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The Maoling gold deposit is located in the southwestern part of the Liaodong rift, NE China, and has estimated reserves of 25 t. In this paper we present the results of an investigation into the geochronology and geodynamic mechanisms of igneous activity and metallogenesis within the Maoling gold deposit. New zircon U–Pb age data, biotite 40Ar/39Ar age data, whole-rock geochemistry, and Hf isotopic analyses are presented in order to constrain the petrogenesis and mineralization of the deposit. Zircon U–Pb dating of the Wolongquan biotite monzogranite and Maoling biotite granite yielded mean ages of 194.0 ± 1.1 Ma and 196.1 ± 1.1 Ma, respectively. All the granites are characteristically high-K calc-alkaline, enriched in light rare earth elements and large ion lithophile elements, and depleted in high field strength elements, which is consistent with the geochemical characteristics of arc-type magmas. The Hf isotope characteristics indicate that the granites formed by partial melting of early Paleoproterozoic crustal material. In addition, biotite 40Ar/39Ar dating indicates that the Maoling gold deposit formed at 188.9 ± 1.2 Ma, implying that the mineralization was related to both the granite intrusions. Taking into account previous data on S–Pb–O–H isotopes and our new age data, the Maoling deposit can be classified as an intrusion-related gold deposit. Taking into account the geology of the study area and adjacent regions, we propose that the Maoling gold deposit and its associated granitic intrusions formed in a geodynamic setting that was dominated by subduction of the Paleo-Pacific Plate beneath the Eurasian continent.

Using Chagan Lake area as the study area and based on the DN value of sixth band of the Landsat 5 TM image of the region in 2011, this paper uses mono window algorithm to inverse the real surface temperature of the study area under the regional thermal radiation condition and curtained atmospheric transmissivity atmospheric transmission rate and emissivity. Then the inversion data and actual measured data are compared and analyzed. It is shown that the mono- window inversion algorithm achieved a high accuracy, and can better reflect the distribution of surface temperatures. On this basis, the temperature distribution of the region and its influencing factors are analyzed.