Multi-temporal Digital Elevation Models Research Articles

Detection of pyroclastic material and deformation of the lava dome in Mt. Sinabung with multi-temporal analysis (2010-2020)

The persistent eruptions of Mt. Sinabung resulted in the lava dome’s deformation and blanketed the surrounding area with pyroclastic material. This research focused on determining the changes in Mt. Sinabung during the prolonged eruptions from 2010-2020. A total of 22 volcanic ash samples were collected following a 1x1 km grid interval spread over from the East to South slope of Mt. Sinabung. The studied area is the most affected by the volcanic eruption. Digital elevation models from the shuttle radar topographic mission and sentinel-1 were utilized to monitor deformations of the lava dome and the distribution of pyroclastic material on Mt. Sinabung. Sentinel Application Platform and Google Earth Engine were used as the main tools in multi-temporal digital elevation model (DEM) data processing. The eruption of Mt. Sinabung from 2010 to 2020 changed the height from 2,460 m to 2,404.3 m and created a new crater (5.35 ha). The lava dome volume from 2010 to 2020 is about 2,308,041 m3 and has collapsed to produce pyroclastic material which deposits to the surrounding area of Mt. Sinabung during the eruption. The distribution of pyroclastic material increased from 2010 to 2019, covered up an area of 103.27 ha (2010), 846.48 ha (2013), 1,029.74 ha (2016), 1,235.97 ha (2017) and 1,463.62 ha (2019). The thickness of the pyroclastic material deposits at Mt. Sinabung until 2020 varied from 13,24 cm to 219 cm. The findings from this study can be used as a reference for observing topographic changes due to volcanic activities and drawing a mitigation and contingency plan for a volcanic disaster program in the active volcanic region of Indonesia.

Monitoring the annual geodetic mass balance of Bordu and Sary-Tor glaciers using UAV data

Abstract The geodetic mass balance of a glacier corresponds to glacier-wide volume changes, converted to mass changes using density assumptions. It is typically calculated by differencing multi-temporal digital elevation models. In this study, we show how the annual geodetic mass balance of a glacier can be derived from uncrewed aerial vehicle (UAV) data. The presented workflow is applied to two small- to medium-sized glaciers in the Kyrgyz Tien Shan (Central Asia): Bordu glacier and Sary-Tor glacier. The obtained geodetic mass balance is compared with the glaciological mass balance derived from a network of ablation stakes and snow pits. A previously calibrated mass-balance model is used to correct for the difference in acquisition dates. The results show that the determined geodetic mass balance matches closely with the glaciological mass balance. Besides, for both glaciers the geodetic mass balance does not seem to be particularly sensitive to the assumptions regarding volume-to-mass conversion. Therefore, our results demonstrate that UAVs can serve as a valuable instrument to quantify the annual geodetic mass balance and to validate the glaciological mass balance. The conventional glaciological mass-balance estimation often relies on interpolation and extrapolation methods, whereas UAVs offer the potential for direct data acquisition over the entire glacier surface.

Identifying active retrogressive thaw slumps from ArcticDEM

Permafrost degradation in the Arctic is accelerating and affects northern communities, ecosystems, and global soil carbon storage. However, the extent, distribution, and rates of permafrost degradation in the pan-Arctic remain unknown, contributing to the challenges of mapping and monitoring it in a harsh and remote environment. We applied feature extraction, deep learning, and crowdsourcing to an open-access, high-resolution (2 m), and multi-temporal digital elevation models (i.e. ArcticDEM), to identify retrogressive thaw slumps (RTSs), a dynamic form of permafrost degradation widespread across the Arctic. Specifically, we (1) developed an automated pipeline to process approximately 200 TB of ArcticDEM data; (2) designed feature extractors (pixel-wise elevation differences, polygons of elevation reductions, lines of narrow-steep slopes, and RTS headwall lines) to identify slumps; (3) trained a super-efficient object detection algorithm based on deep learning (YOLOv4) and used it to locate RTSs from composite imagery derived from the ArcticDEM; (4) combined the extracted features and the bounding boxes output by YOLOv4 to obtain mapping results at a manageable level; and (5) developed a crowdsourcing system and invited volunteers to validate and refine the results. The final map included 2494 RTSs (actively expanding during ArcticDEM observation) across the Arctic. The results also show that (1) it is necessary to combine the extracted features and deep learning to remove many false positives in the scenario with limited training data, but large regions to map; (2) some hotspots of RTSs need further and detailed investigation, including an RTS cluster in Greenland; (3) the crowdsourcing system is useful for the validation of a large dataset, but responses to this work were limited, possibly because RTSs are a quite specific topic that not many people are familiar with. The results likely miss many RTSs due to the limitation in the method for identifying RTSs and uncertainties as well as short observation periods of ArcticDEM at many locations. This study provides data and serves as a starting point to develop a global inventory and better understand permafrost thaw in the pan-Arctic using very high resolution remote sensing.

