Digital ElevationModel(DEM)refers to a digital map of the surface of the Earth that only shows the bare ground,without any buildings,plants,or other characteristics.However,obtaining unlimited access to DEM data at hi...Digital ElevationModel(DEM)refers to a digital map of the surface of the Earth that only shows the bare ground,without any buildings,plants,or other characteristics.However,obtaining unlimited access to DEM data at high and medium resolutions is very hard.Consequently,users often question the accuracy of freely available DEMs and their suitability for various applications.By comparing them to Global Positioning System(GPS)elevation data,this study aimed to identify themost reliable and widely available DEM for various terrains.The objectives of this study were to generate DEMs fromdifferent open sources and validate the accuracy of these DEMs using GPS elevation data.Various DEM types including Sentinel-1,ALOS PALSAR,SRTM,AW3D30,and ASTER were compared.Root Mean Square Error(RMSE)andMean Error(ME)were used to measure the difference between the DEM-derived elevations and the GPS-measured elevations.The results showed that even though Sentinel-1 has higher resolutions,the accuracy of the DEM from Sentinel-1 depends on issues including coherence and interferometry,surface features,and temporal stability.On the other hand,ALOS PALSAR could accurately represent surfaces in some situations.Additionally,DEMs with lower resolutions,such as SRTM and AW3D30,demonstrated greater consistency across various types of terrain.In contrast,the ASTER DEM showed more variability in complex terrains.While freely available DEMs are easy to use and accessible,their accuracy varies depending on the source and terrain features.Future improvements could include adding more ground control points and using advanced filtering methods to enhance precision.展开更多
Topographic shielding of cosmic radiation flux is a key parameter in using cosmogenic nuclides to determine surface exposure ages or erosion rates. Traditionally, this parameter is measured in the field and uncertaint...Topographic shielding of cosmic radiation flux is a key parameter in using cosmogenic nuclides to determine surface exposure ages or erosion rates. Traditionally, this parameter is measured in the field and uncertainty and/or inconsistency may exist among different investigators. This paper provides an ArcGIS python code to determine topographic shielding factors using digital elevation models （DEMs）. This code can be imported into ArcGIS as a geoprocessing tool with a user-friendly graphical interface. The DEM-derived parameters using this method were validated with field measurements in central Tian Shan. Results indicate that DEM-derived shielding factors are consistent with field-measured values. It provides a valuable tool to save fieldwork efforts and has the potential to provide consistent results for different regions in the world to facilitate the comparison of cosmogenie nuclide results.展开更多
Although many studies have investigated slope gradient uncertainty derived from Digital Elevation Models(DEMs), the research concerning slope length uncertainty is far from mature. This discrepancy affects the availab...Although many studies have investigated slope gradient uncertainty derived from Digital Elevation Models(DEMs), the research concerning slope length uncertainty is far from mature. This discrepancy affects the availability and accuracy of soil erosion as well as hydrological modeling. This study investigates the formation and distribution of existing errors and uncertainties in slope length derivation based on 5-m resolution DEMs of the Loess Plateau in the middle of China. The slope length accuracy in three different landform areas is examined to analyse algorithm effects. The experiments indicate that the accuracy of the flat test area is lower than that of the rougher areas. The value from the specific contributing area(SCA) method is greater than the cumulative slope length(CSL), and the differences between these two methods arise from the shape of the upslope area. The variation of mean slope length derived from various DEM resolutions and landforms. The slope length accuracy decreases with increasing grid size and terrain complexity at the six test sites. A regression model is built to express the relationship of mean slope length with DEM resolution less than 85 m and terrain complexity represented by gully density. The results support the understanding of the slope length accuracy, thereby aiding in the effective evaluation of the modeling effect of surface process.展开更多
Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the ...Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the potential to be a cost-effective method for monitoring surface displacements over extensive areas,such as open-pit mines.DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model(DEM).However,since the topography of the ground surface in open-pit mines changes largely due to excavations,measurement errors can occur due to insufficient information on the elevation of mining areas.In this paper,effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry.In addition,validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system(GPS)monitoring conducted for three years at the same limestone quarry.It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters.Comparing the monitoring results of DInSAR and GPS,the root mean square error(RMSE)of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM,considering the excavation processes,is used.It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.展开更多
In China, many scenic and tourism areas are suffering from the urbanization that results from physical development of tourism projects, leading to the removal of the vegetative cover, the creation of areas impermeable...In China, many scenic and tourism areas are suffering from the urbanization that results from physical development of tourism projects, leading to the removal of the vegetative cover, the creation of areas impermeable to water, in-stream modifications, and other problems. In this paper, the risk of soil erosion and its ecological risks in the West Lake Scenic Spots （WLSS） area were quantitatively evaluated by integrating the revised universal soil loss equation （RUSLE） with a digital elevation model （DEM） and geographical information system （GIS） software. The standard RUSLE factors were modified to account for local climatic and topographic characteristics reflected in the DEM maps, and for the soil types and vegetation cover types. An interface was created between the Areinfo software and RUSLE so that the level of soil erosion and its ecological risk in the WLSS area could be mapped immediately once the model factors were defined for the area. The results from an analysis using the Areinfo-RUSLE interface showed that the risk value in 93 % of the expanding western part of the WLSS area was moderate or more severe and the soil erosion risk in this area was thus large compared with that in the rest of the area. This paper mainly aimed to increase the awareness of the soil erosion risk in urbanizing areas and suggest that the local governments should consider the probable ecological risk resulting from soil erosion when enlarging and developing tourism areas.展开更多
