated satellite-airborne remote sensing (ISARS) is presented. (UK)
Mohamed, L.; Farag, A. Z. A.
North African countries struggle with insufficient, polluted, oversubscribed, and increasingly expensive water. This natural water shortage, in addition to the lack of a comprehensive scheme for the identification of new water resources challenge the political settings in north Africa. Groundwater is one of the main water resources and its occurrence is controlled by the structural elements which are still poorly understood. Integration of remote sensing images and geophysical tools enable us to delineate the surface and subsurface structures (i.e. faults, joints and shear zones), identify the role of these structures on groundwater flow and then to define the proper locations for groundwater wells. This approach were applied to three different areas in Egypt; southern Sinai, north eastern Sinai and the Eastern Desert using remote sensing, geophysical and hydrogeological datasets as follows: (1) identification of the spatial and temporal rainfall events using meteorological station data and Tropical Rainfall Measuring Mission data; (2) delineation of major faults and shear zones using ALOS Palsar, Landsat 8 and ASTER images, geological maps and field investigation; (3) generation of a normalized difference ratio image using Envisat radar images before and after the rain events to identify preferential water-channeling discontinuities in the crystalline terrain; (4) analysis of well data and derivations of hydrological parameters; (5) validation of the water-channeling discontinuities using Very Low Frequency, testing the structural elements (pre-delineated by remote sensing data) and their depth using gravity, magnetic and Vertical Electrical Sounding methods; (6) generation of regional groundwater flow and isotopic (18O and 2H) distribution maps for the sedimentary aquifer and an approximation flow map for the crystalline aquifer. The outputs include: (1) a conceptual/physical model for the groundwater flow in fractured crystalline and sedimentary aquifers; (2
Labak, Peter; Sussman, Aviva; Rowlands, Aled; Chiappini, Massimo; Malich, Gregor; MacLeod, Gordon; Sankey, Peter; Sweeney, Jerry; Tuckwell, George
The Integrated Field Exercise of 2014 (IFE14) was a field event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of a Comprehensive Test Ban Treaty's (CTBT) on-site inspection (OSI). During an OSI, up to 40 inspectors search a 1000km2 inspection area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of an OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams to execute the scenario in which the exercise was played, to those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, a number of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force Group (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, as well as other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection by other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.
Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea
Mathematical models of cholera dynamics can not only help in identifying environmental drivers and processes that influence disease transmission, but may also represent valuable tools for the prediction of the epidemiological patterns in time and space as well as for the allocation of health care resources. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. They have been ravaging the shore of Lake Kivu in the east of the country repeatedly during the last decades. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of the lake. Remotely sensed data sets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multiyear data set of reported cholera cases. The best fourteen models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via proper cross validation. Among these, the one accounting for seasonality, El Niño Southern Oscillation, precipitation and human mobility outperforms the others in cross validation. Some drivers (such as human mobility and rainfall) are retained only by a few models, possibly indicating that the mechanisms through which they influence cholera dynamics in the area will have to be investigated further.
Salazar, Luis Alonso
This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.
Goldshleger, N.; Basson, U.; Azaria, I.
The Dead Sea coastal area is exposed to the destructive process of sinkhole collapse. The increase in sinkhole activity in the last two decades has been substantial, resulting from the continuous decrease in the Dead Sea's level, with more than 1,000 sinkholes developing as a result of upper layer collapse. Large sinkholes can reach 25 m in diameter. They are concentrated mainly in clusters in several dozens of sites with different characteristics. In this research, methods for mapping, monitoring and predicting sinkholes were developed using active and passive remote-sensing methods: field spectrometer, geophysical ground penetration radar (GPR) and a frequency domain electromagnetic instrument (FDEM). The research was conducted in three stages: 1) literature review and data collection; 2) mapping regions abundant with sinkholes in various stages and regions vulnerable to sinkholes; 3) analyzing the data and translating it into cognitive and accessible scientific information. Field spectrometry enabled a comparison between the spectral signatures of soil samples collected near active or progressing sinkholes, and those collected in regions with no visual sign of sinkhole occurrence. FDEM and GPR investigations showed that electrical conductivity and soil moisture are higher in regions affected by sinkholes. Measurements taken at different time points over several seasons allowed monitoring the progress of an 'embryonic' sinkhole.
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...
Singh, R. B.; Kumar, Dilip
In India, land resources have reached a critical stage due to the rapidly growing population. This challenge requires an integrated approach toward harnessing land resources, while taking into account the vulnerable environmental conditions. Remote sensing and Geographical Information System (GIS) based technologies may be applied to an area in order to generate a sustainable development plan that is optimally suited to the terrain and to the productive potential of the local resources. The present study area is a part of the middle Ganga plain, known as Son-Karamnasa interfluve, in India. Alternative land use systems and the integration of livestock enterprises with the agricultural system have been suggested for land resources management. The objective of this paper is to prepare a land resource development plan in order to increase the productivity of land for sustainable development. The present study will contribute necessary input for policy makers to improve the socio-economic and environmental conditions of the region.
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.
Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc
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).
Al-Naimi, Noora; Al-Ghouti, Mohammad A; Balakrishnan, Perumal
Mangroves are unique ecosystems that dominate tropical and subtropical coastlines around the world. They provide shelter and nursery to wide variety of species such as fish and birds. Around 73 species of mangroves were recognized around the world. In Qatar, there is only one mangrove species Avicennia marina that is predominant along the northeastern coast. Assessing the health of these valuable ecosystems is vital for protection, management, and conservation of those resources. In this study, an integrated approach of chemical and remote sensing analysis was implemented to investigate the current status of the mangrove trees in Al-Khor, Qatar. Fifteen different A. marina trees from different locations in the mangrove forest were examined for their chlorophyll and nitrogen content levels. Soil analysis was also conducted to understand the effect of moisture on nitrogen availability. Results shows that currently, mangroves are in a good status in terms of nitrogen availability and chlorophyll levels which are related and both are key factors for photosynthesis. Remote sensing techniques were used for chlorophyll prediction. The results showed that these methods have the potential to be used for chlorophyll prediction and estimation.
Full Text Available The Tibetan Plateau (TP has been observed by satellite optical remote sensing, altimetry, and gravimetry for a variety of geophysical parameters, including water storage change. However, each of these sensors has its respective limitation in the parameters observed, accuracy and spatial-temporal resolution. Here, we utilized an integrated approach to combine remote sensing imagery, digital elevation model, and satellite radar and laser altimetry data, to quantify freshwater storage change in a twin lake system named Chibuzhang Co and Dorsoidong Co in the central TP, and compared that with independent observations including mass changes from the Gravity Recovery and Climate Experiment (GRACE data. Our results show that this twin lake, located within the Tanggula glacier system, remained almost steady during 1973–2000. However, Dorsoidong Co has experienced a significant lake level rise since 2000, especially during 2000–2005, that resulted in the plausible connection between the two lakes. The contemporary increasing lake level signal at a rate of 0.89 ± 0.05 cm·yr−1, in a 2° by 2° grid equivalent water height since 2002, is higher than the GRACE observed trend at 0.41 ± 0.17 cm·yr−1 during the same time span. Finally, a down-turning trend or inter-annual variability shown in the GRACE signal is observed after 2012, while the lake level is still rising at a consistent rate.
Poulter, B.; Ciais, P.; Joetzjer, E.; Maignan, F.; Luyssaert, S.; Barichivich, J.
Accurately estimating forest biomass and forest carbon dynamics requires new integrated remote sensing, forest inventory, and carbon cycle modeling approaches. Presently, there is an increasing and urgent need to reduce forest biomass uncertainty in order to meet the requirements of carbon mitigation treaties, such as Reducing Emissions from Deforestation and forest Degradation (REDD+). Here we describe a new parameterization and assimilation methodology used to estimate tropical forest biomass using the ORCHIDEE-CAN dynamic global vegetation model. ORCHIDEE-CAN simulates carbon uptake and allocation to individual trees using a mechanistic representation of photosynthesis, respiration and other first-order processes. The model is first parameterized using forest inventory data to constrain background mortality rates, i.e., self-thinning, and productivity. Satellite remote sensing data for forest structure, i.e., canopy height, is used to constrain simulated forest stand conditions using a look-up table approach to match canopy height distributions. The resulting forest biomass estimates are provided for spatial grids that match REDD+ project boundaries and aim to provide carbon estimates for the criteria described in the IPCC Good Practice Guidelines Tier 3 category. With the increasing availability of forest structure variables derived from high-resolution LIDAR, RADAR, and optical imagery, new methodologies and applications with process-based carbon cycle models are becoming more readily available to inform land management.
Atwell, B. H.
The Mississippi Sound Remote Sensing Study was initiated as part of the research program of the NASA Earth Resources Laboratory. The objective of this study is development of remote sensing techniques to study near-shore marine waters. Included within this general objective are the following: (1) evaluate existing techniques and instruments used for remote measurement of parameters of interest within these waters; (2) develop methods for interpretation of state-of-the-art remote sensing data which are most meaningful to an understanding of processes taking place within near-shore waters; (3) define hardware development requirements and/or system specifications; (4) develop a system combining data from remote and surface measurements which will most efficiently assess conditions in near-shore waters; (5) conduct projects in coordination with appropriate operating agencies to demonstrate applicability of this research to environmental and economic problems.
Fondekar, S.P.; Rao, L.V.G.
the drawback of expensive conventional surveying methods. An airborne remote sensing system used for monitoring and surveillance of oil comprises different sensors such as side-looking airborne radar, synthetic aperture radar, infrared/ultraviolet line scanner...
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...
Ahmadi, Farshid Farnood; Ebadi, Hamid
3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented.
Farshid Farnood Ahmadi
Full Text Available 3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs; direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS is presented.
Rao, M.; Silber-coats, Z.; Lawrence, F.
California's ongoing drought condition shriveled not just the agricultural sector, but also the natural resources sector including forestry, wildlife, and fisheries. As future predictions of drought and fire severity become more real in California, there is an increased awareness to pursue innovative and cost-effective solutions that are based on silvicultural treatments and controlled burns to improve forest health and reduce the risk of high-severity wildfires. The main goal of this study is to develop a GIS map of the drought-impacted region of northern and central California using remote sensing data for the summer period of 2014. Specifically, Landsat/NAIP imagery will be analyzed using a combination of object-oriented classification and spectral indices such as the Modified Perpendicular Drought Index (MPDI). This spectral index basically scales the line perpendicular to the soil line defined in the Red-NIR feature space in conjunction with added information about vegetative fraction derived using NDVI. The resulting output will be correlated with USGS-produced estimates of climatic water deficit (CWD) data to characterize the severity of the drought. The CWD is simulated based on hydrological tool, Basin Characterization Model (BCM) that ingests historical climate data in conjunction with soils, topography, and geological data to predict other monthly hydrological outputs including runoff, recharge, and snowpack. In addition to field data, data collected by state agencies including USFS, calforests.org will be used in the classification and accuracy assessment procedures. Visual assessment using high-resolution imagery such as NAIP will be used to further refine the spatial maps. The drought severity maps produced will greatly facilitate site-specific planning efforts aimed at implementing resource management decisions.
Philipson, W. R.; Erb, T. L.; Fernandez, D.; Mcleester, J. N.
Cornell's Remote Sensing Program has been involved in a continuing investigation to assess the value of remote sensing for vineyard management. Program staff members have conducted a series of site and crop analysis studies. These include: (1) panchromatic aerial photography for planning artificial drainage in a new vineyard; (2) color infrared aerial photography for assessing crop vigor/health; and (3) color infrared aerial photography and aircraft multispectral scanner data for evaluating yield related factors. These studies and their findings are reviewed.
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.
El-Baz, F.; Hassan, M.H.A.; Cappellini, V.
The purpose of the Workshop was to study in depth the application of remote sensing technology to the fields of archaeology, astronomy, geography, geology, and physics. Some emphasis was placed on utilizing remote sensing methods and techniques in the search for water, mineral and land resources. The Workshop was attended by 90 people from 35 countries. The proceedings of this meeting includes 15 papers, 12 of them have a separate abstract in the INIS Database. Refs, figs and tabs
West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tama...
El-Gafy, Mohamed Anwar
Transportation projects will have impact on the environment. The general environmental pollution and damage caused by roads is closely associated with the level of economic activity. Although Environmental Impact Assessments (EIAs) are dependent on geo-spatial information in order to make an assessment, there are no rules per se how to conduct an environmental assessment. Also, the particular objective of each assessment is dictated case-by-case, based on what information and analyses are required. The conventional way of Environmental Impact Assessment (EIA) study is a time consuming process because it has large number of dependent and independent variables which have to be taken into account, which also have different consequences. With the emergence of satellite remote sensing technology and Geographic Information Systems (GIS), this research presents a new framework for the analysis phase of the Environmental Impact Assessment (EIA) for transportation projects based on the integration between remote sensing technology, geographic information systems, and spatial modeling. By integrating the merits of the map overlay method and the matrix method, the framework analyzes comprehensively the environmental vulnerability around the road and its impact on the environment. This framework is expected to: (1) improve the quality of the decision making process, (2) be applied both to urban and inter-urban projects, regardless of transport mode, and (3) present the data and make the appropriate analysis to support the decision of the decision-makers and allow them to present these data to the public hearings in a simple manner. Case studies, transportation projects in the State of Florida, were analyzed to illustrate the use of the decision support framework and demonstrate its capabilities. This cohesive and integrated system will facilitate rational decisions through cost effective coordination of environmental information and data management that can be tailored to
Masini, N.; Rizzo, E.; Lasaponara, R.; Orefici, G.
This paper is focused on the jointly use of satellite Quickbird (QB) images and Ground Probing Radar (GPR) for assessing their capability in the detection of archaeological adobe structures (sun-dried earth material). Such detection is particularly complex. due to the low contrast generally existing between the archaeological features and the background. Two significant test areas were investigated in the Ceremonial Centre of Cahuachi (in the Nasca territory, Southern Peru) dating back to 6th century BC to 4th century AD. Our results showed that both satellite and GPR data provided valuable indications for unearthing precious ancient remains. Our preliminary analyses pointed out that the integrated use of non destructive remote sensing techniques has high potentiality for its important scientific implications and for its significant contributions to cultural resource management.
Full Text Available Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1 A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM derived from LiDAR data; 2 The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3 Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4 The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90 performed better than Li
Wang, Z.; Wu, J.; Wang, Y.; Kong, X.; Bao, H.; Ni, Y.; Ma, L.; Jin, J.
Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR) and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1) A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM) derived from LiDAR data; 2) The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3) Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4) The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90) performed better than LiDAR-metrics method (OA = 79
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.
Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang
The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process
Cracknell, A P [ed.
Various aspects of remote sensing are discussed. Topics include: the EARTHNET data acquisition, processing, and distribution facility the design and implementation of a digital interactive image processing system geometrical aspects of remote sensing and space cartography remote sensing of a complex surface legal aspects of remote sensing remote sensing of pollution, dust storms, ice masses, and ocean waves and currents use of satellite images for weather forecasting. Notes on field trips and work-sheets for laboratory exercises are included.
Full Text Available Information about the distribution of grass nitrogen (N) concentration is crucial in understanding rangeland vitality and facilitates effective management of wildlife and livestock. A challenge in estimating grass N concentration using remote...
Sensing systems are an important element of mobile teleoperators and robots. This paper discusses certain problems and limitations of vision and other sensing systems with respect to operations in a radiological accident environment. Methods which appear promising for near-term improvements to sensor technology are described. 3 refs
Lazaridou, M. A.; Patmio, E. N.
Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS) is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc), and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers) in the Lab. of Photogrammetry - Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.
Dierssen, Heidi M.; Randolph, Kaylan
The oceans cover over 70% of the earth's surface and the life inhabiting the oceans play an important role in shaping the earth's climate. Phytoplankton, the microscopic organisms in the surface ocean, are responsible for half of the photosynthesis on the planet. These organisms at the base of the food web take up light and carbon dioxide and fix carbon into biological structures releasing oxygen. Estimating the amount of microscopic phytoplankton and their associated primary productivity over the vast expanses of the ocean is extremely challenging from ships. However, as phytoplankton take up light for photosynthesis, they change the color of the surface ocean from blue to green. Such shifts in ocean color can be measured from sensors placed high above the sea on satellites or aircraft and is called "ocean color remote sensing." In open ocean waters, the ocean color is predominantly driven by the phytoplankton concentration and ocean color remote sensing has been used to estimate the amount of chlorophyll a, the primary light-absorbing pigment in all phytoplankton. For the last few decades, satellite data have been used to estimate large-scale patterns of chlorophyll and to model primary productivity across the global ocean from daily to interannual timescales. Such global estimates of chlorophyll and primary productivity have been integrated into climate models and illustrate the important feedbacks between ocean life and global climate processes. In coastal and estuarine systems, ocean color is significantly influenced by other light-absorbing and light-scattering components besides phytoplankton. New approaches have been developed to evaluate the ocean color in relationship to colored dissolved organic matter, suspended sediments, and even to characterize the bathymetry and composition of the seafloor in optically shallow waters. Ocean color measurements are increasingly being used for environmental monitoring of harmful algal blooms, critical coastal habitats
Cyples, N.; Ielpi, A.; Dirszowsky, R.
The Kicking Horse River is a gravel-bed stream originating from glacial meltwater supplied by the Wapta Icefields in south-eastern British Columbia. An alluvial tract extends for 7 km through Field, BC, where the trunk channel undergoes diurnal and seasonal fluctuations in flow as a result of varying glacial-meltwater supply and runoff recharge. Prior studies erected the Kicking Horse River as a reference for proximal braided systems, and documented bar formation and sediment distribution patterns from ground observations. However, a consistent model of planform evolution and related stratigraphic signature is lacking. Specific objectives of this study are to examine the morphodynamic evolution and stratigraphic signature of channel-bar complexes using high-resolution satellite imagery, sedimentologic and discharge observations, and ground-penetrating radar (GPR). Remote sensing highlights rates of lateral channel migration of as much as 270 meters over eight years ( 34 meters/year), and demonstrates how flood stages are associated with stepwise episodes of channel braiding and anabranching. GPR analysis aided in the identification of five distinct radar facies, including: discontinuous, inclined, planar, trough-shaped, and mounded reflectors, which were respectively related to specific architectural elements and fluvial processes responsible for bar evolution. Across-stream GPR transects demonstrated higher heterogeneity in facies distribution, while downstream-oriented transects yielded a more monotonous distribution in radar facies. Notably, large-scale inclined reflectors related to step-wise bar accretion are depicted only in downstream-oriented transects, while discontinuous reflectors related to bedform stacking appear to be dominant in along-stream transects. Integration of sedimentological data with remote sensing, gauging records, and GPR analysis allows for high-resolution modelling of stepwise changes in alluvial morphology. Conceptual models stemming
Zuckerberg, B.; McCabe, J.; Yin, H.; Pidgeon, A. M.; Bonter, D. N.; Radeloff, V.
Urbanization causes the simplification of animal communities dominated by exotic and invasive species with few top predators. In recent years, however, many animal predators (e.g., coyotes, cougars, and hawks) have become increasingly common in urban environments. As predator recovery is central to the mission of conservation biology, this colonization of urban environments represents a unique experiment in predator colonization and its associated ecological consequences. One such predator that is recovering from decades of widespread population declines are accipiter hawks. These woodland hawks are widely distributed throughout North America and are increasingly common in urban and suburban landscapes. Using data from Project FeederWatch, a national citizen science program, we quantified 25 years (1990-2015) of changes in the spatiotemporal dynamics of accipiter hawks in Washington D.C. and Chicago. We estimated change in hawk occupancy over time and identified the environmental characteristics associated with occupancy for two accipiter hawk species, Cooper's Hawk (Accipiter cooperii) and Sharp-shinned Hawk (Accipiter striatus), using Bayesian hierarchical models and remotely-sensed temperature (MODIS) and land cover data (NLCD). We found the proportion of sites recording the presence of accipiter hawks increased from 10% in the early 1990's to over 80% in 2015. This increase in occupancy followed a discrete pattern of establishment, growth, and saturation. Colonizing hawks were more strongly associated with remnant forest patches in urban environments. Over time, we found hawks became more tolerant of urban landscapes with higher amounts of impervious surface, suggesting that these predators became adapted to urbanization. The implications of returning predators and altered ecological dynamics in urban environments is of critical importance to conservation biology, and integrating remote sensing observations and citizen science allowed for an unprecedented
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....