Unmanned Aerial Photography Futures to explore surface deformations and their visualization on the geoportal “ActiveTectonics”

On the example of the Rita River delta and alluvial fan of the Shartlai River located on the northwestern coast of Lake Baikal, we show the possibilities of ultra-detailed aerial photography, which allows tracing surface discontinuities with displacements from a few centimeters. The software package "Agisoft Metashape" was applied for analyzing the multi-temporal digital elevation models with the same spatial resolution of 1,67 cm/pixel to fix possible changes in the earth's surface over the year for the local area of earthquake-induced ground failures at Cape Rytyi. It has been established that most of this part has sunk by an average of 5–10 cm per year, and in the axial parts of the faults, subsidence has reached 33 cm. The greatest accumulation of sediments (up to 40 cm thick in some places) occurred on the shore, which is mainly due to the geological activity of the waves of Lake Baikal. Based on the relationship between ruptures and alluvial fans of different ages, we concluded at least two rupturing paleoearthquakes at Cape Shartlai. On the author's geoportal "ActiveTectonics", we uploaded some materials of unmanned aerial photography and geological objects in the form of orthophotomaps, digital elevation models and 360° panoramas that significantly expands the possibilities of data perception which are the basis for scientific results and conclusions.

Application of airborne laser scanning and electrical resistivity tomography in the study of an active landslide and geology of the cliff, Jastrzębia Góra, Poland

The cliff in Jastrzębia Góra is one of the most an active landslide areas along the Polish Baltic coast. The aim of these studies was to determine the dynamics of displacements in an active landslide and to identify the geology of the cliff. Two methods, ALS (Airborne Laser Scanning) and ERT (Electrical Resistivity Tomography), were used for this purpose. Multitemporal ALS data were used to determine the geomorphological changes within the cliff and find the causes of the rapid rate of cliff edge landslides. ALS differential models were the sources of new information about the dynamics of vertical displacement in the landslide and helped calculate the volume of displaced rock masses that occurred over 12 years. The cliff was found to become significantly an active in 2010. This process was observed by analysing the relief of multitemporal digital elevation models, differential models, AND morphological sections and by conducting long-term field observations. The ERT surveys made it possible to generate two 3D ERT electrical resistivity models that provided much new information about the geological structure of the cliff. Additionally, a 2D ERT profile was made through the landslide. The internal structure of the landslide was recognized, and the depth of the slip surface was estimated. The results permitted clarifying the cause of the high landslide activity and the rapid rate of retreat of the cliff edge over the past 12 years. In addition, by means of the results of electrical resistivity surveys and the use of archival boreholes, it was possible to extrapolate a model of the surface relief of the clay hill using geostatistical methods. It was found that at the boundary with the active landslide—the top of the clay layer—is tilted towards the north, i.e. towards the sea, which favours the activation of the landslide. The proposed research methodology, as well as the obtained information, may be of significant assistance in further diagnosis and prognosis of the dynamics of landslide development and the causes of landslide formation within cliff coasts.

A Step-Wise Workflow for SAR Remote Sensing of Perennial Heaving Mound/Crater on the Yamal Peninsula, Western Siberia

Climate change in the Arctic region is more significant than in other parts of our planet. One of the manifestations of these changes is crater creation with blowouts of a gas, ice and frozen soil mixture. In this context, dynamics studies of long-term heaving mounds that turn into craters as a result are relevant. A workflow for detecting and assessing anomalous dynamics of heaving mounds in the Arctic regions is proposed. Areas with anomalous increase of ALOS-2 PALSAR-2 synthetic aperture radar (SAR) backscattering intensity are detected in the first stage. These increases take place due to sudden changes in local terrain slopes when the scattering surface (mound slope) turns toward the radar. Radar backscattering intensity also rises due to depolarization at newly formed frost cracks. Validation of the detected anomaly is carried out at the second stage through a comparison of multi-temporal digital elevation models obtained from bistatic radar interferometry TerraSAR-X/TanDEM-X data. At the final stage, the deformations are assessed within the detected areas using differential SAR interferometry (DInSAR) technique by ALOS-2 PALSAR-2 data. The magnitude of the heaving along the line of sight (LOS) was 22–24 cm in the period from January 2019 to January 2020. In general, effectiveness for detecting the perennial heaving mounds and the rate assessment of their increase were demonstrated in the suggested workflow.

