Satellite Communications Part 8 ppt

Mapping and Estimation of Chemical Concentrations in Surface Soils Using LANDSAT TM Satellite Imagery 201 Ben-Dor, E. & Banin, A. (1995) Near infrared analysis (NIRA) as a method to simultaneously evaluate spectral featureless constituents in soils. Soil Sci, Vol.4, pp.259-270. Bergkvist, P.; Jarvis, N.; Berggren, D. & Carlgren, K. (2003) Long-term effects of sewage sludge applications on soil properties, cadmium availability and distribution in arable soil. Agric. Ecosyst. Environ, Vol.97, pp.167-179. Bogrekci, I. & Lee, W.S. (2005) Spectral soil signatures and sensing phosphorus. Biosyst. Eng, Vol.92, pp.527-533. Bogrekci, I. & Lee, W.S. (2007) Comparison of ultraviolet, visible and near infrared sensing for soil phosphorus. Biosyst. Eng, Vol.96, pp.293-299. Chang, A.C.; Page, A.L.; Sutherland, F.H. & Grgurevic, E. (1983) Fractionation of phosphorus in sludge affected soils. J. Environ. Qual, Vol.12, pp.286-290. Chang, C.W.; Laird, D.A.; Mausbach, M.J. & Hurburgh, Jr C.R. (2001) Near-infrared reflectance spectroscopy – principal component regression analysis of soil properties. Soil Sci. Soc. Am. J, Vol.65, pp.480-490. Chen, F.; Kissel, D.E.; West, L.T. & Adkins, W. (2000) Field-scale mapping of surface soil organic carbon using remotely sensed imagery. Soil Sci. Soc. Am. J, Vol.64, pp.746- 753. Dalal, R.C. & Henry, R.J. (1986) Simultaneous determination of moisture, organic carbon, and total nitrogen by near infrared reflectance spectrophotometry. Soil Sci. Soc. Am. J, Vol.50, pp.120-123. Dematte, J.A.M.; Pereira, H.S.; Nanni, M.R.; Cooper, M. & Fiora, P.R. (2003) Soil chemical alterations promoted by fertilizer application assessed by spectral reflectance. Soil Sci, Vol.168, pp.730-747. Durbin, J. & Watson, G.S. (1951) Testing for serial correlation in least squares regression: II. Biometrica, Vol.38, pp.159-178. Epstein, E.; Taylor, J.M. & Chaney, R.L. (1975) Effects of sewage sludge on some soil physical properties. J. Environ. Qual, Vol.4, pp.139-142. Henderson, T.L.; Baumgardner, M.F.; Franzmeieir, D.P.; Stott, D.E & Coster, D.C. (1992) High dimensional reflectance analysis of soil organic matter. Soil Sci. Soc. Am. J, Vol.56, pp.865-872. Ji, J.F.; Balsam, W.L.; Chen, J. & Liu, L.W. (2002) Rapid and quantitative measurement of hematite and goethite in the Chinese Loess-Paleosol sequence by diffuse reflectance spectroscopy. Clay Miner, Vol.50, pp.208-216. Lobell, D.B. & Asner, G.P. (2002) Moisture effects on soil reflectance. Soil Sci. Soc. Am. J, Vol.66, pp.722-727. Maguire, R.O.; Sims, J.T. & Coale, F.J. (2000) Phosphorus fractionation in biosolids–amended soils: Relationship to soluble and desorbable phosphorus. Soil Sci. Soc. Am. J, Vol.64, pp.2018-2024. Mantovi P, Baldoni G, Toderi G. Reuse of liquid, dewatered, and composted sewage sludge on agricultural land: effects of long-term application on soil and crop. Water Res. 2005; Vol.39, pp.289-296. McNulty, W.S. (2005) The creation of a GIS database and the determination of sludge’s spectral signature in an agricultural setting. M.S. Thesis. Department of Geology, Bowling Green State University, Bowling Green, OH, USA. MINITAB Statistical Software Version 15. State College, PA: MINITAB Inc.; 2007-2008. Morra, M.J.; Hall, M.H. & Freeborn, L.L. (1991) Carbon and nitrogen analysis of soil fractions using near infrared reflectance spectroscopy. Soil Sci. Soc. Am. J, Vol.55, pp.288-291. Nanni, M.R. & Dematte, J.A.M. (2006) Spectral reflectance methodology in comparison to traditional soil analysis. Soil Sci. Soc. Am. J, Vol.70, pp.393-407. New York Times (2008) Tennessee ash flood larger than initial estimate, Published on December 26, 2008, URL: http://www.nytimes.com/2008/12/27/us/27sludge. html? _r=2&ref=us (last date accessed: 1 July 2009). Nyamangara, J. & Mzezewa, J. (1999) The effect of long-term sewage sludge application on Zn, Cu, Ni and Pb levels in a clay loam soil under pasture grass in Zimbabwe. Agric. Ecosyst. Environ, Vol.73, pp.199-204. Page, A.L.; Elseewi, A.A. & Straughan, I.R. (1979) Physical and chemical properties of fly ash from coal-fired power plants with special reference to environmental impacts. Residue Reviews, Vol.71, pp.83-120. Post, D.F.; Fimbres, A.; Matthias, A.D.; Sano, E.E.; Accioly, L.; Batchily, A.K. & Ferreira, L.G. (2000) Predicting soil albedo from soil color and spectral reflectance data. Soil Sci. Soc. Am. J, Vol.64, pp.1027-1034. Reeves, III J.B.; McCarty, G.W.; Mimmo, T. (2002) The potential of diffuse reflectance spectroscopy for the determination of carbon inventories in soil. Environ. Pollut. Vol.116, pp.S264-S277. SAS Institute. SAS Software Version 9.1. Cary, NC: SAS Institute, Inc.; 2002-2003. Shober, A.L. & Sims, J.T. (2003) Phosphorus restrictions for land application of biosolids: current status and future trends. J. Environ. Qual, Vol.32, pp.1955-1964. Singh, R.P. & Agrawal, M. (2008) Potentail benefits and risks of land application of sewage sludge. Waste Management, Vol.28, pp.347-358. Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. Web Soil Survey. http://websoilsurvey.nrcs.usda.gov. 2007. Sommers, L.E. (1977) Chemical composition of sewage sludges and analysis of their potential use as fertilizers. J. Environ. Qual, Vol.6, pp.225-232. Sridhar, B.B.M. & Vincent, R.K. (2009) Mapping and estimation of phosphorus and copper concentrations in fly ash spill area using LANDSAT TM Images. Photogrammetric Engineering and Remote Sensing, Vol.75, Nb.9, pp.1030-1033. Sridhar, B.B.M.; Vincent, R.K.; Witter, J.D. & Spongberg, A.J. (2009) Mapping the total phosphorus concentration of biosolid amended surface soils using LANDSAT TM data. Science of Total Environment, Vol.47, pp.2894-2899. Sullivan, D.G.; Shaw, J.N. & Rickman, D. (2005) IKONOS imagery to estimate surface soil property variability in two Alabama physiographies. Soil Sci. Soc. Am. J, Vol.69, pp.1789-1798. Tennessee Valley Authority (2009) Corrective Action Plan for the TVA Kingston Fossil Plant Ash Release, URL: http://www.tva.gov/kingston/cap/ TVA_ Corrective _ Action_ Plan_Draft _D5.pdf (last date accessed: 1 July 2009). Tetra Tech EM Inc. (2009) Final CERCLA emergency response report, Kingston fossil plant Fly ash response Harriman, Roane County, Tennessee Tetra Tech Inc. Soil and ash sampling results Kingston fossil fly ash response Harriman, Roane County, Tennessee, URL: http://www.epaosc.org/sites/4642/files/ erfinal reporttvakingston.pdf (last date accessed: 1 July 2009). Satellite Communications202 U. S. Environmental Protection Agency. Standards for the use or disposal of sewage sludge. Office of Water, Washington D. C, 2002. U. S. Environmental Protection Agency. Test methods for evaluating solid waste. Office of Solid Waste and Emergency Response, Washington D. C, 1998. Udom, B.E.; Mbagwu, J.S.C.; Adesodun, J.K. & Agbim, N.N. (2004) Distributions of zinc, copper, cadmium and lead in a tropical ultisol after long-term disposal of sewage sludge. Environ. Int. Vol.30, pp.467-470. Varvel, G.E.; Schlemmer, M.R. & Schepers, J.S. (1999) Relationship between spectral data from an aerial image and soil organic matter and phosphorus levels. Precision Agric, Vol.1, pp.291-300. Vincent, R.K. (1997) Fundametals of geological and environmental remote sensing. Prentice Hall, Upper Saddle River, NJ. Vincent, R.K. (2000) Forecasts of monthly averaged daily temperature highs in Bowling Green, Ohio from monthly sea surface temperature anomalies in Eastern Pacific ocean during the previous year. Photogramm. Eng. Remote Sens, Vol.66, pp.1001- 1009. Vincent, R.K.; Qin, X.; McKay, R.M.L.; Miner, J.; Czajkowski, K.; Savino, J. & Bridgeman, T. (2004) Phycocyanin detection from LANDSAT TM data for mapping cyanobacterial blooms in Lake Erie. Remote Sens. of Environ, Vol.89, pp.381-392. Wei, Q.F.; Lowery, B. & Peterson, A.E. (1985) Effect of sludge application on physical properties of a silty clay loam soil. J. Environ. Qual, Vol.14, pp.178-180. OLFISH - A complete, paperless solution for the collection, management and dissemination of marine data 203 OLFISH - A complete, paperless solution for the collection, management and dissemination of marine data Dr. Amos Barkai, Fatima Felaar, Karl Geggus, Zahrah Dantie and Arno Hayes X OLFISH - A complete, paperless solution for the collection, management and dissemination of marine data Dr. Amos Barkai, Fatima Felaar, Karl Geggus, Zahrah Dantie and Arno Hayes Olrac (Ocean Land Resource Assessment Consultants) South Africa 1. Introduction Fisheries management is continually frustrated by the lack, or poor quality, of critical data on fishing operations (catches, duration, gear, locations and relevant environmental conditions). While quantitative methods for managing fisheries have developed with considerable complexity, the quality of the available data remains an obstacle for meaningful advances in fisheries management. There are a number of aspects to the problem, not all of which are technical. A culture of protecting catch data and disinformation is common amongst fishers, fishing companies and even formal state-run offices, and significant education is needed in order to change this culture. Another problem is the poor quality of historic data in many fisheries around the world. Much energy is wasted and important opportunities lost because of the uncertainty surrounding crucial historic data. For example, there are typically many factors related to catch-per-unit-effort data, a key index of trends in resource abundance, which are not recorded, and hence cannot be incorporated into statistical analyses. Frequently, these missing data are crucial to management decisions. For scientists, unreliable data leads to a poor basis for stock assessment models and management programs. For industry, the lack of sound data significantly reduces its fishing efficiency, since past performance cannot be studied properly. As a result, poor management decisions based on unreliable analyses are made, often with substantial cost and risk to fish resources and the fishing industry. Although there is presently greater awareness amongst scientists and fisheries managers about the importance of collecting fishing data, there is still confusion about exactly which data are needed, and how to collect and store them. It is common for skippers to record scientific data on one form, for shore managers to use another for commercial purposes, and for skippers to keep separate fishing logbooks. These data are then transferred to different computer systems, often complex spreadsheets, or, sometimes, are left in paper format in large, inaccessible books and files. There is a degradation in the quality of data because of the multi-stage process of transcription from handwritten logbook sheets to paper forms and then to computer databases. 