基于机器学习的生产建设扰动范围识别技术研究——以上海市浦东新区为例

Research on the Identification Technology of Production and Construction Disturbance Range Based on Machine Learning—Taking Pudong New Area, Shanghai as an Example

摘要: 为准确掌握生产建设扰动范围，提升水土保持监督管理工作效率，以上海市浦东新区为研究案例，探索了基于机器学习的生产建设扰动范围识别技术研究。该研究开发了基于遥感指数计算、轮廓识别的面向对象人工智能识别方法。通过调用ENVI/IDL和ArcGIS Engine软件的图像处理功能，结合实地调研数据对比，实现水土保持生产建设项目识别的自动化。所识别的内容包括生产建设项目扰动区域的地理位置、形状轮廓和面积范围。研究结果表明该方法总体精度正确率达86.2%，具有巨大的应用潜力。

Abstract: To accurately grasp the disturbance range of production and construction activities and enhance the efficiency of soil and water conservation supervision and management, this study takes Pudong New Area in Shanghai as a case study and explores the technology of identifying the disturbance range of production and construction activities based on machine learning. The research utilizes an object-oriented artificial intelligence recognition method that combines remote sensing index calculation and contour recognition. By utilizing the image processing functions of ENVI/IDL and ArcGIS Engine software, and comparing with field survey data, it achieves automation in the identification of soil and water conservation production and construction projects. The identified content includes the geographical location, shape contour, and area range of the disturbance areas caused by production and construction projects. The research results show that the overall accuracy of this method reaches 86.2%, indicating its great potential for application.