Potential Analysis Of GF-5 To Monitor The Risk Source In Drinking Water Source

GF-5 being launched in 2017 is one of China's new generation high spectral resolution remote sensing satellite.It can be used to dynamically monitor the risk source in drinking water source.The purpose of this paper is to explore the potential of the GF-5 satellite to monitor the risk source in drinking water source.Based on Yuqiao reservoir and its surrounding for the study area,in the absence of proper simulated GF-5 data,Landsat-8 OLI data sharing a similar spectral and spatial setup with GF-5 data is used as substitution,statistics and analyze the spectral characteristics and index characteristics of village,industrial land,mining land,cultivated land and planting greenhouse,then discusses the target object separability in the remote sensing image,which will benefit for detecting the potential of remote sensing image.This paper makes the following concrete work:(1)According to GF-5 20 m resolution satellite full spectrum parameters of multi spectral visible spectrum and SWIR,we fusion the 30m multi spectral data and 15m panchromatic data,then the 15m fusion data will be resize to 20 m spatial resolution.(2)The water management requirements will be considered into,and field expert knowledge,field research,and the high resolution image interpretation means will be utilized,then we will reference attributes and land use remote sensing image features,we optimize the risk source of drinking water in experimentation area class system.(3)Under the analysis of single source image in drinking water sources,we select a remote sensing image of May 13,2016,to achieve statistical visualization of mean spectral features and index characteristics of different objects,the result shows that the test area of woodland,water,aquaculture and bare land in the remote sensing images respectively can realize the distinction between and other objects,and between the rest of man-made objects of natural objects is difficult to achieve distinction.(4)Remote sensing images were taken from the experimental area on 23 February 2016,13 May 2016 and 23 December 2016,typical indistinguishable objects as the main research object based on the result of the single image analysis.we use the visual way of the multi temporal image index statistical feature,and research and discuss the objects distinction performance before atmospheric correction and afer atmospheric correction.The results show that the multi temporal images atmospheric correction can effectively improve the classification.Meanwhile,in remote sensing image data of phase selection,it is best to use the remote sensing image of winter,and the second is the spring,finally the phase of the summer.