Improved Prediction of Forest Variables Using Data Assimilation of Interferometric Sy... | RTCL.TV
Channel: STEM RTCL TV
Date: 2024-01-06

### Keywords ###
#dataset #statisticalframework #remotesensing #updateforest #forestdatabases #combiningexisting #dataassimilation #RTCLTV #shorts

### Article Attribution ###
Title: Improved Prediction of Forest Variables Using Data Assimilation of Interferometric Synthetic Aperture Radar Data
Authors: Nils Lindgren, Henrik J. Persson, Mattias Nyström, Kenneth Nyström, Anton Grafström, Anders Muszta, Erik Willén, Johan E. S. Fransson, Göran Ståhl ,and Håkan Olsson
Publisher: Taylor & Francis Group
DOI: 10.1080/07038992.2017.1356220
DOAJ URL: https://doaj.org/article/60662effd2b24f4c93040cb4c5e090fb



### Image Attribution ###
We used stable diffusion to programmatically generate the background images. 
Viewer discretion is advised.

### Channels ###
YouTube Channel: https://www.youtube.com/@stemrtcltv
Odysee Channel: https://odysee.com/@stem_rtcl_tv

### Video Timestamps ###
0:00:00 - Summary 
0:00:51 - Title 
0:00:57 - End