Precision agriculture:
GPS Guidance and Auto-steer
Section Control on Sprayers
Row Control on Planters and Seeders
Yield Monitoring
Remote Sensing
In-field Sensing
Data Management
Variable Rate Applications
Telematics
Robotics
Crop production precision ag technologies 3 20-2013John Nowatzki
This document discusses precision agriculture technologies for crop production, including GPS guidance systems, section and row control for planters and sprayers, and variable rate technology. It describes how to create field management zones using yield monitors, remote sensing imagery, and crop sensors. GPS guidance allows for auto-steer, while section control and variable rate equipment can change application rates based on management zones. Crop sensors use light absorption and reflection to assess crop health and determine real-time nitrogen needs within a field. Precision agriculture aims to maximize profits through more efficient inputs while increasing yields and protecting the environment.
Telematics, automation, control systems in precision ag 2014John Nowatzki
Current technology for managing digital farm data. Includes new commercial data management programs that provide detailed field-level prescription maps and agronomic recommendations.
This document discusses precision agriculture technologies including GPS guidance, section and row control for implements, yield monitoring and data management, remote and in-field sensing, variable rate application, telematics, and autonomous vehicles. It notes that some technologies like herbicide-tolerant crops were adopted quickly by farmers while others like tractors replaced horses and mules more slowly over decades. The document outlines GPS guidance options and technologies for section and row control, yield monitoring, remote sensing, variable rate fertilization, and field management zones and application maps. It also discusses telematics and autonomous vehicles in agriculture.
Adoption of precision farming technologies in pakistanWaqas Javed
Precision agriculture (PA) is an approach to farm management that uses information technology (IT) to ensure that the crops and soil receive exactly what they need for optimum health and productivity. The goal of PA is to ensure profitability, sustainability and protection of the environment. PA is also known as satellite agriculture, as-needed farming and site-specific crop management (SSCM).
Precision Agriculture: Modern Agricultural Technologydrizlmari
Today world population is increased day by day gradually at same time the food production is being declined. So for modern techniques is required to feed the population
Skywards industries then showed their work in generating remote sensing data at a local level using drones. This can be used for mapping farms and assessing which crops are being grown. The drones can also be used for assessing agricultural health based on infrared reflectance. These images can then be reviewed by farmers in the field using tablets or mobile devices to assess areas of damage
GPS-based applications in precision farming are being used for farm planning, field mapping, soil sampling, tractor guidance, crop scouting, variable rate applications, and yield mapping. GPS allows farmers to work during low visibility field conditions such as rain, dust, fog, and darkness.
This document discusses the use of agricultural drones in India. It begins with an overview of the importance of agriculture to the Indian economy and population. It then discusses how precision agriculture and drone technology can help enhance productivity and efficiency by providing accurate field data. The document outlines the various sensor technologies used on agri-drones and their applications, which include soil and crop monitoring, precision spraying, irrigation management, and mapping. The benefits of agri-drones are higher yields, reduced costs and pesticide use, and improved decision making. Challenges to adoption include system and technology issues.
Crop production precision ag technologies 3 20-2013John Nowatzki
This document discusses precision agriculture technologies for crop production, including GPS guidance systems, section and row control for planters and sprayers, and variable rate technology. It describes how to create field management zones using yield monitors, remote sensing imagery, and crop sensors. GPS guidance allows for auto-steer, while section control and variable rate equipment can change application rates based on management zones. Crop sensors use light absorption and reflection to assess crop health and determine real-time nitrogen needs within a field. Precision agriculture aims to maximize profits through more efficient inputs while increasing yields and protecting the environment.
Telematics, automation, control systems in precision ag 2014John Nowatzki
Current technology for managing digital farm data. Includes new commercial data management programs that provide detailed field-level prescription maps and agronomic recommendations.