Validation studies of global Digital Elevation Models(DEMs)in the existing literature are limited by the diversity and spread of landscapes,terrain types considered and sparseness of groundtruth.Moreover,there are kno...Validation studies of global Digital Elevation Models(DEMs)in the existing literature are limited by the diversity and spread of landscapes,terrain types considered and sparseness of groundtruth.Moreover,there are knowledge gaps on the accuracy variations in rugged and complex landscapes,and previous studies have often not relied on robust internal and external validation measures.Thus,there is still only partial understanding and limited perspective of the reliability and adequacy of global DEMs for several applications.In this study,we utilize a dense spread of LiDAR groundtruth to assess the vertical accuracies of four medium-resolution,readily available,free-access and global coverage 1 arc-second(30 m)DEMs:NASADEM,ASTER GDEM,Copernicus GLO-30,and ALOS World 3D(AW3D).The assessment is carried out at landscapes spread across Cape Town,Southern Africa(urban/industrial,agricultural,mountain,peninsula and grassland/shrubland)and forested national parks in Gabon,Central Africa(low-relief tropical rainforest and high-relief tropical rainforest).The statistical analysis is based on robust accuracy metrics that cater for normal and non-normal elevation error distribution,and error ranking.In Cape Town,Copernicus DEM generally had the least vertical error with an overall Mean Error(ME)of 0.82 m and Root Mean Square Error(RMSE)of 2.34 m while ASTER DEM had the poorest performance.However,ASTER GDEM and NASADEM performed better in the low-relief and high-relief tropical forests of Gabon.Generally,the DEM errors have a moderate to high positive correlation in forests,and a low to moderate positive correlation in mountains and urban areas.Copernicus DEM showed superior vertical accuracy in forests with less than 40%tree cover,while ASTER and NASADEM performed better in denser forests with tree cover greater than 70%.This study is a robust regional assessment of these global DEMs.展开更多
High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications.The Ice,Cloud,and Land elevation Satellite 2(ICESat-2)/ATL08 terrain product has shown...High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications.The Ice,Cloud,and Land elevation Satellite 2(ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights,but it has not been fully evaluated.Hence,this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER),the Shuttle Radar Topography Mission(SRTM),and TanDEM-X(TDX)DEMs over vegetated mountainous areas.We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy.Then,the results were evaluated against a reference airborne LiDAR digital terrain model(DTM),by selecting 10,000 points over the entire area and comparing the accuracy of ASTER,SRTM,and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER,SRTM,and TDX DEMs assessed by the ATL08 strong beams,weak beams,and all beams.We also detected the impact of the terrain aspect,slope,and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty.Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%;while the weak beams accuracy was enhanced by 74.05%.Furthermore,slope strongly influenced ATL08 height errors and height uncertainty;especially on the weak beams.The errors induced by the slope significantly decreased when the uncertainty levels were reduced to<20 m.The evaluations of ASTER,SRTM,and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams.These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.展开更多
This paper presents a component object model(COM)based framework for managing,analyzing and visualizing massive multi-scale digital elevation models(DEMs).The framework consists of a data management component(DMC),whi...This paper presents a component object model(COM)based framework for managing,analyzing and visualizing massive multi-scale digital elevation models(DEMs).The framework consists of a data management component(DMC),which is based on RDBMS/ORDBMS,a data analysis component(DAC)and a data render component(DRC).DMC can manage massive multi-scale data expressed at various reference frames within a pyramid database and can support fast access to data at variable resolution.DAC integrates many useful applied analytic functions whose results can be overlaid with the 3D scene rendered by DRC.DRC provides view-dependent data paging with the support of the underlying DMC and organizes the potential visible data at different levels into rendering.展开更多
The influence of pre-quaternary underlying terrain on the formation of loess landforms, i.e., the geomorphological inheritance issue, is a focus in studies of loess landforms. On the basis of multi-source information,...The influence of pre-quaternary underlying terrain on the formation of loess landforms, i.e., the geomorphological inheritance issue, is a focus in studies of loess landforms. On the basis of multi-source information, we used GIS spatial analysis methods to construct a simulated digital elevation model of a pre-quaternary paleotopographic surface in a severe soil erosion area of the Loess Plateau. To reveal the spatial relationship between underlying paleotopography and modern terrain, an XY scatter diagram, hypsometric curve, gradient and concavity of terrain profiles are used in the experiments. The experiments show that the altitude, gradient and concavity results have significant linear positive correlation between both terrains, which shows a relatively strong landform inheritance relationship, particularly in the intact and complete loess deposit areas. Despite the current surface appearing somewhat changed from the original shape of the underlying terrain under different erosion forces, we reveal that the modern terrain generally smoothes the topographic relief of underlying terrain in the loess deposition process. Our results deepen understanding of the characteristics of geomorphological inheritance in the formation and evolution of loess landforms.展开更多
