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

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

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

Own level : Accuracy increase due to Effort1

Zone level : Accuracy increase due to Effort1

Global level : Accuracy increase due to Effort1

Incorporating ALOS/PALSAR data in developing LDA modelALOS/ 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

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)

Thank you

phalke@wisc.edu