Super cyclone 'SIDR'


Super Cylone SIDR, AFP

In Depth Coverage

Digital Change Detection of Super cyclone 'SIDR' of the Barguna District using State- of-the art Remotely Sensed Imageries

A tropical cyclone occurrence is a gigantic catastrophic natural hazard in Bangladesh. So far many people, properties, crops, livestock and the whole economy have been damaged by cyclone activities in the southern coastal region of Bangladesh. Those cyclones have been coming and affecting the area from north-western of Indian Ocean to southern coast region of Bangladesh since 1960. This study will estimate the impact of 'super cyclone' SIDR, assessing damage to physical and cultural features and quantifying present hydrology and high concentration of vegetation in the target study area using remote sensing technique and geographic information system techniques.

  • Link With Climate Change


    Climate change due to increasing greenhouse gases from anthropogenic activities has led to higher sea level in tropical ocean basins, higher global mean surface temperature, melting of ice at the North Pole, and regional climate sensitivity all of which contribute to stronger tropical cyclones. Cyclone damage to existing physical and cultural features causes water pollution, various diseases, famine, and ecosystem changes that affect biodiversity as well as agricultural systems in the southern coast of Bangladesh.

  • Objectives


    The explicit objectives of the research are as followings,

    1.To map and estimate the damage of the target study area on the cyclone SIDR.
    2.Detect digital changes of major land use feature before and after cyclone SIDR.
    3.Investigate damages of hydrological characteristics in the target study area.
    4.Quantify present high concentration of vegetation using suitable indices.

  • Work plan


    To be developed

  • Schedule


    To be developed

  • Technical and Scientific Approach & Methods Proposed


    Proposed Methodology
    The proposed methodological steps are as follows:

    1 Pre-processing:
    Geometric Correction:
    Geometric correction is the best possible technical way to remove geometric distortion of an image. It makes a good relationship between the raw image coordinate system to target coordinate system. Zone 46 North of Universal Transverse Mercator (UTM) will be selected as master coordinate system in this study. Raw digital images usually contain geometric distortions so significant that they can not be used directly as a map base without subsequent processing (Lillesand & Keifer, 2004).

    2 Image Processing:
    Image Masking:
    A vector polygon map of the study area can be used to extract study area from different types of sensor data.

    Training Data Collection:
    Training data (field) or area of interest is commonly used and plays a vital role in remote sensing image analysis. For each training dataset, real object information is collected from the real environment as well. The purpose of field data is to permit reconstruction, in as much detail as possible, of ground conditions at the place and time that imagery was acquired (Campbell, 1996). A field data collection and reconnaissance will be performed randomly by modern GPS. It is also used for doing visual checking and evaluation (Pellikka et al. 2004).

    Image Classification:
    Image classification techniques are a very significant procedure used to reach the specific objective of any kind of remote sensing research. In this study, image classification should be used as a vital function during the analysis stage using pre and post cyclone SIDR imagery. Supervised classification method is recommended in this study. Supervised classification will be done using sample training areas (Pellikka et al. 2004). Maximum likelihood and spectral angle mapper (SAM) classifier of supervised classification techniques will be followed to carry out satellite image classification in this study.

    Change Detection:
    Change detection where satellite images acquired at different times are compared has been used within remote sensing for a long time (Perez et al, 2001). It is a very useful way to detect change from previous condition to recent condition of the environment especially pre and post of cyclone SIDR situation. Many change detection techniques have been developed (Moran et al, 2004); like write function memory insertion, multi-date image composite, image algebra, post classification comparison, image regression, image differencing, image rationing, principle component analysis, change vector analysis and so on. Image difference and image statistics of post classification comparison method of change detection are strongly recommended in this research. Post classification comparison change detection is widely used and easy to understand (Jensen, 1996). Image difference method will show visual change of two classified image of pre and post cyclone SIDR and on the other hand, image statistics method will describe statistical change between pre and post cyclone SIDR damage by area, percentage and image pixel. In a variety of studies, the post-classification change-detection method was found to be the most suitable for detecting land cover change (Weismiller et al., 1977; Wickware and Howarth, 1981). The change detection statistics routine is used to compile a detailed tabulation of changes between two classification images (Gabriels et al, 2006).

    3 Post-Classification
    Accuracy Assessment:
    Accuracy assessment is a viable way to determine the accuracy of thematic mapping. Here the processed images will input as classified data and ground truth GPS data input as reference data in a confusion matrix or contingency matrix table. Confusion Matrix shows the accuracy of a classification result by comparing a classification result with ground truth information (ENVI, 2006). More pay attention will be given on overall accuracy as well as producer and consumer accuracy in this study. It is a measure of the difference between the actual agreement between reference data and an automated classifier and the chance agreement between the reference data and a random classifier (Lillesand & Keifer, 2004).

    4 Review Existing Data
    After completing the research, the results should be checked for cross validation with existing databases that have been produced by government or non-government agency.

  • Results


    It is anticipated that multi sources data set with direct field data will yield high accuracy of research analysis or damage assessment. Both spatial and non-spatial databases from satellite imagery, GIS layers and human interaction will be shown to be useful tools for assessing the damage of SIDR in the target study area.

  • Deliverables


    To be developed

  • Use of Satellite Imagery and GIS Solutions


    To be developed

  • Local Actions


    The results of this research should be added as crucial component towards sustainable coastal development and disaster management. Some seminars with local inhabitants can be arranged during field investigation concerning cyclones and their impact focusing on the recent affect of cyclone SIDR. Outputs of this research will be printed out and sent to the local authorities.

  • Region Name

    Barguna District, Bangladesh
  • Partners involved in project

    Jim Cory Founder, GIS Analyst Horizon Mapping (, Wisconsin, USAjcory17@charter.netTel: 608-233-4730