11 Satellite Communications204 So even when good will is present, technically, the absence of a flexible and comprehensive system for capturing essential data during fishing operations is a major obstacle. A large amount of logistical and environmental data is lost simply because of the difficulty of recording this information easily in real time. This is despite the advent of a complex array of sensory equipment available in the bridge of modern fishing vessels. As a result, environmental patterns become part of a skipper’s experience and seldom, if ever, become formally available to scientists or managers of fishing operations. The most logical first point of data entry, through the fishing vessel skipper, should occur in digital format directly into a computer. One of the difficulties with fisheries data is the complexity of the logical linkages between the different types of data. Any reasonable approach to the problem requires the use of modern relational databases which are able to address the multidimensional complexity of the problem. In order to address many of the problems described above, Olrac (www.olrac.com) a South African company, has developed a data collection and management system it has named Olfish (www.olfish.com) for the specific use of operators and managers in the marine environment with a special focus on the commercial fishing industry. 2. Electronic Logbooking 2.1 Benefits An obvious approach to the “data crises” is to bring modern data and information technology (Elog) to the marine environment in general, and to the commercial and recreational fishing industry in particular. Providing fishers with accurate yet easy to use data logging tools could potentially transform the entire fishing fleet and the fishers community into the largest surveyors group of the marine environment in the world. The calibre of data produced through electronic logbooks has the potential to benefit all sectors of the fishing industry, from the fishers themselves to seafood consumers, resource managers, scientists and government enforcement agencies in between. In addition, the international shift towards a greater emphasis on output control measures, such as annual catch limits (ACL’s) and total allowable catches (TAC’s), requires the implementation of sophisticated catch monitoring tools in order to allow for a near-real-time auditing of catch versus TAC. However, it is important to note that the benefits of electronic data logging go beyond merely adhering to regulations. It is crucial for the industry to realise that it will ultimately be the greatest beneficiary of accumulated good quality data. A few obvious benefits derived from the collection of a large amount of accurate data in a near-real-time environment are: 2.1.1 Better Stock Assessments The accuracy and timely delivery of electronically recorded data will allow for more exact indications of catch in a current year. In the past, due to the delays of paper-based reporting, incomplete data from preceding years has been used to estimate the TAC of the following year. The uncertainty associated with such calculations has resulted in conservative stock assessments which lead to overly restrictive TAC’s. This means that there is often an over- discard of fish which would otherwise be commercially viable. Electronic data logging would allow for up-to-date and accurate data to be used for TAC estimation, thus eliminating much uncertainty and adding weight and justification to the TAC’s allocated. 2.1.2 Better Targeting and Gear Utilization The security and verification features of electronic logbooks, (see Security and Data Integrity – 5.4.7 below), as well as multimedia photographic and video utilities (see Multinote Taker and Notebook – 6.2 below), can potentially replace the role of an observer onboard a vessel. This can then be adapted into an incentive scheme for improved gear and fishing-ground selectivity, thus reducing unintended bycatch. Capturing target species may also lead to a decrease in days at sea, which is often beneficial for the skipper. 2.1.3 Faster Transmission Faster transmission of information from sea to shore allows for “on-time reaction”, i.e. decisions made on a regulatory, managerial, commercial or environmental basis are relevant to what is actually happening at sea. Back-logged, non-electronic reporting means that any event at sea is only registered on shore sometimes up to several weeks after it has occurred. Responding to month-old information, particularly in an ever-dynamic ocean environment, is practically pointless. Faster transmission will have a substantially positive effect on, for example, quota management, conservation and even commercial decision-making. 2.1.4 Catch Prediction and Management Built-in analytical tools available within electronic logbook software (see Olfish Explorer - 6.4 below) are able to harness historical information stored in their electronic databases to help fishers calculate and predict fish migration, fishing hotspots etc. This greatly increases efficiency in a number of fields, such as targeting areas and the selection of fishing grounds and techniques. Similarly, fishers will be able to avoid “dry” areas, maximizing their time at sea and ultimately reducing discarding rates. 2.1.5 Traceability Traceability is the ability to locate the source and “journey” of a fish from ocean to supermarket shelf. Legal organizations, such as the Marine Stewardship Council, prohibit fish without certification logos from entering the market. Such logos are obtained through traceability, i.e. proving that the fish in question had been caught in a certified area under certified conditions. Electronic data logging makes traceability a simple and speedy process. Information from the vessel at sea can be efficiently transmitted to market authorities who can then clear the catch for sale. Furthermore, electronic data logging allows for a highly detailed recording of catch information. Thus, catch freshness can easily be proven, increasing its market value. Buyers then benefits from being able to accurately estimate the shelf-life of the product they have bought. None of this would be possible without verifiable and immediate traceability. 