Analysis Of Changes In Agricultural Planting Before And After The Syrian Civil War Based On Remote Sensing

In early 2011,a democratic protest broke out in Syria and spread to the entire Arab world.By December of this year,the United Nations officially declared a struggle between the Syrian government forces and various factions,and the civil war officially began.By June 2014,ISIS(Islamic State)declared the establishment of the Caliphate and occupied a large area of Syria.With the development of social science and technology,remote sensing technology is widely used in the fields of environmental resource census,earthquake prevention and disaster mitigation,agricultural estimation,war disaster,and social development,etc.due to its characteristics of multi-time,accuracy and wide range.This paper takes the Syrian civil war as the research background and uses the analysis of the changes in agricultural cultivation in the country to objectively evaluate the impact of war on people's lives.Therefore,the time series MODIS image and time series Landsat series of images before and after the outbreak of the civil war in Syria were selected as the data source to extract the planting area of the main crops(cereal crops,cotton,double crops),and analyze the Syrian civil war on this basis.The main research contents and conclusions of the degree of damage to agricultural cultivation in the region are as follows:(1)Remote sensing technology is an effective means of assessing the civil war in Syria.It is found through statistics that food crops are seriously affected by the war(reducing 40% before the war).Therefore,based on remote sensing images before and after the Syrian civil war(2010 and 2017),the main crops were extracted,and the impact of war on the agricultural planting structure in Syria was accurately analyzed.At the same time,the technical route of central thought drawing was established.(2)Medium-resolution MODIS images and higher-resolution Landsat series images are ideal remote sensing data sources with wide spatial and temporal scales in the extraction of cultivated land and crop planting structures,and the MODIS of the entire period is obtained by band extraction and calculation.Image NDVI and NDVI of EVI and Landsat series of images,while using Google Earth and Landsat series of high-resolution images for sample point selection of each category.(3)Using SG,AG,DL three filtering methods to curve the 2017 MODIS NDVI and EVI data with the multi-temporal Landsat NDVI data,and found that both data are better reflected in the Syrian region.The phenological changes of the crops were performed,so the SG filter data reconstruction was performed separately;and 11 phenological parameters were respectively performed on the MODIS NDVI and EVI reconstruction data by TIMESAT 3.1 under MATLAB(Start of season,End of season,Length of season,base value,Position of middle of season,Maximum of fitted data,Amplitude,Left derivative,Right derivative,Small integral,Large integral,and the extraction by PH)are combined into nine Situation: SGNDVI,SGEVI,SGNDVI+SGE VI,PHNDVI,PHEVI,PHNNDVI+PHEVI,SGNDVI+PHNDVI,SGEVI+PHEVI,SGND VI+PHNDVI+SGEVI+PHEVI.(4)To carry out crop classification research on the above nine combined data and the NDVI of the reconstructed Landsat series of images.Firstly,the 9 kinds of combined data of MODIS images are used to establish a decision tree by using the QUEST method in the ENVI extension module RuleGen,and the main crops are classified.Accuracy verification comparison:SGNDVI+PHNDVI>SGNDVI+PHNDV I+SGEVI+PHEVI>SGNDVI+SGEVI>SGNDVI>SGEVI+PHEVI>SGEVI>PHEVI>PHNDVI+PHEVI>PHNDVI,the KAPPA coefficient of the highest precision combination(SGNDVI+PHNDVI)It is 94.42 as the classification result of the final MODIS data.Then,the NDVI data reconstructed by Landsat in 2017 is band-synthesized in chronological order,and the planting information of the main crops is extracted by using the object-oriented rule set method.Finally,the results of the classification of the two types of data are compared,and both have better classification results.The MODIS data is more convenient and faster,more applicable to the world,and the methods available are more flexible,so the classification results of MODIS data are finally selected for analysis.(5)Analysis of the classification results of major crops before and after the Syrian Civil War(2010 and 2017)of MODIS data,using crop landscape pattern index:crop type change range and crop dynamic degree(crop dynamic degree)Analysis of changes in Syria's two major crops over the past two years.According to the two indices,the intensity of crop damage in 13 provinces in Syria will be divided into five levels: the intensity of Damascus and Deir ez-Zor is 5;Aleppo The intensity of theprovince of Idlib is 4;the intensity of Hasaka and Raqqah is 3;the intensity of Latakia,Hama and Sweda is 2;Tartus Province,Holm The intensity of the provinces,Quneitra and Dar'a is 1.