Analysis Of Work Crop Damage Due To Flood Using Remote Sensing & GIS

One of the major challenges during flood is to get an overall view of the incident with accurate extent of the affected area and assessment of damaged property. Using traditional methods such as ground survey and aerial observation, flood mapping is time consuming, expensive and need to be involved skilled persons. Moreover, if the occurrence is extensive then it is very difficult to monitor the flood event accurately and quickly. Nowadays, the availability of multiple satellite data can be used as an effective alternative to monitor flood situation and extent in the particular area.

The analysis of spatial extent and temporal pattern of flood inundation from remotely sensed imagery is of critical importance to flood mitigation and management. Knowledge of the spatial extent of extreme flooding is an asset for decision makers and disaster relief agencies to efficiently provide immediate and lasting support to those populations affected by flood events.

In this research work crop damage due to flood have been analysed using Remote Sensing & GIS for decision makers and crop insurance industries. To meet the research objectives MODIS NDVI product (2000-2011), Landsat TM and Landsat ETM+ satellite images were used. All the data is freely available and downloaded from NASA website. In this research work flood induced area have been calculated using geospatial technology. Further, flood induced agricultural crop area have been examined. To assess flood induced area water indices i. e. NDWI, RSWIR and GSWIR have been used. Total of 18676. 90, 18158. 60 and 20238. 70 hectares of area was found flood inundated on 11th September 2008 using NDWI, RSWIR and GSWIR water indices respectively. Whereas, 6336. 05, 9842. 06 and 13606. 90 hectares of area was found flooded on 27 September 2008 using above mentioned water indices. The comparative analysis of NDWI, RSWIR and GSWIR using spatial statistical techniques and visual interpretation suggests RSWIR to be more efficient for delineating water bodies during floods. Post event Landsat ETM+ data is used to find out affected agricultural crop area. The damaged agricultural crop area was analysed using NDVI technique. Further, based on the affected crop area the deluged villages were divided into four categorize such as low, moderate, total and no damage crop area.

NDVI values showed the decrease of vegetation covers and an increase of water covers (negative NDVI values) after the flood of September 2008. Results shows that, most of the agricultural crop in the villages were totally damaged during the flood of September 2008, very few villages were found moderate and low damaged. Agricultural crop in 123 villages were found totally damaged, whereas agricultural crop in 23 villages and 4 villages were found moderate and slightly damaged respectively. Only 1 village was found with no damage. In this research mismatch between actual crop damage and compensation paid to the farmers against crop damage is also assessed. Number of villages affected and agricultural crop area affected in the villages have been analysed using geospatial technology. The similar data have been collected from the Government agencies, compensation paid to the farmers against the crop damage is also collected and then comparative analysis have been done on the data analysed through geospatial technique and data collected from the Government organization. The analysis showed differences between agricultural crop area damaged through Remote Sensing and GIS and data collected from the Government organization. About 17636. 95 hectares of agricultural land was found damaged in 154 villages using Remote Sensing and GIS. However, according the data collected from the government organization about 12079. 32 hectares agricultural land in 70 villages were affected due to the flood. Inputs for crop insurance industries i. e. spatial extent of the flood, affected agricultural crop area, inundation duration and crop condition profile is prepared to formulate crop insurance policies. For the validation of the analysis flood year NDVI and normal year NDVI have been compared. It is clear from normal year and flood year NDVI maps that, normal year NDVI is higher than the flood year NDVI. Field survey was also done to verify the results. This research work presented an overview of flood mapping and Geospatial technology to measure the potential impact of extreme flood events on agricultural land in Banki and Dampara Block, Cuttack, Odisha. The results indicate satellite data-based information during flood and post-flood along with GIS and ground information, flood damages can also be estimated. Based on the duration of flooding, area affected, types of land use features etc. , flood damage map can be prepared.

On the basis of above it could be concluded that, NDVI can be used to extract affected agricultural crop area due to flood. Water indices such as NDWI, GSWIR and RSWIR can be used to determine the flood water. EO as one of the major data sources to timely and automatically estimate flood induced area, crop damage and other flood-related products. The results obtained from Geospatial technology could be used for crop insurance policy formulation, and flood crop damage compensation.