Bulletin des sciences géographiques de l'INCT
Volume 16, Numéro 1, Pages 52-58
2012-06-30
Authors : Mansour D . Saha S.k . Patel N.r . Road Kalidas .
This paper reviews the application of remote sensing techniques and maximum likelihood classification for crop discrimination, using optical data for crop identification in both crop seasons (Rabi and Kharif'). Satellite data are extensively used to produce the crop and land use inventory. The present study was conducted to evaluate the contribution of multi -temporal images analysis to elaborate the cropland land use inventory. This study has been carried out for Saharanpur district of Uttar Pradesh State for crop acreage estimation and yield distribution, during Rabi and kharif of the year 2005-2006. Two types of data have been used in this study - IRS IC- LISS III for October 15,2005 and IRS IC- LISS III for February 12, 2006. In this approach, the district administrative boundary of Saharanpur district was overlaid over the remote sensing image to extract the image Saharanpur district in ali four bands. Then crops area were identified and estimated by following super vised maximum likelihood digital classification. Statistic results of multidate images classification of March and October, show accuracies 91.41% and 97% respectively for October and February. As well as the yield distribution around 39% of geographical area of Saharanpur district between 32q/ha to 39q/ha.
remote sensing, digital classification, crop inventory, acreage, yields.
صالحة د. رائد أحمد طه
.
أبو حويج مرفت جابر
.
المغير د. م. محمد محمد عبد ربه
.
ص 803-832.
تاهمي صادق
.
ص 04-14.
Benslimane , M
.
Hamidet A
.
Seddini A
.
Mederbel K
.
pages 18-36.
Fouzia Rouagh
.
pages 21-28.
Merah Othmane
.
pages 25-33.