Shmirko, Konstantin; Bobrikov, Alexey; Pavlov, Andrey
Atmosphere responses for more than 90% of all radiation measured by satellite. Due to this, atmospheric correction plays an important role in separating water leaving radiance from the signal, evaluating concentration of various water pigments (chlorophyll-A, DOM, CDOM, etc). The elimination of atmospheric intrinsic radiance from remote sensing signal referred to as atmospheric correction.
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.
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.
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.
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.
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...
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)
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...
Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan
GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.
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.
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.
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.
Short, David A.
Rainrates retrieved from past and present satellite-borne microwave sensors are affected by a fundamental remote sensing problem. Sensor fields-of-view are typically large enough to encompass substantial rainrate variability, whereas the retrieval algorithms, based on radiative transfer calculations, show a non-linear relationship between rainrate and microwave brightness temperature. Retrieved rainrates are systematically too low. A statistical model of the bias problem shows that bias correction factors depend on the probability distribution of instantaneous rainrate and on the average thickness of the rain layer.
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
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 ...
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.
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.
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...
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 ...
Ao, Hou-jun; Yang, Le-ping; Zhu, Yan-wei; Zhang, Yuan-wen; Huang, Huan
Rescue of satellite with attitude fault is of great value. Satellite with improper injection attitude may lose contact with ground as the antenna points to the wrong direction, or encounter energy problems as solar arrays are not facing the sun. Improper uploaded command may set the attitude out of control, exemplified by Japanese Hitomi spacecraft. In engineering practice, traditional physical contact approaches have been applied, yet with a potential risk of collision and a lack of versatility since the mechanical systems are mission-specific. This paper puts forward a touchless attitude correction approach, in which three satellites are considered, one having constant dipole and two having magnetic coils to control attitude of the first. Particular correction configurations are designed and analyzed to maintain the target's orbit during the attitude correction process. A reference coordinate system is introduced to simplify the control process and avoid the singular value problem of Euler angles. Based on the spherical triangle basic relations, the accurate varying geomagnetic field is considered in the attitude dynamic mode. Sliding mode control method is utilized to design the correction law. Finally, numerical simulation is conducted to verify the theoretical derivation. It can be safely concluded that the no-contact attitude correction approach for the satellite with uniaxial constant magnetic moment is feasible and potentially applicable to on-orbit operations.
Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei
Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.
Dean, K.; Servilla, M.; Roach, A.; Foster, B.; Engle, K.
Satellite monitoring of remote volcanoes is greatly benefitting the Alaska Volcano Observatory (AVO), and last year's eruption of the Okmok Volcano in the Aleutian Islands is a good case in point. The facility was able to issue and refine warnings of the eruption and related activity quickly, something that could not have been done using conventional seismic surveillance techniques, since seismometers have not been installed at these locations.AVO monitors about 100 active volcanoes in the North Pacific (NOPAC) region, but only a handful are observed by costly and logistically complex conventional means. The region is remote and vast, about 5000 × 2500 km, extending from Alaska west to the Kamchatka Peninsula in Russia (Figure 1). Warnings are transmitted to local communities and airlines that might be endangered by eruptions. More than 70,000 passenger and cargo flights fly over the region annually, and airborne volcanic ash is a threat to them. Many remote eruptions have been detected shortly after the initial magmatic activity using satellite data, and eruption clouds have been tracked across air traffic routes. Within minutes after eruptions are detected, information is relayed to government agencies, private companies, and the general public using telephone, fax, and e-mail. Monitoring of volcanoes using satellite image data involves direct reception, real-time monitoring, and data analysis. Two satellite data receiving stations, located at the Geophysical Institute, University of Alaska Fairbanks (UAF), are capable of receiving data from the advanced very high resolution radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites and from synthetic aperture radar (SAR) equipped satellites.
Topaz, Jeremy M.; Braun, Ofer; Freiman, Dov
An athermalized objective has been designed for a compact, lightweight push-broom camera which is under development at El-Op Ltd. for use in small remote-sensing satellites. The high performance objective has a fixed focus setting, but maintains focus passively over the full range of temperatures encountered in small satellites. The lens is an F/5.0, 320 mm focal length Tessar type, operating over the range 0.5 - 0.9 micrometers . It has a 16 degree(s) field of view and accommodates various state-of-the-art silicon detector arrays. The design and performance of the objective is described in this paper.
Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.
Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary
Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs
Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.
Sogacheva, Larisa; Kolmonen, Pekka; Saponaro, Giulia; Virtanen, Timo; Rodriguez, Edith; Sundström, Anu-Maija; Atlaskina, Ksenia; de Leeuw, Gerrit
Satellite remote sensing provides the spatial distribution of aerosol and cloud properties over a wide area. In our studies large data sets are used for statistical studies on aerosol and cloud interaction in an area over Fennoscandia, the Baltic Sea and adjacent regions over the European mainland. This area spans several regimes with different influences on aerosol cloud interaction such as a the transition from relative clean air over Fennoscandia to more anthropogenically polluted air further south, and the influence maritime air over the Baltic and oceanic air advected from the North Atlantic. Anthropogenic pollution occurs in several parts of the study area, and in particular near densely populated areas and megacities, but also in industrialized areas and areas with dense traffic. The aerosol in such areas is quite different from that produced over the boreal forest and has different effects on air quality and climate. Studies have been made on the effects of aerosols on air quality and on the radiation balance in China. The aim of the study is to study the effect of these different regimes on aerosol-cloud interaction using a large aerosol and cloud data set retrieved with the (Advanced) Along Track Scanning Radiometer (A)ATSR Dual View algorithm (ADV) further developed at Finnish Meteorological Institute and aerosol and cloud data provided by MODIS. Retrieval algorithms for aerosol and clouds have been developed for the (A)ATSR, consisting of a series of instruments of which we use the second and third one: ATSR-2 which flew on the ERS-2 satellite (1995-2003) and AATSR which flew on the ENVISAT satellite (2002-2012) (both from the European Space Agency, ESA). The ADV algorithm provides aerosol data on a global scale with a default resolution of 10x10km2 (L2) and an aggregate product on 1x1 degree (L3). Optional, a 1x1 km2 retrieval products is available over smaller areas for specific studies. Since for the retrieval of AOD no prior knowledge is needed on
Dushin, N V; Beliaev, V S; Gonchar, P A; Barashkov, V I; Kravchinina, V V; Frolov, M A
Remote results evidence high refraction efficiency of tunnel keratoplasty, stable results being observed for up to 15 years. A total of 104 operations (58 patients) were analyzed for a period of observation of more than 10 years. The patients' ages varied from 17 to 52 years, there were 34 women and 24 men. The main advantage of interlamellar refraction meridional keratoplasty is easiness of operation. At present it is the operation of choice for dosed reduction of eye refraction aimed at correction of high myopia and astigmatism. The possibility of correcting residual myopia after keratotomy and repair of refraction abnormalities resultant from perforating keratoplasty is particularly interesting. The possibility of regulating the corrective effect in remote periods by replacing the implants also deserves attention. Hence, low traumatism, high efficiency, and stability of the refraction effect once more confirm our recommendation to use tunnel keratoplasty in clinical practice.
Hoque, M. M.; Jakowski, N.
The ionosphere is recognized as a major error source for single-frequency operations of global navigation satellite systems (GNSS). To enhance single-frequency operations the global positioning system (GPS) uses an ionospheric correction algorithm (ICA) driven by 8 coefficients broadcasted in the navigation message every 24 h. Similarly, the global navigation satellite system Galileo uses the electron density NeQuick model for ionospheric correction. The Galileo satellite vehicles (SVs) transmit 3 ionospheric correction coefficients as driver parameters of the NeQuick model. In the present work, we propose an alternative ionospheric correction algorithm called Neustrelitz TEC broadcast model NTCM-BC that is also applicable for global satellite navigation systems. Like the GPS ICA or Galileo NeQuick, the NTCM-BC can be optimized on a daily basis by utilizing GNSS data obtained at the previous day at monitor stations. To drive the NTCM-BC, 9 ionospheric correction coefficients need to be uploaded to the SVs for broadcasting in the navigation message. Our investigation using GPS data of about 200 worldwide ground stations shows that the 24-h-ahead prediction performance of the NTCM-BC is better than the GPS ICA and comparable to the Galileo NeQuick model. We have found that the 95 percentiles of the prediction error are about 16.1, 16.1 and 13.4 TECU for the GPS ICA, Galileo NeQuick and NTCM-BC, respectively, during a selected quiet ionospheric period, whereas the corresponding numbers are found about 40.5, 28.2 and 26.5 TECU during a selected geomagnetic perturbed period. However, in terms of complexity the NTCM-BC is easier to handle than the Galileo NeQuick and in this respect comparable to the GPS ICA.
Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter
With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.
Haris Akram Bhatti
Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.
Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter
With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363
Tramutoli, V; Di Bello, G [Potenza Univ., Potenza (Italy). Dipt. di Ingegneria e Fisica dell' Ambiente; Pergola, N; Piscitelli, S [Consiglio Nazionale delle Ricerche, Istituto di Metodologie Avanzate di Analisi Ambientale, Potenza (Italy)
Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity) whose variable contributions to the investigated signal can be so high as to completely mask (or simulate) the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT) has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks) which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observation field also in the presence of highly variable contributions from atmospheric (transmittance), surface (emissivity and morphology) and observational (time/season, but also solar and satellite zenithal angles) conditions. This work presents the first preliminary results, based on several years of NOA A/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications) as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.
Full Text Available Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity whose variable contributions to the investigated signal can be so high as to completely mask (or simulate the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observational field also in the presence of highly variable contributions from atmospheric (transmittance, surface (emissivity and morphology and observational (time/season, but also solar and satellite zenithal angles conditions.This work presents the first preliminary results, based on several years of NOAA/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.
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.
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.
Delgreco, F.P.; Eastes, R.W.; Huffman, R.E.
The Polar BEAR satellite carries the Auroral Ionospheric Remote Sensor (AIRS) instrument, which is designed to return four simultaneous images of atmospheric radiation at northern latitudes, has thus far yielded over 5000 images. Polar BEAR was in operation during March, 1987, when the preliminary K(p) reached a value of 9 over a six-hour period; at that time, AIRS was operating at the 1304 A atomic oxygen wavelength and recorded remarkable data, which are here presented. Due to the intense activity, the AIRS data were barely able to register the poleward edge of the aurora. 6 refs
Henderson, Frederick B.; Penfield, Glen T.; Grubbs, Donald K.
The new LANDSAT-4,-5/Thematic Mapper (TM) land observational satellite remote sensing systems are providing dramatically new and important short wave infrared (SWIR) data, which combined with Landsat's Multi-Spectral Scanner (MSS) visible (VIS), very near infrared (VNIR), and thermal infrared (TI) data greatly improves regional geological mapping on a global scale. The TM will significantly improve clay, iron oxide, aluminum, and nickel laterite mapping capabilities over large areas of the world. It will also improve the ability to discriminate vegetation stress and species distribution associated with lateritic environments. Nickel laterites on Gag Island, Indonesia are defined by MSS imagery. Satellite imagery of the Cape Bougainville and the Darling Range, Australia bauxite deposits show the potential use of MSS data for exploration and mining applications. Examples of satellite syn-thetic aperture radar (SAR) for Jamaica document the use of this method for bauxite exploration. Thematic Mapper data will be combined with the French SPOT satellite's high spatial resolution and stereoscopic digital data, and U.S., Japanese, European, and Canadian Synthetic Aperture Radar (SAR) data to assist with logistics, mine development, and environ-mental concerns associated with aluminum and nickel lateritic deposits worldwide.
Full Text Available The uneven illumination phenomenon caused by thin clouds will reduce the quality of remote sensing images, and bring adverse effects to the image interpretation. To remove the effect of thin clouds on images, an uneven illumination correction can be applied. In this paper, an effective uneven illumination correction algorithm is proposed to remove the effect of thin clouds and to restore the ground information of the optical remote sensing image. The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image. As a result, a wavelet domain enhancement is performed for the image in Hue-Saturation-Value (HSV color space. We use images with thin clouds in Wuhan area captured by QuickBird and ZiYuan-3 (ZY-3 satellites for experiments. Three traditional uneven illumination correction algorithms, i.e., multi-scale Retinex (MSR algorithm, homomorphic filtering (HF-based algorithm, and wavelet transform-based MASK (WT-MASK algorithm are performed for comparison. Five indicators, i.e., mean value, standard deviation, information entropy, average gradient, and hue deviation index (HDI are used to analyze the effect of the algorithms. The experimental results show that the proposed algorithm can effectively eliminate the influences of thin clouds and restore the real color of ground objects under thin clouds.
Omar A. Alcover Firpi
Full Text Available A review of Google Earth Engine for archaeological remote sensing using satellite data. GEE is a freely accessible software option for processing remotely sensed data, part of the larger Google suite of products.
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.
Kazaryan, Maretta; Shakhramanyan, Mihail; Nedkov, Roumen; Richter, Andrey; Borisova, Denitsa; Stankova, Nataliya; Ivanova, Iva; Zaharinova, Mariana
In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.
Tao Zhangsheng; Zhao Yingjun
Based on the application status of satellite remote sensing technology to nuclear safeguards, advantage of satellite remote sensing technology is analyzed, main types of satellite image used in nuclear safeguards are elaborated and the main application of satellite images is regarded to detect, verify and monitor nuclear activities; verify additional protocol declaration and design information, support performing complementary access inspections; investigate alleged undeclared activities based on open source or the third party information. Application examples of satellite image in nuclear safeguards to analyze nuclear facilities by other countries, the ability of remote sensing technology in nuclear safeguards is discussed. (authors)
Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.
Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.
Jackson, J. M.; Munger, J.; Emch, P. G.; Sen, B.; Gu, D.
Satellite to ground communication bandwidth limitations place constraints on current earth remote sensing instruments which limit the spatial and spectral resolution of data transmitted to the ground for processing. Instruments such as VIIRS, CrIS and OMPS on the Soumi-NPP spacecraft must aggregate data both spatially and spectrally in order to fit inside current data rate constraints limiting the optimal use of the as-built sensors. Future planned missions such as HyspIRI, SLI, PACE, and NISAR will have to trade spatial and spectral resolution if increased communication band width is not made available. A number of high-impact, environmental remote sensing disciplines such as hurricane observation, mega-city air quality, wild fire detection and monitoring, and monitoring of coastal oceans would benefit dramatically from enabling the downlinking of sensor data at higher spatial and spectral resolutions. The enabling technologies of multi-Gbps Ka-Band communication, flexible high speed on-board processing, and multi-Terabit SSRs are currently available with high technological maturity enabling high data volume mission requirements to be met with minimal mission constraints while utilizing a limited set of ground sites from NASA's Near Earth Network (NEN) or TDRSS. These enabling technologies will be described in detail with emphasis on benefits to future remote sensing missions currently under consideration by government agencies.
Full Text Available Coal is the main source of energy. In China and Vietnam, coal resources are very rich, but the exploration level is relatively low. This is mainly caused by the complicated geological structure, the low efficiency, the related damage, and other bad situations. To this end, we need to make use of some advanced technologies to guarantee the resource exploration is implemented smoothly and orderly. Numerous studies show that remote sensing technology is an effective way in coal exploration and measurement. In this paper, we try to measure the distribution and reserves of open-air coal area through satellite imagery. The satellite picture of open-air coal mining region in Quang Ninh Province of Vietnam was collected as the experimental data. Firstly, the ENVI software is used to eliminate satellite imagery spectral interference. Then, the image classification model is established by the improved ELM algorithm. Finally, the effectiveness of the improved ELM algorithm is verified by using MATLAB simulations. The results show that the accuracies of the testing set reach 96.5%. And it reaches 83% of the image discernment precision compared with the same image from Google.
Full Text Available An autonomous remote clock control system is proposed to provide time synchronization and frequency syntonization for satellite to satellite or ground to satellite time transfer, with the system comprising on-board voltage controlled oven controlled crystal oscillators (VC-OCXOs that are disciplined to a remote master atomic clock or oscillator. The synchronization loop aims to provide autonomous operation over extended periods, be widely applicable to a variety of scenarios and robust. A new architecture comprising the use of frequency division duplex (FDD, synchronous time division (STDD duplex and code division multiple access (CDMA with a centralized topology is employed. This new design utilizes dual one-way ranging methods to precisely measure the clock error, adopts least square (LS methods to predict the clock error and employs a third-order phase lock loop (PLL to generate the voltage control signal. A general functional model for this system is proposed and the error sources and delays that affect the time synchronization are discussed. Related algorithms for estimating and correcting these errors are also proposed. The performance of the proposed system is simulated and guidance for selecting the clock is provided.
To understand and assess the effect of the sensor spectral response function (SRF) on the accuracy of the top of the atmosphere (TOA) Rayleigh-scattering radiance computation, new TOA Rayleigh radiance lookup tables (LUTs) over global oceans and inland waters have been generated. The new Rayleigh LUTs include spectral coverage of 335-2555 nm, all possible solar-sensor geometries, and surface wind speeds of 0-30 m/s. Using the new Rayleigh LUTs, the sensor SRF effect on the accuracy of the TOA Rayleigh radiance computation has been evaluated for spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Joint Polar Satellite System (JPSS)-1, showing some important uncertainties for VIIRS-SNPP particularly for large solar- and/or sensor-zenith angles as well as for large Rayleigh optical thicknesses (i.e., short wavelengths) and bands with broad spectral bandwidths. To accurately account for the sensor SRF effect, a new correction algorithm has been developed for VIIRS spectral bands, which improves the TOA Rayleigh radiance accuracy to ~0.01% even for the large solar-zenith angles of 70°-80°, compared with the error of ~0.7% without applying the correction for the VIIRS-SNPP 410 nm band. The same methodology that accounts for the sensor SRF effect on the Rayleigh radiance computation can be used for other satellite sensors. In addition, with the new Rayleigh LUTs, the effect of surface atmospheric pressure variation on the TOA Rayleigh radiance computation can be calculated precisely, and no specific atmospheric pressure correction algorithm is needed. There are some other important applications and advantages to using the new Rayleigh LUTs for satellite remote sensing, including an efficient and accurate TOA Rayleigh radiance computation for hyperspectral satellite remote sensing, detector-based TOA Rayleigh radiance computation, Rayleigh radiance calculations for high altitude
Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon
The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development.
Petersen, G. W.; Connors, K. F.; Miller, D. A.; Day, R. L.; Gardner, T. W.
Remote sensing data on desert soils and landscapes, obtained by the Landsat TM, Heat Capacity Mapping Mission (HCMM), Simulated SPOT, and Thermal IR Multispectral Scanner (TIMS) aboard an aircraft, are discussed together with the analytical techniques used in the studies. The TM data for southwestern Nevada were used to discriminate among the alluvial fan deposits with different degrees of desert pavement and varnish, and different vegetation cover. Thermal-IR data acquired from the HCMM satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures in central Utah. Simulated SPOT data for northwestern New Mexico identified geomorphic features, such as differences in eolian sand cover and fluvial incision, while the TIMS data depicted surface geologic features of the Saline Valley in California.
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
Sahai, Arushi; Shao, Andrew; Toloba, Elisa; Guhathakurta, Puragra; Peng, Eric W.; Zhang, Hao
We present a sample of “orphan” globular clusters (GCs) with previously unknown parent galaxies, which we determine to be remote satellites of M87, a massive elliptical galaxy at the center of the Virgo Cluster of Galaxies. Because GCs were formed in the early universe along with their original parent galaxies, which were cannibalized by massive galaxies such as M87, they share similar age and chemical properties. In this study, we first confirm that M87 is the adoptive parent galaxy of our orphan GCs using photometric and spectroscopic data to analyze spatial and velocity distributions. Next, we increase the signal-to-noise ratio of our samples’ spectra through a process known as coaddition. We utilize spectroscopic absorption lines to determine the age and metallicity of our orphan GCs through comparison to stellar population synthesis models, which we then relate to the GCs’ original parent galaxies using a mass-metallicity relation. Our finding that remote GCs of M87 likely developed in galaxies with ~1010 solar masses implies that M87’s outer halo is formed of relatively massive galaxies, serving as important parameters for developing theories about the formation and evolution of massive galaxies.This research was funded in part by NASA/STScI and the National Science Foundation. Most of this work was carried out by high school students working under the auspices of the Science Internship Program at UC Santa Cruz.
Hlaing, Soe; Gilerson, Alexander; Harmal, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir
Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.
Alder-Golden, Steven M.; Rochford, Peter; Matthew, Michael; Berk, Alexander
Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.
A. H. Ahrari
Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.
Jonckheere, Inge; Sandoval, Alberto
REDD, which stands for 'Reducing Emissions from Deforestation and Forest Degradation in Developing Countries' - is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. The UN-REDD Programme, a collaborative partnership between FAO, UNDP and UNEP launched in September 2008, supports countries to develop capacity to REDD and to implement a future REDD mechanism in a post- 2012 climate regime. The programme works at both the national and global scale, through support mechanisms for country-driven REDD strategies and international consensus-building on REDD processes. The UN-REDD Programme gathers technical teams from around the world to develop common approaches, analyses and guidelines on issues such as measurement, reporting and verification (MRV) of carbon emissions and flows, remote sensing, and greenhouse gas inventories. Within the partnership, FAO supports countries on technical issues related to forestry and the development of cost effective and credible MRV processes for emission reductions. While at the international level, it fosters improved guidance on MRV approaches, including consensus on principles and guidelines for MRV and training programmes.It provides guidance on how best to design and implement REDD, to ensure that forests continue to provide multiple benefits for livelihoods and biodiversity to societies while storing carbon at the same time. Other areas of work include national forest assessments and monitoring of in-country policy and institutional change. The outcomes about the role of satellite remote sensing technologies as a tool for monitoring, assessment, reporting and verification of carbon credits and co-benefits under the REDD mechanism are here presented.
Wahballah, Walid A.; Bazan, Taher M.; El-Tohamy, Fawzy; Fathy, Mahmoud
High-resolution remote sensing satellites (HRRSS) that use time delay and integration (TDI) CCDs have the potential to introduce large amounts of image smear. Clocking and velocity mismatch smear are two of the key factors in inducing image smear. Clocking smear is caused by the discrete manner in which the charge is clocked in the TDI-CCDs. The relative motion between the HRRSS and the observed object obliges that the image motion velocity must be strictly synchronized with the velocity of the charge packet transfer (line rate) throughout the integration time. During imaging an object off-nadir, the image motion velocity changes resulting in asynchronization between the image velocity and the CCD's line rate. A Model for estimating the image motion velocity in HRRSS is derived. The influence of this velocity mismatch combined with clocking smear on the modulation transfer function (MTF) is investigated by using Matlab simulation. The analysis is performed for cross-track and along-track imaging with different satellite attitude angles and TDI steps. The results reveal that the velocity mismatch ratio and the number of TDI steps have a serious impact on the smear MTF; a velocity mismatch ratio of 2% degrades the MTFsmear by 32% at Nyquist frequency when the TDI steps change from 32 to 96. In addition, the results show that to achieve the requirement of MTFsmear >= 0.95 , for TDI steps of 16 and 64, the allowable roll angles are 13.7° and 6.85° and the permissible pitch angles are no more than 9.6° and 4.8°, respectively.
Kuo, Jen-Chueh; Ling, Jer
The optical telescope system in remote sensing satellite must be precisely aligned to obtain high quality images during its mission life. In practical, because the telescope mirrors could be misaligned due to launch loads, thermal distortion on supporting structures or hygroscopic distortion effect in some composite materials, the optical telescope system is often equipped with refocussing mechanism to re-align the optical elements while optical element positions are out of range during image acquisition. This paper is to introduce satellite Refocussing mechanism function model design development process and the engineering models. The design concept of the refocussing mechanism can be applied on either cassegrain type telescope or korsch type telescope, and the refocussing mechanism is located at the rear of the secondary mirror in this paper. The purpose to put the refocussing mechanism on the secondary mirror is due to its higher sensitivity on MTF degradation than other optical elements. There are two types of refocussing mechanism model to be introduced: linear type model and rotation type model. For the linear refocussing mechanism function model, the model is composed of ceramic piezoelectric linear step motor, optical rule as well as controller. The secondary mirror is designed to be precisely moved in telescope despace direction through refocussing mechanism. For the rotation refocussing mechanism function model, the model is assembled with two ceramic piezoelectric rotational motors around two orthogonal directions in order to adjust the secondary mirror attitude in tilt angle and yaw angle. From the validation test results, the linear type refocussing mechanism function model can be operated to adjust the secondary mirror position with minimum 500 nm resolution with close loop control. For the rotation type model, the attitude angle of the secondary mirror can be adjusted with the minimum 6 sec of arc resolution and 5°/sec of angle velocity.
Wang, Menghua; Shi, Wei; Jiang, Lide
A regional near-infrared (NIR) ocean normalized water-leaving radiance (nL(w)(λ)) model is proposed for atmospheric correction for ocean color data processing in the western Pacific region, including the Bohai Sea, Yellow Sea, and East China Sea. Our motivation for this work is to derive ocean color products in the highly turbid western Pacific region using the Geostationary Ocean Color Imager (GOCI) onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS). GOCI has eight spectral bands from 412 to 865 nm but does not have shortwave infrared (SWIR) bands that are needed for satellite ocean color remote sensing in the turbid ocean region. Based on a regional empirical relationship between the NIR nL(w)(λ) and diffuse attenuation coefficient at 490 nm (K(d)(490)), which is derived from the long-term measurements with the Moderate-resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, an iterative scheme with the NIR-based atmospheric correction algorithm has been developed. Results from MODIS-Aqua measurements show that ocean color products in the region derived from the new proposed NIR-corrected atmospheric correction algorithm match well with those from the SWIR atmospheric correction algorithm. Thus, the proposed new atmospheric correction method provides an alternative for ocean color data processing for GOCI (and other ocean color satellite sensors without SWIR bands) in the turbid ocean regions of the Bohai Sea, Yellow Sea, and East China Sea, although the SWIR-based atmospheric correction approach is still much preferred. The proposed atmospheric correction methodology can also be applied to other turbid coastal regions.
Liu, Ruian; Liu, Nan; Zeng, Beibei; Chen, Tingting; Yin, Ninghao
Aiming at the disadvantage of current geometry correction algorithm for UAV remote sensing image, a new algorithm is proposed. Adaptive genetic algorithm (AGA) and RBF neural network are introduced into this algorithm. And combined with the geometry correction principle for UAV remote sensing image, the algorithm and solving steps of AGA-RBF are presented in order to realize geometry correction for UAV remote sensing. The correction accuracy and operational efficiency is improved through optimizing the structure and connection weight of RBF neural network separately with AGA and LMS algorithm. Finally, experiments show that AGA-RBF algorithm has the advantages of high correction accuracy, high running rate and strong generalization ability.
Hilker, Thomas; Lyapustin, Alexei I.; Tucker, Compton J.; Sellers, Piers J.; Hall, Forrest G.; Wang, Yujie
Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased
Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman
Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.
Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.
This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.
Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming
This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919
Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming
This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.
Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.
Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.
Byoung-Sun Lee; Jung-Hyun Jo; Sang-Young Park; Kyu-Hong Choi; Chun-Hwey Kim
The differential correction process determining osculating orbital elements as correct as possible at a given instant of time from tracking data of artificial satellite was accomplished. Preliminary orbital elements were used as an initial value of the differential correction procedure and iterated until the residual of real observation(O) and computed observation(C) was minimized. Tracking satellite was NOAA-9 or TIROS-N series. Two types of tracking data were prediction data precomputed fro...
Snow and Avalanche Study Establishment, Defence Research and Development Organisation,. Chandigarh 160 ... IRS P6 satellite images and the qualitative and quantitative comparative analysis in detail. Both .... Top: AWiFS satellite image of Western Himalaya and bottom: zoom image of the study area shown with white.
Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang
According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.
Roy, D.; Purna Kumari, B.; Manju Sarma, M.; Aparna, N.; Gopal Krishna, B.
The quality of Remote Sensing data is an important parameter that defines the extent of its usability in various applications. The data from Remote Sensing satellites is received as raw data frames at the ground station. This data may be corrupted with data losses due to interferences during data transmission, data acquisition and sensor anomalies. Thus it is important to assess the quality of the raw data before product generation for early anomaly detection, faster corrective actions and product rejection minimization. Manual screening of raw images is a time consuming process and not very accurate. In this paper, an automated process for identification and quantification of losses in raw data like pixel drop out, line loss and data loss due to sensor anomalies is discussed. Quality assessment of raw scenes based on these losses is also explained. This process is introduced in the data pre-processing stage and gives crucial data quality information to users at the time of browsing data for product ordering. It has also improved the product generation workflow by enabling faster and more accurate quality estimation.
Chen, Chia-Ray; Hwang, Feng-Tai; Hsueh, Chuang-Wei
Revisiting time and global coverage are two major requirements for most of the remote sensing satellites. Constellation of satellites can get the benefit of short revisit time and global coverage. Typically, remote sensing satellites prefer to choose Sun Synchronous Orbit (SSO) because of fixed revisiting time and Sun beta angle. The system design and mission operation will be simple and straightforward. However, if we focus on providing remote sensing and store-and-forward communication services for low latitude countries, Sun Synchronous Orbit will not be the best choice because we need more satellites to cover the communication service gap in low latitude region. Sometimes the design drivers for remote sensing payloads are conflicted with the communication payloads. For example, lower orbit altitude is better for remote sensing payload performance, but the communication service zone will be smaller and we need more satellites to provide all time communication service. The current studies focus on how to provide remote sensing and communication services for low latitude countries. A cost effective approach for the mission, i.e. constellation of microsatellites, will be evaluated in this paper.
Remote sensing provides an important source of information to characterize soil and crop variability for both within-season and after-season management despite the availability of numerous ground-based soil and crop sensors. Remote sensing applications in precision agriculture have been steadily inc...
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding
sensed satellite data using open source support. Richa Sharma .... Decision tree classification techniques have been .... the USGS Earth Resource Observation Systems. (EROS) ... for shallow water, 11% were for sparse and dense built-up ...
Piester, D.; Rost, M.; Fujieda, M.; Feldmann, T.; Bauch, A.
In the global network of institutions engaged with the realization of International Atomic Time (TAI), atomic clocks and time scales are compared by means of the Global Positioning System (GPS) and by employing telecommunication satellites for two-way satellite time and frequency transfer (TWSTFT). The frequencies of the state-of-the-art primary caesium fountain clocks can be compared at the level of 10−15 (relative, 1 day averaging) and time scales can be synchronized...
We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the
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
Full Text Available Under the background of the trouble shooting requirements of FENGYUN-3 (FY-3 meteorological satellites data acquisition in domestic and oversea ground stations, a remote fault reasoning diagnosis system is developed by Java 1.6 in eclipse 3.6 platform. The general framework is analyzed, the workflow is introduced. Based on the system, it can realize the remote and centralized monitoring of equipment running status in ground stations，triggering automatic fault diagnosis and rule based fault reasoning by parsing the equipment quality logs, generating trouble tickets and importing expert experience database, providing text and graphics query methods. Through the practical verification, the system can assist knowledge engineers in remote precise and rapid fault location with friendly graphical user interface, boost the fault diagnosis efficiency, enhance the remote monitoring ability of integrity operating control system. The system has a certain practical significance to improve reliability of FY-3 meteorological satellites data acquisition.
Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.
Gavili Kilaneh, Narin; Mashhadi Hossainali, Masoud
Due to the recent advances in the Global Navigation Satellite System Remote sensing (GNSS¬R) applications, optimization of a satellite orbit to investigate the Earth's properties seems significant. The comparison of the GNSS direct and reflected signals received by a Low Earth Orbit (LEO) satellite introduces a new technique to remotely sense the Earth. Several GNSS¬R missions including Cyclone Global Navigation Satellite System (CYGNSS) have been proposed for different applications such as the ocean wind speed and height monitoring. The geometric optimization of the satellite orbit before starting the mission is a key step for every space mission. Since satellite constellation design varies depending on the application, we have focused on the required geometric criteria for oceanography applications in a specified region. Here, the total number of specular points, their spatial distribution and the accuracy of their position are assumed to be sufficient for oceanography applications. Gleason's method is used to determine the position of specular points. We considered the 2-D lattice and 3-D lattice theory of flower constellation to survey whether a circular orbit or an elliptical one is suitable to improve the solution. Genetic algorithm is implemented to solve the problem. To check the visibility condition between the LEO and GPS satellites, the satellite initial state is propagated by a variable step size numerical integration method. Constellation orbit parameters achieved by optimization provide a better resolution and precession for the specular points in the study area of this research.
Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T
An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.
Saito, R.; Houweling, S.; Patra, P. K.; Belikov, D.; Lokupitiya, R.; Niwa, Y.; Chevallier, F.; Saeki, T.; Maksyutov, S.
A model-based three-dimensional (3-D) climatology of atmospheric CO2 concentrations has been constructed for the analysis of satellite observations, as a priori information in retrieval calculations, and for preliminary evaluation of remote sensing products. The locations of ground-based instruments
Carmichael, J.; Eldridge, R.; Friedman, E.; Keitz, E.
An approach to the development of a prioritized list of scientific goals in atmospheric research is provided. The results of the analysis are used to estimate the contribution of various spacecraft/remote sensor combinations for each of several important constituents of the stratosphere. The evaluation of the combinations includes both single-instrument and multiple-instrument payloads. Attention was turned to the physical and chemical features of the atmosphere as well as the performance capability of a number of atmospheric remote sensors. In addition, various orbit considerations were reviewed along with detailed information on stratospheric aerosols and the impact of spacecraft environment on the operation of the sensors.
Maharana, P. K.; Goel, P. S.
The effect of flexible arrays on sun tracking for the IRS satellite is studied. Equations of motion of satellites carrying a rotating flexible appendage are developed following the Newton-Euler approach and utilizing the constrained modes of the appendage. The drive torque, detent torque and friction torque in the SADA are included in the model. Extensive simulations of the slewing motion are carried out. The phenomena of back-stepping, step-missing, step-slipping and the influences of array flexibility in the acquisition mode are observed for certain combinations of parameters.
Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre
While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.
Nielsen, Søren Zebitz
This thesis studies the spatio-temporal patterns and trends in NO2 air pollution over Denmark using the satellite remote sensing product OMNO2e retrieved from the OMI instrument on the NASA AURA satellite. These data are related to in situ measurements of NO2 made at four rural and four urban...... measured in Denmark. Trends in the data are assessed and declining trends are seen over several European cities, whereas no significant trends are found in the Danish area. The mean distribution of NO2 from the satellite data is also used to evaluate the NOx emission inventory....
Since the launch of Sputnik I in 1957, satellite radio beacons have been used to measure the total electron content of the ionosphere. A review of the role of satellite beacons in studies of the vertical and spatial structure of the total electron content and on the occurrence of plasma irregularities, both of which affect transionospheric radio signals, is presented. Measurements of Faraday rotation and time of flight give information on the topside of the ionosphere and on the protonosphere. Morphological studies show that the slab thickness of the ionosphere depends on the solar index but is approximately independent of geographical location. Scintillation of amplitude, phase, polarization, and angle provide information on plasma irregularity occurrence in space and time. (author). 23 refs., 16 figs ., 4 tabs
P R Renosh
Full Text Available Satellite remote sensing observations allow the ocean surface to be sampled synoptically over large spatio-temporal scales. The images provided from visible and thermal infrared satellite observations are widely used in physical, biological, and ecological oceanography. The present work proposes a method to understand the multi-scaling properties of satellite products such as the Chlorophyll-a (Chl-a, and the Sea Surface Temperature (SST, rarely studied. The specific objectives of this study are to show how the small scale heterogeneities of satellite images can be characterised using tools borrowed from the fields of turbulence. For that purpose, we show how the structure function, which is classically used in the frame of scaling time series analysis, can be used also in 2D. The main advantage of this method is that it can be applied to process images which have missing data. Based on both simulated and real images, we demonstrate that coarse-graining (CG of a gradient modulus transform of the original image does not provide correct scaling exponents. We show, using a fractional Brownian simulation in 2D, that the structure function (SF can be used with randomly sampled couple of points, and verify that 1 million of couple of points provides enough statistics.
Mishchenko, M I; Cairns, B; Chowdhary, J; Geogdzhayev, I V; Liu, L; Travis, L D
This review paper outlines the rationale for long-term monitoring of the global distribution of natural and anthropogenic aerosols and clouds with specificity, accuracy, and coverage necessary for a reliable quantification of the direct and indirect aerosol effects on climate. We discuss the hierarchy of passive instruments suitable for aerosol remote sensing and give examples of aerosol retrievals obtained with instruments representing the low and the high end of this hierarchy
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.
Toellner, R.L.; Copland, G.V.
An automatic system for positioning a Ku band microwave antenna accurately to within approximately 0.1 degrees to point at a particular satellite located among others having as close as 2 degree angular spacing in geosynchronous earth orbit from a remote location for establishing a Ku band microwave communication link from the remote location via the satellite is described comprising: a Ku band microwave antenna having a gimbal mount adapted to move in at least azimuth and elevation; means for driving the gimbal mount in azimuth and means for driving the gimbal mount in elevation; means for sensing a satellite signal detected by the antenna and for producing an output signal representative of the strength of the satellite signal and a separate output signal indicative of a satellite code or signature; inclinometer means for measuring the actual elevation angle of the elevation gimbal with respect to vertical and for generating an output signal representative thereof; means for measuring the azimuth angle of the azimuth gimbal relative to a fixed reference and for generating an output signal representative thereof; computer means capable of receiving input data comprising the earth latitude and longitude of a remote location and a satellite position and capable of receiving as inputs the strength representative signal; means for pointing the elevation gimbal to a fixed direction and for scanning the azimuth gimbal to a computed direction based on the earth latitude and longitude and the satellite position signals; and wherein the computer means further includes means capable of receiving the input signal indicative of a satellite code or signature and means for comparing the code or signature input signal with a predetermined reference code or signature signal in the memory of the computer means
Sasaki, Takanori; Tanabu, Yoshimine; Fujita, Shigetaka; Zhao Wenhui
Interest in nuclear power generation is increasing by rising of power demand and environmental concern. It is important more and more to confirm and show the safety operation of nuclear plants, which is useful to remove anxiety of residents. Satellite remote sensing is one of the way of it. Large observation width and long and continuous observation period are advantage of satellite remote sensing. In addition, it is very important to be able to monitor without visitation on the site. We have continued local area environmental analysis using various satellites. MODIS on Terra and Aqua which are NASA satellites received by Hachinohe Institute of Technology is mainly used. According to these results, we have shown that combined analysis of various information parameters such as land surface temperature, geographical changes, vegetation, etc. is very effective to monitor environmental changes. In these analyses, error detection is very important. Therefore, enough storage data with continuously monitoring in usual state is necessary. Moreover, it is thought that the confirmation of stable operation of plants by means of continuous monitoring can contribute to reduce residents' anxiety of nuclear power plant. Additionally, in the case that the change of influence on surroundings is detected, it is possible to grasp the situation and take measure in early stage by error detection. In this paper, as an possible example of continuous monitoring using satellite remote sensing, we introduce the result of analysis and investigation of which changes of sea surface temperature and chlorophyll concentration on the sea around power plant. (author)
Hu, Taiyang; Lv, Rongchuan; Jin, Xu; Li, Hao; Chen, Wenxin
The nonlinear bias analysis and correction of receiving channels in Chinese FY-3C meteorological satellite Microwave Temperature Sounder (MWTS) is a key technology of data assimilation for satellite radiance data. The thermal-vacuum chamber calibration data acquired from the MWTS can be analyzed to evaluate the instrument performance, including radiometric temperature sensitivity, channel nonlinearity and calibration accuracy. Especially, the nonlinearity parameters due to imperfect square-law detectors will be calculated from calibration data and further used to correct the nonlinear bias contributions of microwave receiving channels. Based upon the operational principles and thermalvacuum chamber calibration procedures of MWTS, this paper mainly focuses on the nonlinear bias analysis and correction methods for improving the calibration accuracy of the important instrument onboard FY-3C meteorological satellite, from the perspective of theoretical and experimental studies. Furthermore, a series of original results are presented to demonstrate the feasibility and significance of the methods.
Brown, Molly E.; Essam, Timothy; Leonard, Kenneth
Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.
Stamnes, K. H.; Fan, Y.; Li, W.; Voss, K. J.; Gatebe, C. K.
