Harris Geospatial Solutions offers introductory, intermediate, and advanced courses in ENVI image analysis software. Classes are held year round and can be customized to meet your unique requirements. Our expert instructors focus on your goals and how you can best utilize our tools to achieve them.
Boot Camp is a scenario-based introduction to ENVI designed to get military geospatial engineers, geospatial analysts and image analysts up-to-speed as quickly as possible. Each scenario is designed to represent a real world scenario in which the student must utilize tools in ENVI to solve a problem and generate an output product.
Prerequisite: Some basic understanding of remote sensing and Geographic Information Systems is suggested.
View our Classroom Training Calendar
LiDAR data contains boundless information on terrain and 3D features. Knowing how to effectively work with LiDAR so that you can quickly get the information you need from it is vital to getting the most out of your investment. In this course you will learn how you can use the LiDAR tools in ENVI to extract 3D features and elevation-based products quickly and easily. ENVI support the most common LiDAR formats such as LAS, Binary, ASCII, and NITF LiDAR. With ENVI you can generate elevation products such as Digital Surface Models (DSMs), Digital Elevation Models (DEMs), and digital elevation contours. ENVI also automatically extracts 3D features from LiDAR point clouds such as buildings, trees, power lines, and power poles. p>
Prerequisite: A basic understanding of LiDAR data is useful but not necessary. Some experience with remote sensing and/or GIS software is useful but not necessary.
Do you need to quickly get up-to-speed on the full-featured functionality offered by ENVI, the premier remote sensing exploitation package? In this course you’ll learn much about the core functionality of ENVI and also work with Feature Extraction, the object-oriented classification workflow. You will also be given an introduction to hyperspectral data analysis that can be used as a stepping-stone for learning about ENVI’s advanced hyperspectral analysis capabilities. Data from various multispectral, hyperspectral and radar sensors, including ASTER, AVIRIS, Quickbird, RadarSat, AVHRR, SPOT, Landsat, TMS, and USGS DEM data are used in a mixture of lectures and exercises. In addition, you will be shown ways to extend ENVI using batch processing, Band and Spectral Math, and incorporating your own programs.
Prerequisite: A basic level of remote sensing knowledge is necessary to take advantage of what this course has to offer.
Extending ENVI with IDL is a four day course for remote sensing scientists, engineers and developers who wish to incorporate their own algorithms and workflows into ENVI. This course provides an overview of the programming constructs available in IDL, the language in which ENVI is written, as well as the tools necessary for a user to extend ENVI with IDL, including ENVI library routines, custom file readers and writers, batch mode programs and user functions. Students should be familiar with ENVI, ideally having taken Exploring ENVI. Several ENVI programs are developed in class. Though it is helpful to have programming experience in IDL, familiarity with basic programming topics in any language is suitable.
Prerequisite: Exploring ENVI (or equivalent experience) and familiarity with basic programming.
Discover the power of the spectral analysis tools that make ENVI the industry leader in hyperspectral imagery exploitation. Hyperspectral data analysis allows the identification of materials on the Earth’s surface due to the detailed sampling of the electromagnetic spectrum by hyperspectral sensors. This intensive four-day course focuses first on understanding the theory behind hyperspectral imaging, and then challenges the student to apply the theory with ENVI’s advanced analysis and mapping algorithms. Topics covered include image classification, principal components analysis, Minimum Noise Fraction, spectral libraries, spectral signatures, whole-pixel and sub-pixel analysis, and ENVI’s powerful endmember extraction algorithms. You’ll use data from several of the most widely used sensors, including AVIRIS, AISA and HyMap.
Prerequisite: A basic level of remote sensing knowledge is necessary to take advantage of what this course has to offer. This is an advanced ENVI class; a working knowledge of ENVI is desirable.
Sign Up for News & Updates: Stay informed with the latest news, events, technologies and special offers.