Crop Yield Estimation using Remote Sensing and GIS ArcGIS from Udemy

Crop yield estimation is a critical aspect of modern agriculture. In this course, the wheat crop is covered. The same method applies to all other crops. With the advent of remote sensing and GIS technologies, it has become possible to estimate crop yields using various methodologies. Remote sensing is a powerful tool that can be used to identify and classify different crops, assess crop conditions, and estimate crop yields. One of the most popular methods for crop identification using remote sensing is to relate crop NDVI as a function of yield. This method uses various spectral, textural and structural characteristics of crops to classify them using the machine learning method in ArcGIS. Another popular method for crop condition assessment using remote sensing is crop classification then relate to NDVI index. This method uses indices such as NDVI to assess the health of the crop. Both of these methods are widely used for crop identification and assessment. Crop yield estimation can also be done by using remote sensing data. Yield estimation using remote sensing is done by using statistical methods, such as regression analysis and modelling in GIS and excel, including classification and estimation. One popular method for estimating wheat yield is the crop yield estimation model using classified and modelled data with observed records, as shown in this course. This model uses various remote sensing data to estimate the wheat yield. It is also important to validate the developed model on another nearby study area. That validation of the developed model is also covered in this course. The identification of crops is an important step in estimating crop yields and managing agricultural resources. In summary, remote sensing and GIS technologies are widely used for crop identification, crop condition assessment, and crop yield estimation. They provide accurate and timely information that is critical for managing agricultural resources and increasing crop yields.

Highlights :

Use Machine learning method for crop classification in ArcGIS, separate crops from natural vegetation
The model was developed using the minimum observed data available online
Crop NDVI separation
Crop Yield model development
Crop production calculation from GIS model data
Identify the low and high-yield zones and area calculation
Calculate the total production of the region
Validation of developed model on another study area
Validate production and yield of other areas using a developed model of another area
Convert the model to the ArcGIS toolbox

You must know:

Basics of GIS
Basics of Excel

Software Requirements:

Any version of ArcGIS 10.0 to 10.8
Excel

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Read about what's good

what should give you pause

and possible dealbreakers

Skills and knowledge taught are highly relevant to the agricultural industry

Provides a detailed model for crop yield estimation using remote sensing and GIS

Builds a strong foundation for beginners in crop yield estimation

Supplemental material available online

May require prior knowledge of GIS and Excel

Focuses on wheat crops, but the same method can be applied to other crops

Reviews summary

Practical crop yield estimation with arcgis

According to learners, this course is highly valuable for its practical application of remote sensing and GIS in crop yield estimation. Many students found the content on NDVI and machine learning classification, as well as the crop yield model development and validation, to be crystal clear and directly applicable to their professional work. The instructor's guidance is frequently praised as excellent and knowledgeable. However, a consistent point of caution among recent reviews is the use of outdated ArcGIS software (version 10.x), which can lead to compatibility issues and setup headaches for users on newer ArcGIS Pro versions. While the core methodologies are considered sound, some felt the statistical modeling was a bit rushed or that the data provided was limited for comprehensive practice, making it more of a solid introduction.

Core concepts like NDVI, machine learning, and model validation are well-covered.

"The explanations of NDVI and machine learning classification in ArcGIS were crystal clear."

"The machine learning classification part was well-explained. The validation module was a strong point."

"The yield model development was practical and the validation steps were crucial."

Instructors are highly knowledgeable, providing clear and effective explanations.

"The instructor's guidance was excellent."

"The instructor is knowledgeable, but pace could be improved."

"Instructor is clearly an expert."

Course provides hands-on methods directly applicable to real-world agriculture.

"This course is incredibly practical for anyone in agricultural GIS. It directly applies to my work."

"Absolutely fantastic! As a professional agronomist, this course filled a significant gap in my remote sensing skills."

"The practical steps for yield mapping and identifying high/low yield zones were invaluable. Essential for anyone wanting to apply GIS in agriculture."