This document discusses precision agriculture technologies including GPS guidance, section and row control for implements, yield monitoring and data management, remote and in-field sensing, variable rate application, telematics, and autonomous vehicles. It notes that some technologies like herbicide-tolerant crops were adopted quickly by farmers while others like tractors replaced horses and mules more slowly over decades. The document outlines GPS guidance options and technologies for section and row control, yield monitoring, remote sensing, variable rate fertilization, and field management zones and application maps. It also discusses telematics and autonomous vehicles in agriculture.
Adoption of precision farming technologies in pakistanWaqas Javed
Precision agriculture (PA) is an approach to farm management that uses information technology (IT) to ensure that the crops and soil receive exactly what they need for optimum health and productivity. The goal of PA is to ensure profitability, sustainability and protection of the environment. PA is also known as satellite agriculture, as-needed farming and site-specific crop management (SSCM).
Precision Agriculture: Modern Agricultural Technologydrizlmari
Today world population is increased day by day gradually at same time the food production is being declined. So for modern techniques is required to feed the population
Skywards industries then showed their work in generating remote sensing data at a local level using drones. This can be used for mapping farms and assessing which crops are being grown. The drones can also be used for assessing agricultural health based on infrared reflectance. These images can then be reviewed by farmers in the field using tablets or mobile devices to assess areas of damage
GPS-based applications in precision farming are being used for farm planning, field mapping, soil sampling, tractor guidance, crop scouting, variable rate applications, and yield mapping. GPS allows farmers to work during low visibility field conditions such as rain, dust, fog, and darkness.
This document discusses the use of agricultural drones in India. It begins with an overview of the importance of agriculture to the Indian economy and population. It then discusses how precision agriculture and drone technology can help enhance productivity and efficiency by providing accurate field data. The document outlines the various sensor technologies used on agri-drones and their applications, which include soil and crop monitoring, precision spraying, irrigation management, and mapping. The benefits of agri-drones are higher yields, reduced costs and pesticide use, and improved decision making. Challenges to adoption include system and technology issues.
The document provides an overview of a presentation on remote sensing and GIS and their applications. It discusses what remote sensing is, the steps involved which include the source, sensors, and processing units. It describes different types of remote sensing based on the energy source, including passive sensors like Landsat and active sensors like LIDAR and RADAR. It outlines applications of remote sensing in areas like agriculture, natural resource management, and national security. It also provides an introduction to GIS, describing it as a computer-based information system for capturing and displaying spatially referenced data, and listing some of its functions and advantages.
Precision agriculture aims to control variability in agricultural production to improve output and environmental quality. It involves dividing fields into management zones based on factors like soil quality. Zone inputs are controlled using GPS and GIS technologies. This allows applying the right amount of fertilizer, water, and pesticides only where needed. Precision agriculture can benefit both farmers economically through reduced input costs and the environment by minimizing waste. However, there are also concerns for its adoption in Indian agriculture including small landholdings, lack of infrastructure, and farmers' technical knowledge about the technologies involved.
Black Sea Summit conference 2016
От БПЛА к сенсорам. спутникам и системам поддержки принятия решений
Feedback form: http://bit.ly/2cyQWjX
Website: http://blacksea-it.com/en/
Survey Grade LiDAR Technologies for Transportation EngineeringQuantum Spatial
This presentation was given during the 2013 Annual Civil Engineering Conference by Tim Stagg of AeroMetric. It covers system/sensor configurations, application advantages/disadvantages, analysis from sensor data, feature extraction/deliverables, and client pains in relation to survey grade LiDAR technologies for transportation engineering.
Precision farming uses technology like GPS, GIS, remote sensing, and variable rate application to optimize crop production by accounting for spatial and temporal variability within fields. It involves accessing variability through soil sampling and mapping, then managing that variability using tools like variable rate technology, site-specific planting, and nutrient management. This contrasts with traditional farming which treats entire fields uniformly without consideration for variability. The goal of precision farming is to improve crop yields and quality while reducing costs, waste, and environmental impact.