Understanding bidirectional effects including sunglint is important for GEO-CAPE for several reasons: (i) correct interpretation of ocean color data; (ii) comparing consistency of spectral radiance data derived from space observations with a single instrument for a variety of illumination and viewing conditions; (iii) merging data collected by different instruments operating simultaneously. We present a new neural network (NN) method to correct bidirectional effects in water-leaving radiance for both Case 1 and Case 2 waters. We also discuss a new BRDF and 2D sun-glint model that was validated by comparing simulated surface reflectances with Cloud Absorption Radiometer (CAR) data. Finally, we present an extension of our marine bio-optical model to the UV range that accounts for the seasonal dependence of the inherent optical properties (IOPs).
Downs, S. W., Jr.
Some examples are presented of the use of remote sensing in cultivated crops, forestry, and range management. Areas of concern include: the determination of crop areas and types, prediction of yield, and detection of disease; the determination of forest areas and types, timber volume estimation, detection of insect and disease attack, and forest fires; and the determination of range conditions and inventory, and livestock inventory. Articles in the literature are summarized and specific examples of work being performed at the Marshall Space Flight Center are given. Primarily, aerial photographs and photo-like ERTS images are considered.
Clandillon, Stephen; Yésou, Hervé; Schneiderhan, Tobias; de Boissezon, Hélène; de Fraipont, Paul
During disasters rescue and relief organisations need quick access to reliable and accurate information to be better equipped to do their job. It is increasingly felt that satellites offer a unique near real time (NRT) tool to aid disaster management. A short introduction to the International Charter 'Space and Major Disasters', in operation since 2000 promoting worldwide cooperation among member space agencies, will be given as it is the foundation on which satellite-based, emergency response, damage assessment has been built. Other complementary mechanisms will also be discussed. The user access, triggering mechanism, an essential component for this user-driven service, will be highlighted with its 24/7 single access point. Then, a clear distinction will be made between data provision and geo-information delivery mechanisms to underline the user need for geo-information that is easily integrated into their working environments. Briefly, the path to assured emergency response product quality will be presented beginning with user requirements, expressed early-on, for emergency response value-adding services. Initiatives were then established, supported by national and European institutions, to develop the sector, with SERTIT and DLR being key players, providing support to decision makers in headquarters and relief teams in the field. To consistently meet the high quality levels demanded by users, rapid mapping has been transformed via workflow and quality control standardisation to improve both speed and quality. As such, SERTIT located in Alsace, France, and DLR/ZKI from Bavaria, Germany, join their knowledge in this presentation to report about recent standards as both have ISO certified their rapid mapping services based on experienced, well-trained, 24/7 on-call teams and established systems providing the first crisis analysis product in 6 hours after satellite data reception. The three main product types provided are then outlined: up-to-date pre
Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily
The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.
Hill, David P.
Dynamic stresses associated with crustal surface waves with 15–30 s periods and peak amplitudes Coulomb failure models based on a frictional strength threshold offer one explanation for instances of rapid‐onset triggered seismicity that develop during the surface‐wave peak dynamic stressing. Evaluation of the triggering potential of surface‐wave dynamic stresses acting on critically stressed faults using a Mohr’s circle representation together with the Coulomb failure criteria indicates that Love waves should have a higher triggering potential than Rayleigh waves for most fault orientations and wave incidence angles. That (1) the onset of triggered seismicity often appears to begin during the Rayleigh wave rather than the earlier arriving Love wave, and (2) Love‐wave amplitudes typically exceed those for Rayleigh waves suggests that the explanation for rapid‐onset dynamic triggering may not reside solely with a simple static‐threshold friction mode. The results also indicate that normal faults should be more susceptible to dynamic triggering by 20‐s Rayleigh‐wave stresses than thrust faults in the shallow seismogenic crust (<10 km) while the advantage tips in favor of reverse faults greater depths. This transition depth scales with wavelength and coincides roughly with the transition from retrograde‐to‐prograde particle motion. Locally elevated pore pressures may have a role in the observed prevalence of dynamic triggering in extensional regimes and geothermal/volcanic systems. The result is consistent with the apparent elevated susceptibility of extensional or transtensional tectonic regimes to remote triggering by Rayleigh‐wave dynamic stresses than compressional or transpressional regimes.
Umara Firman Rizidansyah
Full Text Available The purpose of this research is to examine suitability of three types of haze correction methods toward distinctness of surface objects in land cover. Considering the formation of haze therefore the main research are divided into both region namely rural assumed as vegetation and urban assumed as non vegetation area. Region of interest for rural selected Balaraja and urban selected Penjaringan. Haze imagery reduction utilized techniques such as Dark Object Substration, Virtual Cloud Point and Histogram Match. By applying an equation of Haze Optimized Transformation HOT = DNbluesin(∂-DNredcos(∂, the main result of this research includes: in the case of AVNIR-Rural, VCP has good results on Band 1 while the HM has good results on band 2, 3 and 4, therefore in the case of Avnir-Rural can be applied to HM. in the case of AVNIR-Urban, DOS has good result on band 1, 2 and 3 meanwhile HM has good results on band 4, therefore in the case of AVNIR-Urban can be applied to DOS. In the case of Landsat-Rural, DOS has good result on band 1, 2 and 6 meanwhile VCP has good results on band 4 and 5 and the smallest average value of HOT is 106.547 by VCP, therefore in the case of Lansat-Rural can be applied to DOS and VCP. In the case of Landsat-Urban, DOS has good result on band 1, 2 and 6 meanwhile VCP has good results on band 3, 4 and 5, therefore in the case of Landsat-Urban can be applied to VCP. Tujuan penelitian ini untuk menguji kesesuaian tiga jenis metode koreksi haze terhadap kejelasan obyek permukaan di wilayah tutupan vegetasi dan non vegetasi, berkenaan menghilangkan haze di wilayah citra satelit optis yang memiliki karakteristik tertentu dan diduga proses pembentukan partikel hazenya berbeda. Sehingga daerah penelitian dibagi menjadi wilayah rural yang diasumsikan sebagai daerah vegetasi dan urban sebagai non vegetasi. Pedesaan terpilih kecamatan Balaraja dan Perkotaan terpilih kecamatan Penjaringan. Tiap lokasi menggunakan Avnir-2 dan Landsat
Y. H. Ahn
in the context of operational mapping and monitoring of the springtime evolution of LSW plume in the ECS. The results were very encouraging and showed interesting features in surface CDOM and salinity fields in the vicinity of the Yangtze River estuary and its offshore domains, when a regional atmospheric correction (SSMM was employed instead of the standard (global SeaWiFS algorithm (SAC which revealed large errors around the edges of clouds/aerosols while masking out the nearshore areas. Nevertheless, there was good consistency between these two atmospheric correction algorithms over the relatively clear regions with a mean difference of 0.009 in aCDOM (400 (m−1 and 0.096 in salinity (psu. This study suggests the possible utilization of satellite remote sensing to assess CDOM and salinity and thus provides great potential in advancing our knowledge of the shelf-slope evolution and migration of the LSW plume properties in the ECS.
Xu, Lingzhe; Yang, Shihai
Astronomers are ever dreaming of sites with best seeing on the Earth surface for celestial observation, and the Antarctica is one of a few such sites only left owing to the global air pollution. However, Antarctica region is largely unaccessible for human being due to lacking of fundamental living conditions, travel facilities and effective ways of communication. Worst of all, the popular internet source as a general way of communication scarcely exists there. Facing such a dilemma and as a solution remote control and data transmission for telescopes through iridium satellite communication has been put forward for the Chinese network Antarctic Schmidt Telescopes 3 (AST3), which is currently under all round research and development. This paper presents iridium satellite-based remote control application adapted to telescope control. The pioneer work in China involves hardware and software configuration utilizing techniques for reliable and secure communication, which is outlined in the paper too.
Holzrichter, Nils; Szwillus, Wolfgang; Götze, Hans-Jürgen
Subsurface modelling with gravity data includes a reliable topographic mass correction. Since decades, this mandatory step is a standard procedure. However, originally methods were developed for local terrestrial surveys. Therefore, these methods often include defaults like a limited correction area of 167 km around an observation point, resampling topography depending on the distance to the station or disregard the curvature of the earth. New satellite gravity data (e.g. GOCE) can be used for large scale lithospheric modelling with gravity data. The investigation areas can include thousands of kilometres. In addition, measurements are located in the flight height of the satellite (e.g. ~250 km for GOCE). The standard definition of the correction area and the specific grid spacing around an observation point was not developed for stations located in these heights and areas of these dimensions. This asks for a revaluation of the defaults used for topographic correction. We developed an algorithm which resamples the topography based on an adaptive approach. Instead of resampling topography depending on the distance to the station, the grids will be resampled depending on its influence at the station. Therefore, the only value the user has to define is the desired accuracy of the topographic correction. It is not necessary to define the grid spacing and a limited correction area. Furthermore, the algorithm calculates the topographic mass response with a spherical shaped polyhedral body. We show examples for local and global gravity datasets and compare the results of the topographic mass correction to existing approaches. We provide suggestions how satellite gravity and gradient data should be corrected.
Lafitte, Marc; Robin, Jean‑Philippe
The mission of the European Union Satellite Centre (SatCen) is “to support the decision making and actions of the European Union in the field of the CFSP and in particular the CSDP, including European Union crisis management missions and operations, by providing, at the request of the Council or the European Union High Representative, products and services resulting from the exploitation of relevant space assets and collateral data, including satellite and aerial imagery, and related services”. The SatCen Non‑Proliferation Team, part of the SatCen Operations Division, is responsible for the analysis of installations that are involved, or could be involved, in the preparation or acquisition of capabilities intended to divert the production of nuclear material for military purposes and, in particular, regarding the spread of Weapons of Mass destruction and their means of delivery. For the last four decades, satellite imagery and associated remote sensing and geospatial techniques have increasingly expanded their capabilities. The unprecedented Very High Resolution (VHR) data currently available, the improved spectral capabilities, the increasing number of sensors and ever increasing computing capacity, has opened up a wide range of new perspectives for remote sensing applications. Concurrently, the availability of open source information (OSINF), has increased exponentially through the medium of the internet. This range of new capabilities for sensors and associated remote sensing techniques have strengthened the SatCen analysis capabilities for the monitoring of suspected proliferation installations for the detection of undeclared nuclear facilities, processes and activities. The combination of these remote sensing techniques, imagery analysis, open source investigation and their integration into Geographic Information Systems (GIS), undoubtedly improve the efficiency and comprehensive analysis capability provided by the SatCen to the EU stake‑holders. The
Hong, Yang; Adler, Robert F.; Huffman, George J.
Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1
Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...
Hashim, M; Pour, A B; Onn, C H
Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate
Sader, Steven A.; Jadkowski, Mark A.
A cooperative commercial development project designed to focus on cost-effective and practical applications of satellite remote sensing in forest management is discussed. The project, initiated in September, 1988 is being executed in three phases: (1) development of a forest resource inventory and geographic information system (GIS) updating systems; (2) testing and evaluation of remote-sensing products against forest industry specifications; and (3) integration of remote-sensing services and products in an operational setting. An advisory group represented by eleven major forest-product companies will provide direct involvement of the target market. The advisory group will focus on the following questions: Does the technology work for them? How can it be packaged to provide the needed forest-management information? Can the products and information be provided in a cost-effective manner?
Datla, Raju; Weinreb, Michael; Rice, Joseph; Johnson, B Carol; Shirley, Eric; Cao, Changyong
This paper traces the cooperative efforts of scientists at the National Oceanic and Atmospheric Administration (NOAA) and the National Institute of Standards and Technology (NIST) to improve the calibration of operational satellite sensors for remote sensing of the Earth's land, atmosphere and oceans. It gives a chronological perspective of the NOAA satellite program and the interactions between the two agencies' scientists to address pre-launch calibration and issues of sensor performance on orbit. The drive to improve accuracy of measurements has had a new impetus in recent years because of the need for improved weather prediction and climate monitoring. The highlights of this cooperation and strategies to achieve SI-traceability and improve accuracy for optical satellite sensor data are summarized.
Karakoylu, E.; Franz, B.
First attempt at quantifying uncertainties in ocean remote sensing reflectance satellite measurements. Based on 1000 iterations of Monte Carlo. Data source is a SeaWiFS 4-day composite, 2003. The uncertainty is for remote sensing reflectance (Rrs) at 443 nm.
An airborne surveillance program has been conducted over the Belgian part of the North Sea since 1991. The role of the program is to detect infringements on the Marpol Convention via remote sensing, and to take legal action against polluters through the use of recorded observations. Although Belgium has a restricted sea area of about 3,500 km with no fixed offshore oil installations, a pollution risk is constantly present due to 2 dense traffic separation schemes close to the shoreline. The Belgian marine areas and adjacent waters are regularly scanned with a Side Looking Airborne Radar (SLAR) on board a remote sensing aircraft. This paper describes an evaluation trial that the Belgian Management Unit of the North Sea Mathematical Models (MUMM) joined in 2004, together with various agencies from the United Kingdom, Germany and the Netherlands. The trial consists of a cost-sharing satellite service for oil detection with ENVISAT ASAR data. The trial was co-funded by the European Space Agency (ESA) and run by Kongsberg Satellite Services. MUMM's objective was to evaluate the effectiveness and operational character of satellite services for detecting oil spills at sea. The results of the 3 month trial have indicated that aerial remote sensing for the detection of illegal oil discharges at sea increases the chances of catching polluters more efficiently, with improved chances of evidence collecting. It was concluded that when various services are integrated and strict operational conditions are met, satellite services may prove to be valuable in restricted, very densely navigated national waters that are easily reached by airborne means. 12 refs., 8 tabs., 3 figs
Yassin Mounir Yassin
Full Text Available This approach is concerned with adapting the operations of attitude determination and control subsystem (ADCS of low earth orbit LEO satellites through analyzing the telemetry readings received by mission control center, and then responding to ADCS off-nominal situations. This can be achieved by sending corrective operational Tele-commands within real time. Our approach is related to the fuzzy membership of off-nominal telemetry readings of corrective actions through a set of fuzzy rules based on understanding the ADCS modes resulted from the satellite telemetry readings. Response in real time gives us a chance to avoid risky situations. The approach is tested on the EgyptSat-1 engineering model, which is our method to simulate the results.
Knowledge of the environment has grown to such an extent that information technology (IT) is essential to make sense of the available data. An example of this is remote sensing by satellite. In recent years this field has grown in importance and remote sensing is used for a range of uses including the automatic survey of wheat yields in North…
Viezzoli, Andrea; Edsen, Anders; Auken, Esben
, satellite remote sensing has been successfully used to identify numerous candidate sites that are most likely to host waste materials. This result was the basis for further monitoring activities based on the use of an helicopter transient electromagnetic (TEM) system, to be carried out at end of April 2009...... and remote sensing methods represents a useful instrument for environmental management....
Full Text Available The differential correction process determining osculating orbital elements as correct as possible at a given instant of time from tracking data of artificial satellite was accomplished. Preliminary orbital elements were used as an initial value of the differential correction procedure and iterated until the residual of real observation(O and computed observation(C was minimized. Tracking satellite was NOAA-9 or TIROS-N series. Two types of tracking data were prediction data precomputed from mean orbital elements of TBUS and real data obtained from tracking 1.707GHz HRPT signal of NOAA-9 using 5 meter auto-track antenna in Radio Research Laboratory. According to tracking data either Gauss method or Herrick-Gibbs method was applied to preliminary orbit determination. In the differential correction stage we used both of the Escobal(1975's analytical method and numerical ones are nearly consistent. And the differentially corrected orbit converged to the same value in spite of the differences between preliminary orbits of each time span.
Trusenkova, O.; Kachur, V.; Aleksanin, A. I.
It was carried out an error analysis of satellite reflectance coefficients (Rrs) of MODIS/AQUA colour data for two atmospheric correction algorithms (NIR, MUMM) in the Far-Eastern region. Some sets of unique data of in situ and satellite measurements have been analysed. A set has some measurements with ASD spectroradiometer for each satellite pass. The measurement allocations were selected so the Chlorophyll-a concentration has high variability. Analysis of arbitrary set demonstrated that the main error component is systematic error, and it has simple relations on Rrs values. The reasons of such error behavior are considered. The most probable explanation of the large errors of oceanic color parameters in the Far-Eastern region is the ability of high concentrations of continental aerosol. A comparison of satellite and in situ measurements at AERONET stations of USA and South Korea regions has been made. It was shown that for NIR-correction of the atmosphere influence the error values in these two regions have differences up to 10 times for almost the same water turbidity and relatively good accuracy of computation of aerosol optical thickness. The study was supported by grant Russian Scientific Foundation No. 14-50-00034, by grant of Russian Foundation of Basic Research No.15-35-21032-mol-a-ved, and by Program of Basic Research "Far East" of Far Eastern Branch of Russian Academy of Sciences.
Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming
Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.
We propose the general scheme of remote one-qubit information concentration. To achieve the task, the Bell-correlated mixed states are exploited. In addition, the nonremote one-qubit information concentration is equivalent to the decoding of the quantum error-correction code. Here we propose how to decode the stabilizer codes. In particular, the proposed scheme can be used for the operator quantum error-correction codes. The encoded state can be recreated on the errorless qubit, regardless how many bit-flip errors and phase-flip errors have occurred
Kolodner, Marc A.
The NOAA-15 Advanced Microwave Sounding Unit-B (AMSU-B) was designed in the same spirit as the Special Sensor Microwave Water Vapor Profiler (SSM/T-2) on board the DMSP F11-14 satellites, to perform remote sensing of spatial and temporal variations in mid and upper troposphere humidity. While the SSM/T-2 instruments have a 48 km spatial resolution at nadir and 28 beam positions per scan, AMSU-B provides an improvement with a 16 km spatial resolution at nadir and 90 beam positions per scan. The AMSU-B instrument, though, has been experiencing radio frequency interference (RFI) contamination from the NOAA-15 transmitters whose effect is dependent upon channel, geographic location, and current spacecraft antenna configuration. This has lead to large cross-track biases reaching as high as 100 Kelvin for channel 17 (150 GHz) and 50 Kelvin for channel 19 (183 +/-3 GHz). NOAA-NESDIS has recently provided a series of bias corrections for AMSU-B data starting from March, 1999. These corrections are available for each of the five channels, for every third field of view, and for three cycles within an eight second period. There is also a quality indicator in each data record to indicate whether or not the bias corrections should be applied. As a precursor to performing retrievals of mid and upper troposphere humidity, a validation study is performed by statistically analyzing the differences between the F14 SSM/T-2 and the bias corrected AMSU-B brightness temperatures for three months in the spring of 1999.
Full Text Available The increased availability of unmanned aerial vehicles (UAVs has resulted in their frequent adoption for a growing range of remote sensing tasks which include precision agriculture, vegetation surveying and fine-scale topographic mapping. The development and utilisation of UAV platforms requires broad technical skills covering the three major facets of remote sensing: data acquisition, data post-processing, and image analysis. In this study, UAV image data acquired by a miniature 6-band multispectral imaging sensor was corrected and calibrated using practical image-based data post-processing techniques. Data correction techniques included dark offset subtraction to reduce sensor noise, flat-field derived per-pixel look-up-tables to correct vignetting, and implementation of the Brown- Conrady model to correct lens distortion. Radiometric calibration was conducted with an image-based empirical line model using pseudo-invariant features (PIFs. Sensor corrections and radiometric calibration improve the quality of the data, aiding quantitative analysis and generating consistency with other calibrated datasets.
Stéphane Saux Picart
Full Text Available Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST derived from infrared remote sensing and ground “truth” from drifting buoy measurements. A large dataset of collocation between satellite SST and in situ SST is explored. Four regression models are used: Simple multi-linear regression, Least Square Shrinkage and Selection Operator (LASSO, Generalised Additive Model (GAM and random forest. In the case of geostationary satellites for which a large number of collocations is available, results show that the random forest model is the best model to predict the systematic errors and it is computationally fast, making it a good candidate for operational processing. It is able to explain nearly 31% of the total variance of the bias (in comparison to about 24% for the multi-linear regression model.
Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.
Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.
Giardino, Marco J.; Haley, Bryan S.
Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously
Trinh, R. C.; Holt, B.; Gierach, M.
Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also
Full Text Available The high resolution satellite with the longer focal length and the larger aperture has been widely used in georeferencing of the observed scene in recent years. The consistent end to end model of high resolution remote sensing satellite geometric chain is presented, which consists of the scene, the three line array camera, the platform including attitude and position information, the time system and the processing algorithm. The integrated design of the camera and the star tracker is considered and the simulation method of the geolocation accuracy is put forward by introduce the new index of the angle between the camera and the star tracker. The model is validated by the geolocation accuracy simulation according to the test method of the ZY-3 satellite imagery rigorously. The simulation results show that the geolocation accuracy is within 25m, which is highly consistent with the test results. The geolocation accuracy can be improved about 7 m by the integrated design. The model combined with the simulation method is applicable to the geolocation accuracy estimate before the satellite launching.
Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)
Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.
Boresjoe Bronge, Laine
Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given
Chen, Sheng-Bo; Wang, Jing-Ran; Guo, Peng-Ju; Wang, Ming-Chang
The Moon may be considered as the frontier base for the deep space exploration. The spectral analysis is one of the key techniques to determine the lunar surface rock and mineral compositions. But the lunar topographic relief is more remarkable than that of the Earth. It is necessary to conduct the topographic correction for lunar spectral data before they are used to retrieve the compositions. In the present paper, a lunar Sandmeier model was proposed by considering the radiance effect from the macro and ambient topographic relief. And the reflectance correction model was also reduced based on the Sandmeier model. The Spectral Profile (SP) data from KAGUYA satellite in the Sinus Iridum quadrangle was taken as an example. And the digital elevation data from Lunar Orbiter Laser Altimeter are used to calculate the slope, aspect, incidence and emergence angles, and terrain-viewing factor for the topographic correction Thus, the lunar surface reflectance from the SP data was corrected by the proposed model after the direct component of irradiance on a horizontal surface was derived. As a result, the high spectral reflectance facing the sun is decreased and low spectral reflectance back to the sun is compensated. The statistical histogram of reflectance-corrected pixel numbers presents Gaussian distribution Therefore, the model is robust to correct lunar topographic effect and estimate lunar surface reflectance.
Full Text Available Pointing accuracy is an important thing in satellite communication. Because the satellite’s distance to the surface of the earth's satellite is so huge, thus 1 degree of pointing error will make the antenna can not send data to satellites. To overcome this, the auto-tracking satellite controller is made. This system uses a microcontroller as the controller, with the GPS as the indicator location of the antenna, digital compass as the beginning of antenna pointing direction, rotary encoder as sensor azimuth and elevation, and modem to see Eb/No signal. The microcontroller use serial communication to read the input. Thus the programming should be focused on in the UART and serial communication software UART. This controller use 2 phase in the process of tracking satellites. Early stages is the method Elevation-Azimuth, where at this stage with input from GPS, Digital Compass, and the position of satellites (both coordinates, and height that are stored in microcontroller. Controller will calculate the elevation and azimuth angle, then move the antenna according to the antenna azimuth and elevation angle. Next stages is correction modem, where in this stage controller only use modem as the input, and antenna movement is set up to obtain the largest value of Eb/No signal. From the results of the controller operation, there is a change in the value of the original input level from -81.7 dB to -30.2 dB with end of Eb/No value, reaching 5.7 dB.
Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun
With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice.
Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun
With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice
Y. H. Ahn
.98 rather than a linear function of salinity measured in a variety of water types from this and other regions. Validation against a discrete in-situ data set showed that empirical algorithms derived from the above relationships could be successfully applied to satellite data over the range of water types for which they have been developed. Thus, we applied these algorithms to a series of SeaWiFS images for the derivation of CDOM and salinity in the context of operational mapping and monitoring of the springtime evolution of LSW plume in the ECS. The results were very encouraging and showed interesting features in surface CDOM and salinity fields in the vicinity of the Yangtze River estuary and its offshore domains, when a regional atmospheric correction (SSMM was employed instead of the standard (global SeaWiFS algorithm (SAC which revealed large errors around the edges of clouds/aerosols while masking out the nearshore areas. Nevertheless, there was good consistency between these two atmospheric correction algorithms over the relatively clear regions with a mean difference of 0.009 in aCDOM (400 (m−1 and 0.096 in salinity (psu. This study suggests the possible utilization of satellite remote sensing to assess CDOM and salinity and thus provides great potential in advancing our knowledge of the shelf-slope evolution and migration of the LSW plume properties in the ECS.
Kreuer, Dieter; Quernheim, Ulrich
Comite Consultatif International des Telegraphe et Telephone (CCITT) Signalling System No. 7 (SS7) provides a level 2 error correction protocol particularly suited for links with propagation delays higher than 15 ms. Not being originally designed for satellite links, however, the so called Preventive Cyclic Retransmission (PCR) Method only performs well on satellite channels when traffic is low. A modified level 2 error control protocol, termed Fix Delay Retransmission (FDR) method is suggested which performs better at high loads, thus providing a more efficient use of the limited carrier capacity. Both the PCR and the FDR methods are investigated by means of simulation and results concerning throughput, queueing delay, and system delay, respectively. The FDR method exhibits higher capacity and shorter delay than the PCR method.
Christopher, S. A.; Feng, N.; Guo, Y.; Hong, S.
Severe yellow haze hit a vast portion of Eastern China during the second week on June, 2012, as large area in Hubei, Henan, Hunan, Jiangsu, Anhui, Jiangxi, Shandong, Zhejiang provinces and Shanghai city were covered by lingering haze. This massive haze conditions caused considerable inconvenience to people's daily lives. Previous global air quality studies have also shown that Eastern China is one of regions with highest fine particulate matter (PM2.5) concentrations around the world. In this study, we estimate spatial and temporal variations of PM2.5 concentrations using satellite observations of this severe haze pollution on June, 2012. Satellite derived Aerosol Optical Thickness (AOT), sites measured hourly PM2.5 and meteorological fields from surface are statistically correlated based on a multiple regression model. We also explore the utility of higher spatial resolution aerosol retrieval from MODIS. Both satellite-derived and in-situ values have peak daily mean concentrations of approximately 400 μg m-3 on June 12th, 2012 in the City of Wuhan, which is nearly 10 times of the primary standard of PM2.5 concentration of China's "Ambient Air Quality Standards" (35 μg m-3). Cities in the Eastern China, e.g. Nanjing, Hangzhou and Nanchang, have also witnessed similar peak values, along with heavy smog during the same period. Satellite observations in this case study demonstrate that the transport of smoke plumes can be one of the main drivers of regional haze pollution over Eastern China. Comparing to the U.S., current limited ground-based stations is one of the biggest problem to develop the PM2.5 monitoring program over China. Our results may suggest the potential of combining satellite remote sensing with atmospheric model to map the PM2.5 spatial concentration over the nationwide level, which can further accelerate the construction of PM2.5 monitoring network over China.
Simonsen, Sebastian Bjerregaard; Barletta, Valentina Roberta; Forsberg, René
IS hamper in situ observations. Here, we evaluate available data from remote sensing and find a drainage basin in rapid change. An analysis of data from the Gravity Recovery and Climate Experiment (GRACE) satellites shows a mean seasonal freshwater flux into Godthåbsfjord of 18.2 ± 1.2 Gt, in addition......, from various remote-sensing data sets, estimate the freshwater flux from the GrIS into a specific fjord system, the Godthåbsfjord, in southwest Greenland. The area of the GrIS draining into Godthåbsfjord covers approximately 36,700 km2. The large areal extent and the multiple outlets from the Gr...... to an imbalance in the mass balance of the drainage basin from 2003 to 2013 of 14.4 ± 0.2 Gt year−1. Altimetry data from air and spaceborne missions also suggest rapid changes in the outlet glacier dynamics. We find that only applying data from the Ice, Cloud, and land Elevation Satellite (ICESat) mission...
Otto, C; Pipe, A
The purpose of this investigation was to demonstrate the potential of remote, mobile telemedicine during a four-week, high-altitude mountaineering expedition to Mount Logan, Canada's highest summit. Using a mobile satellite terminal and a laptop computer (both powered by a photovoltaic solar panel), ECG tracings and blood pressure measurements, in addition to colour images, short-segment video and audio clips were transmitted during the course of the ascent. The data were transmitted via a mobile communications satellite to a ground station in Ottawa, a distance of over 4000 km. The data were then transferred to the public switched data network and delivered to the University of Ottawa Heart Institute for analysis. Similarly, data were transmitted from the ground station to the expedition team on Mount Logan throughout the ascent. Using this technique, medical diagnosis and emergency care can be facilitated in extreme and isolated locations lacking a telecommunications infrastructure. Such technology has applications in developing countries, disaster response efforts, remote civilian and military operations, and in space operations.
Full Text Available The multi-channel measuring instruments with both the classical structure and the isolated one is identified their errors major factors basing on general it metrological properties analysis. Limiting possibilities of the remote automatic method for additive and multiplicative errors correction of measuring instruments with help of code-control measures are studied. For on-site calibration of multi- channel measuring instruments, the portable voltage calibrators structures are suggested and their metrological properties while automatic errors adjusting are analysed. It was experimentally envisaged that unadjusted error value does not exceed ± 1 mV that satisfies most industrial applications. This has confirmed the main approval concerning the possibilities of remote errors self-adjustment as well multi- channel measuring instruments as calibration tools for proper verification.
Wenhao, Zhang; Yingcheng, Li; Delong, Li; Changsheng, Teng; Jin, Liu
In China, natural disasters are characterized by wide distribution, severe destruction and high impact range, and they cause significant property damage and casualties every year. Following a disaster, timely and accurate acquisition of geospatial information can provide an important basis for disaster assessment, emergency relief, and reconstruction. In recent years, Unmanned Aerial Vehicle (UAV) remote sensing systems have played an important role in major natural disasters, with UAVs becoming an important technique of obtaining disaster information. UAV is equipped with a non-metric digital camera with lens distortion, resulting in larger geometric deformation for acquired images, and affecting the accuracy of subsequent processing. The slow speed of the traditional CPU-based distortion correction algorithm cannot meet the requirements of disaster emergencies. Therefore, we propose a Compute Unified Device Architecture (CUDA)-based image distortion correction algorithm for UAV remote sensing, which takes advantage of the powerful parallel processing capability of the GPU, greatly improving the efficiency of distortion correction. Our experiments show that, compared with traditional CPU algorithms and regardless of image loading and saving times, the maximum acceleration ratio using our proposed algorithm reaches 58 times that using the traditional algorithm. Thus, data processing time can be reduced by one to two hours, thereby considerably improving disaster emergency response capability
Aleksanin, A. I.; Kachur, V. A.
Calculation errors in ocean-brightness coefficients in the Far Eastern are analyzed for two atmospheric correction algorithms (NIR and MUMM). The daylight measurements in different water types show that the main error component is systematic and has a simple dependence on the magnitudes of the coefficients. The causes of the error behavior are considered. The most probable explanation for the large errors in ocean-color parameters in the Far East is a high concentration of continental aerosol absorbing light. A comparison between satellite and in situ measurements at AERONET stations in the United States and South Korea has been made. It is shown the errors in these two regions differ by up to 10 times upon close water turbidity and relatively high aerosol optical-depth computation precision in the case of using the NIR correction of the atmospheric effect.
Christopher, S. A.
Satellite Remote Sensing of Particulate Matter Air Quality: Progress, Potential and Pitfalls Abstract. Fine or respirable particles with particle aerodynamic diameters less than 2.5 µm (PM2.5) affect visibility, change cloud properties, reflect and absorb incoming solar radiation, affect human health and are ubiquitous in the atmosphere. These particles are injected into the atmosphere either as primary emissions or form into the atmosphere by gas to particle conversion. There are various sources of PM2.5 including emissions from automobiles, industrial exhaust, and agricultural fires. In 2006, the United States Environmental Protection Agency (EPA) made the standards stringent by changing the 24-hr averaged PM2.5 mass values from 65µgm-3 to 35µgm-3. This was primarily based on epidemiological studies that showed the long term health benefits of making the PM2.5 standards stringent. Typically PM2.5 mass concentration is measured from surface monitors and in the United States there are nearly 1000 such filter based daily and 600 contiguous stations managed by federal, state, local, and tribal agencies. Worldwide, there are few PM2.5 ground monitors since they are expensive to purchase, maintain and operate. Satellite remote sensing therefore provides a viable method for monitoring PM2.5 from space. Although, there are several hundred satellites currently in orbit and not all of them are suited for PM2.5 air quality assessments. Typically multi-spectral reflected solar radiation measurements from space-borne sensors are converted to aerosol optical depth (AOD) which is a measure of the column (surface to top of atmosphere) integrated extinction (absorption plus scattering). This column AOD (usually at 550 nm) is often converted to PM2.5 mass near the ground using various techniques. In this presentation we discuss the progress over the last decade on assessing PM2.5 from satellites; outline the potential and discuss the various pitfalls that one encounters. We
Lee, S.; Ryu, Y.; Jiang, C.
Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI
Wessels, R. L.; Griswold, J. P.
Satellite remote sensing provided timely observations of the volcanic unrest and several months-long eruption at Sinabung Volcano, Indonesia. Visible to thermal optical and synthetic aperture radar (SAR) systems provided frequent observations of Sinabung. High resolution image data with spatial resolutions from 0.5 to 1.5m offered detailed measurements of early summit deformation and subsequent lava dome and lava flow extrusion. The high resolution data were captured by commercial satellites such as WorldView-1 and -2 visible to near-infrared (VNIR) sensors and by CosmoSkyMed, Radarsat-2, and TerraSar-X SAR systems. Less frequent 90 to 100m spatial resolution night time thermal infrared (TIR) observations were provided by ASTER and Landsat-8. The combination of data from multiple sensors allowed us to construct a more complete timeline of volcanic activity than was available via only ground-based observations. This satellite observation timeline documents estimates of lava volume and effusion rates and major explosive and lava collapse events. Frequent, repeat volume estimates suggest at least three high effusion rate pulses of up to 20 m3/s occurred during the first three months of lava effusion with an average effusion rate of 6m3/s from January 2014 to August 2014. Many of these rates and events show some correlation to variations in the Real-time Seismic-Amplitude Measurement (RSAM) documented by the Indonesian Center for Volcanology and Geologic Hazard Mitigation (CVGHM).
Gao, H.; Zhang, S.; Zhao, G.; Li, Y.
With a total global capacity of more than 6000 km3, reservoirs play a key role in the hydrological cycle and in water resources management. However, essential reservoir data (e.g., elevation, storage, and evaporation loss) are usually not shared at a large scale. While satellite remote sensing offers a unique opportunity for monitoring large reservoirs from space, the commonly used radar altimeters can only detect storage variations of about 15% of global lakes at a repeat period of 10 days or longer. To advance the capabilities of reservoir sensing, we developed a series of algorithms geared towards generating long term reservoir records at improved spatial coverage, and at improved temporal resolution. To this goal, observations are leveraged from multiple satellite sensors, which include radar/laser altimeters, imagers, and passive microwave radiometers. In South Asia, we demonstrate that reservoir storage can be estimated under all-weather conditions at a 4 day time step, with the total capacity of monitored reservoirs increased to 45%. Within the Continuous United States, a first Landsat based evaporation loss dataset was developed (containing 204 reservoirs) from 1984 to 2011. The evaporation trends of these reservoirs are identified and the causes are analyzed. All of these algorithms and products were validated with gauge observations. Future satellite missions, which will make significant contributions to monitoring global reservoirs, are also discussed.
Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M
The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.
Siemann, Amanda Lynn
The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the
S. I. Khan
Full Text Available Study of hydro-climatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data over the last two decades combined with the recently available multiple-years satellite remote sensing data, we analyzed and simulated, with a distributed hydrologic model, the hydro-climatology in Nzoia, one of the major contributing sub-basins of Lake Victoria in the East African highlands. The basin, with a semi arid climate, has no sustained base flow contribution to Lake Victoria. The short spell of high discharge showed that rain is the prime cause of floods in the basin. There is only a marginal increase in annual mean discharge over the last 21 years. The 2-, 5- and 10- year peak discharges, for the entire study period showed that more years since the mid 1990's have had high peak discharges despite having relatively less annual rain. The study also presents the hydrologic model calibration and validation results over the Nzoia basin. The spatiotemporal variability of the water cycle components were quantified using a hydrologic model, with in-situ and multi-satellite remote sensing datasets. The model is calibrated using daily observed discharge data for the period between 1985 and 1999, for which model performance is estimated with a Nash Sutcliffe Efficiency (NSCE of 0.87 and 0.23% bias. The model validation showed an error metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic capability of satellite precipitation (TRMM-3B42 V6 is evaluated. In terms of reconstruction of the water cycle components the spatial distribution and time series of modeling results for precipitation and runoff showed considerable agreement with the monthly model runoff estimates and gauge observations. Runoff values responded to precipitation events that occurred across the catchment during the wet season from March to
Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu
Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection
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
The methods of measuring the existence of erosion and the effects of sand stabilization control systems are described. The mechanics of sand movement, the nature of sand erosion, and the use of satellite data to measure these factors and their surrogates are discussed using the locational and control aspects of aeolian and litoral erosion zones along the sand beach of the Mississippi coast. The aeolian erosion is highlighted due to the redeposition of the sand which causes high cleanup costs, property damage, and safety and health hazards. The areas of differential erosion and the patterns of beach sand movement are illustrated and the use of remote sensing methods to identify the areas of erosion are evaluated.
Labibian, Amir; Bahrami, Amir Hossein; Haghshenas, Javad
This paper presents a computationally efficient algorithm for attitude estimation of remote a sensing satellite. In this study, gyro, magnetometer, sun sensor and star tracker are used in Extended Kalman Filter (EKF) structure for the purpose of Attitude Determination (AD). However, utilizing all of the measurement data simultaneously in EKF structure increases computational burden. Specifically, assuming n observation vectors, an inverse of a 3n×3n matrix is required for gain calculation. In order to solve this problem, an efficient version of EKF, namely Murrell's version, is employed. This method utilizes measurements separately at each sampling time for gain computation. Therefore, an inverse of a 3n×3n matrix is replaced by an inverse of a 3×3 matrix for each measurement vector. Moreover, gyro drifts during the time can reduce the pointing accuracy. Therefore, a calibration algorithm is utilized for estimation of the main gyro parameters.
Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.
Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite
Burns, J.A.; Matthews, M.S.
The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system
Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.
In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.
Shen, Xiang; Liu, Bin; Li, Qing-Quan
The Rational Function Model (RFM) has proven to be a viable alternative to the rigorous sensor models used for geo-processing of high-resolution satellite imagery. Because of various errors in the satellite ephemeris and instrument calibration, the Rational Polynomial Coefficients (RPCs) supplied by image vendors are often not sufficiently accurate, and there is therefore a clear need to correct the systematic biases in order to meet the requirements of high-precision topographic mapping. In this paper, we propose a new RPC bias-correction method using the thin-plate spline modeling technique. Benefiting from its excellent performance and high flexibility in data fitting, the thin-plate spline model has the potential to remove complex distortions in vendor-provided RPCs, such as the errors caused by short-period orbital perturbations. The performance of the new method was evaluated by using Ziyuan-3 satellite images and was compared against the recently developed least-squares collocation approach, as well as the classical affine-transformation and quadratic-polynomial based methods. The results show that the accuracies of the thin-plate spline and the least-squares collocation approaches were better than the other two methods, which indicates that strong non-rigid deformations exist in the test data because they cannot be adequately modeled by simple polynomial-based methods. The performance of the thin-plate spline method was close to that of the least-squares collocation approach when only a few Ground Control Points (GCPs) were used, and it improved more rapidly with an increase in the number of redundant observations. In the test scenario using 21 GCPs (some of them located at the four corners of the scene), the correction residuals of the thin-plate spline method were about 36%, 37%, and 19% smaller than those of the affine transformation method, the quadratic polynomial method, and the least-squares collocation algorithm, respectively, which demonstrates
Kinoshita, Y.; Nimura, T.; Furuta, R.
The atmospheric delay effect is one of the limitations for the accurate surface displacement detection by Synthetic Aperture Radar Interferometry (InSAR). Many previous studies have attempted to mitigate the neutral atmospheric delay in InSAR (e.g. Jolivet et al. 2014; Foster et al. 2006; Kinoshita et al. 2013). Hanssen et al. (2001) investigated the relationship between the 27 hourly observations of GNSS precipitable water vapor (PWV) and the infrared brightness temperature derived from visible satellite imagery, and showed a good correlation. Here we showed a preliminary result of the newly developed method for the neutral atmospheric delay correction using the Himawari-8 Japanese geostationary meteorological satellite data. The Himawari-8 satellite is the Japanese state-of-the-art geostationary meteorological satellite that has 16 observation channels and has spatial resolutions of 0.5 km (visible) and 2.0 km (near-infrared and infrared) with an time interval of 2.5 minutes around Japan. To estimate the relationship between the satellite brightness temperature and the atmospheric delay amount. Since the InSAR atmospheric delay is principally the same as that in GNSS, we at first compared the Himawari-8 data with the GNSS zenith tropospheric delay data derived from the Japanese dense GNSS network. The comparison of them showed that the band with the wavelength of 6.9 μm had the highest correlation to the GNSS observation. Based on this result, we developed an InSAR atmospheric delay model that uses the Himawari-8 6.9 μm band data. For the model validation, we generated InSAR images from the ESA's C-band Sentinel-1 SLC data with the GAMMA SAR software. We selected two regions around Tokyo and Sapporo (both in Japan) as the test sites because of the less temporal decorrelation. The validation result showed that the delay model reasonably estimate large scale phase variation whose spatial scale was on the order of over 20 km. On the other hand, phase variations of
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
Loyola, D. G.
