updated lasi-dad image, ai climate, permafrost, cedar project

Author: YOO-uN-ee

_data/research.yml

@@ -6,6 +6,29 @@
   abstract: Utilizing AI to enhance knowledge of the environment and climate, specifically in fields such as agriculture or forestry.
   paper:
   sponsor:
+  link: https://cse.umn.edu/aiclimate
+  github:
+  demo:
+- title: Permafrost Peatlands Mapping Modeling
+  progress: ongoing
+  image: 
+  klass: 
+  desc: Employing ML models to map and predict permafrost and peatlands across U.S.
+  abstract: This project employs machine learning models to map and predict the extent and characteristics of permafrost and peatlands across the United States. This project is conducted under AI-CLIMATE and in conjunction with the Jelinski Lab.
+  paper:
+  sponsor:
+  link: https://www.jelinskilabpedology.org/
+  github:
+  demo:
+- title: CEDAR
+  progress: ongoing
+  image: 
+  klass: 
+  desc: Estimating aboveground biomass and carbon stocks in forests.
+  abstract: Carbon Estimation with Deep LeARning (CEDAR) is a project designed to estimate aboveground biomass and carbon stocks in forests by leveraging deep learning models. CEDAR is a collaboration with Chad Babcock's Lab.
+  paper:
+  sponsor:
+  link: https://forestry.umn.edu/people/chad-babcock
   github:
   demo:
 - title: Critical MAAS
@@ -34,8 +57,8 @@
   progress: ongoing
   image: images/research/LASI_DAD.png
   klass: 
-  desc: Detecting elements of the built environment in India to better understand aging and dementia.
-  abstract: Detecting elements of the built environment in India to better understand aging and dementia.
+  desc: Exploring human and environment interaction to better understand the determinants of dementia and its impact on society in India
+  abstract: Exploring human and environment interaction to better understand the determinants of dementia and its impact on society in India
   paper:
   sponsor:
   github: