When it comes to electrical power distribution over transmission or distribution wires, a lack of vegetation management around the powerlines can lead to high maintenance costs. Vegetation management is crucial, as uncontrolled vegetation encroachments can lead to forest fires, power outages during a storm, and so on. Identifying these maintenance spots that will need trimming or vegetation management takes time. Often, you will need to conduct a manual survey, or one partially assisted by remote sensing data. Companies must spend time, money, and resources on vegetation encroachment management.

Need to take your spatial data (GIS, Remote Sensing) analysis, and visualization one step further? Everyone around you is talking about deep learning and machine learning but you feel frustrated as you don't know any programming and think that it is not for you? This course will introduce you to the basics of deep learning and teach you the application of deep learning algorithms (such as convolution neural networks) for ArcGIS Pro and give you the skills necessary to improve your geospatial skills and get great job opportunities. By the end of this course, you will be able to take your own project and find data, manipulate it with deep learning algorithms, and create useful results for your peers, professors, clients, etc. This course is absolutely a must for all who want to learn deep learning but don't know how to start with this challenging subject.

It has been a big year for advancements in deep learning here at Esri. We have added new pretrained deep learning models, new and enhanced data types, tasks and experiences, updates to the developer story and introduced a new SaaS offering. These updates have been made to support optimized workflows for our GIS Analysts, Developers and Data Scientists among others.

Esri India, the country's Geographic Information System (GIS) software and solutions provider, has introduced Site Scan for ArcGIS, a complete cloud-based drone mapping solution. The solution encompasses flight planning, data capture, data processing, analysis, data sharing and drone fleet management. It is offered as'Software as a Service' (SaaS) with unlimited storage and computing. Site Scan for ArcGIS is hosted in India, on a cloud approved by the Government of India and ensures that the drone data is stored and processed within India in compliance with the government regulations. Site Scan for ArcGIS exhibits the capability to process data captured by most of the drones manufactured in India or abroad.

With the fire hose of imagery that's streaming daily from a variety of sensors, the need for using artificial intelligence (AI) to automate feature extraction is only increasing. The ability to train more than a dozen deep learning models on geospatial datasets and derive information products has been available using the ArcGIS API for Python or ArcGIS Pro, and users can scale up processing using ArcGIS Image Server. Esri is taking AI to the next level with ready-to-use geospatial AI models in the ArcGIS Living Atlas of the World. Initially, three models have been made available. Two of the models use satellite imagery.

Today was a fun and exciting day at the Esri Federal GIS Conference 2021 highlighted by great user presentations, inspiring talks, and a powerful technology showcase. The imagery and remote sensing demonstration showed how AI was effectively put to use in a SAAS environment. Driving the AI was a pre-trained model that is downloadable for all users from ArcGIS Living Atlas. This is just one of the many models that have been released on ArcGIS Living Atlas of the World. Ever since the pre-trained geospatial deep learning models were released on ArcGIS Living Atlas, they have been well received.

Welcome to part 4 of my AI and GeoAI Series that will cover the more technical aspects of GeoAI and ArcGIS. Previously, part 1 of this series covered the Future Impacts of AI on Mapping and Modernization which introduced the concept of GeoAI and why you should care about having an AI as a future coworker. Part 2 of the series, GIS, Artificial Intelligence, and Automation in the Workplace covered specific geospatial professions that will be drastically effected by introduction of GeoAI technology in the workplace. Part 3 addressed Teaming with the Machine - AI in the workplace the emergence of the new geospatial working relationship between information, humans, and artificial intelligence to be successful in an organizations mission. For part 4, we will address 3 specific GeoAI areas in ArcGIS that will help you with your journey to developing your Deep Learning workflows.

ArcGIS is a geographic information system (GIS) for working with maps and geographic information. Developed by Esri over 20 years ago, it is widely used for creating maps, analyzing mapped information, managing geographic information, compiling geographic data, and finally sharing and discovering geographic information. Our plugin allows you to detect objects and patterns with machine learning without leaving ArcGIS – it perfectly integrates with the workflow. Picterra is a web platform that leverages AI to put object detection and image segmentation on geospatial imagery at your fingertips. But as an ArcGIS Pro user, you may not want to switch between tools multiple times a day, and (rightly so) prefer to be able to do everything within your GIS software. This is the reason why we've developed the ArcGIS add-in for Picterra.

Artificial Intelligence (AI) has arrived. It is not science fiction anymore. Computers already recognize objects in images and understand speech and language at least as well as, if not better than, humans. This has been made possible with rapid advances in hardware, vast amounts of training data, and innovations in machine learning algorithms such as deep neural networks. Deep learning is the driving force behind the current AI revolution and is giving intelligence to today's self-driving cars, smartphone and smart speakers, and making deep inroads into radiology and even gaming.

While so-called'deep learning' methods, that is machine learning techniques that use layered, artificial neural networks, to perform learning of unstructured data, has gained great popularity in research in the last few years, its integration within GIS is not always easy without specialist knowledge. New tools, however, are being and have been developed that potentially will allow a wider field of researchers to better take advantage of machine learning and deep learning specifically. So far, two clear leaders have emerged. ArcGIS has spent significantly in recent years to develop better tools for deep learning. They have used a variety of platforms that have been developed for imagery analysis, such as Keras and Tensorflow which are popular deep learning platforms, and have integrated them with ArcGIS Pro tools, such as ArcGIS Image Server.