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Assessment of multifunctional landscapes dynamics in the mountainous basin of the Mo River （Togo, West Africa）

Journal of Geographical Sciences 2017年第5期27卷 579-605页

作者： DIWEDIGA Badabate AGODZO Sampson WALA Kperkouma LE Quang Bao WASCAL Graduate Research Program in Climate Change and Land Use Department of Civil Engineering Kwame Nkrumah University of Science and Technology Kumasi Ghana Department of Agricultural Engineering Kwame Nkrumah University of Science and Technology Kumasi Ghana Laboratory of Botany and Plant Ecology University of Lomb Togo CGIAR Research Program on Dryland Systems (CRP-DS) International Centre for Agricultural Research in Dry Areas (ICARDA) Amman 11195 Jordan

In this study, historical landscape dynamics were investigated to（i） map the land use/cover types for the years 1972, 1987, 2000 and 2014;（ii） determine the types and processes of landscape dynamics; and（iii） assess the landscape fragmentation and habitat loss over time. Supervised classification of multi-temporal Landsat images was used through a pixel-based approach. Post–classification methods included systematic and random change detection, trajectories analysis and landscape fragmentation assessment. The overall accuracies（and Kappa statistics） were of 68.86%（0.63）, 91.32%（0.79）, 90.66%（0.88） and 91.88%（0.89） for 1972, 1987, 2000 and 2014, respectively. The spatio-temporal analyses indicated that forests, woodlands and savannahs dominated the landscapes during the four dates, though constant areal decreases were observed. The most important dynamic process was the decline of woodlands with an average annual net loss rate of –2%. Meanwhile, the most important land transformation occurred during the transition 2000–2014, due to anthropogenic pressures. Though the most important loss of vegetation greenness occurred in the unprotected areas, the overall analyses of change indicated a declining trend of land cover quality and an increasing landscape fragmentation. Sustainable conservation strategies should be promoted while focusing restoration attention on degraded lands and fragmented ecosystems in order to support rural livelihood and biodiversity conservation.

关键词： land cover dynamics spatio-temporal patterns swap change landscape fragmentation protected areas Mo River Basin Togo

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Drone Application Model for Image Acquisition of Plantation Areas and Oil Palm Trees Counting 7

Drone Application Model for Image Acquisition of Plantation ...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Sastrohartono, Hermantoro Suryotomo, Andiko Putro Saifullah, Shoffan Suparyanto, Teddy Perbangsa, Anzaludin Samsinga Pardamean, Bens Instiper Yogyakarta Faculty of Agricultural Technology Department of Agricultural Engineering Yogyakarta55281 Indonesia Universitas Pembangunan Nasional Veteran Yogyakarta Department of Informatics Yogyakarta55283 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustainable productivity. The high-performance computing technologies, Internet of Things (IoT), Big Data, Artificial Intelligence, spatial modeling, and drones are the answers to these needs. This study aims to design an application that can obtain plantation image data and analyze the calculation of the number of oil palm trees. The image of oil palm plantations is obtained from processing photo data from drones through a mosaic and composite process. This study also employed Scrum and UML as a system model development method. The image of the oil palm plantation area is used to build a tree counting model using the Viola-Jones algorithm. The oil palm tree count information generated by this system can then be used by management for fertilizing, harvesting, and monitoring the condition of oil palm trees. © 2022 IEEE.