2.2 The Olfish System: A Short Overview Olfish is a third-generation, data logging and data management, software tool which was initially developed for the commercial fishing industry, but now provides a complete solution for the collection, management and reporting of other vessel-based activities, such as commercial and recreational fishing trips, oceanographic surveys, marine inspections, cargo and service trips, surveillance missions, etc. OLFISH - A complete, paperless solution for the collection, management and dissemination of marine data 205 So even when good will is present, technically, the absence of a flexible and comprehensive system for capturing essential data during fishing operations is a major obstacle. A large amount of logistical and environmental data is lost simply because of the difficulty of recording this information easily in real time. This is despite the advent of a complex array of sensory equipment available in the bridge of modern fishing vessels. As a result, environmental patterns become part of a skipper’s experience and seldom, if ever, become formally available to scientists or managers of fishing operations. The most logical first point of data entry, through the fishing vessel skipper, should occur in digital format directly into a computer. One of the difficulties with fisheries data is the complexity of the logical linkages between the different types of data. Any reasonable approach to the problem requires the use of modern relational databases which are able to address the multidimensional complexity of the problem. In order to address many of the problems described above, Olrac (www.olrac.com) a South African company, has developed a data collection and management system it has named Olfish (www.olfish.com) for the specific use of operators and managers in the marine environment with a special focus on the commercial fishing industry. 2. Electronic Logbooking 2.1 Benefits An obvious approach to the “data crises” is to bring modern data and information technology (Elog) to the marine environment in general, and to the commercial and recreational fishing industry in particular. Providing fishers with accurate yet easy to use data logging tools could potentially transform the entire fishing fleet and the fishers community into the largest surveyors group of the marine environment in the world. The calibre of data produced through electronic logbooks has the potential to benefit all sectors of the fishing industry, from the fishers themselves to seafood consumers, resource managers, scientists and government enforcement agencies in between. In addition, the international shift towards a greater emphasis on output control measures, such as annual catch limits (ACL’s) and total allowable catches (TAC’s), requires the implementation of sophisticated catch monitoring tools in order to allow for a near-real-time auditing of catch versus TAC. However, it is important to note that the benefits of electronic data logging go beyond merely adhering to regulations. It is crucial for the industry to realise that it will ultimately be the greatest beneficiary of accumulated good quality data. A few obvious benefits derived from the collection of a large amount of accurate data in a near-real-time environment are: 2.1.1 Better Stock Assessments The accuracy and timely delivery of electronically recorded data will allow for more exact indications of catch in a current year. In the past, due to the delays of paper-based reporting, incomplete data from preceding years has been used to estimate the TAC of the following year. The uncertainty associated with such calculations has resulted in conservative stock assessments which lead to overly restrictive TAC’s. This means that there is often an over- discard of fish which would otherwise be commercially viable. Electronic data logging would allow for up-to-date and accurate data to be used for TAC estimation, thus eliminating much uncertainty and adding weight and justification to the TAC’s allocated. 2.1.2 Better Targeting and Gear Utilization The security and verification features of electronic logbooks, (see Security and Data Integrity – 5.4.7 below), as well as multimedia photographic and video utilities (see Multinote Taker and Notebook – 6.2 below), can potentially replace the role of an observer onboard a vessel. This can then be adapted into an incentive scheme for improved gear and fishing-ground selectivity, thus reducing unintended bycatch. Capturing target species may also lead to a decrease in days at sea, which is often beneficial for the skipper. 2.1.3 Faster Transmission Faster transmission of information from sea to shore allows for “on-time reaction”, i.e. decisions made on a regulatory, managerial, commercial or environmental basis are relevant to what is actually happening at sea. Back-logged, non-electronic reporting means that any event at sea is only registered on shore sometimes up to several weeks after it has occurred. Responding to month-old information, particularly in an ever-dynamic ocean environment, is practically pointless. Faster transmission will have a substantially positive effect on, for example, quota management, conservation and even commercial decision-making. 2.1.4 Catch Prediction and Management Built-in analytical tools available within electronic logbook software (see Olfish Explorer - 6.4 below) are able to harness historical information stored in their electronic databases to help fishers calculate and predict fish migration, fishing hotspots etc. This greatly increases efficiency in a number of fields, such as targeting areas and the selection of fishing grounds and techniques. Similarly, fishers will be able to avoid “dry” areas, maximizing their time at sea and ultimately reducing discarding rates. 