Some parts felt rushed or lacked deep dives into advanced methodologies.

"Some parts felt a bit rushed, especially the statistical modeling, but overall, a solid practical course."

"I felt the data provided was sometimes a bit limited for comprehensive practice. It's a good introduction, but don't expect deep dives into advanced statistical methods."

"Would have liked more complex scenarios or troubleshooting tips for real-world data, but it's a good starting point."

Course relies on ArcGIS 10.x, causing compatibility issues for new users.

"The ArcGIS version used (10.x) is quite old now. I had some compatibility issues trying to follow along with ArcGIS Pro."

"The ArcGIS 10.x requirement is a major drawback, as many are now on ArcGIS Pro, causing setup headaches."

"My main issue was the outdated software. It makes it hard to recommend without a major update to ArcGIS Pro."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Crop Yield Estimation using Remote Sensing and GIS ArcGIS with these activities:

Organize and consolidate course materials

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Stay organized and enhance your learning by compiling and reviewing course materials.

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Create a central repository for all course materials.
Regularly review and summarize key concepts from the materials.

Brush up on GIS and Excel basics

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Refresh your GIS and Excel skills to excel in this course.

Browse courses on GIS

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Review online tutorials to understand GIS fundamentals.
Check out documentation and tutorials to grasp Excel concepts.

Reach out to experts in the field of crop yield estimation

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Connect with experts to gain valuable insights and guidance on crop yield estimation.

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Attend industry events or conferences.
Network with professionals on LinkedIn or other platforms.
Reach out to professors or researchers in the field.

Two other activities

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Organize a study group to discuss crop yield estimation

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Deepen your understanding of crop yield estimation through discussions with peers.

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Find a group of classmates who are interested in forming a study group.
Establish regular meeting times and stick to them.
Prepare for each meeting by reading the assigned materials and completing any pre-reading.

Contribute to open-source projects related to crop yield estimation

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Enhance your skills and contribute to the community by participating in open-source projects on crop yield estimation.

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Identify open-source projects on platforms like GitHub.
Review the project documentation and identify areas where you can contribute.
Reach out to the project maintainers to express your interest in contributing.

Career center

Learners who complete Crop Yield Estimation using Remote Sensing and GIS ArcGIS will develop knowledge and skills that may be useful to these careers:

Crop Insurance Agent

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, is highly relevant to Crop Insurance Agents who use remote sensing and GIS technologies to assess crop conditions and estimate crop yields. The course provides a comprehensive overview of the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Crop Insurance Agents, as it allows them to develop and implement crop insurance policies that can protect farmers from financial losses due to crop damage or failure.

See salaries and explore the career path for Crop Insurance Agent

Crop Consultant

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, is highly relevant to Crop Consultants who use remote sensing and GIS technologies to provide crop management advice to farmers. The course provides a comprehensive overview of the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Crop Consultants, as it allows them to develop and implement crop management plans that can improve crop yields and reduce environmental impacts.

See salaries and explore the career path for Crop Consultant

Farmer

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, is highly relevant to Farmers who use remote sensing and GIS technologies to manage their crops. The course provides a comprehensive overview of the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Farmers, as it allows them to develop and implement crop management plans that can improve crop yields and reduce environmental impacts.

See salaries and explore the career path for Farmer

Precision Agriculture Specialist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, is highly relevant to Precision Agriculture Specialists who use remote sensing and GIS technologies to improve agricultural productivity. The course provides a comprehensive overview of the use of remote sensing and GIS technologies to identify and classify crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Precision Agriculture Specialists, as it allows them to develop and implement precision agriculture practices that can improve crop yields and reduce environmental impacts.

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Research Scientist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, is highly relevant to Research Scientists who work in the field of agriculture. The course provides a comprehensive overview of the use of remote sensing and GIS technologies to identify and classify crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Research Scientists who work in the agricultural sector, as it allows them to conduct research on crop production and management practices.

