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
Water erosion is a serious problem that leads to soil degradation,loss,and the destruction of structures.Assessing the risk of erosion and determining the affected areas has become crucial in order to understand the m...Water erosion is a serious problem that leads to soil degradation,loss,and the destruction of structures.Assessing the risk of erosion and determining the affected areas has become crucial in order to understand the main factors influencing its evolution and to minimize its impacts.This study focuses on evaluating the risk of erosion in the Assif el mal watershed,which is located in the High Atlas Mountains.The Erosion Potential Model(EPM)is used to estimate soil losses depending on various parameters such as lithology,hydrology,topography,and morphometry.Geographic information systems and remote sensing techniques are employed to map areas with high erosive potential and their relationship with the distribution of factors involved.Different digital elevation models are also used in this study to highlight the impact of data quality on the accuracy of the results.The findings reveal that approximately 59%of the total area in the Assif el mal basin has low to very low potential for soil losses,while 22%is moderately affected and 19.9%is at high to very high risk.It is therefore crucial to implement soil conservation measures to mitigate and prevent erosion risks.展开更多
High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to ana...High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of Asia.The science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m DEM.In this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land covers.Inferences were made from statistical quantifiers and elevation profiles.For the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test sites.The second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,respectively.The third test site,situated in the Zanda County of the Qinghai-Xizang,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible bias.Additionally,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological parameters.The results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.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
The Longchuan River basin lies within the China Sichuan-Yunnan rhomboid block.The NS-trending Yuanmou-Lvzhi River Fault(YLF),NW-trending Chuxiong-Nanhua Fault(CNF)and Shiyang-Huoshaotun Fault(HSF)are found within the ...The Longchuan River basin lies within the China Sichuan-Yunnan rhomboid block.The NS-trending Yuanmou-Lvzhi River Fault(YLF),NW-trending Chuxiong-Nanhua Fault(CNF)and Shiyang-Huoshaotun Fault(HSF)are found within the basin.The nature of the faults is complex,and the tectonic activity distribution characteristics require further clarification.By extraction from a digital elevation model,the measured longitudinal profile and the geomorphic indices of the Longchuan River,basin showed a stream-length gradient index(SL)of 49–650,hypsometric integral(HI)of 0.27–0.58,drainage basin asymmetry factor(AF)of 3.29–27.47,basin shape index(BS)of 0.87–2.75,valley floor width-to-height ratio(VF)of 0.06–5.40,and evaluation of relative tectonic activity(Iat)of 1.6–2.6.Results showed that river morphology and geomorphological indices in the Longchuan River basin were influenced by tectonic activity,bedrock lithology,climatic conditions,and development time,with tectonic activity playing a dominant role.The relative tectonic activity of the Longchuan River basin was zoned,with a gradual increase in relative tectonic activity from the south to the north.That the slip fault zone primarily controls the tectonic deformation of the Longchuan River basin in central Yunnan and the dynamics of the central Yunnan massif are consistent with the“rigid block lateral extrusion”1model.展开更多
0 INTRODUCTION.The global availability of digital elevation model(DEM)data,such as 90-m Shuttle Radar Topography Mission(SRTM)DEM and 30-m Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital ...0 INTRODUCTION.The global availability of digital elevation model(DEM)data,such as 90-m Shuttle Radar Topography Mission(SRTM)DEM and 30-m Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM),has been extensively utilized in morphotectonic analyses(e.g.,Wang et al.,2024;Cheng et al.,2018;Pérez-Pe?a et al.,2010;El Hamdouni et al.,2008).展开更多
Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and ...Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and AW3D30 Digital Surface Model data,combined with three machine learning algorithms—Random Forest(RF),Back Propagation Neural Network(BPNN),and Extreme Gradient Boosting(XGBoost)—to evaluate the performance of canopy height inversion and understory terrain reconstruction.The analysis emphasizes the impact of topographic and vegetation-related factors on model accuracy.Results reveal that slope is the most influential variable,contributing three to five times more to model performance than other features.In low-slope areas,understory terrain tends to be underestimated,whereas high-slope areas often result in overestimation.Moreover,the Normalized Difference Vegetation Index(NDVI)and land cover types,particularly forests and grasslands,significantly affect prediction accuracy,with model performance showing heightened sensitivity to vegetation characteristics in these regions.Among the models tested,XGBoost demonstrated superior performance,achieving a canopy height bias of-0.06 m,a root mean square error(RMSE)of 4.69 m for canopy height,and an RMSE of 9.82 m for understory terrain.Its ability to capture complex nonlinear relationships and handle high-dimensional data underlines its robustness.While the RF model exhibited strong stability and resistance to noise,its accuracy lagged slightly behind XGBoost.The BPNN model,by contrast,struggled in areas with complex terrain.This study offers valuable insights into feature selection and optimization in remote sensing applications,providing a reference framework for enhancing the accuracy and efficiency of environmental monitoring practices.展开更多