The integration of Unmanned Aerial Vehicles(UAVs)and Uncrewed Surface Vehicles(USVs)has revolutionized topographic and bathymetricmapping,significantly enhancing the accuracy and efficiency of geospatial data acquisit...The integration of Unmanned Aerial Vehicles(UAVs)and Uncrewed Surface Vehicles(USVs)has revolutionized topographic and bathymetricmapping,significantly enhancing the accuracy and efficiency of geospatial data acquisition processes.This innovative approach synergistically combines terrestrial data collected by UAVs with underwater data obtained through USVs,culminating in the creation of unified high-resolution Digital Elevation Models(DEMs)of the river basin region represents a vital step toward understanding the dynamic interactions between land and water bodies.Hence,the seamless Topo-Bathymetric Elevation Model offers a detailed perspective of the river system,supporting informed decision-making in addressing sediment transport,erosion,and river morphology.This manuscript provides a comprehensive review examines the advanced methodologies for creating seamlessmultisource Topo-Bathymetry ElevationModels(TBEMs)in river basin contexts,emphasising critical factors such as cost-effectiveness,operational efficiency,and data precision.In particular,UAVs deliver high-resolution(1-3 cm)topographic mapping with 5-10 km operational ranges,while USVs provide complementary bathymetric data(1 m resolution)across 3-5 km.This synergy enables seamless land-water surveys,achieving superior precision(±8 cmterrestrial,±3 cmunderwater)and efficiency over traditional methods.By analysing the benefits and limitations inherent in these technologies,this review elucidates the potential of UAV-USV synergy to improve the accuracy and reliability of geospatial data,thereby supporting well-versed decision-making processes in environmental management and conservation efforts.Furthermore,the findings underscore the broader implications of this integrated approach for riverine and coastal studies,advocating for its wider adoption in various applications,including habitat monitoring,flood risk assessment,and sustainable resource management.The synthesis of terrestrial and aquatic data through UAV-USV collaboration not only advances the field of geospatial science but also fosters a deeper understanding of the interdependencies between land and water systems,ultimately contributing to more effective environmental stewardship.展开更多
Forests exert significant biogeophysical cooling effects(CE)through processes such as increased evapotranspiration,reduced albedo,and enhanced surface roughness.However,little is known about the extent to which elevat...Forests exert significant biogeophysical cooling effects(CE)through processes such as increased evapotranspiration,reduced albedo,and enhanced surface roughness.However,little is known about the extent to which elevation-induced temperature differences bias the observed CE and how this bias interacts with the underlying biogeophysical mechanisms.In this study,we integrated multisensor remote sensing products and Shuttle Radar Topography Mission(SRTM)elevation data on the Google Earth Engine(GEE)platform,and applied a spatial-temporal window regression approach to quantify and correct the sensitivity of land surface temperature(LST)to elevation for forest pixels across China from 2001 to 2022.First,we found that forest LST exhibited a significant negative relationship with elevation,leading to systematic CE overestimation by 0.61 K during the day and 0.60 K at night compared with altitudecorrected CE values.Second,after correction,the CE showed clear spatial heterogeneity,with stronger daytime cooling in tropical(-0.54 K)and temperate forests(-0.24 K),and warming in cold(+0.11 K)and arid regions(+0.53 K),while most regions experienced nighttime warming.Among forest types,evergreen needleleaf forests(ENF)exhibited the strongest daytime cooling(-0.36 K),whereas deciduous broadleaf(DBF)and open shrublands(OS)tended to warm.Third,mechanism analysis revealed that elevation correction strengthened the correlations of CE with leaf area index(LAI)and evapotranspiration,while maintaining a significant negative correlation with albedo,indicating that both radiative and non-radiative processes jointly shape the unbiased CE.These findings provide a more accurate quantification of forest CE by eliminating elevation-induced bias,which providing a more accurate assessment of the climate mitigation potential of forests,which is crucial for developing more effective forest management and ecological restoration strategies.展开更多
This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the la...This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the latter derived from the former. It is confirmed that significant differences exist between uncertainty descriptors, and propagation of uncertainty to end products is immensely affected by the specification of source uncertainty.展开更多
Subtraction of elevation datasets(e.g.digital elevation models(DEMs)and non-continuous elevation points)acquired at different times is a useful method to monitor landform surface change.Due to heavy post-processing of...Subtraction of elevation datasets(e.g.digital elevation models(DEMs)and non-continuous elevation points)acquired at different times is a useful method to monitor landform surface change.Due to heavy post-processing of these elevation datasets,multi-source errors are introduced into the resulting elevation data products.To improve the estimation of elevation change,co-registration of elevation datasets is a prerequisite.This paper presents an open-source automated GIS tool(arc Pycor)for co-registering elevation datasets.arc Pycor is coded in Python 2.7 and is run via Arc GIS for Desktop.The performances of arc Pycor have been evaluated using a series of experiments.In benchmark tests,the resolved co-registration vectors of arc Pycor are compared to the predefined shift vectors obtained by artificially misaligning the slave DEMs from the master elevation datasets.Results show that arc Pycor is able to co-register DEMs with relative high accuracy and can well align slave DEMs to non-continuous elevation points,which indicates its robustness in co-registering of elevation datasets.arc Pycor is also able to co-register multi-sourced DEMs of different resolutions in mountain areas.展开更多
Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes,where segmentati...Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes,where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions.To address these issues,we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder,guided multimodal fusion,and deep supervision.The framework is built upon the synergistic combination of cross-attention,gated fusion,and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation,enabling efficient context modeling and robust feature exchange between modalities.The decoder captures long-range context at deeper levels using lightweight cross-attention and refines spatial details at shallower levels through attention-gated skip fusion,enabling precise boundary delineation and fewer false positives.The gated fusion further enhances multimodal integration of optical and topographical cues,and the deep supervision stabilizes training and improves generalization.Moreover,to mitigate checkerboard artifacts,a learnable sub-pixel upsampling is devised to replace the traditional transposed convolution.Despite its compact design with fewer parameters,the model consistently outperforms state-of-the-art baselines.Experiments on two benchmark datasets,Landslide4Sense and Bijie,confirm the effectiveness of the framework.On the Bijie dataset,it achieves an F1-score of 0.9110 and an intersection over union(IoU)of 0.8839.These results highlight its potential for accurate large-scale landslide inventory mapping and real-time disaster response.The implementation is publicly available at https://github.com/mishaown/DiGATe-UNet-LandSlide-Segmentation(accessed on 3 November 2025).展开更多
Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was e...Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.展开更多
In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landfor...In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.展开更多
Blumeria graminis f. sp. tritici, the pathogen that causes wheat powdery mildew, is one of the most important diseases affecting wheat production in China, and the oversummering is the key stage of wheat powdery milde...Blumeria graminis f. sp. tritici, the pathogen that causes wheat powdery mildew, is one of the most important diseases affecting wheat production in China, and the oversummering is the key stage of wheat powdery mildew epidemic. The more oversummering regionalization of wheat powdery mildew has played an important role in disease prediction, prevention and control. In this study, we analyzed the correlation between oversummering data of wheat powdery mildew and the meteorological factors over the past years, and determined that temperature was the key meteorological factor influencing oversummering of wheat powdery mildew. The average temperature at which wheat powdery mildew growth was terminated(26.2°C) was used as the threshold temperature to regionalize the oversummering range of wheat powdery mildew. This regionalization was done using the GIS ordinary kriging method combined with the Digital Elevation model(DEM) of China. The results showed that annual probability of oversummering region based on Model 26.2 were consistent with the actual survey of the more summer wheat powdery mildew. Wheat powdery mildew oversummering regions in China mainly cover mountainous or high-altitude areas, and these regions form a narrow north-south oversummering zone. Oversummering regions of wheat powdery mildew is mainly concentrated in the high-altitude wheat growing areas, including northern and southern Yunnan, northwestern Guizhou, northern and southern Sichuan, northern and southern Chongqing, eastern and southern Gansu, southeastern Ningxia, northern and southern Shaanxi, central Shanxi, western Hubei, western Henan, northern and western Hebei, western Liaoning, eastern Tibet, eastern Qinghai, western Xinjiang and other regions of China.展开更多
Tropical mountainous areas not only provide substantial carbon storage and play an important role in global biological diversity, but also provide basic livelihood for a large number of poor ethnic minorities. However...Tropical mountainous areas not only provide substantial carbon storage and play an important role in global biological diversity, but also provide basic livelihood for a large number of poor ethnic minorities. However, there is no unified and explicit definition for mountainous areas. The local elevation range(LER) is a crucial structural parameter for delineating mountainous areas. However, current LER products are limited by the subjective selection of an optimum statistical window or coarser spatial resolution of topographical data. In this study, we presented an approach using thresholds for three topographic parameters, elevation, slope, and LER, derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM) to redelineate the vast mountainous areas of mainland Southeast Asia(MSEA). The mean change-point analysis method was applied to determine the optimum statistical window of the 1 arc second(approximately 30 m)-resolution GDEM LER. The results showed that: First, the optimum statistical window is 38 × 38 cell units(width × height) in a rectangular neighborhood, or an area of about 1.30 km^2 for calculating GDEM LER in MSEA. Second, the LER of more than 80% of the area ranges from 30 m to 499 m in MSEA. The LERs in the northern and northwestern MSEA are greater than their counterparts in the south and east. Third, the area of the re-delineated mountainous areas was 83.52 × 10~4 km^2, about 38.71% of the total area. Spatially, the mountainous areas are mainly distributed in the north and northeast of MSEA. The re-delineated 30-m resolution map of the mountainous areas will serve as a topographical dataset for monitoring mountainrelated land surface changes in MSEA. The parameter-modified mountain extraction procedure can be expanded to delineate global mountainous areas.展开更多
A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined b...A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined by computing the spatial gradient of triangle and triangle edges. Outflow edge was defined by comparing the contribution area that is separated by the steepest descent of the triangle. Local channels were then tracked to build drainage networks. Both triangle edges and facets were considered to construct flow path. The algorithm has been tested in the site for Hawaiian Island of Kaho'olawe, and the results were compared with those calculated by ARCGIS as well as terrain map. The reported algorithm has been proved to be a reliable approach with high efficiency to generate well-connected and coherent drainage networks.展开更多
Researchers in P.R.China commonly create triangulate irregular networks(TINs) from contours and then convert TINs into digital elevation models(DEMs).However,the DEM produced by this method can not precisely describe ...Researchers in P.R.China commonly create triangulate irregular networks(TINs) from contours and then convert TINs into digital elevation models(DEMs).However,the DEM produced by this method can not precisely describe and simulate key hydrological features such as rivers and drainage borders.Taking a hilly region in southwestern China as a research area and using ArcGISTM software,we analyzed the errors of different interpolations to obtain distributions of the errors and precisions of different algorithms and to provide references for DEM productions.The results show that different interpolation errors satisfy normal distributions,and large error exists near the structure line of the terrain.Furthermore,the results also show that the precision of a DEM interpolated with the Australian National University digital elevation model(ANUDEM) is higher than that interpolated with TIN.The DEM interpolated with TIN is acceptable for generating DEMs in the hilly region of southwestern China.展开更多
基金funded by the Ministry of Higher Education Malaysia(MOHE)through the Fundamental Research Grant Scheme(FRGS/1/2021/WAB07/UiTM/02/1).