Use of High-Resolution Multi-Temporal DEM Data for Landslide Detection

Landslides in urban areas have been relatively well-documented in landslide inventories despite issues in accuracy and completeness, e.g., the absence of small landslides. By contrast, less attention has been paid to landslides in sparsely populated areas in terms of their occurrences and locations. This study utilizes high-resolution and LiDAR-derived digital elevation models (DEMs) at two different times for landslide detection to (1) improve the localization and detection accuracies in landslide inventories, (2) minimize human intervention in the landslide detection process, and (3) identify landslides that cannot be easily documented in the current state of the practice. To achieve this goal, multiple preprocessing steps were used to ensure the spatial alignment of the multi-temporal DEMs. Map algebra was then used to calculate the vertical displacement for each cell and create a DEM of Difference (DoD) to obtain a quantitative estimation of ground deformations. Next, the elevation changes were filtered via an appropriate Level of Detection (LoD) threshold to mark potential landslide candidates. The landslide candidates were further assessed with the aid of customized topographic maps as auxiliary data and pattern recognition to distinguish landslides (true positive changes) from construction, erosion, and deposition (false positives). The results from the proposed method were compared with existing landslide inventories and reports to evaluate its performance. The new method was also validated with temporal high-resolution Google Earth images. The results showed the successful application of the method in landslide detection and mapping. Compared with traditional methods, the proposed method provides a semi-automatic way to obtain landslide inventories with publicly available yet lowly utilized DEM data, which can be valuable in preliminary analysis for landslide detection.

AN OPEN-SOURCE-BASED WORKFLOW FOR DEM GENERATION FROM SENTINEL-1 FOR LANDSLIDE VOLUME ESTIMATION

Abstract. Digital elevation models (DEMs) serve as a basis for various geomorphological applications, such as, landform mapping, natural hazard assessment, and landslide characterisation. The inter-comparison of DEMs can be used to provide estimates of topographic change, for example, volume changes. Sentinel-1 synthetic aperture radar (SAR) data can be used to generate multitemporal topographic datasets using interferometric SAR (InSAR). Such analyses are often conducted using commercial software; however, a well-structured workflow based on free and open-source software (FOSS) increases the applicability and transferability of the DEM generation method and can facilitate the use of multi-temporal topographic analysis within the Earth Sciences. In this study, we aim to develop an open-source-based workflow for the generation of multi-temporal DEMs from Sentinel-1 data, and to explore their potential for landslide volume estimation using FOSS. We implemented this semi-automated and transferable workflow bundled in the open-source Python package “SliDEM”, which relies on SNAP, SNAPHU, and several other open-source software for geospatial and geomorphological applications, all distributed within a Docker image. Two major landslides in Austria and Norway were selected to test, evaluate, and validate the workflow in terms of reliability, performance, reproducibility, and transferability. Even if the quality of the Sentinel-1-based DEMs varies among the study areas, the preliminary results are promising. However, there is a need for improvement and thorough analysis of the causes of elevation errors. A comprehensive evaluation of the influence of the perpendicular and temporal baselines, topography, land use/land cover, and other environmental conditions can be systematically assessed within the “SliDEM” workflow.

A New Method for Automated Measurement of Sand Dune Migration Based on Multi-Temporal LiDAR-Derived Digital Elevation Models

While remote sensing methods have long been used for coastal and desert sand dune studies, few methods have been developed for the automated measurement of dune migration in large dune fields. To overcome a major limitation of an existing method named “pairs of source and target points (PSTP)”, this paper proposes a toe line tracking (TLT) method for the automated measurement of dune migration rate and direction using multi-temporal digital elevation models (DEM) derived from light detection and ranging (LiDAR) data. Based on a few simple parameters, the TLT method automatically extracts the base level of a dune field and toe lines of individual dunes. The toe line polygons derived from two DEMs are processed using logical operators and other spatial analysis methods implemented in the Python programming language in a geographic information system. By generating thousands of random sampling points along source toe lines, dune migration distances and directions are calculated and saved with the sampling point feature class. The application of the TLT method was demonstrated using multi-temporal LiDAR-derived DEMs for a 9 km by 2.4 km area in the White Sands Dune Field in New Mexico (USA). Dune migration distances and directions for three periods (24 January 2009–26 September 2009, 26 September 2009–6 June 2010, and 24 January 2009–6 January 2010) were calculated. Sensitivity analyses were carried out using different window sizes and toe heights. The results suggest that both PSTP and TLT produce similar sand dune migration rates and directions, but TLT is a more generic method that works for dunes with or without slipfaces that reach the angle of repose.