2.1.5 Traceability Traceability is the ability to locate the source and “journey” of a fish from ocean to supermarket shelf. Legal organizations, such as the Marine Stewardship Council, prohibit fish without certification logos from entering the market. Such logos are obtained through traceability, i.e. proving that the fish in question had been caught in a certified area under certified conditions. Electronic data logging makes traceability a simple and speedy process. Information from the vessel at sea can be efficiently transmitted to market authorities who can then clear the catch for sale. Furthermore, electronic data logging allows for a highly detailed recording of catch information. Thus, catch freshness can easily be proven, increasing its market value. Buyers then benefits from being able to accurately estimate the shelf-life of the product they have bought. None of this would be possible without verifiable and immediate traceability. 2.2 The Olfish System: A Short Overview Olfish is a third-generation, data logging and data management, software tool which was initially developed for the commercial fishing industry, but now provides a complete solution for the collection, management and reporting of other vessel-based activities, such as commercial and recreational fishing trips, oceanographic surveys, marine inspections, cargo and service trips, surveillance missions, etc. Satellite Communications206 The present version of Olfish includes three basic components in order to cater for the entire data flow, from at-sea collection to the generation and dissemination of reports. The onboard, data collection component named Olfish Dynamic Data Logger (Olfish-DDL) is a standalone data collection tool installed onboard the vessel’s PC. Olfish-DDL also has a shore component which is identical to the vessel version but allows data from many vessels to be stored and viewed on one user-interface. This component is available in two versions: a. A Single Fleet unit that aggregates operational data from vessels of a single company or organisation. b. A Meta-Shore unit, which can aggregate operational data received from many shore units. The Meta-Shore unit can be used by a government agency, fishing association or even a union of states to manage data from a number of countries/states.  DatabaseServer OtherPermitted DataRecipients Reports Management System(RMS) XMLSchema Validation WebServer XML Web Services RMS WebPortal VMS SATCOM GPS FirstSales www.olfish.com Fig. 1. Overall structure of the Olfish data collection and management system The third component of Olfish is a web application named Olfish- Report Management System (Olfish-RMS™) and its main function is to receive, store and disseminate reports coming from Olfish-DDL (or, if necessary, other, third party, data logging systems). Olfish- RMS also allows for the direct entry of data via an internet interface for cases where the use of an onboard data-logger is not practical (cost or unsuitable working environment). With Olfish-RMS the entire fleet of vessels can be managed. It includes a vessel registry, a full quota management system and an elaborate administrative component which allows Olfish- RMS to be customised to satisfy many needs. 2.3 Olfish Dynamic Data Logger 2.3.1 Basic Functionality Olfish-DDL is a touch-screen-ready utility that captures data in real-time and/or after the fishing activity has taken place. Olfish-DDL can read GPS input via an additional GPS logging utility and it incorporates GIS capabilities for easy viewing of vessel movements and other operational fishing data. With Olfish-DDL, the user can collect any type of data in any form. These include images, video clips, numerical and alphanumeric fields, free text comments, date, time, location, etc. Olfish allows data to be inserted from guiding images (“infograph”) to guide it through complex data entry needs. Each mode of data entry has its own unique data entry interface, specifically designed for the type of data recorded. Olfish- DDL is highly customisable and can be easily modified to address vastly different data recording and reporting needs. Fig. 2. Olfish vessel unit on a tablet PC OLFISH - A complete, paperless solution for the collection, management and dissemination of marine data 207 The present version of Olfish includes three basic components in order to cater for the entire data flow, from at-sea collection to the generation and dissemination of reports. The onboard, data collection component named Olfish Dynamic Data Logger (Olfish-DDL) is a standalone data collection tool installed onboard the vessel’s PC. Olfish-DDL also has a shore component which is identical to the vessel version but allows data from many vessels to be stored and viewed on one user-interface. This component is available in two versions: a. A Single Fleet unit that aggregates operational data from vessels of a single company or organisation. b. A Meta-Shore unit, which can aggregate operational data received from many shore units. The Meta-Shore unit can be used by a government agency, fishing association or even a union of states to manage data from a number of countries/states.  DatabaseServer OtherPermitted DataRecipients Reports Management System(RMS) XMLSchema Validation WebServer XML Web Services RMS WebPortal VMS SATCOM GPS FirstSales www.olfish.com Fig. 1. Overall structure of the Olfish data collection and management system The third component of Olfish is a web application named Olfish- Report Management System (Olfish-RMS™) and its main function is to receive, store and disseminate reports coming from Olfish-DDL (or, if necessary, other, third party, data logging systems). Olfish- RMS also allows for the direct entry of data via an internet interface for cases where the use of an onboard data-logger is not practical (cost or unsuitable working environment). With Olfish-RMS the entire fleet of vessels can be managed. It includes a vessel registry, a full quota management system and an elaborate administrative component which allows Olfish- RMS to be customised to satisfy many needs. 