Flood Inundated Agricultural Damage and Loss Assessment Using Earth Observation Technique

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International Journal of Excellence Innovation and Development ||Volume 1, Issue 1, Nov. 2018||Page No. 060-069||

Flood Inundated Agricultural Damage and Loss Assessment Using Earth Observation Technique Md. Fazle Rabby1, Dewan Mohammad Enamul Haque2, Md. Selim3 1

Masters Student, Department of Disaster Science and Management, Faculty of Earth and Environmental Sciences, University of Dhaka, Bangladesh. 2 Assistant Professor, Department of Disaster Science and Management, Faculty of Earth and Environmental Sciences, University of Dhaka, Bangladesh. 3 Lecturer, Department of Disaster Science and Management, Faculty of Earth and Environmental Sciences, University of Dhaka, Bangladesh.

Abstract––Earth observation technique is an efficient way for flood damage mapping and assessment. This paper describes a synergic use of high resolution optical and radar image for retrieving information regarding flood inundation and resulting damage to the paddy fields. To reach the goal, Ullapara Upazila of Sirajganj District in Bangladesh has been selected as a test site and 2017 flood is the concerned event. In this research, the cultivable area (paddy field) identification and the corresponding yield calculation have been done for estimating damage and loss. “Polarimetry” and “Spectral and spatial analysis” techniques have been applied to extract the inundated area from Sentinel 1 radar and Sentinel 2 optical image respectively. In both cases, images for flood time have been used to estimate the damage. Sensitivity analysis has been performed for best parameter selection. The research outcomes have also been validated by the field observation. A significant amount of area has been inundated and 4798 hectares damaged croplands have been found from the radar image and 3937 hectares from the optical image and the economic losses have been found 18.06 crores and 14.82 crores respectively. Keywords––Damage and loss analysis, earth observation technique, polarimetry, sensitivity analysis, spatio-temporal analysis.

INTRODUCTION Flood disaster is a major threat to the environment and is responsible for the economic loss worldwide. A single major flood event can affect several countries simultaneously and can pressure on risk reduction and transfer [1]. Damage and loss assessment (DALA) is important for flood risk & crisis management but it is always challenging considering its complexity in dealing with big data, damage types, spatial and temporal scales i.e. depth of analysis [2,3]. Often due to the limitation and availability of data and information, simple approaches are used. Damage assessment depends on an assumption like spatial and temporal boundary selection and economic evaluation like depreciated values or replacement cost, classification of the element at risk, quantification of the exposed asset values and approaches for describing susceptibility [4]. Cost of www.ijeid.com

different types of natural hazard includes direct cost, indirect cost, intangible effect and cost of mitigation [5]. Nowadays Earth Observation (EO) technique is being widely used for disaster damage and loss assessment [69]. Flood monitoring, early warning, and rapid damage assessment have improved greatly because of the advancement in the geographic information system (GIS) and remote sensing (RS) [10]. Actual flood extent cannot be assessed fully from field visit because of the area vastness and the restriction of the mobility, thus EO data is important [11]. EO gives advantages where data is limited, costly and hard to access and needs frequent revisit times [12]. This situation has greatly improved because of availability of high-resolution satellite images, cost-effective flood monitoring, large area coverage and no risk to human lives [11,13]. Optical and radar data is common for flood monitoring and damage assessment and proven to be efficient in flood inundation mapping because of their distinct properties. [14-18]. Both these two sensors have respective advantages and disadvantages. The optical data is widely used to identify the water body form other land covers because of its distinct water reflectance property as it absorbs most of the incident solar energy [11]. Vegetation can be efficiently delineated from the other cover classes utilizing the information contained in a near-infrared and red band of optical imagery [6]. On the other hand, bad weather condition and presence of cloud is a major problem of optical images as flood occur mainly rainy season [12,16,19,20]. Microwave spectral bands of radar sensors are sensitive to the physical roughness of the surface and water is certainly smothered than other land cover types [12,19]. Radar imagery has the advantage over bad weather condition. Radar microwave pulse can penetrate through the cloud and applicable for both day and night and detect water under vegetation which makes radar extremely good for flood water area extraction [12,20,21]. But it has some problems. Presence of heavy rain and wind can cause roughening of the water surface and backscatter to like surrounding land. Multiple reflections can occur due to building and emergent vegetation, reduce the accuracy [22]. Land cover classification may sometimes a bit of difficulty because of surface roughness, speckle,

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