Yuvraj Adagale

With a Master’s degree in Geoinformatics and more than 9 years of experience in the field of GIS, I am confident that I have the skills and expertise required for this role.

Throughout my career, I have gained extensive experience in full-stack development in GIS, including designing and implementing GIS systems, developing web mapping applications, and creating custom GIS tools. I have developed multiple applications using the Esri JavaScript API, Leaflet API, MapBox API such as a web mapping application that displays oil and gas-related data on a map and an interactive tool to visualize the historical changes of land use in a specific area using time-enabled maps. I have also created custom GIS tools in Python, a tool to calculate different types of indices like NDVI, LAI using AWS cloud-optimized GeoTIFF and such as a tool to extract features from a large dataset, a tool to calculate spatial statistics of data, a script to automate the publishing of Map and Feature Services on multiple deployment servers.

I would also like to highlight my extensive experience with ESRI technologies, which include ArcGIS Desktop, ArcGIS Server, ArcGIS Online, ArcGIS Pro, and ArcGIS Enterprise, among others. Over the course of my career, I have worked on a variety of GIS projects that have required the use of these technologies, and I have gained a deep understanding of their capabilities and how to leverage them to create effective GIS solutions.

In my previous roles, I have also worked with a range of web development frameworks and libraries. For example, I have developed a web-based mapping application using Angular that allows users to visualize the distribution of crimes across a city, and street children population and analyze spatial patterns. I have also worked with Node.js to build a web service that utilizes machine learning algorithms to classify satellite imagery for land cover mapping.

Additionally, I have experience with cloud-based platforms such as AWS and Azure. I have deployed GIS applications on AWS Elastic Beanstalk and used Azure Machine Learning to train models for land use classification. I also have experience with DevOps practices such as CI/CD pipelines, containerization, and orchestration.

With a Master’s degree in Geoinformatics and more than 9 years of experience in the field of GIS, I am confident that I have the skills and expertise required for this role.

Throughout my career, I have gained extensive experience in full-stack development in GIS, including designing and implementing GIS systems, developing web mapping applications, and creating custom GIS tools. I have developed multiple applications using the Esri JavaScript API, Leaflet API, MapBox API such as a web mapping application that displays oil and gas-related data on a map and an interactive tool to visualize the historical changes of land use in a specific area using time-enabled maps. I have also created custom GIS tools in Python, a tool to calculate different types of indices like NDVI, LAI using AWS cloud-optimized GeoTIFF and such as a tool to extract features from a large dataset, a tool to calculate spatial statistics of data, a script to automate the publishing of Map and Feature Services on multiple deployment servers.

I would also like to highlight my extensive experience with ESRI technologies, which include ArcGIS Desktop, ArcGIS Server, ArcGIS Online, ArcGIS Pro, and ArcGIS Enterprise, among others. Over the course of my career, I have worked on a variety of GIS projects that have required the use of these technologies, and I have gained a deep understanding of their capabilities and how to leverage them to create effective GIS solutions.

In my previous roles, I have also worked with a range of web development frameworks and libraries. For example, I have developed a web-based mapping application using Angular that allows users to visualize the distribution of crimes across a city, and street children population and analyze spatial patterns. I have also worked with Node.js to build a web service that utilizes machine learning algorithms to classify satellite imagery for land cover mapping.

Additionally, I have experience with cloud-based platforms such as AWS and Azure. I have deployed GIS applications on AWS Elastic Beanstalk and used Azure Machine Learning to train models for land use classification. I also have experience with DevOps practices such as CI/CD pipelines, containerization, and orchestration.

Master in GIS and Remote Sensing