【摘要】 当前武汉市城市更新行动，从大拆大建，进入“留改拆”并举的2.0时代，改造方式也从局部改造向成片连片更新转变。在当前2.0时代中，如何利用人工智能（Artificial Intelligence,AI）技术智能识别出城市“留改拆”单元显得尤为重要。当前AI和遥感技术已在自然资源典型地物类型识别、耕地保护和执法监察中得到广泛应用，本文第一次将AI和遥感技术用于“留改拆”单元的智能识别中，以辅助智能化城市更新行动。建立“留改拆”单元的样本，利用深度学习网络建立AI+遥感技术的智能化识别模型，选择遥感数据，进行武汉市更新片区“留改拆”单元智能化识别。通过遥感技术与深度学习算法的融合，提升了城市更新行动中“留改拆”单元识别的工作效率，为城市更新行动中的难点问题提供了科学依据。更多还原

【Abstract】 At present, the urban renewal action of Wuhan has changed from large-scale demolition and construction to the era of "retaining, replacing and dismantling". The transformation mode has also changed from local transformation to continuous renewal. In the current era, it is particularly important to identify urban "retained, replaced and demolished" units intelligently. Recently, the combination of AI and remote sensing has been widely used for the identification of typical surface features of natural resources, cultivated land protection,and law enforcement supervision. In this paper, we combine AI and remote sensing to identify "retention, reconstruction and demolition" units. First, we establish training samples of the "retention, replacement and demolition" unit, then use the deep learning network to establish the artificial intelligent model, and finally select the remote sensing data to carry out the identification of "retention, replacement and demolition" unit in Wuhan. The integration of remote sensing and deep learning improves work efficiency of the identification of "retaining,replacing and dismantling" units, and provides scientific basis for solving the pain points in urban renewal.更多还原