The satellite remote sensing retrievals are usually ill-posed inverse problems that are typically solved by finding a state vector that minimizes the residual between simulated data and real measurements. The classical inversion methods are very time-consuming as they require iterative calls to complex radiative-transfer forward models to simulate radiances and Jacobians, and subsequent inversion of relatively large matrices. In this work we present a novel and extremely fast algorithm for solving inverse problems called full-physics inverse learning machine (FP-ILM). The FP-ILM algorithm consists of a training phase in which machine learning techniques are used to derive an inversion operator based on synthetic data generated using a radiative transfer model (which expresses the "full-physics" component) and the smart sampling technique, and an operational phase in which the inversion operator is applied to real measurements. FP-ILM has been successfully applied to the retrieval of the SO2 plume height during volcanic eruptions and to the retrieval of ozone profile shapes from UV/VIS satellite sensors. Furthermore, FP-ILM will be used for the near-real-time processing of the upcoming generation of European Sentinel sensors with their unprecedented spectral and spatial resolution and associated large increases in the amount of data.
Full Text Available The successful launch of the first very high resolution (VHR satellites capable of capturing panchromatic imagery of the land surface with ground sample distance even lower than 1 m (e.g. IKONOS in 1999 or QuickBird in 2001 marked the beginning of a wholly new age in remote sensing. On January 4, 2010, images of WorldView-2 were placed on the market. Possibly it is the most sophisticated commercial VHR satellite currently orbiting the Earth and the exploitation of its data poses a challenge to researchers worldwide. Moreover, the practice of under plastic agriculture had a great development in the Mediterranean area during the past 60 years, especially in Almeria, acting as a key economic driver in the area. The goal of this work is the automatic greenhouse mapping by using Object Based Image Analysis (OBIA. The required input data will be a pan-sharpened orthoimage and a normalized digital surface model (nDSM for objects, both products generated from a WorldView-2 stereo pair. The attained results show that the very high resolution 8-band multispectral and the nDSM data improve the greenhouses automatic detection. In this way, overall accuracies higher than 90% can be achieved.
Xue, Xiaoiuan; Meng, Oingyan; Xie, Yong; Sun, Zhangli; Wang, Chang; Zhao, Hang
In this study, atmospheric radiative transfer model 6S was used to simulate the radioactive transfer process in the surface-atmosphere-sensor. An algorithm based on the look-up table (LUT) founded by 6S model was used to correct (HJ-1) CCD image pixel by pixel. Then, the effect of atmospheric correction on CCD data of HJ-1 satellite was analyzed in terms of the spectral curves and evaluated against the measured reflectance acquired during HJ-1B satellite overpass, finally, the normalized difference vegetation index (NDVI) before and after atmospheric correction were compared. The results showed: (1) Atmospheric correction on CCD data of HJ-1 satellite can reduce the ''increase'' effect of the atmosphere. (2) Apparent reflectance are higher than those of surface reflectance corrected by 6S model in band1∼band3, but they are lower in the near-infrared band; the surface reflectance values corrected agree with the measured reflectance values well. (3)The NDVI increases significantly after atmospheric correction, which indicates the atmospheric correction can highlight the vegetation information
Ramsey, M. S.
The ability to detect the onset of new activity at a remote volcano commonly relies on high temporal resolution thermal infrared (TIR) satellite-based observations. These observations from sensors such as AVHRR and MODIS are being used in innovative ways to produce trends of activity, which are critical for hazard response planning and scientific modeling. Such data are excellent for detection of new thermal features, volcanic plumes, and tracking changes over the hour time scale, for example. For some remote volcanoes, the lack of ground-based monitoring typically means that these sensors provide the first and only confirmation of renewed activity. However, what is lacking is the context of the higher spatial scale, which provides the volcanologist with meter-scale information on specific temperatures and changes in the composition and texture of the eruptive products. For the past eleven years, the joint US-Japanese ASTER instrument has been acquiring image-based data of volcanic eruptions around the world, including in the remote northern Pacific region. There have been more ASTER observations of Kamchatka volcanoes than any other location on the globe due mainly to an operational program put into place in 2004. Automated hot spot alarms from AVHRR data trigger ASTER acquisitions using the instrument's "rapid response" mode. Specifically for Kamchatka, this program has resulted in more than 700 additional ASTER images of the most thermally-active volcanoes (e.g., Shiveluch, Kliuchevskoi, Karymsky, Bezymianny). The scientific results from this program at these volcanoes will be highlighted. These results were strengthened by several field seasons used to map new products, collect samples for laboratory-based spectroscopy, and acquire TIR camera data. The fusion of ground, laboratory and space-based spectroscopy provided the most accurate interpretation of the eruptions and laid the ground work for future VSWIR/TIR sensors such as HyspIRI, which are a critically
Daniel, K. C.; Suresh, A.; Paredes Mesa, S.
Lakes are one of the few sources of freshwater used throughout the world but due to human activities, its quality and availability has been decreasing. The drying of lakes is a concerning issue in different communities around the world. This problem can affect jobs and the lives of individuals who use lakes as a source of income, consumption and recreation. Another dilemma that has occurred in lakes is eutrophication which is the buildup of excess nutrients in the lakes caused by runoff. This natural process can lead to anoxic conditions that may have a detrimental impact on surrounding ecosystems. Therefore, causing a devastating impact to economies and human livelihood worldwide. To monitor these issues, satellite data can be used to assess the water quality of different lakes throughout the world. Landsat satellite data from the past 10 years was used to conduct this research. By using the IOP (Inherent Optical Properties) of chlorophyll and suspended solids in the visible spectrum, the presence of algal blooms and sediments was determined. ARCGIS was used to outline the areas of the lakes and obtain reflectance values for quantity and quality assessment. Because there is always a certain amount of contamination in the lake, this research is used to evaluate the condition of the lakes throughout the years. Using the data that we have collected, we are able to understand how the issues addressed can harm civilians seasonally. Key Words: Lakes, Water Quality, Algal Blooms, Eutrophication, Remote Sensing, Satellite DataData Source: Landsat 4, Landsat 5, Landsat 7, Landsat 8
Sowden, M.; Mueller, U.; Blake, D.
The accurate measurements of natural and anthropogenic aerosol particulate matter (PM) is important in managing both environmental and health risks; however, limited monitoring in regional areas hinders accurate quantification. This article provides an overview of the ability of recently launched geostationary earth orbit (GEO) satellites, such as GOES-R (North America) and HIMAWARI (Asia and Oceania), to provide near real-time ground-level PM concentrations (GLCs). The review examines the literature relating to the spatial and temporal resolution required by air quality studies, the removal of cloud and surface effects, the aerosol inversion problem, and the computation of ground-level concentrations rather than columnar aerosol optical depth (AOD). Determining surface PM concentrations using remote sensing is complicated by differentiating intrinsic aerosol properties (size, shape, composition, and quantity) from extrinsic signal intensities, particularly as the number of unknown intrinsic parameters exceeds the number of known extrinsic measurements. The review confirms that development of GEO satellite products has led to improvements in the use of coupled products such as GEOS-CHEM, aerosol types have consolidated on model species rather than prior descriptive classifications, and forward radiative transfer models have led to a better understanding of predictive spectra interdependencies across different aerosol types, despite fewer wavelength bands. However, it is apparent that the aerosol inversion problem remains challenging because there are limited wavelength bands for characterising localised mineralogy. The review finds that the frequency of GEO satellite data exceeds the temporal resolution required for air quality studies, but the spatial resolution is too coarse for localised air quality studies. Continual monitoring necessitates using the less sensitive thermal infra-red bands, which also reduce surface absorption effects. However, given the
Schultz, L. A.; Molthan, A.; McGrath, K.; Bell, J. R.; Cole, T.; Burks, J.
In recent years, the NWS has developed a GIS-based application, called the Damage Assessment Toolkit (DAT), to conduct storm surveys after severe weather events. At present, the toolkit is primarily used for tornado damage surveys and facilitates the identification of damage indicators in accordance with the Enhanced Fujita (EF) intensity scale by allowing surveyors to compare time- and geo-tagged photos against the EF scale guidelines. Mobile and web-based applications provide easy access to the DAT for NWS personnel while performing their duties in the field or office. Multispectral satellite remote sensing imagery has demonstrated benefits for the detection and mapping of damage tracks caused by tornadoes, especially for long-track events and/or areas not easily accessed by NWS personnel. For example, imagery from MODIS, Landsat 7, Landsat 8, ASTER, Sentinel 2, and commercial satellites, collected and distributed in collaboration with the USGS Hazards Data Distribution System, have been useful for refining track location and extent through a "bird's eye" view of the damaged areas. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been working with the NWS and USGS to provide imagery and derived products from polar-orbiting satellite platforms to assist in the detection and refinement of tornado tracks as part of a NASA Applied Science: Disasters project. Working closely with select Weather Forecast Offices (WFOs) and Regional Operations Centers (ROCs) in both the NWS Central and Southern regions, high- and medium-resolution (0.5 - 30 m and 250 m - 1 km resolutions, respectively) imagery and derived products have been provided to the DAT interface for evaluation of operational utility by the NWS for their use in both the field and in the office during post event analysis. Highlighted in this presentation will be case studies where the remotely sensed imagery assisted in the adjustment of a tornado track. Examples will be shown highlighting
Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki
In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. PMID:26378532
Crawford, T. N.; Schaeffer, B. A.
Anthropogenic nutrient pollution is a major stressor of aquatic ecosystems around the world. In the United States, states and tribes can adopt numeric water quality values (i.e. criteria) into their water quality management standards to protect aquatic life from eutrophication impacts. However, budget and resource constraints have limited the ability of many states and tribes to collect the water quality monitoring data needed to derive numeric criteria. Over the last few decades, satellite technology has provided water quality measurements on a global scale over long time periods. Water quality managers are finding the data provided by satellite technology useful in managing eutrophication impacts in coastal waters, estuaries, lakes, and reservoirs. In recent years EPA has worked with states and tribes to derive remotely sensed numeric Chl-a criteria for coastal waters with limited field-based data. This approach is now being expanded and used to derive Chl-a criteria in freshwater systems across the United States. This presentation will cover EPA's approach to derive numeric Chl-a criteria using satellite remote sensing, recommendations to improve satellite sensors to expand applications, potential areas of interest, and the challenges of using remote sensing to establish water quality management goals, as well as provide a case in which this approach has been applied.
A. N. Grigoriev
Full Text Available The paper deals with technologies of ground secondary processing of heterogeneous multispectral data. The factors of heterogeneous data include uneven illumination of objects on the Earth surface caused by different properties of the relief. A procedure for the image restoration of spectral channels by means of terrain distortion compensation is developed. The object matter of this paper is to improve the quality of the results during image restoration of areas with large and medium landforms. Methods. Researches are based on the elements of the digital image processing theory, statistical processing of the observation results and the theory of multi-dimensional arrays. Main Results. The author has introduced operations on multidimensional arrays: concatenation and elementwise division. Extended model description for input data about the area is given. The model contains all necessary data for image restoration. Correction method for multispectral data radiometric distortions of the Earth remote sensing has been developed. The method consists of two phases: construction of empirical dependences for spectral reflectance on the relief properties and restoration of spectral images according to semiempirical data. Practical Relevance. Research novelty lies in developme nt of the application theory of multidimensional arrays with respect to the processing of multispectral data, together with data on the topography and terrain objects. The results are usable for development of radiometric data correction tools. Processing is performed on the basis of a digital terrain model without carrying out ground works connected with research of the objects reflective properties.
In national and international economics, geographic information plays a role which is generally acknowledged to be important but which is however, difficult to assess quantitatively, its applications being rather miscellaneous and indirect. Computer graphics and telecommunications increae that importance still more and justify many investments and research into new cartographic forms. As part of its responsibility for participating in the promotion of those developments, by taking into account needs expressed by public or private users, the National Council for Geographic Information (C.N.I.G.) has undertaken a general evaluation of the economic and social utility of geographic information in France. The study involves an estimation of the cost of production and research activities, which are probably about 0.1% of the Cross National Product—similar to many other countries. It also devised a method of estimating "cost/advantage" ratios applicable to these "intangible" benefits. Within that framework, remote sensing emphasizes particular aspects related both to the increase of economic performances in cartographic production and to the advent of new products and new ways of utilization. A review of some significant sectors shows effective earnings of about 10-20%, or even 50% or 100% of the costs, and these are doubtless much greater for the efficacy in the exploitation of products. Finally, many applications, entirely new result from extensions in various fields which would have been impossible without remote sensing: here the "cost advantage" ratio cannot even be compared with previous processes. Studies were undertaken in parallel for defining different types of products derived from satellite imagery, as well as those domains where development effort is required in order to make new advances.
Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.
Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.
Full Text Available In recent years, the area of plastic-mulched farmland (PMF has undergone rapid growth and raised remarkable environmental problems. Therefore, mapping the PMF plays a crucial role in agricultural production, environmental protection and resource management. However, appropriate data selection criteria are currently lacking. Thus, this study was carried out in two main plastic-mulching practice regions, Jizhou and Guyuan, to look for an appropriate spatial scale for mapping PMF with remote sensing. The average local variance (ALV function was used to obtain the appropriate spatial scale for mapping PMF based on the GaoFen-1 (GF-1 satellite imagery. Afterwards, in order to validate the effectiveness of the selected method and to interpret the relationship between the appropriate spatial scale derived from the ALV and the spatial scale with the highest classification accuracy, we classified the imagery with varying spatial resolution by the Support Vector Machine (SVM algorithm using the spectral features, textural features and the combined spectral and textural features respectively. The results indicated that the appropriate spatial scales from the ALV lie between 8 m and 20 m for mapping the PMF both in Jizhou and Guyuan. However, there is a proportional relation: the spatial scale with the highest classification accuracy is at the 1/2 location of the appropriate spatial scale generated from the ALV in Jizhou and at the 2/3 location of the appropriate spatial scale generated from the ALV in Guyuan. Therefore, the ALV method for quantitatively selecting the appropriate spatial scale for mapping PMF with remote sensing imagery has theoretical and practical significance.
Full Text Available Satellite remote sensing (RS is routinely used for the large-scale monitoring of microphytobenthos (MPB biomass in intertidal mudflats and has greatly improved our knowledge of MPB spatio-temporal variability and its potential drivers. Processes operating on smaller scales however, such as the impact of benthic macrofauna on MPB development, to date remain underinvestigated. In this study, we analysed the influence of wild Crassostrea gigas oyster reefs on MPB biofilm development using multispectral RS. A 30-year time series (1985–2015 combining high-resolution (30 m Landsat and SPOT data was built in order to explore the relationship between C. gigas reefs and MPB spatial distribution and seasonal dynamics, using the normalized difference vegetation index (NDVI. Emphasis was placed on the analysis of a before–after control-impact (BACI experiment designed to assess the effect of oyster killing on the surrounding MPB biofilms. Our RS data reveal that the presence of oyster reefs positively affects MPB biofilm development. Analysis of the historical time series first showed the presence of persistent, highly concentrated MPB patches around oyster reefs. This observation was supported by the BACI experiment which showed that killing the oysters (while leaving the physical reef structure, i.e. oyster shells, intact negatively affected both MPB biofilm biomass and spatial stability around the reef. As such, our results are consistent with the hypothesis of nutrient input as an explanation for the MPB growth-promoting effect of oysters, whereby organic and inorganic matter released through oyster excretion and biodeposition stimulates MPB biomass accumulation. MPB also showed marked seasonal variations in biomass and patch shape, size and degree of aggregation around the oyster reefs. Seasonal variations in biomass, with higher NDVI during spring and autumn, were consistent with those observed on broader scales in other European mudflats. Our
Echappé, Caroline; Gernez, Pierre; Méléder, Vona; Jesus, Bruno; Cognie, Bruno; Decottignies, Priscilla; Sabbe, Koen; Barillé, Laurent
Satellite remote sensing (RS) is routinely used for the large-scale monitoring of microphytobenthos (MPB) biomass in intertidal mudflats and has greatly improved our knowledge of MPB spatio-temporal variability and its potential drivers. Processes operating on smaller scales however, such as the impact of benthic macrofauna on MPB development, to date remain underinvestigated. In this study, we analysed the influence of wild Crassostrea gigas oyster reefs on MPB biofilm development using multispectral RS. A 30-year time series (1985-2015) combining high-resolution (30 m) Landsat and SPOT data was built in order to explore the relationship between C. gigas reefs and MPB spatial distribution and seasonal dynamics, using the normalized difference vegetation index (NDVI). Emphasis was placed on the analysis of a before-after control-impact (BACI) experiment designed to assess the effect of oyster killing on the surrounding MPB biofilms. Our RS data reveal that the presence of oyster reefs positively affects MPB biofilm development. Analysis of the historical time series first showed the presence of persistent, highly concentrated MPB patches around oyster reefs. This observation was supported by the BACI experiment which showed that killing the oysters (while leaving the physical reef structure, i.e. oyster shells, intact) negatively affected both MPB biofilm biomass and spatial stability around the reef. As such, our results are consistent with the hypothesis of nutrient input as an explanation for the MPB growth-promoting effect of oysters, whereby organic and inorganic matter released through oyster excretion and biodeposition stimulates MPB biomass accumulation. MPB also showed marked seasonal variations in biomass and patch shape, size and degree of aggregation around the oyster reefs. Seasonal variations in biomass, with higher NDVI during spring and autumn, were consistent with those observed on broader scales in other European mudflats. Our study provides the
Canuet, Lucien; Védrenne, Nicolas; Conan, Jean-Marc; Petit, Cyril; Artaud, Geraldine; Rissons, Angelique; Lacan, Jerome
In the framework of satellite-to-ground laser downlinks, an analytical model describing the variations of the instantaneous coupled flux into a single-mode fiber after correction of the incoming wavefront by partial adaptive optics (AO) is presented. Expressions for the probability density function and the cumulative distribution function as well as for the average fading duration and fading duration distribution of the corrected coupled flux are given. These results are of prime interest for the computation of metrics related to coded transmissions over correlated channels, and they are confronted by end-to-end wave-optics simulations in the case of a geosynchronous satellite (GEO)-to-ground and a low earth orbit satellite (LEO)-to-ground scenario. Eventually, the impact of different AO performances on the aforementioned fading duration distribution is analytically investigated for both scenarios.
Skoglund, S. K.; Weathers, K. C.; Norouzi, H.; Prakash, S.; Ewing, H. A.
Many northern temperate freshwater lakes are freezing over later and thawing earlier. This shift in timing, and the resulting shorter duration of seasonal ice cover, is expected to impact ecological processes, negatively affecting aquatic species and the quality of water we drink. Long-term, direct observations have been used to analyze changes in ice phenology, but those data are sparse relative to the number of lakes affected. Here we develop a model to utilize remote sensing data in approximating the dates of ice-on and ice-off for many years over a variety of lakes. Day and night surface temperatures from MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra (MYD11A1 and MOD11A1 data products) for 2002-2017 were utilized in combination with observed ice-on and ice-off dates of Lake Auburn, Maine, to determine the ability of MODIS data to match ground-based observations. A moving average served to interpolate MODIS temperature data to fill data gaps from cloudy days. The nighttime data were used for ice-off, and the daytime measurements were used for ice-on predictions to avoid fluctuations between day and night ice/water status. The 0˚C intercepts of those data were used to mark approximate days of ice-on or ice-off. This revealed that approximations for ice-off dates were satisfactory (average ±8.2 days) for Lake Auburn as well as for Lake Sunapee, New Hampshire (average ±8.1 days), while approximations for Lake Auburn ice-on were less accurate and showed consistently earlier-than-observed ice-on dates (average -33.8 days). The comparison of observed and remotely sensed Lake Auburn ice cover duration showed relative agreement with a correlation coefficient of 0.46. Other remote sensing observations, such as the new GOES-R satellite, and further exploration of the ice formation process can improve ice-on approximation methods. The model shows promise for estimating ice-on, ice-off, and ice cover duration for northern temperate lakes.
di, L.; Yang, W.; Bai, Y.
Remote sensing is one of the major methods for collecting geospatial data. Hugh amount of remote sensing data has been collected by space agencies and private companies around the world. For example, NASA's Earth Observing System (EOS) is generating more than 3 Tb of remote sensing data per day. The data collected by EOS are processed, distributed, archived, and managed by the EOS Data and Information System (EOSDIS). Currently, EOSDIS is managing several petabytes of data. All of those data are not only valuable for global change research, but also useful for local and regional application and decision makings. How to make the data easily accessible to and usable by the user community is one of key issues for realizing the full potential of these valuable datasets. In the past several years, the Open Geospatial Consortium (OGC) has developed several interoperability protocols aiming at making geospatial data easily accessible to and usable by the user community through Internet. The protocols particularly relevant to the discovery, access, and integration of multi-source satellite remote sensing data are the Catalog Service for Web (CS/W) and Web Coverage Services (WCS) Specifications. The OGC CS/W specifies the interfaces, HTTP protocol bindings, and a framework for defining application profiles required to publish and access digital catalogues of metadata for geographic data, services, and related resource information. The OGC WCS specification defines the interfaces between web-based clients and servers for accessing on-line multi-dimensional, multi-temporal geospatial coverage in an interoperable way. Based on definitions by OGC and ISO 19123, coverage data include all remote sensing images as well as gridded model outputs. The Laboratory for Advanced Information Technology and Standards (LAITS), George Mason University, has been working on developing and implementing OGC specifications for better serving NASA Earth science data to the user community for many
Fishman, Jack; Al-Saadi, Jassim A.; Neil, Doreen O.; Creilson, John K.; Severance, Kurt; Thomason, Larry W.; Edwards, David R.
When the first observations of a tropospheric trace gas were obtained in the 1980s, carbon monoxide enhancements from tropical biomass burning dominated the observed features. In 2005, an active remote-sensing system to provide detailed information on the vertical distribution of aerosols and clouds was launched, and again, one of the most imposing features observed was the presence of emissions from tropical biomass burning. This paper presents a brief overview of space-borne observations of the distribution of trace gases and aerosols and how tropical biomass burning, primarily in the Southern Hemisphere, has provided an initially surprising picture of the distribution of these species and how they have evolved from prevailing transport patterns in that hemisphere. We also show how interpretation of these observations has improved significantly as a result of the improved capability of trajectory modeling in recent years and how information from this capability has provided additional insight into previous measurements form satellites. Key words: pollution; biomass burning; aerosols; tropical trace gas emissions; Southern Hemisphere; carbon monoxide.
Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.
In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.
Suhartono Nurdin; Muzzneena Ahmad Mustapha; Tukimat Lihan; Mazlan Abdul Ghaffar; Muzzneena Ahmad Mustapha; Nurdin, S.
Analysis of relationship between sea surface temperature (SST) and Chlorophyll-a (chl-a) improves our understanding on the variability and productivity of the marine environment, which is important for exploring fishery resources. Monthly level 3 and daily level 1 images of Moderate Resolution Imaging Spectroradiometer Satellite (MODIS) derived SST and chl-a from July 2002 to June 2011 around the archipelagic waters of Spermonde Indonesia were used to investigate the relationship between SST and chl-a and to forecast the potential fishing ground of Rastrelliger kanagurta. The results indicated that there was positive correlation between SST and chl-a (R=0.3, p<0.05). Positive correlation was also found between SST and chl-a with the catch of R. kanagurta (R=0.7, p<0.05). The potential fishing grounds of R. kanagurta were found located along the coast (at accuracy of 76.9 %). This study indicated that, with the integration of remote sensing technology, statistical modeling and geographic information systems (GIS) technique were able to determine the relationship between SST and chl-a and also able to forecast aggregation of R. kanagurta. This may contribute in decision making and reducing search hunting time and cost in fishing activities. (author)
the application of satellite Earth Observation (EO) methods to the analysis of transportation networks. Other geospatial technologies, including geographic information systems (GIS) and the Global Positioning System (GPS), sharply enhance the utility of EO data in identifying potential road hazards and providing an objective basis for allocating resources to reduce their risks. In combination, these powerful information technologies provide substantial public benefits and increased business opportunities to remote sensing value-added firms. departments in rural jurisdictions improve the trafficability of the roads under their management during severe weather. We are developing and testing these methods in the U.S. Southwest, where thousands of kilometers of unimproved and graded dirt roads cross Native American reservations. This generally arid region is nevertheless subject to periodic summer rainstorms and winter snow and ice, creating hazardous conditions for the region's transportation lifelines. Arizona and Southeast Utah, as well as digital terrain models from the U.S. Geological Survey. We have analyzed several risk factors, such as slope, road curvature, and intersections, by means of multi-criteria evaluation (MCE) on both unimproved and improved roads. In partnership with the Hopi Indian Nation in Arizona, we have acquired and analyzed GPS road centerline data and accident data that validate our methodology. hazards along paved and unpaved roads of the American Southwest. They are also transferable to the international settings, particularly in similarly arid climates.
Full Text Available Critical land classification can be analyzed using combination between Top Soil Thickness - Land erosion method, and BRLT methods. Both methods are needed soil erosion data as one of input data. The soil erosion data can be analyzed using USLE and MUSLE methods. The combination of two critical land analyses methods with input soil erosion data from two analyses methods will be produced four combinations of critical land classification. In this research, four of the critical land classification and two soil erosion classification will be analyzed using GIS. The best method to classify critical land will be investigated in this research. The best classified critical land is the classified critical land data is nearest with the field condition. Percentage of vegetation cover (PVC is one of the most important input data in the critical land classification analysis using BRLKT method. This data have 50% weight. PVC condition is classified into five categories i.e. very good, good, fair, poor, and very poor. Each category have score 5, 4, 3, 2, 1 respectively. To analyze this PVC classification, NDVI generated from satellite remote sensing data is used in this research. From the four methods of land critical classification analyses used in this research, critical land classified using BRLKT method with input soil erosion analyzed using method is produced the critical land classification nearest with the critical land condition in the field.
Blake, R.; Liou-Mark, J.
The U.S. remains in grave danger of losing its global competitive edge in STEM. To find solutions to this problem, the Obama Administration proposed two new national initiatives: the Educate to Innovate Initiative and the $100 million government/private industry initiative to train 100,000 STEM teachers and graduate 1 million additional STEM students over the next decade. To assist in ameliorating the national STEM plight, the New York City College of Technology has designed its NSF Research Experience for Undergraduate (REU) program in satellite and ground-based remote sensing to target underrepresented minority students. Since the inception of the program in 2008, a total of 45 undergraduate students of which 38 (84%) are considered underrepresented minorities in STEM have finished or are continuing with their research or are pursuing their STEM endeavors. The program is comprised of the three primary components. The first component, Structured Learning Environments: Preparation and Mentorship, provides the REU Scholars with the skill sets necessary for proficiency in satellite and ground-based remote sensing research. The students are offered mini-courses in Geographic Information Systems, MATLAB, and Remote Sensing. They also participate in workshops on the Ethics of Research. Each REU student is a member of a team that consists of faculty mentors, post doctorate/graduate students, and high school students. The second component, Student Support and Safety Nets, provides undergraduates a learning environment that supports them in becoming successful researchers. Special networking and Brown Bag sessions, and an annual picnic with research scientists are organized so that REU Scholars are provided with opportunities to expand their professional community. Graduate school support is provided by offering free Graduate Record Examination preparation courses and workshops on the graduate school application process. Additionally, students are supported by college
Grimes, D Jay; Ford, Tim E; Colwell, Rita R; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G
Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions.
Kai Xu; Guo Zhang; Qingjun Zhang; Deren Li
In studies involving the extraction of surface physical parameters using optical remote sensing satellite imagery, sun-sensor geometry must be known, especially for sensor viewing angles. However, while pixel-by-pixel acquisitions of sensor viewing angles are of critical importance to many studies, currently available algorithms for calculating sensor-viewing angles focus only on the center-point pixel or are complicated and are not well known. Thus, this study aims to provide a simple and ge...
Pinkevych, Mykola; Cromer, Deborah; Tolstrup, Martin
[This corrects the article DOI: 10.1371/journal.ppat.1005000.][This corrects the article DOI: 10.1371/journal.ppat.1005740.][This corrects the article DOI: 10.1371/journal.ppat.1005679.].......[This corrects the article DOI: 10.1371/journal.ppat.1005000.][This corrects the article DOI: 10.1371/journal.ppat.1005740.][This corrects the article DOI: 10.1371/journal.ppat.1005679.]....
Johnson, D. M.; Dorn, M. F.; Crawford, C.
Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a
Carvalho, Gustavo A.; Minnett, Peter J.; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner
In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs. PMID:21037979
Ermida, S. L.; Trigo, I. F.; DaCamara, C.; Ghent, D.
Land surface temperature (LST) values retrieved from satellite measurements in the thermal infrared (TIR) may be strongly affected by spatial anisotropy. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a parametric model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. Two models are consistently analyzed to evaluate their performance of and to assess their respective potential to correct directional effects on LST for a wide range of surface conditions, in terms of tree coverage, vegetation density, surface emissivity. We also propose an optimization of the correction of directional effects through a synergistic use of both models. The models are calibrated using LST data as provided by two sensors: MODIS on-board NASA's TERRA and AQUA; and SEVIRI on-board EUMETSAT's MSG. As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is stratified by means of a cluster analysis using information on land cover type, fraction of vegetation cover and topography. The models are then adjusted to LST data corresponding to each cluster. It is shown that the quality of the cluster based models is very close to the pixel based ones. Furthermore, the reduced number of parameters allows improving the model trough the incorporation of a
Beria, H.; Nanda, T., Sr.; Chatterjee, C.
High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.
The application of satellite images in an oil spill response operation, was discussed. The oil movement and satellite imagery of the Sea Empress spill was described in detail. There were large discrepancies in the predictions by Radarsat satellite imagery and the actual oil movement, and in this instance, the satellite imagery proved to be more of a distraction than a useful tool. It was suggested that the greatest potential for satellite imagery is in detecting smaller releases of oil, such as from illegal tank washings, ballast waters from ships, or operational malfunctions at oil rigs. 4 refs., 10 figs
Hernandes, Gilberto Luis Sanches [TBG Transportadora Brasileira Gasoduto Bolivia-Brasil, Rio de Janeiro, RJ (Brazil)
This paper presents the results of CBERS-2B' Brazilian Remote Sensing Satellite to help to monitor the Bolivia-Brazil Gas Pipeline. The CBERS-2B is the third satellite launched in 2007 by the CBERS Program (China-Brazil Earth Resources Satellite) and the innovation was the HRC camera that produces high resolution images. It will be possible to obtain one complete coverage of the country every 130 days. In this study, 2 images from different parts of the Bolivia- Brazil Gas Pipeline were selected. Image processing involved the geometric registration of CBERS-2B satellite images with airborne images, contrast stretch transform and pseudo color. The analysis of satellite and airborne images in a GIS software to detect third party encroachment was effective to detect native vegetation removal, street construction, growth of urban areas, farming and residential/industrial land development. Very young, the CBERS-2B is a good promise to help to inspect the areas along the pipelines. (author)
Lamsal, L. N.; Martin, R. V.; Krotkov, N. A.; Bucsela, E. J.; Celarier, E. A.; vanDonkelaar, A.; Parrish, D.
Nitrogen oxides (NO(x)) are key actors in air quality and climate change. Satellite remote sensing of tropospheric NO2 has developed rapidly with enhanced spatial and temporal resolution since initial observations in 1995. We have developed an improved algorithm and retrieved tropospheric NO2 columns from Ozone Monitoring Instrument. Column observations of tropospheric NO2 from the nadir-viewing satellite sensors contain large contributions from the boundary layer due to strong enhancement of NO2 in the boundary layer. We infer ground-level NO2 concentrations from the OMI satellite instrument which demonstrate significant agreement with in-situ surface measurements. We examine how NO2 columns measured by satellite, ground-level NO2 derived from satellite, and NO(x) emissions obtained from bottom-up inventories relate to world's urban population. We perform inverse modeling analysis of NO2 measurements from OMI to estimate "top-down" surface NO(x) emissions, which are used to evaluate and improve "bottom-up" emission inventories. We use NO2 column observations from OMI and the relationship between NO2 columns and NO(x) emissions from a GEOS-Chem model simulation to estimate the annual change in bottom-up NO(x) emissions. The emission updates offer an improved estimate of NO(x) that are critical to our understanding of air quality, acid deposition, and climate change.
Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei
Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.
Leifer, Ira [University of California (United States); Clark, Roger; Swayze, Gregg [US Geology Survey (United States); Jones, Cathleen [California Institute of Technology (United States); Svejkovsky, Jan [Ocean Imaging Corporation (United States)
This study stresses the value of using satellite technology in quantifying oil seepage impact, and how it can be applied to the case of Horizon oil spill. The purpose of the study is to clarify the remote sensing process as it applies to oil spills, and how testing resources should be properly allocated so as to come up with the optimal response strategy. Many parameters were involved in this research, of which the most important were the environmental factors, the active and passive remote sensing measures, satellite imagery and imaging spectroscopy, and oil thickness measurements using thermal infrared and laser-induced fluorescence. These parameters were later used to quantify the spills in the impacted regions. Results showed that remote sensing would always be accompanied by certain errors, however, in the case of the Horizon spill, the infrared approach proved to be a convenient and a reliable approach for impact analysis process. The study also put emphasis on the importance of oil spatial patterns in validating the reliability of a test procedure.
Leifer, Ira; Clark, Roger; Swayze, Gregg; Jones, Cathleen; Svejkovsky, Jan
This study stresses the value of using satellite technology in quantifying oil seepage impact, and how it can be applied to the case of Horizon oil spill. The purpose of the study is to clarify the remote sensing process as it applies to oil spills, and how testing resources should be properly allocated so as to come up with the optimal response strategy. Many parameters were involved in this research, of which the most important were the environmental factors, the active and passive remote sensing measures, satellite imagery and imaging spectroscopy, and oil thickness measurements using thermal infrared and laser-induced fluorescence. These parameters were later used to quantify the spills in the impacted regions. Results showed that remote sensing would always be accompanied by certain errors, however, in the case of the Horizon spill, the infrared approach proved to be a convenient and a reliable approach for impact analysis process. The study also put emphasis on the importance of oil spatial patterns in validating the reliability of a test procedure.
Full Text Available This paper will assess the most recently available open access high-resolution optical satellite data (0.3 m–0.6 m and its detection of buried ancient features versus ground based remote sensing tools. It also discusses the importance of CORONA satellite data to evaluate landscape changes over the past 50 years surrounding sites. The study concentrates on Egypt’s Nile Delta, which is threatened by rising sea and water tables and urbanization. Many ancient coastal sites will be lost in the next few decades, thus this paper emphasizes the need to map them before they disappear. It shows that high resolution satellites can sometimes provide the same general picture on ancient sites in the Egyptian Nile Delta as ground based remote sensing, with relatively sandier sedimentary and degrading tell environments, during periods of rainfall, and higher groundwater conditions. Research results also suggest potential solutions for rapid mapping of threatened Delta sites, and urge a collaborative global effort to maps them before they disappear.
Polishchuk, G. M; Kozlov, V. I; Urlichich, Y. M; Dvorkin, V. V; Gvozdev, V. V
... for the Russian Federation and a system of global navigation satellite system monitoring. These projects are some of the basic ones in the Federal program "Global Navigation System," aimed at maintenance and development of the GLONASS system...
Herron-Thorpe, F. L.; Mount, G. H.; Emmons, L. K.; Lamb, B. K.; Jaffe, D. A.; Wigder, N. L.; Chung, S. H.; Zhang, R.; Woelfle, M.; Vaughan, J. K.; Leung, F. T.
The WSU AIRPACT air quality modeling system for the Pacific Northwest forecasts hourly levels of aerosols and atmospheric trace gases for use in determining potential health and ecosystem impacts by air quality managers. AIRPACT uses the WRF/SMOKE/CMAQ modeling framework, derives dynamic boundary conditions from MOZART-4 forecast simulations with assimilated MOPITT CO, and uses the BlueSky framework to derive fire emissions. A suite of surface measurements and satellite-based remote sensing data products across the AIRPACT domain are used to evaluate and improve model performance. Specific investigations include anthropogenic emissions, wildfire simulations, and the effects of long-range transport on surface ozone. In this work we synthesize results for multiple comparisons of AIRPACT with satellite products such as IASI ammonia, AIRS carbon monoxide, MODIS AOD, OMI tropospheric ozone and nitrogen dioxide, and MISR plume height. Features and benefits of the newest version of AIRPACT's web-interface are also presented.
Wang, N.; Yang, R.
Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.
Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong
The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.
Lu, Y C; Tian, Q J; Lyu, C G; Fu, W X; Han, W C
An optical remote sensing model has been established based on two-beam interference theory to estimate marine oil slick thickness. Extinction coefficient and normalized reflectance of oil are two important parts in this model. Extinction coefficient is an important inherent optical property and will not vary with the background reflectance changed. Normalized reflectance can be used to eliminate the background differences between in situ measured spectra and remotely sensing image. Therefore, marine oil slick thickness and area can be estimated and mapped based on optical remotely sensing image and extinction coefficient
Full Text Available Results of numerous evaluation studies indicated that satellite-rainfall products are contaminated with significant systematic and random errors. Therefore, such products may require refinement and correction before being used for hydrologic applications. In the present study, we explore a rainfall-runoff modeling application using the Climate Prediction Center-MORPHing (CMORPH satellite rainfall product. The study area is the Gilgel Abbay catchment situated at the source basin of the Upper Blue Nile basin in Ethiopia, Eastern Africa. Rain gauge networks in such area are typically sparse. We examine different bias correction schemes applied locally to the CMORPH product. These schemes vary in the degree to which spatial and temporal variability in the CMORPH bias fields are accounted for. Three schemes are tested: space and time-invariant, time-variant and spatially invariant, and space and time variant. Bias-corrected CMORPH products were used to calibrate and drive the Hydrologiska Byråns Vattenbalansavdelning (HBV rainfall-runoff model. Applying the space and time-fixed bias correction scheme resulted in slight improvement of the CMORPH-driven runoff simulations, but in some instances caused deterioration. Accounting for temporal variation in the bias reduced the rainfall bias by up to 50%. Additional improvements were observed when both the spatial and temporal variability in the bias was accounted for. The rainfall bias was found to have a pronounced effect on model calibration. The calibrated model parameters changed significantly when using rainfall input from gauges alone, uncorrected, and bias-corrected CMORPH estimates. Changes of up to 81% were obtained for model parameters controlling the stream flow volume.
Full Text Available In this study we present calibration/validation activities associated with satellite MERIS image processing and aimed at estimatingchl a and CDOM in the Curonian Lagoon. Field data were used to validate the performances of two atmospheric correction algorithms,to build a band-ratio algorithm for chl a and to validate MERIS-derived maps. The neural network-based Case 2 Regional processor wasfound suitable for mapping CDOM; for chl a the band-ratio algorithm applied to image data corrected with the 6S code was found moreappropriate. Maps were in agreement with in situ measurements.This study confirmed the importance of atmospheric correction to estimate water quality and demonstrated the usefulness ofMERIS in investigating eutrophic aquatic ecosystems.
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.
Morel, Yann G; Favoretto, Fabio
All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions; (ii) in order to specify and operate the simplified radiative transfer equation (RTE); (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need for (i) formal atmospheric correction; (ii) conversion of relative radiance into calibrated reflectance; or (iii) existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a "near-nadir" view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.