文摘Digital ElevationModel(DEM)refers to a digital map of the surface of the Earth that only shows the bare ground,without any buildings,plants,or other characteristics.However,obtaining unlimited access to DEM data at high and medium resolutions is very hard.Consequently,users often question the accuracy of freely available DEMs and their suitability for various applications.By comparing them to Global Positioning System(GPS)elevation data,this study aimed to identify themost reliable and widely available DEM for various terrains.The objectives of this study were to generate DEMs fromdifferent open sources and validate the accuracy of these DEMs using GPS elevation data.Various DEM types including Sentinel-1,ALOS PALSAR,SRTM,AW3D30,and ASTER were compared.Root Mean Square Error(RMSE)andMean Error(ME)were used to measure the difference between the DEM-derived elevations and the GPS-measured elevations.The results showed that even though Sentinel-1 has higher resolutions,the accuracy of the DEM from Sentinel-1 depends on issues including coherence and interferometry,surface features,and temporal stability.On the other hand,ALOS PALSAR could accurately represent surfaces in some situations.Additionally,DEMs with lower resolutions,such as SRTM and AW3D30,demonstrated greater consistency across various types of terrain.In contrast,the ASTER DEM showed more variability in complex terrains.While freely available DEMs are easy to use and accessible,their accuracy varies depending on the source and terrain features.Future improvements could include adding more ground control points and using advanced filtering methods to enhance precision.
基金supported by the Professional Development Award of the University of Tennessee
文摘Topographic shielding of cosmic radiation flux is a key parameter in using cosmogenic nuclides to determine surface exposure ages or erosion rates. Traditionally, this parameter is measured in the field and uncertainty and/or inconsistency may exist among different investigators. This paper provides an ArcGIS python code to determine topographic shielding factors using digital elevation models （DEMs）. This code can be imported into ArcGIS as a geoprocessing tool with a user-friendly graphical interface. The DEM-derived parameters using this method were validated with field measurements in central Tian Shan. Results indicate that DEM-derived shielding factors are consistent with field-measured values. It provides a valuable tool to save fieldwork efforts and has the potential to provide consistent results for different regions in the world to facilitate the comparison of cosmogenie nuclide results.
基金supported by the National Natural Science Foundation of China(Grant Nos.41471316,41401456)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions-PAPD(Grant No.164320H101)+1 种基金Major University Science Research Project of Jiangsu Province(Grant No.13KJA170001)the financial support provided by the PhD Scholarship from Eurasic Pacific Uninet for collaboration research in Austria
文摘Although many studies have investigated slope gradient uncertainty derived from Digital Elevation Models(DEMs), the research concerning slope length uncertainty is far from mature. This discrepancy affects the availability and accuracy of soil erosion as well as hydrological modeling. This study investigates the formation and distribution of existing errors and uncertainties in slope length derivation based on 5-m resolution DEMs of the Loess Plateau in the middle of China. The slope length accuracy in three different landform areas is examined to analyse algorithm effects. The experiments indicate that the accuracy of the flat test area is lower than that of the rougher areas. The value from the specific contributing area(SCA) method is greater than the cumulative slope length(CSL), and the differences between these two methods arise from the shape of the upslope area. The variation of mean slope length derived from various DEM resolutions and landforms. The slope length accuracy decreases with increasing grid size and terrain complexity at the six test sites. A regression model is built to express the relationship of mean slope length with DEM resolution less than 85 m and terrain complexity represented by gully density. The results support the understanding of the slope length accuracy, thereby aiding in the effective evaluation of the modeling effect of surface process.
基金partially supported by JSPS KAKENHI(Grant No.16H03153)the Limestone Association of Japan。
文摘Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the potential to be a cost-effective method for monitoring surface displacements over extensive areas,such as open-pit mines.DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model(DEM).However,since the topography of the ground surface in open-pit mines changes largely due to excavations,measurement errors can occur due to insufficient information on the elevation of mining areas.In this paper,effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry.In addition,validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system(GPS)monitoring conducted for three years at the same limestone quarry.It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters.Comparing the monitoring results of DInSAR and GPS,the root mean square error(RMSE)of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM,considering the excavation processes,is used.It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.
基金financial support from the National Natural Science Foundation of China(No.40201021)the Zhejiang Natural Science Foundation of China(M403040).
文摘In China, many scenic and tourism areas are suffering from the urbanization that results from physical development of tourism projects, leading to the removal of the vegetative cover, the creation of areas impermeable to water, in-stream modifications, and other problems. In this paper, the risk of soil erosion and its ecological risks in the West Lake Scenic Spots （WLSS） area were quantitatively evaluated by integrating the revised universal soil loss equation （RUSLE） with a digital elevation model （DEM） and geographical information system （GIS） software. The standard RUSLE factors were modified to account for local climatic and topographic characteristics reflected in the DEM maps, and for the soil types and vegetation cover types. An interface was created between the Areinfo software and RUSLE so that the level of soil erosion and its ecological risk in the WLSS area could be mapped immediately once the model factors were defined for the area. The results from an analysis using the Areinfo-RUSLE interface showed that the risk value in 93 % of the expanding western part of the WLSS area was moderate or more severe and the soil erosion risk in this area was thus large compared with that in the rest of the area. This paper mainly aimed to increase the awareness of the soil erosion risk in urbanizing areas and suggest that the local governments should consider the probable ecological risk resulting from soil erosion when enlarging and developing tourism areas.
基金supported by the(i)Commonwealth Scholarship Commission and the Foreign,Commonwealth and Development Office in the UK[Grant number NGCN-2021-239](ii)University of Cape Town Postgraduate Funding Office.