Precision agriculture involves collecting data about variability within fields in order to make targeted management decisions in smaller subfield areas. It utilizes technologies like GPS, GIS, yield monitors, and remote sensing to gather and analyze spatial and temporal data on factors like soil composition, crop yields, and pest populations. This allows for more efficient and environmentally friendly practices like variable rate application of inputs tailored to each subfield's specific needs, reducing costs and increasing yields. While the concept has existed for hundreds of years, recent technological advances have enabled much finer-scale data collection and analysis, driving improved management precision.
Precision agriculture involves collecting data about variability within fields in order to make targeted management decisions on a sub-field level. This allows for more efficient use of inputs like fertilizer and chemicals by varying application rates within a single field based on differences in soil type, crop growth, and other factors. While the concept has existed for hundreds of years, recent technologies like GPS, GIS, sensors, and data analysis software have enabled much more precise data collection and implementation at scale. Potential benefits include cost savings from reduced input usage, improved environmental stewardship, and increased economic returns through optimized field management.
Application of Remote Sensing In Agriculture with Drone System.pptxVikki Nandeshwar
1. The document discusses the application of remote sensing and drone technology in agriculture. Remote sensing allows obtaining information about objects from a distance by analyzing electromagnetic radiation. Drones can be used for tasks like monitoring crop health, soil conditions, precision agriculture, and irrigation.
2. Drones provide benefits like detailed imaging, monitoring large fields, and assessing soil moisture without damaging plants. Current applications include crop scouting, field monitoring, spraying, planting, security, and experimental uses like pollination.
3. While drone technology has benefits, regulations vary and more research is needed to expand their effective use in smaller-scale and developing country agriculture. Drones show potential but may not be practical for all farmers.
2018 GIS in the Rockies Vendor Showcase (Wed): Helping Construction from Abov...GIS in the Rockies
The problem with unforgiving schedules is that it allows little to no room for error. Unfortunately, when errors do occur it can be catastrophic to a project. As was the case with Juniper Unmanned’s client, a global renewable energy company that develops, constructs, and operates wind farms, solar fields, and energy storage facilities.
In March of 2018, Juniper’s client found themselves in a predicament that began with defective land surveys and compounded into a compressed project schedule, deployed personnel, expensive heavy machinery sitting idle. The defective surveys, forty-four in total, were for access roads and pad sites for a wind farm development in Kansas. Logically, the surveys needed to be re-done immediately. Traditional survey methods would take three to four weeks to complete, which didn’t solve the immediate problem of deployed personnel, heavy machinery, dissolving budgets, and diminishing schedules.
Juniper Unmanned rapidly deployed its field operations team, equipped with unmanned aircraft systems), LiDAR sensors and GPS base stations. Four days and 30 UAS flights later, the data acquisition was complete. The client was delivered a 1’ contour map and accompanying topographic surface the following week. These deliverables enabled the client’s excavators and personnel to begin cutting in new access roads and pad sites for the wind farm project. The use of Juniper’s UAS LiDAR sensing and analytics solutions helped the client get the project back on track with minimal scheduling and budgeting impacts.
Precision farming aims to optimize crop yields through site-specific management. It involves assessing field variability through soil sampling and remote sensing, mapping this variability using GPS and GIS technologies, and then managing the field variably based on these maps. This may include variable rate application of seeds, fertilizers, pesticides, and irrigation. Key technologies used include GPS for positioning, GIS for mapping and analysis of spatial data, and remote sensing for non-contact assessment of field conditions.
Precision farming uses remote sensing and data analysis to optimize crop yields. It involves observing field variations in crops and soil properties to determine management needs. Precision farming can increase productivity while reducing environmental impacts through efficient use of land, water, and agrochemicals. However, challenges remain in implementing precision farming technologies in some countries due to lack of expertise, high costs, and poor infrastructure.