关键词： Drones

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IoT for Water Quality Categorization 5

IoT for Water Quality Categorization

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Sastrohartono, Hermantoro Krisdiarto, Andreas Wahyu Uktoro, Arief Ika Rahutomo, Reza Suparyanto, Teddy Pardamean, Bens Institute of Agriculture Stiper Faculty of Agricultural Technology Agricultural Engineering Department Yogyakarta Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics & Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350369489

In agricultural water research, the adoption of Internet of Things (IoT) technology has emerged as a pivotal approach for large-scale data collection. Water availability in the context of water quality is very important, both for domestic and industrial purposes. For domestic purposes, drinking water and bathing water are separated. Meanwhile, for the palm oil industry, boiler filler is differentiated from additional process water (dilution water). Water quality parameters can be assessed from turbidity and Total Dissolve Solid (TDS). Measurements using measuring instruments separately and repeatedly require significant energy, time, and costs. This research was conducted with the primary objective of presenting a novel method for categorizing water quality with the approach of IoT sensor technology. The research methodology entailed the utilization of an integrated IoT water sensors system in conjunction with manual water categorization. The methods consist of (1) system design, (2) design and installation of sensor and IoT-based microcontrollers, and (3) accuracy and precision testing compared with laboratory measurements. The precision of the integrated IoT water sensors was assessed through a dedicated sensor precision test, resulting in an accuracy rate of 94.4% for the turbidity sensor and 97.5% for the TDS sensor. Notably, this approach successfully discriminated drinking water with valid categorization, while other water types, including groundwater, water with tea, and water with coffee, yielded null categorization results. © 2023 IEEE.

关键词： Internet of things

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CVN 68 class solid waste flow analysis

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NAVAL ENGINEERS JOURNAL 1998年第6期110卷 73-87页

作者： Markle, SP Gill, SE LCdr. Stephen P. Markely USN:is a career Engineering Duty Oficer assigned to Naval Sea Systems Command Arlington VA where he is Deputy Directol Environmental Protection Systems Division (SEA 03 LIB). He is responsible for Program Management activities associated with all afloat environmental protection equipment and serves on several teams designed to promote Navy wide awareraess of environmental protection requirements and Navy programs to meet these challenges. He is a 1993 graduate of the Naval Construction and Engineering Program at the Massachusetts Institute of Zchmlogy where he received a Naval Engineering Degree and Master of Science in Mechanical Engineering. His interest in environmental issues predates his undergraduate studies at Syracuse UniversitylState University of New York College of Environmental Science and Forestw where he received a Bachelm of Science degree in Forrest Engineering from the School of Environmental and Resource Engineeriw. LCdr Markle has qualified as a Surface Warfare Oficer and in submarines through Engineering Duty Dolphin Program. He is a Professional Engineer registered in the State of New York and is a member ofASNE NSPE ASTM SNAME and SAE. Sean G. Gill:is a Senior Engineer with GEO-CENTERS incorporated in Pittsburgh PA where he provides technical and administrative support to the Naval Sea Systems Command (SEA 03L1) and the Carderock Division of the Naval Surfme Waflare Center (Code a) principal& on the shipboard and submarine solid waste management programs. Prior to joining GEO-CENTERS incorporated in 1996 he worked for eleven years at the Carderock Division of the Naval Surfme Warfare Center as a project engineer and a Branch Head. In the former capacity Mr Gill participated in various blackwatel gray watel and oily wastewater treatment projects oversaw the development of the Navy Pulper and was Center's technical team leader for the NAVSEA Solid Waste management program. In 1994 he was assigned to be Branch Head of Code 634 the Solid Waste Management

Through a detailed Research and Development program, the U.S. Navy has developed a suite of shipboard solid waste management equipment enabling compliance with federal and international law. Four major equipment types have been developed to outfit twenty-seven classes of naval surface ships. The major equipment types are: Plastic Waste Processor (PWP), Metal/Glass Shredder (MGS), Large Pulper (LP), and Small Pulper (SP). The Navy is aggressively procuring and installing this equipment aboard all ships of FFG 7 Class and larger. A deadline of December 31, 2000 has been set for completion. engineering analysis and held waste generation studies were conducted to select the specific equipment suite and develop alteration documentation for each ship class. Specific factors in this process were: solid waste generation rates, equipment reliability analysis, ship arrangement considerations, daily equipment operation Limits, and shipboard quality of life issues. A solid waste management study was conducted in the fall of 1997 to validate Navy equipment and ship design parameters onboard the USS John C. Stennis (CVN 74). Generation rates for shipboard solid waste were determined for plastic, metal and glass, food, paper, cardboard, fabric and wood. engineering analysis of data allowed a decrease in CVN 68 Class design waste generation rates. engineering analysis enabled a reduction in the number of PWPs and MGSs required, and fewer spaces for efficient operation. Ship arrangement studies were conducted to optimize efficiency and equipment mix of Solid Waste Processing Rooms (SWPRs) relative to waste generation sites. This paper briefly articulates the process followed by the Navy in responding to regulations governing solid waste management in the marine environment. Evidence validating the engineering procedures followed is presented.