Texture analysis methods offer substantial advantages and potential in examining macro-topographic features of dunes.Despite these advantages,comprehensive approaches that integrate digital elevation model(DEM)with qu...Texture analysis methods offer substantial advantages and potential in examining macro-topographic features of dunes.Despite these advantages,comprehensive approaches that integrate digital elevation model(DEM)with quantitative texture features have not been fully developed.This study introduced an automatic classification framework for dunes that combines texture and topographic features and validated it through a typical coastal aeolian landform,namely,dunes in the Namib Desert.A three-stage approach was outlined:(1)segmentation of dune units was conducted using digital terrain analysis;(2)six texture features(angular second moment,contrast,correlation,variance,entropy,and inverse difference moment)were extracted from the gray-level co-occurrence matrix(GLCM)and subsequently quantified;and(3)texture–topographic indices were integrated into the random forest(RF)model for classification.The results show that the RF model fused with texture features can accurately identify dune morphological characteristics;through accuracy evaluation and remote sensing image verification,the overall accuracy reaches 78.0%(kappa coefficient=0.72),outperforming traditional spectral-based methods.In addition,spatial analysis reveals that coastal dunes exhibit complex texture patterns,with texture homogeneity being closely linked to dune-type transitions.Specifically,homogeneous textures correspond to simple and stable forms such as barchans,while heterogeneous textures are associated with complex or composite dunes.The complexity,periodicity,and directionality of texture features are highly consistent with the spatial distribution of dunes.Validation using high-resolution remote sensing imagery(Sentinel-2)further confirms that the method effectively clusters similar dunes and distinguishes different dune types.Additionally,the dune classification results have a good correspondence with changes in near-surface wind regimes.Overall,the findings suggest that texture features derived from DEM can accurately capture the dynamic characteristics of dune morphology,offering a novel approach for automatic dune classification.Compared with traditional methods,the developed approach facilitates large-scale and high-precision dune mapping while reducing the workload of manual interpretation,thus advancing research on aeolian geomorphology.展开更多
Geomorphometric modeling and mapping of Antarctic oases are promising for obtaining new quantitative knowledge about the topography of these unique landscapes and for the further use of morphometric information in Ant...Geomorphometric modeling and mapping of Antarctic oases are promising for obtaining new quantitative knowledge about the topography of these unique landscapes and for the further use of morphometric information in Antarctic research.Within the framework of a project to create a thematic physical-geographical scientific reference geomorphometric atlas of ice-free areas of Antarctica,we performed geomorphometric modeling and mapping of the Bunger Hills(Knox Coast,Wilkes Land,East Antarctica),one of the largest Antarctic oases.By processing a fragment of the Reference Elevation Model of Antarctica(REMA)covering the Bunger Hills and adjacent glaciers,we created,for the first time,a series of 37 medium-to large-scale maps of nine of the most scientifically important morphometric variables(i.e.,slope gradient,slope aspect,vertical curvature,horizontal curvature,maximal curvature,minimal curvature,catchment area,topographic wetness index,and stream power index).The morphometric maps describe the topography of the Bunger Hills in a quantitative,rigorous,and reproducible manner.New morphometric data can be useful for further geological,geomorphological,glaciological,ecological,and hydrological studies of this Antarctic oasis.展开更多
Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(...Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.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
A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, ...A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.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
Soil salinity is one of the most severe environmental problems worldwide. It is necessary to develop a soil-salinity-estimation model to project the spatial distribution of soil salinity. The aims of this study were t...Soil salinity is one of the most severe environmental problems worldwide. It is necessary to develop a soil-salinity-estimation model to project the spatial distribution of soil salinity. The aims of this study were to use remote sensed images and digital elevation model(DEM) to develop quantitative models for estimating soil salinity and to investigate the influence of vegetation on soil salinity estimation. Digital bands of Landsat Thematic Mapper(TM) images, vegetation indices, and terrain indices were selected as predictive variables for the estimation. The generalized additive model(GAM) was used to analyze the quantitative relationship between soil salt content, spectral properties, and terrain indices. Akaike's information criterion(AIC) was used to select relevant predictive variables for fitted GAMs. A correlation analysis and root mean square error between predicted and observed soil salt contents were used to validate the fitted GAMs. A high ratio of explained deviance suggests that an integrated approach using spectral and terrain indices with GAM was practical and efficient for estimating soil salinity. The performance of the fitted GAMs varied with changes in vegetation cover.Salinity in sparsely vegetated areas was estimated better than in densely vegetated areas. Visible red and near-infrared bands, and the second and third components of the tasseled cap transformation were the most important spectral variables for the estimation. Variable combinations in the fitted GAMs and their contribution varied with changes in vegetation cover. The contribution of terrain indices was smaller than that of spectral indices, possibly due to the low spatial resolution of DEM. This research may provide some beneficial references for regional soil salinity estimation.展开更多