Kottek, M.; Rubel, F. [Univ. of Veterinary Medicine, Vienna (Austria). Biometeorology Group
Global daily precipitation analyses are mainly based on satellite estimates, often calibrated with monthly ground analyses or merged with model predictions. We argue here that an essential improvement of their accuracy is only possible by incorporation of daily ground measurements. In this work we apply geostatistical methods to compile a global precipitation product based on daily rain gauge measurements. The raw ground measurements, disseminated via Global Telecommunication System (GTS), are corrected for their systematic measurement errors and interpolated onto a global 1 degree grid. For interpolation ordinary block kriging is applied, with precalculated spatial auto-correlation functions (ACFs). This technique allows to incorporate additional climate information. First, monthly ACFs are calculated from the daily data; second, they are regionalised according to the five main climatic zones of the Koeppen-Geiger climate classification. The interpolation error, a by-product of kriging, is used to flag grid points as missing if the error is above a predefined threshold. But for many applications missing values constitute a problem. Due to a combination of the ground analyses with the daily multi-satellite product of the Global Precipitation Climatology Project (GPCP-1DD) not only these missing values are replaced but also the spatial structure of the satellite estimates is considered. As merging method bivariate ordinary co-kriging is applied. The ACFs necessary for the gauge and the satellite fields as well as the corresponding spatial cross-correlation functions (CCFs) are again precalculated for each of the five main climatic zones and for each individual month. As a result two new global daily data sets for the period 1996 up to today will be available on the Internet (www.gmes-geoland.info): A precipitation product over land, analysed from ground measurements; and a global precipitation product merged from this and the GPCP-1DD multi-satellite product. (orig.)
Full Text Available Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and spacebased remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response.Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and space-based remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response.Understanding urban atmospheric transport in the Los Angeles Basin, where topographic influences on transport patterns are significant, was improved by leveraging the Aliso Canyon leak as an atmospheric tracer. Plume characterization data was collected by the AutoMObile trace Gas (AMOG Surveyor, a commuter car modified for science. Mobile surface in situ CH4 and winds were measured by AMOG Surveyor under Santa Ana conditions to estimate an emission rate of 365±30% Gg yr-1. Vertical profiles were collected by AMOG Surveyor by leveraging local topography for vertical profiling to identify the planetary boundary layer at ~700 m. Topography significantly constrained plume dispersion by up to a factor of two. The observed plume trajectory was used to validate satellite aerosol optical depth-inferred atmospheric transport, which suggested the plume first was driven offshore, but then veered back towards land. Numerical long-range transport model predictions confirm this interpretation. This study demonstrated a novel application of satellite aerosol remote
Full Text Available The accurate measurement of suspended particulate matter (SPM concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal (ρw tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i an assessment of existing atmospheric correction (AC algorithms developed for turbid coastal waters; and (ii a switching method that automatically selects the most sensitive SPM vs. ρw relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE with a method based on multi-temporal analyses of atmospheric constituents (MACCS. For the selected scenes, the ACOLITE-MACCS difference was
Raju, P. L. N.; Gupta, P. K.
One of the prime activities of Indian Space Research Organisation's (ISRO) Space Program is providing satellite communication services, viz., television broadcasting, mobile communication, cyclone disaster warning and rescue operations etc. so as to improve their economic conditions, disseminate technical / scientific knowledge to improve the agriculture production and education for rural people of India. ISRO, along with National Aeronautical and Space Administration (NASA) conducted experimental satellite communication project i.e. Satellite Instructional Television Experiment (SITE) using NASA's Advanced Telecommunication Satellite (i.e. ATS 6) with an objective to educate poor people of India via satellite broadcasting in 1975 and 1976, covering more than 2600 villages in six states of India and territories. Over the years India built communication satellites indigenously to meet the communication requirements of India. This has further lead to launch of an exclusive satellite from ISRO for educational purposes i.e. EDUSAT in 2004 through which rich audio-video content is transmitted / received, recreating virtual classes through interactivity. Indian Institute of Remote Sensing (IIRS) established in 1966, a premier institute in south East Asia in disseminating Remote Sensing (RS) and Geographical Information System (GIS), mainly focusing on contact based programs. But expanded the scope with satellite based Distance Learning Programs for Universities, utilizing the dedicated communication satellite i.e. EDUSAT in 2007. IIRS conducted successfully eight Distance Learning Programs in the last five years and training more than 6000 students mainly at postgraduate level from more than 60 universities /Institutions spread across India. IIRS obtained feedback and improved the programs on the continuous basis. Expanded the scope of IIRS outreach program to train user departments tailor made in any of the applications of Remote Sensing and Geoinformation, capacity
Huang, Chengcheng; Zheng, Xiaogu; Tait, Andrew; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Li, Tao; Wang, Zhonglei
Partial thin-plate smoothing spline model is used to construct the trend surface.Correction of the spline estimated trend surface is often necessary in practice.Cressman weight is modified and applied in residual correction.The modified Cressman weight performs better than Cressman weight.A method for estimating the error covariance matrix of gridded field is provided.
Stockmann, Reto; Christiansen, Freddy; Olsen, Nils
We present an attempt to improve the quality of the geomagnetic field measurements from the Polar Orbiting Geophysical Observatory (POGO) satellite missions in the late 1960s. Inaccurate satellite positions are believed to be a major source of errors for using the magnetic observations for field...... modelling. To improve the data, we use aniterative approach consisting of two main parts: one is a main field modelling process to obtain the radial fieldgradient to perturb the orbits and the other is the state-of-the-art GPS orbit modelling software BERNESE to calculatenew physical orbits. We report....... With this approach, weeliminate the orbit discontinuities at midnight but only tiny quality improvements could be achieved forgeomagnetically quiet data. We believe that improvements to the data are probably still possible, but it would require the original tracking observations to be found....
Umar, M.; Rhoads, Bruce L.; Greenberg, Jonathan A.
Although past work has noted that contrasts in turbidity often are detectable on remotely sensed images of rivers downstream from confluences, no systematic methodology has been developed for assessing mixing over distance of confluent flows with differing surficial suspended sediment concentrations (SSSC). In contrast to field measurements of mixing below confluences, satellite remote-sensing can provide detailed information on spatial distributions of SSSC over long distances. This paper presents a methodology that uses remote-sensing data to estimate spatial patterns of SSSC downstream of confluences along large rivers and to determine changes in the amount of mixing over distance from confluences. The method develops a calibrated Random Forest (RF) model by relating training SSSC data from river gaging stations to derived spectral indices for the pixels corresponding to gaging-station locations. The calibrated model is then used to predict SSSC values for every river pixel in a remotely sensed image, which provides the basis for mapping of spatial variability in SSSCs along the river. The pixel data are used to estimate average surficial values of SSSC at cross sections spaced uniformly along the river. Based on the cross-section data, a mixing metric is computed for each cross section. The spatial pattern of change in this metric over distance can be used to define rates and length scales of surficial mixing of suspended sediment downstream of a confluence. This type of information is useful for exploring the potential influence of various controlling factors on mixing downstream of confluences, for evaluating how mixing in a river system varies over time and space, and for determining how these variations influence water quality and ecological conditions along the river.
Rushi, B. R.; Ellenburg, W. L.; Adams, E. C.; Flores, A.; Limaye, A. S.; Valdés-Pineda, R.; Roy, T.; Valdés, J. B.; Mithieu, F.; Omondi, S.
SERVIR, a joint NASA-USAID initiative, works to build capacity in Earth observation technologies in developing countries for improved environmental decision making in the arena of: weather and climate, water and disasters, food security and land use/land cover. SERVIR partners with leading regional organizations in Eastern and Southern Africa, Hindu Kush-Himalaya, Mekong region, and West Africa to achieve its objectives. SERVIR develops hydrological applications to address specific needs articulated by key stakeholders and daily rainfall estimates are a vital input for these applications. Satellite-derived rainfall is subjected to systemic biases which need to be corrected before it can be used for any hydrologic application such as real-time or seasonal forecasting. SERVIR and the SWAAT team at the University of Arizona, have co-developed an open-source and user friendly tool of rainfall bias correction approaches for SPPs. Bias correction tools were developed based on Linear Scaling and Quantile Mapping techniques. A set of SPPs, such as PERSIANN-CCS, TMPA-RT, and CMORPH, are bias corrected using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data which incorporates ground based precipitation observations. This bias correction tools also contains a component, which is included to improve monthly mean of CHIRPS using precipitation products of the Global Surface Summary of the Day (GSOD) database developed by the National Climatic Data Center (NCDC). This tool takes input from command-line which makes it user-friendly and applicable in any operating platform without prior programming skills. This presentation will focus on this bias-correction tool for SPPs, including application scenarios.
Leifer, Ira; Lehr, William J.; Simecek-Beatty, Debra; Bradley, Eliza; Clark, Roger N.; Dennison, Philip E.; Hu, Yongxiang; Matheson, Scott; Jones, Cathleen E; Holt, Benjamin; Reif, Molly; Roberts, Dar A.; Svejkovsky, Jan; Swayze, Gregg A.; Wozencraft, Jennifer M.
The vast and persistent Deepwater Horizon (DWH) spill challenged response capabilities, which required accurate, quantitative oil assessment at synoptic and operational scales. Although experienced observers are a spill response's mainstay, few trained observers and confounding factors including weather, oil emulsification, and scene illumination geometry present challenges. DWH spill and impact monitoring was aided by extensive airborne and spaceborne passive and active remote sensing.Oil slick thickness and oil-to-water emulsion ratios are key spill response parameters for containment/cleanup and were derived quantitatively for thick (> 0.1 mm) slicks from AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data using a spectral library approach based on the shape and depth of near infrared spectral absorption features. MODIS (Moderate Resolution Imaging Spectroradiometer) satellite, visible-spectrum broadband data of surface-slick modulation of sunglint reflection allowed extrapolation to the total slick. A multispectral expert system used a neural network approach to provide Rapid Response thickness class maps.Airborne and satellite synthetic aperture radar (SAR) provides synoptic data under all-sky conditions; however, SAR generally cannot discriminate thick (> 100 μm) oil slicks from thin sheens (to 0.1 μm). The UAVSAR's (Uninhabited Aerial Vehicle SAR) significantly greater signal-to-noise ratio and finer spatial resolution allowed successful pattern discrimination related to a combination of oil slick thickness, fractional surface coverage, and emulsification.In situ burning and smoke plumes were studied with AVIRIS and corroborated spaceborne CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations of combustion aerosols. CALIPSO and bathymetry lidar data documented shallow subsurface oil, although ancillary data were required for confirmation.Airborne hyperspectral, thermal infrared data have nighttime and
Goetz, Alexander F. H.
The application of remote sensing techniques to mineral exploration involves the use of both spatial (morphological) as well as spectral information. This paper is directed toward a discussion of the uses of spectral image information and emphasizes the newest airborne and spaceborne sensor developments involving imaging spectrometers.
McCarthy, Matthew J; Colna, Kaitlyn E; El-Mezayen, Mahmoud M; Laureano-Rosario, Abdiel E; Méndez-Lázaro, Pablo; Otis, Daniel B; Toro-Farmer, Gerardo; Vega-Rodriguez, Maria; Muller-Karger, Frank E
Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.
McCarthy, Matthew J.; Colna, Kaitlyn E.; El-Mezayen, Mahmoud M.; Laureano-Rosario, Abdiel E.; Méndez-Lázaro, Pablo; Otis, Daniel B.; Toro-Farmer, Gerardo; Vega-Rodriguez, Maria; Muller-Karger, Frank E.
Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.
Menenti, M.; Mulders, C.W.B.
This report describes the development and adaptation of distributed numerical simulation models of hydrological processes in complex watersheds typical of the Andean region. These distributed models take advantage of the synoptic capabilities of sensors on-board satellites and GIS procedures have
Cook, S.A.; Crowe, R.D.; Roblyer, S.P.; Toffer, H.
The Hanford N Reactor is operated by UNC Nuclear Industries for the Department of Energy for the production of special isotopes and electric energy. The reactor has a unique design in which the equipment such as pumps, turbines, generators and diesel engines are located in separate buildings. This equipment arrangement has led to the conclusion that the most cost-effective implementation of a dedicated vibration monitoring system would be to install a computerized network system in lieu of a single analyzing station. In this approach, semi-autonomous micro processor based data collection stations referred to as satellite stations are located near each concentration of machinery to be monitored. The satellite stations provide near continuous monitoring of the machinery. They are linked to a minicomputer using voice grade telephone circuits and hardware and software specifically designed for network communications. The communications link between the satellite stations and the minicomputer permits data and programs to be transmitted between the units. This paper will describe the satellite station associated with large vertical pumps vibration monitoring. The reactor has four of these pumps to supply tertiary cooling to reactor systems. 4 figs
Brown, Molly E.; Grace, Kathryn; Shively, Gerald; Johnson, Kiersten B.; Carroll, Mark
Climate change and degradation of ecosystem services functioning may threaten the ability of current agricultural systems to keep up with demand for adequate and inexpensive food and for clean water, waste disposal and other broader ecosystem services. Human health is likely to be affected by changes occurring across multiple geographic and time scales. Impacts range from increasing transmissibility and the range of vector-borne diseases, such as malaria and yellow fever, to undermining nutrition through deleterious impacts on food production and concomitant increases in food prices. This paper uses case studies to describe methods that make use of satellite remote sensing and Demographic and Health Survey data to better understand individual-level human health and nutrition outcomes. By bringing these diverse datasets together, the connection between environmental change and human health outcomes can be described through new research and analysis.
Kindt-Larsen, Lotte; Berg, Casper Willestofte; Tougaard, J.
grounds, quantify fishing effort and document harbour porpoise bycatch. Movement data from 66 harbour porpoises equipped with satellite transmitters from 1997 to 2012 were used to model population density. A simple model was constructed to investigate the relationship between the response (number...... telemetry or REM data allow for identification of areas of potential high and low bycatch risk, and better predictions are obtained when combining the 2 sources of data. The final model can thus be used as a tool to identify areas of bycatch risk...... and lower risk of porpoise bycatch. From May 2010 to April 2011, 4 commercial gillnet vessels were equipped with remote electronic monitoring (REM) systems. The REM system recorded time, GPS position and closed-circuit television (CCTV) footage of all gillnet hauls. REM data were used to identify fishing...
Yann G. Morel
Full Text Available All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i use only the relative radiance data in the image along with published data, and several new assumptions; (ii in order to specify and operate the simplified radiative transfer equation (RTE; (iii for the purpose of retrieving both the satellite derived bathymetry (SDB and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need for (i formal atmospheric correction; (ii conversion of relative radiance into calibrated reflectance; or (iii existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM. This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.
Lin, C. Q.; Liu, G.; Lau, A. K. H.; Li, Y.; Li, C. C.; Fung, J. C. H.; Lao, X. Q.
Given the vast territory of China, the long-term PM2.5 trends may substantially differ among the provinces. In this study, we aim to assess the provincial PM2.5 trends in China during the past few Five-Year Plan (FYP) periods. The lack of long-term PM2.5 measurements, however, makes such assessment difficult. Satellite remote sensing of PM2.5 concentration is an important step toward filling this data gap. In this study, a PM2.5 data set was built over China at a resolution of 1 km from 2001 to 2015 using satellite remote sensing. Analyses show that the national average of PM2.5 concentration increased by 0.04 μg·m-3·yr-1 during the 10th FYP period (2001-2005) and started to decline by -0.65 μg·m-3·yr-1 and -2.33 μg·m-3·yr-1 during the 11th (2006-2010) and the 12th (2011-2015) FYP period, respectively. In addition, substantial differences in the PM2.5 trends were observed among the provinces. Provinces in the Beijing-Tianjin-Hebei (BTH) region had the largest reduction of PM2.5 concentrations during the 10th and 12th FYP period. The greatest reduction rate of PM2.5 concentration during the 10th and 12th FYP period was observed in Beijing (-3.68 μg·m-3·yr-1) and Tianjin (-6.62 μg·m-3·yr-1), respectively. In contrast, PM2.5 concentrations remained steady for provinces in eastern and southeastern China (e.g., Shanghai) during the 12th FYP period. In overall, great efforts are still required to effectively reduce the PM2.5 concentrations in future.
Ou, Steve Szu-Cheng; Liou, Kuo-Nan; Wang, Xingjuan; Hansell, Richard; Lefevre, Randy; Cocks, Stephen
We undertook a new approach to investigate the aerosol indirect effect of the first kind on ice cloud formation by using available data products from the Moderate-Resolution Imaging Spectrometer (MODIS) and obtained physical understanding about the interaction between aerosols and ice clouds. Our analysis focused on the examination of the variability in the correlation between ice cloud parameters (optical depth, effective particle size, cloud water path, and cloud particle number concentration) and aerosol optical depth and number concentration that were inferred from available satellite cloud and aerosol data products. Correlation results for a number of selected scenes containing dust and ice clouds are presented, and dust aerosol indirect effects on ice clouds are directly demonstrated from satellite observations.
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)...
Tile Calorimeter modules stored at CERN. The larger modules belong to the Barrel, whereas the smaller ones are for the two Extended Barrels. (The article was about the completion of the 64 modules for one of the latter.) The photo on the first page of the Bulletin n°26/2002, from 24 July 2002, illustrating the article «The ATLAS Tile Calorimeter gets into shape» was published with a wrong caption. We would like to apologise for this mistake and so publish it again with the correct caption.
Full Text Available Precision agriculture is a way to manage the crop yield resources like water, fertilizers, soil, seeds in order to increase production, quality, gain and reduce squander products so that the existing system become eco-friendly. The main target of precision agriculture is to match resources and execution according to the crop and climate to ameliorate the effects of Praxis. Global Positioning System, Geographic Information System, Remote sensing technologies and various sensors are used in Precision farming for identifying the variability in field and using different methods to deal with them. Satellite based remote sensing is used to study the variability in crop and ground but suffer from various disadvantageous such as prohibited use, high price, less revisiting them, poor resolution due to great height, Unmanned Aerial Vehicle (UAV is other alternative option for application in precision farming. UAV overcomes the drawback of the ground based system, i.e. inaccessibility to muddy and very dense regions. Hovering at a peak of 500 meter - 1000 meter is good enough to offer various advantageous in image acquisition such as high spatial and temporal resolution, full flexibility, low cost. Recent studies of application of UAV in precision farming indicate advanced designing of UAV, enhancement in georeferencing and the mosaicking of image, analysis and extraction of information required for supplying a true end product to farmers. This paper also discusses the various platforms of UAV used in farming applications, its technical constraints, seclusion rites, reliability and safety.
Full Text Available This study assesses the impact assimilating the scatterometer near-surface wind observations and total precipitable water from the SSMI, into WRF on genesis and track forecasting of four tropical cyclones (TCs. These TCs are selected to be representative of different intensity categories and basins. Impact is via a series of data denial experiments that systematically exclude the remote sensed information. Compared with the control case, in which only the final analysis atmospheric variables are used to initialize and provide the lateral boundary conditions, the data assimilation runs performed consistently better, but with very different skill levels for the different TCs. Eliassen-Palm flux analyses are employed. It is confirmed that if a polar orbital satellite footprint passes over the TC’s critical genesis region, the forecast will profit most from assimilating the remotely sensed information. If the critical genesis region lies within an interorbital gap then, regardless of how strong the TC later becomes (e.g., Katrina 2005, the improvement from assimilating near-surface winds and total precipitable water in the model prediction is severely limited. This underpins the need for a synergy of data from different scatterometers/radiometers. Other approaches are suggested to improve the accuracy in the prediction of TC genesis and tracks.
Priede, Imants G.
The development of knowledge of global biogeography of the oceans from sixteenthcentury European voyages of exploration to present-day use of satellite remote sensing is reviewed in three parts; the pre-satellite era (1513-1977), the satellite era leading to a first global synthesis (1978-1998), and more recent studies since 1998. The Gulf Stream was first identified as a strong open-ocean feature in 1513 and by the eighteenth century, regular transatlantic voyages by sailing ships had established the general patterns of winds and circulation, enabling optimisation of passage times. Differences in water temperature, water colour and species of animals were recognised as important cues for navigation. Systematic collection of information from ships' logs enabled Maury (The Physical Geography of the Sea Harper and Bros. New York 1855) to produce a chart of prevailing winds across the entire world's oceans, and by the early twentieth century the global surface ocean circulation that defines the major biogeographic regions was well-known. This information was further supplemented by data from large-scale plankton surveys. The launch of the Coastal Zone Color Scanner, specifically designed to study living marine resources on board the Nimbus 7 polar orbiting satellite in 1978, marked the advent of the satellite era. Over subsequent decades, correlation of satellite-derived sea surface temperature and chlorophyll data with in situ measurements enabled Longhurst (Ecological Geography of the Sea. Academic Press, New York 1998) to divide the global ocean into 51 ecological provinces with Polar, Westerly Wind, Trade Wind and Coastal Biomes clearly recognisable from earlier subdivisions of the oceans. Satellite imagery with semi-synoptic images of large areas of the oceans greatly aided definition of boundaries between provinces. However, ocean boundaries are dynamic, varying from season to season and year to year. More recent work has focused on the study of variability of
Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao
A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation. PMID:26404292
Full Text Available A typical application scenario of remote wireless sensor networks (WSNs is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.
Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao
A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.
Werdell, P. Jeremy; Franz, Bryan A.; Bailey, Sean W.
The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nL(sub w)(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nL(sub w)(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nL(sub w)(lambda) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nL(sub w)(lambda) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nL(sub w)(lambda) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach.
Malakar, Nabin K.; Lary, D. L.; Moore, A.; Gencaga, D.; Roscoe, B.; Albayrak, Arif; Petrenko, Maksym; Wei, Jennifer
Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.
The main environmental issues affecting the broad acceptability of nuclear power plant are the emission of radioactive materials, the generation of radioactive waste, and the potential for nuclear accidents. All nuclear fission reactors, regardless of design, location, operator or regulator, have the potential to undergo catastrophic accidents involving loss of control of the reactor core, failure of safety systems and subsequent widespread fallout of hazardous fission products. Risk is the mathematical product of probability and consequences, so lowprobability and high-consequence accidents, by definition, have a high risk. NPP environment surveillance is a very important task in frame of risk assessment. Satellite remote sensing data had been applied for dosimeter levels first time for Chernobyl NPP accident in 1986. Just for a normal functioning of a nuclear power plant, multitemporal and multispectral satellite data in complementarily with field data are very useful tools for NPP environment surveillance and risk assessment. Satellite remote sensing is used as an important technology to help environmental research to support research analysis of spatio-temporal dynamics of environmental features nearby nuclear facilities. Digital processing techniques applied to several LANDSAT, MODIS and QuickBird data in synergy with in-situ data are used to assess the extent and magnitude of radiation and non-radiation effects on the water, near field soil, vegetation and air. As a test case the methodology was applied for for Nuclear Power Plant (NPP) Cernavoda, Romania. Thermal discharge from nuclear reactors cooling is dissipated as waste heat in Danube-Black -Sea Canal and Danube River. Water temperatures captured in thermal IR imagery are correlated with meteorological parameters. If during the winter thermal plume is localized to an area of a few km of NPP, the temperature difference between the plume and non-plume areas being about 1.5 oC, during summer and fall , is
Full Text Available Regarding Gorelik, G., & Shackelford, T.K. (2011. Human sexual conflict from molecules to culture. Evolutionary Psychology, 9, 564–587: The authors wish to correct an omission in citation to the existing literature. In the final paragraph on p. 570, we neglected to cite Burch and Gallup (2006 [Burch, R. L., & Gallup, G. G., Jr. (2006. The psychobiology of human semen. In S. M. Platek & T. K. Shackelford (Eds., Female infidelity and paternal uncertainty (pp. 141–172. New York: Cambridge University Press.]. Burch and Gallup (2006 reviewed the relevant literature on FSH and LH discussed in this paragraph, and should have been cited accordingly. In addition, Burch and Gallup (2006 should have been cited as the originators of the hypothesis regarding the role of FSH and LH in the semen of rapists. The authors apologize for this oversight.
The photo on the second page of the Bulletin n°48/2002, from 25 November 2002, illustrating the article «Spanish Visit to CERN» was published with a wrong caption. We would like to apologise for this mistake and so publish it again with the correct caption. The Spanish delegation, accompanied by Spanish scientists at CERN, also visited the LHC superconducting magnet test hall (photo). From left to right: Felix Rodriguez Mateos of CERN LHC Division, Josep Piqué i Camps, Spanish Minister of Science and Technology, César Dopazo, Director-General of CIEMAT (Spanish Research Centre for Energy, Environment and Technology), Juan Antonio Rubio, ETT Division Leader at CERN, Manuel Aguilar-Benitez, Spanish Delegate to Council, Manuel Delfino, IT Division Leader at CERN, and Gonzalo León, Secretary-General of Scientific Policy to the Minister.
Full Text Available Regarding Tagler, M. J., and Jeffers, H. M. (2013. Sex differences in attitudes toward partner infidelity. Evolutionary Psychology, 11, 821–832: The authors wish to correct values in the originally published manuscript. Specifically, incorrect 95% confidence intervals around the Cohen's d values were reported on page 826 of the manuscript where we reported the within-sex simple effects for the significant Participant Sex × Infidelity Type interaction (first paragraph, and for attitudes toward partner infidelity (second paragraph. Corrected values are presented in bold below. The authors would like to thank Dr. Bernard Beins at Ithaca College for bringing these errors to our attention. Men rated sexual infidelity significantly more distressing (M = 4.69, SD = 0.74 than they rated emotional infidelity (M = 4.32, SD = 0.92, F(1, 322 = 23.96, p < .001, d = 0.44, 95% CI [0.23, 0.65], but there was little difference between women's ratings of sexual (M = 4.80, SD = 0.48 and emotional infidelity (M = 4.76, SD = 0.57, F(1, 322 = 0.48, p = .29, d = 0.08, 95% CI [−0.10, 0.26]. As expected, men rated sexual infidelity (M = 1.44, SD = 0.70 more negatively than they rated emotional infidelity (M = 2.66, SD = 1.37, F(1, 322 = 120.00, p < .001, d = 1.12, 95% CI [0.85, 1.39]. Although women also rated sexual infidelity (M = 1.40, SD = 0.62 more negatively than they rated emotional infidelity (M = 2.09, SD = 1.10, this difference was not as large and thus in the evolutionary theory supportive direction, F(1, 322 = 72.03, p < .001, d = 0.77, 95% CI [0.60, 0.94].
Hung, R. J.; Tsao, Y. D.
Rawinsonde data and geosynchronous satellite imagery were used to investigate the life cycles of St. Anthony, Minnesota's severe convective storms. It is found that the fully developed storm clouds, with overshooting cloud tops penetrating above the tropopause, collapsed about three minutes before the touchdown of the tornadoes. Results indicate that the probability of producing an outbreak of tornadoes causing greater damage increases when there are higher values of potential energy storage per unit area for overshooting cloud tops penetrating the tropopause. It is also found that there is less chance for clouds with a lower moisture content to be outgrown as a storm cloud than clouds with a higher moisture content.
Cole, Tony A.; Molthan, Andrew L.; Schultz, Lori A.; Roman, Miguel O.; Wanik, David W.
Observations made by the VIIRS day/night band (DNB) provide daily, nighttime measurements to monitor Earth surface processes.However, these observations are impacted by variations in reflected solar radiation on the moon's surface. As the moon transitions from new to full phase, increasing radiance is reflected to the Earth's surface and contributes additional reflected moonlight from clouds and land surface, in addition to emissions from other light sources observed by the DNB. The introduction of a bi-directional reflectance distribution function (BRDF) algorithm serves to remove these lunar variations and normalize observed radiances. Provided by the Terrestrial Information Systems Laboratory at Goddard Space Flight Center, a 1 km gridded lunar BRDF-corrected DNB product and VIIRS cloud mask can be used for a multitude of nighttime applications without influence from the moon. Such applications include the detection of power outages following severe weather events using pre-and post-event DNB imagery, as well as the identification of boat features to curtail illegal fishing practices. This presentation will provide context on the importance of the lunar BRDF correction algorithm and explore the aforementioned uses of this improved DNB product for applied science applications.
Cole, T.; Molthan, A.; Schultz, L. A.; Roman, M. O.; Wanik, D. W.
Observations made by the VIIRS day/night band (DNB) provide daily, nighttime measurements to monitor Earth surface processes. However, these observations are impacted by variations in reflected solar radiation on the moon's surface. As the moon transitions from new to full phase, increasing radiance is reflected to the Earth's surface and contributes additional reflected moonlight from clouds and land surface, in addition to emissions from other light sources observed by the DNB. The introduction of a bi-directional reflectance distribution function (BRDF) algorithm serves to remove these lunar variations and normalize observed radiances. Provided by the Terrestrial Information Systems Laboratory at Goddard Space Flight Center, a 1 km gridded lunar BRDF-corrected DNB product and VIIRS cloud mask can be used for a multitude of nighttime applications without influence from the moon. Such applications include the detection of power outages following severe weather events using pre- and post-event DNB imagery, as well as the identification of boat features to curtail illegal fishing practices. This presentation will provide context on the importance of the lunar BRDF correction algorithm and explore the aforementioned uses of this improved DNB product for applied science applications.
Shepherd, M.; Santanello, J. A., Jr.
When Explorer 1 launched nearly 60 years ago, it helped usher in a golden age of scientific understanding of arguably the most important planet in our solar system. From its inception NASA and its partners were charged with leveraging the vantagepoint of space to advance knowledge outside and within Earth's atmosphere. Earth is a particularly complex natural system that is increasingly modified by human activities. The hydrological or water cycle is a critical circuit in the Earth system. Its complexity requires novel observations and simulation capability to fully understand it and predict changes. This talk will introduce some of the unique satellite-based observations used for hydroclimate studies. Two specific examples will be presented. The first example explores a relatively new thread of research examining the impact of soil moisture on landfalling and other types of tropical systems. Recent literature suggests that tropical cyclones or large rain-producing systems like the one that caused catastrophic flooding in Louisiana (2016) derive moisture from a "brown ocean" of wet soils or wetlands. The second example summarizes a decade of research on how urbanization has altered the precipitation and land surface hydrology components of the water cycle. With both cases, a multitude of satellite or model-based datesets will be summarized (e.g., TRMM, GPM, SMAP, NLDAS).
Smith, Laurence C.
The growing availability of multi-temporal satellite data has increased opportunities for monitoring large rivers from space. A variety of passive and active sensors operating in the visible and microwave range are currently operating, or planned, which can estimate inundation area and delineate flood boundaries. Radar altimeters show great promise for directly measuring stage variation in large rivers. It also appears to be possible to obtain estimates of river discharge from space, using ground measurements and satellite data to construct empirical curves that relate water surface area to discharge. Extrapolation of these curves to ungauged sites may be possible for the special case of braided rivers.Where clouds, trees and floating vegetation do not obscure the water surface, high-resolution visible/infrared sensors provide good delineation of inundated areas. Synthetic aperture radar (SAR) sensors can penetrate clouds and can also detect standing water through emergent aquatic plants and forest canopies. However, multiple frequencies and polarizations are required for optimal discrimination of various inundated vegetation cover types. Existing single-polarization, fixed-frequency SARs are not sufficient for mapping inundation area in all riverine environments. In the absence of a space-borne multi-parameter SAR, a synergistic approach using single-frequency, fixed-polarization SAR and visible/infrared data will provide the best results over densely vegetated river floodplains.
Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.
Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to
Royden, H. N.; Green, D. W.; Walson, G. R.
Faraday-rotation data from the linearly polarized 137-MHz beacons of the ATS-1, SIRIO, and Kiku-2 geosynchronous satellites are used to determine the ionospheric corrections to the range and Doppler data for interplanetary spacecraft navigation. The JPL operates the Deep Space Network of tracking stations for NASA; these stations monitor Faraday rotation with dual orthogonal, linearly polarized antennas, Teledyne polarization tracking receivers, analog-to-digital converter/scanners, and other support equipment. Computer software examines the Faraday data, resolves the pi ambiguities, constructs a continuous Faraday-rotation profile and converts the profile to columnar zenith total electron content at the ionospheric reference point; a second program computes the line-of-sight ionospheric correction for each pass of the spacecraft over each tracking complex. Line-of-sight ionospheric electron content using mapped Faraday-rotation data is compared with that using dispersive Doppler data from the Voyager spacecraft; a difference of about 0.4 meters, or 5 x 10 to the 16th electrons/sq m is obtained. The technique of determining the electron content of interplanetary plasma by subtraction of the ionospheric contribution is demonstrated on the plasma torus surrounding the orbit of Io.
Brown, Molly E.; Pinzon, Jorge E.; Prince, Stephen D.
Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.
Zasetsky, A. Y.; Khalizov, A.; Sloan, J.
Observations of broadband Infrared satellites such as ILAS-II (Ministry of the Environment, Japan, launched 14 December 2002) and SciSat-1 (Canadian Space Agency, launched 12 August 2003) can provide details of the chemical composition and particle size of atmospheric aerosols by direct inversion without recourse to models. During the past decade, we have developed mathematical methods to achieve this inversion by working with FTIR observations of model atmospheric aerosols in cryogenic flowtubes. More recently, we have converted these to operational algorithms for use in the above missions. In this presentation, we will briefly outline these procedures and illustrate their capabilities using laboratory data. These laboratory results show that the chemical compositions, phases and sizes of ensembles of particles can be obtained simultaneously using these procedures. We will also report chemical and microphysical properties of lower stratospheric clouds and aerosols derived by applying these procedures to observations from space.
Yamamoto, Y.; Kondoh, T.; Kida, T.; Nishikawa, H.
The thickness of the soil layers in which tree roots are able to develop freely influences forest composition and growth. Trees growing in shallow soil are usually less well supplied with water and mineral nutrients than those growing in deeper soil. A soil may be deep in an absolute sense but, because of a relatively impervious layer, such as hardpan or because of a high water-table, may be shallow in a physiological sense. Penetrability measurements have been found useful in evaluating the influence of different forest types on the physical properties of soils. Commonly the penetrability of soils can be measured by using the Hasegawa-formed soil penetrometer and can be judged as the soil softness content (SSC). Previous studies report soil with more than 1.9 cm/drop of SSC to be highly permeable and therefore roots are more likely to be extensively developed. Based upon this theory the depth of soil layer with more than 1.9 cm/drop of SSC can be defined as the Effective Depth of Soil Layer (EDSL). We examined the relationship between the Ratio Vegetation Index (RVI) and the EDSL and established a 'Runoff Simulation Model (RSM)' based upon the theory of the Storage Function Model method. The conclusions are that (1) a strong positive correlation between the RVI (ground measured) and the EDSL was given, (2) applying results of conclusion (1) to satellite analysis a similar correlation between the RVI (satellite analysis of JERS 1/OPS data) and the EDSL was observed and (3) the simulated storm-runoff hydro graph coincides with the observed one well
Coffield, S. R.; Crosson, W. L.; Al-Hamdan, M. Z.; Barik, M. G.
Consistent and accurate monitoring of the Great Lakes is critical for protecting the freshwater ecosystems, quantifying the impacts of climate change, understanding harmful algal blooms, and safeguarding public health for the millions who rely on the Lakes for drinking water. While ground-based monitoring is often hampered by limited sampling resolution, satellite data provide surface reflectance measurements at much more complete spatial and temporal scales. In this study, we implemented NASA data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to build robust water quality models. We developed and validated models for chlorophyll-a, nitrogen, phosphorus, and turbidity based on combinations of the six MODIS Ocean Color bands (412, 443, 488, 531, 547, and 667nm) for 2003-2016. Second, we applied these models to quantify trends in water quality through time and in relation to changing land cover, runoff, and climate for six selected coastal areas in Lakes Michigan and Erie. We found strongest models for chlorophyll-a in Lake Huron (R2 = 0.75), nitrogen in Lake Ontario (R2=0.66), phosphorus in Lake Erie (R2=0.60), and turbidity in Lake Erie (R2=0.86). These offer improvements over previous efforts to model chlorophyll-a while adding nitrogen, phosphorus, and turbidity. Mapped water quality parameters showed high spatial variability, with nitrogen concentrated largely in Superior and coastal Michigan and high turbidity, phosphorus, and chlorophyll near urban and agricultural areas of Erie. Temporal analysis also showed concurrence of high runoff or precipitation and nitrogen in Lake Michigan offshore of wetlands, suggesting that water quality in these areas is sensitive to changes in climate.
Full Text Available In this review paper we present geographical, ecological and historical aspects of Southeast Asia from the perspective of forest degradation monitoring and critically discuss available approaches for large area forest degradation monitoring with satellite remote sensing data at high to medium spatial resolution (5–30 m. Several authors have achieved promising results in geographically limited areas within Southeast Asia using automated detection algorithms. However, the application of automated methods to large area assessments remains a major challenge. To-date, nearly all large area assessments of forest degradation in the region have included a strong visual interpretation component. We conclude that due to the variety of forest types and forest disturbance levels, as well as the variable image acquisition conditions in Southeast Asia, it is unlikely that forest degradation monitoring can be conducted throughout the region using a single automated approach with currently available remote sensing data. The provision of regionally consistent information on forest degradation from satellite remote sensing data remains therefore challenging. However, the expected increase in observation frequency in the near future (due to Landsat 8 and Sentinel-2 satellites may lead to the desired improvement in data availability and enable consistent and robust regional forest degradation monitoring in Southeast Asia. Keywords: Tropical forest disturbance, Selective logging, Shifting cultivation, Satellite data, Indochina peninsula, Maritime continent
Piffl, V.; Pichal, J.
The following topics were dealt with: (i) Current status of the Garching/Greifswald connection; (ii) Remote participation across national boundaries; (iii) The TEC approach to a remote control room at TEXTOR; (iv) Uniform data access for remote participation; (v) Remote participation in the US transport code collaboration; (vi) Client-server for remote collaboration and remote invocation of analysis applications and application to the national transport code; (vii) Remote collaboration and data access at the DIII-D national fusion facility; (viii) The collaboration for support of scientific research; and (ix) JET and remote participation. (P.A.)
Piffl, V; Pichal, J [eds.
The following topics were dealt with: (i) Current status of the Garching/Greifswald connection; (ii) Remote participation across national boundaries; (iii) The TEC approach to a remote control room at TEXTOR; (iv) Uniform data access for remote participation; (v) Remote participation in the US transport code collaboration; (vi) Client-server for remote collaboration and remote invocation of analysis applications and application to the national transport code; (vii) Remote collaboration and data access at the DIII-D national fusion facility; (viii) The collaboration for support of scientific research; and (ix) JET and remote participation. (P.A.)
Full Text Available Water level (WL and water volume (WV of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite radar altimetry (RA, Envisat and Jason-2 and Landsat-5/-7/-8 Thematic Mapper (TM/Enhanced Thematic Mapper plus (ETM+/Operational Land Imager (OLI optical remote sensing (RS imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between WL variation and water extent was first established for each dam, and then the combined long-term WL time series from Landsat images are reconstructed for the dams. The R2 between altimetry WL and Landsat water area measurements is >0.95. Next, the Tropical Rainfall Measuring Mission (TRMM data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in situ gauge data, in term of root-mean-square error (RMSE is at 2–5 m level. The estimated WV variations derived from combined RA
P. M. E. Décréau
latitudes, is radiating radio waves. The radio waves are issued from multiple sources of small size, each related to a given fs series and radiating inside a beam of narrow cone angle, referred to as a beamlet. The beamlets illuminate different satellites simultaneously, at different characteristic fs values, according to the latitude at which the satellite is placed. Second, when an observing satellite moves away from its assumed source region (the plasmapause surface, it is illuminated by several beamlets, issued from nearby sources with characteristic fs values close to each other. The addition of radio waves blurs the spectra of the overall received electric field. It can move the signal peaks such that their position fs satisfiesfs = (n+α df, with 0 < α < 1. These findings open new perspectives for the interpretation of NTC events displaying harmonic signatures.
Chen, Gongbo; Knibbs, Luke D; Zhang, Wenyi; Li, Shanshan; Cao, Wei; Guo, Jianping; Ren, Hongyan; Wang, Boguang; Wang, Hao; Williams, Gail; Hamm, N A S; Guo, Yuming
PM 1 might be more hazardous than PM 2.5 (particulate matter with an aerodynamic diameter ≤ 1 μm and ≤2.5 μm, respectively). However, studies on PM 1 concentrations and its health effects are limited due to a lack of PM 1 monitoring data. To estimate spatial and temporal variations of PM 1 concentrations in China during 2005-2014 using satellite remote sensing, meteorology, and land use information. Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) data, Dark Target (DT) and Deep Blue (DB), were combined. Generalised additive model (GAM) was developed to link ground-monitored PM 1 data with AOD data and other spatial and temporal predictors (e.g., urban cover, forest cover and calendar month). A 10-fold cross-validation was performed to assess the predictive ability. The results of 10-fold cross-validation showed R 2 and Root Mean Squared Error (RMSE) for monthly prediction were 71% and 13.0 μg/m 3 , respectively. For seasonal prediction, the R 2 and RMSE were 77% and 11.4 μg/m 3 , respectively. The predicted annual mean concentration of PM 1 across China was 26.9 μg/m 3 . The PM 1 level was highest in winter while lowest in summer. Generally, the PM 1 levels in entire China did not substantially change during the past decade. Regarding local heavy polluted regions, PM 1 levels increased substantially in the South-Western Hebei and Beijing-Tianjin region. GAM with satellite-retrieved AOD, meteorology, and land use information has high predictive ability to estimate ground-level PM 1 . Ambient PM 1 reached high levels in China during the past decade. The estimated results can be applied to evaluate the health effects of PM 1 . Copyright © 2017 Elsevier Ltd. All rights reserved.
Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.
Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.
Zhang, G.; Perrie, W. A.; Liu, G.; Zhang, L.
Hurricanes over the ocean have been observed by spaceborne aperture radar (SAR) since the first SAR images were available in 1978. SAR has high spatial resolution (about 1 km), relatively large coverage and capability for observations during almost all-weather, day-and-night conditions. In this study, seven C-band RADARSAT-2 dual-polarized (VV and VH) ScanSAR wide images from the Canadian Space Agency (CSA) Hurricane Watch Program in 2017 are collected over five hurricanes: Harvey, Irma, Maria, Nate, and Ophelia. We retrieve the ocean winds by applying our C-band Cross-Polarization Coupled-Parameters Ocean (C-3PO) wind retrieval model [Zhang et al., 2017, IEEE TGRS] to the SAR images. Ocean waves are estimated by applying a relationship based on the fetch- and duration-limited nature of wave growth inside hurricanes [Hwang et al., 2016; 2017, J. Phys. Ocean.]. We estimate the ocean surface currents using the Doppler Shift extracted from VV-polarized SAR images [Kang et al., 2016, IEEE TGRS]. C-3PO model is based on theoretical analysis of ocean surface waves and SAR microwave backscatter. Based on the retrieved ocean winds, we estimate the hurricane center locations, maxima wind speeds, and radii of the five hurricanes by adopting the SHEW model (Symmetric Hurricane Estimates for Wind) by Zhang et al. [2017, IEEE TGRS]. Thus, we investigate possible relations between hurricane structures and intensities, and especially some possible effects of the asymmetrical characteristics on changes in the hurricane intensities, such as the eyewall replacement cycle. The three SAR images of Ophelia include the north coast of Ireland and east coast of Scotland allowing study of ocean surface currents respond to the hurricane. A system of methods capable of observing marine winds, surface waves, and surface currents from satellites is of value, even if these data are only available in near real-time or from SAR-related satellite images. Insight into high resolution ocean winds
P. L. N. Raju
Full Text Available One of the prime activities of Indian Space Research Organisation's (ISRO Space Program is providing satellite communication services, viz., television broadcasting, mobile communication, cyclone disaster warning and rescue operations etc. so as to improve their economic conditions, disseminate technical / scientific knowledge to improve the agriculture production and education for rural people of India. ISRO, along with National Aeronautical and Space Administration (NASA conducted experimental satellite communication project i.e. Satellite Instructional Television Experiment (SITE using NASA’s Advanced Telecommunication Satellite (i.e. ATS 6 with an objective to educate poor people of India via satellite broadcasting in 1975 and 1976, covering more than 2600 villages in six states of India and territories. Over the years India built communication satellites indigenously to meet the communication requirements of India. This has further lead to launch of an exclusive satellite from ISRO for educational purposes i.e. EDUSAT in 2004 through which rich audio-video content is transmitted / received, recreating virtual classes through interactivity. Indian Institute of Remote Sensing (IIRS established in 1966, a premier institute in south East Asia in disseminating Remote Sensing (RS and Geographical Information System (GIS, mainly focusing on contact based programs. But expanded the scope with satellite based Distance Learning Programs for Universities, utilizing the dedicated communication satellite i.e. EDUSAT in 2007. IIRS conducted successfully eight Distance Learning Programs in the last five years and training more than 6000 students mainly at postgraduate level from more than 60 universities /Institutions spread across India. IIRS obtained feedback and improved the programs on the continuous basis. Expanded the scope of IIRS outreach program to train user departments tailor made in any of the applications of Remote Sensing and
Full Text Available The collinear rigorous geometric model contains the atmosphere refraction geometric error in off-nadir observation. In order to estimate and correct the atmosphere refraction geometric error, the ISO international standard atmospheric model and Owens atmosphere refractive index algorithm are applied to calculate the index of atmosphere refraction in different latitude and altitude. The paper uses the weighted mean algorithm to reduce the eight layers ISO standard atmospheric model into a simple troposphere and stratosphere two layers spherical atmosphere. And the LOS vector track geometric algorithm is used to estimate the atmosphere refraction geometric error in different observation off-nadir angle. The results show that the atmosphere refraction will introduce about 2.5 m or 9 m geometric displacement in 30 or 45 degree off-nadir angle individual. Therefore, during geo-location processing of agile platform and extra wide high spatial resolution imagery, there is need to take into account the influence of atmosphere refraction and correct the atmosphere refraction geometric error to enhance the geo-location precision without GCPs.
Avisse, Nicolas; Tilmant, Amaury; François Müller, Marc; Zhang, Hua
In river basins with water storage facilities, the availability of regularly updated information on reservoir level and capacity is of paramount importance for the effective management of those systems. However, for the vast majority of reservoirs around the world, storage levels are either not measured or not readily available due to financial, political, or legal considerations. This paper proposes a novel approach using Landsat imagery and digital elevation models (DEMs) to retrieve information on storage variations in any inaccessible region. Unlike existing approaches, the method does not require any in situ measurement and is appropriate for monitoring small, and often undocumented, irrigation reservoirs. It consists of three recovery steps: (i) a 2-D dynamic classification of Landsat spectral band information to quantify the surface area of water, (ii) a statistical correction of DEM data to characterize the topography of each reservoir, and (iii) a 3-D reconstruction algorithm to correct for clouds and Landsat 7 Scan Line Corrector failure. The method is applied to quantify reservoir storage in the Yarmouk basin in southern Syria, where ground monitoring is impeded by the ongoing civil war. It is validated against available in situ measurements in neighbouring Jordanian reservoirs. Coefficients of determination range from 0.69 to 0.84, and the normalized root-mean-square error from 10 to 16 % for storage estimations on six Jordanian reservoirs with maximal water surface areas ranging from 0.59 to 3.79 km2.
Kimijiama, S; Nagai, M
In Greater Mekong Sub-region (GMS), economic liberalization and deregulation facilitated by GMS Regional Economic Corporation Program (GMS-ECP) has triggered urbanization in the region. However, the urbanization rate and its linkage to socio-economic activities are ambiguous. The objectives of this paper are to: (a) determine the changes in urban area from 1972 to 2013 using remote sensing data, and (b) analyse the relationships between urbanization with respect to socio-economic activities in central Laos. The study employed supervised classification and human visible interpretation to determine changes in urbanization rate. Regression analysis was used to analyze the correlation between the urbanization rate and socio-economic variables. The result shows that the urban area increased significantly from 1972 to 2013. The socio-economic variables such as school enrollment, labour force, mortality rate, water source and sanitation highly correlated with the rate of urbanization during the period. The study concluded that identifying the highly correlated socio-economic variables with urbanization rate could enable us to conduct a further urbanization simulation. The simulation helps in designing policies for sustainable development
Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix
Potato is one of the staple foods and cash crops in Bangladesh. It is widely cultivated in all of the districts and ranks second after rice in production. Bangladesh is the fourth largest potato producer in Asia and is among the world's top 15 potato producing countries. The weather condition for potato cultivation is favorable during the sowing, growing and harvesting period. It is a winter crop and is cultivated during the period of November to March. Bangladesh is mainly an agricultural based country with respect to agriculture's contribution to GDP, employment and consumption. Potato is a prominent crop in consideration of production, its internal demand and economic value. Bangladesh has a big economic activities related to potato cultivation and marketing, especially the economic relations among farmers, traders, stockers and cold storage owners. Potato yield prediction before harvest is an important issue for the Government and the stakeholders in managing and controlling the potato market. Advanced very high resolution radiometer (AVHRR) based satellite data product vegetation health indices VCI (vegetation condition index) and TCI (temperature condition index) are used as predictors for early prediction. Artificial neural network (ANN) is used to develop a prediction model. The simulated result from this model is encouraging and the error of prediction is less than 10%.
Die, Hu; Lei, Zhang; Hongbin, Wang
In this study, Aerosol Optical Depth (AOD) at 550nm from the MODIS sensor on board the Terra/Aqua satellites were compared with sun photometer (CE-318) measurements from 11 AERONET stations in China. The average correlation coefficient (R) value from the AOD product, using the Aqua-MODIS Deep Blue algorithm, in the Hexi Corridor was 0.67. The MODIS Dark Target algorithm AOD product is superior to Deep Blue algorithm AOD products in SACOL of the Semi-arid regions of the Loess Plateau. These two kinds of algorithm are not applicable to sites in Lanzhou city. The average R value of Dark Target algorithm AOD MODIS products is 0.91 for Terra and 0.88 for Aqua in the eastern part of China. According to the analysis of spatial and temporal characteristics of the two MODIS AOD products in China, high value areas are mainly distributed in the southern part of Xinjiang (0.5∼0.8), Sichuan Basin (0.8∼0.9), North China (0.6∼0.8) and the middle and lower reaches of the Changjiang River (0.8∼1.0). The Deep Blue algorithm for Aqua-MODIS is a good supplement for the retrieval of AOD above bright surfaces of deserts in Northwest China
The angular distribution of radiation scattered by the earth surface contains information on the structural and optical properties of the surface. Potentially, this information may be retrieved through the inversion of surface bidirectional reflectance distribution function (BRDF) models. This report details the limitations and efficient application of BRDF model inversions using data from ground- and satellite-based sensors. A turbid medium BRDF model, based on the discrete ordinates solution to the transport equation, was used to quantify the sensitivity of top-of-canopy reflectance to vegetation and soil parameters. Results were used to define parameter sets for inversions. Using synthetic reflectance values, the invertibility of the model was investigated for different optimization algorithms, surface and sampling conditions. Inversions were also conducted with field data from a ground-based radiometer. First, a soil BRDF model was inverted for different soil and sampling conditions. A condition-invariant solution was determined and used as the lower boundary condition in canopy model inversions. Finally, a scheme was developed to improve the speed and accuracy of inversions.
Allen, G. H.; David, C. H.; Andreadis, K. M.; Emery, C. M.; Famiglietti, J. S.
Earth observing satellites provide valuable near real-time (NRT) information about flood occurrence and magnitude worldwide. This NRT information can be used in early flood warning systems and other flood management applications to save lives and mitigate flood damage. However, these NRT products are only useful to early flood warning systems if they are quickly made available, with sufficient time for flood mitigation actions to be implemented. More specifically, NRT data latency, or the time period between the satellite observation and when the user has access to the information, must be less than the time it takes a flood to travel from the flood observation location to a given downstream point of interest. Yet the paradigm that "lower latency is always better" may not necessarily hold true in river systems due to tradeoffs between data latency and data quality. Further, the existence of statistical breaks in the global distribution of flood wave travel time (i.e. a jagged statistical distribution) would represent preferable latencies for river-observation NRT remote sensing products. Here we present a global analysis of flood wave velocity (i.e. flow celerity) and travel time. We apply a simple kinematic wave model to a global hydrography dataset and calculate flow wave celerity and travel time during bankfull flow conditions. Bankfull flow corresponds to the condition of maximum celerity and thus we present the "worst-case scenario" minimum flow wave travel time. We conduct a similar analysis with respect to the time it takes flood waves to reach the next downstream city, as well as the next downstream reservoir. Finally, we conduct these same analyses, but with regards to the technical capabilities of the planned Surface Water and Ocean Topography (SWOT) satellite mission, which is anticipated to provide waterbody elevation and extent measurements at an unprecedented spatial and temporal resolution. We validate these results with discharge records from paired
Full Text Available In river basins with water storage facilities, the availability of regularly updated information on reservoir level and capacity is of paramount importance for the effective management of those systems. However, for the vast majority of reservoirs around the world, storage levels are either not measured or not readily available due to financial, political, or legal considerations. This paper proposes a novel approach using Landsat imagery and digital elevation models (DEMs to retrieve information on storage variations in any inaccessible region. Unlike existing approaches, the method does not require any in situ measurement and is appropriate for monitoring small, and often undocumented, irrigation reservoirs. It consists of three recovery steps: (i a 2-D dynamic classification of Landsat spectral band information to quantify the surface area of water, (ii a statistical correction of DEM data to characterize the topography of each reservoir, and (iii a 3-D reconstruction algorithm to correct for clouds and Landsat 7 Scan Line Corrector failure. The method is applied to quantify reservoir storage in the Yarmouk basin in southern Syria, where ground monitoring is impeded by the ongoing civil war. It is validated against available in situ measurements in neighbouring Jordanian reservoirs. Coefficients of determination range from 0.69 to 0.84, and the normalized root-mean-square error from 10 to 16 % for storage estimations on six Jordanian reservoirs with maximal water surface areas ranging from 0.59 to 3.79 km2.
Griesbach, J.; Wetterer, C.; Sydney, P.; Gerber, J.
Photometric processing of non-resolved Electro-Optical (EO) images has commonly required the use of dark and flat calibration frames that are obtained to correct for charge coupled device (CCD) dark (thermal) noise and CCD quantum efficiency/optical path vignetting effects respectively. It is necessary to account/calibrate for these effects so that the brightness of objects of interest (e.g. stars or resident space objects (RSOs)) may be measured in a consistent manner across the CCD field of view. Detected objects typically require further calibration using aperture photometry to compensate for sky background (shot noise). For this, annuluses are measured around each detected object whose contained pixels are used to estimate an average background level that is subtracted from the detected pixel measurements. In a new photometric calibration software tool developed for AFRL/RD, called Efficient Photometry In-Frame Calibration (EPIC), an automated background normalization technique is proposed that eliminates the requirement to capture dark and flat calibration images. The proposed technique simultaneously corrects for dark noise, shot noise, and CCD quantum efficiency/optical path vignetting effects. With this, a constant detection threshold may be applied for constant false alarm rate (CFAR) object detection without the need for aperture photometry corrections. The detected pixels may be simply summed (without further correction) for an accurate instrumental magnitude estimate. The noise distribution associated with each pixel is assumed to be sampled from a Poisson distribution. Since Poisson distributed data closely resembles Gaussian data for parameterized means greater than 10, the data may be corrected by applying bias subtraction and standard-deviation division. EPIC performs automated background normalization on rate-tracked satellite images using the following technique. A deck of approximately 50-100 images is combined by performing an independent median
Zoran, M. A.; Nicolae, D. N.; Talianu, C. L.; Ciobanu, M.; Ciuciu, J. G.
The synergistic use of multi-temporal and multi-spectral remote sensing data offers the possibility of monitoring of environment quality in the vicinity of nuclear power plants (NPP). Advanced digital processing techniques applied to several LANDSAT, MODIS and ASTER data are used to assess the extent and magnitude of radiation and non-radiation effects on the water, near field soil, vegetation and air for NPP Cernavoda , Romania . Cernavoda Unit 1 power plant, using CANDU technology, having 706.5 MW power, is successfully in operation since 1996. Cernavoda Unit 2 which is currently under construction will be operational in 2007. Thermal discharge from nuclear reactor cooling is dissipated as waste heat in Danube-Black -Sea Canal and Danube river. Water temperature distributions captured in thermal IR imagery are correlated with meteorological parameters. Additional information regarding flooding events and earthquake risks is considered . During the winter, the thermal plume is localized to an area within a few km of the power plant, and the temperature difference between the plume and non-plume areas is about 1.5 oC. During the summer and fall, there is a larger thermal plume extending 5-6 km far along Danube Black Sea Canal, and the temperature change is about 1.0 oC. Variation of surface water temperature in the thermal plume is analyzed. The strong seasonal difference in the thermal plume is related to vertical mixing of the water column in winter and to stratification in summer. Hydrodynamic simulation leads to better understanding of the mechanisms by which waste heat from NPP Cernavoda is dissipated in the environment.
Broich, M.; Tulbure, M. G.; Wijaya, A.; Weisse, M.; Stolle, F.
Deforestation and forest degradation form the 2nd largest source of anthropogenic CO2 emissions. While deforestation is being globally mapped with satellite image time series, degradation remains insufficiently quantified. Previous studies quantified degradation for small scale, local sites. A method suitable for accurate mapping across large areas has not yet been developed due to the variability of the low magnitude and short-lived degradation signal and the absence of data with suitable resolution properties. Here we use a combination of newly available streams of free optical and radar image time series acquired by NASA and ESA, and HPC-based data science algorithms to innovatively quantify degradation consistently across Southeast Asia (SEA). We used Sentinel1 c-band radar data and NASA's new Harmonized Landsat8 (L8) Sentinel2 (S2) product (HLS) for cloud free optical images. Our results show that dense time series of cloud penetrating Sentinel 1 c-band radar can provide degradation alarm flags, while the HLS product of cloud-free optical images can unambiguously confirm degradation alarms. The detectability of degradation differed across SEA. In the seasonal forest of continental SEA the reliability of our radar-based alarm flags increased as the variability in landscape moisture decreases in the dry season. We reliably confirmed alarms with optical image time series during the late dry season, where degradation in open canopy forests becomes detectable once the undergrowth vegetation has died down. Conversely, in insular SEA landscape moisture is low, the radar time series generated degradation alarms flags with moderate to high reliability throughout the year, further confirmed with the HLS product. Based on the HLS product we can now confirm degradation within time series provides better results than either one on its own. Our results provide significant information with application for carbon trading policy and land management.
Udelhoven, Thomas; Schlerf, Martin; Segl, Karl; Mallick, Kaniska; Bossung, Christian; Retzlaff, Rebecca; Rock, Gilles; Fischer, Peter; Müller, Andreas; Storch, Tobias; Eisele, Andreas; Weise, Dennis; Hupfer, Werner; Knigge, Thiemo
This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1-5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2-12.5 µm (instrument NEDT 0.05 K-0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0-10.25 µm and 10.25-12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1-3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.
Full Text Available This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping. The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir. At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month. To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1 a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K and a ground sampling distance (GSD of 60 m, and (2 a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days to combine data from the visible and near infrared (VNIR, the shortwave infrared (SWIR and TIR spectral regions and to refine parameter retrieval.
Karale, Yogita; Mohite, Jayant; Jagyasi, Bhushan
In this paper, we envision the use of satellite images coupled with GIS to obtain location specific crop type information in order to disseminate crop specific advises to the farmers. In our ongoing mKRISHI R project, the accurate information about the field level crop type and acreage will help in the agro-advisory services and supply chain planning and management. The key contribution of this paper is the field level crop classification using multi temporal images of Landsat-8 acquired during November 2013 to April 2014. The study area chosen is Vani, Maharashtra, India, from where the field level ground truth information for various crops such as grape, wheat, onion, soybean, tomato, along with fodder and fallow fields has been collected using the mobile application. The ground truth information includes crop type, crop stage and GPS location for 104 farms in the study area with approximate area of 42 hectares. The seven multi-temporal images of the Landsat-8 were used to compute the vegetation indices namely: Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Difference Vegetation Index (DVI) for the study area. The vegetation indices values of the pixels within a field were then averaged to obtain the field level vegetation indices. For each crop, binary classification has been carried out using the feed forward neural network operating on the field level vegetation indices. The classification accuracy for the individual crop was in the range of 74.5% to 97.5% and the overall classification accuracy was found to be 88.49%.
Gogoi, Mukunda M.; Babu, S. Suresh
In view of the increasing anthropogenic presence and influence of aerosols in the northern polar regions, long-term continuous measurements of aerosol optical parameters have been investigated over the Svalbard region of Norwegian Arctic (Ny-Ålesund, 79°N, 12°E, 8 m ASL). This study has shown a consistent enhancement in the aerosol scattering and absorption coefficients during spring. The relative dominance of absorbing aerosols is more near the surface (lower single scattering albedo), compared to that at the higher altitude. This is indicative of the presence of local anthropogenic activities. In addition, long-range transported biomass burning aerosols (inferred from the spectral variation of absorption coefficient) also contribute significantly to the higher aerosol absorption in the Arctic spring. Aerosol optical depth (AOD) estimates from ground based Microtop sun-photometer measurements reveals that the columnar abundance of aerosols reaches the peak during spring season. Comparison of AODs between ground based and satellite remote sensing indicates that deep blue algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over Arctic snow surfaces overestimate the columnar AOD.
Zhao, Y.; Lobell, D. B.; Chen, X.
A large gap between maize yields on average farmers' fields and the highest yields achieved by either experiment or farmers is typical throughout the developing world, including in the North China Plain (NCP). This maize yield gap as identified by previous studies indicates large opportunities for raising yield by improving agronomy. Quzhou county is typical of the winter-wheat summer-maize system in NCP where the average plot size is as small as 0.25 hectares. To analyze this cropping system amidst the challenge of substantial heterogeneity, we identified fields that were either persistently higher or lower yielding according to the remote sensing yield estimates, and then conducted detailed field surveys. We found irrigation facility to be a major constraint to yield both in terms of irrigation water quality and farmers' access to wells. In total, improving the access to unsalty water would be associated with a 0.32t/ha (4.2%) increase in multi-year average yield. In addition, farmers' method of choosing cultivar, which likely relates to their overall knowledge level, significantly explained yield variation. In particular, those choosing cultivars according to technician advice, personal experiences and high yielding neighbors' advice had on average higher yield than farmers that either followed seed sellers' advice or collectively purchased seeds. Overall, the study presents a generalizable methodology of assessing yield gap as well as its persistent factors using a combination of satellite and survey data.
The development of better agricultural monitoring capabilities is clearly considered as a critical step for strengthening food production information and market transparency thanks to timely information about crop status, crop area and yield forecasts. The documentation of global production will contribute to tackle price volatility by allowing local, national and international operators to make decisions and anticipate market trends with reduced uncertainty. Several operational agricultural monitoring systems are currently operating at national and international scales. Most are based on the methods derived from the pioneering experiences completed some decades ago, and use remote sensing to qualitatively compare one year to the others to estimate the risks of deviation from a normal year. The GEO Agricultural Monitoring Community of Practice described the current monitoring capabilities at the national and global levels. An overall diagram summarized the diverse relationships between satellite EO and agriculture information. There is now a large gap between the current operational large scale systems and the scientific state of the art in crop remote sensing, probably because the latter mainly focused on local studies. The poor availability of suitable in-situ and satellite data over extended areas hampers large scale demonstrations preventing the much needed up scaling research effort. For the cropland extent, this paper reports a recent research achievement using the full ENVISAT MERIS 300 m archive in the context of the ESA Climate Change Initiative. A flexible combination of classification methods depending to the region of the world allows mapping the land cover as well as the global croplands at 300 m for the period 2008 2012. This wall to wall product is then compared with regards to the FP 7-Geoland 2 results obtained using as Landsat-based sampling strategy over the IGADD countries. On the other hand, the vegetation indices and the biophysical variables
Remote Sensing Editorial Office
Full Text Available Due to a technical error at the Editorial Office, Figure 8 of manuscript  is missing in the published paper. The correct version of the figure is reproduced below. We apologize for any inconvenience caused to authors or readers of Remote Sensing.[...
Full Text Available The upper ranges of the northern Andes are characterized by unique Neotropical, high altitude ecosystems known as paramos. These tundra-like grasslands are widely recognized by the scientific community for their biodiversity and their important ecosystem services for the local human population. Despite their remoteness, limited accessibility for humans and waterlogged soils, paramos are highly flammable ecosystems. They are constantly under the influence of seasonal biomass burning mostly caused by humans. Nevertheless, little is known about the spatial extent of these fires, their regime and the resulting ecological impacts. This paper presents a thorough mapping and analysis of the fires in one of the world’s largest paramo, namely the “Complejo de Páramos” of Cruz Verde-Sumapaz in the Eastern mountain range of the Andes (Colombia. Landsat TM/ETM+ and MODIS imagery from 2001 to 2013 was used to map and analyze the spatial distribution of fires and their intra- and inter-annual variability. Moreover, a logistic regression model analysis was undertaken to test the hypothesis that the dynamics of the paramo fires can be related to human pressures. The resulting map shows that the burned paramo areas account for 57,179.8 hectares, of which 50% (28,604.3 hectares are located within the Sumapaz National Park. The findings show that the fire season mainly occurs from January to March. The accuracy assessment carried out using a confusion matrix based on 20 reference burned areas shows values of 90.1% (producer accuracy for the mapped burned areas with a Kappa Index of Agreement (KIA of 0.746. The results of the logistic regression model suggest a significant predictive relevance of the variables road distance (0.55 ROC (receiver operating characteristic and slope gradient (0.53 ROC, indicating that the higher the probability of fire occurrence, the smaller the distance to the road and the higher the probability of more gentle slopes. The paper
Mitchell, D. L.; Garnier, A.; Mejia, J.; Avery, M. A.; Erfani, E.
To date, it is not clear whether the climate intervention method known as cirrus cloud thinning (CCT) can be viable since it requires cirrus clouds to form through homogeneous ice nucleation (henceforth hom) and some recent GCM studies predict cirrus are formed primarily through heterogeneous ice nucleation (henceforth het). A new CALIPSO infrared retrieval method has been developed for single-layer cirrus cloud that measures the temperature dependence of their layer-averaged number concentration N, effective diameter De and ice water content for optical depths (OD) between 0.3 and 3.0. Based on N, the prevailing ice nucleation mechanism (hom or het) can be estimated as a function of temperature, season, latitude and surface type. These satellite results indicate that seeding cirrus clouds at high latitudes during winter may produce significant global surface cooling. This is because hom often appears to dominate over land during winter north of 30°N latitude while the same appears true for most of the Southern Hemisphere (south of 30°S) during all seasons. Moreover, the sampled cirrus cloud frequency of occurrence in the Arctic is at least twice as large during winter relative to other seasons, while frequency of occurrence in the Antarctic peaks in the spring and is second-highest during winter. During Arctic winter, a combination of frequent hom cirrus, maximum cirrus coverage and an extreme or absent sun angle produces the maximum seasonal cirrus net radiative forcing (warming). Thus a reduction in OD and coverage (via CCT) for these cirrus clouds could yield a significant net cooling effect. From these CALIPSO retrievals, De-T relationships are generated as a function of season, latitude and surface type (land vs. ocean). These will be used in CAM5 to estimate De and the ice fall speed, from which the cirrus radiative forcing will be estimated during winter north of 30°latitude, where hom cirrus are common. Another CAM5 simulation will replace the hom
Hsu, N. Christina; Gautam, Ritesh
The Himalayan glaciers and snowpacks play an important role in the hydrological cycle over Asia. The seasonal snow melt from the Himalayan glaciers and snowpacks is one of the key elements to the livelihood of the downstream densely populated regions of South Asia. During the pre-monsoon season (April-May-June), South Asia not only experiences the reversal of the regional meridional tropospheric temperature gradient (i.e., the onset of the summer monsoon), but also is being bombarded by dry westerly airmass that transports mineral dust from various Southwest Asian desert and arid regions into the Indo-Gangetic Plains in northern India. Mixed with heavy anthropogenic pollution, mineral dust constitutes the bulk of regional aerosol loading and forms an extensive and vertically extended brown haze lapping against the southern slopes of the Himalayas. Episodic dust plumes are advected over the Himalayas, and are discernible in satellite imagery, resulting in dust-capped snow surface. Motivated by the potential implications of accelerated snowmelt, we examine the changes in radiative energetics induced by aerosol transport over the Himalayan snow cover by utilizing space borne observations. Our objective lies in the investigation of potential impacts of aerosol solar absorption on the Top-of-Atmosphere (TOA) spectral reflectivity and the broadband albedo, and hence the accelerated snowmelt, particularly in the western Himalayas. Lambertian Equivalent Reflectivity (LER) in the visible and near-infrared wavelengths, derived from Moderate Resolution Imaging Spectroradiometer radiances, is used to generate statistics for determining perturbation caused due to dust layer over snow surface in over ten years of continuous observations. Case studies indicate significant reduction of LER ranging from 5 to 8% in the 412-860nm spectra. Broadband flux observations, from the Clouds and the Earth's Radiant Energy System, are also used to investigate changes in shortwave TOA flux over
Yuichi Sarusawa; Kohei Arai
Regression analysis based method for turbidity and ocean current velocity estimation with remote sensing satellite data is proposed. Through regressive analysis with MODIS data and measured data of turbidity and ocean current velocity, regressive equation which allows estimation of turbidity and ocean current velocity is obtained. With the regressive equation as well as long term MODIS data, turbidity and ocean current velocity trends in Ariake Sea area are clarified. It is also confirmed tha...
Kahn, Ralph A.
The organizers of the National Academy of Sciences Arthur M. Sackler Colloquia Series on Improving Our Fundamental Understanding of the Role of Aerosol-Cloud Interactions in the Climate System would like to post Ralph Kahn's presentation entitled Remote Sensing of Aerosols from Satellites: Why has it been so difficult to quantify aerosol-cloud interactions for climate assessment, and how can we make progress? to their public website.
Marcos J. Montes
Full Text Available Studies of phytoplankton ecology in Monterey Bay, CA, USA, using the Hyperspectral Imager for the Coastal Ocean (HICO and other satellite remote sensing and in-situ observations, were presented in . [...
Emery, Charlotte Marie; Paris, Adrien; Biancamaria, Sylvain; Boone, Aaron; Calmant, Stéphane; Garambois, Pierre-André; Santos da Silva, Joecila
Land surface models (LSMs) are widely used to study the continental part of the water cycle. However, even though their accuracy is increasing, inherent model uncertainties can not be avoided. In the meantime, remotely sensed observations of the continental water cycle variables such as soil moisture, lakes and river elevations are more frequent and accurate. Therefore, those two different types of information can be combined, using data assimilation techniques to reduce a model's uncertainties in its state variables or/and in its input parameters. The objective of this study is to present a data assimilation platform that assimilates into the large-scale ISBA-CTRIP LSM a punctual river discharge product, derived from ENVISAT nadir altimeter water elevation measurements and rating curves, over the whole Amazon basin. To deal with the scale difference between the model and the observation, the study also presents an initial development for a localization treatment that allows one to limit the impact of observations to areas close to the observation and in the same hydrological network. This assimilation platform is based on the ensemble Kalman filter and can correct either the CTRIP river water storage or the discharge. Root mean square error (RMSE) compared to gauge discharges is globally reduced until 21 % and at Óbidos, near the outlet, RMSE is reduced by up to 52 % compared to ENVISAT-based discharge. Finally, it is shown that localization improves results along the main tributaries.
Full Text Available An accurate and comprehensive representation of an observation task is a prerequisite in disaster monitoring to achieve reliable sensor observation planning. However, the extant disaster event or task information models do not fully satisfy the observation requirements for the accurate and efficient planning of remote-sensing satellite sensors. By considering the modeling requirements for a disaster observation task, we propose an observation task chain (OTChain representation model that includes four basic OTChain segments and eight-tuple observation task metadata description structures. A prototype system, namely OTChainManager, is implemented to provide functions for modeling, managing, querying, and visualizing observation tasks. In the case of flood water monitoring, we use a flood remote-sensing satellite sensor observation task for the experiment. The results show that the proposed OTChain representation model can be used in modeling process-owned flood disaster observation tasks. By querying and visualizing the flood observation task instances in the Jinsha River Basin, the proposed model can effectively express observation task processes, represent personalized observation constraints, and plan global remote-sensing satellite sensor observations. Compared with typical observation task information models or engines, the proposed OTChain representation model satisfies the information demands of the OTChain and its processes as well as impels the development of a long time-series sensor observation scheme.
Wells, G. L.; Tapley, B. D.; Bettadpur, S. V.; Howard, T.; Porter, B.; Smith, S.; Teng, L.; Tapley, C.
The effective use of remote sensing products as guidance to emergency managers and first responders during field operations requires close coordination and communication with state-level decision makers, incident commanders and the leaders of individual strike teams. Information must be tailored to meet the needs of different emergency support functions and must contain current (ideally near real-time) data delivered in standard formats in time to influence decisions made under rapidly changing conditions. Since 2003, a representative of the University of Texas Center for Space Research (CSR) has served as a member of the Governor's Emergency Management Council and has directed the flow of information from remote sensing observations and high performance computing modeling and simulations to the Texas Division of Emergency Management in the State Operations Center. The CSR team has supported response and recovery missions resulting from hurricanes, tornadoes, flash floods, wildfires, oil spills and other natural and man-made disasters in Texas and surrounding states. Through web mapping services, state emergency managers and field teams have received threat model forecasts, real-time vehicle tracking displays and imagery to support search-and-clear operations before hurricane landfall, search-and-rescue missions following floods, tactical wildfire suppression, pollution monitoring and hazardous materials detection. Data servers provide near real-time satellite imagery collected by CSR's direct broadcast receiving system and post data products delivered during activations of the United Nations International Charter on Space and Major Disasters. In the aftermath of large-scale events, CSR is charged with tasking state aviation resources, including the Air National Guard and Texas Civil Air Patrol, to acquire geolocated aerial photography of the affected region for wide area damage assessment. A data archive for each disaster is available online for years following
Akanda, A. S.; Serman, E. A.; Jutla, A.
focuses on stretching this understanding to water and health implications in this growing megacity and adjoining slum areas, and how satellite remote sensing data products and derived knowledge can inform urban planning, water management, and public health sectors to adapt to these climatic and anthropogenic changes for the benefit of societies.
Tariq, Salman; Zia, ul-Haq; Ali, Muhammad
Due to increase in population and economic development, the mega-cities are facing increased haze events which are causing important effects on the regional environment and climate. In order to understand these effects, we require an in-depth knowledge of optical and physical properties of aerosols in intense haze conditions. In this paper an effort has been made to analyze the microphysical and optical properties of aerosols during intense haze event over mega-city of Lahore by using remote sensing data obtained from satellites (Terra/Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)) and ground based instrument (AErosol RObotic NETwork (AERONET)) during 6-14 October 2013. The instantaneous highest value of Aerosol Optical Depth (AOD) is observed to be 3.70 on 9 October 2013 followed by 3.12 on 8 October 2013. The primary cause of such high values is large scale crop residue burning and urban-industrial emissions in the study region. AERONET observations show daily mean AOD of 2.36 which is eight times higher than the observed values on normal day. The observed fine mode volume concentration is more than 1.5 times greater than the coarse mode volume concentration on the high aerosol burden day. We also find high values (~0.95) of Single Scattering Albedo (SSA) on 9 October 2013. Scatter-plot between AOD (500 nm) and Angstrom exponent (440-870 nm) reveals that biomass burning/urban-industrial aerosols are the dominant aerosol type on the heavy aerosol loading day over Lahore. MODIS fire activity image suggests that the areas in the southeast of Lahore across the border with India are dominated by biomass burning activities. A Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model backward trajectory showed that the winds at 1000 m above the ground are responsible for transport from southeast region of biomass burning to Lahore. CALIPSO derived sub-types of
Lee, Zhongping; Shang, Shaoling; Hu, Chuanmin; Zibordi, Giuseppe
Using 901 remote-sensing reflectance spectra (R(rs)(λ), sr⁻¹, λ from 400 to 700 nm with a 5 nm resolution), we evaluated the correlations of R(rs)(λ) between neighboring spectral bands in order to characterize (1) the spectral interdependence of R(rs)(λ) at different bands and (2) to what extent hyperspectral R(rs)(λ) can be reconstructed from multiband measurements. The 901 R(rs) spectra were measured over a wide variety of aquatic environments in which water color varied from oceanic blue to coastal green or brown, with chlorophyll-a concentrations ranging from ~0.02 to >100 mg m⁻³, bottom depths from ~1 m to >1000 m, and bottom substrates including sand, coral reef, and seagrass. The correlation coefficient of R(rs)(λ) between neighboring bands at center wavelengths λ(k) and λ(l), r(Δλ)(λ(k), λ(l)), was evaluated systematically, with the spectral gap (Δλ=λ(l)-λ(k)) changing between 5, 10, 15, 20, 25, and 30 nm, respectively. It was found that r(Δλ) decreased with increasing Δλ, but remained >0.97 for Δλ≤20 nm for all spectral bands. Further, using 15 spectral bands between 400 and 710 nm, we reconstructed, via multivariant linear regression, hyperspectral R(rs)(λ) (from 400 to 700 nm with a 5 nm resolution). The percentage difference between measured and reconstructed R(rs) for each band in the 400-700 nm range was generally less than 1%, with a correlation coefficient close to 1.0. The mean absolute error between measured and reconstructed R(rs) was about 0.00002 sr⁻¹ for each band, which is significantly smaller than the R(rs) uncertainties from all past and current ocean color satellite radiometric products. These results echo findings of earlier studies that R(rs) measurements at ~15 spectral bands in the visible domain can provide nearly identical spectral information as with hyperspectral (contiguous bands at 5 nm spectral resolution) measurements. Such results provide insights for data
Hansell, Richard Allen, Jr.
The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud
Roupioz, L; Nerry, F; Jia, L; Menenti, M
The Qinghai-Tibetan Plateau is characterised by a very strong relief which affects albedo retrieval from satellite data. The objective of this study is to highlight the effects of sub-pixel topography and to account for those effects when retrieving land surface albedo from geostationary satellite FengYun-2D (FY-2D) data with 1.25km spatial resolution using the high spatial resolution (30 m) data of the Digital Elevation Model (DEM) from ASTER. The methodology integrates the effects of sub-pixel topography on the estimation of the total irradiance received at the surface, allowing the computation of the topographically corrected surface reflectance. Furthermore, surface albedo is estimated by applying the parametric BRDF (Bidirectional Reflectance Distribution Function) model called RPV (Rahman-Pinty-Verstraete) to the terrain corrected surface reflectance. The results, evaluated against ground measurements collected over several experimental sites on the Qinghai-Tibetan Plateau, document the advantage of integrating the sub-pixel topography effects in the land surface reflectance at 1km resolution to estimate the land surface albedo. The results obtained after using sub-pixel topographic correction are compared with the ones obtained after using pixel level topographic correction. The preliminary results imply that, in highly rugged terrain, the sub-pixel topography correction method gives more accurate results. The pixel level correction tends to overestimate surface albedo
Raju, P. L. N.; Gupta, P. K.; Roy, P. S.
Geoinformatics is a highly specialized discipline that deals with Remote Sensing, Geographical Information System (GIS), Global Positioning System (GPS) and field surveys for assessing, quantification, development and management of resources, planning and infrastructure development, utility services etc. Indian Institute of Remote Sensing (IIRS), a premier institute and one of its kinds has played a key role for capacity Building in this specialized area since its inception in 1966. Realizing the large demand, IIRS has started outreach program in basics of Remote Sensing, GIS and GPS for universities and institutions. EDUSAT (Educational Satellite) is the communication satellite built and launched by ISRO in 2004 exclusively for serving the educational sector to meet the demand for an interactive satellite based distance education system for the country. IIRS has used EDUSAT (shifted to INSAT 4 CR recently due to termination of services from EDUSAT) for its distance learning program to impart basic training in Remote Sensing, GIS and GPS, catering to the universities spread across India. The EDUSAT based training is following similar to e-learning method but has advantage of live interaction sessions between teacher and the students when the lecture is delivered using EDUSAT satellite communication. Because of its good quality reception the interactions are not constrained due to bandwidth problems of Internet. National Natural Resource Management System, Department of Space, Government of India, under Standing Committee in Training and Technology funded this unique program to conduct the basic training in Geoinformatics. IIRS conducts 6 weeks basic training course on "Remote Sensing, GIS and GPS" regularly since the year 2007. The course duration is spread over the period of 3 months beginning with the start of the academic year (1st semester) i.e., July to December every year, for university students. IIRS has utilized EDUSAT satellite for conducting 4 six weeks
We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the ...
Cappelle, J.; Iverson, S.A.; Takekawa, John Y.; Newman, S.H.; Dodman, T.; Gaidet, N.
We provide recommendations for implementing telemetry studies on waterfowl on the basis of our experience in a tracking study conducted in three countries of sub-Saharan Africa. The aim of the study was to document movements by duck species identified as priority candidates for the potential spread of avian influenza. Our study design included both captive and field test components on four wild duck species (Garganey, Comb Duck, White-faced Duck and Fulvous Duck). We used our location data to evaluate marking success and determine when signal loss occurred. The captive study of eight ducks marked with non-working transmitters in a zoo in Montpellier, France, prior to fieldwork showed no evidence of adverse effects, and the harness design appeared to work well. The field study in Malawi, Nigeria and Mali started in 2007 on 2 February, 6 February and 14 February, and ended on 22 November 2007 (288 d), 20 January 2010 (1 079 d), and 3 November 2008 (628 d), respectively. The field study indicated that 38 of 47 (81%) of the platform transmitter terminals (PTTs) kept transmitting after initial deployment, and the transmitters provided 15 576 locations. Signal loss during the field study was attributed to three main causes: PTT loss, PTT failure and mortality (natural, human-caused and PTT-related). The PTT signal quality varied by geographic region, and interference caused signal loss in the Mediterranean Sea region. We recommend careful attention at the beginning of the study to determine the optimum timing of transmitter deployment and the number of transmitters to be deployed per species. These sample sizes should be calculated by taking into account region-specific causes of signal loss to ensure research objectives are met. These recommendations should be useful for researchers undertaking a satellite tracking program, especially when working in remote areas of Africa where logistics are difficult or with poorly-known species. ?? NISC (Pty) Ltd.