Quantifying Debris Flood Deposits in an Alaskan Fjord Using Multitemporal Digital Elevation Models.

Six DEMs over a 10-year period were used to estimate flood-related sedimentation in the Japanese Creek drainage located in Seward, Alaska. We analyze two existing LiDAR DEMs and one GNSS-derived DEM along with three additional DEMs that we generated using differential Global Navigation Satellite System (dGNSS) and Structure from Motion (SfM) techniques. Uncertainties in each DEM were accounted for, and a DEMs of Difference (DoD) technique was used to quantify the amount and pattern of sediment introduced, redistributed, or exiting the system. Through correlating the changes in sediment budget with rainfall data and flood events, the study demonstrates that the major flood events in 2006 and 2012—the 7th and 5th highest precipitation events on record—resulted in an increased sedimentation in the drainage as a whole. At a minimum the 2006 and 2012 events increased the sediment in the lower reaches by 70,100 and 53,900 cubic meters, respectively. The study shows that the DoD method and using multiple technologies to create DEMs is effective in quantifying the volumetric change and general spatial patterns of sediment redistribution between the acquisition of DEMs.

Assessment of Changes in Mass Balance of the Tuyuksu Group of Glaciers, Northern Tien Shan, Between 1958 and 2016 Using Ground-Based Observations and Pléiades Satellite Imagery

Continuous measurements of glaciological mass balance have been conducted at the Central Tuyuksu glacier, Tuyuksu group of glaciers, Ile Alatau, northern Tien Shan since 1957 showing that cumulative mass balance was negative since the 1970s. Geodetic mass balance was calculated for the 1958-1998 and 1998-2016 periods using multi-temporal digital elevation models derived from the historic photogrammetric surveys from 1958 and 1998, and the high-resolution Pleiades satellite stereo imagery from 2016. Geodetic measurements revealed a mean surface lowering of 23.2±2.2 m (0.40 ± 0.04 m a-1) and reduction in volume of (67.7±6.7)x106 m3 in 1958-2016 at the Central Tuyuksu glacier yielding a geodetic mass balance of -21.8±2.6 m w.e. Similar trends were observed at other glaciers of the Tuyuksu group which lost in total 83.4x106 m3 of ice. Annual rates of mass balance have not changed significantly from 1958-1998 (-0.39±0.05 m w.e.) to 1998-2016 (-0.35±0.18 m w.e.) at the Central Tuyuksu and at other glaciers of the Tuyuksu group whose maximum elevations exceed 4000 m a.s.l. While glacier thinning intensified in the ablation zone and affected larger area in 1998-2016 extending to 3600-3700 m a.s.l., accumulation increased at higher elevations in 1998-2016. Geodetic mass balance was more negative in 1998-2016 than in 1958-1998 at the smaller glaciers with lower maximum elevations. At the Central Tuyuksu, geodetic mass balance was in close agreement with glaciological mass balance particularly in 1958-1998 when the difference between the geodetic and cumulative glaciological mass balance values did not exceed 5 %. During 1998-2016, this difference increased to 14 % with glaciological method producing more negative mass balance. This discrepancy was attributed to a systematic bias introduced by the lack of stakes in the accumulation zone of Central Tuyuksu whose contribution to uncertainty increased in 1998-2016 in line with an increase in accumulation. Negative mass balance of the Tuyuksu group of glaciers was attributed to continuing increase in summer temperatures and low accumulation observed in the 1970s-1980s and at the turn of the century.