Yield monitoring uses sensors and GPS data to collect georeferenced crop yield and characteristic data while harvesting. This allows farmers to create detailed yield maps of their fields to identify variable areas and optimize management practices. While yield monitors can provide accurate yield estimates if well-calibrated, challenges include sensor errors, moisture variations, and calibration biases. Yield monitoring is an important part of precision agriculture, enabling site-specific planting and variable input applications to improve efficiency and profitability.
This document provides an overview of geographical information systems (GIS) and remote sensing. It defines GIS and explains its key components, principles, functions, data types, advantages and disadvantages. It also defines remote sensing, describes its principles and stages, and outlines its applications in geology, natural resource management, national security and more. The advantages of remote sensing include large area coverage and permanent data records, while disadvantages include high costs and need for specialized training.
Development of machine vision and laser radar based autonomous vehicle guidan...ravikantghotekar
The document summarizes a seminar presentation on the development of machine vision and laser radar based autonomous vehicle guidance systems for navigating citrus groves. The key points are:
1) The system was developed to automate citrus harvesting in Florida as GPS is unreliable under citrus tree canopies. It uses machine vision and laser radar sensors along with a PID controller to autonomously steer a tractor down citrus alleyways.
2) Experiments were conducted using artificial paths made of hay bales to evaluate the performance of the machine vision and laser radar guidance systems. The laser radar based system showed better guidance at speeds up to 3.1 m/s.
3) Testing in actual citrus
This document discusses in-field crop sensors and their applications in crop production. It describes the differences between in-field and remote sensors, how sensor technologies work, and examples of commercial crop sensors including the GreenSeeker, OptRx, CropSpec, Crop Circle, and GreenSeeker handheld sensors. The document outlines how sensors can be used to determine real-time nitrogen needs and application rates, maximize yields, reduce nitrogen inputs, predict early yields, and enable precision desiccant application. It provides information on sensor costs, operation principles, and implications for improving crop management.
This document discusses the use of unmanned aerial vehicles (UAVs) for agriculture in the United Arab Emirates (UAE). It notes that UAE farms use over two-thirds of the country's water and covers approximately 200,000 acres of land. UAVs can provide high-resolution images from 1cm to view crop health through metrics like NDVI, helping save costs, time and resources compared to traditional ground surveys or lower-resolution satellite imagery. The document outlines UAV applications like crop management, livestock monitoring, water quality checks, and precision weed/pest control. It also notes factors to consider when choosing a UAV platform and provides an example of detailed imagery and NDVI maps collected from agricultural UAV
The document discusses the Global Positioning System (GPS) and its applications in mining. GPS is a U.S. satellite-based navigation system that provides location and timing services worldwide. It uses 24 satellites that orbit the Earth every 12 hours. A GPS receiver needs signals from at least 4 satellites to determine its precise 3D position, velocity and time. In mining, GPS can be used to track equipment locations, monitor dig progress, optimize truck dispatching and routing, and improve productivity, utilization, and safety.
LiDAR uses laser pulses to measure distances to surfaces and create 3D point clouds. It provides accurate elevation data day or night. Sources of error include scan angle, strip adjustment, ground point selection, interpolation, and visualization. Acquisition factors like flight parameters and weather affect data quality. Processing involves correcting systematic errors between flight lines and filtering points. Derivative products include DEMs, DTMs, and intensity images. Validation is needed due to inherent errors introduced during data collection and processing.
- Geographic Information Systems (GIS) is a computer-based tool that allows users to create, analyze, and display spatial information. GIS integrates many types of data to provide insights.
- GIS is used widely by international organizations, private industry, and government for applications like transportation planning, environmental analysis, and disaster management. It stores geographic data in layers that can be linked by location.
- Remote sensing involves collecting information about an area from a distance, such as via satellite or aerial imagery. High resolution sensors are commonly used to create accurate base maps and infrastructure data. Remote sensing data is extracted and digitized in GIS to build geographic databases.