关键词： Ship equipment

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AN OVERVIEW OF IN-SITU AIR SPARGING

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GROUND WATER MONITORING AND REMEDIATION 1993年第4期13卷 127-135页

作者： JOHNSON, RL JOHNSON, PC MCWHORTER, DB HINCHEE, RE GOODMAN, I Dr. Richard L. Johnson is an associate professor in the Department of Environmental Science and Engineering at the Oregon Graduate Institute (P.O. Box 91000 Portland OR 97291). He is also the director of the OGI Center for Groundwater Research and the OGI Large Experimental Aquifer Program. Dr. Paul C. Johnson is a senior research engineer at Shell Development Co. (Westhollow Research Center P.O. Box 1380 Houston TX 77251). Dr. David B. McWhorter is a professor in the Department of Agricultural and Chemical Engineering at Colorado State University (Engineering Research Center Foothills Campus Fort Collins CO 80523). Dr. Robert Hinchee is a research leader in the Environmental Technology Department at Battelle Memorial Institute (505 King Ave. Columbus OH 43201). Iris Goodman is an environmental scientist with the Advanced Monitoring Systems Division at the U.S. EPA Environmental Monitoring Systems Laboratory (P.O. Box 93478 Las Vegas NV 89192).

In situ air sparging (IAS) is becoming a widely used technology for remediating sites contaminated by volatile organic materials such as petroleum hydrocarbons. Published data indicate that the injection of air into subsurface water saturated areas coupled with soil vapor extraction (SVE) can increase removal rates in comparison to SVE alone for cases where hydrocarbons are distributed within the water saturated zone. However, the technology is still in its infancy and has not been subject to adequate research, nor have adequate monitoring methods been employed or even developed. Consequently, most IAS applications are, designed, operated, and monitored based upon the experience of the individual practitioner. The use of in situ air sparging poses risks not generally associated with most practiced remedial technologies: air injection can enhance the undesirable off-site migration of vapors and ground water contamination plumes. Migration of previously immobile liquid hydrocarbons con also be induced. Thus, them is an added incentive to fully understand this technology prior to application. This overview of the current state of the practice of air sparging is a review of available published literature, consultation with practitioners, a range of unpublished data reports, as well as theoretical considerations. Potential strengths and weaknesses of the technology are discussed and recommendations for future investigations given.

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IoT for Water Quality Categorization

IoT for Water Quality Categorization

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Hermantoro Sastrohartono Andreas Wahyu Krisdiarto Arief Ika Uktoro Reza Rahutomo Teddy Suparyanto Bens Pardamean Agricultural Engineering Department Faculty of Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

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Field Scale Simulation of Drainage Water Management Using Swat+: Analysis on the Model Performance, Intra Field Variability, Climate Variability, and Viability for Eastern South Dakota

SSRN

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SSRN 2022年

作者： Sharma, Abhinav McDaniel, Rachel Mehan, Sushant Arnold, Jeff Trooien, Todd Sammons, Nancy Amegbletor, Louis Department of Biological and Agricultural Engineering North Carolina State University RaleighNC27695 United States NOAA/NWS/OWP/National Water Center TuscaloosaAL35401 United States Biological Systems Engineering University of Wisconsin – Madison MadisonWI53706 United States Grassland Soil and Water Research Laboratory USDA-ARS TempleTX76502 United States Department of Agricultural and Biosystems Engineering BrookingsSD57007 United States Environmental Systems Graduate Program University of California Merced MercedCA95343 United States

