Saptarshi Mondal | Birla Institute of Technology, Mesra (Ranchi) India (original) (raw)

Papers by Saptarshi Mondal

The advancement in satellite technology in terms of spatial, temporal, spectral and radiometric r... more The advancement in satellite technology in terms of spatial, temporal, spectral and radiometric
resolutions leads, successfully, to more specific and intensified research on agriculture. Automatic
assessment of spatio-temporal cropping pattern and extent at multi-scale (community level,
regional level and global level) has been a challenge to researchers. This study aims to develop a
semi-automated approach using Indian Remote Sensing (IRS) satellite data and associated vegetation
indices to extract annual cropping pattern in Muzaffarpur district of Bihar, India at a fine scale
(1:50,000). Three vegetation indices (VIs) – NDVI, EVI2 and NDSBVI, were calculated using three
seasonal (Kharif, Rabi and Zaid) IRS Resourcesat 2 LISS-III images. Threshold reference values
for vegetation and non-vegetation thematic classes were extracted based on 40 training samples over
each of the seasonal VI. Using these estimated value range a decision tree was established to classify
three seasonal VI stack images which reveals seven different cropping patterns and plantation. In
addition, a digitised reference map was also generated from multi-seasonal LISS-III images to check
the accuracy of the semi-automatically extracted VI based classified image. The overall accuracies of
86.08%, 83.1% and 83.3% were achieved between reference map and NDVI, EVI2 and NDSBVI,
respectively. Plantation was successfully identified in all cases with 96% (NDVI), 95% (EVI2) and
91% (NDSBVI) accuracy.

The enhancement technique is basically done for the betterment of image interpretability and anal... more The enhancement technique is basically done for the betterment of image interpretability and analysis. This may be statistical or object oriented. For the study like change detection or object dynamics, object oriented enhancement shouldbe given importance. The object oriented enhancement can be said as supervised enhancement which like the point operation, is the combination of spectral bands using algebraic operation from mathematical or algebraic functions by which selected target spectral features can be enhanced. In this present study a new object oriented enhancement algorithm has been proposed and a raster codification technique has been done to monitor the cropland type i.e. single, double, multiple etc within Bardhaman block of Bardwan district and has been applied on multi-seasonal digital database to get the
typification of the croplands. Finally the distribution pattern of the crop land type has been experienced.

Conference Presentations by Saptarshi Mondal

Word Limit of the Paper should not be more than 3000 Words = 7/8 Pages)

The advancement in satellite technology in terms of spatial, temporal, spectral and radiometric r... more The advancement in satellite technology in terms of spatial, temporal, spectral and radiometric
resolutions leads, successfully, to more specific and intensified research on agriculture. Automatic
assessment of spatio-temporal cropping pattern and extent at multi-scale (community level,
regional level and global level) has been a challenge to researchers. This study aims to develop a
semi-automated approach using Indian Remote Sensing (IRS) satellite data and associated vegetation
indices to extract annual cropping pattern in Muzaffarpur district of Bihar, India at a fine scale
(1:50,000). Three vegetation indices (VIs) – NDVI, EVI2 and NDSBVI, were calculated using three
seasonal (Kharif, Rabi and Zaid) IRS Resourcesat 2 LISS-III images. Threshold reference values
for vegetation and non-vegetation thematic classes were extracted based on 40 training samples over
each of the seasonal VI. Using these estimated value range a decision tree was established to classify
three seasonal VI stack images which reveals seven different cropping patterns and plantation. In
addition, a digitised reference map was also generated from multi-seasonal LISS-III images to check
the accuracy of the semi-automatically extracted VI based classified image. The overall accuracies of
86.08%, 83.1% and 83.3% were achieved between reference map and NDVI, EVI2 and NDSBVI,
respectively. Plantation was successfully identified in all cases with 96% (NDVI), 95% (EVI2) and
91% (NDSBVI) accuracy.

The enhancement technique is basically done for the betterment of image interpretability and anal... more The enhancement technique is basically done for the betterment of image interpretability and analysis. This may be statistical or object oriented. For the study like change detection or object dynamics, object oriented enhancement shouldbe given importance. The object oriented enhancement can be said as supervised enhancement which like the point operation, is the combination of spectral bands using algebraic operation from mathematical or algebraic functions by which selected target spectral features can be enhanced. In this present study a new object oriented enhancement algorithm has been proposed and a raster codification technique has been done to monitor the cropland type i.e. single, double, multiple etc within Bardhaman block of Bardwan district and has been applied on multi-seasonal digital database to get the
typification of the croplands. Finally the distribution pattern of the crop land type has been experienced.

Word Limit of the Paper should not be more than 3000 Words = 7/8 Pages)