This document discusses apps, maps, and drones for forest landowners and managers. It provides an overview of mapping and logging apps that can be used with GPS receivers and drones for forestry applications like inventory, inspections, and mapping. Specific apps and hardware are highlighted, such as the 4Loads logging app and Trimble PG200 GPS. It also reviews the desktop mapping program Terrain Navigator Pro and current FAA regulations for commercial drone use.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
The document provides an overview of a presentation on remote sensing and GIS and their applications. It discusses what remote sensing is, the steps involved which include the source, sensors, and processing units. It describes different types of remote sensing based on the energy source, including passive sensors like Landsat and active sensors like LIDAR and RADAR. It outlines applications of remote sensing in areas like agriculture, natural resource management, and national security. It also provides an introduction to GIS, describing it as a computer-based information system for capturing and displaying spatially referenced data, and listing some of its functions and advantages.
Precision agriculture aims to control variability in agricultural production to improve output and environmental quality. It involves dividing fields into management zones based on factors like soil quality. Zone inputs are controlled using GPS and GIS technologies. This allows applying the right amount of fertilizer, water, and pesticides only where needed. Precision agriculture can benefit both farmers economically through reduced input costs and the environment by minimizing waste. However, there are also concerns for its adoption in Indian agriculture including small landholdings, lack of infrastructure, and farmers' technical knowledge about the technologies involved.
Black Sea Summit conference 2016
От БПЛА к сенсорам. спутникам и системам поддержки принятия решений
Feedback form: http://bit.ly/2cyQWjX
Website: http://blacksea-it.com/en/
Survey Grade LiDAR Technologies for Transportation EngineeringQuantum Spatial
This presentation was given during the 2013 Annual Civil Engineering Conference by Tim Stagg of AeroMetric. It covers system/sensor configurations, application advantages/disadvantages, analysis from sensor data, feature extraction/deliverables, and client pains in relation to survey grade LiDAR technologies for transportation engineering.
Precision farming uses technology like GPS, GIS, remote sensing, and variable rate application to optimize crop production by accounting for spatial and temporal variability within fields. It involves accessing variability through soil sampling and mapping, then managing that variability using tools like variable rate technology, site-specific planting, and nutrient management. This contrasts with traditional farming which treats entire fields uniformly without consideration for variability. The goal of precision farming is to improve crop yields and quality while reducing costs, waste, and environmental impact.
Precision agriculture involves collecting data about variability within fields in order to make targeted management decisions in smaller subfield areas. It utilizes technologies like GPS, GIS, yield monitors, and remote sensing to gather and analyze spatial and temporal data on factors like soil composition, crop yields, and pest populations. This allows for more efficient and environmentally friendly practices like variable rate application of inputs tailored to each subfield's specific needs, reducing costs and increasing yields. While the concept has existed for hundreds of years, recent technological advances have enabled much finer-scale data collection and analysis, driving improved management precision.
Precision agriculture involves collecting data about variability within fields in order to make targeted management decisions on a sub-field level. This allows for more efficient use of inputs like fertilizer and chemicals by varying application rates within a single field based on differences in soil type, crop growth, and other factors. While the concept has existed for hundreds of years, recent technologies like GPS, GIS, sensors, and data analysis software have enabled much more precise data collection and implementation at scale. Potential benefits include cost savings from reduced input usage, improved environmental stewardship, and increased economic returns through optimized field management.
Application of Remote Sensing In Agriculture with Drone System.pptxVikki Nandeshwar
1. The document discusses the application of remote sensing and drone technology in agriculture. Remote sensing allows obtaining information about objects from a distance by analyzing electromagnetic radiation. Drones can be used for tasks like monitoring crop health, soil conditions, precision agriculture, and irrigation.
2. Drones provide benefits like detailed imaging, monitoring large fields, and assessing soil moisture without damaging plants. Current applications include crop scouting, field monitoring, spraying, planting, security, and experimental uses like pollination.