文摘Validation studies of global Digital Elevation Models(DEMs)in the existing literature are limited by the diversity and spread of landscapes,terrain types considered and sparseness of groundtruth.Moreover,there are knowledge gaps on the accuracy variations in rugged and complex landscapes,and previous studies have often not relied on robust internal and external validation measures.Thus,there is still only partial understanding and limited perspective of the reliability and adequacy of global DEMs for several applications.In this study,we utilize a dense spread of LiDAR groundtruth to assess the vertical accuracies of four medium-resolution,readily available,free-access and global coverage 1 arc-second(30 m)DEMs:NASADEM,ASTER GDEM,Copernicus GLO-30,and ALOS World 3D(AW3D).The assessment is carried out at landscapes spread across Cape Town,Southern Africa(urban/industrial,agricultural,mountain,peninsula and grassland/shrubland)and forested national parks in Gabon,Central Africa(low-relief tropical rainforest and high-relief tropical rainforest).The statistical analysis is based on robust accuracy metrics that cater for normal and non-normal elevation error distribution,and error ranking.In Cape Town,Copernicus DEM generally had the least vertical error with an overall Mean Error(ME)of 0.82 m and Root Mean Square Error(RMSE)of 2.34 m while ASTER DEM had the poorest performance.However,ASTER GDEM and NASADEM performed better in the low-relief and high-relief tropical forests of Gabon.Generally,the DEM errors have a moderate to high positive correlation in forests,and a low to moderate positive correlation in mountains and urban areas.Copernicus DEM showed superior vertical accuracy in forests with less than 40%tree cover,while ASTER and NASADEM performed better in denser forests with tree cover greater than 70%.This study is a robust regional assessment of these global DEMs.
基金supported in part by the National Natural Science Foundation of China under grant of 42090012in part by the project supported by the Open Fund of Hubei Luojia Laboratory(220100009)+3 种基金in part by 03 special research and 5G project of Jiangxi province in China(20212ABC03A09)Zhuhai industry university research cooperation project of China(ZH22017001210098PWC)Sichuan Science and Technology Program(2022YFN0031)Zhizhuo Research Fund on Spatial-Temporal Artificial Intelligence(Grant No.ZZJJ202202).
文摘High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications.The Ice,Cloud,and Land elevation Satellite 2(ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights,but it has not been fully evaluated.Hence,this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER),the Shuttle Radar Topography Mission(SRTM),and TanDEM-X(TDX)DEMs over vegetated mountainous areas.We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy.Then,the results were evaluated against a reference airborne LiDAR digital terrain model(DTM),by selecting 10,000 points over the entire area and comparing the accuracy of ASTER,SRTM,and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER,SRTM,and TDX DEMs assessed by the ATL08 strong beams,weak beams,and all beams.We also detected the impact of the terrain aspect,slope,and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty.Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%;while the weak beams accuracy was enhanced by 74.05%.Furthermore,slope strongly influenced ATL08 height errors and height uncertainty;especially on the weak beams.The errors induced by the slope significantly decreased when the uncertainty levels were reduced to<20 m.The evaluations of ASTER,SRTM,and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams.These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.
文摘This paper presents a component object model(COM)based framework for managing,analyzing and visualizing massive multi-scale digital elevation models(DEMs).The framework consists of a data management component(DMC),which is based on RDBMS/ORDBMS,a data analysis component(DAC)and a data render component(DRC).DMC can manage massive multi-scale data expressed at various reference frames within a pyramid database and can support fast access to data at variable resolution.DAC integrates many useful applied analytic functions whose results can be overlaid with the 3D scene rendered by DRC.DRC provides view-dependent data paging with the support of the underlying DMC and organizes the potential visible data at different levels into rendering.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40930531, 41171320)the National High Technology Research and Development Program of China (Grant No. 2011AA120303)Open Foundation of State Key Laboratory of Resources and Environmental Information System (Grant No. 2010KF0002SA)
文摘The influence of pre-quaternary underlying terrain on the formation of loess landforms, i.e., the geomorphological inheritance issue, is a focus in studies of loess landforms. On the basis of multi-source information, we used GIS spatial analysis methods to construct a simulated digital elevation model of a pre-quaternary paleotopographic surface in a severe soil erosion area of the Loess Plateau. To reveal the spatial relationship between underlying paleotopography and modern terrain, an XY scatter diagram, hypsometric curve, gradient and concavity of terrain profiles are used in the experiments. The experiments show that the altitude, gradient and concavity results have significant linear positive correlation between both terrains, which shows a relatively strong landform inheritance relationship, particularly in the intact and complete loess deposit areas. Despite the current surface appearing somewhat changed from the original shape of the underlying terrain under different erosion forces, we reveal that the modern terrain generally smoothes the topographic relief of underlying terrain in the loess deposition process. Our results deepen understanding of the characteristics of geomorphological inheritance in the formation and evolution of loess landforms.
基金financed by Universiti Teknologi Malaysia Encouragement Research Grant(Vot Q.J130000.3852.42J12)to provide incentives and financial support for UTM academic staff to lead research projects that contribute to the university’s research Key Performance Indicators(KPIs)and foster the development of high-quality,competitive research proposals.