Elevation Correction of Multi-Temporal Digital Elevation Model based on Unmanned Aerial Vehicle Images over Agricultural Area

Elevation Correction of Multi-Temporal Digital Elevation Model based on Unmanned Aerial Vehicle Images over Agricultural Area

Glacier mass changes over Duxueshan, Burog Kangri, and Zangser Kangri in the Inner Tibetan Plateau

The variation of glacier mass balance during the past decades remains poorly known for Duxueshan, Burog Kangri, and Zangser Kangri (DBZ) which are located in the Inner Tibetan Plateau (ITP), a transition zone with shifting influences between the westerlies and the Indian summer monsoon. In the present study, glacier area and mass changes were determined by topographic maps (TOPO), Landsat imagery and multi-temporal digital elevation models (DEMs) generated with TOPO, SRTM, TanDEM-X bistatic interferometric synthetic aperture radar (InSAR) images, and High Mountain Asia 8-m DEMs. On average, the glaciers showed a slight retreat from 343.27 ± 5.23 km2 in 1971 to 334.67 ± 3.21 km2 in 2018 (0.05 ± 0.04% a−1). However, glaciers lost mass at a rate of -0.32 ± 0.03 m w.e. a−1 from 1971 to 2012. For the 1999–2012 and 2012–2017 periods, mass balances of − 0.03 ± 0.16 and 0.09 ± 0.04 m w.e. a−1, respectively, were observed, which represents an approximately equilibrium. Two glaciers also advanced in our investigation period, and we confirmed one of them surged in 2015.

DEM Construction Method for Slopes Using Three-Dimensional Point Cloud Data Based on Moving Least Square Theory

AbstractThe multitemporal digital elevation model (DEM) of slopes constructed from three-dimensional (3D) point cloud data (PCD), which is obtained by terrestrial laser scanning (TLS), can realize ...

Integration of TanDEM-X and SRTM DEMs and Spectral Imagery to Improve the Large-Scale Detection of Opencast Mining Areas

Land use and land cover (LULC) is a key variable of the Earth’s system and has become an important indicator to evaluate the impact of human activities on the Earth’s ecosystems. With the increasing demand of mine resources, widespread opencast mining has led to significant changes in LULC and caused substantial damage to the environment. An efficient approach of detecting mining activities at large scales is of critical importance in mitigating their potential impacts on downstream settlements and in assessing LULC characteristics. In this study, we present a novel approach for enabling large-scale automatic detection of opencast mining areas by integrating multitemporal digital elevation models (DEMs, including the SRTM DEM and the recently released TanDEM-X DEM) and multispectral imagery in object-based image analysis and random forest (RF) algorithms. A sequence of data preparation, image segmentation, threshold analysis, calculation of metrics, and influence factor regulation was developed and tested on the Landsat 8 sample dataset in Inner Mongolia in China, which is a mineral-rich area. Aside from spectral metrics, such as brightness and reflectance value, introduced topographical features enhanced the modeling and classification significantly, and the overall performance is greatly influenced by feature selection (the out-of-bag error rate in the RF algorithm is 7.54% for the integrated DEM method in comparison with 12.70% for the only-optical images method). The integrated use of spectral imagery and multitemporal DEMs reveals that the identified mining area is about 1100 km2 in the study area and period, and the topographic changes of opencast mining in terms of elevation difference is between −258 and 162 m. The results show that the method can map the locations and extents of mining areas automatically from spectral and DEM data and can potentially be applied to larger areas.

The 2007 caldera collapse at Piton de la Fournaise: new insights from multi-temporal structure-from-motion

We produced new multi-temporal Digital Elevation Models (DEMs) of the April 2007 summit collapse at Piton de la Fournaise from previously unused aerial photographs. This dataset revealed the precise temporal evolution of collapsed volume and caldera morphological changes. Four days after the onset of an eruption at an unusually low elevation, the summit started to collapse (20:48 UTC April 5th). During the first 30 hours, collapsing was relatively fast (840 m3 s-1 average), and continued for at least the following 12 days, at a slower rate (46 m3 s-1 average). On April 19th, the collapse reached 96% of its final volume, while the remaining 4% were probably attained by May 1st (end of lava emission at the vent). The post-collapse hydrothermal activity in the caldera is closely associated with the main ring faults evidenced as active during the collapse, which are now preferential paths for fluids to reach the surface.