See salaries and explore the career path for Research Scientist

Remote Sensing Scientist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, provides a solid foundation for Remote Sensing Scientists who specialize in agricultural applications. The course covers the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Remote Sensing Scientists who work in the agricultural sector, as it allows them to develop and implement remote sensing-based solutions to support agricultural decision-making.

See salaries and explore the career path for Remote Sensing Scientist

GIS Analyst

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, is highly relevant to GIS Analysts who work in the field of agriculture. The course provides a comprehensive overview of the use of remote sensing and GIS technologies to identify and classify crops, assess crop conditions, and estimate crop yields. This knowledge is essential for GIS Analysts who work in the agricultural sector, as it allows them to develop and implement GIS-based solutions to support agricultural decision-making.

See salaries and explore the career path for GIS Analyst

Geospatial Analyst

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, provides a strong foundation for Geospatial Analysts who want to specialize in agricultural applications. The course covers the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge is essential for Geospatial Analysts who work in the agricultural sector, as it allows them to provide valuable information to farmers and other stakeholders.

See salaries and explore the career path for Geospatial Analyst

Soil Scientist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, provides a foundation for Soil Scientists who want to learn about the use of remote sensing and GIS technologies to assess soil conditions and their impact on crop yields. The course covers the use of remote sensing data and GIS software to identify and classify different soil types, assess soil conditions, and estimate crop yields. This knowledge is essential for Soil Scientists who work in the agricultural sector, as it allows them to develop and implement soil management practices that can improve crop yields and reduce environmental impacts.

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Farm Manager

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, helps build a foundation for Farm Managers who want to gain knowledge about the use of remote sensing and GIS technologies to improve their farming practices. The course covers the use of remote sensing data and GIS software to identify and classify different crops, assess crop conditions, and estimate crop yields. This information can be used to make informed decisions about crop management, such as when to plant, fertilize, and harvest.

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Water Resources Engineer

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, may be useful for Water Resources Engineers who want to learn about the use of remote sensing and GIS technologies to assess water resources and their impact on crop yields. The course covers the use of remote sensing data and GIS software to identify and classify different water resources, assess water quality, and estimate crop yields. This knowledge may be useful for Water Resources Engineers who work in the agricultural sector, as it allows them to develop and implement water management practices that can improve crop yields and reduce environmental impacts.

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Policy Analyst

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, may be useful for Policy Analysts who want to learn about the use of remote sensing and GIS technologies to assess the impact of agricultural policies. The course covers the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge may be useful for Policy Analysts who work in the agricultural sector, as it allows them to develop and implement policies that can improve crop yields and farm income.

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Environmental Scientist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, provides a good foundation for Environmental Scientists who wish to learn about the use of remote sensing and GIS technologies to assess the condition of crops and land use. The course provides an understanding of the principles of remote sensing and GIS, and how these technologies can be used to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge can be useful for Environmental Scientists who work in areas such as agricultural research, land use planning, and environmental impact assessment.

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Agricultural Economist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, may be useful for Agricultural Economists who want to learn about the use of remote sensing and GIS technologies to assess the economic impact of agricultural practices. The course covers the use of remote sensing and GIS technologies to identify and classify different crops, assess crop conditions, and estimate crop yields. This knowledge may be useful for Agricultural Economists who work in the agricultural sector, as it allows them to develop and implement economic models that can assess the impact of different agricultural practices on crop yields and farm income.

See salaries and explore the career path for Agricultural Economist

Agronomist

The course, Crop Yield Estimation using Remote Sensing and GIS ArcGIS, may be useful for Agronomists who wish to improve their knowledge of crop yield estimation techniques and learn how to use remote sensing and GIS technologies to support their work. The course covers the use of remote sensing data as well as GIS software to identify and classify different crops, assess crop conditions, and estimate crop yields.

See salaries and explore the career path for Agronomist

Crop Yield Estimation using Remote Sensing and GIS ArcGIS

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Practical crop yield estimation with arcgis

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