文摘The integration of Unmanned Aerial Vehicles(UAVs)and Uncrewed Surface Vehicles(USVs)has revolutionized topographic and bathymetricmapping,significantly enhancing the accuracy and efficiency of geospatial data acquisition processes.This innovative approach synergistically combines terrestrial data collected by UAVs with underwater data obtained through USVs,culminating in the creation of unified high-resolution Digital Elevation Models(DEMs)of the river basin region represents a vital step toward understanding the dynamic interactions between land and water bodies.Hence,the seamless Topo-Bathymetric Elevation Model offers a detailed perspective of the river system,supporting informed decision-making in addressing sediment transport,erosion,and river morphology.This manuscript provides a comprehensive review examines the advanced methodologies for creating seamlessmultisource Topo-Bathymetry ElevationModels(TBEMs)in river basin contexts,emphasising critical factors such as cost-effectiveness,operational efficiency,and data precision.In particular,UAVs deliver high-resolution(1-3 cm)topographic mapping with 5-10 km operational ranges,while USVs provide complementary bathymetric data(1 m resolution)across 3-5 km.This synergy enables seamless land-water surveys,achieving superior precision(±8 cmterrestrial,±3 cmunderwater)and efficiency over traditional methods.By analysing the benefits and limitations inherent in these technologies,this review elucidates the potential of UAV-USV synergy to improve the accuracy and reliability of geospatial data,thereby supporting well-versed decision-making processes in environmental management and conservation efforts.Furthermore,the findings underscore the broader implications of this integrated approach for riverine and coastal studies,advocating for its wider adoption in various applications,including habitat monitoring,flood risk assessment,and sustainable resource management.The synthesis of terrestrial and aquatic data through UAV-USV collaboration not only advances the field of geospatial science but also fosters a deeper understanding of the interdependencies between land and water systems,ultimately contributing to more effective environmental stewardship.
基金Under the auspices of National Social Sciences Foundation of China(No.21BJY114)。
文摘Forests exert significant biogeophysical cooling effects(CE)through processes such as increased evapotranspiration,reduced albedo,and enhanced surface roughness.However,little is known about the extent to which elevation-induced temperature differences bias the observed CE and how this bias interacts with the underlying biogeophysical mechanisms.In this study,we integrated multisensor remote sensing products and Shuttle Radar Topography Mission(SRTM)elevation data on the Google Earth Engine(GEE)platform,and applied a spatial-temporal window regression approach to quantify and correct the sensitivity of land surface temperature(LST)to elevation for forest pixels across China from 2001 to 2022.First,we found that forest LST exhibited a significant negative relationship with elevation,leading to systematic CE overestimation by 0.61 K during the day and 0.60 K at night compared with altitudecorrected CE values.Second,after correction,the CE showed clear spatial heterogeneity,with stronger daytime cooling in tropical(-0.54 K)and temperate forests(-0.24 K),and warming in cold(+0.11 K)and arid regions(+0.53 K),while most regions experienced nighttime warming.Among forest types,evergreen needleleaf forests(ENF)exhibited the strongest daytime cooling(-0.36 K),whereas deciduous broadleaf(DBF)and open shrublands(OS)tended to warm.Third,mechanism analysis revealed that elevation correction strengthened the correlations of CE with leaf area index(LAI)and evapotranspiration,while maintaining a significant negative correlation with albedo,indicating that both radiative and non-radiative processes jointly shape the unbiased CE.These findings provide a more accurate quantification of forest CE by eliminating elevation-induced bias,which providing a more accurate assessment of the climate mitigation potential of forests,which is crucial for developing more effective forest management and ecological restoration strategies.
文摘This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the latter derived from the former. It is confirmed that significant differences exist between uncertainty descriptors, and propagation of uncertainty to end products is immensely affected by the specification of source uncertainty.
基金supported by the National Natural Science Foundation of China(grant 41901088)the China Postdoctoral Science Foundation(grant 2020M670423)+2 种基金supported by the National Natural Science Foundation of China(grant 41530748)the second Tibetan Plateau Scientific Expedition and Research Program(grant 2019QZKK0202)the 13th Five-year Informatization Plan of Chinese Academy of Sciences(grant XXH13505-06)。
文摘Subtraction of elevation datasets(e.g.digital elevation models(DEMs)and non-continuous elevation points)acquired at different times is a useful method to monitor landform surface change.Due to heavy post-processing of these elevation datasets,multi-source errors are introduced into the resulting elevation data products.To improve the estimation of elevation change,co-registration of elevation datasets is a prerequisite.This paper presents an open-source automated GIS tool(arc Pycor)for co-registering elevation datasets.arc Pycor is coded in Python 2.7 and is run via Arc GIS for Desktop.The performances of arc Pycor have been evaluated using a series of experiments.In benchmark tests,the resolved co-registration vectors of arc Pycor are compared to the predefined shift vectors obtained by artificially misaligning the slave DEMs from the master elevation datasets.Results show that arc Pycor is able to co-register DEMs with relative high accuracy and can well align slave DEMs to non-continuous elevation points,which indicates its robustness in co-registering of elevation datasets.arc Pycor is also able to co-register multi-sourced DEMs of different resolutions in mountain areas.
基金funded by the National Natural Science Foundation of China,grant number 62262045the Fundamental Research Funds for the Central Universities,grant number 2023CDJYGRH-YB11the Open Funding of SUGON Industrial Control and Security Center,grant number CUIT-SICSC-2025-03.
文摘Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes,where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions.To address these issues,we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder,guided multimodal fusion,and deep supervision.The framework is built upon the synergistic combination of cross-attention,gated fusion,and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation,enabling efficient context modeling and robust feature exchange between modalities.The decoder captures long-range context at deeper levels using lightweight cross-attention and refines spatial details at shallower levels through attention-gated skip fusion,enabling precise boundary delineation and fewer false positives.The gated fusion further enhances multimodal integration of optical and topographical cues,and the deep supervision stabilizes training and improves generalization.Moreover,to mitigate checkerboard artifacts,a learnable sub-pixel upsampling is devised to replace the traditional transposed convolution.Despite its compact design with fewer parameters,the model consistently outperforms state-of-the-art baselines.Experiments on two benchmark datasets,Landslide4Sense and Bijie,confirm the effectiveness of the framework.On the Bijie dataset,it achieves an F1-score of 0.9110 and an intersection over union(IoU)of 0.8839.These results highlight its potential for accurate large-scale landslide inventory mapping and real-time disaster response.The implementation is publicly available at https://github.com/mishaown/DiGATe-UNet-LandSlide-Segmentation(accessed on 3 November 2025).