In this study, the autoDWM module developed to simulate Drainage Water Management (DWM) for the restructured version of the Soil and Water Assessment Tool (SWAT+) was tested for a field site in eastern South Dakota. One half of the site was under DWM (eastern half), and the other (western half) was under conventional drainage. Next, multiple runs were used to quantify the impact of intra field, and climate variability on DWM performance, and discuss the applicability of DWM for the study region. SWAT+ produced satisfactory results for a daily time step simulation of tile flow during the model calibration period, 2016 and 2017 (East: NSE = 0.82, PBIAS = -26.8, RSR = 0.42;West: NSE = 0.75, PBIAS = -30.5, RSR = 0.5) and model validation period, 2018 (East: NSE = 0.71, PBIAS = -17, RSR = 0.55;West: NSE = 0.81, PBIAS = -4.6, RSR = 0.44). Results for the 10-year implementation period (2009 - 2018) showed that on average DWM resulted in a 6.5 mm annual tile flow reduction with an average deviation of ± 1.7 mm due to intra field variability. Precipitation had a profound effect on DWM performance during early summer months through the end of each cropping season. Conversely, temperature dominated tile flows during spring when snowmelt resulted in tile flow. Throughout the implementation period, annual tile flow reductions varied from -24 to +36 mm suggesting a combined effect of both precipitation and temperature. Overall, DWM resulted in a cumulative reduction of 63 lbs in N export from the field at an operational cost averaging $0.8 per pound N removed per year per acre. Results from the study successfully explored the variation in DWM performance on a field scale setup and is pivotal in spearheading the adoptability campaign by stakeholders and policymakers in the region. © 2022, The Authors. All rights reserved.

关键词： Climate models

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Green Logistics Approach in Bioethanol Conversion from Potato Starch in Central Java

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IOP Conference Series: Materials Science and engineering 2019年第1期598卷

作者： R Yusianto Marimin Suprihatin H Hardjomidjojo Graduate Program of Agro-Industrial Technology Bogor Agricultural University (IPB) Bogor Indonesia Department of Agro-Industrial Technology Faculty of Agricultural Technology Bogor Agricultural University (IPB) Bogor Indonesia Division of Industrial and Systems Engineering (TSI) Bogor Agricultural University (IPB) Bogor Indonesia

The demand for alternative sources of fossil fuel energy in Indonesia is increasing. One alternative to fossil fuels is bioethanol. Potato skin starch can be a raw material for making bioethanol. Potato skin contains starch, cellulose, hemicellulose, lignin and sugar. Bioethanol can be used must go through several stages, including the logistics system. Logistics activities require transportation, material handling equipment, and warehouses. In Indonesia, transportation sector which is the biggest user of fuel actually receives fuel subsidies. Bioethanol is the most appropriate alternative solution to replace gasoline. In processing, bioethanol through five stages, namely, potato skin starch, raw material logistics, processing bioethanol, delivery process and customer. This study presents green logistics model of potato transportation with a cost model and GWP. The results of the study show that the green logistics model by looking at the total costs and environmental impacts can be used as a reference in developing environmentally friendly bioethanol production in the future.

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The Effect of Alfalfa on Subsurface Discharge and Nutrient Losses Mediated by Precipitation Characteristics and Antecedent Moisture Conditions

SSRN

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SSRN 2024年

作者： Arrueta, Lourdes King, Kevin Hanrahan, Brittany Martin, Jay Kalcic, Margaret Environmental Science Graduate Program The Ohio State University 3138A Smith Lab 174 West 18th ColumbusOH43210 United States 590 Woody Hayes Dr. ColumbusOH43210 United States 12201 Sunrise Valley Drive RestonVA20192 United States Department of Food Agricultural and Biological Engineering 590 Woody Hayes Drive ColumbusOH43210 United States The Ohio State University Sustainability Institute 3018 Smith Lab 174 W. 18th Avenue ColumbusOH43210 United States Biological Systems Engineering Department University of Wisconsin-Madison 115 Agricultural Engineering Building 460 Henry Mall MadisonWI53706 United States