Surveillance and tracking of oil spills has been a feature of most spill response situations for many years. The simplest and most direct method uses visual observations from an aircraft and hand-plotting of the data on a map. This technique has proven adequate for most small spills and for responses in fair weather. As the size of the spill increases or the weather deteriorates, there is a need to augment visual aerial observations with remote sensing methods. Remote sensing and its associated systems are one of the most technically complex and sophisticated elements of an oil spill response. During the past few years, a number of initiatives have been undertaken to use contemporary electronic and computing systems to develop new and improved remote sensing systems
Wukelic, G.E.; Foote, H.P.; Blair, S.C.; Begej, C.D.
This study successfully utilized advanced, remote-sensing computer-analysis techniques to quantify and map land- and water-use trends potentially relevant to siting, developing, and operating a national high-level nuclear waste repository on the US Department of Energy's (DOE) Hanford Site in eastern Washington State. Specifically, using a variety of digital data bases (primarily multidate Landsat data) and digital analysis programs, the study produced unique numerical data and integrated data reference maps relevant to regional (Columbia Plateau) and localized (Pasco Basin) hydrologic considerations associated with developing such a facility. Accordingly, study results should directly contribute to the preparation of the Basalt Waste Isolation Project site-characterization report currently in progress. Moreover, since all study data developed are in digital form, they can be called upon to contribute to furute reference repository location monitoring and reporting efforts, as well as be utilized in other DOE programmatic areas having technical and/or environmental interest in the Columbia Plateau region. The results obtained indicate that multidate digital Landsat data provide an inexpensive, up-to-date, and accurate data base and reference map of natural and cultural features existing in any region. These data can be (1) computer enhanced to highlight selected surface features of interest; (2) processed/analyzed to provide regional land-cover/use information and trend data; and (3) combined with other line and point data files to accomodate interactive, correlative analyses and integrated color-graphic displays to aid interpretation and modeling efforts
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
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.
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.
Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.
Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and
Bethel, Glenn R.
A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.
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
Gilani, H.; Jain, A. K.
This study assembles information from three sources - remote sensing, terrestrial photography and ground-based inventory data, to understand the dynamics of Nepal's tropical and sub-tropical forests and plantation sites for the period 1990-2015. Our study focuses on following three specific district areas, which have conserved forests through social and agroforestry management practices: 1. Dolakha district: This site has been selected to study the impact of community-based forest management on land cover change using repeat photography and satellite imagery, in combination with interviews with community members. The study time period is during the period 1990-2010. We determined that satellite data with ground photographs can provide transparency for long term monitoring. The initial results also suggests that community-based forest management program in the mid-hills of Nepal was successful. 2. Chitwan district: Here we use high resolution remote sensing data and optimized community field inventories to evaluate potential application and operational feasibility of community level REDD+ measuring, reporting and verification (MRV) systems. The study uses temporal dynamics of land cover transitions, tree canopy size classes and biomass over a Kayar khola watershed REDD+ study area with community forest to evaluate satellite Image segmentation for land cover, linear regression model for above ground biomass (AGB), and estimation and monitoring field data for tree crowns and AGB. We study three specific years 2002, 2009, 2012. Using integration of WorldView-2 and airborne LiDAR data for tree species level. 3. Nuwakot district: This district was selected to study the impact of establishment of tree plantation on total barren/fallow. Over the last 40 year, this area has went through a drastic changes, from barren land to forest area with tree species consisting of Dalbergia sissoo, Leucaena leucocephala, Michelia champaca, etc. In 1994, this district area was registered
Seo, Bumsuk; Lee, Jihye; Kang, Sinkyu
The weather-related risks in crop production is not only crucial for farmers but also for market participants and policy makers since securing food supply is an important issue for society. While crop growth condition and phenology are essential information about such risks, the extensive observations on those are often non-existent in many parts of the world. In this study, we have developed a novel integrative approach to remotely sense crop growth condition and phenology at a large scale. For corn and soybeans in Iowa and Illinois of USA (2003-2014), we assessed crop growth condition and crop phenology by EO data and validated it against the United States Department of Agriculture (USDA) National Agriculture Statistics System (NASS) crop statistics. For growth condition, we used two distinguished approaches to acquire crop condition indicators: a process-based crop growth modelling and a satellite NDVI based method. Based on their pixel-wise historic distributions, we determined relative growth conditions and scaled-down to the state-level. For crop phenology, we calculated three crop phenology metrics [i.e., start of season (SOS), end of season (EOS), and peak of season (POS)] at the pixel level from MODIS 8-day Normalized Difference Vegetation Index (NDVI). The estimates were compared with the Crop Progress and Condition (CPC) data of NASS. For the condition, the state-level 10-day estimates showed a moderate agreement (RMSE 70%). Notably, the condition estimates corresponded to the severe soybeans disease in 2003 and the drought in 2012 for both crops. For the phenology, the average RMSE of the estimates was 8.6 day for the all three metrics. The average |ME| was smaller than 1.0 day after bias correction. The proposed method enables us to evaluate crop growth at any given period and place. Global climate changes are increasing the risk in agricultural production such as long-term drought. We hope that the presented remote sensing method for crop condition
Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for 2013. Nominations were selected by the Editor-in-Chief and selected editorial board members from among all the papers published in 2009. Reviews and research papers were evaluated separately.
Balmer, M.L.; Lange, F.F.; Levi, C.G.
These proceedings contain papers presented at the Eighth Thematic Conference on Geologic Remote Sensing. This meeting was held April 29-May 2, 1991, in Denver, Colorado, USA. The conference was organized by the Environmental Research Institute of Michigan, in Cooperation with an international program committee composed primarily of geologic remote sensing specialists. The meeting was convened to discuss state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing as well as research and development activities aimed at increasing the future capabilities of this technology. The presentations in these volumes address the following topics: Spectral Geology; U.S. and International Hydrocarbon Exploration; Radar and Thermal Infrared Remote Sensing; Engineering Geology and Hydrogeology; Minerals Exploration; Remote Sensing for Marine and Environmental Applications; Image Processing and Analysis; Geobotanical Remote Sensing; Data Integration and Geographic Information Systems
This volume contains the proceedings of SPIE's remote sensing symposium which was held September 22--24, 1998, in Barcelona, Spain. Topics of discussion include the following: calibration techniques for soil moisture measurements; remote sensing of grasslands and biomass estimation of meadows; evaluation of agricultural disasters; monitoring of industrial and natural radioactive elements; and remote sensing of vegetation and of forest fires
Wolter, Andrea Elaine
I apply a forensic, multidisciplinary approach that integrates engineering geology field investigations, engineering geomorphology mapping, long-range terrestrial photogrammetry, and a numerical modelling toolbox to two large rock slope failures to study their causes, initiation, kinematics, and dynamics. I demonstrate the significance of endogenic and exogenic processes, both separately and in concert, in contributing to landscape evolution and conditioning slopes for failure, and use geomor...
Full Text Available The technological developments in remote sensing (RS during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS, which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users’ needs. The present paper gives the theoretic overview of the issue, besides
Barsi, Á.; Kugler, Zs.; László, I.; Szabó, Gy.; Abdulmutalib, H. M.
The technological developments in remote sensing (RS) during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS), which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users' needs. The present paper gives the theoretic overview of the issue, besides selected, practice
Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen
This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946
Leonhart, L.S.; Wukelic, G.E.; Foote, H.P.; Blair, S.C.
This study successfully utilized advanced, remote-sensing computer-analysis techniques to quantify and map land- and water-use trends potentially relevant to siting, developing, and operating a high-level national, nuclear waste repository on the US Department of Energy's Hanford Site in eastern Washington State. Specifically, using a variety of digital data bases (primarily multidate LANDSAT data) and digital analysis programs, the study produced unique numerical data and integrated data reference maps relevant to regional (Columbia Plateau) and localized (Pasco Basin) hydrologic considerations associated with developing such a facility. Because all study data developed are in digital form, they can be called upon to contribute to future reference repository location monitoring and reporting efforts, as well as to be utilized in other US Department of Energy programmatic areas having technical and/or environmental interest in the Columbia Plateau region. The results obtained indicate that multidate digital LANDSAT data provide an inexpensive, up-to-date, and accurate data base and reference map of natural and cultural features existing in any region. These data can be (1) computer enhanced to highlight selected surface features of interest; (2) processed/analyzed to provide regional land cover/use information and trend data; and (3) combined with other line and point data files to accommodate interactive, correlative analyses and integrated colorgraphic displays to aid interpretation and modeling efforts. Once the digital base is established, selected site information can be assessed immediately, various forms of data can be accessed concurrently or separately, and data sets may be displayed or mapped at any scale. Available editing software provides the opportunity to generate credible scenarios for a site while preserving the actual data base. 6 references
Terrazzino, Alfonso; Volponi, Silvia; Borgogno Mondino, Enrico
An investigation has been carried out, concerning remote sensing techniques, in order to assess their potential application to the energy system business: the most interesting results concern a new approach, based on digital data from remote sensing, to infrastructures with a large territorial distribution: in particular OverHead Transmission Lines, for the high voltage transmission and distribution of electricity on large distances. Remote sensing could in principle be applied to all the phases of the system lifetime, from planning to design, to construction, management, monitoring and maintenance. In this article, a remote sensing based approach is presented, targeted to the line planning: optimization of OHTLs path and layout, according to different parameters (technical, environmental and industrial). Planning new OHTLs is of particular interest in emerging markets, where typically the cartography is missing or available only on low accuracy scale (1:50.000 and lower), often not updated. Multi- spectral images can be used to generate thematic maps of the region of interest for the planning (soil coverage). Digital Elevation Models (DEMs), allow the planners to easily access the morphologic information of the surface. Other auxiliary information from local laws, environmental instances, international (IEC) standards can be integrated in order to perform an accurate optimized path choice and preliminary spotting of the OHTLs. This operation is carried out by an ABB proprietary optimization algorithm: the output is a preliminary path that bests fits the optimization parameters of the line in a life cycle approach.
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...
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...
Full Text Available using state of the art Light Detection And Ranging (LiDAR) instrumentation and other active and passive remote sensing tools. First “Lidar Field Campaign” • 2-day measurement campaign at University of Pretoria • First 23-hour continuous measurement... head2rightCirrus cloud morphology and dynamics. Atmospheric Research in Southern Africa and Indian Ocean (ARSAIO) Slide 24 © CSIR 2008 www.csir.co.za Middle atmosphere dynamics and thermal structure: comparative studies from...
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)
Trochim, Erin D.
This work presents improved approaches for integrating patterns and processes within hydrology, geomorphology, ecology and permafrost on Arctic landscapes. Emphasis was placed on addressing fundamental interdisciplinary questions using robust, repeatable methods. Water tracks were examined in the foothills of the Brooks Range to ascertain their role within the range of features that transport water in Arctic regions. Classes of water tracks were developed using multiple factor analysis based on their geomorphic, soil and vegetation characteristics. These classes were validated to verify that they were repeatable. Water tracks represented a broad spectrum of patterns and processes primarily driven by surficial geology. This research demonstrated a new approach to better understanding regional hydrological patterns. The locations of the water track classes were mapped using a combination method where intermediate processing of spectral classifications, texture and topography were fed into random forests to identify the water track classes. Overall, the water track classes were best visualized where they were the most discrete from the background landscape in terms of both shape and content. Issues with overlapping and imbalances between water track classes were the biggest challenges. Resolving the spatial locations of different water tracks represents a significant step forward for understanding periglacial landscape dynamics. Leaf area index (LAI) calculations using the gap-method were optimized using normalized difference vegetation index (NDVI) as input for both WorldView-2 and Landsat-7 imagery. The study design used groups to separate the effects of surficial drainage networks and the relative magnitude of change in NDVI over time. LAI values were higher for the WorldView-2 data and for each sensor and group combination the distribution of LAI values was unique. This study indicated that there are tradeoffs between increased spatial resolution and the ability
Hariss, M.; Purkis, S.; Ellis, J. M.; Swart, P. K.; Reijmer, J.
Great Bahama Bank (GBB) has been used in many models to illustrate depositional facies variation across flat-topped, isolated carbonate platforms. Such models have served as subsurface analogs at a variety of scales. In this presentation we have integrated Landsat TM imagery, a refined bathymetric digital elevation model, and seafloor sample data compiled into ArcGIS and analyzed with eCognition to develop a depositional facies map that is more robust than previous versions. For the portion of the GBB lying to the west of Andros Island, the facies map was generated by pairing an extensive set of GPS-constrained field observations and samples (n=275) (Reijmer et al., 2009, IAS Spec Pub 41) with computer and manual interpretation of the Landsat imagery. For the remainder of the platform, which lacked such rigorous ground-control, the Landsat imagery was segmented into lithotopes - interpreted to be distinct bodies of uniform sediment - using a combination of edge detection, spectral and textural analysis, and manual editing. A map was then developed by assigning lithotopes to facies classes on the basis of lessons derived from the portion of the platform for which we had rigorous conditioning. The new analysis reveals that GBB is essentially a very grainy platform with muddier accumulations only in the lee of substantial island barriers; in this regard Andros Island, which is the largest island on GBB, exerts a direct control over the muddiest portion of GBB. Mudstones, wackestones, and mud-rich packstones cover 7%, 6%, and 15%, respectively, of the GBB platform top. By contrast, mud-poor packstones, grainstones, and rudstones account for 19%, 44%, and 3%, respectively. Of the 44% of the platform-top classified as grainstone, only 4% is composed of 'high-energy' deposits characterized by the development of sandbar complexes. The diversity and size of facies bodies is broadly the same on the eastern and western limb of the GBB platform, though the narrower eastern
Goetz, S. J.; Rogers, B. M.; Mack, M. C.; Goulden, M.; Pastick, N. J.; Berner, L. T.; Fisher, J.
The Arctic and boreal forest biomes have global significance in terms of climate feedbacks associated with land surface interactions with the atmosphere. Changes in Arctic tundra and boreal forest ecosystem productivity and fire disturbance feedbacks have been well documented in recent years, but findings are often only locally relevant and are sometimes inconsistent among research teams. Part of these inconsistencies lie in utilization of different data sets and time periods considered. Integrated approaches are thus needed to adequately address changes in these ecosystems in order to assess consistency and variability of change, as well as ecosystem vulnerability and resiliency across spatial and temporal scales. Ultimately this can best be accomplished via multiple lines of evidence including remote sensing, field measurements and various types of data-constrained models. We will discuss some recent results integrating multiple lines of evidence for directional ecosystem change in the Arctic and boreal forest biomes of North America. There is increasing evidence for widespread spatial and temporal variability in Arctic and boreal ecosystem productivity changes that are strongly influenced by cycles of changing fire disturbance severity and its longer-term implications (i.e legacy effects). Integrated, multi-approach research, like that currently underway as part of the NASA-led Arctic Boreal Vulnerability Experiment (above.nasa.gov), is an effective way to capture the complex mechanisms that drive patterns and directionality of ecosystem structure and function, and ultimately determine feedbacks to environmental change, particularly in the context of global climate change. Additional ongoing ABoVE research will improve our understanding of the consequences of environmental changes underway, as well as increase our confidence in making projections of the ecosystem responses, vulnerability and resilience to change. ABoVE will also build a lasting legacy of
Andrades-Filho, Clódis de Oliveira; Rossetti, Dilce de Fátima; Bezerra, Francisco Hilario Rego; Medeiros, Walter Eugênio; Valeriano, Márcio de Morisson; Cremon, Édipo Henrique; Oliveira, Roberto Gusmão de
Neogene and late Quaternary sedimentary deposits corresponding respectively to the Barreiras Formation and Post-Barreiras Sediments are abundant along the Brazilian coast. Such deposits are valuable for reconstructing sea level fluctuations and recording tectonic reactivation along the passive margin of South America. Despite this relevance, much effort remains to be invested in discriminating these units in their various areas of occurrence. The main objective of this work is to develop and test a new methodology for semi-automated mapping of Neogene and late Quaternary sedimentary deposits in northeastern Brazil integrating geophysical and remote sensing data. The central onshore Paraíba Basin was selected due to the recent availability of a detailed map based on the integration of surface and subsurface geological data. We used airborne gamma-ray spectrometry (i.e., potassium-K and thorium-Th concentration) and morphometric data (i.e., relief-dissection, slope and elevation) extracted from the digital elevation model (DEM) generated by the Shuttle Radar Topography Mission (SRTM). The procedures included: (a) data integration using geographic information systems (GIS); (b) exploratory statistical analyses, including the definition of parameters and thresholds for class discrimination for a set of sample plots; and (c) development and application of a decision-tree classification. Data validation was based on: (i) statistical analysis of geochemical and airborne gamma-ray spectrometry data consisting of K and Th concentrations; and (ii) map validation with the support of a confusion matrix, overall accuracy, as well as quantity disagreement and allocation disagreement for accuracy assessment based on field points. The concentration of K successfully separated the sedimentary units of the basin from Precambrian basement rocks. The relief-dissection morphometric variable allowed the discrimination between the Barreiras Formation and the Post-Barreiras Sediments. In
Tilmann, S. E.; Enslin, W. R.; Hill-Rowley, R.
A computer-based information system is described designed to assist in the integration of commonly available spatial data for regional planning and resource analysis. The Resource Analysis Program (RAP) provides a variety of analytical and mapping phases for single factor or multi-factor analyses. The unique analytical and graphic capabilities of RAP are demonstrated with a study conducted in Windsor Township, Eaton County, Michigan. Soil, land cover/use, topographic and geological maps were used as a data base to develope an eleven map portfolio. The major themes of the portfolio are land cover/use, non-point water pollution, waste disposal, and ground water recharge.
Hakkenberg, C R; Zhu, K; Peet, R K; Song, C
The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly
Fussi, Fabio; Fava, Francesco; Di Mauro, Biagio; Bonomi, Tullia; Fumagalli, Letizia; DI Leo, Margherita; Hamidou Kane, Cheik; Faye, Gayane; Niang, Magatte; Wade, Souleye; Hamidou, Barry; Colombo, Roberto
In several countries of the world the situation of water supply is still critical, far from the international target defined by United Nations for 2015 (Millenium Development Goals) and producing a huge impact on health and living condition of the population. Manual drilling (it means techniques to drill boreholes for water using human or animal power) is well known and practiced for centuries in many countries. In recent years, it has been considered a potential strategy to increase water access in poor countries and has raised the attention of national governments and international organizations. Manual drilling is applicable only where hydrogeological context is suitable, according to the following conditions: thick layers of unconsolidated sediments and shallow water table. Mapping of zones with suitable hydrogeological context has been carried out in several countries in Africa, but the results have evident limitations; previous methods are based on existing direct data and qualitative experience, leading to unreliable interpretation when direct data are limited. This research aims to develop a methodology to estimate shallow hydrogeological features and asses the distribution of suitable zones for manual drilling through the integration of indirect information obtained from remote sensing and other existing source of data. The research is carried out in two different study areas, in Senegal and Guinea (Western Africa), with semi-arid climate, moderate vegetation cover, unconsolidated sandy and clay deposits overlaying sedimentary and igneous rocks A set of variables have been obtained through processing of three categories of data, listed below: - geology, geomorphology, soil and land cover, obtained from existing thematic maps; - vegetation phenology, apparent thermal inertia, and soil moisture, obtained from analysis of multitemporal optical (MOD13Q1), thermal (MOD11A1), and radar (ASAR) remotely sensed data: -morphometric parameters, obtained from public
Ethiopian Journal of Environmental Studies and Management ... technology provides an efficient avenue of assessment of biomass content of any area. ... use data, can be integrated into GIS together with results from remote sensing analysis ...
West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.
West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.
Vahmani, P.; Hogue, T. S.
