- File Size: 121166 KB
- Print Length: 154 pages
- Simultaneous Device Usage: Up to 4 simultaneous devices, per publisher limits
- Publisher: CRC Press; 1 edition (December 6, 2019)
- Publication Date: December 6, 2019
- Sold by: Amazon.com Services LLC
- Language: English
- ASIN: B082FQMQ7D
- Text-to-Speech: Not enabled
- Word Wise: Not Enabled
- Lending: Not Enabled
SAR Image Interpretation for Various Land Covers: A Practical Guide 1st Edition, Kindle Edition
Use the Amazon App to scan ISBNs and compare prices.
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Recommended popular audiobooks
About the Author
Élizabeth L. Simms is Associate Professor in the Department of Geography at Memorial University. She received her MSc degree from the Université de Sherbrooke and completed her PhD from the Université de Montréal. She worked for the Application Division of the Canada Centre for Remote Sensing on research projects related to the ocean, coastal environment, agriculture, and natural resource monitoring. In 1990, she joined the Department of Geography, Memorial University. Her academic activities include teaching courses in remote sensing, introductory geography information sciences, field methods, research design, and quantitative methods. Dr. Simms is currently coordinator of the Diploma in Geographic Information Sciences. Dr. Simms supervised graduate students in research based on radar and multispectral images, applied to mapping of coastal ice, boundary environments such as the coastal zone, Arctic tree line and glacier ice margins. Her research interest include developing teaching material to assist with learning of land use and land cover interpretation from RADARSAT-2 and COSMO- SkyMed images, developed area intensity classification from synthetic aperture radar, and the evaluation of remote sensing classification schemes for the representation of landscape features described through Aboriginal language.
Would you like to tell us about a lower price?
|5 star (0%)||0%|
|4 star (0%)||0%|
|3 star (0%)||0%|
|2 star (0%)||0%|
|1 star (0%)||0%|