TY - GEN
T1 - A research on Agricultural Mapping Capabilities of the SPOT 6 satellite images
AU - Alganci, Ugur
AU - Sertel, Elif
AU - Kaya, Sinasi
AU - Ustundag, B. Berk
PY - 2013
Y1 - 2013
N2 - This study focused on crop type identification and area estimation of the cultivated parcels using images with 1.5m spatial resolution and 60km × 60km coverage from newly launched SPOT 6 satellite. A test site and a district in Sanliurfa Province, Southeastern Turkey were selected as study region where ground truth data was also available. After the geometric correction of SPOT 6 images; further image processing methods were applied. In the first step, a comparative analysis was performed at a test site to find out optimum parameters to be applied for this research. For this analysis, object based image classification (OBC) was applied to SPOT 6 image and feature extraction was performed from classification results to identify different parcels within the study area. Extracted features were compared to parcel vector database and accuracy metrics of parcel identification and area estimation was produced. In the second step, analysis was extended to district scale and classification OBC classification was performed for Suruc district of Sanliurfa. Accuracy assessment was performed with stratified random point selection for district scale classification results.
AB - This study focused on crop type identification and area estimation of the cultivated parcels using images with 1.5m spatial resolution and 60km × 60km coverage from newly launched SPOT 6 satellite. A test site and a district in Sanliurfa Province, Southeastern Turkey were selected as study region where ground truth data was also available. After the geometric correction of SPOT 6 images; further image processing methods were applied. In the first step, a comparative analysis was performed at a test site to find out optimum parameters to be applied for this research. For this analysis, object based image classification (OBC) was applied to SPOT 6 image and feature extraction was performed from classification results to identify different parcels within the study area. Extracted features were compared to parcel vector database and accuracy metrics of parcel identification and area estimation was produced. In the second step, analysis was extended to district scale and classification OBC classification was performed for Suruc district of Sanliurfa. Accuracy assessment was performed with stratified random point selection for district scale classification results.
KW - Area estimation
KW - Crop type identification
KW - Object based classification
KW - Parcel level analysis
KW - SPOT6 satellite image
UR - http://www.scopus.com/inward/record.url?scp=84888861639&partnerID=8YFLogxK
U2 - 10.1109/Argo-Geoinformatics.2013.6621886
DO - 10.1109/Argo-Geoinformatics.2013.6621886
M3 - Conference contribution
AN - SCOPUS:84888861639
SN - 9781479908684
T3 - 2013 2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013
SP - 93
EP - 96
BT - 2013 2nd International Conference on Agro-Geoinformatics
T2 - 2013 2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013
Y2 - 12 August 2013 through 16 August 2013
ER -