Regional meteorological models are increasingly being applied in urban areas. Accurate representation of urban surface physical characteristics in these models is critical for predictions of surface-atmosphere fluxes of sensible heat, latent heat, and momentum, which in turn affect weather and climate forecasting capabilities. Yet, the specification of surface parameters largely relies on out-dated land-use maps and lookup tables. In this contribution, we use the Noah LSM (Land Surface Model)-SLUCM (Single Layer Urban Canopy Model) modeling framework to investigate the usefulness of remotely sensed data in the model parameterization and validation processes, the sensitivity of the model to the defined parameters, and the model's performance improvement when the new parameter sets are implemented. Fused Landsat ETM and MODIS data are used to generate high resolution (30 m) spatial maps of monthly GVF (Green Vegetation Fraction), ISA (Impervious Surface Area), LAI (Leaf Area Index), albedo, and emissivity over the Los Angeles metropolitan area, which are then directly implemented in the model simulations. Parameters derived from remote sensing platforms show significant temporal and spatial differences from traditional Noah LSM values. For example, GVF shows significantly less seasonal variability, reflecting the impact of heavy year round irrigation in the study domain, which is not accounted in the default parameters. Assimilating remotely sensed model parameters into Noah/SLUCM results in significant changes in the simulated energy and water fluxes over the study area. The results show a high sensitivity of model simulations to all investigated parameters except for emissivity. Finally, the model's performance is evaluated utilizing Landsat based land surface temperature and evapotranspiration measurements from CIMIS (California Irrigation Management Information System) stations. Results reveal that the surface energy and water budget estimation accuracies are
NASA's Operation IceBridge (OIB), the largest airborne survey of Earth's polar ice uses remote sensing methods to collect data on changing sea and land ice. PolarTREC teacher Kelly McCarthy joined the team during the 2016 Spring Arctic Campaign. This presentation explores ways in which k-12 students were engaged in the work being done by OIB through classroom learning experiences, digital communications, and independent research. Initially, digital communication including chats via NASA's Mission Tools Suite for Education (MTSE) platform was leveraged to engage students in the daily work of OIB. Two lessons were piloted with student groups during the 2016-2017 academic year both for students who actively engaged in communications with the team during the expedition and those who had no prior connections to the field. All of the data collected on OIB missions is stored for public use in a digital portal on the National Snow and Ice Data Center (NSIDC) website. In one lesson, 10th-12th grade students were guided through a tutorial to learn how to access data and begin to develop a story about Greenland's Jakobshavn Glacier using pre-selected data sets, Google's MyMaps app, and independent research methods. In the second lesson, 8th grade students were introduced to remote sensing, first through a discussion on vocabulary using productive talk moves and then via a demonstration using Vernier motion detectors and a graph matching simulation. Students worked in groups to develop procedures to map a hidden surface region (boxed assortment of miscellaneous objects) using a Vernier motion sensor to simulate sonar. Students translated data points collected from the motion sensor into a vertical profile of the simulated surface region. Both lessons allowed students a way to engage in two of the most important components of OIB. The ability to work with real data collected by the OIB team provided a unique context through which students gained skill and overcame challenges in
Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.
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.
Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in
Polarimeter for Remote Sensing Studies 5b. GRANT NUMBER FA9550-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1. Scott Tyo 5e. TASK...and tested at the University of Arizona, and preliminary images are shown in this final report. 15. SUBJECT TERMS Remote Sensing , polarimetry 16...7.0 LWIR Microgrid Polarimeter for Remote Sensing Studies J. Scott Tyo College of Optical Sciences University of Arizona Tucson, AZ, 85721 tyo
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.
Feldman, S.C.; Castor, S.B.; Tingley, J.V.
In 1989 the U.S. Department of Energy filed an application with the U.S. Bureau of Land Management for an administrative land withdrawal of about 4,300 acres bordering the western edge of the Nevada Test Site (NTS) and the southern edge of the Nellis Air Force Range. This area, which is referred to as the Yucca Mountain Addition, includes approximately 400 acres that are being considered as part of a potential repository for high-level nuclear waste at Yucca Mountain. A study of the geology and mineral deposits is required for a land withdrawal request under federal law. The Yucca Mountain Addition mineral evaluation was accomplished in late 1989 by field examination, sample collection, geochemical analysis, the analysis of satellite remote sensing data, and the collection of rock spectra in the field. Data from the Yucca Mountain Addition and from mining districts in the area were collected and analyzed, and the two data sets were then compared. The evaluation was limited to surficial data both at the Yucca Mountain Addition and in the mining districts. Evidence from both geochemical and remote sensing analyses indicate that the potential for mineral deposits is low in the Yucca Mountain Addition
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.
El Ghawaby, M.A.
Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs
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.
Rudd, R. D.; Bowden, L. W.; Colwell, R. N.; Estes, J. E.
A selective bibliography is presented which cites 89 textbooks, monographs, and articles covering introductory and advanced remote sensing techniques, photointerpretation, photogrammetry, and image processing.
The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and
Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W
In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data
The current state of understanding of the biosphere is reviewed, the major scientific issues to be addressed are discussed, and techniques, existing and in need of development, for the science are evaluated. It is primarily concerned with developing the scientific capabilities of remote sensing for advancing the subject. The global nature of the scientific objectives requires the use of space-based techniques. The capability to look at the Earth as a whole was developed only recently. The space program has provided the technology to study the entire Earth from artificial satellites, and thus is a primary force in approaches to planetary biology. Space technology has also permitted comparative studies of planetary atmospheres and surfaces. These studies coupled with the growing awareness of the effects that life has on the entire Earth, are opening new lines of inquiry in science.
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
Summers, R. A.; Smith, W. L.; Short, N. M.
The nature of the U.S. energy problem is examined. Based upon the best available estimates, it appears that demand for OPEC oil will exceed OPEC productive capacity in the early to mid-eighties. The upward pressure on world oil prices resulting from this supply/demand gap could have serious international consequences, both financial and in terms of foreign policy implementation. National Energy Plan objectives in response to this situation are discussed. Major strategies for achieving these objectives include a conversion of industry and utilities from oil and gas to coal and other abundant fuels. Remote sensing from aircraft and spacecraft could make significant contributions to the solution of energy problems in a number of ways, related to exploration of energy-related resources, the efficiency and safety of exploitation procedures, power plant siting, environmental monitoring and assessment, and the transportation infrastructure.
Townsend, Alan R.; Asner, Gregory P.; Bustamante, Mercedes M. C.
Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.
This report summarizes the technical work accomplished under Project THEMIS, A Center for Remote Sensing at the University of Kansas during the...period 16 September 1967 through 15 September 1973. The highlights of the four major areas forming the remote sensing system are presented. A detailed description of the latest radar spectrometer results is presented.
Zhang, Z; Xu, W; Zhou, W; Zhang, L; Xiao, Y; Ouyang, Z; Ou, X
The increasing exploitation of Karst resources is leading to severe environmental impacts, as Karst frequently occurs in the most fragile and vulnerable environments. This paper presents a multi-criteria evaluation (MCE) approach in a spatial context to support Karst rocky desertification (KRD) assessment by integrating remote sensing data with GIS. The study area is located in Wenshan Prefecture, Yunnan Province, Southwest of China. Criteria and impact factors for KRD first were identified and weighted through pairwise comparison method. A GIS fuzzy set membership function was then used to generate gradient effects of each criterion, and a clustering method based on K-mean algorithms was used to classify KRD into several descending rank zones (or levels). Both ROC and error matrix assessments indicated that the MCE approach is better than the NDVI approach. In addition, we found it is useful to integrate the topographic and human disturbance factors into KRD mapping and assessment, compared with most of the previous KRD assessment studies mainly focused on developing vegetation or land cover information in karst regions by using remote sensing alone. Furthermore, the integrated MCE approach is robust, flexible, and easy to be implemented. It also explicitly includes the quantitative and qualitative information, for instance, opinions of decision makers and experts as well as characteristics of the landscape
Falge, Eva; Brümmer, Christian
Park, South Africa, Setting up individual-based models to predict ecosystem dynamics under (post-) disturbance management, Monitoring vegetation amount and heterogeneity using remotely sensed images and aerial photography over several decades to examine time series of land cover change, and Investigations of livelihood strategies with focus on carbon balance components to develop sustainable management strategies for disturbed ecosystems and land use change. Despite recent advances, major innovations in understanding carbon cycle, greenhouse gases, air quality and measures of adaptation to and mitigation of climate change are still limited by the lack of global accessibility and comparability of relevant data (open data issues), long-term and sustainable interdisciplinary and trans-institutional research collaborations, and ongoing effective dialogues on multiple levels (policy, science, society).
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...
Estes, J. E.; Star, J. L.
Remote sensing uses a wide variety of techniques and methods. Resulting data are analyzed by man and machine, using both analog and digital technology. The newest and most important initiatives in the U. S. civilian space program currently revolve around the space station complex, which includes the core station as well as co-orbiting and polar satellite platforms. This proposed suite of platforms and support systems offers a unique potential for facilitating long term, multidisciplinary scientific investigations on a truly global scale. Unlike previous generations of satellites, designed for relatively limited constituencies, the space station offers the potential to provide an integrated source of information which recognizes the scientific interest in investigating the dynamic coupling between the oceans, land surface, and atmosphere. Earth scientist already face problems that are truly global in extent. Problems such as the global carbon balance, regional deforestation, and desertification require new approaches, which combine multidisciplinary, multinational research teams, employing advanced technologies to produce a type, quantity, and quality of data not previously available. The challenge before the international scientific community is to continue to develop both the infrastructure and expertise to, on the one hand, develop the science and technology of remote sensing, while on the other hand, develop an integrated understanding of global life support systems, and work toward a quantiative science of the biosphere.
Parking is an integral part of the traffic system everywhere. Provision of parking facilities to meet peak of demands parking in cities of millions is always a real challenge for traffic and transport experts. Parking demand is a function of population and car ownership which is obtained from traffic statistics. Parking supply in an area is the number of legal parking stalls available in that area. The traditional treatment of the parking studies utilizes data collected either directly from on street counting and inquiries or indirectly from local and national traffic censuses. Both methods consume time, efforts, and funds. Alternatively, it is reasonable to make use of the eventually available data based on remotely sensed data which might be flown for other purposes. The objective of this work is to develop a new approach based on utilization of integration of remotely sensed data, field measurements, censuses and traffic records of the studied area for studying domestic parking problems in residential areas especially in informal areas. Expected outcomes from the research project establish a methodology to manage the issue and to find the reasons caused the shortage in domestics and the solutions to overcome this problems.
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
Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Forkel, Matthias; Tito Rademacher, Tim; Santoro, Maurizio; Tum, Markus; Schmullius, Christiane
Long-term vegetation dynamics are one of the key uncertainties of the carbon cycle. There are large differences in simulated vegetation carbon stocks and fluxes including productivity, respiration and carbon turnover between global vegetation models. Especially the implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current models and their importance at global scale is highly uncertain. These shortcomings have been due to the lack of spatially extensive information on vegetation carbon stocks, which cannot be provided by inventory data alone. Instead, we recently have been able to estimate northern boreal and temperate forest carbon stocks based on radar remote sensing data. Our spatially explicit product (0.01° resolution) shows strong agreement to inventory-based estimates at a regional scale and allows for a spatial evaluation of carbon stocks and dynamics simulated by global vegetation models. By combining this state-of-the-art biomass product and NPP datasets originating from remote sensing, we are able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests along spatial gradients. We observe an increasing turnover rate with colder winter temperatures and longer winters in boreal forests, suggesting frost damage and the trade-off between frost adaptation and growth being important mortality processes in this ecosystem. In contrast, turnover rate increases with climatic conditions favouring drought and insect outbreaks in temperate forests. Investigated global vegetation models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce observation-based spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well in terms of NPP, simulated
Policelli, Frederick S.
Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.
Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert
The Wadden Sea is a large coastal transition area adjoining the southern North Sea uniting ecological key functions with an important role in coastal protection. The region is strictly protected by EU directives and national law and is a UNESCO World Heritage Site, requiring frequent quality assessments and regular monitoring. In 2014 an intertidal bedform area characterised by alternating crests and water-covered troughs on the tidal flats of the island of Norderney (German Wadden Sea sector) was chosen to test different remote sensing methods for habitat mapping: airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye). The results revealed that, although sensitive to different surface qualities, all sensors were able to image the bedforms. A digital terrain model generated from the lidar data shows crests and slopes of the bedforms with high geometric accuracy in the centimetre range, but high costs limit the operation area. TerraSAR-X data enabled identifying the positions of the bedforms reflecting the residual water in the troughs also with a high resolution of up to 1.1 m, but with larger footprints and much higher temporal availability. RapidEye data are sensitive to differences in sediment moisture employed to identify crest areas, slopes and troughs, with high spatial coverage but the lowest resolution (6.5 m). Monitoring concepts may differ in their remote sensing requirements regarding areal coverage, spatial and temporal resolution, sensitivity and geometric accuracy. Also financial budgets limit the selection of sensors. Thus, combining differing assets into an integrated concept of remote sensing contributes to solving these issues.
Tesser, D.; Hoang, L.; McDonald, K. C.
Efforts to improve municipal water supply systems increasingly rely on an ability to elucidate variables that drive hydrologic dynamics within large watersheds. However, fundamental model variables such as precipitation, soil moisture, evapotranspiration, and soil freeze/thaw state remain difficult to measure empirically across large, heterogeneous watersheds. Satellite remote sensing presents a method to validate these spatially and temporally dynamic variables as well as better inform the watershed models that monitor the water supply for many of the planet's most populous urban centers. PALSAR 2 L-band, Sentinel 1 C-band, and SMAP L-band scenes covering the Cannonsville branch of the New York City (NYC) water supply watershed were obtained for the period of March 2015 - October 2017. The SAR data provides information on soil moisture, free/thaw state, seasonal surface inundation, and variable source areas within the study site. Integrating the remote sensing products with watershed model outputs and ground survey data improves the representation of related processes in the Soil and Water Assessment Tool (SWAT) utilized to monitor the NYC water supply. PALSAR 2 supports accurate mapping of the extent of variable source areas while Sentinel 1 presents a method to model the timing and magnitude of snowmelt runoff events. SMAP Active Radar soil moisture product directly validates SWAT outputs at the subbasin level. This blended approach verifies the distribution of soil wetness classes within the watershed that delineate Hydrologic Response Units (HRUs) in the modified SWAT-Hillslope. The research expands the ability to model the NYC water supply source beyond a subset of the watershed while also providing high resolution information across a larger spatial scale. The global availability of these remote sensing products provides a method to capture fundamental hydrology variables in regions where current modeling efforts and in situ data remain limited.
Full Text Available Stipa purpurea is the representative type of alpine grassland in Tibet and the surviving and development material for herdsmen. This paper takes Shenzha County as the research area. Based on the analysis of typical hyperspectral variables sensitive to chlorophyll content of Stipa purpurea, 10 spectral variables with significant correlation with chlorophyll were extracted. The estimation model of chlorophyll was established. The photosynthetic pigment contents in the Shenzha area were calculated by using HJ-1A remote sensing images. The results show that (1 there are significant correlations between chlorophyll content and spectral variables; in particular, the coefficient of Chlb in Stipa purpurea with RVI is the largest (0.728; (2 10 variables are correlated with chlorophyll, and the order of correlation is Chlb > Chla > Chls; (3 for the estimation of Chla, the EVI is the best variable. RVI, NDVI, and VI2 are suitable for Chlb; RVI and NDVI are also suitable for the estimation of Chls; (4 the mean estimated content of Chla in Stipa bungeana is about 4.88 times that of Chlb, while Cars is slightly more than Chlb; (5 the distribution of Chla is opposite to Chlb and Chls content in water area.
Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael
Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.
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.
Murtha, T., Jr.; Duffy, C.; Cook, B. D.; Schroder, W.; Webster, D.; French, K. D.; Alcover, O.; Golden, C.; Balzotti, C.; Shaffer, D.
Relying on a niche inheritance perspective, this paper discusses the long-term spatial and temporal dynamics of land-use management, agricultural decision making and patterns of resource availability in the tropical lowlands of Central America. We introduce and describe ongoing research that addresses a series of long standing questions about coupled natural and human history dynamics in the Central Maya lowlands, emphasizing the role of landscape and region to address these questions. First, we summarize the results of a CNH pilot study focused on the evolution of the regional landscape of Tikal, Guatemala. Particular attention is centered on how we integrated landscape survey, traditional archaeology and soil studies to understand the spatial and temporal dynamics of agricultural land use and intensification over a two thousand period. Additionally, we discuss how these results were integrated into remote sensing, hydrological and erosion models to better understand how past changes in available water and productive land compare to what we know about settlement patterns in the Tikal Region over that same time period. We not only describe how the Maya transformed this landscape, but also how the region influenced changing patterns of settlement and land use. We finish this section with a discussion of some of the unique challenges integrating archaeological information to study CNH dynamics during this pilot study. Second, we introduce a new project designed to `scale up' the pilot study for a macro-regional analysis of the lowland Maya landscape. The new project leverages a uniquely sampled LIDAR data set designed to refine measurements of above ground carbon storage. Our new project quantitatively examines these data for evidence for past human activity. Preliminary results offer a promising path for tightly integrating archaeology, natural science, remote sensing and modeling for studying CNH dynamics in the deep and recent past.
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.
Mustard, J.F.; Sen, A.; Swanson, C.; Mendelsohn, D.
A project to assess the effects of thermal effluent from a electrical generating facility on an estuary is described. The project is designed to integrate remote sensing observations with in situ field data and a computer model system to provide continuous, estuary-wide predictions of the effluent plume location and configurations. Remote sensing data was acquired over the ebb tide cycle by an aircraft-mounted multi-channel imaging spectrometer. A ground truth field program measured water temperature on a series of transects during the overflights. Moored instruments continuously acquired data on currents, salinity, temperature and dissolved oxygen before, during and after the day of the overflight. A hydrodynamic model was used to predict the three-dimensional structure of the currents, temperature and salinity in the estuary. A Lagrangian particle-based trajectory model was used to predict the small scale surface features seen in the overflight images. Results indicate that such a system can provide useful data in support of analyses of thermal effects of the ecology of estuarine environments
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
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.
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...
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.
Aircraft and satellite aerial photographs represent indispensible tools for environmental observation today. They contribute to a systematic inventory of important environmental parameters such as climate, vegetation or surface water. Their great importance lies in the continuous monitoring of large regions so that changes in environmental conditions are quickly detected. This book provides an overview of the capabilities of remote sensing in environmental monitoring and in the recognition of environmental problems as well as of the usefulness of remote sensing data for environmental planning. Also addressed is the role of remote sensing in the monitoring of natural hazards such as earthquakes and volcano eruptions as well as problems of remote sensing technology transfer to developing countries. (orig.) [de
Full Text Available industries. In this paper we introduce the results from a remote sensing campaign performed in September 2001 at night time. For the first time nocturnal light pollution was measured at high spatial and spectral resolution using two airborne hyperspectral sensors, namely the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS and the Visible InfraRed Scanner (VIRS-200. These imagers, generally employed for day-time Earth remote sensing, were flown over the Tuscany coast (Italy on board of a Casa 212/200 airplane from an altitude of 1.5-2.0 km. We describe the experimental activities which preceded the remote sensing campaign, the optimization of sensor configuration, and the images as far acquired. The obtained results point out the novelty of the performed measurements and highlight the need to employ advanced remote sensing techniques as a spectroscopic tool for light pollution monitoring.
We used a combination of data from USDA Forest Service inventories, intensivechronosequences, extensive sites, and satellite remote sensing, to estimate biomassand net primary production (NPP) for the forested region of western Oregon. Thestudy area was divided int...
.... Remote sensing and field surveys were used to determine vegetative cover. In the field, vegetative cover data were collected on systematically allocated plots during the peak of the growing season in 1997...
Michel, N. L.; Wilsey, C.; Burkhalter, C.; Trusty, B.; Langham, G.
Scalable indicators of biodiversity change are critical to reporting overall progress towards national and global targets for biodiversity conservation (e.g. Aichi Targets) and sustainable development (SDGs). These essential biodiversity variables capitalize on new remote sensing technologies and growth of community science participation. Here we present a novel biodiversity metric quantifying resilience of bird communities and, by extension, of their associated ecological communities. This metric adds breadth to the community composition class of essential biodiversity variables that track trends in condition and vulnerability of ecological communities. We developed this index for use with North American grassland birds, a guild that has experienced stronger population declines than any other avian guild, in order to evaluate gains from the implementation of best management practices on private lands. The Bird Community Resilience Index was designed to incorporate the full suite of species-specific responses to management actions, and be flexible enough to work across broad climatic, land cover, and bird community gradients (i.e., grasslands from northern Mexico through Canada). The Bird Community Resilience Index consists of four components: density estimates of grassland and arid land birds; weighting based on conservation need; a functional diversity metric to incorporate resiliency of bird communities and their ecosystems; and a standardized scoring system to control for interannual variation caused by extrinsic factors (e.g., climate). We present an analysis of bird community resilience across ranches in the Northern Great Plains region of the United States. As predicted, Bird Community Resilience was higher in lands implementing best management practices than elsewhere. While developed for grassland birds, this metric holds great potential for use as an Essential Biodiversity Variable for community composition in a variety of habitat.
Ren, Yin; Yan, Jing; Wei, Xiaohua; Wang, Yajun; Yang, Yusheng; Hua, Lizhong; Xiong, Yongzhu; Niu, Xiang; Song, Xiaodong
Research on the effects of urban sprawl on carbon stocks within urban forests can help support policy for sustainable urban design. This is particularly important given climate change and environmental deterioration as a result of rapid urbanization. The purpose of this study was to quantify the effects of urban sprawl on dynamics of forest carbon stock and density in Xiamen, a typical city experiencing rapid urbanization in China. Forest resource inventory data collected from 32,898 patches in 4 years (1972, 1988, 1996 and 2006), together with remotely sensed data (from 1988, 1996 and 2006), were used to investigate vegetation carbon densities and stocks in Xiamen, China. We classified the forests into four groups: (1) forest patches connected to construction land; (2) forest patches connected to farmland; (3) forest patches connected to both construction land and farmland and (4) close forest patches. Carbon stocks and densities of four different types of forest patches during different urbanization periods in three zones (urban core, suburb and exurb) were compared to assess the impact of human disturbance on forest carbon. In the urban core, the carbon stock and carbon density in all four forest patch types declined over the study period. In the suburbs, different urbanization processes influenced forest carbon density and carbon stock in all four forest patch types. Urban sprawl negatively affected the surrounding forests. In the exurbs, the carbon stock and carbon density in all four forest patch types tended to increase over the study period. The results revealed that human disturbance played the dominant role in influencing the carbon stock and density of forest patches close to the locations of human activities. In forest patches far away from the locations of human activities, natural forest regrowth was the dominant factor affecting carbon stock and density. Copyright © 2012 Elsevier Ltd. All rights reserved.
Deines, J. M.; Kendall, A. D.; Butler, J. J., Jr.; Hyndman, D. W.
Irrigation greatly enhances agricultural yields and stabilizes farmer incomes, but overexploitation of water resources has depleted groundwater aquifers around the globe. In much of the High Plains Aquifer (HPA) in the United States, water-level declines threaten the continued viability of agricultural operations reliant on irrigation. Policy and management institutions to address this sustainability challenge differ widely across the HPA and the world. In Kansas, grassroots-driven legislation in 2012 allowed local stakeholder groups to establish Local Enhanced Management Areas (LEMAs) and work with state officials to generate enforceable and monitored water use reduction programs. The pioneering LEMA was formed in 2013, following a popular vote by farmers within a 256 km2 region in northwestern Kansas. The group sought to reduce groundwater pumping by 20% through 2017 in order to stabilize water levels while minimally reducing crop productivity. Initial statistical estimates indicate the LEMA has been successful; planning is underway to extend it for five years (2018-2022) and to implement additional LEMAs in the wider groundwater management district. Here, we assess the efficacy of this first LEMA with coupled crop-hydrology models to quantify water budget impacts and any associated trade-offs in crop productivity. We drive these models with a novel data fusion of water use data and our recent remotely sensed Annual Irrigation Maps (AIM) dataset, allowing detailed tracking of irrigation water in space and time. Results from these process-based models provide detailed insights into changes in the physical system resulting from the LEMA program that can inform future stakeholder-driven management in Kansas and in stressed aquifers around the world.
Full Text Available This paper describes the application of remote sensing techniques, based on SAR interferometry for the intensity zonation of the landslide affecting the Castagnola village (Northern Apennines of Liguria region, Italy. The study of the instability conditions of the landslide started in 2001 with the installation of conventional monitoring systems, such as inclinometers and crackmeters, ranging in time from April 2001 to April 2002, which allowed to define the deformation rates of the landslide and to locate the actual landslide sliding surface, as well as to record the intensity of the damages and cracks affecting the buildings located within the landslide perimeter. In order to investigate the past long-term evolution of the ground movements a PSI (Persistent Scatterers Interferometry analysis has been performed making use of a set of ERS1/ERS2 images acquired in 1992–2001 period. The outcome of the PSI analysis has allowed to confirm the landslide extension as mapped within the official landslide inventory map as well as to reconstruct the past line-of-sight average velocities of the landslide and the time-series deformations. Following the high velocities detected by the PSI, and the extensive damages surveyed in the buildings of the village, the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR system has been installed. The GBInSAR monitoring system has been equipped during October 2008 and three distinct campaigns have been carried out from October 2008 until March 2009. The interpretation of the data has allowed deriving a multi-temporal deformation map of the landslide, showing the up-to-date displacement field and the average landslide velocity. A new landslide boundary has been defined and two landslide sectors characterized by different displacement rates have been identified.
EI Raey, M.
Full text: Basic principles of remote sensing of environment are outlined emphasizing inherent physical and target properties leading to proper identification and classification. Basic processing techniques are discussed. Applications of remote sensing techniques in various aspects of environmental monitoring and assessment is surveyed with emphasis on aspects of main concern to developing communities such as planning, sea level impacts, mine detection and earthquake prediction are all outlined and discussed
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.
Ahmad, T.; Shah, A.
A set of operators of remote sensing applications have been proposed to fulfill most of the Functional Requirements (FR). These operators capture the functions of the applications, which can be considered as the services provided by the applications. In general, a good application meets maximum FR from user. In this paper, we have defined a remote sensing application by a set, having all images created at dissimilar time instances, and each image is categorized into set of different layers. (author)
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.
Rahman, Md Rejaur; Shi, Z H; Chongfa, Cai
This study was an attempt to analyse the regional environmental quality with the application of remote sensing, geographical information system, and spatial multiple criteria decision analysis and, to project a quantitative method applicable to identify the status of the regional environment of the study area. Using spatial multi-criteria evaluation (SMCE) approach with expert knowledge in this study, an integrated regional environmental quality index (REQI) was computed and classified into five levels of regional environment quality viz. worse, poor, moderate, good, and very good. During the process, a set of spatial criteria were selected (here, 15 criterions) together with the degree of importance of criteria in sustainability of the regional environment. Integrated remote sensing and GIS technique and models were applied to generate the necessary factors (criterions) maps for the SMCE approach. The ranking, along with expected value method, was used to standardize the factors and on the other hand, an analytical hierarchy process (AHP) was applied for calculating factor weights. The entire process was executed in the integrated land and water information system (ILWIS) software tool that supports SMCE. The analysis showed that the overall regional environmental quality of the area was at moderate level and was partly determined by elevation. Areas under worse and poor quality of environment indicated that the regional environmental status showed decline in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate, and soil conditions have serious influence on the regional environment condition of the area. Considering the regional characteristics of environmental quality, priority, and practical needs for environmental restoration, the study area was further regionalized into four priority areas which may serve as base areas of decision making for the recovery, rebuilding, and
Jones, A. S.; Andales, A.; McGovern, C.; Smith, G. E. B.; David, O.; Fletcher, S. J.
US agricultural and Govt. lands have a unique co-dependent relationship, particularly in the Western US. More than 30% of all irrigated US agricultural output comes from lands sustained by the Ogallala Aquifer in the western Great Plains. Six US Forest Service National Grasslands reside within the aquifer region, consisting of over 375,000 ha (3,759 km2) of USFS managed lands. Likewise, National Forest lands are the headwaters to many intensive agricultural regions. Our Ogallala Aquifer team is enhancing crop irrigation decision tools with predictive weather and remote sensing data to better manage water for irrigated crops within these regions. An integrated multi-model software framework is used to link irrigation decision tools, resulting in positive management benefits on natural water resources. Teams and teams-of-teams can build upon these multi-disciplinary multi-faceted modeling capabilities. For example, the CSU Catalyst for Innovative Partnerships program has formed a new multidisciplinary team that will address "Rural Wealth Creation" focusing on the many integrated links between economic, agricultural production and management, natural resource availabilities, and key social aspects of govt. policy recommendations. By enhancing tools like these with predictive weather and other related data (like in situ measurements, hydrologic models, remotely sensed data sets, and (in the near future) linking to agro-economic and life cycle assessment models) this work demonstrates an integrated data-driven future vision of inter-meshed dynamic systems that can address challenging multi-system problems. We will present the present state of the work and opportunities for future involvement.
Ke-long Tan; Yu-qing Wan; Sun-xin Sun; Gui-bao Bao; Jing-shui Kuang [Aerophotogrammetry and Remote Sensing Center of China Coal, Xi' an (China)
In China it is important to explore coal prospecting by taking advantage of modern remote sensing and geographic information system technologies. Given a theoretical basis for coal prospecting by remote sensing, the methodologies and existing problems are demonstrated systematically by summarizing past practices of coal prospecting with remote sensing. A new theory of coal prospecting with remote sensing is proposed. In uncovered areas, coal resources can be prospected by direct interpretation. In coal bearing strata of developed areas covered by thin Quaternary strata or vegetation, prospecting for coal can be carried out by indirect interpretation of geomorphology and vegetation. For deeply buried underground deposits, coal prospecting can rely on tectonic structures, interpretation and analysis of new tectonic clues and regularity of coal formation and preservation controlled by tectonic structures. By applying newly hyper-spectral, multi-polarization, multi-angle, multi-temporal and multi-resolution remote sensing data and carrying out integrated analysis of geographic attributes, ground attributes, geophysical exploration results, geochemical exploration results, geological drilling results and remote sensing data by GIS tools, coal geology resources and mineralogical regularities can be explored and coal resource information can be acquired with some confidence. 12 refs., 4 figs., 3 tabs.
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...
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...
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.
Wang, Tianhe; Zhou, Tao; Jia, Xiaodong
The unmanned airborne (UAV) laser spectrum radar has played a leading role in remote sensing because the transmitter and the receiver are together at laser spectrum radar. The advantages of the integrated transceiver laser spectrum radar is that it can be used in the oil and gas pipeline leak detection patrol line which needs the non-contact reflective detection. The UAV laser spectrum radar can patrol the line and specially detect the swept the area are now in no man's land because most of the oil and gas pipelines are in no man's land. It can save labor costs compared to the manned aircraft and ensure the safety of the pilots. The UAV laser spectrum radar can be also applied in the post disaster relief which detects the gas composition before the firefighters entering the scene of the rescue.
Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for the year 2014.
A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave
The theme of IGARSS'99, ``Remote Sensing of the System Earth--A Challenge for the 21st Century,'' shows how earth observation based on satellite remote sensing can significantly contribute to the future study of the environment and the changes it is undergoing, whether from natural causes or human activities. The wide range of topics offers an interdisciplinary approach and suggests integrated techniques and theory in remote sensing are essential for modeling and understanding the environment. Topics covered include: new instrumentation and future systems; high resolution SAR/InSAR; earth system science educational initiative; data fusion; radar sensing of ice sheets; image processing techniques; clouds and ice particles; internal waves; natural hazards and disaster monitoring; advanced passive and active sensors and sensor calibration; radar assessment of rain, oil spills and natural slicks; data standards and distribution; and vegetation monitoring using BRDF approaches.
Henderson, Frederick B.
Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources
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
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
This slide presentation reviews current NASA Earth Remote Sensing observations in specific reference to improving public health information in view of pollen sensing. While pollen sampling has instrumentation, there are limitations, such as lack of stations, and reporting lag time. Therefore it is desirable use remote sensing to act as early warning system for public health reasons. The use of Juniper Pollen was chosen to test the possibility of using MODIS data and a dust transport model, Dust REgional Atmospheric Model (DREAM) to act as an early warning system.
The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.
Al-Wassai, Firouz Abdullah; Kalyankar, N. V.
Several remote sensing software packages are used to the explicit purpose of analyzing and visualizing remotely sensed data, with the developing of remote sensing sensor technologies from last ten years. Accord-ing to literature, the remote sensing is still the lack of software tools for effective information extraction from remote sensing data. So, this paper provides a state-of-art of multi-sensor image fusion technologies as well as review on the quality evaluation of the single image or f...
Full Text Available Portraying urban functional zones provides useful insights into understanding complex urban systems and establishing rational urban planning. Although several studies have confirmed the efficacy of remote sensing imagery in urban studies, coupling remote sensing and new human sensing data like mobile phone positioning data to identify urban functional zones has still not been investigated. In this study, a new framework integrating remote sensing imagery and mobile phone positioning data was developed to analyze urban functional zones with landscape and human activity metrics. Landscapes metrics were calculated based on land cover from remote sensing images. Human activities were extracted from massive mobile phone positioning data. By integrating them, urban functional zones (urban center, sub-center, suburbs, urban buffer, transit region and ecological area were identified by a hierarchical clustering. Finally, gradient analysis in three typical transects was conducted to investigate the pattern of landscapes and human activities. Taking Shenzhen, China, as an example, the conducted experiment shows that the pattern of landscapes and human activities in the urban functional zones in Shenzhen does not totally conform to the classical urban theories. It demonstrates that the fusion of remote sensing imagery and human sensing data can characterize the complex urban spatial structure in Shenzhen well. Urban functional zones have the potential to act as bridges between the urban structure, human activity and urban planning policy, providing scientific support for rational urban planning and sustainable urban development policymaking.
Rodríguez-González, Patricia María; Albuquerque, António; Martínez-Almarza, Miguel; Díaz-Delgado, Ricardo
Implementing long-term monitoring programs that effectively inform conservation plans is a top priority in environmental management. In floodplain forests, historical pressures interplay with the complex multiscale dynamics of fluvial systems and require integrative approaches to pinpoint drivers for their deterioration and ecosystem services loss. Combining a conceptual framework such as the Driver-Pressure-State-Impact-Response (DPSIR) with the development of valid biological indicators can contribute to the analysis of the driving forces and their effects on the ecosystem in order to formulate coordinated conservation measures. In the present study, we evaluate the initial results of a decade (2004-2014) of floodplain forest monitoring. We adopted the DPSIR framework to summarize the main drivers in land use and environmental change, analyzed the effects on biological indicators of foundation trees and compared the consistency of the main drivers and their effects at two spatial scales. The monitoring program was conducted in one of the largest and best preserved floodplain forests in SW Europe located within Doñana National Park (Spain) which is dominated by Salix atrocinerea and Fraxinus angustifolia. The program combined field (in situ) surveys on a network of permanent plots with several remote sensing sources. The accuracy obtained in spectral classifications allowed shifts in species cover across the whole forest to be detected and assessed. However, remote sensing did not reflect the ecological status of forest populations. The field survey revealed a general decline in Salix populations, especially in the first five years of sampling -a factor probably associated with a lag effect from past human impact on the hydrology of the catchment and recent extreme climatic episodes (drought). In spite of much reduced seed regeneration, a resprouting strategy allows long-lived Salix individuals to persist in complex spatial dynamics. This suggests the beginning
Full Text Available Net Primary Production, NPP, is one of the most important variables characterizing the performance of an ecosystem. It is the difference between the total carbon uptake from the air through photosynthesis and the carbon loss due to respiration by living plants. However, field measurements of NPP are time-consuming and expensive. Current techniques are therefore not useful for obtaining NPP estimates over large areas. By combining the remote sensing and GIS technology and modelling, we can estimate NPP of a large ecosystem with a little ease. This paper discusses the use of a process based physiological sunshade canopy models in estimating NPP of Lore Lindu National Park (LLNP. The discussion includes on how to parameterize the models and how to scale up from leaf to the canopy. The version documented in this manuscript is called NetPro Model, which is a potential NPP model where water effect is not included yet. The model integrates CIS and the use of Remote Sensing, and written in Visual Basic 6.0 programming language and Map Objects 2.1. NetPro has the capability of estimating NPP of Cs vegetation under present environmental condition and under future scenarios (increasing [CO2], increasing temperature and increasing or decreasing leaf nitrogen level. Based on site-measured parameterisation of VaM* (Photosynthetic capacity, /Jj (Respiration and leaf nitrogen ONi, the model was run under increasing CO2 level and temperature and varied leaf nitrogen. The output of the semi-mechanistic modelling is radiation use efficiency (?. Analysis of remote sensing data give Normalized Difference Vegetation Index (NDVI and related Leaf Area Index (LAI and traction of absorbed Photosynthetically Active Radiation (/M > AK. Climate data are obtained from 12 meteorological stations around die parks, which includes global radiations, minimum and maximum temperature. CO2 absorbed by vegetation (Gross Primary Production, GPP is then calculated using the above
M. A. Lazaridou
Full Text Available Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc, and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers in the Lab. of Photogrammetry – Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.
van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie
workflows should be multidisciplinary and remote sensing data should be integrated with field observations and subsurface geophysical data to monitor and understand geologic processes.
B.E. Law; D. Turner; M. Goeckede
GOAL: To develop and apply an approach to quantify and understand the regional carbon balance of the west coast states for the North American Carbon Program. OBJECTIVE: As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 in the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance. APPROACH: In performing the regional analysis, the research plan for the bottom-up approach uses a nested hierarchy of observations that include AmeriFlux data (i.e., net ecosystem exchange (NEE) from eddy covariance and associated biometric data), intermediate intensity inventories from an extended plot array partially developed from the PI's previous research, Forest Service FIA and CVS inventory data, time since disturbance, disturbance type, and cover type from Landsat developed in this study, and productivity estimates from MODIS algorithms. The BIOME-BGC model is used to integrate information from these sources and quantify C balance across the region. The inverse modeling approach assimilates flux data from AmeriFlux sites, high precision CO2 concentration data from AmeriFlux towers and four new calibrated CO2 sites
Oo, Tin Ko
The Mogok Stone Tract area has long been known for world famous finest ruby since 1597. The Mogok area lies in northern Myanmar and is located at about 205.99km northeast from Mandalay, the second largest city of Myanmar. The Mogok Group of metasedimentary rocks is divided into four units: (1) Wabyudaung Marble, (2) Ayenyeinchantha Calc-silicate, (3) Gwebin Quartzite, and (4) Kabe Gneiss. Igneous rocks in the Mogok area are classified into two units: (1) Kabaing Granite and (2) Pingutaung Leucogranite. The Mogok area has a complex structure involving several folds and faults. Using marbles and calc-silicates as marker horizons, a series of anticline and syncline can be identified such as Mogok syncline, Ongaing anticline, Bawpadan syncline, and Kyatpyin anticline. All the foldings show a low-angle plunge to the south. The main precious stones of the Mogok area are ruby and sapphire; and the other important semi-precious stones are spinel, topaz, peridot, garnet, apatite, beryl, tourmaline (rubellite), quartz, diopside, fluorite, and enstatite. Geological and remote sensing data are processed to extract the indicative features of gem mineralized areas: lithology, structure, and hydrothermal alteration. Density slice version of Landsat ETM band ratios 5/7 is used to map clay alterations. Filtering Landsat ETM band 5 by using edge detection filter is applied for lineament mapping. Spatial integration of various geoscience and remote sensing data sets such as geological maps, Landsat ETM images, and the location map of gem mines show the distribution of alteration zones associated with the gem mineralization in the study area. Geographic Information System (GIS) model has been designed and implemented by ARCVIEW software package based on the overlay of lithologic, lineament, and alteration vector maps. This process has resulted in delineation of most promising areas of probable gem mineralized zones as on the output map.
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.
Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form
Teng, W. L.; de Jeu, R. A.; Doraiswamy, P. C.; Kempler, S. J.; Shannon, H. D.
A primary goal of the U.S. Department of Agriculture (USDA) is to expand markets for U.S. agricultural products and support global economic development. The USDA World Agricultural Outlook Board (WAOB) supports this goal by developing monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Because weather has a significant impact on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments, in a GIS-based, Global Agricultural Decision Support Environment (GLADSE). The main objective of this project, thus, is to improve WAOB's estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE. Soil moisture is a primary data gap at WAOB. Soil moisture data, generated by the Land Parameter Retrieval Model (LPRM, developed by NASA GSFC and Vrije Universiteit Amsterdam) and customized to WAOB's requirements, will be directly integrated into GLADSE, as well as indirectly by first being integrated into USDA Agricultural Research Service (ARS)'s Environmental Policy Integrated Climate (EPIC) crop model. The LPRM-enhanced EPIC will be validated using three major agricultural regions important to WAOB and then integrated into GLADSE. Project benchmarking will be based on retrospective analyses of WAOB's analog year comparisons. The latter are between a given year and historical years with similar weather patterns. WAOB is the focal point for economic intelligence within the USDA. Thus, improving WAOB's agricultural estimates by integrating NASA satellite observations and model outputs will visibly demonstrate the value of NASA resources and maximize the societal benefits of NASA investments.
Li, Chong-yang; Hao, Yan-hui; Xu, Peng-mei; Wang, Dong-jie; Ma, Li-na; Zhao, Ying-long
For the high precision requirement of spaceborne low light remote sensing camera optical registration, optical registration of dual channel for CCD and EMCCD is achieved by the high magnification optical registration system. System integration optical registration and accuracy of optical registration scheme for spaceborne low light remote sensing camera with short focal depth and wide field of view is proposed in this paper. It also includes analysis of parallel misalignment of CCD and accuracy of optical registration. Actual registration results show that imaging clearly, MTF and accuracy of optical registration meet requirements, it provide important guarantee to get high quality image data in orbit.
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.
Full Text Available Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers.
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.
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.
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
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...
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...... will be able to record the spectral signatures of water and land surfaces with a pixel resolution of around 15 cm, whereas the thermal camera will sense water and land surface temperature with a resolution of 40 cm. Post-processing of data from the thermal camera will allow retrieving vegetation and soil...
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
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.