2.3 Olfish Dynamic Data Logger 2.3.1 Basic Functionality Olfish-DDL is a touch-screen-ready utility that captures data in real-time and/or after the fishing activity has taken place. Olfish-DDL can read GPS input via an additional GPS logging utility and it incorporates GIS capabilities for easy viewing of vessel movements and other operational fishing data. With Olfish-DDL, the user can collect any type of data in any form. These include images, video clips, numerical and alphanumeric fields, free text comments, date, time, location, etc. Olfish allows data to be inserted from guiding images (“infograph”) to guide it through complex data entry needs. Each mode of data entry has its own unique data entry interface, specifically designed for the type of data recorded. Olfish- DDL is highly customisable and can be easily modified to address vastly different data recording and reporting needs. Fig. 2. Olfish vessel unit on a tablet PC Satellite Communications208 2.3.2 Overall Structure Olfish-DDL consists of the following:  Configuration files defining levels, fields, parameters  Database for working data  Database for archived data  User interface elements: Data Entry, Data Browser, Mapper, Data Centre, Mini Reporter, Explorer  Input/output modules for the following types of data: a. Reports to specific agencies and third-parties b. Import / export of operational data c. Backup of the complete system d. Error / exception handling reports to Olfish Support There are two main levels of configuration in Olfish-DDL: User interface: This is a developer-level configuration which governs the way the command bar menu (Dynamic Commands Bar – DCB) functions, based on client specific needs. Field and lookup values: As a business model, Olrac ships Olfish-DDL with as many predefined fields as possible. However, within Olfish-DDL, the user can:  modify field parameters, such as: display names, maximum and minimum values, set mandatory and carry over fields, capture on start/on end, make visible etc. Olfish-DDL ensures that changes which could affect underlying data capture logic are not allowed.  hide and show lookup table records.  add, edit and delete lookup table records.  add fields – these fields have as much functionality and legitimacy as any original predefined fields.                  GPS Logger MapperData Browser Data Entry   WorkingStore  DB Archive Mail Reporter Data Centre Explorer User Config. IP SMTO MAPI Satellite Physical Media Reports (toagencies etc.) Import/ Export(to otherOlfish Units) Backup Error/ Exception Config. From Olfish Fig. 3. Olfish-DDL basic structure Ol dr o sa v W h ea s co n ar e w h ‘tr i us e of Fi g A n to co n ba to t ac t su r fish-DDL make s o pdown lists to v in g time. Howe v h ile Olfish-DDL s il y confi g ured n fi g uration. Wit h e compulsor y an d h ich data fields s i p start’, ‘trip e n e rs to set up up p t y pos. g . 4. Olfish-DDL l n other feature of O “intelli g entl y ” n fi g ured to refle c sic underl y in g u s t all y dif f erent fo r t ivities (sea-far m r ve y s, etc.). s extensive use enter data helps v er, new fields a n is normall y shi p to fit the “tas t h Olfish-DDL, th d which are rem e s hould be visibl e n d’ and, within a p er and lower li m l ookup table cus t O lfish-DDL is a D g uide the user c t data lo gg in g a c s er interface can r ms of fishin g ( t m s maintenance, of dropdown to maintain da t n d values can be a p ped with the cli e t e” and needs o e user can decid e mbered from p r e in which phas e a trip activit y , ‘s t m its for an y num e t omisation form Dy namic Comm a durin g its dat a c tions of vastl y d i have different D t rawl, lon g line, p car g o deliver y , lists whenever t a inte g rit y , thus a dded b y users i f e nt’s basic user c o f different us e e which fields s h r evious entries. T h e of the vessel o p t art’ and ‘end’. O e rical field in ord e a nds Bar (DCB) w a lo gg in g activi t i fferent activities . D CBs and can be p urse seine, tra p coastal g uard p possible. The u minimisin g t y p o f necessar y . c onfi g uration, it e rs of the same h ould be visible, h e user can also p eration. Examp l O lfish-DDL also e r to reduce the c w hich can be conf i t ies. The DCB c . For example, th e used to collect d p s, etc.) or other p atrols, oceano g u se of o s and can be basic which decide l es are allows c hance ig ured c an be e same ata for vessel g raphic OLFISH - A complete, paperless solution for the collection, management and dissemination of marine data 209 2.3.2 Overall Structure Olfish-DDL consists of the following:  Configuration files defining levels, fields, parameters  Database for working data  Database for archived data  User interface elements: Data Entry, Data Browser, Mapper, Data Centre, Mini Reporter, Explorer  Input/output modules for the following types of data: a. Reports to specific agencies and third-parties b. Import / export of operational data c. Backup of the complete system d. Error / exception handling reports to Olfish Support There are two main levels of configuration in Olfish-DDL: User interface: This is a developer-level configuration which governs the way the command bar menu (Dynamic Commands Bar – DCB) functions, based on client specific needs. Field and lookup values: As a business model, Olrac ships Olfish-DDL with as many predefined fields as possible. However, within Olfish-DDL, the user can:  modify field parameters, such as: display names, maximum and minimum values, set mandatory and carry over fields, capture on start/on end, make visible etc. Olfish-DDL ensures that changes which could affect underlying data capture logic are not allowed.  