煤矿高强度开采易引起地表沉陷和地裂缝等灾害，损伤地表生态，甚至诱发遗煤自燃，威胁煤矿安全生产。 西部矿区土地荒漠化严重，部分矿区地表覆盖风积沙，地表采动裂缝易被风积沙掩盖，常规监测方法难于识别采动地表浅层隐蔽裂缝。 为探究采动地表浅层隐蔽裂缝识别的可行性 提出了基于无人机红外识别采动地表浅层隐蔽裂缝的方法。 以神东矿区大柳塔煤矿 52605 工作面为工程背景，对工作面上方一地表采动裂缝设计不同埋深的隐蔽裂缝并于夜间进行连续监测，获取了不同时刻的红外图像，并对不同时刻红外图像中隐蔽裂缝、风积沙、植被的温度信息进行了提取和分析。 研究结果表明:基于无人机搭载红外相机可有效识别采动地表浅层隐蔽裂缝且不同时刻可识别的埋深不同，隐蔽裂缝与周围地物温差越大，其越易于被识别。 隐蔽裂缝温度在采动裂缝导热和环境温度共同作用下不同于周边地物的温度，且与埋深相关性较强。 该研究条件下，21:00 pm 至 5:00 am，隐蔽裂缝温度、地表采动裂缝温度、风积沙温度、植被温度不断下降。 1:00 am 至 5:00 am 期间，不同埋深隐蔽裂缝与风积沙的绝对温差均≥1.2 °C 、与植被的绝对温差均≥2.1 °C ，绝对温差较大，此期间易于识别隐蔽裂缝。 而 21:00 pm 时，埋深 15，20，30 cm 隐蔽裂缝与风积沙的绝对温差分别为 0.8，0.6，0.8 °C ;23:00 pm 时，埋深 20 cm 隐蔽裂缝与风积沙的绝对温差为 0.7 °C ，温差绝对值相对较小;因此，21:00 pm，23:00 pm 时上述埋深的隐蔽裂缝难于识别。

High mining intensity of coal mines can induce disasters easily，such as surface subsidence and ground fis⁃ sures，and damage surface ecology. Moreover，the spontaneous combustion of residual coal also appears，which can threaten the safety of coal mine production. In addition，the degree of desertification is relatively serious in the western mining area.The surface of some coal mines is covered with aeolian sand，which easily leadsto the ground mining⁃induced fissures covered by aeolian sand. The shallowhidden mining⁃induced ground fissures are difficult to be identified by the conventional monitoring methods. To explore the feasibility of identifying shallow hidden mining⁃in⁃ duced ground fissures，a method based on an unmanned aerial vehicle (UAV) infrared technology was proposed. Tak⁃ ing working face No.52605 of the Daliuta coal mine in the Shendong Mine area as the engineering background， the hidden mining⁃induced fissures with different buried depths were designed and prepared. At night，the infrared im⁃ ages at different times were obtained by continuous monitoring. The temperature of the hidden mining⁃induced fissures，aeolian sand，and vegetation in infrared images at different times were statistically analyzed. The results show that a UAV equipped with an infrared camera can effectively identify the shallow hidden mining⁃induced ground fissures，and the buried depth of the identified hidden mining⁃induced fissure is different at different times. The greater the temperature difference between hidden mining⁃induced fissures and surrounding ground objects，the easier it is to be identified. The temperature of the hidden mining⁃induced fissure is different from that of surround⁃ ing ground objects under the combined action of heat conduction of mining⁃induced fissure and ambient temperature and has an obvious correlation with burial depth. Under the research conditions of this paper， the temperature of the hidden mining⁃induced fissure，ground mining⁃induced fissure，aeolian sand，and vegetation decreases continu⁃ ously from 9:00 pm to 5:00 am. The absolute temperature difference between hidden mining⁃induced fissures with dif⁃ ferent burial depths and aeolian sand and vegetation is large between 1:00 am and 5:00 am. The absolute tempera⁃ ture difference between hidden mining⁃induced fissureswith different buried depths and aeolian sand is ≥1.2 °C， and the absolute temperature difference between hidden mining⁃induced fissures and vegetation is ≥ 2. 1 °C . Therefore，the hidden mining⁃induced ground fissuresare easy to be identified during this period. However，at 9:00 pm，the absolute temperature difference between hidden mining⁃induced fissures buried 15，20，and 30 cm and aeolian sand is 0.8，0.6，and 0.8 °C，respectively.At 11:00 pm，the absolute temperature difference between hidden mining⁃in⁃ duced fissures buried 20 cm and aeolian sand is 0.7 °C.The absolute value of temperature difference is relatively small，and the hidden mining⁃induced fissures with the aforementioned buried depths are difficult to be identified from 9:00 pm to 11:00 pm.