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…
Burton, E. A.; Pickles, W. L.; Gouveia, F. J.; Bogen, K. T.; Rau, G. H.; Friedmann, J.
Correct assessment of the potential for CO2 leakage to the atmosphere or near surface is key to managing the risk associated with CO2 storage. Catastrophic, point-source leaks, diffuse seepage, and low leakage rates all merit assessment. Smaller leaks may be early warnings of catastrophic failures, and may be sufficient to damage natural vegetation or crops. Small leaks also may lead to cumulative build-up of lethal levels of CO2 in enclosed spaces, such as basements, groundwater-well head spaces, and caverns. Working with our ZERT partners, we are integrating a variety of monitoring and modeling approaches to understand how to assess potential health, property and environmental risks across this spectrum of leakage types. Remote sensing offers a rapid technique to monitor large areas for adverse environmental effects. If it can be deployed prior to the onset of storage operations, remote sensing also can document baseline conditions against which future claims of environmental damage can be compared. LLNL has been using hyperspectral imaging to detect plant stress associated with CO2 gas leakage, and has begun investigating use of NASA's new satellite or airborne instrumentation that directly measures gas compositions in the atmosphere. While remote sensing techniques have been criticized as lacking the necessary resolution to address environmental problems, new instruments and data processing techniques are demonstrated to resolve environmental changes at the scale associated with gas-leakage scenarios. During the shallow low-flow- CO2 release field experiments planned by ZERT, for the first time, we will have the opportunity to ground- truth hyperspectral data by simultaneous measurement of changes in hyperspectral readings, soil and root zone microbiology, ambient air, soil and aquifer CO2 concentrations. When monitoring data appear to indicate a CO2 leakage event, risk assessment and mitigation of that event requires a robust and nearly real-time method for
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
The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The 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 are 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 is developed
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.
Brown, M. E.; Racoviteanu, A. E.; Tarboton, D. G.; Gupta, A. Sen; Nigro, J.; Policelli, F.; Habib, S.; Tokay, M.; Shrestha, M. S.; Bajracharya, S.; Hummel, P.; Gray, M.; Duda, P.; Zaitchik, B.; Mahat, V.; Artan, G.; Tokar, S.
Quantification of the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Hindu Kush Himalayan (HKH) region is important for decision-making in water sensitive sectors, and for water resources management and flood risk reduction. In this area, access to and monitoring of the glaciers and their melt outflow is challenging due to difficult access, thus modeling based on remote sensing offers the potential for providing information to improve water resources management and decision making. This paper describes an integrated modeling system developed using downscaled NASA satellite based and earth system data products coupled with in-situ hydrologic data to assess the contribution of snow and glaciers to the flows of the rivers in the HKH region. Snow and glacier melt was estimated using the Utah Energy Balance (UEB) model, further enhanced to accommodate glacier ice melt over clean and debris-covered tongues, then meltwater was input into the USGS Geospatial Stream Flow Model (GeoSFM). The two model components were integrated into Better Assessment Science Integrating point and Nonpoint Sources modeling framework (BASINS) as a user-friendly open source system and was made available to countries in high Asia. Here we present a case study from the Langtang Khola watershed in the monsoon-influenced Nepal Himalaya, used to validate our energy balance approach and to test the applicability of our modeling system. The snow and glacier melt model predicts that for the eight years used for model evaluation (October 2003-September 2010), the total surface water input over the basin was 9.43 m, originating as 62% from glacier melt, 30% from snowmelt and 8% from rainfall. Measured streamflow for those years were 5.02 m, reflecting a runoff coefficient of 0.53. GeoSFM simulated streamflow was 5.31 m indicating reasonable correspondence between measured and model confirming the capability of the integrated system to provide a quantification of
Brown, M. E.; Racoviteanu, A. E.; Tarboton, D. G.; Sen Gupta, A.; Nigro, J.; Policelli, F.; Habib, S.; Tokay, M.; Shrestha, M. S.; Bajracharya, S.
Quantification of the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Hindu Kush Himalayan (HKH) region is important for decision-making in water sensitive sectors, and for water resources management and flood risk reduction. In this area, access to and monitoring of the glaciers and their melt outflow is challenging due to difficult access, thus modeling based on remote sensing offers the potential for providing information to improve water resources management and decision making. This paper describes an integrated modeling system developed using downscaled NASA satellite based and earth system data products coupled with in-situ hydrologic data to assess the contribution of snow and glaciers to the flows of the rivers in the HKH region. Snow and glacier melt was estimated using the Utah Energy Balance (UEB) model, further enhanced to accommodate glacier ice melt over clean and debris-covered tongues, then meltwater was input into the USGS Geospatial Stream Flow Model (Geo- SFM). The two model components were integrated into Better Assessment Science Integrating point and Nonpoint Sources modeling framework (BASINS) as a user-friendly open source system and was made available to countries in high Asia. Here we present a case study from the Langtang Khola watershed in the monsoon-influenced Nepal Himalaya, used to validate our energy balance approach and to test the applicability of our modeling system. The snow and glacier melt model predicts that for the eight years used for model evaluation (October 2003-September 2010), the total surface water input over the basin was 9.43 m, originating as 62% from glacier melt, 30% from snowmelt and 8% from rainfall. Measured streamflow for those years were 5.02 m, reflecting a runoff coefficient of 0.53. GeoSFM simulated streamflow was 5.31 m indicating reasonable correspondence between measured and model confirming the capability of the integrated system to provide a quantification
van Genderen, J.L.
A preliminary reconnaissance is being carried out to study the methods and procedures most useful for the detection of vegetation stress resulting from the various forms of environmental pollution, in the industrial area of Teesside, NE England, by means of a multiband remote sensing programme.
Li, Z.; Zhang, Y.; Hong, J.
Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF), whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.
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...
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
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...
Full Text Available Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF, whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.
Su, Z.; Troch, P.A.A.
In order to quantify the rates of the exchanges of energy and matter among hydrosphere, biosphere and atmosphere, quantitative description of land surface processes by means of measurements at different scales are essential. Quantitative remote sensing plays an important role in this respect. The
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.
Semiconductor injection lasers are required for implementing virtually all spaceborne remote sensing systems. Their main advantages are high reliability and efficiency, and their main roles are envisioned in pumping and injection locking of solid state lasers. In some shorter range applications they may even be utilized directly as the sources.
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 ...
Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA)...
Golberg, Mark; Polani, Sagi; Ozana, Nisan; Beiderman, Yevgeny; Garcia, Javier; Ruiz-Rivas Onses, Joaquin; Sanz Sabater, Martin; Shatsky, Max; Zalevsky, Zeev
In this paper we present the usage of photonic remote laser based device for sensing nano-vibrations for detection of muscle contraction and fatigue, eye movements and in-vivo estimation of glucose concentration. The same concept is also used to realize a remote optical stethoscope. The advantage of doing the measurements from a distance is in preventing passage of infections as in the case of optical stethoscope or in the capability to monitor e.g. sleep quality without disturbing the patient. The remote monitoring of glucose concentration in the blood stream and the capability to perform opto-myography for the Messer muscles (chewing) is very useful for nutrition and weight control. The optical configuration for sensing the nano-vibrations is based upon analyzing the statistics of the secondary speckle patterns reflected from various tissues along the body of the subjects. Experimental results present the preliminary capability of the proposed configuration for the above mentioned applications.
Full Text Available Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high- and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove
Gerstl, S.A.; Cooke, B.J.; Henderson, B.G.; Love, S.P.; Zardecki, A.
This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The science and technology of satellite remote sensing is an emerging interdisciplinary field that is growing rapidly with many global and regional applications requiring quantitative sensing of earth`s surface features as well as its atmosphere from space. It is possible today to resolve structures on the earth`s surface as small as one meter from space. If this high spatial resolution is coupled with high spectral resolution, instant object identification can also be achieved. To interpret these spectral signatures correctly, it is necessary to perform a computational correction on the satellite imagery that removes the distorting effects of the atmosphere. This project studied such new concepts and applied innovative new approaches in remote sensing science.
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...
Mapping water use and drought with satellite remote sensing. Martha C. Anderson, Bill Kustas, Feng Gao, Kate Semmens. USDA-Agricultural Research Service Hydrology and Remote Sensing Laboratory, Beltsville, MD. Chris Hain NOAA-NESDIS
Opportunities for Increasing Societal Value of Remote Sensing Data in South Africa's Strategic Development Priorities: A Review. ... Despite the enormous capital required to fund remote sensing initiatives, governments ... HOW TO USE AJOL.
Assessing the accuracy of remote sensing techniques in vegetation fractions estimation. ... This study aimed at exploring different remote sensing (RS) techniques for quantitatively measuring vegetation and bare soil ... HOW TO USE AJOL.
-Natal and MONDI Business Paper have recently embarked on a remote sensing cooperative. The primary focus of this cooperative is to explore the potential benefits associated with using remote sensing for forestry-related activities.
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.
Carrino, Thais Andressa; Crósta, Alvaro Penteado; Toledo, Catarina Labouré Bemfica; Silva, Adalene Moreira
Remote sensing is a strategic key tool for mineral exploration, due to its capacity of detecting hydrothermal alteration minerals or alteration mineral zones associated with different types of mineralization systems. A case study of an epithermal system located in southern Peru is presented, aimed at the characterization of mineral assemblies for discriminating potential high sulfidation epithermal targets, using hyperspectral imagery integrated with petrography, XRD and magnetic data. HyMap images were processed using the Mixture Tuned Matched Filtering (MTMF) technique for producing alteration map in the Chapi Chiara epithermal gold prospect. Extensive areas marked by advanced argillic alteration (alunite-kaolinite-dickite ± topaz) were mapped in detail, as well as limited argillic (illite-smectite) and propylitic (chlorite spectral domain) alteration. The magmatic-hydrothermal processes responsible for the formation of hypogene minerals were also related to the destruction of ferrimagnetic minerals (e.g., magnetite) of host rocks such as andesite, and the remobilization/formation of paramagnetic Fe-Ti oxides (e.g., rutile, anatase). The large alteration zones of advanced argillic alteration are controlled by structures related to a regional NW-SE trend, and also by local NE-SW and ENE-WSW ones.
Full Text Available Hydrological predictions in ungauged lakes are one of the most important issues in hydrological sciences. The habitat of the Relict Gull (Larus relictus in the Erdos Larus relictus National Nature Reserve (ELRNNR has been seriously endangered by lake shrinkage, yet the hydrological processes in the catchment are poorly understood due to the lack of in-situ observations. Therefore, it is necessary to assess the variation in lake streamflow and its drivers. In this study, we employed the remote sensing technique and empirical equation to quantify the time series of lake water budgets, and integrated a water balance model and climate elasticity method to further examine ELRNNR basin streamflow variations from1974 to 2013. The results show that lake variations went through three phases with significant differences: The rapidly expanding sub-period (1974–1979, the relatively stable sub-period (1980–1999, and the dramatically shrinking sub-period (2000–2013. Both climate variation (expressed by precipitation and evapotranspiration and human activities were quantified as drivers of streamflow variation, and the driving forces in the three phases had different contributions. As human activities gradually intensified, the contributions of human disturbances on streamflow variation obviously increased, accounting for 22.3% during 1980–1999 and up to 59.2% during 2000–2013. Intensified human interferences and climate warming have jointly led to the lake shrinkage since 1999. This study provides a useful reference to quantify lake streamflow and its drivers in ungauged basins.
Yeo, I. Y.
We report the recent progress on our effort to improve the mapping of wetland dynamics and the modelling of its functioning and hydrological connection to the downstream waters. Our study focused on the Coastal Plain of the Chesapeake Bay Watershed (CBW), the Delmarva Peninsula, where the most of wetlands in CBW are densely distributed. The wetland ecosystem plays crucial roles in improving water quality and ecological integrity for the downstream waters and the Chesapeake Bay, and headwater wetlands in the region, such as Delmarva Bay, are now subject to the legal protection under the Clean Water Rules. We developed new wetland maps using time series Landsat images and a highly accurate LiDAR map over last 30 years. These maps show the changes in surface water fraction at a 30-m grid cell at annual time scale. Using GIS, we analyse these maps to characterize changing dynamics of wetland inundation due to the physical environmental factors (e.g., weather variability, tide) and assessed the hydrological connection of wetlands to the downstream water at the watershed scale. Focusing on the two adjacent watersheds in the upper region of the Choptank River Basin, we study how wetland inundation dynamics and the hydrologic linkage of wetlands to downstream water would vary by the local hydrogeological setting and attempt to identify the key landscape factors affecting the wetland ecosystems and functioning. We then discuss the potential of using remote sensing products to improve the physical modelling of wetlands from our experience with SWAT (Soil and Water Assessment Tool).
Grecchi, Rosana Cristina; Beuchle, René; Shimabukuro, Yosio Edemir; Aragão, Luiz E. O. C.; Arai, Egidio; Simonetti, Dario; Achard, Frédéric
Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the
Grecchi, Rosana Cristina; Beuchle, René; Shimabukuro, Yosio Edemir; Aragão, Luiz E O C; Arai, Egidio; Simonetti, Dario; Achard, Frédéric
Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase
Full Text Available This paper introduces the processing technology of high resolution remote sensing image, the specific making process of tourism map and different remote sensing data in the key application of tourism planning and so on. Remote sensing extracts agricultural tourism planning information, improving the scientificalness and operability of agricultural tourism planning. Therefore remote sensing image in the application of agricultural tourism planning will be the inevitable trend of tourism development.
Shamin Roman; Alberto Gabriel Enrike; Uryngaliyeva Ayzhana; Semenov Aleksandr
The article considers the issues of optimizing the use of remote sensing data. Built a mathematical model to describe the economic effect of the use of remote sensing data. It is shown that this model is incorrect optimisation task. Given a numerical method of solving this problem. Also discusses how to optimize organizational structure by using genetic algorithm based on remote sensing. The methods considered allow the use of remote sensing data in an optimal way. The proposed mathematical m...
Sebastian Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez
The island of Puerto Rico has both a high population density and a long history of ineffective land use planning. This study integrates geospatial technology and population census data to understand how people use and develop the lands. We define three new regions for Puerto Rico: Urban (16%), Densely Populated Rural (36%), and Sparsely Populated Rural (48%). Eleven...
Pryse-Phillips, A.; Woolgar, R. [Hatch Ltd., St. John' s, NL (Canada); Puestow, T.; Warren, S. [Memorial Univ. of Newfoundland, St. John' s, NL (Canada). C-Core; Rogers, K. [Nalcor Energy, St. John' s, NL (Canada); Khan, A. [Government of Newfoundland and Labrador, St. Johns, NL (Canada)
There has been an increase in the earth observation missions providing satellite imagery for operational monitoring applications. This technique has been found to be especially useful for the surveillance of large, remote areas, which is challenging to achieve in a cost-effective manner by conventional field-based or aerial means. This paper discussed the utility of satellite-based monitoring for different applications relevant to hydrology and water resources management. Emphasis was placed on the monitoring of river ice covers in near, real-time and water resources management. The paper first outlined river ice monitoring using remote sensing on the Lower Churchill River. The benefits of remote sensing over traditional survey methods for the dam industry was then outlined. Satellite image acquisition and interpretation for the Churchill River was then presented. Several images were offered. Watershed physiographic characterization using remote sensing was also described. It was concluded that satellite imagery proved to be a useful tool to develop physiographic characteristics when conducting rainfall-runoff modelling. 3 refs., 1 tab., 11 figs.
Maresca, P. A.; Lefler, R. M.
The requirements of potential users were considered in the design of an integrated data base management system, developed to be independent of any specific computer or operating system, and to be used to support investigations in weather and climate. Ultimately, the system would expand to include data from the agriculture, hydrology, and related Earth resources disciplines. An overview of the system and its capabilities is presented. Aspects discussed cover the proposed interactive command language; the application program command language; storage and tabular data maintained by the regional data base management system; the handling of data files and the use of system standard formats; various control structures required to support the internal architecture of the system; and the actual system architecture with the various modules needed to implement the system. The concepts on which the relational data model is based; data integrity, consistency, and quality; and provisions for supporting concurrent access to data within the system are covered in the appendices.
Walker, A.S.; Robinove, Charles J.
Remote sensing techniques are valuable for locating, assessing, and monitoring desertification. Remotely sensed data provide a permanent record of the condition of the land in a format that allows changes in land features and condition to be measured. The annotated bibliography of 118 items discusses remote sensing methods that may be applied to desertification studies.
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.
S. Healey; P. Patterson; S. Urbanski
Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...
Badar, Bazigha; Romshoo, Shakil A; Khan, M A
Dal Lake, a cradle of Kashmiri civilization has strong linkage with socioeconomics of the state of Jammu and Kashmir. During last few decades, anthropogenic pressures in Dal Lake Catchment have caused environmental deterioration impairing, inter-alia, sustained biotic communities and water quality. The present research was an integrated impact analysis of socioeconomic and biophysical processes at the watershed level on the current status of Dal Lake using multi-sensor and multi-temporal satellite data, simulation modelling together with field data verification. Thirteen watersheds (designated as 'W1-W13') were identified and investigated for land use/land cover change detection, quantification of erosion and sediment loads and socioeconomic analysis (total population, total households, literacy rate and economic development status). All the data for the respective watersheds was integrated into the GIS environment based upon multi-criteria analysis and knowledge-based weightage system was adopted for watershed prioritization based on its factors and after carefully observing the field situation. The land use/land cover change detection revealed significant changes with a uniform trend of decreased vegetation and increased impervious surface cover. Increased erosion and sediment loadings were recorded for the watersheds corresponding to their changing land systems, with bare and agriculture lands being the major contributors. The prioritization analysis revealed that W5 > W2 > W6 > W8 > W1 ranked highest in priority and W13 > W3 > W4 > W11 > W7 under medium priority. W12 > W9 > W10 belonged to low-priority category. The integration of the biophysical and the socioeconomic environment at the watershed level using modern geospatial tools would be of vital importance for the conservation and management strategies of Dal Lake ecosystem.
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
Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Fielding, E. J.; Agram, P.; Manipon, G.; Stough, T. M.; Simons, M.; Rosen, P. A.; Wilson, B. D.; Poland, M. P.; Cervelli, P. F.; Cruz, J.
Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR) and Continuous Global Positioning System (CGPS) are now important elements in our toolset for monitoring earthquake-generating faults, volcanic eruptions, hurricane damage, landslides, reservoir subsidence, and other natural and man-made hazards. Geodetic imaging's unique ability to capture surface deformation with high spatial and temporal resolution has revolutionized both earthquake science and volcanology. Continuous monitoring of surface deformation and surface change before, during, and after natural hazards improves decision-making from better forecasts, increased situational awareness, and more informed recovery. However, analyses of InSAR and GPS data sets are currently handcrafted following events and are not generated rapidly and reliably enough for use in operational response to natural disasters. Additionally, the sheer data volumes needed to handle a continuous stream of InSAR data sets also presents a bottleneck. It has been estimated that continuous processing of InSAR coverage of California alone over 3-years would reach PB-scale data volumes. Our Advanced Rapid Imaging and Analysis for Monitoring Hazards (ARIA-MH) science data system enables both science and decision-making communities to monitor areas of interest with derived geodetic data products via seamless data preparation, processing, discovery, and access. We will present our findings on the use of hybrid-cloud computing to improve the timely processing and delivery of geodetic data products, integrating event notifications from USGS to improve the timely processing for response, as well as providing browse results for quick looks with other tools for integrative analysis.
Riccio, Giovanni; Gennarelli, Claudio
A Trihedral Corner Reflector (TCR) is formed by three mutually orthogonal metal plates of various shapes and is a very important scattering structure since it exhibits a high monostatic Radar Cross Section (RCS) over a wide angular range. Moreover it is a handy passive device with low manufacturing costs and robust geometric construction, the maintenance of its efficiency is not difficult and expensive, and it can be used in all weather conditions (i.e., fog, rain, smoke, and dusty environment). These characteristics make it suitable as reference target and radar enhancement device for satellite- and ground-based microwave remote sensing techniques. For instance, TCRs have been recently employed to improve the signal-to-noise ratio of the backscattered signal in the case of urban ground deformation monitoring  and dynamic survey of civil infrastructures without natural corners as the Musmeci bridge in Basilicata, Italy . The region of interest for the calculation of TCR's monostatic RCS is here confined to the first quadrant containing the boresight direction. The backscattering term is presented in closed form by evaluating the far-field scattering integral involving the contributions related to the direct illumination and the internal bouncing mechanisms. The Geometrical Optics (GO) laws allow one to determine the field incident on each TCR plate and the patch (integration domain) illuminated by it, thus enabling the use of a Physical Optics (PO) approximation for the corresponding surface current densities to consider for integration on each patch. Accordingly, five contributions are associated to each TCR plate: one contribution is due to the direct illumination of the whole internal surface; two contributions originate by the impinging rays that are simply reflected by the other two internal surfaces; and two contributions are related to the impinging rays that undergo two internal reflections. It is useful to note that the six contributions due to the
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.