On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang st...On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km<SUP>2</SUP> of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.展开更多
The spatial structure characteristics of landform are the foundation of geomorphologic classification and recognition.This paper proposed a new method on quantifying spatial structure characteristics of terrain surfac...The spatial structure characteristics of landform are the foundation of geomorphologic classification and recognition.This paper proposed a new method on quantifying spatial structure characteristics of terrain surface based on improved 3D Lacunarity model.Lacunarity curve and its numerical integration are used in this model to improve traditional classification result that different morphological types may share the close value of indexes based on global statistical analysis.Experiments at four test areas with different landform types show that improved 3D Lacunarity model can effectively distinguish different morphological types per texture analysis.Higher sensitivity in distinguishing the tiny differences of texture characteristics of terrain surface shows that the quantification method by 3D Lacu-narity model and its numerical integration presented in this paper could contribute to improving the accuracy of land-form classifications and relative studies.展开更多
Floods are one of the most common natural hazards occurring all around the world.However,the knowledge of the origins of a food and its possible magnitude in a given region remains unclear yet.This lack of understandi...Floods are one of the most common natural hazards occurring all around the world.However,the knowledge of the origins of a food and its possible magnitude in a given region remains unclear yet.This lack of understanding is particularly acute in mountainous regions with large degrees in Sichuan Province,China,where runoff is seldom measured.The nature of streamflow in a region is related to the time and spatial distribution of rainfall quantity and watershed geomorphology.The geomorphologic characteristics are the channel network and surrounding landscape which transform the rainfall input into an output hydrograph at the outlet of the watershed.With the given geomorphologic properties of the watershed,theoretically the hydrological response function can be determined hydraulically without using any recorded data of past rainfall or runoff events.In this study,a kinematic-wave-based geomorphologic instantaneous unit hydrograph (KW-GIUH) model was adopted and verified to estimate runoff in ungauged areas.Two mountain watersheds,the Yingjing River watershed and Tianquan River watershed in Sichuan were selected as study sites.The geomorphologic factors of the two watersheds were obtained by using a digital elevation model (DEM) based on the topographic database obtained from the Shuttle Radar Topography Mission of US's NASA.The tests of the model on the two watersheds were performed both at gauged and ungauged sites.Comparison between the simulated and observed hydrographs for a number of rainstorms at the gauged sites indicated the potential of the KW-GIUH model as a useful tool for runoff analysis in these regions.Moreover,to simulate possible concentrated rainstorms that could result in serious flooding in these areas,synthetic rainfall hyetographs were adopted as input to the KW-GIUH model to obtain the flow hydrographs at two ungauged sites for different return period conditions.Hydroeconomic analysis can be performed in the future to select the optimum design return period for determining the flood control work.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
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
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.
文摘Water erosion is a serious problem that leads to soil degradation,loss,and the destruction of structures.Assessing the risk of erosion and determining the affected areas has become crucial in order to understand the main factors influencing its evolution and to minimize its impacts.This study focuses on evaluating the risk of erosion in the Assif el mal watershed,which is located in the High Atlas Mountains.The Erosion Potential Model(EPM)is used to estimate soil losses depending on various parameters such as lithology,hydrology,topography,and morphometry.Geographic information systems and remote sensing techniques are employed to map areas with high erosive potential and their relationship with the distribution of factors involved.Different digital elevation models are also used in this study to highlight the impact of data quality on the accuracy of the results.The findings reveal that approximately 59%of the total area in the Assif el mal basin has low to very low potential for soil losses,while 22%is moderately affected and 19.9%is at high to very high risk.It is therefore crucial to implement soil conservation measures to mitigate and prevent erosion risks.