hide and show lookup table records.  add, edit and delete lookup table records.  add fields – these fields have as much functionality and legitimacy as any original predefined fields.                  GPS Logger MapperData Browser Data Entry   WorkingStore  DB Archive Mail Reporter Data Centre Explorer User Config. IP SMTO MAPI Satellite Physical Media Reports (toagencies etc.) Import/ Export(to otherOlfish Units) Backu p  Error/ Exce p tion Config. From Olfish Fig. 3. Olfish-DDL basic structure Ol dr o sa v W h ea s co n ar e w h ‘tr i us e of Fi g A n to co n ba to t ac t su r fish-DDL make s o pdown lists to v in g time. Howe v h ile Olfish-DDL s il y confi g ured n fi g uration. Wit h e compulsor y an d h ich data fields s i p start’, ‘trip e n e rs to set up up p t y pos. g . 4. Olfish-DDL l n other feature of O “intelligently” n fi g ured to refle c sic underl y in g u s t all y dif f erent fo r t ivities (sea-far m r ve y s, etc.). s extensive use enter data helps v er, new fields a n is normall y shi p to fit the “tas t h Olfish-DDL, th d which are rem e s hould be visibl e n d’ and, within a p er and lower li m l ookup table cus t O lfish-DDL is a D g uide the user c t data lo gg in g a c s er interface can r ms of fishin g ( t m s maintenance, of dropdown to maintain da t n d values can be a p ped with the cli e t e” and needs o e user can decid e mbered from p r e in which phas e a trip activit y , ‘s t m its for an y num e t omisation form Dy namic Comm a during its dat a c tions of vastl y d i have different D t rawl, lon g line, p car g o deliver y , lists whenever t a inte g rit y , thus a dded b y users i f e nt’s basic user c o f different us e e which fields s h r evious entries. T h e of the vessel o p t art’ and ‘end’. O e rical field in ord e a nds Bar (DCB) w a logging activi t i fferent activities . D CBs and can be p urse seine, tra p coastal g uard p possible. The u minimisin g t y p o f necessar y . c onfi g uration, it e rs of the same h ould be visible, h e user can also p eration. Examp l O lfish-DDL also e r to reduce the c w hich can be conf i t ies. The DCB c . For example, th e used to collect d p s, etc.) or other p atrols, oceano g u se of o s and can be basic which decide l es are allows c hance ig ured c an be e same ata for vessel g raphic Satellite Communications210 Fi g Ol u n co n u n hi g sc i D D or d re g D a (X M d a eit (V e g . 5. Olfish-DDL m fish-DDL has b e n der certain circ n fi g uration and n wanted confi g u r g her level mana g i entific pro g ram D L and constrai n d er to “force” u n g ulatio n -controll e a ta collected b y O M L, HTML, CS a tabases (such as t her directly, usi e ssel Monitorin g Activities Tree (data and reports) m ain dashboard e e n desi g ned to umstances, it i s customisation p r ation chan g es i n g ement bod y (ex a mana g ers, etc.). n the user’s abilit y n iformit y and fu e d data lo gg in g a O lfish-DDL can V, PDF, etc.). T Olfish-DDL sh o i ng portable sto r S y stem) or othe r scree n be a hi g hl y cus t s undesirable to p re-setup. With n cases where d a a mples are: comp a In such cases, it y to hide or i g n o ll data lo gg in g e a ctivities. be used to g en e T hese reports c a o re version, Olfi s r age devices, or r onboard satellit e Text a n Multi m brows t omisable data l o allow the use r Olfish-DDL, it i a ta definition is s a n y head offices, is possible to “ h o re certain fields. e xecution when O e rate an y t y pe o f a n be saved an d s h-RMS or other in real-time us i e communicatio n n d m edia er D yn Co m (D C ogg in g tool. Ho w r to chan g e th e i s possible to p s trictl y controlle d mana g ement a ge h ard” confi g ure O This is mainl y d O lfis h -DDL is u s f report in an y f d transferred to third part y dat a ing the onboar d n s y stems. n amic m mands Bar C B) GIS Brow (Mapper) w ever, e basic p revent d b y a e ncies, O lfish- d one in s ed for f ormat other a bases) d VMS ser Fi g 2. 3 Ol in G P se r T h “li D D w i le v T h su p A n in f in f m a th e re c T h d a G P st a an g . 6. Examples fo r 3 .3 GPS-Logger fish-DDL can pl o date, time and l P S unit can eithe r r ial or USB conn e h e Olfish-DDL a p g ht-wei g ht”, sta n D L. This applica t i th this GPS-Lo gg v el interfacin g w i h is means that o n p port for new G P n other advanta ge f ormation even f ormation to pro a rker data are n e e GPS-Lo gg er c a c orded GPS poin t h e GPS-Lo gg er ca a ta from an y set o P S information, b a ndard. These d e emometers amo n r Olfish-DDL Da t o t vessel movem e ocation and oth e r be a VMS trans p e ction. p plication does n o n d-alone applic a t ion is the GPS- L g er via a simple a i th the various G n l y the GPS-Lo gg P S or VMS units. e to havin g the if Olfish-DDL i s vide marker val e eded durin g no n a n also be used t s. n actuall y read a n o f NMEA 0183 s e b ut also an y info r e vices could incl u ng st others. Fields t a Editor e nts and trips an d e r GPS related fi e p onder or a stan d o t, in fact, talk d a tion runs conti n L o gg er, develop e a pplication pro gr G PS units to be h g er application n GPS-Lo gg er ru n s not runnin g . O ues b y means o f n -real-time data to plot vessel t r ny serial port inf o e ntences. This al l r mation outputt