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Some of the Raman LIDAR applications for monitoring the atmosphere are reviewed. Following a definition of Raman scattering, the basic design of a Raman LIDAR system is described and the atmosphere-monitoring potentialities and limitations of the system are discussed, along with the possibilities of further progress.
The determination of the microstructure, chemical nature, and dynamical evolution of scattering particulates in the atmosphere is considered. A description is given of indirect sampling techniques which can circumvent most of the difficulties associated with direct sampling techniques, taking into account methods based on scattering, extinction, and diffraction of an incident light beam. Approaches for reconstructing the particulate size distribution from the direct and the scattered radiation are discussed. A new method is proposed for determining the chemical composition of the particulates and attention is given to the relevance of methods of solution involving first kind Fredholm integral equations.
To provide guidance for conducting future water monitoring missions over U.S. coasts, aircraft and spacecraft approaches were defined and quantitatively compared. Sensors, aircraft and spacecraft were selected from current or developmental types for the hardware concepts and monitoring was assumed to begin in 1981-1983. Comparative data are presented on capabilities and costs to monitor both recognized pollution sites and broad shelf areas. For these mission requirements, a large fleet of light aircraft provided better coverage and at lower costs generally than one spacecraft, assuming a single, multi-spectral sensor on each platform. This result could change, however, should additional useful sensors with low cost penalties be found for the spacecraft.
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It was shown that a subject can reliably discriminate a difference in video image quality (using a specific commercial product) for image compression levels ranging from 384 kbits per second to 1536 kbits per second. However, their discriminations are significantly influenced by whether or not the TV camera is stable or moving and whether or not the animals are quiescent or active, which is correlated with illumination level (daylight versus night illumination, respectively). The highest video rate used here was 1.54 megabits per second, which is about 18 percent of the so-called normal TV resolution of 8.4MHz. Since this video rate was judged to be acceptable by 27 of the 34 subjects (79 percent), for monitoring the general health and status of small animals within their illuminated (lights on) cages (regardless of whether the camera was stable or moved), it suggests that an immediate Space Station Freedom to ground bandwidth reduction of about 80 percent can be tolerated without a significant loss in general monitoring capability. Another general conclusion is that the present methodology appears to be effective in quantifying visual judgments of video image quality.
This study aims to provide accurate information about changes in agricultural systems (AS) using phenological metrics derived from the NDVI time series. Use of such information could help land managers optimize land use choices and monitor the status of agricultural lands, under a variety of environmental and socioeconomic conditions. For this purpose, the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data were used to derive phenological metrics over the Oum Er-Rbia basin (central Morocco). Random forest (RF), support vector machine (SVM), and K-nearest neighbor (KNN) classifiers were explored and compared on their ability to classify AS classes over the study area. Four main AS classes have been considered: (1) irrigated annual crop (IAC), (2) irrigated perennial crop (IPC), (3) rainfed area (RA), and (4) fallow (FA). By comparing the accuracy of the three classifiers, the RF method showed the best performance with an overall accuracy of 0.97 and kappa coefficient of 0.96.The RF method was then chosen to examine time variations in AS over a 16-year period (2000–2016). The AS main variations were detected and evaluated for the four AS classes. These variations have been found to be linked well with other indicators of local agricultural land management, as well as the historical agricultural drought changes over the study area. Overall, the results present a tool for decision makers to improve agricultural management and provide a different perspective in understanding the spatiotemporal dynamics of agricultural systems.
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A remote water monitoring system is described that integrates the functions of sampling, sample preservation, sample analysis, data transmission and remote operation. The system employs a floating buoy carrying an antenna connected by lines to one or more sampling units containing several sample chambers. Receipt of a command signal actuates a solenoid to open an intake valve outward from the sampling unit and communicates the water sample to an identifiable sample chamber. Such response to each signal receipt is repeated until all sample chambers are filled in a sample unit. Each sample taken is analyzed by an electrochemical sensor for a specific property and the data obtained is transmitted to a remote sending and receiving station. Thereafter, the samples remain isolated in the sample chambers until the sampling unit is recovered and the samples removed for further laboratory analysis.