基金The authors gratefully acknowledge the science teams of NASA High Mountain Asia 8-meter DEM and NASA ICESat-2 for providing access to the data.This work was conducted with the infrastructure provided by the National Remote Sensing Centre(NRSC),for which the authors were indebted to the Director,NRSC,Hyderabad.We acknowledge the continued support and scientific insights from Mr.Rakesh Fararoda,Mr.Sagar S Salunkhe,Mr.Hansraj Meena,Mr.Ashish K.Jain and other staff members of Regional Remote Sensing Centre-West,NRSC/ISRO,Jodhpur.The authors want to acknowledge Dr.Kamal Pandey,Scientist,IIRS,Dehradun,for sharing field-level information about the Auli-Joshimath.This research did not receive any specific grant from funding agencies in the public,commercial,or not-for-profit sectors.
文摘High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of Asia.The science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m DEM.In this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land covers.Inferences were made from statistical quantifiers and elevation profiles.For the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test sites.The second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,respectively.The third test site,situated in the Zanda County of the Qinghai-Xizang,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible bias.Additionally,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological parameters.The results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.
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.
基金central Yunnan Province(1:50,000)Chuxiong City,central Yunnan Province(Grant/Award Numbers:DD20220987)the National Natural Science Foundation of China(Grant/Award Numbers:41972118).
文摘The Longchuan River basin lies within the China Sichuan-Yunnan rhomboid block.The NS-trending Yuanmou-Lvzhi River Fault(YLF),NW-trending Chuxiong-Nanhua Fault(CNF)and Shiyang-Huoshaotun Fault(HSF)are found within the basin.The nature of the faults is complex,and the tectonic activity distribution characteristics require further clarification.By extraction from a digital elevation model,the measured longitudinal profile and the geomorphic indices of the Longchuan River,basin showed a stream-length gradient index(SL)of 49–650,hypsometric integral(HI)of 0.27–0.58,drainage basin asymmetry factor(AF)of 3.29–27.47,basin shape index(BS)of 0.87–2.75,valley floor width-to-height ratio(VF)of 0.06–5.40,and evaluation of relative tectonic activity(Iat)of 1.6–2.6.Results showed that river morphology and geomorphological indices in the Longchuan River basin were influenced by tectonic activity,bedrock lithology,climatic conditions,and development time,with tectonic activity playing a dominant role.The relative tectonic activity of the Longchuan River basin was zoned,with a gradual increase in relative tectonic activity from the south to the north.That the slip fault zone primarily controls the tectonic deformation of the Longchuan River basin in central Yunnan and the dynamics of the central Yunnan massif are consistent with the“rigid block lateral extrusion”1model.
基金supported by the National Key Research and Development Project of China(No.2023YFC3007303)the Open Research Project of the Hubei Key Laboratory of Intelligent Geo-Information Processing(No.KLIGIP-2019B08)。
文摘0 INTRODUCTION.The global availability of digital elevation model(DEM)data,such as 90-m Shuttle Radar Topography Mission(SRTM)DEM and 30-m Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM),has been extensively utilized in morphotectonic analyses(e.g.,Wang et al.,2024;Cheng et al.,2018;Pérez-Pe?a et al.,2010;El Hamdouni et al.,2008).
基金funded by the National Key Research and Development Program(Grants No.2023YFE0207900)。
文摘Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and AW3D30 Digital Surface Model data,combined with three machine learning algorithms—Random Forest(RF),Back Propagation Neural Network(BPNN),and Extreme Gradient Boosting(XGBoost)—to evaluate the performance of canopy height inversion and understory terrain reconstruction.The analysis emphasizes the impact of topographic and vegetation-related factors on model accuracy.Results reveal that slope is the most influential variable,contributing three to five times more to model performance than other features.In low-slope areas,understory terrain tends to be underestimated,whereas high-slope areas often result in overestimation.Moreover,the Normalized Difference Vegetation Index(NDVI)and land cover types,particularly forests and grasslands,significantly affect prediction accuracy,with model performance showing heightened sensitivity to vegetation characteristics in these regions.Among the models tested,XGBoost demonstrated superior performance,achieving a canopy height bias of-0.06 m,a root mean square error(RMSE)of 4.69 m for canopy height,and an RMSE of 9.82 m for understory terrain.Its ability to capture complex nonlinear relationships and handle high-dimensional data underlines its robustness.While the RF model exhibited strong stability and resistance to noise,its accuracy lagged slightly behind XGBoost.The BPNN model,by contrast,struggled in areas with complex terrain.This study offers valuable insights into feature selection and optimization in remote sensing applications,providing a reference framework for enhancing the accuracy and efficiency of environmental monitoring practices.
