基于图像识别的山地城市绿色空间景观生态破损区域监测技术

Image recognition based ecological damage area monitoring technology for green space landscape of mountainous cities

传统区域监测方法不能根据山地城市绿色空间景观生态破损区域的具体图像情况进行实时监测。为了有效解决此问题,建立新型基于图像识别的山地城市绿色空间景观生态破损区域实时监测模型。通过山地城市绿色空间景观生态破损区域特征判断、基于特征判断的识别方法确定、卷积神经网络,完成山地城市绿色空间景观生态破损区域的图像识别。通过实时目标检测、确定实时监测区域、透视变换,完成基于图像识别区域实时监测模型的搭建。设计对比实验结果表明,新型区域监测模型与传统模型相比,充分提升了山地城市绿色空间景观生态破损区域识别图像的清晰度,并可对区域内景观进行实时监测。

As the real-time monitoring of ecological damage area cannot be performed according to its specific images for green space landscape of mountainous cities in the traditional area monitoring method,a new ecological damage area real-time monitoring model for green space landscape of mountainous cities is established based on image recognition. Ecological damage area image recognition for green space landscape of mountainous cities is accomplished by means of ecological damage area feature judgment for green space landscape of mountainous cities,recognition method determination based on feature judgment,and convolutional neural network. Establishment of image recognition based area real-time monitoring model is accomplished by means of real-time target monitoring,determination of real-time monitoring area,and perspective transformation. A comparison experiment was designed. The results show that in comparison with the traditional model,the new area monitoring model can fully improve the definition of ecological damage area recognition images for green space landscape of mountainous cities,and perform real-time monitoring of the landscape in the area.