Determination of the Flooded Agricultural Lands with Spot 6 High Resolution Satellite Images: A Case Study of Menderes Plain, Turkey

2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) Pub Date : 2019-07-16 DOI:10.1109/Agro-Geoinformatics.2019.8820242

U. Alganci, Elif Sertel, S. Kaya

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引用次数: 1

Abstract

This research aims to determine the flooded agricultural lands after the flood that occurred in April 2015 on the Menderes Plain. The unexpected heavy and continuous precipitation in spring season induced a flash flood on the Menderes River, which directly damaged the agricultural lands. The flooded areas are determined by geographic object based GEOBIA classification of normalized difference water index (NDWI) data calculated from after-disaster SPOT 6 satellite image and land cover type of the flooded areas are verified from pre-disaster SPOT 6 satellite image. Moreover, topographic characteristics of the flooded areas are produced from open access ALOS W3D DSM data in order to investigate the relationship between the flood and topography. Results of this research exhibited that, optical satellite images are feasible data sources in determining flooded areas due to unique reflectance responses of them especially in the green and near infrared portions of the spectrum. Both flood extent and agricultural parcels affected by the flood are accurately mapped by using SPOT 6 image and GEOBIA approach.

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利用spot6高分辨率卫星图像确定被淹农田:以土耳其Menderes平原为例

本研究旨在确定2015年4月孟德雷斯平原洪水后被淹没的农业用地。春季出乎意料的连续强降水，导致门德斯河发生山洪暴发，直接破坏了农田。洪灾区域采用基于地理对象的GEOBIA分类确定，灾后SPOT 6卫星图像计算归一化差水指数(NDWI)数据，灾前SPOT 6卫星图像验证洪灾区域的土地覆盖类型。此外，利用开放获取的ALOS W3D DSM数据生成洪涝地区的地形特征，研究洪涝与地形的关系。研究结果表明，光学卫星图像具有独特的反射率响应，特别是在光谱的绿色和近红外部分，是确定洪水区域的可行数据源。利用spot6图像和GEOBIA方法，对洪水范围和受洪水影响的农业地块进行了精确的测绘。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)

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