Faundeen, John L.; Longhenry, Ryan
The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.
Steinmaus, K.; Robert, B.; Berezin, S.A.
In June and July of 1997, the US Department of Energy, in cooperation with the Republic of Kazakhstan Ministry of Science - Academy of Science conducted a remote sensing mission to Kazakhstan. The mission was conducted as a technology demonstration under a Memorandum of Understanding between the United States Department of Energy and the Republic of Kazakhstan's Ministry of science - Academy of Science. The mission was performed using a US Navy P-3 Orion aircraft and imaging capabilities developed by the Department of Energy's Office of Non-proliferation and National Security. The imaging capabilities consisted of two imaging pods - a synthetic aperture radar (SAR) pod and a multi sensor imaging pod (MSI). Seven experiments were conducted to demonstrate how remote sensing can be used to support city planning, land cover mapping, mineral exploration, and non-proliferation monitoring. Results of the mission will be presented
Although the Federation does not sponsor or undertake surveillance and remote sensing research and development projects, it is a potential user of remote sensing equipment when responding to oil spills. Indeed, the Federation has already made use of suitably equipped aircraft on a number of occasions in Europe. Several countries in north west Europe, viz. France, Germany, Netherlands, Norway, Sweden and the U.K., operate aircraft fitted with broadly similar systems comprising side-looking airborne radar (SLAR), infra-red line scanners (IRLS) and ultra-violet line scanners (UVLS). These aircraft are used routinely for the detection of operational discharges of oil from ships in violation of the International Convention on the Prevention of Pollution from Ships 73/78 (MARPOL 73/78)
Chang, Sheng-Huei; Rubin, Tod D.
Traditional commercial remote sensing has focused on the geologic market, with primary focus on mineral identification and mapping in the visible through short-wave infrared spectral regions (0.4 to 2.4 microns). Commercial remote sensing users now demand airborne scanning capabilities spanning the entire wavelength range from ultraviolet through thermal infrared (0.3 to 12 microns). This spectral range enables detection, identification, and mapping of objects and liquids on the earth's surface and gases in the air. Applications requiring this range of wavelengths include detection and mapping of oil spills, soil and water contamination, stressed vegetation, and renewable and non-renewable natural resources, and also change detection, natural hazard mitigation, emergency response, agricultural management, and urban planning. GER has designed and built a configurable scanner that acquires high resolution images in 63 selected wave bands in this broad wavelength range.
Hamilton, P M [Central Electricity Research Lab., Leatherhead, England; Varey, R H; Millan, M M
A discussion showed that only correlation spectrometry and differential lidar are sensitive enough to measure trace amounts of SO/sub 2/. The correlation spectrometer measures line integrals of concentration, or burdens, by analyzing incident uv radiation for absorption by SO/sub 2/. It has been widely used to measure vertical burdens against a skylight background and emission rates from traverses of a plume near its source, which are limited by the accuracy of the associated wind speed rather than by the spectrometer. Comprehensive measurements of horizontal dispersion and its dependence on times of travel and sampling have also been obtained from traverses farther downwind. The differential lidar provides range-resolved measurements of concentration by reflecting pulses of laser light at two wavelengths with different absorption coefficients from particles along the line of sight. It offers a sensitivity of a few ppB to ranges over 1 km with resolution in space and time of 1000 m and 10 sec. The instrument has already been demonstrated in prototype form and is now being developed for operational use. Table, graphs, and 39 references are included.
Aplicaciones Cientificas-C (SAC-C) satellites. CHAMP provided 8 years of radio oc- cultation data consisting of around 440,000 measurements from February...applications, various modifi- cations of terrestrial receivers are required, including hardware and software modifications to enhance surviv- ability in a...Dop- pler shifts. On the other hand, special hardware and software is required to support non-navigation remote sensing applications in space, such
Yertay, Alibek; Garrison, James L
Today, there are more than eight thousand satellites in space. Therefore, Radio Frequency (RF) signals broadcast from satellites can be accessed from almost every point on the earth. There will be number of satellites available at most points on earth with different frequency bands. These satellite signals can be used for remote sensing, therefore software that visualizes footprints of satellites and shows characteristics of every satellite available at any point would be useful in determinin...
remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed
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
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
Bo Cao; Shengmei Yang; Song Ye
Dammed lakes are an important secondary hazard caused by earthquakes. They can induce further damage to nearby humans. Current hydrology calculation research on dammed lakes usually lacks spatial expressive ability and cannot accurately conduct impact assessment without the support of remote sensing, which obtains important characteristic information of dammed lakes. The current study aims to address the issues of the potential impact area estimate of earthquake-induced dammed lakes by combin...
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
Lynnes, Christopher; Leptoukh, Greg
This slide presentation reviews some of the issues in quality of remote sensing data. Data "quality" is used in several different contexts in remote sensing data, with quite different meanings. At the pixel level, quality typically refers to a quality control process exercised by the processing algorithm, not an explicit declaration of accuracy or precision. File level quality is usually a statistical summary of the pixel-level quality but is of doubtful use for scenes covering large areal extents. Quality at the dataset or product level, on the other hand, usually refers to how accurately the dataset is believed to represent the physical quantities it purports to measure. This assessment often bears but an indirect relationship at best to pixel level quality. In addition to ambiguity at different levels of granularity, ambiguity is endemic within levels. Pixel-level quality terms vary widely, as do recommendations for use of these flags. At the dataset/product level, quality for low-resolution gridded products is often extrapolated from validation campaigns using high spatial resolution swath data, a suspect practice at best. Making use of quality at all levels is complicated by the dependence on application needs. We will present examples of the various meanings of quality in remote sensing data and possible ways forward toward a more unified and usable quality framework.
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
Blackburn, George Alan
The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments.
Voss, Kerstin; Goetzke, Roland; Hodam, Henryk
The "Remote Sensing in Schools" project aims at improving the integration of "Satellite remote sensing" into school teaching. Therefore, it is the project's overall objective to teach students in primary and secondary schools the basics and fields of application of remote sensing. Existing results show that many teachers are interested in remote sensing and at same time motivated to integrate it into their teaching. Despite the good intention, in the end, the implementation often fails due to the complexity and poor set-up of the information provided. Therefore, a comprehensive and well-structured learning platform on the topic of remote sensing is developed. The platform shall allow a structured introduction to the topic.
Thatch, L. M.; Maxwell, R. M.; Gilbert, J. M.
Over the past century, groundwater levels in California's San Joaquin Valley have dropped more than 30 meters in some areas due to excessive groundwater extraction to irrigate agricultural lands and feed a growing population. Between 2012 and 2016 California experienced the worst drought in its recorded history, further exacerbating this groundwater depletion. Due to lack of groundwater regulation, exact quantities of extracted groundwater in California are unknown and hard to quantify. We use a synthesis of integrated hydrologic model simulations and remote sensing products to quantify the impact of drought and groundwater pumping on the Central Valley water tables. The Parflow-CLM model was used to evaluate groundwater depletion in the San Joaquin River basin under multiple groundwater extraction scenarios simulated from pre-drought through recent drought years. Extraction scenarios included pre-development conditions, with no groundwater pumping; historical conditions based on decreasing groundwater level measurements; and estimated groundwater extraction rates calculated from the deficit between the predicted crop water demand, based on county land use surveys, and available surface water supplies. Results were compared to NASA's Gravity Recover and Climate Experiment (GRACE) data products to constrain water table decline from groundwater extraction during severe drought. This approach untangles various factors leading to groundwater depletion within the San Joaquin Valley both during drought and years of normal recharge to help evaluate which areas are most susceptible to groundwater overdraft, as well as further evaluating the spatially and temporally variable sustainable yield. Recent efforts to improve water management and ensure reliable water supplies are highlighted by California's Sustainable Groundwater Management Act (SGMA) which mandates Groundwater Sustainability Agencies to determine the maximum quantity of groundwater that can be withdrawn through
Wang, J.; Sheng, Y.; Wada, Y.
The fluvial lake system across China's Yangtze Plain (YP), a World Wildlife Fund (WWF) ecoregion, are critical freshwater storages for nearly half a billion people. Our mapping using daily MODIS imagery revealed an approximately 10% net loss in the YP lake area from 2000 to 2011. Causes of this decadal lake decline were highly contentious, as it coincided with several meteorological droughts, a rising human water consumption (HWC), and the initial and yearly intensified water regulation from the world's largest hydroelectric project, the Three Gorges Dam (TGD). Here we integrated optical remote sensing, hydrological modeling, and in situ measurements to decouple the impacts of climate variability and anthropogenic activities including (i) Yangtze flow and sediment alterations by the TGD and (ii) HWC in agricultural, industrial, and domestic sectors throughout the downstream Yangtze Basin. Results suggest that this decadal lake decline was predominantly driven by climate variability closely linked to the El Niño-Southern Oscillation. Studied human activities, despite varying seasonal impacts that peak in fall, contribute ˜10-20% or less to the inter-annual lake area decline. Given that the TGD impacts on the total YP lake area and its seasonal variation are both under ˜5%, we also dismiss the speculation that the TGD might be responsible for evident downstream climate change by altering lake surface extent and thus open water evaporation. Nevertheless, anthropogenic impacts exhibited a strengthening trend during the past decade. Although the TGD has reached its full-capacity water regulation, the negative impacts of HWC and TGD-induced net channel erosion, which are already comparable to that of TGD's flow regulation, may continue to grow as crucial anthropogenic factors to future YP lake conservation.
Focardi, Silvia; Corsi, Ilaria; Mazzuoli, Stefania; Vignoli, Leonardo; Loiselle, Steven A; Focardi, Silvano
Aquatic ecosystems around the world, lake, estuaries and coastal areas are increasingly impacted by anthropogenic pollutants through different sources such as agricultural, industrial and urban discharges, atmospheric deposition and terrestrial drainage. Lake Victoria is the second largest lake in the world and the largest tropical lake. Bordered by Tanzania, Uganda, and Kenya, it provides a livelihood for millions of Africans in the region. However, the lake is under threat from eutrophication, a huge decline in the number of native fish species caused by several factors including loss of biodiversity, over fishing and pollution has been recently documented. Increasing usage of pesticides and insecticides in the adjacent agricultural areas as well as mercury contamination from processing of gold ore on the southern shores are currently considered among the most emergent phenomena of chemical contamination in the lake. By the application of globally consistent and comprehensive geospatial data-sets based on remote sensing integrated with information on heavy metals accumulation and insecticides exposure in native and alien fish populations, the present study aims at assessing the environmental risk associated to the contamination of the Lake Victoria water body on fish health, land cover distribution, biodiversity and the agricultural area surrounding the lake. By the elaboration of Landsat 7 TM data of November 2002 and Landsat 7 TM 1986 we have calculated the agriculture area which borders the Lake Victoria bay, which is an upland plain. The resulting enhanced nutrient loading to the soil is subsequently transported to the lake by rain or as dry fall. The data has been inserted in a Geographical information System (ARCGIS) to be upgraded and consulted. Heavy metals in fish fillets showed concentrations rather low except for mercury being higher than others as already described in previous investigations. In the same tissue, cholinesterases activity (ChE) as an
Zoran, Maria; Ciobanu, Mircea; Mitrea, Marius Gabriel; Talianu, Camelia; Cotarlan, Costel; Mateciuc, Doru; Radulescu, Florin; Biter Mircea
The majority of strong Romanian earthquakes has the origin in Vrancea region. Subduction of the Black Sea Sub-Plate under the Pannonian Plate produces faulting processes. Crustal displacement identification and monitoring is very important for a seismically active area like Vrancea-Focsani. Earthquake displacements are very well revealed by satellite remote sensing data. At the same time, geomorphologic analysis of topographic maps is carried out and particularly longitudinal and transverse profiles are constructed, as well as structural-geomorphologic maps. Faults are interpreted by specific features in nature of relief, straightness of line of river beds and their tributaries, exits of springs, etc. Remote sensing analysis and field studies of active faults can provide a geologic history that overcomes many of the shortcomings of instrumental and historic records. Our theoretical models developed in the frame of this project are presented as follows: a) Spectral Mixture Analysis model of geomorphological and topographic characteristics for Vrancea region proposed for satellite images analysis which assumes that the different classes present in a pixel (image unit) contribute independently to its reflectance. Therefore, the reflectance of a pixel at a particular frequency is the sum of the reflectances of the components at that frequency. The same test region in Vrancea area is imaged at several different frequencies (spectral bands), leading to multispectral observations for each pixel. It is useful to merge different satellite data into a hybrid image with high spatial and spectral resolution to create detailed images map of the abundance of various materials within the scene based on material spectral fingerprint. Image fusion produces a high-resolution multispectral image that is then unmixed into high-resolution material maps. b) Model of seismic cross section analysis which is applied in seismic active zones morphology. Since a seismic section can be
Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.
Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product
Hamid, Amna Ahmed; Ali, Mohamed M.
The main objective of the paper is to illustrate the potential of remote sensing data in the study and monitoring of environmental changes in western Sudan where considerable part of the area is under rangeland use. Data from NOAA satellite AVHRR sensor as well as thematic mapper Tm was used to assess the environment of the area during 1982-1997. The AVHRR data was processed into vegetation index (NDVI) images. Image analysis and classification was done using image display and analysis (IDA) GIS method to study vegetation condition in time series. The obtained information from field observations. The result showed high correlation between the information the work concluded the followings: NDVI images and thematic mapper data proved to be efficient in environment change analysis. NOAA AVHRR satellite data can provide an early-warning indicator of an approaching disaster. Remote sensing integrated into a GIS can contribute effectively to improve land management through better understanding of environment variability.(Author)
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.
National Aeronautics and Space Administration — A Web-based Airborne Remote Sensing Telemetry Server (WARSTS) is proposed to integrate UAV telemetry and web-technology into an innovative communication, command,...
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
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.
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
Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard
Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.
Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.
Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.
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
Tinney, L.; Christel, L.; Clark, H.; Mackey, H.
The United States Department of Energy (USDOE) maintains a Remote Sensing Laboratory (RSL) to support nuclear related programs of the US Government. The mission of the organization includes both emergency response and routine environmental assessments of nuclear facilities. The unique suite of equipment used by RSL for multisensor surveys of nuclear facilities include gamma radiation sensors, mapping quality aerial cameras, video cameras, thermal imagers, and multispectral scanners. Results for RSL multisensor surveys that have been conducted at the Savannah River Site (SRS) located in South Carolina are presented
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.
Bernabeu i Altayó, Gerard; Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius
Remote sensing spatial, spectral, and temporal resolutions of images, acquired Les resolucions espacials, espectrals i temporals d'imatges de teledetecci ó, adquirides a una mida raonable, donen com a resultat imatges que es poden processar per a representar grans àrees de terreny amb un nivell de detall espacial que es Las resoluciones espaciales, espectrales y temporales de imágenes de teledetección, adquiridas a un tamaño razonable, dan como resultado imágenes que se pueden procesar ...
Handley, J F
The contribution of remote sensing to environmental management procedures at the sub-regional scale is examined in relation to the County Structure environmental management plan for Merseyside County, England. The various seasons, scales and emulsions used for aerial photography in the county are indicated, and results of aerial surveys of the distribution of derelict and despoiled land and of natural environments are presented and compared with ground surveys. The use of color infrared and panchromatic aerial photographs indicating areas of environmental stress and land use in the formulation, implementation and monitoring of environmental management activities is then discussed.
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.
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.
Wilson, H.; Cary, T. K.; Goward, S. N.
It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.
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.
Thompson, M. D.
A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.
Walter, S. H. G.; Gasselt, S. V.; Michael, G.; Neukum, G.
The geometric outline of remote sensing image data, the so called footprint, can be represented as a number of coordinate tuples. These polygons are associated with according attribute information such as orbit name, ground- and image resolution, solar longitude and illumination conditions to generate a powerful base for classification of planetary experiment data. Speed, handling and extended capabilites are the reasons for using geodatabases to store and access these data types. Techniques for such a spatial database of footprint data are demonstrated using the Relational Database Management System (RDBMS) PostgreSQL, spatially enabled by the PostGIS extension. Exemplary, footprints of the HRSC and OMEGA instruments, both onboard ESA's Mars Express Orbiter, are generated and connected to attribute information. The aim is to provide high-resolution footprints of the OMEGA instrument to the science community for the first time and make them available for web-based mapping applications like the "Planetary Interactive GIS-on-the-Web Analyzable Database" (PIG- WAD), produced by the USGS. Map overlays with HRSC or other instruments like MOC and THEMIS (footprint maps are already available for these instruments and can be integrated into the database) allow on-the-fly intersection and comparison as well as extended statistics of the data. Footprint polygons are generated one by one using standard software provided by the instrument teams. Attribute data is calculated and stored together with the geometric information. In the case of HRSC, the coordinates of the footprints are already available in the VICAR label of each image file. Using the VICAR RTL and PostgreSQL's libpq C library they are loaded into the database using the Well-Known Text (WKT) notation by the Open Geospatial Consortium, Inc. (OGC). For the OMEGA instrument, image data is read using IDL routines developed and distributed by the OMEGA team. Image outlines are exported together with relevant attribute
The proceedings contain papers discussing the state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing, along with the research and development activities aimed at increasing the future capabilities of this technology. The following topics are addressed: spectral geology, U.S. and international hydrocarbon exporation, radar and thermal infrared remote sensing, engineering geology and hydrogeology, mineral exploration, remote sensing for marine and environmental applications, image processing and analysis, geobotanical remote sensing, and data integration and geographic information systems. Particular attention is given to spectral alteration mapping with imaging spectrometers, mapping the coastal plain of the Congo with airborne digital radar, applications of remote sensing techniques to the assessment of dam safety, remote sensing of ferric iron minerals as guides for gold exploration, principal component analysis for alteration mappping, and the application of remote sensing techniques for gold prospecting in the north Fujian province.
Desa, E.; Brown, R.; Shenoi, S.S.C.; Joseph, G.
Conference (PORSEC), earlier known as the Paci c Ocean Remote Sensing Conference (PORSEC), was formed in 1992 to provide a venue for international cooperation in the increasingly important area of remote sensing of the ocean. Many countries that border... and ocean dynamics, and modeling with satellite sensor (mainly microwave) data. Some of the presentations are of regional interest, while others will nd an audience beyond the satellite remote sensing community. These rst results through their simple...
Remote sensing is a kind of very effective method which can be used in all stages of geological prospecting. Geological prospecting with remote sensing method must be based on different genetic models of ore deposits, characteristics of geology-landscape and comprehensive analysis for geophysical and geochemical data, that is, by way of conceptual model prospecting. The prospecting results based on remote sensing geology should be assessed from three aspects such as direct, indirect and potential ones
The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was
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
Full Text Available Automated detection of landscape patterns on Remote Sensing imagery has seen virtually little or no development in the archaeological domain, notwithstanding the fact that large portion of cultural landscapes worldwide are characterized by land engineering applications. The current extraordinary availability of remotely sensed images makes it now urgent to envision and develop automatic methods that can simplify their inspection and the extraction of relevant information from them, as the quantity of information is no longer manageable by traditional “human” visual interpretation. This paper expands on the development of automatic methods for the detection of target landscape features—represented by field system patterns—in very high spatial resolution images, within the framework of an archaeological project focused on the landscape engineering embedded in Roman cadasters. The targets of interest consist of a variety of similarly oriented objects of diverse nature (such as roads, drainage channels, etc. concurring to demark the current landscape organization, which reflects the one imposed by Romans over two millennia ago. The proposed workflow exploits the textural and shape properties of real-world elements forming the field patterns using multiscale analysis of dominant oriented response filters. Trials showed that this approach provides accurate localization of target linear objects and alignments signaled by a wide range of physical entities with very different characteristics.
Full Text Available For agronomic, environmental, and economic reasons, the need for spatialized information about agricultural practices is expected to rapidly increase. In this context, we reviewed the literature on remote sensing for mapping cropping practices. The reviewed studies were grouped into three categories of practices: crop succession (crop rotation and fallowing, cropping pattern (single tree crop planting pattern, sequential cropping, and intercropping/agroforestry, and cropping techniques (irrigation, soil tillage, harvest and post-harvest practices, crop varieties, and agro-ecological infrastructures. We observed that the majority of the studies were exploratory investigations, tested on a local scale with a high dependence on ground data, and used only one type of remote sensing sensor. Furthermore, to be correctly implemented, most of the methods relied heavily on local knowledge on the management practices, the environment, and the biological material. These limitations point to future research directions, such as the use of land stratification, multi-sensor data combination, and expert knowledge-driven methods. Finally, the new spatial technologies, and particularly the Sentinel constellation, are expected to improve the monitoring of cropping practices in the challenging context of food security and better management of agro-environmental issues.
