ASTER Global Digital Elevation Model Research Articles

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

Abstract. The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

VERTICAL ACCURACY ASSESSMENT OF 30-M RESOLUTION ALOS, ASTER, AND SRTM GLOBAL DEMS OVER NORTHEASTERN MINDANAO, PHILIPPINES

Abstract. The ALOS World 3D – 30 m (AW3D30), ASTER Global DEM Version 2 (GDEM2), and SRTM-30 m are Digital Elevation Models (DEMs) that have been made available to the general public free of charge. An important feature of these DEMs is their unprecedented horizontal resolution of 30-m and almost global coverage. The very recent release of these DEMs, particularly AW3D30 and SRTM- 30 m, calls for opportunities for the conduct of localized assessment of the DEM’s quality and accuracy to verify their suitability for a wide range of applications in hydrology, geomorphology, archaelogy, and many others. In this study, we conducted a vertical accuracy assessment of these DEMs by comparing the elevation of 274 control points scattered over various sites in northeastern Mindanao, Philippines. The elevations of these control points (referred to the Mean Sea Level, MSL) were obtained through 3rd order differential levelling using a high precision digital level, and their horizontal positions measured using a global positioning system (GPS) receiver. These control points are representative of five (5) land-cover classes namely brushland (45 points), built-up (32), cultivated areas (97), dense vegetation (74), and grassland (26). Results showed that AW3D30 has the lowest Root Mean Square Error (RMSE) of 5.68 m, followed by SRTM-30 m (RMSE = 8.28 m), and ASTER GDEM2 (RMSE = 11.98 m). While all the three DEMs overestimated the true ground elevations, the mean and standard deviations of the differences in elevations were found to be lower in AW3D30 compared to SRTM-30 m and ASTER GDEM2. The superiority of AW3D30 over the other two DEMS was also found to be consistent even under different landcover types, with AW3D30's RMSEs ranging from 4.29 m (built-up) to 6.75 m (dense vegetation). For SRTM-30 m, the RMSE ranges from 5.91 m (built-up) to 10.42 m (brushland); for ASTER GDEM2, the RMSE ranges from 9.27 m (brushland) to 14.88 m (dense vegetation). The results of the vertical accuracy assessment suggest that the AW3D30 is more accurate than SRTM-30 m and ASTER GDEM2, at least for the areas considered in this study. On the other hand, the tendencies of the three DEMs to overestimate true ground elevation can be considered an important finding that users of the DEMs in the Philippines should be aware of, and must be considered into decisions regarding use of these data products in various applications.

VERTICAL ACCURACY ASSESSMENT OF 30-M RESOLUTION ALOS, ASTER, AND SRTM GLOBAL DEMS OVER NORTHEASTERN MINDANAO, PHILIPPINES

The ALOS World 3D – 30 m (AW3D30), ASTER Global DEM Version 2 (GDEM2), and SRTM-30 m are Digital Elevation Models (DEMs) that have been made available to the general public free of charge. An important feature of these DEMs is their unprecedented horizontal resolution of 30-m and almost global coverage. The very recent release of these DEMs, particularly AW3D30 and SRTM- 30 m, calls for opportunities for the conduct of localized assessment of the DEM’s quality and accuracy to verify their suitability for a wide range of applications in hydrology, geomorphology, archaelogy, and many others. In this study, we conducted a vertical accuracy assessment of these DEMs by comparing the elevation of 274 control points scattered over various sites in northeastern Mindanao, Philippines. The elevations of these control points (referred to the Mean Sea Level, MSL) were obtained through 3rd order differential levelling using a high precision digital level, and their horizontal positions measured using a global positioning system (GPS) receiver. These control points are representative of five (5) land-cover classes namely brushland (45 points), built-up (32), cultivated areas (97), dense vegetation (74), and grassland (26). Results showed that AW3D30 has the lowest Root Mean Square Error (RMSE) of 5.68 m, followed by SRTM-30 m (RMSE = 8.28 m), and ASTER GDEM2 (RMSE = 11.98 m). While all the three DEMs overestimated the true ground elevations, the mean and standard deviations of the differences in elevations were found to be lower in AW3D30 compared to SRTM-30 m and ASTER GDEM2. The superiority of AW3D30 over the other two DEMS was also found to be consistent even under different landcover types, with AW3D30's RMSEs ranging from 4.29 m (built-up) to 6.75 m (dense vegetation). For SRTM-30 m, the RMSE ranges from 5.91 m (built-up) to 10.42 m (brushland); for ASTER GDEM2, the RMSE ranges from 9.27 m (brushland) to 14.88 m (dense vegetation). The results of the vertical accuracy assessment suggest that the AW3D30 is more accurate than SRTM-30 m and ASTER GDEM2, at least for the areas considered in this study. On the other hand, the tendencies of the three DEMs to overestimate true ground elevation can be considered an important finding that users of the DEMs in the Philippines should be aware of, and must be considered into decisions regarding use of these data products in various applications.