Exploring the Impact of Multitemporal DEM Data on the Susceptibility Mapping of Landslides

Digital elevation models (DEMs) are fundamental data models used for susceptibility assessment of landslides. Due to landscape change and reshaping processes, a DEM can show obvious temporal variation and has a significant influence on assessment results. To explore the impact of DEM temporal variation on hazard susceptibility, the southern area of Sichuan province in China is selected as a study area. Multitemporal DEM data spanning over 17 years are collected and the topographic variation of the landscape in this area is investigated. Multitemporal susceptibility maps of landslides are subsequently generated using the widely accepted logistic regression model (LRM). A positive correlation between the topographic variation and landslide susceptibility that was supported by previous studies is quantitatively verified. The ratio of the number of landslides to the susceptibility level areas (RNA) in which the hazards occur is introduced. The RNA demonstrates a general decrease in the susceptibility level from 2000 to 2009, while the ratio of the decreased level is more than fifteen times greater than that of the ratio of the increased level. The impact of the multitemporal DEM on susceptibility mapping is demonstrated to be significant. As such, susceptibility assessments should use DEM data at the time of study.

Investigation of landslide detection using radial basis functions: a case study of the Taşkent landslide, Turkey.

This paper investigates landslide detection over flat and steep-slope areas with large forest cover using different radial basis function interpolation methods, which can affect the quality of a digital elevation model. Unmanned aerial vehicles have been widely used in landslide detection studies. The generation of image-based point clouds is achievable with various matching algorithms from computer vision systems. Point cloud-based analysis was performed by generating multi-temporal digital elevation models to detect landslide displacement. Interpolation methodology has a crucial task to fill the gaps in insufficient areas that result from filtered areas or sensors that do not generate spatial information. Radial basis function interpolations are the most commonly used technique for estimating the unknown values in survey areas. However, the quality of the radial basis function interpolation methods for landslide studies has not been thoroughly investigated in previous studies. In this study, radial basis function interpolation methods are investigated and compared with the global navigational satellite systems, which provide high accuracy for geodetic measurement systems. The main purpose of this study was to investigate the various radial basis function models to detect landslides using a point cloud-based digital elevation model and determine the quality of detection with global navigational satellite systems. As a result of this study, each of the radial basis function-generated digital elevation models was found to be statistically compatible with global navigational satellite systems, resulting in displacements from the ground truth data.

Accelerated glacier mass loss (2011–2016) over the Puruogangri ice field in the inner Tibetan Plateau revealed by bistatic InSAR measurements

The temporal variation of glacier mass balance during recent years remains poorly known for the mountain glaciers in the inner Tibetan Plateau (ITP), due to the lack of field measurements. In this study, we retrieved the annual glacier mass balance of the Puruogangri ice field, which is the largest modern ice mass in the ITP, by differencing multi-temporal digital elevation models (DEMs) generated with five pairs of TanDEM-X bistatic interferometric synthetic aperture radar (InSAR) images acquired between April 2011 and January 2016. We compared the TanDEM-X DEMs in January and April 2012 to estimate the X-band radar penetration depth difference (0.61 ± 0.06 m), which enabled systematic bias correction in the estimation of annual glacier mass balance. The observed mass balance reveals a glacier mass gain of 0.44 ± 0.10 m w.e. yr−1 in 2011–12, which was followed by accelerated glacier mass loss in 2012–16. Glacier mass balances of −0.13 ± 0.03, −0.34 ± 0.06, and − 0.52 ± 0.10 m w.e. yr−1 were estimated for the periods of 2012–13, 2013–14, and 2014–16, respectively. This accelerating trend of glacier mass loss is likely caused by the continuous decrease in annual precipitation, according to the climate data recorded by adjacent meteorological stations. This study demonstrates that repeated bistatic InSAR measurement is a promising method for monitoring glacier elevation change and mass balance at regular intervals.

Changes in glacier volume on Mt. Gongga, southeastern Tibetan Plateau, based on the analysis of multi-temporal DEMs from 1966 to 2015

ABSTRACTThe accelerated retreat of glaciers and the reduction of glacier ice reserves caused by climate change can significantly affect regional water resources and hydrological cycles. Changes in glacier thickness are among the key indicators that reflect this process. We analyzed changes observed in the elevation of glacier surfaces in the Gongga Mountains (GGM) using multi-temporal Digital Elevation Models (DEMs) derived from topographic maps, SRTM, ICESat and ZY-3 data. The results showed that the mean rate of change in glacier surface altitude in the GGM was ~−26.7 ± 2.03 m (0.54 ± 0.04 m a−1) between 1966 and 2015. The mean melt rates differed over different time periods, latterly showing an accelerating trend. As a general rule, glaciers appear to be losing more volume at lower than at higher elevations. Further analysis of these results suggests that supraglacial debris coverage in the GGM promotes higher rates of mass loss.