David J. Lary
Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.
Sorek-Hamer, Meytar; Just, Allan C; Kloog, Itai
Particulate matter air pollution is a ubiquitous exposure linked with multiple adverse health outcomes for children and across the life course. The recent development of satellite-based remote-sensing models for air pollution enables the quantification of these risks and addresses many limitations of previous air pollution research strategies. We review the recent literature on the applications of satellite remote sensing in air quality research, with a focus on their use in epidemiological studies. Aerosol optical depth (AOD) is a focus of this review and a significant number of studies show that ground-level particulate matter can be estimated from columnar AOD. Satellite measurements have been found to be an important source of data for particulate matter model-based exposure estimates, and recently have been used in health studies to increase the spatial breadth and temporal resolution of these estimates. It is suggested that satellite-based models improve our understanding of the spatial characteristics of air quality. Although the adoption of satellite-based measures of air quality in health studies is in its infancy, it is rapidly growing. Nevertheless, further investigation is still needed in order to have a better understanding of the AOD contribution to these prediction models in order to use them with higher accuracy in epidemiological studies.
Bishop, W. P.; Heacock, E. L.
The current offer by the United States Department of Commerce to transfer the U.S. land remote sensing program to the private sector is described. A Request for Proposals (RFP) was issued, soliciting offers from U.S. firms to provide a commercial land remote sensing satellite system. Proposals must address a complete system including satellite, communications, and ground data processing systems. Offerors are encouraged to propose to take over the Government LANDSAT system which consists of LANDSAT 4 and LANDSAT D'. Also required in proposals are the market development procedures and plans to ensure that commercialization is feasible and the business will become self-supporting at the earliest possible time. As a matter of Federal Policy, the solicitation is designed to protect both national security and foreign policy considerations. In keeping with these concerns, an offeror must be a U.S. Firm. Requirements for data quality, quantity, distribution and delivery are met by current operational procedures. It is the Government's desire that the Offeror be prepared to develop and operate follow-on systems without Government subsidies. However, to facilitate rapid commercialization, an offeror may elect to include in his proposal mechanisms for short term government financial assistance.
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.
Xu, Duanyang; Song, Alin; Song, Xiao
To combat desertification, the Chinese government has launched a series of Desertification Controlling Projects and Policies over the past several decades. However, the effect of these projects and policies remains controversial due to a lack of suitable methods and data to assess them. In this paper, the authors selected the farming-pastoral region of the northern Shaanxi Province in China as a sample region and attempted to assess the effect of Desertification Controlling Projects and Policies launched after 2000 by combining remote sensing and farmer investigation data. The results showed that the combination of these two complementary assessments can provide comprehensive information to support decision-making. According to the remote sensing and Net Primary Production data, the research region experienced an obvious desertification reversion between 2000 and 2010, and approximately 70% of this reversion can be explained by Desertification Controlling Projects and Policies. Farmer investigation data also indicated that these projects and policies were the dominating factor contributing to desertification reversion, and approximately 70% of investigated farmers agreed with this conclusion. However, low supervision and subsidy levels were issues that limited the policy effect. Therefore, it is necessary for the government to enhance supervision, raise subsidy levels, and develop environmental protection regulations to encourage more farmers to participate in desertification control.
Full Text Available One of the waters that has been contaminated by industrial waste and domestic waste is the waters in estuaries inlet of Semarang Eastern Flood Canal which is the estuary of the river system, which passes through the eastern city of Semarang which is dense with residential and industrial. So it is necessary to have information about the assessment of water quality in Estuaries Inlet of Semarang Eastern Flood Canal. Remote sensing technology can analyze the results of recording the spectral characteristics of water with water quality parameters. One of the parameters for assessing water quality is Chlorophyll-a and Total Suspended Solid, can be estimated through remote sensing technology using multispectral Sentinel-2A Satellite images. In this research there are 3 algorithms that will be used in determining the content of chlorophyll a, and for determining TSS. Image accuracy test is done to find out how far the image can give information about Chlorophyll-a and TSS in the waters. The results of the image accuracy test will be compared with the value of chlorophyll-a and TSS that have been tested through laboratory analysis. The result of this research is the distribution map of chlorophyll-a and TSS content in the waters.
Subiyanto, Sawitri; Ramadhanis, Zainab; Baktiar, Aditya Hafidh
One of the waters that has been contaminated by industrial waste and domestic waste is the waters in estuaries inlet of Semarang Eastern Flood Canal which is the estuary of the river system, which passes through the eastern city of Semarang which is dense with residential and industrial. So it is necessary to have information about the assessment of water quality in Estuaries Inlet of Semarang Eastern Flood Canal. Remote sensing technology can analyze the results of recording the spectral characteristics of water with water quality parameters. One of the parameters for assessing water quality is Chlorophyll-a and Total Suspended Solid, can be estimated through remote sensing technology using multispectral Sentinel-2A Satellite images. In this research there are 3 algorithms that will be used in determining the content of chlorophyll a, and for determining TSS. Image accuracy test is done to find out how far the image can give information about Chlorophyll-a and TSS in the waters. The results of the image accuracy test will be compared with the value of chlorophyll-a and TSS that have been tested through laboratory analysis. The result of this research is the distribution map of chlorophyll-a and TSS content in the waters.
Full Text Available Dammed lakes are an important secondary hazard caused by earthquakes. They can induce further damage to nearby humans. Current hydrology calculation research on dammed lakes usually lacks spatial expressive ability and cannot accurately conduct impact assessment without the support of remote sensing, which obtains important characteristic information of dammed lakes. The current study aims to address the issues of the potential impact area estimate of earthquake-induced dammed lakes by combining remote sensing (RS, a geographic information system (GIS, and hydrological modeling. The Tangjiashan dammed lake induced by the Wenchuan earthquake was selected as the case for study. The elevation-versus-reservoir capacity curve was first calculated using the seed-growing algorithm based on digital elevation model (DEM data. The simulated annealing algorithm was applied to train the hydrological modeling parameters according to the historical hydrologic data. Then, the downstream water elevation variational process under different collapse capacity conditions was performed based on the obtained parameters. Finally, the downstream potential impact area was estimated by the highest water elevation values at different hydrologic sections. Results show that a flood with a collapse elevation of at least 680 m will impact the entire downstream region of Beichuan town. We conclude that spatial information technology combined with hydrological modeling can accurately predict and demonstrate the potential impact area with limited data resources. This paper provides a better guide for future immediate responses to dammed lake hazard mitigation.
Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.
Remote sensing offers the potential to augment current levee monitoring programs by providing rapid and consistent data collection over large areas irrespective of the ground accessibility of the sites of interest, at repeat intervals that are difficult or costly to maintain with ground-based surveys, and in rapid response to emergency situations. While synthetic aperture radar (SAR) has long been used for subsidence measurements over large areas, applying this technique directly to regional levee monitoring is a new endeavor, mainly because it requires both a wide imaging swath and fine spatial resolution to resolve individual levees within the scene, a combination that has not historically been available. Application of SAR remote sensing directly to levee monitoring has only been attempted in a few pilot studies. Here we describe how SAR remote sensing can be used to assess levee conditions, such as seepage, drawing from the results of two levee studies: one of the Sacramento-San Joaquin Delta levees in California that has been ongoing since July 2009 and a second that covered the levees near Vicksburg, Mississippi, during the spring 2011 floods. These studies have both used data acquired with NASA's UAVSAR L-band synthetic aperture radar, which has the spatial resolution needed for this application (1.7 m single-look), sufficiently wide imaging swath (22 km), and the longer wavelength (L-band, 0.238 m) required to maintain phase coherence between repeat collections over levees, an essential requirement for applying differential interferometry (DInSAR) to a time series of repeated collections for levee deformation measurement. We report the development and demonstration of new techniques that employ SAR polarimetry and differential interferometry to successfully assess levee health through the quantitative measurement of deformation on and near levees and through detection of areas experiencing seepage. The Sacramento-San Joaquin Delta levee study, which covers
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.
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.
El-Din, Gamal Kamal; Abdelkareem, Mohamed
The Qena-Safaga shear zone (QSSZ) represents a significant structural characteristic in the Eastern Desert of Egypt. Remote Sensing, field and geochemical data were utilized in the present study. The results revealed that the QSSZ dominated by metamorphic complex (MC) that intruded by syn-tectonic granitoids. The low angle thrust fault brings calc-alkaline metavolcanics to overlie MC and its association. Subsequently, the area is dissected by strike-slip faults and the small elongated basins of Hammamat sediments of Precambrian were accumulated. The MC intruded by late-to post-tectonic granites (LPG) and Dokhan Volcanics which comprise felsic varieties forming distinctive columnar joints. Remote sensing analysis and field data revealed that major sub-vertical conspicuous strike-slip faults (SSF) including sinistral NW-SE and dextral ca. E-W shaped the study area. Various shear zones that accompanying the SSF are running NW-SE, NE-SW, E-W, N-S and ENE-WSW. The obtained shear sense presented a multiphase of deformation on each trend. i.e., the predominant NW-SE strike-slip fault trend started with sinistral displacement and is reactivated during later events to be right (dextral) strike slip cutting with dextral displacement the E-W trending faults; while NE-SW movements are cut by both the N-S and NNW - SSE trends. Remote sensing data revealed that the NW-SE direction that dominated the area is associated with hydrothermal alteration processes. This allowed modifying the major and trace elements of the highly deformed rocks that showed depletion in SiO2 and enrichments in Fe2O3, MnO, Al2O3, TiO2, Na2O, K2O, Cu, Zn and Pb contents. The geochemical signatures of major and trace elements revealed two types of granites including I-type calc-alkaline granites (late-to post-tectonic) that formed during an extensional regime. However, syn-tectonic granitoids are related to subduction-related environment.
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.
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.
McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall
The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify
Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 4 : use of knowledge integrated visual analytics system in supporting bridge management.
The goals of integration should be: Supporting domain oriented data analysis through the use of : knowledge augmented visual analytics system. In this project, we focus on: : Providing interactive data exploration for bridge managements. : ...
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.
Buffalano, A. C.; Kochanowski, P.
Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy, and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 300 to 400 million dollars annually for the rest of the world.
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
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.
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.
Porter, Reid; Hush, Don; Harvey, Neal; Theiler, James
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.
Prados, Donald; Johnson, Michael; Mohamed, Mohamed A.; Cao, Chang-Yong; Gasser, Jerry; Powell, Don; McGregor, Lloyd
This paper presents results of a project to port code for processing remotely sensed data from the UNIX environment to Windows. Factors considered during this process include time schedule, cost, resource availability, reuse of existing code, rapid interface development, ease of integration, and platform independence. The approach selected for this project used both Java and C. By using Java for the graphical user interface and C for the domain model, the strengths of both languages were utilized and the resulting code can easily be ported to other platforms. The advantages of this approach are discussed in this paper.
Beverly E. Law
As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 in the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance.
Cohen, Warren [USDA Forest Service
As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 in the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance.
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.
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.
Beginning in 2004, NASA has supported the development of an international network of ground-based remote sensing installations for the measurement of greenhouse gas columns. This collaboration has been successful and is currently used in both carbon cycle investigations and in the efforts to validate the GOSAT space-based column observations of CO2 and CH4. With the support of a grant, this research group has established a network of ground-based column observations that provide an essential link between the satellite observations of CO2, CO, and CH4 and the extensive global in situ surface network. The Total Carbon Column Observing Network (TCCON) was established in 2004. At the time of this report seven sites, employing modern instrumentation, were operational or were expected to be shortly. TCCON is expected to expand. In addition to providing the most direct means of tying the in situ and remote sensing data sets together, TCCON provides a means of testing the retrieval algorithms of SCIAMACHY and GOSAT over the broadest variation in atmospheric state. TCCON provides a critically maintained and long timescale record for identification of temporal drift and spatial bias in the calibration of the space-based sensors. Finally, the global observations from TCCON are improving our understanding of how to use column observations to provide robust estimates of surface exchange of C02 and CH4 in advance of the launch of OCO and GOSAT. TCCON data are being used to better understand the impact of both regional fluxes and long-range transport on gradients in the C02 column. Such knowledge is essential for identifying the tools required to best use the space-based observations. The technical approach and methodology of retrieving greenhouse gas columns from near-IR solar spectra, data quality and process control are described. Additionally, the impact of and relevance to NASA of TCCON and satellite validation and carbon science are addressed.
Full Text Available We studied the non-marine reptile and amphibian species of the volcanic Comoro archipelago in the Western Indian Ocean, a poorly known island herpetofauna comprising numerous microendemic species of potentially high extinction risk and widespread, non-endemic and often invasive taxa. According to our data, the Comoro islands are inhabited by two amphibian species and at least 28 species of reptiles although ongoing genetic studies and unconfirmed historical records suggest an even higher species diversity. 14 of the 28 currently recognized species of terrestrial reptiles (50% and the two amphibians are endemic to a single island or to the Comoro archipelago. The majority of species are most abundant at low elevation. However, a few endemic species, like the gekkonid lizards Paroedura sanctijohannis and Phelsuma nigristriata, are more common in or even confined to higher altitudes. We created habitat maps from remotely sensed data in combination with detailed species distribution maps produced using comprehensive data from field surveys between 2000 and 2010, literature, and historical locality records based on specimens in zoological collections. Using these data, we assessed the conservation status of the endemic terrestrial reptiles and amphibians according to the IUCN Red List criteria. Our results show that although little area of natural forest remains on the Comoros, many species are abundant in degraded forest or plantations. Competition and predation by invasive species appears to be the most important threat factor for the endemic herpetofauna, together with habitat degradation and destruction, which further favours invasive species. We propose the status Endangered for three species, Vulnerable for one species, Near Threatened for six species, Least Concern for four and Data Deficient for two species. The endemic subspecies Oplurus cuvieri comorensis is proposed for the status Critically Endangered. Based on the results of this study
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.
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.
Oevelen, van P.J.
In this thesis the use of microwave remote sensing to estimate soil water content is investigated. A general framework is described which is applicable to both passive and active microwave remote sensing of soil water content. The various steps necessary to estimate areal soil water content
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 ...
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
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...
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...
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...
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
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.
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.
Leptoukh, G.; Zubko, V.; Gopalan, A.; Khayat, M.
We describe Giovanni, the NASA Goddard developed online visualization and analysis tool that allows users explore various phenomena without learning remote sensing data formats and downloading voluminous data. Using MODIS aerosol data as an example, we formulate an approach to the data fusion for Giovanni to further enrich online multi-sensor remote sensing data comparison and analysis.
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...
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 ...
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 ...
Allen, J. E.; Cruz, C.
The ingredients for the highly successful, ongoing educator professional development program, "Integrated Geospatial Education and Technology Training-Remote Sensing (iGETT-RS)" came into place in 2006 when representatives of public and private organizations convened a two-day workshop at the National Science Foundation (NSF) to explore issues around integrating remote sensing with Geographic Information Systems (GIS) instruction at two-year (community and Tribal) colleges. The results of that 2006 workshop informed the shape of a grant proposal, and two phases of iGETT-RS were funded by NSF's Advanced Technological Education Program (NSF DUE #0703185, 2007-2011, and NSF DUE #1205069, 2012-2015). 76 GIS instructors from all over the country have been served. Each of them has spent 18 months on the project, participating in monthly webinars and two Summer Institutes, and creating their own integrated geospatial exercises for the classroom. The project will be completed in June 2015. As the external evaluator for iGETT expressed it, the impact on participating instructors "can only be described as transformative." This paper describes how iGETT came about, how it was designed and implemented, how it affected participants and their programs, and what has been learned by the project staff about delivering professional development in geospatial technologies for workforce preparedness.
Miller, W. Frank; Sever, Thomas L.; Lee, C. Daniel
The concept of integrating ecological perspectives on early man's settlement patterns with advanced remote sensing technologies shows promise for predictive site modeling. Early work with aerial imagery and ecosystem analysis is discussed with respect to the development of a major project in Maya archaeology supported by NASA and the National Geographic Society with technical support from the Mississippi State Remote Sensing Center. A preliminary site reconnaissance model will be developed for testing during the 1991 field season.
Liu, J.; Chen, W.; Sarich, M. [Intermap Technologies Ltd., Nepean, ON (Canada); Cihlar, J. [Canada Centre for Remote Sensing, Ottawa, ON (Canada); Goulden, M. [California Univ., Irvine, CA (United States)
Remote sensing to monitor the behaviour of terrestrial ecosystems over large areas was discussed. For this type of application the boreal ecosystem productivity simulator (BEPS) was developed, with the subsequent incorporation of the more advanced photosynthetic model. The new model improves the methodology through analytical spatial and temporal integration of canopy photosynthesis processes, and is suitable for regional remote sensing applications at moderate resolutions of 250 to 1000 m. 10 refs., 1 tab., 3 figs.
Xiaohui Zhang; George Ball; Eve Halper
This paper presents an integrated system to support urban natural resource management. With the application of remote sensing (RS) and geographic information systems (GIS), the paper emphasizes the methodology of integrating information technology and a scientific basis to support ecosystem-based management. First, a systematic integration framework is developed and...
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.
With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.
Lutton, Stephen M.
Remote sensing is providing voluminous data and value added information products. Electronic sensors, communication electronics, computer software, hardware, and network communications technology have matured to the point where a distributed infrastructure for remotely sensed information is a reality. The amount of remotely sensed data and information is making distributed infrastructure almost a necessity. This infrastructure provides data collection, archiving, cataloging, browsing, processing, and viewing for applications from scientific research to economic, legal, and national security decision making. The remote sensing field is entering a new exciting stage of commercial growth and expansion into the mainstream of government and business decision making. This paper overviews this new distributed infrastructure and then focuses on describing a software system for on-line catalog access and distribution of remotely sensed information.
Plevin, J [ESA, Directorate of Planning and Future Programmes, Paris, France; Pryke, I [ESA, Directorate of Applications Programmes, Toulouse, France
The present activities and future missions of the ESA program of spaceborne remote sensing of earth resources and environment are discussed. Program objectives have been determined to be the satisfaction of European regional needs by agricultural, land use, water resources, coastal and polar surveys, and meeting the requirements of developing nations in the areas of agricultural production, mineral exploration and disaster warning and assessment. The Earthnet system of data processing centers presently is used for the distribution of remote sensing data acquired by NASA satellites. Remote sensing experiments to be flown aboard Spacelab are the Metric Camera, to test high resolution mapping capabilities of a large format camera, and the Microwave Remote-Sensing Experiment, which operates as a two-frequency scatterometer, a synthetic aperture radar and a passive microwave radiometer. Studies carried out on the definition of future remote sensing satellite systems are described, including studies of system concepts for land applications and coastal monitoring satellites.
Yahya, N N; Hashim, M; Ahmad, S
Understanding the sea floor biodiversity requires spatial information that can be acquired from remote sensing satellite data. Species volume, spatial patterns and species coverage are some of the information that can be derived. Current approaches for mapping sea bottom type have evolved from field observation, visual interpretation from aerial photography, mapping from remote sensing satellite data along with field survey and hydrograhic chart. Remote sensing offers most versatile technique to map sea bottom type up to a certain scale. This paper reviews the technical characteristics of signal and light interference within marine features, space and remote sensing satellite. In addition, related image processing techniques that are applicable to remote sensing satellite data for sea bottom type digital mapping is also presented. The sea bottom type can be differentiated by classification method using appropriate spectral bands of satellite data. In order to verify the existence of particular sea bottom type, field observations need to be carried out with proper technique and equipment
Abedin, M. Nurul; Bradley, Arthur T.; Sharma, Shiv K.; Misra, Anupam K.; Lucey, Paul G.; Mckay, Chistopher P.; Ismail, Syed; Sandford, Stephen P.
A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100 m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20 km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters. OCIS codes: (120.0280) Remote sensing and sensors; (130.0250) Optoelectronics; (280.3640) Lidar; (300.2530) Fluorescence, laser-induced; (300.6450) Spectroscopy, Raman; (300.6365) Spectroscopy, laser induced breakdown
de Leeuw, Jan; Georgiadou, P.Y.; Georgiadou, Yola; Kerle, Norman; de Gier, Alfred; Inoue, Yoshio; Ferwerda, Jelle; Smies, Maarten; Narantuya, Davaa
Limited awareness of environmental remote sensing’s potential ability to support environmental policy development constrains the technology’s utilization. This paper reviews the potential of earth observation from the perspective of environmental policy. A literature review of “remote sensing and policy” revealed that while the number of publications in this field increased almost twice as rapidly as that of remote sensing literature as a whole (15.3 versus 8.8% yr−1), there is apparently lit...