基金supported by the National Natural Science Foundation of China(42271421).
文摘Texture analysis methods offer substantial advantages and potential in examining macro-topographic features of dunes.Despite these advantages,comprehensive approaches that integrate digital elevation model(DEM)with quantitative texture features have not been fully developed.This study introduced an automatic classification framework for dunes that combines texture and topographic features and validated it through a typical coastal aeolian landform,namely,dunes in the Namib Desert.A three-stage approach was outlined:(1)segmentation of dune units was conducted using digital terrain analysis;(2)six texture features(angular second moment,contrast,correlation,variance,entropy,and inverse difference moment)were extracted from the gray-level co-occurrence matrix(GLCM)and subsequently quantified;and(3)texture–topographic indices were integrated into the random forest(RF)model for classification.The results show that the RF model fused with texture features can accurately identify dune morphological characteristics;through accuracy evaluation and remote sensing image verification,the overall accuracy reaches 78.0%(kappa coefficient=0.72),outperforming traditional spectral-based methods.In addition,spatial analysis reveals that coastal dunes exhibit complex texture patterns,with texture homogeneity being closely linked to dune-type transitions.Specifically,homogeneous textures correspond to simple and stable forms such as barchans,while heterogeneous textures are associated with complex or composite dunes.The complexity,periodicity,and directionality of texture features are highly consistent with the spatial distribution of dunes.Validation using high-resolution remote sensing imagery(Sentinel-2)further confirms that the method effectively clusters similar dunes and distinguishes different dune types.Additionally,the dune classification results have a good correspondence with changes in near-surface wind regimes.Overall,the findings suggest that texture features derived from DEM can accurately capture the dynamic characteristics of dune morphology,offering a novel approach for automatic dune classification.Compared with traditional methods,the developed approach facilitates large-scale and high-precision dune mapping while reducing the workload of manual interpretation,thus advancing research on aeolian geomorphology.
文摘Geomorphometric modeling and mapping of Antarctic oases are promising for obtaining new quantitative knowledge about the topography of these unique landscapes and for the further use of morphometric information in Antarctic research.Within the framework of a project to create a thematic physical-geographical scientific reference geomorphometric atlas of ice-free areas of Antarctica,we performed geomorphometric modeling and mapping of the Bunger Hills(Knox Coast,Wilkes Land,East Antarctica),one of the largest Antarctic oases.By processing a fragment of the Reference Elevation Model of Antarctica(REMA)covering the Bunger Hills and adjacent glaciers,we created,for the first time,a series of 37 medium-to large-scale maps of nine of the most scientifically important morphometric variables(i.e.,slope gradient,slope aspect,vertical curvature,horizontal curvature,maximal curvature,minimal curvature,catchment area,topographic wetness index,and stream power index).The morphometric maps describe the topography of the Bunger Hills in a quantitative,rigorous,and reproducible manner.New morphometric data can be useful for further geological,geomorphological,glaciological,ecological,and hydrological studies of this Antarctic oasis.
基金Supported by the National Key R&D Program of China (No.2023YFC3008100)the National Natural Science Foundation of China (No.U23A2033)
文摘Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.
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supported by the Research Fund for Commonweal Trades (Meteorology) (Grants No.GYHY200706037, GYHY (QX) 2007-6-1,GYHY200906007,and GYHY201006038)the National Natural Science Foundation of China (Grants No.50479017 and 40971016)Program for Changjiang Scholars and Innovative Research Team in University (Grant No.IRT0717)
文摘A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.