Arabsahebi, Reza; Voosoghi, Behzad; Tourian, Mohammad J.
Tropospheric correction is one of the most important corrections in satellite altimetry measurements. Tropospheric wet and dry path delays have strong dependence on temperature, pressure and humidity. Tropospheric layer has particularly high variability over coastal regions due to humidity, wind and temperature gradients. Depending on the extent of water body and wind conditions over an inland water, Wet Tropospheric Correction (WTC) is within the ranges from a few centimeters to tens of centimeters. Therefore, an extra care is needed to estimate tropospheric corrections on the altimetric measurements over inland waters. This study assesses the role of tropospheric correction on the altimetric measurements over the Urmia Lake in Iran. For this purpose, four types of tropospheric corrections have been used: (i) microwave radiometer (MWR) observations, (ii) tropospheric corrections computed from meteorological models, (iii) GPS observations and (iv) synoptic station data. They have been applied to Jason-2 track no. 133 and SARAL/AltiKa track no. 741 and 356 corresponding to 117-153 and the 23-34 cycles, respectively. In addition, the corresponding measurements of PISTACH and PEACHI, include new retracking method and an innovative wet tropospheric correction, have also been used. Our results show that GPS observation leads to the most accurate tropospheric correction. The results obtained from the PISTACH and PEACHI projects confirm those obtained with the standard SGDR, i.e., the role of GPS in improving the tropospheric corrections. It is inferred that the MWR data from Jason-2 mission is appropriate for the tropospheric corrections, however the SARAL/AltiKa one is not proper because Jason-2 possesses an enhanced WTC near the coast. Furthermore, virtual stations are defined for assessment of the results in terms of time series of Water Level Height (WLH). The results show that GPS tropospheric corrections lead to the most accurate WLH estimation for the selected
Allan C. Just
Full Text Available Satellite-derived estimates of aerosol optical depth (AOD are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systematically used to address the measurement error in AOD. We compare three machine-learning methods: random forests, gradient boosting, and extreme gradient boosting (XGBoost to characterize and correct measurement error in the Multi-Angle Implementation of Atmospheric Correction (MAIAC 1 × 1 km AOD product for Aqua and Terra satellites across the Northeastern/Mid-Atlantic USA versus collocated measures from 79 ground-based AERONET stations over 14 years. Models included 52 quality control, land use, meteorology, and spatially-derived features. Variable importance measures suggest relative azimuth, AOD uncertainty, and the AOD difference in 30–210 km moving windows are among the most important features for predicting measurement error. XGBoost outperformed the other machine-learning approaches, decreasing the root mean squared error in withheld testing data by 43% and 44% for Aqua and Terra. After correction using XGBoost, the correlation of collocated AOD and daily PM2.5 monitors across the region increased by 10 and 9 percentage points for Aqua and Terra. We demonstrate how machine learning with quality control and spatial features substantially improves satellite-derived AOD products for air pollution modeling.
Schroeder, R; Rawlins, M A; McDonald, K C; Podest, E; Zimmermann, R; Kueppers, M
Wetlands are not only primary producers of atmospheric greenhouse gases but also possess unique features that are favourable for application of satellite microwave remote sensing to monitoring their status and trend. In this study we apply combined passive and active microwave remote sensing data sets from the NASA sensors AMSR-E and QuikSCAT to map surface water dynamics over Northern Eurasia. We demonstrate our method on the evolution of large wetland complexes for two consecutive years from January 2006 to December 2007. We apply river discharge measurements from the Ob River along with land surface runoff simulations derived from the Pan-Arctic Water Balance Model during and after snowmelt in 2006 and 2007 to interpret the abundance of widespread flooding along the River Ob in early summer of 2007 observed in the remote sensing products. The coarse-resolution, 25 km, surface water product is compared to a high-resolution, 30 m, inundation map derived from ALOS PALSAR (Advanced Land Observation Satellite phased array L-band synthetic aperture radar) imagery acquired for 11 July 2006, and extending along a transect in the central Western Siberian Plain. We found that the surface water fraction derived from the combined AMSR-E/QuikSCAT data sets closely tracks the inundation mapped using higher-resolution ALOS PALSAR data.
The glaciers in western Karakoram are important for freshwater supply in the rivers of Pakistan. Global warming influences the future water supply from glaciers. In order to study the hydrological conditions and possible impacts of climate change, runoff simulations are performed for the Hunza basin. The hydrological modelling system SRM (Snowmelt Runoff Model) is customized and applied to the Hunza basin. Various data obtained from satellite remote sensing imagery and meteorological stations in the study area are processed, prepared and used as input to SRM. For runoff simulations the basin is divided into five sub-basins. The (sub-) basins are defined by the hydrological response units (HRU) based on the elevation zones and land-cover types. The spatially distributed data are aggregated HRU-wise as input for the model simulations. The energy available for snow and glacier melt is parameterized in SRM by degree day factors which are defined separately for seasonal snow, ice and debris covered glaciers. The model is calibrated for the Hunza basin using the meteorological and remote sensing data from years 2002 and 2003. The daily runoff is simulated and compared with the measured discharge data obtained from the power company. The Nash-Sutcliffe correlation coefficient of simulated versus measured runoff data is 0.87 for year 2002 and 0.96 for year 2003 which indicates a good agreement. An estimation of mass balance of Baltoro glacier is made using the meteorological data from Shigar station applying the hydrological method to estimate accumulation and melt. Based on these data is found that Baltoro glacier has slightly negative mass balance. The ablation rates of debris covered parts of Baltoro glacier at 4150 m elevation are estimated to be between 3 and 4 cm per day. However, the uncertainty in mass balance modelling is high due to poor knowledge of accumulation inferred by spatial extrapolation from station data.Keeping the glacier area unchanged, for the 2002
Vrancken, D.; Paijmans, B.; Fussen, D.; Neefs, E.; Loodts, N.; Dekemper, E.; Vahellemont, F.; Devos, L.; Moelans, W.; Nevejans, D.; Schroeven-Deceuninck, H.; Bernaerts, D.; Zender, J.
There is more and more interest in the understanding and the monitoring of the physics and chemistry of the Earth's atmosphere and its impact on the climate change. Currently a significantly high number of sounders provide the required data to monitor the changes in atmosphere composition, but a dramatic drop in operational atmosphere monitoring missions is expected around 2010. This drop is mainly visible in sounders capable of a high vertical resolution. Currently, instruments on ENVISAT and METOP provide relevant data but this is envisaged to be insufficient to ensure full spatial and temporal coverage and redundancy in the measurement data set. ALTIUS (Atmospheric Limb Tracker for the Investigation of the Upcoming Stratosphere) is a remote sounding experiment proposed by the Belgian Institute for Space Aeronomy (BIRA/IASB) for which a feasibility study was initiated with BELSPO (Belgian Science Policy) and ESA support. The main objective of this study phase was to establish a mission concept, to define the required payload and to establish a satellite platform design. The study was led by the BIRA/IASB team and performed in close collaboration with OIP (payload developer) and Verhaert Space (spacecraft developer). The mission scenario includes bright limb observations in basically all directions, solar occultations around the terminator passages and star occultations during eclipse. These observation modes allow imaging the atmosphere with a high vertical resolution. The spacecraft will be operated in a 10:00 sun-synchronous orbit at an altitude of 695 km, allowing a 3-day revisit time. The envisaged payload for the ALTIUS mission is an imaging spectrometer, observing in the UV, the VIS and the NIR spectral ranges. For each spectral range, an AOTF (Acousto-Optical Tunable Filter) will permit to perform observations of selectable small wavelength domains. A typical set of 10 wavelengths will be recorded within 1 second. The different operational modes impose a
Remote Sensing Editorial Office
Full Text Available Due to an error on our part, the pagination and the doi number of this manuscript  were missing during updating. The correct pagination is 9600–9652, and the doi number is 10.3390/rs6109600. Here is the correct version:[...
Full Text Available In this paper we review the status of new applications research of the Japanese Aerospace Exploration Agency (JAXA for global health promotion using information derived from Earth observation data by satellites in cooperation with inter-disciplinary collaborators. Current research effort at JAXA to promote global public health is focused primarily on the use of remote sensing to address two themes: (i prediction models for malaria and cholera in Kenya, Africa; and (ii air quality assessment of small, particulate matter (PM2.5, nitrogen dioxide (NO2 and ozone (O3. Respiratory and cardivascular diseases constitute cross-boundary public health risk issues on a global scale. The authors report here on results of current of a collaborative research to call attention to the need to take preventive measures against threats to public health using newly arising remote sensing information from space.
Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael
We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEO-CAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O 2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the
Dong S. Ko
Full Text Available We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM were used for the salinity flux, and the diffuse attenuation coefficient (Kd from Moderate Resolution Imaging Spectroradiometer (MODIS were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability was missed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the Louisiana shelf, an important management metric, was substantially improved in comparison to observed hypoxic area by including the satellite data.
Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve
Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.
This report describes an approach for automatic feature detection from fusion of remote sensing imagery using a combination of neural network architecture and the Dempster-Shafer (DS) theory of evidence...
National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....
development and operationalization of new spill response remote sensing tools must precede the next major oil spill. © 2012 Elsevier Inc. All rights reserved...Environment 124 (2012) 185–209 sensing oil spill impacts, and 5) a final discussion. Each section presents background, available remote sensing tools , and...cialized DaVinci command-line software (Clark et al., 2003) then mapped oil slick volume (Clark et al., 2010) in each AVIRIS pixel by identifying the
Panda, Sudhanshu S.; Rao, Mahesh N.; Thenkabail, Prasad S.; Fitzerald, James E.
The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.
Dong S. Ko; Richard W. Gould; Bradley Penta; John C. Lehrter
We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer...
Full Text Available As China is suffering from severe fine particle pollution from dense industrialization and urbanization, satellite-derived aerosol optical depth (AOD has been widely used for estimating particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5. However, the correlation between satellite AOD and ground-level PM2.5 could be influenced by aerosol vertical distribution, as satellite AOD represents the entire column, rather than just ground-level concentration. Here, a new column-to-surface vertical correction scheme is proposed to improve separation of the near-surface and elevated aerosol layers, based on the ratio of the integrated extinction coefficient within 200–500 m above ground level (AGL, using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP aerosol profile products. There are distinct differences in climate, meteorology, terrain, and aerosol transmission throughout China, so comparisons between vertical correction via CALIOP ratio and planetary boundary layer height (PBLH were conducted in different regions from 2014 to 2015, combined with the original Pearson coefficient between satellite AOD and ground-level PM2.5 for reference. Furthermore, the best vertical correction scheme was suggested for different regions to achieve optimal correlation with PM2.5, based on the analysis and discussion of regional and seasonal characteristics of aerosol vertical distribution. According to our results and discussions, vertical correction via PBLH is recommended in northwestern China, where the PBLH varies dramatically, stretching or compressing the surface aerosol layer; vertical correction via the CALIOP ratio is recommended in northeastern China, southwestern China, Central China (excluding summer, North China Plain (excluding Beijing, and the spring in the southeast coast, areas that are susceptible to exogenous aerosols and exhibit the elevated aerosol layer; and original AOD without vertical correction is
A. Beiranvand Pour
Full Text Available The Bentong-Raub Suture Zone (BRSZ of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.
Yang, Yuan-Zheng; Chang, Yu; Hu, Yuan-Man; Liu, Miao; Li, Yue-Hui
To timely and accurately acquire the spatial distribution pattern of wetlands is of significance for the dynamic monitoring, conservation, and sustainable utilization of wetlands. The small remote sensing satellite constellations A/B stars (HJ-1A/1B stars) for environmental hazards were launched by China for monitoring terrestrial resources, which could provide a new data source of remote sensing image acquisition for retrieving wetland types. Taking Liaohe Delta as a case, this paper compared the accuracy of wetland classification map and the area of each wetland type retrieved from CCD data (HJ CCD data) and TM5 data, and validated and explored the applicability and the applied potential of HJ CCD data in wetland resources dynamic monitoring. The results showed that HJ CCD data could completely replace Landsat TM5 data in feature extraction and remote sensing classification. In real-time monitoring, due to its 2 days of data acquisition cycle, HJ CCD data had the priority to Landsat TM5 data (16 days of data acquisition cycle).
Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng
The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.
Full Text Available The present study focuses on the unprecedented flood situation captured through multi-temporal satellite images, witnessed along the Ganga River in Uttar Pradesh during September 2010. At three gauge stations (Kannauj, Ankinghat and Kanpur, river water level exceeded the previous high-flood level attained by river more than a decade ago. The present communication with the aid of pre- and post-flood satellite images, coupled with hydrological (river water level and meteorological (rainfall data, explains about the unprecedented flood situation. In the latter part of the study, a novel and cost-effective method for building a library of flood inundation extents based on historical satellite data analysis and tagging the inundation layer with observed water level is demonstrated. During flood season, based on the forecasted water level, the library can be accessed to fetch the spatial inundation layer corresponding to the forecasted stage and anticipate in advance, likely spatial inundation pattern and submergence of villages and hence in alerting the habitation at risk. This method can be helpful in anticipating the areas to be affected in situations where satellite images cannot be effectively utilized due to cloud cover and also for providing information about the areas being partially covered in satellite data.
Minnis, Patrick [NASA Langley Research Center, Hampton, VA
During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.
Balch, William; Evans, Robert; Brown, Jim; Feldman, Gene; Mcclain, Charles; Esaias, Wayne
Global pigment and primary productivity algorithms based on a new data compilation of over 12,000 stations occupied mostly in the Northern Hemisphere, from the late 1950s to 1988, were tested. The results showed high variability of the fraction of total pigment contributed by chlorophyll, which is required for subsequent predictions of primary productivity. Two models, which predict pigment concentration normalized to an attenuation length of euphotic depth, were checked against 2,800 vertical profiles of pigments. Phaeopigments consistently showed maxima at about one optical depth below the chlorophyll maxima. CZCS data coincident with the sea truth data were also checked. A regression of satellite-derived pigment vs ship-derived pigment had a coefficient of determination. The satellite underestimated the true pigment concentration in mesotrophic and oligotrophic waters and overestimated the pigment concentration in eutrophic waters. The error in the satellite estimate showed no trends with time between 1978 and 1986.
Fowler, Laura D.; Wielicki, Bruce A.; Randall, David A.; Branson, Mark D.; Gibson, Gary G.; Denn, Fredrick M.
Collocated in time and space, top-of-the-atmosphere measurements of the Earth radiation budget (ERB) and cloudiness from passive scanning radiometers, and lidar- and radar-in-space measurements of multilayered cloud systems, are the required combination to improve our understanding of the role of clouds and radiation in climate. Experiments to fly multiple satellites "in formation" to measure simultaneously the radiative and optical properties of overlapping cloud systems are being designed. Because satellites carrying ERB experiments and satellites carrying lidars- or radars-in space have different orbital characteristics, the number of simultaneous measurements of radiation and clouds is reduced relative to the number of measurements made by each satellite independently. Monthly averaged coincident observations of radiation and cloudiness are biased when compared against more frequently sampled observations due, in particular, to the undersampling of their diurnal cycle, Using the Colorado State University General Circulation Model (CSU GCM), the goal of this study is to measure the impact of using simultaneous observations from the Earth Observing System (EOS) platform and companion satellites flying lidars or radars on monthly averaged diagnostics of longwave radiation, cloudiness, and its cloud optical properties. To do so, the hourly varying geographical distributions of coincident locations between the afternoon EOS (EOS-PM) orbit and the orbit of the ICESAT satellite set to fly at the altitude of 600 km, and between the EOS PM orbit and the orbits of the PICASSO satellite proposed to fly at the altitudes of 485 km (PICA485) or 705 km (PICA705), are simulated in the CSU GCM for a 60-month time period starting at the idealistic July 1, 2001, launch date. Monthly averaged diagnostics of the top-of-the-atmosphere, atmospheric, and surface longwave radiation budgets and clouds accumulated over grid boxes corresponding to satellite overpasses are compared against
Escadafal, R.; Huete, A.
The variations of near-infrared red reflectance ratios of ten aridic soil samples were correlated with a ''redness index'' computed from red and green spectral bands. These variations have been shown to limit the performances of vegetation indices (NDVI and SAVI) in discriminating low vegetation covers. The redness index is used to adjust for this ''soil noise''. Dala simulated for vegetation densities of 5 to 15% cover showed that the sensitivity of the corrected vegetation indices was significantly improved. Specifically, the ''noise-corrected'' SAVI was able to assess vegetation amounts with an error four times smaller than the uncorrected NDVI. These promising results should lead to a significant improvement in assessing biomass in arid lands from remotely sensed data. (author) [fr
Full Text Available As a result of increasing attention paid to aerosols in climate studies, numerous global satellite aerosol products have been generated. Aerosol parameters and underlining physical processes are now incorporated in many general circulation models (GCMs in order to account for their direct and indirect effects on the earth's climate, through their interactions with the energy and water cycles. There exists, however, an outstanding problem that these satellite products have substantial discrepancies, that must be lowered substantially for narrowing the range of the estimates of aerosol's climate effects. In this paper, numerous key uncertain factors in the retrieval of aerosol optical depth (AOD are articulated for some widely used and relatively long satellite aerosol products including the AVHRR, TOMS, MODIS, MISR, and SeaWiFS. We systematically review the algorithms developed for these sensors in terms of four key elements that influence the quality of passive satellite aerosol retrieval: calibration, cloud screening, classification of aerosol types, and surface effects. To gain further insights into these uncertain factors, the NOAA AVHRR data are employed to conduct various tests, which help estimate the ranges of uncertainties incurred by each of the factors. At the end, recommendations are made to cope with these issues and to produce a consistent and unified aerosol database of high quality for both environment monitoring and climate studies.
Mark Nelson; Greg Liknes; Charles H. Perry
Analysis and display of forest composition, structure, and pattern provides information for a variety of assessments and management decision support. The objective of this study was to produce geospatial datasets and maps of conterminous United States forest land ownership, forest site productivity, timberland, and reserved forest land. Satellite image-based maps of...
Tran, Annelise; Goutard, Flavie; Chamaillé, Lise; Baghdadi, Nicolas; Lo Seen, Danny
Recent studies have highlighted the potential role of water in the transmission of avian influenza (AI) viruses and the existence of often interacting variables that determine the survival rate of these viruses in water; the two main variables are temperature and salinity. Remote sensing has been used to map and monitor water bodies for several decades. In this paper, we review satellite image analysis methods used for water detection and characterization, focusing on the main variables that influence AI virus survival in water. Optical and radar imagery are useful for detecting water bodies at different spatial and temporal scales. Methods to monitor the temperature of large water surfaces are also available. Current methods for estimating other relevant water variables such as salinity, pH, turbidity and water depth are not presently considered to be effective.
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.
Valderrama-Landeros, L; Flores-de-Santiago, F; Kovacs, J M; Flores-Verdugo, F
Optimizing the classification accuracy of a mangrove forest is of utmost importance for conservation practitioners. Mangrove forest mapping using satellite-based remote sensing techniques is by far the most common method of classification currently used given the logistical difficulties of field endeavors in these forested wetlands. However, there is now an abundance of options from which to choose in regards to satellite sensors, which has led to substantially different estimations of mangrove forest location and extent with particular concern for degraded systems. The objective of this study was to assess the accuracy of mangrove forest classification using different remotely sensed data sources (i.e., Landsat-8, SPOT-5, Sentinel-2, and WorldView-2) for a system located along the Pacific coast of Mexico. Specifically, we examined a stressed semiarid mangrove forest which offers a variety of conditions such as dead areas, degraded stands, healthy mangroves, and very dense mangrove island formations. The results indicated that Landsat-8 (30 m per pixel) had the lowest overall accuracy at 64% and that WorldView-2 (1.6 m per pixel) had the highest at 93%. Moreover, the SPOT-5 and the Sentinel-2 classifications (10 m per pixel) were very similar having accuracies of 75 and 78%, respectively. In comparison to WorldView-2, the other sensors overestimated the extent of Laguncularia racemosa and underestimated the extent of Rhizophora mangle. When considering such type of sensors, the higher spatial resolution can be particularly important in mapping small mangrove islands that often occur in degraded mangrove systems.
Full Text Available The SatBałtyk (Satellite Monitoring of the Baltic Sea Environment project is being realized in Poland by the SatBałtyk Scientific Consortium, specifically appointed for this purpose, which associates four scientific institutions: the Institute of Oceanology PAN in Sopot - coordinator of the project, the University of Gdańsk (Institute of Oceanography, the Pomeranian Academy in Słupsk (Institute of Physics and the University of Szczecin (Institute of Marine Sciences. The project is aiming to prepare a technical infrastructure and set in motion operational procedures for the satellite monitoring of the Baltic Sea ecosystem. The main sources of input data for this system will be the results of systematic observations by metrological and environmental satellites such as TIROS N/NOAA, MSG (currently Meteosat 10, EOS/AQUA and Sentinel -1, 2, 3 (in the future. The system will deliver on a routine basis the variety of structural and functional properties of this sea, based on data provided by relevant satellites and supported by hydro-biological models. Among them: the solar radiation influx to the sea’s waters in various spectral intervals, energy balances of the short- and long-wave radiation at the Baltic Sea surface and in the upper layers of the atmosphere over the Baltic, sea surface temperature distribution, dynamic states of the water surface, concentrations of chlorophyll a and other phytoplankton pigments in the Baltic waters, spatial distributions of algal blooms, the occurrence of coastal upwelling events, and the characteristics of primary production of organic matter and photosynthetically released oxygen in the water and many others. The structure of the system and preliminary results will be presented.
McDonald, K. C.
Snow- and glacier-fed river systems originating from High Mountain Asia (HMA) support diverse ecosystems and provide the basis for food and energy production for more than a billion people living downstream. Climate-driven changes in the melting of snow and glaciers and in precipitation patterns are expected to significantly alter the flow of the rivers in the HMA region at various temporal scales, which in turn could heavily affect the socioeconomics of the region. Hence, climate change effects on seasonal and long-term hydrological conditions may have far reaching economic impact annually and over the century. We are developing a decision support tool utilizing integrated microwave remote sensing datasets, process modeling and economic models to inform water resource management decisions and ecosystem sustainability as related to the High Mountain Asia (HMA) region's response to climate change. The availability of consistent time-series microwave remote sensing datasets from Earth-orbiting scatterometers, radiometers and synthetic aperture radar (SAR) imagery provides the basis for the observational framework of this monitoring system. We discuss the assembly, processing and application of scatterometer and SAR data sets from the Advanced Scatterometer (ASCAT) and Sentinal-1 SARs, and the enlistment of these data to monitor seasonal melt and thaw status of glacier-dominated and surrounding regions. We present current status and future plans for this effort. Our team's study emphasizes processes and economic modeling within the Trishuli basin; our remote sensing analysis supports analyses across the HiMAT domain.
K. H. Lee
Full Text Available In East Asia, satellite observation is important because aerosols from natural and anthropogenic sources have been recognized as a major source of regional and global air pollution. However, retrieving aerosols properties from satellite observations over land can be difficult because of the surface reflection, complex aerosol composition, and aerosol absorption. In this study, a new aerosol retrieval method called as the Moderate Resolution Imaging Spectroradiometer (MODIS satellite aerosol retrieval (MSTAR was developed and applied to three different aerosol event cases over East Asia. MSTAR uses a separation technique that can distinguish aerosol reflectance from top-of-atmosphere (TOA reflectance. The aerosol optical thickness (AOT was determined by comparing this aerosol reflectance with pre-calculated values. Three case studies show how the methodology identifies discrepancies between measured and calculated values to retrieve more accurate AOT. The comparison between MODIS and the Aerosol Robotic Network (AERONET showed improvement using the suggested methodology with the cluster-based look-up-tables (LUTs (linear slope = 0.94, R = 0.92 than using operational MODIS collection 5 aerosol products (linear slope = 0.78, R = 0.87. In conclusion, the suggested methodology is shown to work well with aerosol models acquired by statistical clustering of the observation data in East Asia.
Full Text Available Snow on Antarctic sea ice plays a key role for sea ice physical processes and complicates retrieval of sea ice thickness using altimetry. Current methods of snow depth retrieval are based on satellite microwave radiometry, which perform best for dry, homogeneous snow packs on level sea ice. We introduce an alternative approach based on in-situ measurements of total (sea ice plus snow freeboard and snow depth, which we use to compute snow depth on sea ice from Ice, Cloud, and land Elevation Satellite (ICESat total freeboard observations. We compare ICESat snow depth for early winter and spring of the years 2004 through 2006 with the Advanced Scanning Microwave Radiometer aboard EOS (AMSR-E snow depth product. We find ICESat snow depths agree more closely with ship-based visual and air-borne snow radar observations than AMSR-E snow depths. We obtain average modal and mean ICESat snow depths, which exceed AMSR-E snow depths by 5–10 cm in winter and 10–15 cm in spring. We observe an increase in ICESat snow depth from winter to spring for most Antarctic regions in accordance with ground-based observations, in contrast to AMSR-E snow depths, which we find to stay constant or to decrease. We suggest satellite laser altimetry as an alternative method to derive snow depth on Antarctic sea ice, which is independent of snow physical properties.
Kielkopf, John F.; Carter, B.; Brown, C.; Hart, R.; Hay, J.; Waite, I.
The Digital Science Partnership, a collaboration of the University of Louisville and the University of Southern Queensland, operates a pair of 0.5-meter telescopes for teaching, research, and informal education. The instruments were installed at sites near Toowoomba, Australia, and Louisville, Kentucky in 2006. The Planewave Instruments optical systems employ a unique Dall-Kirkham design incorporating a two-element corrector that demagnifies the image, flattens the focal plane, and reduces coma. These instruments have a moderately fast f/6.8 focal ratio and maintain image quality with little vignetting over a field 42 mm in diameter (0.7 degree). With a 9-micron pixel CCD such as the KAF-6303E, the image scale of 0.55 seconds of arc per pixel typically yields seeing-limited image quality at our sites. The telescopes and their enclosure are operated in a live remote observing mode through Linux-based software, including a dome-control system that uses RFID tags for absolute rotation encoding. After several months of testing and development we have examples of images and photometry from both sites that illustrate the performance of the system. We will discuss image quality, as well as practical matters such as pointing accuracy and field acquisition, auto-guiding, communication latency in large file transfer, and our experience with remote observing assisted by teleconferencing. Time-delay-integration (TDI) imaging, in which the telescope is stationary while the CCD is clocked to track in right ascension, is under study. The technique offers wide fields of view with very high signal-to-noise ratio, and can be implemented in robotically operated instruments used in monitoring, rapid-response, and educational programs. Results for conventional and TDI imaging from the dark site in Australia compared to the brighter suburban site in Kentucky show the benefits of access to dark sites through international partnerships that remote operation technology offers.
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.
Diaz, J. A.; Pieri, D. C.; Bland, G.; Fladeland, M. M.
The development of small unmanned aerial systems (sUAS) with a variety of sensor packages, enables in situ and proximal remote sensing measurements of volcanic plumes. Using Costa Rican volcanoes as a Natural Laboratory, the University of Costa Rica as host institution, in collaboration with four NASA centers, have started an initiative to develop low-cost, field-deployable airborne platforms to perform volcanic gas & ash plume research, and in-situ volcanic monitoring in general, in conjunction with orbital assets and state-of-the-art models of plume transport and composition. Several gas sensors have been deployed into the active plume of Turrialba Volcano including a miniature mass spectrometer, and an electrochemical SO2 sensor system with temperature, pressure, relative humidity, and GPS sensors. Several different airborne platforms such as manned research aircraft, unmanned aerial vehicles, tethered balloons, as well as man-portable in-situ ground truth systems are being used for this research. Remote sensing data is also collected from the ASTER and OMI spaceborne instruments and compared with in situ data. The CARTA-UAV 2013 Mission deployment and follow up measurements successfully demonstrated a path to study and visualize gaseous volcanic emissions using mass spectrometer and gas sensor based instrumentation in harsh environment conditions to correlate in situ ground/airborne data with remote sensing satellite data for calibration and validation purposes. The deployment of such technology improves on our current capabilities to detect, analyze, monitor, model, and predict hazards presented to aircraft by volcanogenic ash clouds from active and impending volcanic eruptions.
Full Text Available In arid zones, the shortage of bee forage is critical and usually compels beekeepers to move their colonies in search of better forages. Identifying and mapping the spatiotemporal distribution of the bee forages over given area is important for better management of bee colonies. In this study honey bee plants in the target areas were inventoried following, ground inventory work supported with GIS applications. The study was conducted on 85 large plots of 50 × 50 m each. At each plot, data on species name, height, base diameter, crown height, crown diameter has been taken for each plant with their respective geographical positions. The data were stored, and processed using Trimble GPS supported with ArcGIS10 software program. The data were used to estimate the relative frequency, density, abundance and species diversity, species important value index and apicultural value of the species. In addition, Remotely Sensed Satellite Image of the area was obtained and processed using Hopfield Artificial Neural Network techniques. During the study, 182 species from 49 plant families were identified as bee forages of the target area. From the total number of species; shrubs, herbs and trees were accounting for 61%, 27.67%, and 11.53% respectively. Of which Ziziphus spina-christi, Acacia tortilis, Acacia origina, Acacia asak, Lavandula dentata, and Hypoestes forskaolii were the major nectar source plants of the area in their degree of importance. The average vegetation cover values of the study areas were low (<30% with low Shannon’s species diversity indices (H′ of 0.5–1.52 for different sites. Based on the eco-climatological factors and the variations in their flowering period, these major bee forage species were found to form eight distinct spatiotemporal categories which allow beekeepers to migrate their colonies to exploit the resources at different seasons and place. The Remote Sensed Satellite Image analysis confirmed the spatial
Leifer, I.; Clark, R.; Jones, C.; Holt, B.; Svejkovsky, J.; Swayze, G.
The vast, persistent, and unconstrained oil release from the DeepWater Horizon (DWH) challenged the spill response, which required accurate quantitative oil assessment at synoptic and operational scales. Experienced observers are the mainstay of oil spill response. Key limitations are weather, scene illumination geometry, and few trained observers, leading to potential observer bias. Aiding the response was extensive passive and active satellite and airborne remote sensing, including intelligent system augmentation, reviewed herein. Oil slick appearance strongly depends on many factors like emulsion composition and scene geometry, yielding false positives and great thickness uncertainty. Oil thicknesses and the oil to water ratios for thick slicks were derived quantitatively with a new spectral library approach based on the shape and depth of spectral features related to C-H vibration bands. The approach used near infrared, imaging spectroscopy data from the AVIRIS (Airborne Visual/InfraRed Imaging Spectrometer) instrument on the NASA ER-2 stratospheric airplane. Extrapolation to the total slick used MODIS satellite visual-spectrum broadband data, which observes sunglint reflection from surface slicks; i.e., indicates the presence of oil and/or surfactant slicks. Oil slick emissivity is less than seawater's allowing MODIS thermal infrared (TIR) nighttime identification; however, water temperature variations can cause false positives. Some strong emissivity features near 6.7 and 9.7 ??m could be analyzed as for the AVIRIS short wave infrared features, but require high spectral resolution data. TIR spectral trends can allow fresh/weathered oil discrimination. Satellite Synthetic Aperture Radar (SSAR) provided synoptic data under all-sky conditions by observing oil dampening of capillary waves; however, SSAR typically cannot discriminate thick from thin oil slicks. Airborne UAVSAR's significantly greater signal-to-noise ratio and fine spatial resolution allowed
meteorological satellite is stated in this paper. exploration of the ocean resources has been a very important question of global strategy in the world. The exploration of the ocean resources includes following items: Making full use of oceanic resources and space, protecting oceanic environment. to observe the ocean is by using of satellite. In 1978, US successfully launched the first ocean observation satellite in the world --- Sea Satellite. It develops ancient oceanography in to advanced space-oceanography. FY-1 B and FY- IC respectively. High quality data were acquired at home and abroad. FY-1 is Chinese meteorological satellite, but with 0.43 ~ 0.48 μm ,0.48 ~ 0.53 μm and 0.53 ~ 0.58 μm three ocean color channels, actually it is a multipurpose remote sensing satellite of meteorology and oceanography. FY-1 satellite's capability of observation on ocean partly, thus the application field is expanded and the value is increased. With the addition of oceanic channels on FY-1, the design of the satellite is changed from the original with meteorological observation as its main purpose into remote sensing satellite possessing capability of observing meteorology and ocean as well. Thus, the social and economic benefit of FY-1 is increased. the social and economic benefit of the development of the satellite is the key technique in the system design of the satellite. technically feasible but also save the funds in researching and manufacturing of the satellite, quicken the tempo of researching and manufacturing satellite. the scanning radiometer for FY-1 is conducted an aviation experiment over Chinese ocean. This experiment was of vital importance to the addition of oceanic observation channel on FY-1. FY-1 oceanic channels design to be correct. detecting ocean color. This is the unique character of Chinese FY-1 meteorological satellite. meteorological remote sensing channel on FY-1 to form detecting capability of three visible channels: red, yellow and blue
Saito, K.; Brown, D.; Spence, R.; Chenvidyakarn, T.; Adams, B.; Bevington, J.; Platt, S.; Chuenpagdee, R.; Juntarashote, K.; Khan, A.
The use of high-resolution optical satellite images is being investigated for evaluating and monitoring recovery after natural disasters. Funded by EPSRC, UK, the aim of the RECOVERY project is to develop indicators of recovery that can exploit the wealth of data now available, including those from satellite imagery, internet-based statistics and advanced field survey techniques. The final output will be a set of guidelines that suggests how remote sensing can be used to help monitor and evaluate the recovery process after natural disasters. The final guideline that will be produced at the end of the two year project, which started in February 2008, will be freely available to aid agencies and anyone that is interested. Currently there is no agreed standard approach for evaluating the effectiveness of recovery aid, although international frameworks such as PDNA (Post-Disaster Needs Assessment, United Nations Development Program, European Commission and World Bank) is currently being developed, and TRIAMS (Tsunami Recovery and Impact Assessment and Monitoring System, by UNDP and WHO) is being implemented to monitor the recovery from the Indian Ocean Tsunami. The RECOVERY project consists of three phases. Phase 1 was completed by September 2008 and focused on user needs survey, developing the recovery indicators and satellite image data identification/acquisition. The user needs survey was conducted to identify whether there were any indicators that the aid community would like to see prioritised. The survey result suggested that most indicators are equally important. Based on this result and also referring to the TRIAMS framework, a comprehensive list of indicators were developed which belong to six large categories, i.e. housing, infrastructure, services, livelihood, environment, social/security, risk reduction. For the RECOVERY project, two case study sites have been identified, i.e. the village of Baan Nam Khem on the west coast of Thailand, which was heavily
Full Text Available The restoration of fire-affected forest areas needs to be combined with their future protection from renewed catastrophic fires, such as those that occurred in Greece during the 2007 summer season. The present work demonstrates that the use of various sources of satellite data in conjunction with weather forecast information is capable of providing valuable information for the characterization of fire danger with the purpose of protecting the Greek national forest areas. This study shows that favourable meteorological conditions have contributed to the fire outbreak during the days of the unusually damaging fires in Peloponnese as well as Euboia (modern Greek: Evia at the end of August 2007. During those days, Greece was located between an extended high pressure system in Central Europe and a low pressure system in the Middle East. Their combination resulted in strong north-northeasterly winds in the Aegean Sea. As a consequence, strong winds were also observed in the regions of Evia and Peloponnese, especially in mountainous areas. The analysis of satellite images showing smoke emitted from the fires corroborates the results from the weather forecasts. A further analysis using the Fraction of Absorbed Photosyntetically Active Radiation (FAPAR as an indicator of active vegetation shows the extent of the destruction caused by the fire. The position of the burned areas coincides with that of the active fires detected in the earlier satellite image. Using the annual maximum FAPAR as an indicator of regional vegetation density, it was found that only regions with relatively high FAPAR were burned.
Bourdet, Alice; Frouin, Robert J.
The classic atmospheric correction algorithm, routinely applied to second-generation ocean-color sensors such as SeaWiFS, MODIS, and MERIS, consists of (i) estimating the aerosol reflectance in the red and near infrared (NIR) where the ocean is considered black (i.e., totally absorbing), and (ii) extrapolating the estimated aerosol reflectance to shorter wavelengths. The marine reflectance is then retrieved by subtraction. Variants and improvements have been made over the years to deal with non-null reflectance in the red and near infrared, a general situation in estuaries and the coastal zone, but the solutions proposed so far still suffer some limitations, due to uncertainties in marine reflectance modeling in the near infrared or difficulty to extrapolate the aerosol signal to the blue when using observations in the shortwave infrared (SWIR), a spectral range far from the ocean-color wavelengths. To estimate the marine signal (i.e., the product of marine reflectance and atmospheric transmittance) in the near infrared, the proposed approach is to decompose the aerosol reflectance in the near infrared to shortwave infrared into principal components. Since aerosol scattering is smooth spectrally, a few components are generally sufficient to represent the perturbing signal, i.e., the aerosol reflectance in the near infrared can be determined from measurements in the shortwave infrared where the ocean is black. This gives access to the marine signal in the near infrared, which can then be used in the classic atmospheric correction algorithm. The methodology is evaluated theoretically from simulations of the top-of-atmosphere reflectance for a wide range of geophysical conditions and angular geometries and applied to actual MODIS imagery acquired over the Gulf of Mexico. The number of discarded pixels is reduced by over 80% using the PC modeling to determine the marine signal in the near infrared prior to applying the classic atmospheric correction algorithm.
Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.
We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity
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.
W. Z. Hou
Full Text Available This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.
Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.
This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.
Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.
We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the
Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.
Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground
Inoue, K.; Abe, H.
To study meteorological characteristics of cool foggy easterly (Yamase), by which rice production in the Tohoku region was frequently damaged, we measured temperature of the fog layer resulted from Yamase, using infrared thermal indicator and meteorological satellite (HIMAWARI). These temperature data were compared with wet-bulb and dry-bulb temperatures obtained by a ventilated psychrometer. Generally, the temperature of fog droplets estimated from infrared thermal indicator was higher than the wet-bulb temperature by about 0∼1°C. This result indicates clearly that fog droplets were cooled by evaporation on the droplet surface. Under the conditions that the fog layer is homogeneous in liquid water content and fog droplet size distribution, the height of the fog layer can be estimated by the observation of visibility and relative solar radiation flux. (author)
Full Text Available One of economically important fish in the Bay of Bone is Skipjack tuna which their distribution and migration are influenced by surrounding environment. This study aims to investigate the relationship between skipjack tuna and their environments, and to predict potential fishing zones (PFZs for the fish in the Bone Bay-Flores Sea using satellite-based oceanography and catch data. Generalized additive models (GAMs were used to assess the relationship. A generalized linear model(GLM constructed from GAMs was used for prediction. Monthly mean sea surface temperature (SST and chlorophyll-a during the northwest monsoon (December-January together with catch data were used for the year 2012-2013. We used the GAMs to assess the effect of the environment variables on skipjack tuna CPUE (catch per unit effort. The best GLM was selected to predict skipjack tuna abundance. Results indicated that the highest CPUEs (fish/trip occurred in areas where SST and chlorophyll-a ranged from 29.5°-31.5°C and 0.15 - 0.25 mg m-3, respectively. The PFZs for skipjack were closely related to the spatial distribution of the optimum oceanographic conditions and these mainly developed in three locations, northern area of Bone Bay in December, in the middle area of the bay (4°-5.5°S and 120.5°-121.5°E during January and moved to the Flores Sea in February. The movement of skipjack concentration was consistent with the fishery data. This suggests that the dynamics of the optimum oceanographic signatures provided a good indicator for predicting feeding grounds as hotspot areas for skipjack tuna in Bone Bay-Flores Sea during northwest monsoon. Keywords: skipjack tuna, potential fishing zones, satellite based-oceanographic data, Northwest monsoon
Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey
The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the
The established procedure to access the quality of atmospheric correction processors and their underlying algorithms is the comparison of satellite data products with related in-situ measurements. Although this approach addresses the accuracy of derived geophysical properties in a straight forward fashion, it is also limited in its ability to catch systematic sensor and processor dependent behaviour of satellite products along the scan-line, which might impair the usefulness of the data in spatial analyses. The Ocean Colour Climate Change Initiative (OC-CCI) aims to create an ocean colour dataset on a global scale to meet the demands of the ecosystem modelling community. The need for products with increasing spatial and temporal resolution that also show as little systematic and random errors as possible, increases. Due to cloud cover, even temporal means can be influenced by along-scanline artefacts if the observations are not balanced and effects cannot be cancelled out mutually. These effects can arise from a multitude of results which are not easily separated, if at all. Among the sources of artefacts, there are some sensor-specific calibration issues which should lead to similar responses in all processors, as well as processor-specific features which correspond with the individual choices in the algorithms. A set of methods is proposed and applied to MERIS data over two regions of interest in the North Atlantic and the South Pacific Gyre. The normalised water leaving reflectance products of four atmospheric correction processors, which have also been evaluated in match-up analysis, is analysed in order to find and interpret systematic effects across track. These results are summed up with a semi-objective ranking and are used as a complement to the match-up analysis in the decision for the best Atmospheric Correction (AC) processor. Although the need for discussion remains concerning the absolutes by which to judge an AC processor, this example demonstrates
Adgaba, Nuru; Alghamdi, Ahmed; Sammoud, Rachid; Shenkute, Awraris; Tadesse, Yilma; Ansari, Mahammad J; Sharma, Deepak; Hepburn, Colleen
In arid zones, the shortage of bee forage is critical and usually compels beekeepers to move their colonies in search of better forages. Identifying and mapping the spatiotemporal distribution of the bee forages over given area is important for better management of bee colonies. In this study honey bee plants in the target areas were inventoried following, ground inventory work supported with GIS applications. The study was conducted on 85 large plots of 50 × 50 m each. At each plot, data on species name, height, base diameter, crown height, crown diameter has been taken for each plant with their respective geographical positions. The data were stored, and processed using Trimble GPS supported with ArcGIS10 software program. The data were used to estimate the relative frequency, density, abundance and species diversity, species important value index and apicultural value of the species. In addition, Remotely Sensed Satellite Image of the area was obtained and processed using Hopfield Artificial Neural Network techniques. During the study, 182 species from 49 plant families were identified as bee forages of the target area. From the total number of species; shrubs, herbs and trees were accounting for 61%, 27.67%, and 11.53% respectively. Of which Ziziphus spina-christi , Acacia tortilis , Acacia origina , Acacia asak , Lavandula dentata , and Hypoestes forskaolii were the major nectar source plants of the area in their degree of importance. The average vegetation cover values of the study areas were low (GIS and satellite image processing techniques could be an important tool for characterizing and mapping the available bee forage resources leading to their efficient and sustainable utilization.
