【摘要】 季节强降雨是诱发滑坡失稳的重要因素之一，特别是在我国中山丘陵地区，滑坡发生场景相对复杂，探究复杂情景下的滑坡检测方法对灾情评估、灾后应急调查等工作具有重要研究意义。针对遥感特征相近地物干扰造成滑坡识别精度低的问题，本文提出了一种结合PCA与IR-MAD的滑坡检测方法，实现了新生滑坡准确提取。结果表明，与现有方法相比，本文方法有效抑制了由作物播种收获、洪水汛期等季相因素产生的裸地、滩涂等滑坡遥感特征相似地物对滑坡检测造成的干扰，其在滑坡检测精确率和滑坡识别模型稳定性方面均有一定提升。更多还原

【Abstract】 Seasonal patterns of torrential rainfall is one of the primary triggering agents which predisposes to catastrophic landslides, especially in the complex terrain medium-elevation mountains and hilly of China. The geographic scene resulted in landslide occurrence is very complex. Therefore, exploring the landslide detection methods in complex situations has important significance for damage assessment and post-disaster emergency investigation. In this paper, we propose a landslide detection method combining PCA and IR-MAD to realize the accurate extraction of nascent landslide.The research results show that compared with the existing methods, the proposed method effectively inhibits the disturbance of landslide detection caused by seasonal factors such as crop seeding and harvest, flood season caused by heavy rainfall, and other similar remote sensing features of bare land and tidal flat. The accuracy rate of landslide detection and the stability of landslide identification model have been improved to a certain extent.更多还原