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Cirques are typical erosional landforms of glaciers and have been used as bases for paleoclimate and paleoenvironment reconstruction and for understanding the interactions between glacial erosion, climate, and topography. The availability of high-resolution digital elevation models (DEMs) provides the opportunity to map large populations of cirques for regional and global scale analysis. However, cirque outlines are still mainly determined based on manual digitization, which is time consuming and labor intensive. This paper introduces an automated method to recognize and delineate cirques using DEMs based on a series of hydrological and morphological analyses, including delineating stream network, filtering streams, determining potential cirque threshold points, and delineating cirque outlines. A semi-automated tool is also developed based on user-specified threshold points or cross sections. The related tools are coded in python and imported into ArcGIS as a toolbox, AutoCirque, with user friendly interfaces. Comparison in a test area of the eastern Tian Shan, China, indicated that the population statistics are relatively consistent between manually digitized and auto-delineated cirques. Detailed comparisons for 11 selected cirques indicated that the AutoCirque-delineated and manually digitized cirque outlines are similar in shape with an average boundary offset of approximately one DEM cell size (30 m) and a 70–90% overlap-fit percentage. The derived cirque metrics are also similar, especially for elevation, slope, and aspect related metrics. This toolbox can significantly speed up the analytical processes, remove the subjectivity in delineating cirque outlines, and allow for the comparison of cirque morphology and metrics at regional and global scales. • This paper presents an automated method to delineate cirque outlines from DEMs. • The developed ArcGIS toolbox incudes both fully automated and semi-automated tools. • Delineated cirques have consistent population statistics with manual-digitized ones. • Manual- and auto-derived cirques are similar in shape with high overlap percentage. • This toolbox allows for large population analyses of cirques at different scales. [ABSTRACT FROM AUTHOR]

Reconstructing three-dimensional palaeoglacier surface, thickness, and volume provides useful information for quantifying palaeo-climate conditions during glacial stages and assessing the impact of glacier change on water resources. A glacial flowline model has been implemented in Excel and ArcGIS to reconstruct palaeoglaciers based on digital elevation models and geomorphic constraints, such as moraines and trimlines that represent the margins and local heights of palaeoglaciers, respectively. However, significant efforts are still needed in using these tools for palaeoglacier reconstruction, such as digitizing flowlines, adjusting shear stress, and deriving shape factors. This paper presents an automated method, PalaeoIce, to reconstruct palaeoglaciers using geomorphic constraints. Coded in python, PalaeoIce is an ArcGIS toolbox with a set of tools to generate glacial flowlines, optimize shear stress, derive shape factors, calculate ice thickness values along flowlines, and interpolate palaeo ice surfaces based on geomorphic constraints. The use of PalaeoIce is demonstrated using extant glaciers with measured thickness values and moraines/trimlines of the Little Ice Age (LIA) and Marine Isotope Stage (MIS) 2 in the eastern Tian Shan, China. The reconstructed ice thickness values of Glacier No. 1 in this area show a reasonable agreement with field measurements with 1.4 % and 5.4 % differences between measured and reconstructed mean ice thickness values using the two methods included in PalaeoIce: a revised ice thickness model for extant glaciers and a palaeoglacier reconstruction method based on glacier outlines, respectively. Two approaches are then illustrated for palaeoglacier reconstructions using two sets of geomorphic constraints: one with the fully reconstructed glacier outlines during the LIA, and the other with just the terminal moraine and limited trimlines during MIS 2. PalaeoIce can significantly improve the efficiency of palaeoglacier reconstructions and the understanding of the impact of glacier change on water resources. • An automated method, PalaeoIce, is presented for palaeoglacier reconstruction. • Tools are developed to create flowlines, modify DEM, and reconstruct palaeoglaciers. • Reconstructed ice thickness data are validated by field measurements in Tian Shan. • Target geomorphic features are of importance for palaeoglacier reconstruction. [ABSTRACT FROM AUTHOR]

Mons Rümker is a preferred candidate landing region for China's Chang'e-5 (CE-5) mission, from where it is of great significance to select safe landing areas. Lunar terrain factors from Digital Elevation Model (DEM) data, limited by their low resolutions (~10 m/pixel), are inapplicable to evaluating the lunar landing area safety, in spite of the fact that lunar remote sensing imagery has higher resolution (~50 cm/pixel). In this paper, we extracted terrain factors in divided square girds by the aid of the high-resolution Lunar Reconnaissance Orbiter (LRO) Narrow-angle Camera (NAC) images, namely, flat area percentage (Fap), distribution pattern of uneven objects (NNI) based on the double-threshold Otsu method, and roughness based on gray level histogram analysis. Mons Rümker can be divided into four geological units, named as LD, B1, B2, and B3, respectively. Unit B1 has a higher roughness and a lower Fap. Unit B2 and B3 are characterized with the highest Fap and the lowest roughness. NNIs of Unit B1, B2, and B3 are >1 while LD's is <1. Thus, the distribution patterns of uneven objects in Unit LD are clustered but dispersed in all Unit B1, B2, and B3. This paper tends to take Fap and roughness as the main terrain factors to evaluate the safety for CE-5 landing in Mons Rümker with NNI being a supplement to Fap. According to Standard 1–3 mentioned in this paper, we would classify the divided square grids of the Mons Rümker region as the safe or unsafe areas, and then discriminate five potential landing areas for CE-5 probe safe landing. Five potential landing areas (red polygons marked with number 1–5). The blue, purple and red colors are the safe grids classified in line with Standard 1–3, separately. The white solid line indicates the boundary of Mons Rümker. The yellow stars show two candidate landing sites for CE-5 mission mentioned by Zhao et al. (2017). Unlabelled Image • Three terrain factors (Fap, NNI and roughness) were derived from the NAC mosaic image of Mons Rümker; • Mons Rümker can be divided into four geological units, which are named as LD, B1, B2, and B3; • Five potential landing areas for CE-5 probe safe landing were recognized based on Standard 1-3. [ABSTRACT FROM AUTHOR]

In ancient China, the course of rivers changed frequently under the influence of the natural environment. The study of changes in paleochannels provides the basis for river regulation and water conservancy, and also supplies an important scientific foundation for the evolution of the geographical environment. However, it is extremely difficult to determine the location of paleochannels due to the limitations of traditional research methods and modern remote sensing interpretation. This paper introduces a new method, Detrended Digital Elevation Model Interpretation, for supporting interpretation of ancient rivers at large scales. A detrended DEM was obtained by removing the overall trend from the original DEM by subtracting a "detrending surface" derived from the original image using a guiding filter. The paleochannels of the Yellow River in the North China Plain were interpreted by GIS analysis with the help of historical materials. The detrended DEM was found to be less affected by the surface environment and had higher identification accuracy compared with an optical image and the colored DEM. Moreover, the detrended DEM could be used to interpret ancient rivers at large scales. Finally, the flow path of ancient rivers in the Eastern Han Dynasty (or near the Jindi River) was hypothesized using the interpretation results. The resulting paleochannel data can be used to revise historical river maps and provide reference for researching and managing the Yellow River. • Detrended Digital Elevation Model Interpretation is a new method for supporting interpretation of paleochannels in a large scale. • Detrending solves the ambiguity of feature details at low altitude of the original DEM by removing the down-valley slope of DEM. • The detrended DEM retains the topographic structure and shows the details of objects without being affected by the surface spectrum and occlusion. • The paleochannel of Yellow River in the Eastern Han Dynasty in Yanggu area is supposed to be located in the north side of Jindi river. [ABSTRACT FROM AUTHOR]