e u de man y analo g selector Dropdown list of images data d set tracks, as w e lds, if it has ac c d ard GPS output t irectl y to the G P n uall y on the co m e d b y Olrac. Olfi r ammin g interfac h andled exclusiv e n eeds to be upd a n continuousl y i s O lfish-DDL can f a small “time m recordin g activi t r acks even if th e o rmation and ca n l ows the GPS-Lo g e d b y devices co n g ue sensors suc h w ell as automatic a c ess to a GPS un t in g NMEA strin g P S unit. Rather, a m puter hostin g O sh-DDL commu n e, allowin g all t h e l y b y the GPS- L a ted as Olfish de s that it still lo g then use this l m achine” utilit y , t ies. The data st o e user has not a c n be extended to e gg er to record n o n formin g to the N h as echo sounde Numerical edit o with “info g rap h list of text data a ll y fill it. The g s on a small, O lfish- n icates h e low- L o gg er. velops g s GPS l o gg ed when o red in c tivel y e xtract o t onl y N MEA rs and o r h ” [...]... trip), an Catches A Trip class ssel nd nd p can have many Sets and a Set can ha many Catche Each class can contain any num n s ave es mber of 214 Satellite Communications fields Typical field for a Trip cou be, for exam ds uld mple, Departure Date, Departure Time, eparture Port an Skipper Nam Possible Set fields could include Start Time, Start nd me De La atitude, Start Lon ngitude, Gear Us sed, etc Possible... 4  XML    OCXML  XML  3rd Party  Zipped  XML  ZIP           unzip  XML  3rd Party  Olfish Compressed  XML  ODDL      XML  ODDL      XML  ODDL      3rd Party  ODDL    OCXML      XML  Olfish   Supplied  Decompression  Tool Olfish Server (on Shore)  Olfish Compressed  XML  OCXML   XML  XML  3rd Party  XML  Fig 13 Transmission of XML files from Olfish- DDL (vessel unit) to third-party (Olfish-DDL shore unit... regulations and XSD schemas Examples of management agencies whose regulations and schemas have been implemented by the Olfish-DDL are: EU regulations (EU 1077/20 08) , AFMA (Australian Fisheries Management Authorities) regulations etc 2 18 Satellite Communications Fig 11 Report Man g nager ate ts L, ven In addition Olfish- DLL can genera output report as PDF, HTML BMP files or ev as for rmal hardcopy lo ogheets... process Fig 21 Form Maker 6 .8 Scales Data Logging Utility The Scales data logging utility facilitates the incorporation of data obtained from mechanical scales (regarding the species, weight, grade and the processing state of catch) The data received from the scales is sent to a computer by either a TCP/IP network connection or a 230 Satellite Communications standard RS232 communications port Olfish-DDL... user then browses to this folder from within one of these third-party email applications, finds the report that has just been generated, and sends it In other cases, the third-party software automatically “polls” the outbox folder, and sends the reports at set intervals Sometimes reports cannot be sent as binary attachments by the third party software In these cases, Olfish-DDL uuencodes the binary... capture information on Trips, Sets, and Catches A trip has, for example, Departure Date, Departure Port and Skipper Name fields Possible Set fields include Start Time, Start Latitude, Start Longitude, Gear Used, etc Possible Catch record fields include Species, Weight, etc From a selected set the user can create Subsets of data for a particular analysis or presentation For example, graphs can be drawn showing... indicating which areas are most like to have the d ely densest po opulation of fish a b Fig 19 Fishing Co g onsultant Setting up prediction parameters (a) P g Projected good f fishing site (b) es 2 28 Satellite Communications A mathematical prediction model is trained on the historical data of catch and all recorded environmental factors The trained model can then predict future catch rates under conditions... extended to e n extract da from any set o NMEA 0 183 se ata of entences This all lows the GPS-Log gger to record no only ot GP information, b also any infor PS but rmation outputte by devices con ed nforming to the N NMEA sta andard These de evices could inclu many analog sensors such as echo sounders and ude gue h anemometers amon ngst others 212 Satellite Communications Fig 7 GPS-Logger g 3 Data Managem... non-fishing period 5.4.4 XML File Transmission Many reports sent from Olfish-DDL to Olfish-RMS or other third party RMS, such as enforcement/regulatory agencies, are in XML (Extensible Markup Language) format XML is not an ideally compact data format, and transmission between vessels and shore using onboard satellite communication systems is often costly It is therefore useful to compress the XML before sending... other than retained catches These should include non-commercial and commercial by-catch, sea-bird and marine mammal interactions, impact on benthic species, detailed information on gear used and 216 Satellite Communications many others For such a quantity and variety of data, paper logbooks are hopelessly inadequate 5.2 Real-Time Management Another advantage of electronic logbook near-real-time reporting . Environ, Vol .89 , pp. 381 -392. Wei, Q.F.; Lowery, B. & Peterson, A.E. (1 985 ) Effect of sludge application on physical properties of a silty clay loam soil. J. Environ. Qual, Vol.14, pp.1 78- 180 . . (20 08) Potentail benefits and risks of land application of sewage sludge. Waste Management, Vol. 28, pp.347-3 58. Soil Survey Staff, Natural Resources Conservation Service, United States Department. the Olfish-DDL are: EU regulations (EU 1077/20 08) , AFMA (Australian Fisheries Management Authorities) regulations etc. Satellite Communications2 18 Fi g In fo r R e of O n us e o u R e re q pr o ac c In