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financially supported by the National Natural Science Foundation of China (Nos. 41001363 and 41471335)the Ocean Public Welfare Scientific Research Project, China (No. 201305021)
文摘Soil salinity is one of the most severe environmental problems worldwide. It is necessary to develop a soil-salinity-estimation model to project the spatial distribution of soil salinity. The aims of this study were to use remote sensed images and digital elevation model(DEM) to develop quantitative models for estimating soil salinity and to investigate the influence of vegetation on soil salinity estimation. Digital bands of Landsat Thematic Mapper(TM) images, vegetation indices, and terrain indices were selected as predictive variables for the estimation. The generalized additive model(GAM) was used to analyze the quantitative relationship between soil salt content, spectral properties, and terrain indices. Akaike's information criterion(AIC) was used to select relevant predictive variables for fitted GAMs. A correlation analysis and root mean square error between predicted and observed soil salt contents were used to validate the fitted GAMs. A high ratio of explained deviance suggests that an integrated approach using spectral and terrain indices with GAM was practical and efficient for estimating soil salinity. The performance of the fitted GAMs varied with changes in vegetation cover.Salinity in sparsely vegetated areas was estimated better than in densely vegetated areas. Visible red and near-infrared bands, and the second and third components of the tasseled cap transformation were the most important spectral variables for the estimation. Variable combinations in the fitted GAMs and their contribution varied with changes in vegetation cover. The contribution of terrain indices was smaller than that of spectral indices, possibly due to the low spatial resolution of DEM. This research may provide some beneficial references for regional soil salinity estimation.
基金The research is jointly supported financially by the National Natural Science Foundation of China under Grant No. 40171016 and 49794030.
文摘On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km<SUP>2</SUP> of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.
基金Under the auspices of National Natural Science Foundation of China (No.40930531,41171320,41001301)
文摘The spatial structure characteristics of landform are the foundation of geomorphologic classification and recognition.This paper proposed a new method on quantifying spatial structure characteristics of terrain surface based on improved 3D Lacunarity model.Lacunarity curve and its numerical integration are used in this model to improve traditional classification result that different morphological types may share the close value of indexes based on global statistical analysis.Experiments at four test areas with different landform types show that improved 3D Lacunarity model can effectively distinguish different morphological types per texture analysis.Higher sensitivity in distinguishing the tiny differences of texture characteristics of terrain surface shows that the quantification method by 3D Lacu-narity model and its numerical integration presented in this paper could contribute to improving the accuracy of land-form classifications and relative studies.
基金supported by the key project of the National Natural Science Foundation of China (NSFC No. 50739002)the National Science Council of Taibei of China (NSC 97-2625-M-019-001)+1 种基金the Open Research Fund Program of State key Laboratory of Hydraulics and River Engineering,Sichuan University,China (No. 1001)Financial supports from the above organizations are fully acknowledged
文摘Floods are one of the most common natural hazards occurring all around the world.However,the knowledge of the origins of a food and its possible magnitude in a given region remains unclear yet.This lack of understanding is particularly acute in mountainous regions with large degrees in Sichuan Province,China,where runoff is seldom measured.The nature of streamflow in a region is related to the time and spatial distribution of rainfall quantity and watershed geomorphology.The geomorphologic characteristics are the channel network and surrounding landscape which transform the rainfall input into an output hydrograph at the outlet of the watershed.With the given geomorphologic properties of the watershed,theoretically the hydrological response function can be determined hydraulically without using any recorded data of past rainfall or runoff events.In this study,a kinematic-wave-based geomorphologic instantaneous unit hydrograph (KW-GIUH) model was adopted and verified to estimate runoff in ungauged areas.Two mountain watersheds,the Yingjing River watershed and Tianquan River watershed in Sichuan were selected as study sites.The geomorphologic factors of the two watersheds were obtained by using a digital elevation model (DEM) based on the topographic database obtained from the Shuttle Radar Topography Mission of US's NASA.The tests of the model on the two watersheds were performed both at gauged and ungauged sites.Comparison between the simulated and observed hydrographs for a number of rainstorms at the gauged sites indicated the potential of the KW-GIUH model as a useful tool for runoff analysis in these regions.Moreover,to simulate possible concentrated rainstorms that could result in serious flooding in these areas,synthetic rainfall hyetographs were adopted as input to the KW-GIUH model to obtain the flow hydrographs at two ungauged sites for different return period conditions.Hydroeconomic analysis can be performed in the future to select the optimum design return period for determining the flood control work.
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.