3. While drone technology has benefits, regulations vary and more research is needed to expand their effective use in smaller-scale and developing country agriculture. Drones show potential but may not be practical for all farmers.
2018 GIS in the Rockies Vendor Showcase (Wed): Helping Construction from Abov...GIS in the Rockies
The problem with unforgiving schedules is that it allows little to no room for error. Unfortunately, when errors do occur it can be catastrophic to a project. As was the case with Juniper Unmanned’s client, a global renewable energy company that develops, constructs, and operates wind farms, solar fields, and energy storage facilities.
In March of 2018, Juniper’s client found themselves in a predicament that began with defective land surveys and compounded into a compressed project schedule, deployed personnel, expensive heavy machinery sitting idle. The defective surveys, forty-four in total, were for access roads and pad sites for a wind farm development in Kansas. Logically, the surveys needed to be re-done immediately. Traditional survey methods would take three to four weeks to complete, which didn’t solve the immediate problem of deployed personnel, heavy machinery, dissolving budgets, and diminishing schedules.
Juniper Unmanned rapidly deployed its field operations team, equipped with unmanned aircraft systems), LiDAR sensors and GPS base stations. Four days and 30 UAS flights later, the data acquisition was complete. The client was delivered a 1’ contour map and accompanying topographic surface the following week. These deliverables enabled the client’s excavators and personnel to begin cutting in new access roads and pad sites for the wind farm project. The use of Juniper’s UAS LiDAR sensing and analytics solutions helped the client get the project back on track with minimal scheduling and budgeting impacts.
Precision farming aims to optimize crop yields through site-specific management. It involves assessing field variability through soil sampling and remote sensing, mapping this variability using GPS and GIS technologies, and then managing the field variably based on these maps. This may include variable rate application of seeds, fertilizers, pesticides, and irrigation. Key technologies used include GPS for positioning, GIS for mapping and analysis of spatial data, and remote sensing for non-contact assessment of field conditions.
Precision farming uses remote sensing and data analysis to optimize crop yields. It involves observing field variations in crops and soil properties to determine management needs. Precision farming can increase productivity while reducing environmental impacts through efficient use of land, water, and agrochemicals. However, challenges remain in implementing precision farming technologies in some countries due to lack of expertise, high costs, and poor infrastructure.
Yield monitoring uses sensors and GPS data to collect georeferenced crop yield and characteristic data while harvesting. This allows farmers to create detailed yield maps of their fields to identify variable areas and optimize management practices. While yield monitors can provide accurate yield estimates if well-calibrated, challenges include sensor errors, moisture variations, and calibration biases. Yield monitoring is an important part of precision agriculture, enabling site-specific planting and variable input applications to improve efficiency and profitability.
This document provides an overview of geographical information systems (GIS) and remote sensing. It defines GIS and explains its key components, principles, functions, data types, advantages and disadvantages. It also defines remote sensing, describes its principles and stages, and outlines its applications in geology, natural resource management, national security and more. The advantages of remote sensing include large area coverage and permanent data records, while disadvantages include high costs and need for specialized training.
Development of machine vision and laser radar based autonomous vehicle guidan...ravikantghotekar
The document summarizes a seminar presentation on the development of machine vision and laser radar based autonomous vehicle guidance systems for navigating citrus groves. The key points are:
1) The system was developed to automate citrus harvesting in Florida as GPS is unreliable under citrus tree canopies. It uses machine vision and laser radar sensors along with a PID controller to autonomously steer a tractor down citrus alleyways.
2) Experiments were conducted using artificial paths made of hay bales to evaluate the performance of the machine vision and laser radar guidance systems. The laser radar based system showed better guidance at speeds up to 3.1 m/s.