Sun, Deyong; Huan, Yu; Qiu, Zhongfeng; Hu, Chuanmin; Wang, Shengqiang; He, Yijun
Phytoplankton size class (PSC), a measure of different phytoplankton functional and structural groups, is a key parameter to the understanding of many marine ecological and biogeochemical processes. In turbid waters where optical properties may be influenced by terrigenous discharge and nonphytoplankton water constituents, remote estimation of PSC is still a challenging task. Here based on measurements of phytoplankton diagnostic pigments, total chlorophyll a, and spectral reflectance in turbid waters of Bohai Sea and Yellow Sea during summer 2015, a customized model is developed and validated to estimate PSC in the two semienclosed seas. Five diagnostic pigments determined through high-performance liquid chromatography (HPLC) measurements are first used to produce weighting factors to model phytoplankton biomass (using total chlorophyll a as a surrogate) with relatively high accuracies. Then, a common method used to calculate contributions of microphytoplankton, nanophytoplankton, and picophytoplankton to the phytoplankton assemblage (i.e., Fm, Fn, and Fp) is customized using local HPLC and other data. Exponential functions are tuned to model the size-specific chlorophyll a concentrations (Cm, Cn, and Cp for microphytoplankton, nanophytoplankton, and picophytoplankton, respectively) with remote-sensing reflectance (Rrs) and total chlorophyll a as the model inputs. Such a PSC model shows two improvements over previous models: (1) a practical strategy (i.e., model Cp and Cn first, and then derive Cm as C-Cp-Cn) with an optimized spectral band (680 nm) for Rrs as the model input; (2) local parameterization, including a local chlorophyll a algorithm. The performance of the PSC model is validated using in situ data that were not used in the model development. Application of the PSC model to GOCI (Geostationary Ocean Color Imager) data leads to spatial and temporal distribution patterns of phytoplankton size classes (PSCs) that are consistent with results reported from
Wivell, Charles E.; Olmsted, Coert; Steinwand, Daniel R.; Taylor, Christopher
Because the pixel location in a line of Synthetic Aperture Radar (SAR) image data is directly related to the distance the pixel is from the radar, terrain elevations cause large displacement errors in the geo-referenced location of the pixel. This is especially true for radar systems with small angles between the nadir and look vectors. Thus, to geo-register a SAR image accurately, the terrain of the area must be taken into account. (Curlander et al., 1987; Kwok et al., 1987, Schreier et al., 1990; Wivell et al., 1992). As part of the 1992 National Aeronautics and Space Administration's Earth Observing System Version 0 activities, a prototype SAR geocod-. ing and terrain correction system was developed at the US. Geological Survey's (USGS) E~os Data Center (EDC) in Sioux Falls, South Dakota. Using this system with 3-arc-second digital elevation models (DEMs) mosaicked at the ED^ Alaska Field Office, 21 ERS-I s.4~ scenes acquired at the Alaska SAR Facility were automatically geocoded, terrain corrected, and mosaicked. The geo-registered scenes were mosaicked using a simple concatenation.
Madry, Scott; Camacho-Lara, Sergio
The first edition of this ground breaking reference work was the most comprehensive reference source available about the key aspects of the satellite applications field. This updated second edition covers the technology, the markets, applications and regulations related to satellite telecommunications, broadcasting and networking—including civilian and military systems; precise satellite navigation and timing networks (i.e. GPS and others); remote sensing and meteorological satellite systems. Created under the auspices of the International Space University based in France, this brand new edition is now expanded to cover new innovative small satellite constellations, new commercial launching systems, innovation in military application satellites and their acquisition, updated appendices, a useful glossary and more.
Crowley, J.K.; Hubbard, B.E.; Mars, J.C.
Remote sensing data from NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the first spaceborne imaging spectrometer, Hyperion, show hydrothermally altered rocks mainly composed of natroalunite, kaolinite, cristobalite, and gypsum on both the Mount Shasta and Shastina cones. Field observations indicate that much of the visible altered rock consists of talus material derived from fractured rock zones within and adjacent to dacitic domes and nearby lava flows. Digital elevation data were utilized to distinguish steeply sloping altered bedrock from more gently sloping talus materials. Volume modeling based on the imagery and digital elevation data indicate that Mount Shasta drainage systems contain moderate volumes of altered rock, a result that is consistent with Mount Shasta's Holocene record of mostly small to moderate debris flows. Similar modeling for selected areas at Mount Rainier and Mount Adams, Washington, indicates larger altered rock volumes consistent with the occurrence of much larger Holocene debris flows at those volcanoes. The availability of digital elevation and spectral data from spaceborne sensors, such as Hyperion and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), greatly expands opportunities for studying potential debris flow source characteristics at stratovolcanoes around the world. ?? 2003 Elsevier Inc. All rights reserved.
Full Text Available Characterizing vertical distributions of ozone from nadir-viewing satellite measurements is known to be challenging, particularly the ozone information in the troposphere. A novel retrieval algorithm called Full-Physics Inverse Learning Machine (FP-ILM, has been developed at DLR in order to estimate ozone profile shapes based on machine learning techniques. In contrast to traditional inversion methods, the FP-ILM algorithm formulates the profile shape retrieval as a classification problem. Its implementation comprises a training phase to derive an inverse function from synthetic measurements, and an operational phase in which the inverse function is applied to real measurements. This paper extends the ability of the FP-ILM retrieval to derive tropospheric ozone columns from GOME- 2 measurements. Results of total and tropical tropospheric ozone columns are compared with the ones using the official GOME Data Processing (GDP product and the convective-cloud-differential (CCD method, respectively. Furthermore, the FP-ILM framework will be used for the near-real-time processing of the new European Sentinel sensors with their unprecedented spectral and spatial resolution and corresponding large increases in the amount of data.
Xu, J.; Heue, K.-P.; Coldewey-Egbers, M.; Romahn, F.; Doicu, A.; Loyola, D.
Characterizing vertical distributions of ozone from nadir-viewing satellite measurements is known to be challenging, particularly the ozone information in the troposphere. A novel retrieval algorithm called Full-Physics Inverse Learning Machine (FP-ILM), has been developed at DLR in order to estimate ozone profile shapes based on machine learning techniques. In contrast to traditional inversion methods, the FP-ILM algorithm formulates the profile shape retrieval as a classification problem. Its implementation comprises a training phase to derive an inverse function from synthetic measurements, and an operational phase in which the inverse function is applied to real measurements. This paper extends the ability of the FP-ILM retrieval to derive tropospheric ozone columns from GOME- 2 measurements. Results of total and tropical tropospheric ozone columns are compared with the ones using the official GOME Data Processing (GDP) product and the convective-cloud-differential (CCD) method, respectively. Furthermore, the FP-ILM framework will be used for the near-real-time processing of the new European Sentinel sensors with their unprecedented spectral and spatial resolution and corresponding large increases in the amount of data.
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
Kanniah, Kasturi Devi; Lim, Hui Qi; Kaskaoutis, Dimitris G.; Cracknell, Arthur P.
Spatio-temporal variation and trends in atmospheric aerosols as well as their impact on solar radiation and clouds are crucial for regional and global climate change assessment. These topics are not so well-documented over Malaysia, the fact that it receives considerable amounts of pollutants from both local and trans-boundary sources. The present study aims to analyse the spatio-temporal evolution and decadal trend of Aerosol Optical Depth (AOD) from Terra and Aqua MODIS sensors, to identify different types and origin of aerosols and explore the link between aerosols and solar radiation. AOD and fine-mode fraction (FMF) products from MODIS, AOD and Ångström Exponent (AE) values from AERONET stations along with ground-based PM10 measurements and solar radiation recordings at selected sites in Peninsular Malaysia are used for this scope. The MODIS AODs exhibit a wide spatio-temporal variation over Peninsular Malaysia, while Aqua AOD is consistently lower than that from Terra. The AOD shows a neutral-to-declining trend during the 2000s (Terra satellite), while that from Aqua exhibits an increasing trend (~ 0.01 per year). AERONET AODs exhibit either insignificant diurnal variation or higher values during the afternoon, while their short-term availability does not allow for a trend analysis. Moreover, the PM10 concentrations exhibit a general increasing trend over the examined locations. The sources and destination of aerosols are identified via the HYSPLIT trajectory model, revealing that aerosols during the dry season (June to September) are mainly originated from the west and southwest (Sumatra, Indonesia), while in the wet season (November to March) they are mostly associated with the northeast monsoon winds from the southern China Sea. Different aerosol types are identified via the relationship of AOD with FMF, revealing that the urban and biomass-burning aerosols are the most abundant over the region contributing to a significant reduction (~- 0.21 MJ m- 2) of
Suzuki, G.; Sakka, T.; Tashiro, T.; Kawamata, H.; Tatsuzawa, S.; Naruse, N.; Takahashi, Y.
For a long time, nomads living in the Arctic Circle around Siberia have been making a living by hunting reindeer traditionally. Wild reindeer have a recurrent migration every year, however, the travel-route of reindeer has been changing recently, so the nomads cannot expect the route in their traditional experience. To support them, one of authors (Tatsuzawa) investigated the route by installing GPS transmitter to some reindeer. The reason of the changing route, however, remain unclear. Previous works indicated that the reason of changing the route must be a global warming, forest fires, thunders, and floods, but they only discuss only on the basis of measurements in specific area. The purpose of this study is to research why the arctic reindeer alter the travel route annually through 1) the annual change of vegetation (NDVI: normalized difference vegetation index) in reindeer ground, and through 2) the annual change of soil water content (mNDWI: modified normalized difference water index) which can be reflected precipitation near Lena river. First, we analyzed NDVI using MODIS images that can be observed over a wide area, filmed in July and August; the reindeer started to travel. We have compared the seasonal changes of the NDVI images with the trace obtained by GPS data from 2010 to 2012. Although NDVI images in July showed similar numerical values in every year, the satellite images taken at August 29 is annually different; NDVI values become lower (0.5 or less) when the reindeer travel to the north area in winter. This suggests that reindeer move to secure enough food in the end of summer. In contrast, mNDWI becomes high when the reindeer travel to the north area. The annual changes of the route may be related to the amount of rainfall.
Coskun, H Gonca; Alganci, Ugur; Usta, Gokce
Accurate and timely information about land use and land cover (LULC) and its changes in urban areas are crucial for urban land management decision-making, ecosystem monitoring and urban planning. Also, monitoring and representation of urban sprawl and its effects on the LULC patterns and hydrological processes of an urbanized watershed is an essential part of water resource planning and management. This paper presents an image analysis study using multi temporal digital satellite imagery of LULC and changes in the Kucukcekmece Watershed (Metropolitan Istanbul, Turkey) from 1992 to 2006. The Kucukcekmece Basin includes portions of the Kucukcekmece District within the municipality of Istanbul so it faces a dramatic urbanization. An urban monitoring analysis approach was first used to implement a land cover classification. A change detection method controlled with ground truth information was then used to determine changes in land cover. During the study period, the variability and magnitude of hydrological components based on land-use patterns were cumulatively influenced by urban sprawl in the watershed. The proposed approach, which uses a combination of Remote Sensing (RS) and Geographical Information System (GIS) techniques, is an effective tool that enhances land-use monitoring, planning, and management of urbanized watersheds.
“Meteorological Satellite Systems” is a primer on weather satellites and their Earth applications. This book reviews historic developments and recent technological advancements in GEO and polar orbiting meteorological satellites. It explores the evolution of these remote sensing technologies and their capabilities to monitor short- and long-term changes in weather patterns in response to climate change. Satellites developed by various countries, such as U.S. meteorological satellites, EUMETSAT, and Russian, Chinese, Japanese and Indian satellite platforms are reviewed. This book also discusses international efforts to coordinate meteorological remote sensing data collection and sharing. This title provides a ready and quick reference for information about meteorological satellites. It serves as a useful tool for a broad audience that includes students, academics, private consultants, engineers, scientists, and teachers.
Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim
Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0
Barrios, José Miguel; Ghilain, Nicolas; Arboleda, Alirio; Gellens-Meulenberghs, Françoise
Evapotranspiration (ET) is the water flux going from the surface into the atmosphere as result of soil and surface water evaporation and plant transpiration. It constitutes a key component of the water cycle and its quantification is of crucial importance for a number of applications like water management, climatic modelling, agriculture monitoring and planning, etc. Estimating ET is not an easy task; specially if large areas are envisaged and various spatio-temporal patterns of ET are present as result of heterogeneity in land cover, land use and climatic conditions. In this respect, spaceborne remote sensing (RS) provides the only alternative to continuously measure surface parameters related to ET over large areas. The Royal Meteorological Institute (RMI) of Belgium, in the framework of EUMETSAT's "Land Surface Analysis-Satellite Application Facility" (LSA-SAF), has developed a model for the estimation of ET. The model is forced by RS data, numerical weather predictions and land cover information. The RS forcing is derived from measurements by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. This ET model is operational and delivers ET estimations over the whole field of view of the MSG satellite (Europe, Africa and Eastern South America) (http://landsaf.meteo.pt) every 30 minutes. The spatial resolution of MSG is 3 x 3 km at subsatellite point and about 4 x 5 km in continental Europe. The spatial resolution of this product may constrain its full exploitation as the interest of potential users (farmers and natural resources scientists) may lie on smaller spatial units. This study aimed at testing methodological alternatives to combine RS imagery (geostationary and polar orbit satellites) for the estimation of ET such that the spatial resolution of the final product is improved. In particular, the study consisted in the implementation of two approaches for combining the current ET estimations with
THE IDEA IS TO USEMODIS IN CONJUNCTION WITH THE CURRENT LIMITED LANDSAT CAPABILITY, COMMERCIAL SATELLITES, ANDUNMANNED AERIAL VEHICLES (UAV), IN A MULTI-STAGE APPROACH TO MEET EPA INFORMATION NEEDS.REMOTE SENSING OVERVIEW: EPA CAPABILITIES, PRIORITY AGENCY APPLICATIONS, SENSOR/AIRCRAFT CAPABILITIES, COST CONSIDERATIONS, SPECTRAL AND SPATIAL RESOLUTIONS, AND TEMPORAL CONSIDERATIONS
EPA remote sensing capabilities include applied research for priority applications and technology support for operational assistance to clients across the Agency. The idea is to use MODIS in conjunction with the current limited Landsat capability, commercial satellites, and Unma...
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
Solander, Kurt C.
The ability to accurately quantify water storages and fluxes in water management systems through observations or models is of increasing importance due to the expected impacts from climate change and population growth worldwide. Here, I describe three innovative techniques developed to better understand this problem. First, a model was created to represent reservoir storage and outflow with the objective of integration into a Land Surface Model (LSM) to simulate the impacts of reservoir management on the climate system. Given this goal, storage capacity represented the lone model input required that is not already available to an LSM user. Model parameterization was linked to air temperature to allow future simulations to adapt to a changing climate, making it the first such model to mimic the potential response of a reservoir operator to climate change. Second, spatial and temporal error properties of future NASA Surface Water and Ocean Topography (SWOT) satellite reservoir operations were quantified. This work invoked the use of the SWOTsim instrument simulator, which was run over a number of synthetic and actual reservoirs so the resulting error properties could be extrapolated to the global scale. The results provide eventual users of SWOT data with a blueprint of expected reservoir error properties so such characteristics can be determined a priori for a reservoir given knowledge about its topology and anticipated repeat orbit pass over its location. Finally, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission was used in conjunction with in-situ water use records to evaluate sustainable water use at the two-digit HUC basin scale over the contiguous United States. Results indicate that the least sustainable water management region is centered in the southwest, where consumptive water use exceeded water availability by over 100% on average for some of these basins. This work represents the first attempt at evaluating sustainable
Wildmann, N.; Kaufmann, F.; Bange, J.
The measurement of water vapour concentration in the atmosphere is an ongoing challenge in environmental research. Satisfactory solutions exist for ground-based meteorological stations and measurements of mean values. However, carrying out advanced research of thermodynamic processes aloft as well, above the surface layer and especially in the atmospheric boundary layer (ABL), requires the resolution of small-scale turbulence. Sophisticated optical instruments are used in airborne meteorology with manned aircraft to achieve the necessary fast-response measurements of the order of 10 Hz (e.g. LiCor 7500). Since these instruments are too large and heavy for the application on small remotely piloted aircraft (RPA), a method is presented in this study that enhances small capacitive humidity sensors to be able to resolve turbulent eddies of the order of 10 m. The sensor examined here is a polymer-based sensor of the type P14-Rapid, by the Swiss company Innovative Sensor Technologies (IST) AG, with a surface area of less than 10 mm2 and a negligible weight. A physical and dynamical model of this sensor is described and then inverted in order to restore original water vapour fluctuations from sensor measurements. Examples of flight measurements show how the method can be used to correct vertical profiles and resolve turbulence spectra up to about 3 Hz. At an airspeed of 25 m s-1 this corresponds to a spatial resolution of less than 10 m.
Southern Californian wildfires can influence climate in a variety of ways, including changes in surface albedo, emission of greenhouse gases and aerosols, and the production of tropospheric ozone. Ecosystem post-fire recovery plays a key role in determining the strength, duration, and relative importance of these climate forcing agents. Southern California's ecosystems vary markedly with topography, creating sharp transitions with elevation, aspect, and slope. Little is known about the ways topography influences ecosystem properties and function, particularly in the context of post-fire recovery. We combined images from the USGS satellite Landsat 5 with flux tower measurements to analyze pre- and post-fire albedo and carbon exchanged by Southern California's ecosystems in the Santa Ana Mountains. We reduced the sources of external variability in Landsat images using several correction methods for topographic and bidirectional effects. We used time series of corrected images to infer the Net Ecosystem Exchange and surface albedo, and calculated the radiative forcing due to CO2 emissions and albedo changes. We analyzed the patterns of recovery and radiative forcing on north- and south-facing slopes, stratified by vegetation classes including grassland, coastal sage scrub, chaparral, and evergreen oak forest. We found that topography strongly influenced post-fire recovery and radiative forcing. Field observations are often limited by the difficulty of collecting ground validation data. Current instrumentation networks do not provide adequate spatial resolution for landscape-level analysis. The deployment of consumer-market technology could reduce the cost of near-surface measurements, allowing the installation of finer-scale instrument networks. We tested the performance of the Microsoft Kinect sensor for measuring vegetation structure. We used Kinect to acquire 3D vegetation point clouds in the field, and used these data to compute plant height, crown diameter, and
Pramod Krishna, Akhouri
A watershed in Chhotanagpur plateau region was investigated utilizing space data from Indian Remote Sensing (IRS) Satellite towards spatial and temporal soil erosion process study. Geomorphologically, this plateau region is an undulating pediplain. The watershed namely Potpoto river watershed covering an area of 8160 hectares is situated in the vicinity of Ranchi, capital city of newly created Jharkahnd state. As per the national watershed atlas, Potpoto river is a tributary of Subarnarekha river system within the Upper Subarnarekha river basin under watershed no. 4H3C8. This rural to semi-urban watershed is important towards various services to Ranchi city as well as experiencing direct or indirect pressures of development. Drivers of land use changes at ground level are responsible for change in soil erosion rates in any watershed in coupled human-environment systems. This may adversely affect the soil cover of such watersheds depicted through changed rates of erosion. In a rural to semi-urban watershed like this, there are general tendencies of land use and thereby land cover changes from forests to agricultural lands, within agricultural land in terms of cropping pattern changes to cash-crops, orchards, commercial plantations and conversions to other land use categories as well towards infrastructure expansions. Universal Soil Loss Equation (USLE) was used as a basis to observe the intensity of erosion using remote sensing, rainfall data, soil data and land use/land cover map. IRS1C LISSIII and IRSP6 LISSIII data were used to identify land use status for the years 1996 and 2004 respectively. LISSIII sensor provides data in the visible to near infrared (Bands 2, 3, 4) as well as short wave infrared (Band 5) range of electromagnetic spectrum. In this study, bands 2 (0.52-0.59 microns), 3 (0.62-0.68 microns) and 4 (0.77-0.86 microns) were used with spatial resolution of 23.5 meters at nadir. Digital image processing was carried out using ERDAS Imagine software
Pelland, N.; Sterling, J.; Springer, A.; Iverson, S.; Johnson, D.; Lea, M. A.; Bond, N. A.; Ream, R.; Lee, C.; Eriksen, C.
Behavioral responses by top marine predators to oceanographic features such as eddies, river plumes, storms, and coastal topography suggest that biophysical interactions in these zones affect predators' prey, foraging behaviors, and potentially fitness. However, examining these pathways is challenged by the obstacles inherent in obtaining simultaneous observations of surface and subsurface environmental fields and predator behavior. This work describes recent publications and ongoing studies of northern fur seal (NFS) foraging ecology during their 8-month migration. Satellite-tracked movement and dive behavior in the North Pacific ocean was compared to remotely sensed data, atmospheric reanalysis, autonomous in situ ocean sampling, and animal borne temperature and salinity data. Integration of these data demonstrates how reproductive fitness, physiology, and environment shape NFS migratory patterns. Seal mass correlates with dive ability and thus larger males exploit prey aggregating at the base of the winter mixed-layer depth in the Bering Sea and interior northern North Pacific Ocean. Smaller adult females migrate to the Gulf of Alaska and California Current ecosystems - where surface wind speeds decline, mixed-layer depths shoal, and coastal production is fueled by upwelling, coastal capes, and eddies - and less commonly to the Transitional Zone Chlorophyll Front, where fronts and eddies may concentrate prey. Surface wind speed and direction influence movement behavior of all age and size classes, though to a greater degree in the smaller pups and adult females than adult males. For naïve and physiologically less-capable pups, the timing and strength of autumn winds during migratory dispersal may play a role in shaping migratory routes and the environmental conditions faced by pups along these routes. In combination with other factors such as pup condition, this may play a role in interannual variations in overwinter survivorship.
Platt, Trevor; Sathyendranath, Shubha
Various conclusions by Balch et al. (1992) about the current state of modeling primary production in the sea (lack of improvement in primary production models, since 1957, utility of analytical models, and merits or weaknesses of complex models) are commented on. It is argued that since they are based on a false premise, these conclusions are not robust, and that the approach used by Balch et al. (the model of Platt and Sathyendranath, 1988) was inadequate for the question they set out to address. The present criticism is based mainly on the issue of whether implementation was correct with respect to parameter selection. It is concluded that the findings of Balch et al. with respect to the model of Platt and Sathyendranath is unreliable. Balch replies that satellite-derived estimates of primary production should be compared directly to that measured in situ in as many regions as possible. This will provide a first-order estimate of the magnitude of the error involved in estimating primary production from space.
Borfecchia, Flavio; Micheli, Carla; Belmonte, Alessandro; De Cecco, Luigi; Sannino, Gianmaria; Bracco, Giovanni; Mattiazzo, Giuliana; Vittoria Struglia, Maria
Marine renewable energy extraction plays a key role both in energy security of small islands and in mitigation of climate change, but at the same time poses the important question of monitoring the effects of the interaction of such devices with the marine environment. In this work we present a new methodology, integrating satellite remote sensing techniques with in situ observations and biophysical parameters analysis, for the monitoring and mapping of Posidonia Oceanica (PO) meadows in shallow coastal waters. This methodology has been applied to the coastal area offshore Pantelleria Island (Southern Mediterranean) where the first Italian Inertial Sea Wave Energy Converter (ISWEC) prototype has been recently installed. The prototype, developed by the Polytechnic of Turin consists of a platform 8 meters wide, 15 meters long and 4.5 meters high, moored at about 800 meters from the shore and at 31 m depth. It is characterized by high conversion efficiency, resulting from its adaptability to different wave conditions, and a limited environmental impact due to its mooring innovative method with absence of fixed anchors to the seabed. The island of Pantelleria, is characterized by high transparency of coastal waters and PO meadows ecosystems with still significant levels of biodiversity and specific adaptation to accentuated hydrodynamics of these shores. Although ISWEC is a low-impact mooring inertial system able to ensure a reliable connection to the electric grid with minimal impact on seagrass growing in the seabed, the prototype installation and operation involves an interaction with local PO and seagrass meadows and possible water transparency decreasing. In this view monitoring of local PO ecosystem is mandatory in order to allow the detection of potential stress and damages due to ISWEC related activities and/or other factors. However, monitoring and collection of accurate and repetitive information over large areas of the necessary parameters by means of
The benefits of a satellite services system and the basic needs of the Space Transportation System to have improved satellite service capability are identified. Specific required servicing equipment are discussed in terms of their technology development status and their operative functions. Concepts include maneuverable television systems, extravehicular maneuvering unit, orbiter exterior lighting, satellite holding and positioning aid, fluid transfer equipment, end effectors for the remote manipulator system, teleoperator maneuvering system, and hand and power tools.
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
Fu, B. H.; Guo, Q.; Yan, F.; Zhang, J.; Shi, P. L.; Ayinuer, M.; Xue, G. L.
The retreat of mountain glaciers, notably in high Asia, provides evidence for the rise of global temperature. The mass balance is vital for the health of a glacier. If the amount of frozen precipitation in the accumulation zone exceeds the quantity of glacial ice loss due to melting or lies in the ablation zone, the glacier will advance. Conversely, if the accumulation is less than the ablation, the glacier will retreat. Glaciers in retreat will have negative mass balances, and if they do not reach an equilibrium between accumulation and ablation, will eventually disappear. Long-term changes of the mountain glaciers in the Tian Shan, Central Asia, are not well constrained. Analyses of satellite remote sensing data combined with the ground observations reveal a 37.5% decline of glaciered area from 1989 to 2014 in No.1 Glacier, the headwaters of the Urumqi River basin, Chinese Tian Shan, which could be linked to increased summer melting. The results show that the area of glaciers was reduced from 31.55 km2 in 18 August 1989 to 28.66 km2 in 24 August 1994 and 19.74 km2 in 31 August 2014. The glacier area was reduced by 0.47 km2/per year in recent 25 years since 1989, and the annual reduction was 1.5%. Meanwhile, the urban area of Urumqi, the biggest city of Xinjiang Uygur Autonomous Region, increased from 156 km2 in 1989 to 555 km2 in 2014. Correspondingly, the population of permanent residents increased from 1.06 million in 1989 to 3.53 million in 2014. We suggest that the decline of glacier area is driven primarily by summer melting and, possibly, linked to the combined effects of the global rise in temperatures and black carbon/CO2 emission from coal-fired power plants, cement plants and petroleum chemical plants from the nearby Urumqi and surrounding regions. The continuing retreat of glaciers will have a number of different quantitative impacts. Populations in the arid Central Asia regions are heavily dependent on snow and glacier melt for their irrigation and
Chander, G.; Hewison, T.J.; Fox, N.; Wu, X.; Xiong, X.; Blackwell, W.J.
Inter-calibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be inter-operable, the instruments must be cross-calibrated. To meet the stringent needs of such applications requires that instruments provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités (SI) traceable Calibration and Validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Inter-calibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Inter-calibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated inter-calibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms
Geostationary or equatorial synchronous satellites are a daily reminder of our space efforts during the past two decades. The nightly television satellite weather picture, the intercontinental telecommunications of television transmissions and telephone conversations, and the establishrnent of educational programs in remote regions on Earth are constant reminders of the presence of these satellites. As used here, the term 'geo stationary' must be taken loosely because, in the long run, the satellites will not remain 'stationary' with respect to an Earth-fixed reference frame. This results from the fact that these satellites, as is true for all satellites, are incessantly subject to perturbations other than the central-body attraction of the Earth. Among the more predominant pertur bations are: the ellipticity of the Earth's equator, the Sun and Moon, and solar radiation pressure. Higher harmonics of the Earth's potential and tidal effects also influence satellite motion, but they are of second order whe...
Remote monitoring of cathodic protection rectifiers of the Bolivia-Brazil Gas Pipeline using low orbit satellite telephone; Monitoracao remota de retificadores de protecao catodica do Gasoduto Bolivia-Brasil utilizando telefone via satelite de baixa orbita
Coelho, Jorge Fernando Pereira [TBG - Transportadora Brasileira Gasoduto Bolivia Brasil S.A., Rio de Janeiro, RJ (Brazil)
The present paper has for objective to present the information collected during definitions, development, implementation, testing and operation phases of the Pilot System for monitoring of the Cathodic Protection Rectifiers MS-10 and SP-09, installed on the Bolivia-Brazil Gas Pipeline. The adopted solution for the Pilot System includes, basically, communication through low-earth satellite telephone, inter linked to the public telephone net, acquisition and data transmission system (Remote Terminal Unit) and data reception in the Supervision and Control Room. (author)
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).
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.
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...
Niemeyer, I.; Listner, C.
The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)
National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...
National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...
Van den Bergh, F
Full Text Available Course resolution earth observation satellites offer large data sets with daily observations at global scales. These data sets represent a rich resource that, because of the high acquisition rate, allows the application of time-series analysis...
Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...
Caverlotti-Silva, M. A.; Arellano-Baeza, A. A.
The correct monitoring of the subsidence of the craters related to the underground mine exploitation is one of the most important endeavors of the satellite remote sensing. The ASTER and LANDSAT satellite images have been used to study the deformation of the crater of the CODELCO/Andina mine, Valparaiso Region, Chile. The high-resolution satellite images were used to detect changes in the lineament patterns related to the subsidence. These results were compared with the ground deformation extracted from the GPS and topography station networks. It was found that sudden changes in the lineament patterns appear when the ground deformation overcomes a definite threshold.
Full Text Available Rainfall intensity plays an important role in landslide prediction especially in mountain areas. However, the rainfall intensity of a location is usually interpolated from rainfall recorded at nearby gauges without considering any possible effects of topographic slopes. In order to obtain reliable rainfall intensity for disaster mitigation, this study proposes a rainfall-vector projection method for topographic-corrected rainfall. The topographic-corrected rainfall is derived from wind speed, terminal velocity of raindrops, and topographical factors from digital terrain model. In addition, scatter plot was used to present landslide distribution with two triggering factors and kernel density analysis is adopted to enhance the perception of the distribution. Numerical analysis is conducted for a historic event, typhoon Mindulle, which occurred in 2004, in a location in central Taiwan. The largest correction reaches 11%, which indicates that topographic correction is significant. The corrected rainfall distribution is then applied to the analysis of landslide triggering factors. The result with corrected rainfall distribution provides better agreement with the actual landslide occurrence than the result without correction.
AghaKouchak, Amir; Nakhjiri, Navid
Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)
Guyot, G.; Seguin, B.
Remote sensing offers new possibilities in agrometeorology. Meteorological satellites (which have good revisit capability but low spatial resolution) and earth observation satellites (which have good spatial resolution but poor revisit capability) give complementary information on crop growth conditions and on the biological status of plants. Thermal infrared data can be used to map local climates, to estimate water balance at the scale of a small region and to determine the extent and the seriousness of damage caused by major climatic accidents (frost, drought). Visible near, near and middle infrared data are well adapted to crop identification and monitoring, biomass estimation and yield forecasting. The combination of information given by these 2 types of satellites should in future provide better knowledge and better control of agricultural production. However the application of such techniques may be limited by the cloud cover [French] La télédétection offre des possibilités nouvelles dans le domaine de l’agrométéorologie. Les satellites météorologiques (qui ont une bonne répétitivité dans le temps mais une faible résolution spatiale) et les satellites d’observation de la terre (qui ont une bonne résolution spatiale mais une faible répétitivité dans le temps) permettent d’obtenir des informations complémentaires sur les conditions dans lesquelles se développent les cultures et sur leur état. Les données de l’infrarouge thermique peuvent être utilisées pour cartographier les climats locaux, estimer les bilans hydriques à l’échelle de la petite région et déterminer l’extension spatiale et l’ampleur des accidents climatiques majeurs (gel, sécheresse). Les données du visible, du proche et du moyen infrarouge permettent d’identifier les cultures, de déterminer leur stade phénologique, de suivre leur évolution, d’estimer leur biomasse et de prévoir leur production. La combinaison des informations fournies par ces 2
Zhan, Wenfeng; Zhou, Ji; Ju, Weimin
Subsurface soil temperature is a key variable of land surface processes and not only responds to but also modulates the interactions of energy fluxes at the Earth's surface. Thermal remote sensing has traditionally been regarded as incapable of detecting the soil temperature beneath the skin-surf...
Zhang, Wen-Yan; Lin, Chao-Yuan
The Soil Conservation Service Curve Number (SCS-CN) method is commonly used in hydrology to estimate direct runoff volume. The CN is the empirical parameter which corresponding to land use/land cover, hydrologic soil group and antecedent soil moisture condition. In large watersheds with complex topography, satellite remote sensing is the appropriate approach to acquire the land use change information. However, the topographic effect have been usually found in the remotely sensed imageries and resulted in land use classification. This research selected summer and winter scenes of Landsat-5 TM during 2008 to classified land use in Chen-You-Lan Watershed, Taiwan. The b-correction, the empirical topographic correction method, was applied to Landsat-5 TM data. Land use were categorized using K-mean classification into 4 groups i.e. forest, grassland, agriculture and river. Accuracy assessment of image classification was performed with national land use map. The results showed that after topographic correction, the overall accuracy of classification was increased from 68.0% to 74.5%. The average CN estimated from remotely sensed imagery decreased from 48.69 to 45.35 where the average CN estimated from national LULC map was 44.11. Therefore, the topographic correction method was recommended to normalize the topographic effect from the satellite remote sensing data before estimating the CN.
Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre
Chambers, Katherine H.; Koschmeder, Louis A.; Hollansworth, James E.; ONeill, Jack; Jones, Robert E.; Gibbons, Richard C.
Emerging applications of commercial mobile satellite communications include satellite delivery of compact disc (CD) quality radio to car drivers who can select their favorite programming as they drive any distance; transmission of current air traffic data to aircraft; and handheld communication of data and images from any remote corner of the world. Experiments with the enabling technologies and tests and demonstrations of these concepts are being conducted before the first satellite is launched by utilizing an existing NASA spacecraft.
Ireland, Sarah; Wulili Narjic, Concepta; Belton, Suzanne; Kildea, Sue
to investigate the beliefs and practices of Aboriginal women who decline transfer to urban hospitals and remain in their remote community to give birth. an ethnographic approach was used which included: the collection of birth histories and narratives, observation and participation in the community for 24 months, field notes, training and employment of an Aboriginal co-researcher, and consultation with and advice from a local reference group. a remote Aboriginal community in the Northern Territory, Australia. narratives were collected from seven Aboriginal women and five family members. findings showed that women, through their previous experiences of standard care, appeared to make conscious decisions and choices about managing their subsequent pregnancies and births. Women took into account their health, the baby's health, the care of their other children, and designated men with a helping role. narratives described a breakdown of traditional birthing practices and high levels of non-compliance with health-system-recommended care. standard care provided for women relocating for birth must be improved, and the provision of a primary maternity service in this particular community may allow Aboriginal Women's Business roles and cultural obligations to be recognised and invigorated. International examples of primary birthing services in remote areas demonstrate that they can be safe alternatives to urban transfer for childbirth. A primary maternity service would provide a safer environment for the women who choose to avoid standard care. Copyright © 2010 Elsevier Ltd. All rights reserved.
Smith, J.A.; Schmugge, T.J.; Ballard, J.R. Jr.
Land Surface Temperature (LST) is an important parameter in understanding global environmental change because it controls many of the underlying processes in the energy budget at the surface and heat and water transport between the surface and the atmosphere. The measurement of LST at a variety of spatial and temporal scales and extension to global coverage requires remote sensing means to achieve these goals. Land surface temperature and emissivity products are currently being derived from satellite and aircraft remote sensing data using a variety of techniques to correct for atmospheric effects. Implicit in the commonly employed approaches is the assumption of isotropy in directional thermal infrared exitance. The theoretical analyses indicate angular variations in apparent infrared temperature will typically yield land surface temperature errors ranging from 1 to 4 C unless corrective measures are applied
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.
Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James
We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.
Chen, Li; Tan, Chih-Hung; Kao, Shuh-Ji; Wang, Tai-Sheng
Parallel GEGA was constructed by incorporating grammatical evolution (GE) into the parallel genetic algorithm (GA) to improve reservoir water quality monitoring based on remote sensing images. A cruise was conducted to ground-truth chlorophyll-a (Chl-a) concentration longitudinally along the Feitsui Reservoir, the primary water supply for Taipei City in Taiwan. Empirical functions with multiple spectral parameters from the Landsat 7 Enhanced Thematic Mapper (ETM+) data were constructed. The GE, an evolutionary automatic programming type system, automatically discovers complex nonlinear mathematical relationships among observed Chl-a concentrations and remote-sensed imageries. A GA was used afterward with GE to optimize the appropriate function type. Various parallel subpopulations were processed to enhance search efficiency during the optimization procedure with GA. Compared with a traditional linear multiple regression (LMR), the performance of parallel GEGA was found to be better than that of the traditional LMR model with lower estimating errors.
Shofiyati, Rizatus; Supriatna, Wahyu; Takeuchi, Wataru; Sofan, Parwati; Darmawan, Soni; Awaluddin
Long droughts experienced in Indonesia in the past are identified as one of the main factors in the failure of rice production. In this regard, special attention to monitor the condition is encouraged to reduce the damage. Currently, various satellite data and approaches can withdraw valuable information for monitoring and anticipating drought hazards. Two types of drought, Meteorology and Agriculture, have been assessed. During the last 10 years, daily and monthly rainfall data derived from TRMM and GSMaP. MTSAT and AMSR-E data have been analyzed to identify meteorological drought. Agricultural drought has been studied by observing the character of some indices (EVI, VCI, VHI, LST, and NDVI) of sixteen-day and monthly MODIS data at a period of 5 years (2009 – 2013). Network for data transfer has been built between LAPAN (data provider), ICALRD (implementer), IAARD Cloud Computing, and University of Tokyo (technical supporter). A Web-GIS based Drought Monitoring Information System has been developed to disseminate the information to end users. This paper describes the implementation of remote sensing drought monitoring model and development of Web-GIS and satellite based information system
Wicaksono, Pramaditya; Danoedoro, Projo; Hartono, Hartono; Nehren, Udo; Ribbe, Lars
Mangrove forest is an important ecosystem located in coastal area that provides various important ecological and economical services. One of the services provided by mangrove forest is the ability to act as carbon sink by sequestering CO2 from atmosphere through photosynthesis and carbon burial on the sediment. The carbon buried on mangrove sediment may persist for millennia before return to the atmosphere, and thus act as an effective long-term carbon sink. Therefore, it is important to understand the distribution of carbon stored within mangrove forest in a spatial and temporal context. In this paper, an effort to map carbon stocks in mangrove forest is presented using remote sensing technology to overcome the handicap encountered by field survey. In mangrove carbon stock mapping, the use of medium spatial resolution Landsat 7 ETM+ is emphasized. Landsat 7 ETM+ images are relatively cheap, widely available and have large area coverage, and thus provide a cost and time effective way of mapping mangrove carbon stocks. Using field data, two image processing techniques namely Vegetation Index and Linear Spectral Unmixing (LSU) were evaluated to find the best method to explain the variation in mangrove carbon stocks using remote sensing data. In addition, we also tried to estimate mangrove carbon sequestration rate via multitemporal analysis. Finally, the technique which produces significantly better result was used to produce a map of mangrove forest carbon stocks, which is spatially extensive and temporally repetitive.
