1. March 19, 2015 Mapping croplands using Landsat data with generalized classifier over large areas Aparna Phalke and Prof. Mutlu Ozdogan Nelson Institute for Environmental Studies University of Wisconsin - Madison

2. Updates on following Efforts to improve accuracy of crop/non-crop map Incorporating ALOS/PALSAR data in developing LDA model Document/paper writing in progress on crop/non-crop algorithm at 30m by Landsat

3. Efforts to improve accuracy of crop/non-crop map 1. Accuracy increase due to its check at segment level previously we had accuracy check for 3*3 pixel location : 2. ALOS/PALSAR data use

4. Own level : Accuracy increase due to Effort1

5. Zone level : Accuracy increase due to Effort1

6. Global level : Accuracy increase due to Effort1

8. Incorporating ALOS/PALSAR data in developing LDA model ALOS/ PALSAR data advantage: The PALSAR-2 aboard the ALOS-2 is a Synthetic Aperture Radar (SAR), which emits microwave and receives the reflection from the ground to acquire information. L-band, which is less affected by clouds and rains. PALSAR data has free access. Good capability to monitor cultivated areas

9. PALSAR data collection One tile of data is 2gb Data preparation, collection and pre- processing is in process. We need total 200 tiles for whole study areas. (Europe, North Africa, Middle East)

10. Thank you phalke@wisc.edu