A remote maintenance monitoring system retrofits to a given hardware device with a sensor implant which gathers and captures failure data from the hardware device, without interfering with its operation. Failure data is continuously obtained from predetermined critical points within the hardware device, and is analyzed with a diagnostic expert system, which isolates failure origin to a particular component within the hardware device. For example, monitoring of a computer-based device may include monitoring of parity error data therefrom, as well as monitoring power supply fluctuations therein, so that parity error and power supply anomaly data may be used to trace the failure origin to a particular plane or power supply within the computer-based device. A plurality of sensor implants may be rerofit to corresponding plural devices comprising a distributed large-scale system. Transparent interface of the sensors to the devices precludes operative interference with the distributed network. Retrofit capability of the sensors permits monitoring of even older devices having no built-in testing technology. Continuous real time monitoring of a distributed network of such devices, coupled with diagnostic expert system analysis thereof, permits capture and analysis of even intermittent failures, thereby facilitating maintenance of the monitored large-scale system.
The remote monitoring of atmospheric pollutants can now be performed in several ways. Laser radar techniques have proven their ability to reveal the spatial distribution of different species or particles. Classical optical techniques can also be used, but yield the average concentration over a given path and hence no range resolution. One such technique is Differential Optical Absorption Spectroscopy, DOAS. Such schemes can be used to monitor paths that a preliminary lidar investigation has shown to be of interest. Having previously had access to a mobile lidar system, a new system has been completed. The construction builds on experience from using the other system and it is meant to be more of a mobile optical laboratory than just a lidar system. A complete system description is given along with some preliminary usage. Future uses are contemplated.
This presentation is part of the Independent Science Board of the State of California Delta Stewardship Council brown bag seminar series on the "How the Delta is Monitored", followed with a panel discussion. Various remote sensing approaches for aquatic vegetation will be reviewed. Key research and application issues with remote sensing monitoring in the Delta will be addressed.
Automated system gives new life to aging network of computers. Remote maintenance monitoring system developed to diagnose problems in large distributed computer network. Consists of data links, displays, controls, software, and more than 200 computers. Uses sensors to collect data on failures and expert system to examine data, diagnose causes of failures, and recommend cures. Designed to be retrofitted into launch processing system at Kennedy Space Center. Reduces downtime, lowers workload and expense of maintenance, and makes network less dependent on human expertise.
The capability of very long baseline interferometry (VLBI) to monitor the stability of remotely located hydrogen maser frequency standards has been demonstrated by a series of experiments conducted between Deep Space Stations in Australia, Spain, and California. The measured stabilities of the clock systems, over approximately 10 day intervals, were 1 to 3 parts in 10 to the 13th power, with the instabilities due to the oscillators, the clock distribution systems, the receiving system delays, and the VLBI measurement error. Experiments were conducted independently using two different systems (BLOCK 0 and WBDAS). Later comparison shows agreement on the order of 1 part in 10 to the 13th power. Closure was demonstrated on three separate occasions to 33, 10, and 13 ns with an error uncertainty of + or - 42 ns. The results represent an important consistency check on VLBI measurements.
'Telescience', defined as the ability of distributed system users to perform remote operations associated with NASA Space Station life science operations, has been explored by a developmental testbed project allowing rapid prototyping to evaluate the functional requirements of telescience implementation in three areas: (1) research planning and design, (2) remote operation of facilities, and (3) remote access to data bases for analysis. Attention is given to the role of expert systems in telescience, its use in realistic simulation of Space Shuttle payload remote monitoring, and remote interaction with life science data bases.
Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.
Remote sensing estimates of area average precipitation are useful to agricultural and climatological applications. Estimates obtained by active or passive microwaves, infrared and visible sensors may be augmented and improved using indirect measures of precipitation, such as the change in near surface soil moisture content caused by a particular event. Measurements of soil moisture using infrared radiances do not provide precipitation information in real time since the sky must clear. However, the resultant estimate of precipitation is a time integrated value which provides a significant savings in data handling and can overcome virtually all of the sampling problems associated with the monitoring of precipitation through storms of long duration.
Electronic central monitoring system, called Remote Monitor Alarm System, RMAS, used to monitor malfunction alarms and power supplies of remotely located equipment modules of transmitting and receiving equipment in fiber-optic communication network at Kennedy Space Center. Includes central monitoring unit at location convenient for technicians, plus remote terminal unit at each remote site containing equipment to be monitored.