Papers by Raihan Jamil
Konsoer for their support and guidance throughout my research and studies. I also would like to t... more Konsoer for their support and guidance throughout my research and studies. I also would like to thank the LSU faculty, particularly Dr. Shelly Meng and Ms. Erika DeLeon, my colleagues, in addition to and classmates, especially Taylor Rowley for their information, encouragement, insightful reviews and feedback. I am thankful to everyone who has supported me in conducting this research directly and indirectly. I would like to give thanks to all the awesome members of the LSU Bangladeshi Students' Association for their wonderful, warm and cordial conducts. I am grateful to my parents, sisters, teachers, friends, and relatives for their motivations, best wishes, and support. I always find them beside me in any of my crises and hardships and they provide me the strength to move on. Finally, all praise is due to the Almighty, who has blessed me with His mercy. iii
Environmental Monitoring and Assessment, 2016
This paper attempts to detect soil salinity from satellite image analysis using remote sensing an... more This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R (2) value, low P value, and low Akaike's Information Criterion. About 20 % variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.
This paper discusses the usefulness of GIS and Remote Sensing (RS) technique in analyzing post-di... more This paper discusses the usefulness of GIS and Remote Sensing (RS) technique in analyzing post-disaster land use change. In doing so, it identifies the land use, as such, livelihood change pattern due to a Sidr, a devastating cyclonic storm-surge in southern part of Bangladesh. The study identifies the land use changes occurred due to the natural disasters using from satellite image interpretations with the help of GIS tools and RS. Firstly, different land covers (Agriculture, forest, ponds, etc.) were identified from the pre and post interpretation of satellite images. To detect the land use changes caused by natural disaster, the images of the study area before and after natural disaster were then used to identify the changes took place due to the natural disaster. The observed land use/ land cover change data are compared including statistical variation. Finally, how storm-surge, thus sea water intrusion leading to water logging and salinity directly and indirectly affects land use change is explained. The findings of the study can be very useful to prepare the action plans for reducing the vulnerability to natural disaster.
Environ Monit Assess, 2016
This paper attempts to detect soil salinity from satellite image analysis using remote sensing an... more This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R 2 value, low P value, and low Akaike’s Information Criterion. About 20 % variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.
This paper discusses the usefulness of GIS and Remote Sensing (RS) technique in analyzing post-di... more This paper discusses the usefulness of GIS and Remote Sensing (RS) technique in analyzing post-disaster land use change. In doing so, it identifies the land use, as such, livelihood change pattern due to a Sidr, a devastating cyclonic storm-surge in southern part of Bangladesh. The study identifies the land use changes occurred due to the natural disasters using from satellite image interpretations with the help of GIS tools and RS. Firstly, different land covers (Agriculture, forest, ponds, etc.) were identified from the pre and post interpretation of satellite images. To detect the land use changes caused by natural disaster, the images of the study area before and after natural disaster were then used to identify the changes took place due to the natural disaster. The observed land use/ land cover change data are compared including statistical variation. Finally, how storm-surge, thus sea water intrusion leading to water logging and salinity directly and indirectly affects land use change is explained. The findings of the study can be very useful to prepare the action plans for reducing the vulnerability to natural disaster.
Conference Presentations by Raihan Jamil
It has often been observed that predictions made by aeolian transport models do not match well wi... more It has often been observed that predictions made by aeolian transport models do not match well with transport data. The poor predictive capabilities of these models remains a fundamental problem. This study evaluates the effectiveness of the recently proposed model's modification in improving transport predictions. This is the mass-weighted frequency distribution proposed by Edwards and Namikas (2015). The evaluation consists of comparisons of predicted transport rates versus observed field and lab tested rates collected from the literature and recalibrating the best fit transport coefficient. The disparity between the predictions from the different models is reduced significantly. After the modification process, the model of Kadib (1965) and Hsu (1971) showed remarkable progress in their statistical parameter (high R 2 value and low RMSE value).
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Papers by Raihan Jamil
Conference Presentations by Raihan Jamil