| Due to the long construction period of the railway construction,large floor space and high resource consumption,it will inevitably have a greater impact on the surrounding environment and ecology during the construction process.In particular,the impact of temporary land occupation such as borrow pits,spoil grounds,construction camps,and mixing stations during the construction period of railway construction projects on the ecological environment.Therefore,it is very necessary to implement environmental monitoring for temporary land occupation of railway construction.Most of the traditional environmental monitoring methods use manual survey methods,which require a large amount of manpower and material resources,and cannot comprehensively and dynamically monitor environmental changes.High-resolution remote sensing imagery have the advantages of wide coverage,strong real-time performance,high resolution,low cost,and high degree of automation,which can effectively compensate for the shortcomings of traditional environmental monitoring methods.In this thesis,highresolution remote sensing imagery are applied to the temporary land occupation environment monitoring of railway construction.The main research contents are as follows:(1)Research on the extraction of temporary land occupation classification information based on remote sensing images.The method of compare after classification is used to detect the environmental change information of temporary land occupation,and an adaptive spatial information MRF based FCM clustering algorithm is proposed.The spatial attraction model and spatial structural features are combined with the traditional MRF,and the MRF of adaptive spatial information is constructed.Then introduced it into the FCM clustering algorithm,so that the algorithm can not only overcome noise influence but also preserves the image edge details.In addition,this method changes the traditional way of fixing spatial information neighborhood weights.The experimental results show that the classification results of the proposed algorithm are good and can be used to extract the current status of the temporary land occupation environment.(2)Temporary land occupation changing information extraction and environmental monitoring and evaluation based on remote sensing images.To further monitor the environmental impact of temporary land occupation this thesis proposes a change detection method based on density attraction and multi-scale and multi-feature fusion to monitor environmental changes in temporary land occupation.The method firstly considers the different contributions of different features,realizes the adaptive weighted combination of spectral features and texture features,and uses information entropy to adaptively fuse texture features with different scales and different directions.Secondly,the density attraction model is combined with the traditional MRF to construct the adaptive weight MRF,which changes the same spatial information weight of the traditional MRF.The experimental results show that the method makes full use of different features,better preserves the image edge detail information,improves the detection accuracy of the change,and can be better used for temporary land occupation environmental monitoring.(3)Design and implementation of a temporary land occupation remote sensing environmental monitoring system.Secondary development based on the open source project MapWindowGIS,and four modules of image classification,change monitoring,accuracy evaluation and environmental assessment are realized.The system is convenient and simple to operate,and provides a secondary development interface,which has high practical value. |