基金This work was supported by Knowledge Innovation Pro-gram Chinese Academy of Sciences (No. KZCX2-SW-320-3 & KZCX3-SW-425).
文摘Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.
基金Under the auspices of National Youth Science Foundation of China(No.41001294)Key Project of National Natural Science Foundation of China(No.40930531)Research Fund of State Key Laboratory Resources and Environment Information System(No.2010KF0002SA)
文摘In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.
基金financially supported by the National Natural Science Foundation of China(31271987)the National key Research and Development Program of China(2016YFD0300702)the Special Fund for Agro-scientific Research in the Public Interest,China(201303016)
文摘Blumeria graminis f. sp. tritici, the pathogen that causes wheat powdery mildew, is one of the most important diseases affecting wheat production in China, and the oversummering is the key stage of wheat powdery mildew epidemic. The more oversummering regionalization of wheat powdery mildew has played an important role in disease prediction, prevention and control. In this study, we analyzed the correlation between oversummering data of wheat powdery mildew and the meteorological factors over the past years, and determined that temperature was the key meteorological factor influencing oversummering of wheat powdery mildew. The average temperature at which wheat powdery mildew growth was terminated(26.2°C) was used as the threshold temperature to regionalize the oversummering range of wheat powdery mildew. This regionalization was done using the GIS ordinary kriging method combined with the Digital Elevation model(DEM) of China. The results showed that annual probability of oversummering region based on Model 26.2 were consistent with the actual survey of the more summer wheat powdery mildew. Wheat powdery mildew oversummering regions in China mainly cover mountainous or high-altitude areas, and these regions form a narrow north-south oversummering zone. Oversummering regions of wheat powdery mildew is mainly concentrated in the high-altitude wheat growing areas, including northern and southern Yunnan, northwestern Guizhou, northern and southern Sichuan, northern and southern Chongqing, eastern and southern Gansu, southeastern Ningxia, northern and southern Shaanxi, central Shanxi, western Hubei, western Henan, northern and western Hebei, western Liaoning, eastern Tibet, eastern Qinghai, western Xinjiang and other regions of China.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA20010203)
文摘Tropical mountainous areas not only provide substantial carbon storage and play an important role in global biological diversity, but also provide basic livelihood for a large number of poor ethnic minorities. However, there is no unified and explicit definition for mountainous areas. The local elevation range(LER) is a crucial structural parameter for delineating mountainous areas. However, current LER products are limited by the subjective selection of an optimum statistical window or coarser spatial resolution of topographical data. In this study, we presented an approach using thresholds for three topographic parameters, elevation, slope, and LER, derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM) to redelineate the vast mountainous areas of mainland Southeast Asia(MSEA). The mean change-point analysis method was applied to determine the optimum statistical window of the 1 arc second(approximately 30 m)-resolution GDEM LER. The results showed that: First, the optimum statistical window is 38 × 38 cell units(width × height) in a rectangular neighborhood, or an area of about 1.30 km^2 for calculating GDEM LER in MSEA. Second, the LER of more than 80% of the area ranges from 30 m to 499 m in MSEA. The LERs in the northern and northwestern MSEA are greater than their counterparts in the south and east. Third, the area of the re-delineated mountainous areas was 83.52 × 10~4 km^2, about 38.71% of the total area. Spatially, the mountainous areas are mainly distributed in the north and northeast of MSEA. The re-delineated 30-m resolution map of the mountainous areas will serve as a topographical dataset for monitoring mountainrelated land surface changes in MSEA. The parameter-modified mountain extraction procedure can be expanded to delineate global mountainous areas.
基金the National Basic Research Program(973)of China(No.2007CB714103)
文摘A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined by computing the spatial gradient of triangle and triangle edges. Outflow edge was defined by comparing the contribution area that is separated by the steepest descent of the triangle. Local channels were then tracked to build drainage networks. Both triangle edges and facets were considered to construct flow path. The algorithm has been tested in the site for Hawaiian Island of Kaho'olawe, and the results were compared with those calculated by ARCGIS as well as terrain map. The reported algorithm has been proved to be a reliable approach with high efficiency to generate well-connected and coherent drainage networks.
基金Funded by the Natural Science Foundation of Chongqing under Grant No. CSTC2006AB1015.
文摘Researchers in P.R.China commonly create triangulate irregular networks(TINs) from contours and then convert TINs into digital elevation models(DEMs).However,the DEM produced by this method can not precisely describe and simulate key hydrological features such as rivers and drainage borders.Taking a hilly region in southwestern China as a research area and using ArcGISTM software,we analyzed the errors of different interpolations to obtain distributions of the errors and precisions of different algorithms and to provide references for DEM productions.The results show that different interpolation errors satisfy normal distributions,and large error exists near the structure line of the terrain.Furthermore,the results also show that the precision of a DEM interpolated with the Australian National University digital elevation model(ANUDEM) is higher than that interpolated with TIN.The DEM interpolated with TIN is acceptable for generating DEMs in the hilly region of southwestern China.