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...
The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.
Douglass, R. W.
A speech is given on operational remote sensing programs in forest management and the importance of remote sensing in forestry is emphasized. Forest service priorities in using remote sensing are outlined.
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
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.
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.
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
Erkmen, Baris I.
This work relates to the generic problem of remote active imaging; that is, a source illuminates a target of interest and a receiver collects the scattered light off the target to obtain an image. Conventional imaging systems consist of an imaging lens and a high-resolution detector array [e.g., a CCD (charge coupled device) array] to register the image. However, conventional imaging systems for remote sensing require high-quality optics and need to support large detector arrays and associated electronics. This results in suboptimal size, weight, and power consumption. Computational ghost imaging (CGI) is a computational alternative to this traditional imaging concept that has a very simple receiver structure. In CGI, the transmitter illuminates the target with a modulated light source. A single-pixel (bucket) detector collects the scattered light. Then, via computation (i.e., postprocessing), the receiver can reconstruct the image using the knowledge of the modulation that was projected onto the target by the transmitter. This way, one can construct a very simple receiver that, in principle, requires no lens to image a target. Ghost imaging is a transverse imaging modality that has been receiving much attention owing to a rich interconnection of novel physical characteristics and novel signal processing algorithms suitable for active computational imaging. The original ghost imaging experiments consisted of two correlated optical beams traversing distinct paths and impinging on two spatially-separated photodetectors: one beam interacts with the target and then illuminates on a single-pixel (bucket) detector that provides no spatial resolution, whereas the other beam traverses an independent path and impinges on a high-resolution camera without any interaction with the target. The term ghost imaging was coined soon after the initial experiments were reported, to emphasize the fact that by cross-correlating two photocurrents, one generates an image of the target. In
Mumby, Peter J.; Skirving, William; Strong, Alan E.; Hardy, John T.; LeDrew, Ellsworth F.; Hochberg, Eric J.; Stumpf, Rick P.; David, Laura T.
There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas
Mumby, Peter J.; Skirving, William; Strong, Alan E.; Hardy, John T.; LeDrew, Ellsworth F.; Hochberg, Eric J.; Stumpf, Rick P.; David, Laura T
There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas.
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
Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasilki; Themistocleous, Kyriacos; Cuca, Branka; Nisantzi, Argyro; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter
Remote sensing science is increasingly being used to support archaeological and cultural heritage research in various ways. Satellite sensors either passive or active are currently used in a systematic basis to detect buried archaeological remains and to systematic monitor tangible heritage. In addition, airborne and low altitude systems are being used for documentation purposes. Ground surveys using remote sensing tools such as spectroradiometers and ground penetrating radars can detect variations of vegetation and soil respectively, which are linked to the presence of underground archaeological features. Education activities and training of remote sensing archaeology to young people is characterized of highly importance. Specific remote sensing tools relevant for archaeological research can be developed including web tools, small libraries, interactive learning games etc. These tools can be then combined and aligned with archaeology and cultural heritage. This can be achieved by presenting historical and pre-historical records, excavated sites or even artifacts under a "remote sensing" approach. Using such non-form educational approach, the students can be involved, ask, read, and seek to learn more about remote sensing and of course to learn about history. The paper aims to present a modern didactical concept and some examples of practical implementation of remote sensing archaeology in secondary schools in Cyprus. The idea was built upon an ongoing project (ATHENA) focused on the sue of remote sensing for archaeological research in Cyprus. Through H2020 ATHENA project, the Remote Sensing Science and Geo-Environment Research Laboratory at the Cyprus University of Technology (CUT), with the support of the National Research Council of Italy (CNR) and the German Aerospace Centre (DLR) aims to enhance its performance in all these new technologies.
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.
Remote sensing techniques developed for exploration programs can often be used to address environmental issues facing the petroleum industry. While this industry becomes increasingly more environmentally conscious, budgets remain tight, requiring any technology used in environmental applications to be cost effective, widely available and reliable. In this paper a three-fold analysis of environmental issues facing the petroleum industry concludes: major areas of concern included environmental mapping natural habitats, surface cover, change through time, pollution monitoring (hazardous wastes, oil seeps and spills on and offshore), earth hazards assessment, baseline studies, facilities sitting and crisis response. options matrices were developed plotting current and near future RS technology vs environmental concerns, and each sensor/platform combination subjectively evaluated to determine which combination could best address the problem. While presently available RS technology (both airborne and spaceborne) has significant capability toward environmental mapping, hazards detection and other concerns, the anticipated launches of ERS-1, JERS-1, Landsat-6 and other systems will provide environmentally useful data available today only from relatively expensive and local airborne surveys. Low altitude airborne surveys and ground/sea truth will continue to be critical to any quantitative studies
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.
Full Text Available Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI. Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.
Qin Kai; Zhao Yingjun; Lu Donghua; Zhang Donghui; Wu Wenhuan
In this thesis, the author explored multi-source management problems of remote sensing data. The main idea is to use the mosaic dataset model, and the ways of an integreted display of image and its interpretation. Based on ArcGIS and IMINT feature knowledge platform, the author used the C# and other programming tools for development work, so as to design and implement multi-source remote sensing data management system function module which is able to simply, conveniently and efficiently manage multi-source remote sensing data. (authors)
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.
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...
The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy
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.
Lin, Shin-Fa; Hwang, Cheinway
Unlike a typical remote sensing satellite that has a global coverage and non-integral orbital revolutions per day, Taiwan's FORMOSAT-2 (FS-2) satellite has a non-global coverage due to the mission requirements of one-day repeat cycle and daily visit around Taiwan. These orbital characteristics result in an integer number of revolutions a day and orbital resonances caused by certain components of the Earth's gravity field. Orbital flight data indicated amplified variations in the amplitudes of FS-2's Keplerian elements. We use twelve years of orbital observations and maneuver data to analyze the cause of the resonances and explain the differences between the simulated (at the pre-launch stage) and real orbits of FS-2. The differences are quantified using orbital perturbation theories that describe secular and long-period orbital evolutions caused by resonances. The resonance-induced orbital rising rate of FS-2 reaches +1.425 m/day, due to the combined (modeled) effect of resonances and atmospheric drags (the relative modeling errors remote sensing mission similar to FS-2, especially in the early mission design and planning phase.
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.
The increase in the number of operational Earth observation satellites gives remote sensing image fusion a new boost. As a powerful tool to integrate images from different sensors it enables multi-scale, multi-temporal and multi-source information extraction. Image fusion aims at providing results that cannot be obtained from a single data source alone. Instead it enables feature and information mining of higher reliability and availability. The process required to prepare remote sensing images for image fusion comprises most of the necessary steps to feed the database of Digital Earth. The virtual representation of the planet uses data and information that is referenced and corrected to suit interpretation and decision-making. The same pre-requisite is valid for image fusion, the outcome of which can directly flow into a geographical information system. The assessment and description of the quality of the results remains critical. Depending on the application and information to be extracted from multi-source images different approaches are necessary. This paper describes the process of image fusion based on a fusion and classification experiment, explains the necessary quality measures involved and shows with this example which criteria have to be considered if the results of image fusion are going to be used in Digital Earth
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
Aug 31, 2017 ... to comprehend the tectonic development of the ... software for the analysis and interpretation of G– .... The application of remote sensing for mapping ..... Pf1 and Pf2 show profile locations adopted for joint G–M modelling.
remote sensing techniques particularly those referring to change detection. This kind of ... Technol. depending on many factors in relation to climate conditions, nature .... geomorphologic position make it a perfect wind corridor. (Chahbani ...
Overview of remote sensing of chlorophyll flourescene in ocean waters. ... Besides empirical algorithms with the blue-green ratio, the algorithms based on ... between fluorescence and chlorophyll concentration and the red shift phenomena.
This comprehensive technical overview of the core theory of thermal remote sensing and its applications in hydrology, agriculture, and forestry includes a host of illuminating examples and covers everything from the basics to likely future trends in the field.
Jun 16, 2017 ... mainly focused on the models established by the remote sensing data in .... Page 5 of 16 58. Organization (WMO) World Weather Watch Pro- gram. ...... the disorder of urban sprawl would bring decreased vegetation cover and ...
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 ...
Houborg, Rasmus; Fisher, Joshua B.; Skidmore, Andrew K.
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
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
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.
.... 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...
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.
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...
A GIS AND REMOTE SENSING APPROACH TO ASSESSMENT OF DEFORESTATION IN ... This study measured and analyzed deforestation in Uyo and examined the possible effects of the ..... the Burkill technique, (1985, 1994, 1995, 1997.
remote sensing data for Uyo for the periods 1969, 1978, 1988, 2001 and 2004; evaluate the ... geographical information system (GIS) technology was applied to carry out this research. Field ..... preventing erosion, landslides, and making the.
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)
Bagli, Stefano; Pistocchi, Alberto; Mazzoli, Paolo; Borga, Marco; Bertoldi, Giacomo; Brenner, Johannes; Luzzi, Valerio
Climate change, increasing pressure on farmland to satisfy the growing demand, and need to ensure environmental quality for agriculture in order to be competitive require an increasing capacity of water management. In this context, web-based for forecasting and monitoring the hydrological conditions of topsoil can be an effective means to save water, maximize crop protection and reduce soil loss and the leaching of pollutants. Such tools need to be targeted to the users and be accessible in a simple way in order to allow adequate take up in the practice. IASMHYN "Improved management of Agricultural Systems by Monitoring and Hydrological evaluation" is a web mapping service designed to provide and update on a daily basis the main water budget variables for farmland management. A beta version of the tool is available at www.gecosistema.com/iasmhyn . IASMHYN is an instrument for "second level monitoring" that takes into account accurate hydro-meteorological information's from ground stations and remote sensing sources, and turns them into practically usable decision variables for precision farming, making use of geostatistical analysis and hydrological models The main routines embedded in IASMYHN exclusively use open source libraries (R packages and Python), to perform following operations: (1) Automatic acquisition of observed data, both from ground stations and remote sensing, concerning precipitation (RADAR) and temperature (MODIS-LST) available from various sources; (2) Interpolation of acquisitions through regression kriging in order to spatially map the meteorological data; (3) Run of hydrological models to obtain spatial information of hydrological soil variables of immediate interest in agriculture. The real time results that are produced are available trough a web interface and provide the user with spatial maps and time series of the following variables, supporting decision on irrigation, soil protection from erosion, pollution risk of groundwater and
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.
Andrew A. Tronin
Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.
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.
Walsh, Brian M., E-mail: firstname.lastname@example.org [NASA Langley Research Center, Hampton, VA 23681 (United States); Lee, Hyung R. [National Institute of Aerospace, Hampton, VA 23666 (United States); Barnes, Norman P. [Science Systems and Applications, Inc., Hampton, VA 23666 (United States)
To accurately measure the concentrations of atmospheric gasses, especially the gasses with low concentrations, strong absorption features must be accessed. Each molecular species or constituent has characteristic mid-infrared absorption features by which either column content or range resolved concentrations can be measured. Because of these characteristic absorption features the mid infrared spectral region is known as the fingerprint region. However, as noted by the Decadal Survey, mid-infrared solid-state lasers needed for DIAL systems are not available. The primary reason is associated with short upper laser level lifetimes of mid infrared transitions. Energy gaps between the energy levels that produce mid-infrared laser transitions are small, promoting rapid nonradiative quenching. Nonradiative quenching is a multiphonon process, the more phonons needed, the smaller the effect. More low energy phonons are required to span an energy gap than high energy phonons. Thus, low energy phonon materials have less nonradiative quenching compared to high energy phonon materials. Common laser materials, such as oxides like YAG, are high phonon energy materials, while fluorides, chlorides and bromides are low phonon materials. Work at NASA Langley is focused on a systematic search for novel lanthanide-doped mid-infrared solid-state lasers using both quantum mechanical models (theoretical) and spectroscopy (experimental) techniques. Only the best candidates are chosen for laser studies. The capabilities of modeling materials, experimental challenges, material properties, spectroscopy, and prospects for lanthanide-doped mid-infrared solid-state laser devices will be presented. - Highlights: • We discuss mid infrared lasers and laser materials. • We discuss applications to remote sensing. • We survey the lanthanide ions in low phonon materials for potential. • We present examples of praseodymium mid infrared spectroscopy and laser design.
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.
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
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.
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.
Full Text Available M B E R 2 0 0 8 15 USING REMOTELY- SENSED DATA FOR OPTIMAL FIELD SAMPLING BY DR PRAVESH DEBBA STATISTICS IS THE SCIENCE pertaining to the collection, summary, analysis, interpretation and presentation of data. It is often impractical... studies are: where to sample, what to sample and how many samples to obtain. Conventional sampling techniques are not always suitable in environmental studies and scientists have explored the use of remotely-sensed data as ancillary information to aid...
at reasonable logistical or financial costs . Remote sensing provides an attractive alternative. We discuss the range of different sensors that are...DARLA: Data Assimilation and Remote Sensing for Littoral Applications Final Report Award Number: N000141010932 Andrew T. Jessup Chris Chickadel...20. Radermacher, M., M. Wengrove, J. V. de Vries, and R. Holman (2014), Applicability of video-derived bathymetry estimates to nearshore current
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.
Full Text Available Africa. 2Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Lynwood Road, Pretoria 0002, South Africa. 3Tshwane University of Technology, Pretoria 0001, South Africa. ABSTRACT A mobile LIDAR (LIght Detection... obtained using the CSIR-NLC mobile LIDAR in a 23 hour field campaign at the University of Pretoria. Index Terms— Atmospheric measurements, Remote sensing, Aerosols, Air pollution, Meteorology 1. INTRODUCTION Remote sensing is a technique...
Senf, Cornelius; Seidl, Rupert; Hostert, Patrick
Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.
Quattrochi, Dale A.; Luvall, Jeffrey C.
Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of
In this chapter the author critically examines the prospects for reducing uncertainties over global biomass burning using remote sensing. First he considers the global temporal, spatial, and intensity distributions of fires and the remotely sensible signals they create and discusses the opportunities and problems that exist for matching available sensors to fire signal. Then he considers problems relating to instrumentation and to atmospheric interference
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
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.
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. PMID:25386759
Moore, Gerald K.
Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m. Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.
Hunt, G.; Patrick, P.H.; Sim, B.
A laboratory investigation was conducted to determine the capability and accuracy of a dual beam sonar system in classifying various targets. The ability to classify fish and/or distinguish fish from debris is essential if hydroacoustics are ever to be used truly remotely for hydroelectric power plant fish passage facilities. Preliminary results indicated that considerable filtering was occurring in the sonar sounder which limited its use in target classification. A wideband sonar detection module was developed which allowed for a more detailed reflected signal which probably will be necessary for fish identification. Another advantage that this modification appears to have over the existing system is an improved spatial resolution of targets, which can be significant if biomass estimates are based on echo counting techniques rather than echo integration ones. Based on the results, it may be possible to filter out or remove the influence of air bubbles in echo returns. As a result echo counts could more accurately be defined as fish counts. Target strengths of sturgeon were estimated using both the modified and original sounder. 12 refs., 11 figs., 2 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.
Wang, Shifeng; Koch, Barbara
The objects of the article are to determine the profits for solar energy integrating remote sensing data: the optimal locations of photovoltaic and the base price of electricity resulting from solar energy. An illustrated experiment with five European countries data sets is taken. Results indicate that Germany is the only optimal region to set up photovoltaic so as to satisfy the electricity demand of the five considered. Results also show that solar energy is a promising energy source since the highest base price of electricity resulting from solar energy is only 0.35 $/kWh. The base electricity price for Germany is the lowest whereas the base electricity price for Italy is the highest. Moreover, the results further indicate that the photovoltaic module price plays a key role in determining the best appropriate region(s) to install photovoltaic and the base electricity price. (author)
Wynne, R.H.; Lillesand, T.M.
The paper examines the general hypothesis that large-scale and long-term trends in lake ice formation and breakup, along with changes in the optical properties of lakes, can serve as robust integrated measures of regional and global climate change. Recent variation in the periodicity of lake ice formation and breakup is investigated using the AVHRR aboard the NOAA/TIROS series of polar orbiting satellites. The study area consists of 44 lakes and reservoirs with a surface area of greater than 1000 hectares in Wisconsin. The utility of AVHRR for lake ice detection with high temporal resolution is demonstrated, the relationship between ice phenology and periodicity with lake morphometry for the lakes in the study is elucidated, and remotely sensed measures of ice periodicity are correlated with local and regional temperature trends. 31 refs
Wang, Shifeng; Koch, Barbara [Department of Remote Sensing and Landscape Information Systems, University of Freiburg, 79106 Freiburg (Germany)
The objects of the article are to determine the profits for solar energy integrating remote sensing data: the optimal locations of photovoltaic and the base price of electricity resulting from solar energy. An illustrated experiment with five European countries data sets is taken. Results indicate that Germany is the only optimal region to set up photovoltaic so as to satisfy the electricity demand of the five considered. Results also show that solar energy is a promising energy source since the highest base price of electricity resulting from solar energy is only 0.35 $/kWh. The base electricity price for Germany is the lowest whereas the base electricity price for Italy is the highest. Moreover, the results further indicate that the photovoltaic module price plays a key role in determining the best appropriate region(s) to install photovoltaic and the base electricity price. (author)
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…
Cosentino, B.L.; Lillesand, T.M.
Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs
The overarching goal of this project was to integrate data from commercial remote sensing and spatial information (CRS&SI) technologies to create a novel data-driven decision making framework that empowers the railroad industry to monitor, assess, an...
Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.
DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at
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
Joseph, A.; Desa, E.
Acoustic techniques have become powerful tools for measurement of ocean circulation mainly because of the ability of acoustic signals to travel long distances in water, and the inherently non-invasive nature of measurement. The satellite remote...
Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes
Full Text Available China's long-term planning major projects "high-resolution earth observation system" has been invested nearly 100 billion and the satellites will reach 100 to 2020. As to 2/3 of China's area covered by mountains，it has a higher demand for remote sensing. In addition to light intensity, frequency, phase, polarization is also the main physical characteristics of remote sensing electromagnetic waves. Polarization is an important component of the reflected information from the surface and the atmospheric information, and the polarization effect of the ground object reflection is the basis of the observation of polarization remote sensing. Therefore, the effect of eliminating the polarization effect is very important for remote sensing applications. The main innovations of this paper is as follows: (1 Remote sensing observation method. It is theoretically deduced and verified that the polarization can weaken the light in the strong light region, and then provide the polarization effective information. In turn, the polarization in the low light region can strengthen the weak light, the same can be obtained polarization effective information. (2 Polarization effect of vegetation. By analyzing the structure characteristics of vegetation, polarization information is obtained, then the vegetation structure information directly affects the absorption of biochemical components of leaves. (3 Atmospheric polarization neutral point observation method. It is proved to be effective to achieve the ground-gas separation, which can achieve the effect of eliminating the atmospheric polarization effect and enhancing the polarization effect of the object.
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
Maria Laura Zoffoli
Full Text Available Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.
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. [...
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.
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.
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.
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.
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)
Pakistan's periled treasures of mangroves require protection from devastating anthropogenic activities, which can only be achieved through the identification and management of this habitat. The primary objective of this study is to identify the potential habitat of mangroves along the coastline of Pakistan with the help of Remote Sensing (RS) and Geographical Information System (GIS) techniques. Once the mangroves were identified, species of mangroves need to be separated through Object Based Image Analysis (OBIA) which gave the area of mangroves and non mangroves sites. Later other parameters of Sea Surface Temperature, Sea Surface Salinity, chlorophyll-a along with altimetry data were used to assess the climatic variations on the spatio-temporal distribution of mangroves. Since mangroves provide economical, ecological, biological indication of Coastal Change or Sea Level Rise. Therefore, this provides a strong platform to assess the climatic variations which are posing negative impacts on the mangroves ecosystem. The results indicate that mangroves are present throughout along the coastline, proving that Pakistan is rich in these diverse ecosystems. Pakistan being at important geo strategic position can also benefit from its vast mangroves and other coastal resources such as coral reefs and fish varieties. Moreover, coastal zone management through involvement of the local community and establishment of Marine Protected Area (MPA) is the need of the hour to avoid deforestation of mangroves, which can prove to be deadly damaging for the fish populace since it provides habitats to various marine animals. However, the established relationship among SST, SSS, chlorophyll-a and altimetry data assisted to know the suitable sites for mangroves. But due to enhanced climatic impacts these relationships are distorted which has posed devastating effects on the growth and distribution of mangroves. Study area was Karachi Coast, Pakistan. The total area of Karachi is about 70