3) Testing in actual citrus
This document discusses in-field crop sensors and their applications in crop production. It describes the differences between in-field and remote sensors, how sensor technologies work, and examples of commercial crop sensors including the GreenSeeker, OptRx, CropSpec, Crop Circle, and GreenSeeker handheld sensors. The document outlines how sensors can be used to determine real-time nitrogen needs and application rates, maximize yields, reduce nitrogen inputs, predict early yields, and enable precision desiccant application. It provides information on sensor costs, operation principles, and implications for improving crop management.
This document discusses the use of unmanned aerial vehicles (UAVs) for agriculture in the United Arab Emirates (UAE). It notes that UAE farms use over two-thirds of the country's water and covers approximately 200,000 acres of land. UAVs can provide high-resolution images from 1cm to view crop health through metrics like NDVI, helping save costs, time and resources compared to traditional ground surveys or lower-resolution satellite imagery. The document outlines UAV applications like crop management, livestock monitoring, water quality checks, and precision weed/pest control. It also notes factors to consider when choosing a UAV platform and provides an example of detailed imagery and NDVI maps collected from agricultural UAV
The document discusses the Global Positioning System (GPS) and its applications in mining. GPS is a U.S. satellite-based navigation system that provides location and timing services worldwide. It uses 24 satellites that orbit the Earth every 12 hours. A GPS receiver needs signals from at least 4 satellites to determine its precise 3D position, velocity and time. In mining, GPS can be used to track equipment locations, monitor dig progress, optimize truck dispatching and routing, and improve productivity, utilization, and safety.
LiDAR uses laser pulses to measure distances to surfaces and create 3D point clouds. It provides accurate elevation data day or night. Sources of error include scan angle, strip adjustment, ground point selection, interpolation, and visualization. Acquisition factors like flight parameters and weather affect data quality. Processing involves correcting systematic errors between flight lines and filtering points. Derivative products include DEMs, DTMs, and intensity images. Validation is needed due to inherent errors introduced during data collection and processing.
- Geographic Information Systems (GIS) is a computer-based tool that allows users to create, analyze, and display spatial information. GIS integrates many types of data to provide insights.
- GIS is used widely by international organizations, private industry, and government for applications like transportation planning, environmental analysis, and disaster management. It stores geographic data in layers that can be linked by location.
- Remote sensing involves collecting information about an area from a distance, such as via satellite or aerial imagery. High resolution sensors are commonly used to create accurate base maps and infrastructure data. Remote sensing data is extracted and digitized in GIS to build geographic databases.
This document discusses apps, maps, and drones for forest landowners and managers. It provides an overview of mapping and logging apps that can be used with GPS receivers and drones for forestry applications like inventory, inspections, and mapping. Specific apps and hardware are highlighted, such as the 4Loads logging app and Trimble PG200 GPS. It also reviews the desktop mapping program Terrain Navigator Pro and current FAA regulations for commercial drone use.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
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A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
5. Technology Adoption in Agriculture
• Lightbars (GPS guidance)
– Gains against overlap and marker alternatives are easily perceived
– Do take a little more investment so less adopted by small farms until
recently
• Tractor cabs
– Hard to measure gain in $ but know it’s there
• GPS-assisted steering
– Larger investment than lightbars but still easy to perceive the
advantage
– Aspects like tractor cabs (reduces stress)
“duh” technologies
Dietrich Kastens
Kansas Agricultural Research Assn.
10. Section and Row Control
• Planters
• Air Seeders
Pneumatic
Electric
Planter Row
ON
Waterway
11. Precision Spraying Technology
• Boom Height Control
• Section and Nozzle Control
• Nozzle Flow Control
• Droplet Size Control
• As-Applied Maps
12. Variable Rate Fertilization
• Variable Rate Application
• Fertilizer, Seed, Variety
• Delineate Uniform Areas
• More Precise Management
• GIS – Data Management
How to Get Needed Information?