This study examines the effect of alfalfa (Medicago sativa L.) on nitrogen (N) and phosphorus (P) loads in subsurface (tile) drainage across storm events using edge-of-field monitoring data from two sites (A and B) located in the northwest region of Ohio, USA. A k-median cluster analysis was used to classify 462 storm events at Site A and 684 storm events at Site B based on precipitation amount and wet antecedent moisture conditions (AMC). Patterns of nutrient loss in tile drainage were compared between fields with alfalfa and fields with cash and cover crops using a difference-in-differences analysis across three identified storm event types: Dry storm events (Site A: AMC25 mm, Site B: AMC>29 mm), and large storm events (Site A: precipitation amount>29 mm, Site B: precipitation amount>38 mm). Compared to the cash and cover crop rotations, alfalfa had the following effects on discharge and water quality: a reduction in subsurface discharge during large storm events at site B;reduced subsurface nitrate (NO3-N) and total N (TN) loads across all storm event types at Site A;reduced subsurface dissolved reactive P (DRP) and total P (TP) loads during large events at both sites. The impact of alfalfa during large storm events is particularly important given that most nutrient export occurs during these events. © 2024, The Authors. All rights reserved.

关键词： Water quality

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Waters network's potential to transform environmental engineering education

Waters network's potential to transform environmental engine...

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114th Annual ASEE Conference and Exposition, 2007

作者： Eschenbach, Elizabeth Montgomery, Jami Johnson, James Brus, Chris Carlson, Patricia Giammar, Dan Grauer, Bette Hotaling, Liesl Oguntimein, Gbekeloluwa Safferman, Steven Wentling, Tim Humboldt State University United States Department of Environmental Resources Engineering Humboldt State University United States WATERS Network - CLEANER Project Office Network Howard University United States Department of Environmental Engineering College of Engineering Architecture and Computer Sciences Howard University United States American Academy of Environmental Engineers United States University of Iowa United States Program University of Iowa United States Rose-Hulman Institute of Technology United States Department of Rhetoric Rose-Hulman Institute of Technology United States National Research Council U. S. Air Force United States NASA's Classroom of the Future Wheeling WV United States Washington University United States Department of Energy Environmental and Chemical Engineering Washington University St. Louis United States Environmental Studies Program Center for Materials Innovation United States McPherson High School United States McPherson High School McPherson KS United States Stevens Institute of Technology United States Stevens Institute of Technology United States Morgan State University United States Michigan State University United States Biosystems and Agricultural Engineering Department Michigan State University United States University of Dayton United States Education Planning Committee National Center for Supercomputing Applications United States Department of Information Science Graduate School of Library and Information Science National Center for Supercomputing Applications University or Illinois United States Knowledge and Learning Systems Group NCSA United States

The WATERS Network (WATer and Environmental Research systems Network) will be an integrated real-time distributed observing system which will enable academic and government scientists, engineers, educators, and practitioners to advance effective management of our nation's water resources by understanding human interactions with water and the natural and built environment. WATERS will provide easily accessible real time environmental data as well as analysis tools to engineers, scientists, educators, K- graduate students and policymakers so they can better understand how water quantity, quality and related components of the hydrologic cycle are impacted by natural and human influences. The WATERS strategic plan will be completed by July 2007 and requires constituent input. This paper describes the draft Conceptual Design and the Education Plan of WATERS Network. This paper will highlight the potential impact of WATERS on undergraduate and graduate environmental engineering education in order to elicit input from the environmental engineering education community on how WATERS Network could better meet the future needs of undergraduate and graduate students and educators. More information can be found at ***. © American Society for engineering Education, 2007.

关键词： Water resources

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