Hu, Chuli; Li, Jie; Lin, Xin; Chen, Nengcheng; Yang, Chao
Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA) ontology model that is resolved around the task-sensor-observation capability (TSOC) ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO) ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors.
Full Text Available Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA ontology model that is resolved around the task-sensor-observation capability (TSOC ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors.
Hale, Stephen Roy
Landsat-7 Enhanced Thematic Mapper satellite imagery was used to model Bicknell's Thrush (Catharus bicknelli) distribution in the White Mountains of New Hampshire. The proof-of-concept was established for using satellite imagery in species-habitat modeling, where for the first time imagery spectral features were used to estimate a species-habitat model variable. The model predicted rising probabilities of thrush presence with decreasing dominant vegetation height, increasing elevation, and decreasing distance to nearest Fir Sapling cover type. To solve the model at all locations required regressor estimates at every pixel, which were not available for the dominant vegetation height and elevation variables. Topographically normalized imagery features Normalized Difference Vegetation Index and Band 1 (blue) were used to estimate dominant vegetation height using multiple linear regression; and a Digital Elevation Model was used to estimate elevation. Distance to nearest Fir Sapling cover type was obtained for each pixel from a land cover map specifically constructed for this project. The Bicknell's Thrush habitat model was derived using logistic regression, which produced the probability of detecting a singing male based on the pattern of model covariates. Model validation using Bicknell's Thrush data not used in model calibration, revealed that the model accurately estimated thrush presence at probabilities ranging from 0 to account for more total individuals and reproductive output than higher density less abundant land area. Efforts to conserve areas of highest individual density under the assumption that density reflects habitat quality could target the smallest fraction of the total population.
V. A. Коrshnyak
Abstract The authors show that in modern biology, life is seen as the ability of living matter, and namely in medicine – the ability of human body, to maintain the existence in natural environment. From this perspective, it is extremely necessary to synchronize the activity of body structures among themselves taking into account the changes of environmental factors. Achieving the harmony between the body activity and environmental changes is carried out using an external pacemaker of life processes’ activity, the role of which is performed by the geomagnetic field (GMF. This became possible due to the fact that the life processes are cyclical, i.e. they possess rhythmic characteristics, and GMF is an electromagnetic field which is changing its characteristics rhythmically. The material for the present study were the data obtained during the neurological examination of 20 healthy people and 100 patients with remote consequences of CTBI which were treated in the clinic of autonomic nervous system pathology of the SI "Institute of neurology, psychiatry and narcology of the NAMS of Ukraine". The results investigations have showed that geomagnetic perturbations, which modify the GMF parameters, exacerbate the disorders of VNS in patients with remote after effects of CTBI. It is associated with the increased desynchronization of the activity of suprasegmental structures of VNS and with breach of brain vascular system’s status that occurs during a magnetic storm. The acupuncture that is aimed at restoring of synchronization of activity of suprasegmental structures of VNS significantly reduces its sensitivity to the geomagnetic disturbances. Keywords: magnetic storm, closed head injury, autonomic nervous system.
Madry, Scott; Camacho-Lara, Sergio
Top space experts from around the world have collaborated to produce this comprehensive, authoritative, and clearly illustrated reference guide to the fast growing, multi-billion dollar field of satellite applications and space communications. This handbook, done under the auspices of the International Space University based in France, addresses not only system technologies but also examines market dynamics, technical standards and regulatory constraints. The handbook is a completely multi-disciplinary reference book that covers, in an in-depth fashion, the fields of satellite telecommunications, Earth observation, remote sensing, satellite navigation, geographical information systems, and geosynchronous meteorological systems. It covers current practices and designs as well as advanced concepts and future systems. It provides a comparative analysis of the common technologies and design elements for satellite application bus structures, thermal controls, power systems, stabilization techniques, telemetry, com...
Full Text Available A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous–plastic (VP sea-ice rheology are compared with synthetic aperture radar (SAR satellite observations (RGPS, RADARSAT Geophysical Processor System for the time period 1996–2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous–plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.
Ramos, M. D.; Tendencia, E.; Espana, K.; Sabido, J.; Bagtasa, G.
Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1) the Tropical Rainfall Measuring Mission (TRMM), (2) the CPC Morphing technique (CMORPH) of NOAA and (3) the Global Satellite Mapping of Precipitation (GSMAP) and (4) Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN). Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC) for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN) values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.
... Plants; Remote sensing; Rhigozum obovatum Burch; Satellite-derived vegetation indices; Woody species; patchiness; semi-arid; dwarf shrubland; shrublands; co2; assimilation; karoo; south africa; ndvi; satellite imagery; geochemical mound; rhigozum obovatum; eriocephalus ericoides; pentzia incana; vegetation; botany
Synergistic use of Lagrangian dispersion and radiative transfer modelling with satellite and surface remote sensing measurements for the investigation of volcanic plumes: the Mount Etna eruption of 25–27 October 2013
Full Text Available In this paper we combine SO2 and ash plume dispersion modelling with satellite and surface remote sensing observations to study the regional influence of a relatively weak volcanic eruption from Mount Etna on the optical and micro-physical properties of Mediterranean aerosols. We analyse the Mount Etna eruption episode of 25–27 October 2013. The evolution of the plume along the trajectory is investigated by means of the FLEXible PARTicle Lagrangian dispersion (FLEXPART model. The satellite data set includes true colour images, retrieved values of volcanic SO2 and ash, estimates of SO2 and ash emission rates derived from MODIS (MODerate resolution Imaging Spectroradiometer observations and estimates of cloud top pressure from SEVIRI (Spinning Enhanced Visible and InfraRed Imager. Surface remote sensing measurements of aerosol and SO2 made at the ENEA Station for Climate Observations (35.52° N, 12.63° E; 50 m a.s.l. on the island of Lampedusa are used in the analysis. The combination of these different data sets suggests that SO2 and ash, despite the initial injection at about 7.0 km altitude, reached altitudes around 10–12 km and influenced the column average aerosol particle size distribution at a distance of more than 350 km downwind. This study indicates that even a relatively weak volcanic eruption may produce an observable effect on the aerosol properties at the regional scale. The impact of secondary sulfate particles on the aerosol size distribution at Lampedusa is discussed and estimates of the clear-sky direct aerosol radiative forcing are derived. Daily shortwave radiative forcing efficiencies, i.e. radiative forcing per unit AOD (aerosol optical depth, are calculated with the LibRadtran model. They are estimated between −39 and −48 W m−2 AOD−1 at the top of the atmosphere and between −66 and −49 W m−2 AOD−1 at the surface, with the variability in the estimates mainly depending on the
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
Barber, T. A.; Bourke, R. D.
Items affecting information transmitted from payload landed on remote planet to Earth via communications satellite including orbit, transmission policy and orbit injection error effect on communication capability
Eck, T. F.; Holben, B. N.; Giles, D. M.; Smirnov, A.; Slutsker, I.; Sinyuk, A.; Schafer, J.; Sorokin, M. G.; Reid, J. S.; Sayer, A. M.; Hsu, N. Y. C.; Levy, R. C.; Lyapustin, A.; Wang, Y.; Rahman, M. A.; Liew, S. C.; Salinas Cortijo, S. V.; Li, T.; Kalbermatter, D.; Keong, K. L.; Elifant, M.; Aditya, F.; Mohamad, M.; Mahmud, M.; Chong, T. K.; Lim, H. S.; Choon, Y. E.; Deranadyan, G.; Kusumaningtyas, S. D. A.
The strong El Nino event in 2015 resulted in below normal rainfall throughout Indonesia, which in turn allowed for exceptionally large numbers of biomass burning fires (including much peat burning) from Aug though Oct 2015. Over the island of Borneo, three AERONET sites measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in Sep and Oct ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain significant signal at mid-visible, therefore a newly developed algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the longer wavelengths as possible. The AOD at longer wavelengths were then utilized to provide estimates of AOD at 550 nm with maximum values of 9 to 11. Additionally, satellite retrievals of AOD at 550 nm from MODIS data and the Dark Target, Deep Blue, and MAIAC algorithms were analyzed and compared to AERONET measured AOD. The AOD was sometimes too high for the satellite algorithms to make retrievals in the densest smoke regions. Since the AOD was often extremely high there was often insufficient AERONET direct sun signal at 440 nm for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, new hybrid sky radiance scans can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for more retrievals and at higher AOD levels. The retrieved volume median radius of the fine mode increased from 0.18 to 0.25 micron as AOD increased from 1 to 3 (at 440 nm). These are very large size particles for biomass burning aerosol and are similar in size to smoke particles measured in Alaska during the very dry years of 2004 and 2005 (Eck et al. 2009) when peat soil burning also contributed to the fuel burned. The average single scattering albedo over the wavelength range of 440 to 1020 nm
Slayback, D. A.; Garvin, J. B.; Asrar, G.; Ferrini, V. L.; Giguere, C.
The surtseyan eruption that formed the Hunga Tonga Hunga Ha'apai (HTHH) volcanic island in the Kingdom of Tonga between late Dec 2014 and the end of Jan 2015 produced a 133m tall tephra cone with flanking pyroclastic flows with a land area similar to that of Surtsey (Iceland). With the advent of sub-meter resolution satellite imaging systems employing both optical and microwave (radar) wavelengths, we have quantitatively documented the post-eruptive evolution of the new island on a monthly basis since Feb 2015 via DigitalGlobe WorldView and Canadian Space Agency Radarsat-2 satellites, resulting in an unprecedented time-series of measurements of the island's surface area, volume, and landscapes. Our results have documented the rapid subaerial evolution of the new island, with a current mean loss of island volume of 12.2% per year. On the basis of the time series of visible images from WorldView and the C-band Spotlight SAR images from Radarsat-2, we developed a first-order evolutionary model for the apparently-tephra dominated island, and compared this to the 53 year evolution of Surtsey. Because the HTHH island is adjacent to two pre-existing islands that form part of the rim of a submarine caldera, the loss of land from the southern coast over its first 5 months resulted in the development of an accretionay spit that connected it to the Hunga Tonga island to the NE, limiting the overall pace of subaerial coastline loss. With marine abrasion accentuated on the southern side of the island, and breaching of the interior crater (lake) of the primary tephra cone, the projected lifetime of the island is likely to be far less than Surtsey, which is protected by palagonitized tephra. From our volume and coast-line measurements, the projected lifetime of the island is likely to fall between 7.5 yrs (shortest) and 70 years, dependent on whether any of the interior deposits forming the primary edifice have been palagoinitized to resist marine abrasion and mass wasting. This
The aim of this study is to investigate pan-sharpening performance of RASAT and GÖKTÜRK-2 images. For this purpose, pan-sharpened images are generated using most popular pan-sharpening methods IHS, Brovey and PCA at first. This procedure is followed by quantitative evaluation of pan-sharpened images using Correlation Coefficient (CC, Root Mean Square Error (RMSE, Relative Average Spectral Error (RASE, Spectral Angle Mapper (SAM and Erreur Relative Globale Adimensionnelle de Synthése (ERGAS metrics. For generation of pan-sharpened images and computation of metrics SharpQ tool is used which is developed with MATLAB computing language. According to metrics, PCA derived pan-sharpened image is the most similar one to multispectral image for RASAT, and Brovey derived pan-sharpened image is the most similar one to multispectral image for GÖKTÜRK-2. Finally, pan-sharpened images are evaluated qualitatively in terms of object availability and completeness for various land covers (such as urban, forest and flat areas by a group of operators who are experienced in remote sensing imagery.
Kolokolova, L.; Buratti, B.; Tishkovets, V.
We have found systematic variations in the spectra of Saturn's icy satellites Rhea and Iapetus obtained by the Cassini Visual and Infrared Mapping Spectrometer (VIMS). The main attribute of these variations is a significantly different depth of the absorption bands at different phase angles. We show that these variations likely result from the coherent backscattering effect (CBE). This effect has been mainly known as the probable reason for a steep opposition spike in brightness observed for some asteroids, moons, and Kuiper Belt Objects at phase angles smaller than 3 deg. The opposition spike has different steepness at different albedos due to the strong dependence of the CBE on the absorption of the material. As a result of this dependence, the impact of the CBE should be different within and outside of the absorption spectral bands. This produces a systematic change in the depth of the absorption bands at different phase angles, as we see in the VIMS spectra of Rhea and Iapetus. Neglecting this effect may result in misinterpretation of the spectra and misleading conclusions about compositional and particle size differences of icy bodies studied at different phase angles. Our computer modeling of the CBE reproduces the observed spectral variations and also shows that they are strongly affected by the size and packing of particles. Thus, the variations in the absorption bands produced by the CBE not only allow us to improve interpretation of the spectra, but also provide a promising approach to study size and packing of the regolith and dust particles.
Xian, George; Homer, Collin G.; Aldridge, Cameron L.
An approach that can generate sagebrush habitat change estimates for monitoring large-area sagebrush ecosystems has been developed and tested in southwestern Wyoming, USA. This prototype method uses a satellite-based image change detection algorithm and regression models to estimate sub-pixel percentage cover for five sagebrush habitat components: bare ground, herbaceous, litter, sagebrush and shrub. Landsat images from three different months in 1988, 1996 and 2006 were selected to identify potential landscape change during these time periods using change vector (CV) analysis incorporated with an image normalization algorithm. Regression tree (RT) models were used to estimate percentage cover for five components on all change areas identified in 1988 and 1996, using unchanged 2006 baseline data as training for both estimates. Over the entire study area (24 950 km2), a net increase of 98.83 km2, or 0.7%, for bare ground was measured between 1988 and 2006. Over the same period, the other four components had net losses of 20.17 km2, or 0.6%, for herbaceous vegetation; 30.16 km2, or 0.7%, for litter; 32.81 km2, or 1.5%, for sagebrush; and 33.34 km2, or 1.2%, for shrubs. The overall accuracy for shrub vegetation change between 1988 and 2006 was 89.56%. Change patterns within sagebrush habitat components differ spatially and quantitatively from each other, potentially indicating unique responses by these components to disturbances imposed upon them.
Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources
the bands needed for atmospheric correction. Spectral definition files for AVIRIS, HYDICE, HYMAP, HYPERION, CASI, and AISA sensors are included as...Satellite Visible Imagery – A Review.” In Lecture Notes on Coastal and Estuarine Studies, edited by R. T. Barber, N. K. Mooers, M. J. Bowman, and B...In Proceedings of SPIE Coastal Ocean Remote Sensing, edited by Robert J. Frouin, ZhongPing Lee, Vol. 6680, 668013-1-668013-9. doi:10.1117/12.736845
Full Text Available Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008 vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI and the recently developed passive-microwave-based Vegetation Optical Depth (VOD. The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.
Full Text Available During the early stage of the G satellite of the Fengyun-2 series (FY-2G, severe cold biases up to ~2.3 K occur in its measurements in the 12.0 μm (IR2 band, which demonstrate time- and scene-dependent characteristics. Similar cold biases in water vapor and carbon dioxide absorption bands of other satellites are considered to be caused by either ice contamination (physical method or spectral response function (SRF shift (empirical method. Simulations indicate that this cold bias of FY-2G indeed suffers from equivalent SRF shift as a whole towards the longer wavelength direction. To overcome it, a novel approach combining both physical and empirical methods is proposed. With the possible ice thicknesses tested before launch, the ice contamination effect is alleviated, while the shape of the SRF can be modified in a physical way. The remaining unknown factors for cold bias are removed by shifting the convolved SRF with an ice transmittance spectrum. Two parameters, i.e., the ice thickness (5 μm and the shifted value (+0.15 μm, are estimated by inter-calibration with reference instruments, and the modification coefficient is also calculated (0.9885 for the onboard blackbody calibration. Meanwhile, the updated SRF was released online on 23 March 2016. For the period between July 2015 and December 2016, the monthly biases of the FY-2G IR2 band remain oscillating around zero, the majorities (~89% of which are within ±1.0 K, while its mean monthly absolute bias is around 0.6 K. Nevertheless, the cold bias phenomenon of the IR2 band no longer exists. The combination method can be referred by other corrections for cold biases.
Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images
Full Text Available Dehesas are highly valuable agro-forestry ecosystems, widely distributed over Mediterranean-type climate areas, which play a key role in rural development, basing their productivity on a sustainable use of multiple resources (crops, livestock, wildlife, etc.. The information derived from remote sensing based models addressing ecosystem water consumption, at different scales, can be used by institutions and private landowners to support management decisions. In this study, the Two-Source Energy Balance (TSEB model is analyzed over two Spanish dehesa areas integrating multiple satellites (MODIS and Landsat for estimating water use (ET, vegetation ground cover, leaf area and phenology. Instantaneous latent heat (LE values are derived on a regional scale and compared with eddy covariance tower (ECT measurements, yielding accurate results (RMSDMODIS Las Majadas 44 Wm−2, Santa Clotilde RMSDMODIS 47 Wm−2 and RMSDLandsat 64 Wm−2. Daily ET(mm is estimated using daily return interval of MODIS for both study sites and compared with the flux measurements of the ECTs, with RMSD of 1 mm day−1 over Las Majadas and 0.99 mm day−1 over Santa Clotilde. Distributed ET over Andalusian dehesa (15% of the region is successfully mapped using MODIS images, as an approach to monitor the ecosystem status and the vegetation water stress on a regular basis.
Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.
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)
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The impact that wireless communications has had for gas and oil producers was discussed. Wireless communication, which has been replacing the traditional formats of radio and telephone data networks, has proved to be cheaper, smaller, and faster than creating privately owned communication networks. With highly developed supervisory control and data acquisition systems - combined with cellular or satellite technology - information from drill sites can be online at the corporate headquarters instantaneously. Eighty percent of Canada's land mass is beyond reach of traditional wireline and wireless services. Research into advanced communications, including telecommunication and mobile applications, yielded lucrative results for service providers such as BCTel, SaskTel, Bell Mobility and AGT. The latest data transmission technology is the cellular digital packet data (CDPD) which will operate over existing cellular networks. However, unlike circuit-switched cellular, CDPD technology provides an airlink where data is secure. It will be available to the marketplace over the course of the coming year. Among other advantages, CDPD will allow producers to remotely monitor production information and downtime alarms from wells and compressor stations. It will also provide fleet operators with the means to monitor operating vital signs on rolling stock
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
Pan, X.; Wong, G. T.; Tai, J.; Ho, T.
By using the observations from multiple satellite sensors, the climatology of the oceanography, including the surface wind vector, sea surface temperature (SST), surface chlorophyll a concentration (Chl_a), and vertically integrated net primary production (PPeu), in the northern South China Sea Shelf-sea (NoSoCS) and adjacent waters is evaluated. Regional and sub-regional mechanisms in driving the coastal processes, which influence the spatial and temporal distributional patterns in water component, are assessed. Seasonal vertical convective mixing by wind and surface heating/cooling is the primary force in driving the annual changes in SST and Chl_a in the open South China Sea (SCS), in which highly negative correlation coefficients between Chl_a and SST and moderately positive correlation coefficients between Chl_a and wind speed are found. Together, the seasonal variations in SST and wind speed account for about 80% of the seasonal variation in Chl_a. In the NoSoCS as a whole, however, the contribution is reduced to about 40%, primarily due to the effect of the Pearl River plume. A tongue of water extending eastward from the mouth of the River into the middle shelf with positive correlation coefficients between Chl_a and SST and around zero or slightly negative correlation coefficients between Chl_a and wind is the most striking feature in the NoSoCS. The westward and eastward propagations of the Pearl River plume are both very small during the northeast monsoonal season, driven primarily by the Coriolis effect. The abrupt increase in the areal coverage of the River plume, which is much more pronounced in the eastward propagation, between June and August can be attributed to the prevailing southwest monsoon as well as the annual peak of the river flow. Coastal upwelling is another sub-regional phenomenon in the NoSoCS. The upwelling at the shelf edge off the Taiwan Bank may be characterized by its elevated Chl_a. Its areal coverage and average Chl_a do not vary
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.
Hucke, Dorothee; Hillebrand, Gudrun; Winterscheid, Axel; Kranz, Susanne; Baschek, Björn
The applications of remote sensing in hydrology are diverse and offer significant benefits for water monitoring. Up to now, operational river monitoring and sediment management in Germany mainly rely on in-situ measurements and on results obtained from numerical modelling. Remote sensing by satellites has a great potential to supplement existing data with two-dimensional information on near-surface turbidity distributions at greater spatial scales than in-situ measurements can offer. Within the project WasMon-CT (WaterMonitoring-Chlorophyll/Turbidity), the Federal Institute of Hydrology (BfG) aims at the implementation of an operational monitoring of turbidity distributions based on satellite images (esp. Sentinel-2, Landsat7 and 8). Initially, selected federal inland and estuarine waterways will be addressed: Rhine, Elbe, Ems, Weser. WasMon-CT is funded within the German Copernicus activities. Within the project, a database of atmospherically corrected, geo-referenced turbidity data will be assembled. The collected corresponding meta-data will include aspects of satellite data as well as hydrological data, e.g. cloud cover and river run-off. Based on this catalogue of spatially linked meta-data, the satellite data will be selected by e.g. cloud cover or run-off. The permanently updated database will include past as well as recent satellite images. It is designed with a long-term perspective to optimize the existing in-situ measurement network, which will serve partly for calibration and partly as validation data set. The aim is to extend, but not to substitute, the existing frequent point measurements with spatially extensive, satellite-derived data from the near surface part of the water column. Here, turbidity is used as proxy for corresponding suspended sediment concentrations. For this, the relationship between turbidity and suspended sediment concentrations will be investigated. Products as e.g. longitudinal profiles or virtual measurement stations will be
Cropland characteristics and accurate maps of their spatial distribution are required to develop strategies for global food security by continental-scale assessments and agricultural land use policies. North America is the major producer and exporter of coarse grains, wheat, and other crops. While cropland characteristics such as crop types are available at country-scales in North America, however, at continental-scale cropland products are lacking at fine sufficient resolution such as 30m. Additionally, applications of automated, open, and rapid methods to map cropland characteristics over large areas without the need of ground samples are needed on efficient high performance computing platforms for timely and long-term cropland monitoring. In this study, I developed novel, automated, and open methods to map cropland extent, crop intensity, and crop types in the North American continent using large remote sensing datasets on high-performance computing platforms. First, a novel method was developed in this study to fuse pixel-based classification of continental-scale Landsat data using Random Forest algorithm available on Google Earth Engine cloud computing platform with an object-based classification approach, recursive hierarchical segmentation (RHSeg) to map cropland extent at continental scale. Using the fusion method, a continental-scale cropland extent map for North America at 30m spatial resolution for the nominal year 2010 was produced. In this map, the total cropland area for North America was estimated at 275.2 million hectares (Mha). This map was assessed for accuracy using randomly distributed samples derived from United States Department of Agriculture (USDA) cropland data layer (CDL), Agriculture and Agri-Food Canada (AAFC) annual crop inventory (ACI), Servicio de Informacion Agroalimentaria y Pesquera (SIAP), Mexico's agricultural boundaries, and photo-interpretation of high-resolution imagery. The overall accuracies of the map are 93.4% with a
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...
Barron, Charlie; Jan, Dastugue; Jackie, May; Rowley, Clark; Smith, Scott; Spence, Peter; Gremes-Cordero, Silvia
Predicting the evolution of ocean temperature in regional ocean models depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. Within the COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates, real-time satellite observations are used to estimate shortwave, longwave, sensible, and latent air-sea heat flux corrections to a background estimate from the prior day's regional or global model forecast. These satellite-corrected fluxes are used to prepare a corrected ocean hindcast and to estimate flux error covariances to project the heat flux corrections for a 3-5 day forecast. In this way, satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. While traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle, COFFEE endeavors to appropriately partition and reduce among various surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using operational global or regional atmospheric forcing. Experiment cases combine different levels of flux calibration with assimilation alternatives. The cases use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is
The characteristics of the Saturn satellites are discussed. The satellites close to Saturn - Janus, Mimas, Enceladus, Tethys, Dione and Rhea - rotate along the circular orbits. High reflectivity is attributed to them, and the density of the satellites is 1 g/cm 3 . Titan is one of the biggest Saturn satellites. Titan has atmosphere many times more powerful than that of Mars. The Titan atmosphere is a peculiar medium with a unique methane and hydrogen distribution in the whole Solar system. The external satellites - Hyperion, Japetus and Phoebe - are poorly investigated. Neither satellite substance density, nor their composition are known. The experimental data on the Saturn rings obtained on the ''Pioneer-11'' and ''Voyager-1'' satellites are presented [ru
Nag, Sreeja; Gatebe, Charles K.; de Weck, Olivier
The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.
Nag, Sreeja; Gatebe, Charles K.; Weck, Olivier de
The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.
Journal of Chemical Education, 2004
The availability of abundant water resources in the Upper Midwest of the United States is nullified by their contamination through heavy commercial and industrial activities. Scientists have taken the responsibility of detecting the water quality of these resources through remote-sensing satellites to develop a wide-ranging water purification plan…
Remote studies allow you to recruit subjects quickly, cheaply, and immediately, and give you the opportunity to observe users as they behave naturally in their own environment. In Remote Research, Nate Bolt and Tony Tulathimutte teach you how to design and conduct remote research studies, top to bottom, with little more than a phone and a laptop.
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.
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
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.
Shamma, Mohammed A.
This presentation is an overview on Satellite Communication for the Aeronautical Telecommunication Management (ATM) research. Satellite Communications are being considered by the FAA and NASA as a possible alternative to the present and future ground systems supporting Air Traffic Communications. The international Civil Aviation Organization (ICAO) have in place Standards and Recommended Practices (SARPS) for the Aeronautical Mobile Satellite Services (AMSS) which is mainly derived from the pre-existing Inmarsat service that has been in service since the 1980s. The Working Group A of the Aeronautical Mobile Communication Panel of ICAO has also been investigating SARPS for what is called the Next Generation Satellite Service (NGSS) which conforms less to the Inmarsat based architecture and explores wider options in terms of satellite architectures. Several designs are being proposed by Firms such as Boeing, ESA, NASA that are geared toward full or secondary usage of satellite communications for ATM. Satellite communications for ATM can serve several purposes ranging from primary usage where ground services would play a minimal backup role, to an integrated solution where it will be used to cover services, or areas that are less likely to be supported by the proposed and existing ground infrastructure. Such Integrated roles can include usage of satellite communications for oceanic and remote land areas for example. It also can include relieving the capacity of the ground network by providing broadcast based services of Traffic Information Services messages (TIS-B), or Flight Information Services (FIS-B) which can take a significant portion of the ground system capacity. Additionally, satellite communication can play a backup role to support any needs for ground replacement, or additional needed capacity even after the new digital systems are in place. The additional bandwidth that can be provided via satellite communications can also open the door for many new
Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon
Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....
Geostationary Satellites Collocation aims to find solutions for deploying a safe and reliable collocation control. Focusing on the orbital perturbation analysis, the mathematical foundations for orbit and control of the geostationary satellite are summarized. The mathematical and physical principle of orbital maneuver and collocation strategies for multi geostationary satellites sharing with the same dead band is also stressed. Moreover, the book presents some applications using the above algorithms and mathematical models to help readers master the corrective method for planning station keeping maneuvers. Engineers and scientists in the fields of aerospace technology and space science can benefit from this book. Hengnian Li is the Deputy Director of State Key Laboratory of Astronautic Dynamics, China.
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...
Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.
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…
Worqlul, Abeyou W.; Ayana, Essayas K.; Maathuis, Ben H. P.; MacAlister, Charlotte; Philpot, William D.; Osorio Leyton, Javier M.; Steenhuis, Tammo S.
In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction.
First page Back Continue Last page Overview Graphics. Satellite Communications. Arthur C Clarke wrote a seminal paper in 1945 in wireless world. Use three satellites in geo-synchronous orbit to enable intercontinental communications. System could be realised in '50 to 100 years'
Stumpf, Rick P; Davis, Timothy W.; Wynne, Timothy T.; Graham, Jennifer L.; Loftin, Keith A.; Johengen, T.H.; Gossiaux, D.; Palladino, D.; Burtner, A.
Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates
Tan, Kok Chooi; Lim, Hwee San; Matjafri, Mohd Zubir; Abdullah, Khiruddin
Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.
Kamhawi, Hani; Dankanich, John; Martinez, Andres; Petro, Andrew
The Iodine Satellite (iSat) spacecraft will be the first CubeSat to demonstrate high change in velocity from a primary propulsion system by using Hall thruster technology and iodine as a propellant. The mission will demonstrate CubeSat maneuverability, including plane change, altitude change and change in its closest approach to Earth to ensure atmospheric reentry in less than 90 days. The mission is planned for launch in fall 2017. Hall thruster technology is a type of electric propulsion. Electric propulsion uses electricity, typically from solar panels, to accelerate the propellant. Electric propulsion can accelerate propellant to 10 times higher velocities than traditional chemical propulsion systems, which significantly increases fuel efficiency. To enable the success of the propulsion subsystem, iSat will also demonstrate power management and thermal control capabilities well beyond the current state-of-the-art for spacecraft of its size. This technology is a viable primary propulsion system that can be used on small satellites ranging from about 22 pounds (10 kilograms) to more than 1,000 pounds (450 kilograms). iSat's fuel efficiency is ten times greater and its propulsion per volume is 100 times greater than current cold-gas systems and three times better than the same system operating on xenon. iSat's iodine propulsion system consists of a 200 watt (W) Hall thruster, a cathode, a tank to store solid iodine, a power processing unit (PPU) and the feed system to supply the iodine. This propulsion system is based on a 200 W Hall thruster developed by Busek Co. Inc., which was previously flown using xenon as the propellant. Several improvements have been made to the original system to include a compact PPU, targeting greater than 80 percent reduction in mass and volume of conventional PPU designs. The cathode technology is planned to enable heaterless cathode conditioning, significantly increasing total system efficiency. The feed system has been designed to
M. D. Ramos
Full Text Available Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1 the Tropical Rainfall Measuring Mission (TRMM, (2 the CPC Morphing technique (CMORPH of NOAA and (3 the Global Satellite Mapping of Precipitation (GSMAP and (4 Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN. Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE and Root Mean Square Error (RMSE. In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.
Pelton, Joseph N
The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r
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
Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.
Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.
Satellite based remote sensing supported by air photo and field surveys, provide a means to area covering forest health assessment on a regional scale. Landsat TM data has been extensively used in studies of spruce and fir defoliation in Europe and North America. The temporal coverage of Landsat TM in combination with cloudiness however restrict the availability of data. In this study the LISS-3 sensor onboard the Indian Resource Satellite, IRS-1C, was evaluated for defoliation assessments in Norway spruce (Picea abies) in the central part of Sweden. The near infrared wavelength band proved to be best correlated with mean stand defoliation. After normalisation of satellite data for topographic conditions, the correlation coefficient increased from -0,19 to -0,83. Normalising satellite data for species composition did not improve the results though. The correction coefficients involved in the procedure were originally developed for Landsat TM, and proved to be inadequate for the LISS-3 data set. A thorough examination of the effects of species composition on LISS-3 data is needed to yield better results. The correlation between observed defoliation in the verification stands and predicted (based on the inverse regression function between corrected NIR values and defoliation in reference stands) was 0,70, despite a very limited range of defoliation in the verification set. IRS-1C LISS-3 is fully comparable to Landsat TM for spruce defoliation studies, although the results would probably not be significantly improved 49 refs, 7 figs, 10 tabs
Su, W G; Su, F Z; Zhou, C H
Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively
Easton, Roger L.; Hall, David
Richard Corfield's article “Sputnik's legacy” (October 2007 pp23-27) states that the satellite on board the US Vanguard rocket, which exploded during launch on 6 December 1957 two months after Sputnik's successful take-off, was “a hastily put together contraption of wires and circuitry designed only to send a radio signal back to Earth”. In fact, the Vanguard satellite was developed over a period of several years and put together carefully using the best techniques and equipment available at the time - such as transistors from Bell Laboratories/Western Electric. The satellite contained not one but two transmitters, in which the crystal-controlled oscillators had been designed to measure both the temperature of the satellite shell and of the internal package.
Olsen, Nils; Stolle, Claudia
Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade....... The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites....
Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.
Hesselbrock, Andrew; Minton, David A.
We recently reported that the orbital architecture of the Martian environment allows for material in orbit around the planet to ``cycle'' between orbiting the planet as a ring, or as coherent satellites. Here we generalize our previous analysis to examine several factors that determine whether satellites accreting at the edge of planetary rings will cycle. In order for the orbiting material to cycle, tidal evolution must decrease the semi-major axis of any accreting satellites. In some systems, the density of the ring/satellite material, the surface mass density of the ring, the tidal parameters of the system, and the rotation rate of the primary body contribute to a competition between resonant ring torques and tidal dissipation that prevent this from occurring, either permanently or temporarily. Analyzing these criteria, we examine various bodies in our solar system (such as Saturn, Uranus, and Eris) to identify systems where cycling may occur. We find that a ring-satellite cycle may give rise to the current Uranian ring-satellite system, and suggest that Miranda may have formed from an early, more massive Uranian ring.
Nocerino, E.; Dubbini, M.; Menna, F.; Remondino, F.; Gattelli, M.; Covi, D.
Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper.
Zibordi, G.; Maracci, G.
Monitoring reflectance of polar icecaps has relevance in climate studies. In fact, climate changes produce variations in the morphology of ice and snow covers, which are detectable as surface reflectance change. Surface reflectance can be retrieved from remotely sensed data. However, absolute values independent of atmospheric turbidity and surface altitude can only be obtained after removing masking effects of the atmosphere. An atmospheric correction model, accounting for surface and sensor altitudes above sea level, is described and validated through data detected over Antarctic surfaces with a Barnes Modular Multispectral Radiometer having bands overlapping those of the Landsat Thematic Mapper. The model is also applied in a sensitivity analysis to investigate error induced in reflectance obtained from satellite data by indeterminacy in optical parameters of atmospheric constituents. Results show that indeterminacy in the atmospheric water vapor optical thickness is the main source of nonaccuracy in the retrieval of surface reflectance from data remotely sensed over Antarctic regions
Turcot, Valérie; Lu, Yingchang; Highland, Heather M
In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.......In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article....
Grundle, D S; Löscher, C R; Krahmann, G
A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.......A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper....
Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.
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
Horais, Brian J.
Remote sensing applications and systems, small satellites for sensing missions, and supporting technologies are the broad topics discussed. Particular papers are presented on small satellites for water cycle experiments, low-cost spacecraft buses for remote sensing applications, Webersat (a low-cost imaging satellite), DARPA initiatives in small-satellite technologies, a solid-state magnetic azimuth sensor for small satellites, and thermal analysis of a small expendable tether satellite package. (For individual items see A93-24152 to A93-24175)
Cable, D. A.; Derocher, W. L., Jr.; Cathcart, J. A.; Keeley, M. G.; Madayev, L.; Nguyen, T. K.; Preese, J. R.
A number of areas of research and laboratory experiments were identified which could lead to development of a cost efficient remote, disable satellite recovery system. Estimates were planned of disabled satellite motion. A concept is defined as a Tumbling Satellite Recovery kit which includes a modular system, composed of a number of subsystem mechanisms that can be readily integrated into varying combinations. This would enable the user to quickly configure a tailored remote, disabled satellite recovery kit to meet a broad spectrum of potential scenarios. The capability was determined of U.S. Earth based satellite tracking facilities to adequately determine the orientation and motion rates of disabled satellites.
Since 1972, Landsat satellites have continuously acquired space-based images of the Earth’s land surface, providing data that serve as valuable resources for land use/land change research. The data are useful to a number of applications including forestry, agriculture, geology, regional planning, and education. Landsat is a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). NASA develops remote sensing instruments and the spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and data distribution. The result of this program is an unprecedented continuing record of natural and human-induced changes on the global landscape.
Satellites have been a highly effective platform for multi- form broadcasts. This has led to a ... diversity offormats, languages, genre, and a universal reach that cannot be met by .... programs can be delivered to whom it is intended. In the case of.
Canadian Satellite Communications (Cancom) has as its core business the provision of television and radio signals to cable systems in Canada, with the objective of making affordable broadcast signals available to remote and/or small communities. Cancom also provides direct-to-home services to backyard receiving dishes, as well as satellite digital data business communications services, satellite business television, and satellite network services. Its business communication services range from satellite links for big-city businesses with small branch operations located far from major centers, to a mobile messaging and tracking system for the trucking industry. Revenues in 1992 totalled $48,212,000 and net income was just over $7 million. Cancom bought 10 percent interest in Leosat Corp. of Washington, DC, who are seeking approval to operate a position locator network from low-orbit satellites. Cancom has also become a partner in SovCan Star Satellite Communications Inc., which will build an international satellite system in partnership with Russia. The first satellite in this east-west business network will be placed in a Russian orbital slot over the Atlantic by 1996, and a second satellite will follow for the Pacific region. This annual report of Cancom's activities for 1992 includes financial statements and a six year financial review.
The SRP remote environmental monitoring system consists of separations facilities stack monitors, production reactor stack monitors, twelve site perimeter monitors, river and stream monitors, a geostationary operational environmental satellite (GOES) data link, reactor cooling lake thermal monitors, meteorological tower system, Weather Information and Display (WIND) system computer, and the VANTAGE data base management system. The remote environmental monitoring system when fully implemented will provide automatic monitoring of key stack releases and automatic inclusion of these source terms in the emergency response codes
Pablito M. López-Serrano
Full Text Available Solar radiation is affected by absorption and emission phenomena during its downward trajectory from the Sun to the Earth’s surface and during the upward trajectory detected by satellite sensors. This leads to distortion of the ground radiometric properties (reflectance recorded by satellite images, used in this study to estimate aboveground forest biomass (AGB. Atmospherically-corrected remote sensing data can be used to estimate AGB on a global scale and with moderate effort. The objective of this study was to evaluate four atmospheric correction algorithms (for surface reflectance, ATCOR2 (Atmospheric Correction for Flat Terrain, COST (Cosine of the Sun Zenith Angle, FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes and 6S (Second Simulation of Satellite Signal in the Solar, and one radiometric correction algorithm (for reflectance at the sensor ToA (Apparent Reflectance at the Top of Atmosphere to estimate AGB in temperate forest in the northeast of the state of Durango, Mexico. The AGB was estimated from Landsat 5 TM imagery and ancillary information from a digital elevation model (DEM using the non-parametric multivariate adaptive regression splines (MARS technique. Field reference data for the model training were collected by systematic sampling of 99 permanent forest growth and soil research sites (SPIFyS established during the winter of 2011. The following predictor variables were identified in the MARS model: Band 7, Band 5, slope (β, Wetness Index (WI, NDVI and MSAVI2. After cross-validation, 6S was found to be the optimal model for estimating AGB (R2 = 0.71 and RMSE = 33.5 Mg·ha−1; 37.61% of the average stand biomass. We conclude that atmospheric and radiometric correction of satellite images can be used along with non-parametric techniques to estimate AGB with acceptable accuracy.
Remote viewing is the supposed faculty which enables a percipient, sited in a closed room, to describe the perceptions of a remote agent visiting an unknown target site. To provide convincing demonstration of such a faculty poses a range of experimental and practical problems, especially if feedback to the percipient is allowed after each trial. The precautions needed are elaborate and troublesome; many potential loopholes have to be plugged and there will be strong temptations to relax standards, requiring exceptional discipline and dedication by the experimenters. Most reports of remote viewing experiments are rather superficial and do not permit assessment of the experimental procedures with confidence; in many cases there is clear evidence of particular loopholes left unclosed. Any serious appraisal of the evidence would have to go beyond the reports. Meanwhile the published evidence is far from compelling, and certainly insufficient to justify overthrow of well-established scientific principles.
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.