15. Remote Sensing : Suitability and Accuracy
Google Earth NAIP – 1 meter
Satellite – 15-30 m Zone Maps
16. In-field Sensors vs. Remote Sensors
• Sensors on
Equipment
• Internal Light
Source
• Real-time
17. Sensor Field Operation
• Rate Determination:
• NDVI Value
• Compare NDVI to
Optimum Area
• Growing Degree Days
• Potential Yield
• Activate Rate Controller
18. Available Crop Sensors
• OptRx – Ag Leader
• CropSpec – Topcon
• GreenSeeker – Trimble
• Crop Circle – Holland Scientific
19. Research Results
• NDSU Oakes - Wheat
• Summary
• 40% N Applied at Planting
• Remainder Early Season
• Results
• Reduced Lodging
• Significant Yield Increase
• Increased Protein
• No Increase in Nitrogen
20. Research Results
• Indian Head Research Farm - Wheat and Canola
• Reduced N Use
• No Effect on Yield
• Pioneer - Corn
• Reduced N Fertilizer
• No Significant Effect on Yield
• Potential Issue: no rain after in-season application
21. Implications in Precision Agriculture
• Real-time Plant Fertilizer Requirements
• Maximize Yield
• Increased Use Efficiency - Reduce Total Application
• Early Yield Prediction
• Precision Desiccant Application
• Issues:
• Additional Application Costs
• Another Pass of Field
• Weather Issues Could Prevent Second Application
22. • Inventory of Nursery Tree Crops
• Crop Stress
• Livestock Observation
• Monitoring Rangeland Condition
• Issues:
• Issues of Operating in Airspace
• Time
• Image Processing Complexities
• Difficulty of Operation
Unmanned Aircraft
23. LiDAR Technology
• Light Detection And Ranging
• Optical Remote Sensing using Lasers
• Measuring Distance to Ground from Airplane
measures the time delay between transmission
of a pulse and detection of the reflected signal
24. Agriculture Applications
• Tile and Surface Drainage
• Topographic Layer for Precision Agriculture
• Road Construction
• Community Development
25. Red River Basin LiDAR Data
www.internationalwaterinstitute.org/lidar.htm
Indian Head Research Data: http://www4.agr.gc.ca/abstract-resume/abstract-resume.htm?lang=eng&id=14859000000337
Clemson University: http://www.ag.auburn.edu/auxiliary/nsdl/scasc/Proceedings/2008/Wiatrack.pdf
Pioneer: https://www.pioneer.com/home/site/us/agronomy/library/template.CONTENT/guid.8AA5...
LiDAR – Light Detection and Ranging . Basically, this technology involves directing laser beams from an airplane to the earth surface, and measuring the length of time it takes for the laser beams to reflect back to a detector on the airplane. This data can be used to quantity features on the surface such as trees and buildings as well as the actual elevation map of the earth surface.
Computer technology is used to segregate the laser returns to first returns (used for features other than the ground surface, such as trees) and bare earth returns used for an elevation map.
Examples of lidar applications:
Flood map
Zone maps for precision agriculture
Construction
Community development
This site allows users to find areas by township and range, towns, or by zooming in to a specific area on their map.
John,
We have been working with several partners on LiDAR data collects during
2010 and 11 for the james river basin and surrounding areas of ND and SD.
Unfortunately none of the data has been delivered yet. We are expecting data to begin showing up in the next 30-60 days.
Please check back then.
Chuck
Chuck Loesch
Habitat and Population Evaluation Team
USFWS
3425 Miriam Ave.
Bismarck, ND 58501
701-355-8537
chuck_loesch@fws.gov
This site allows users to find areas by township and range, towns, or by zooming in to a specific area on their map.
Additional reference GIS layers can be displayed in the Fugro viewer. These layers are available without charges for North Dakota from the ND GIS Hub at: http://www.nd.gov/gis/
The data is downloaded in 12 kilometer square sections. This is an example of a section in West Fargo, ND.
West Fargo, ND. The area outlined in yellow is approximately 65 acres.
1 meter contours.
Users can select any point on the map to list the elevation for that area.