Estimation of Polder Retention Capacity Based on ASTER, SRTM and LIDAR DEMs: The Case of Majdany Polder (West Poland)

This study compares four digital elevation models (DEMs), based on various data sources, to define polder retention capacities. Two commercial and two publically available, free of charge data sources were used. Commercial sources are DEMs based on aerial images and LIDAR (Light Detection and Ranging) data. Free data source DEMs generated are based on: SRTM (Shuttle Radar Topography Mission) and ASTER GDEM (ASTER Global Digital Elevation Model). In addition, the impact of the spatial resolution of the numerical terrain model on the calculated polder volume was evaluated. A DEM based on LIDAR data was used as the reference model and was supplemented with our own geodetic GPS (Global Positioning System) measurements. In flood modeling and management, including retention of river valleys and polders, it is necessary to properly estimate their capacity and the relation between capacity and water level. The study showed the impact of quantitative and qualitative data sources in determining the retention capacity of a polder.

Detection of 2011 Sikkim earthquake-induced landslides using neuro-fuzzy classifier and digital elevation model

In this paper, a semiautomatic method for landslide detection from satellite images and digital terrain information using generalized improved fuzzy Kohonen clustering network (GIFKCN) classifier is presented. The proposed method classifies the pre- and post-landslide images using the GIFKCN classifier which is trained using spectral indices such as normalized difference vegetation index, normalized difference building index and normalized difference water index. The changes in the vegetation class are identified using the pre- and post-classified images. Generally, landslides result in loss of vegetation; thus, using this property, candidate landslides are identified. Finally, false positives are removed using a rule set created from DEM derivatives slope and aspect. The proposed method is applied on Landsat 5 and Advanced Land Imager EO-1 satellite images to detect earthquake-induced landslides that occurred in Sikkim state of India due to the September 18, 2011, earthquake of magnitude M w = 6.9. The terrain information used is ASTER Global Digital Elevation Model of the area. The accuracy assessment of the method is done, and the results show that the landslides are identified and classified efficiently.

Using geoinformatics and geomorphometrics to quantify the geodiversity of Crete, Greece

The geodiversity of Crete is quantified in this study, based on the classification of geomorphometric, geological and climatic factors. A number of geomorphometric variables, extracted from the ASTER Global Digital Elevation Model (ASTER G-DEM) in conjunction with geological and climatic information, are evaluated through various algorithms incorporated into Geographical Information System (GIS) software’s. The derived geoinformatic data sets are then analyzed to produce the geodiversity of Crete. The geodiversity map is used to quantify the geodiversity, by calculating landscape diversity and other spatial pattern indices. Those indices are evaluating the richness, evenness, fragmentation and shape of the landscape patch types. The outcome of this study has highlighted that western Crete is characterized by complex geodiversity with more irregular, elongated and fragmented landscape patterns relative to the eastern part of the island. The geodiversity indices provide insights into the processes shaping landscapes, particularly the “battle” between neotectonic landscape deformation and erosion/deposition. The methodology presented can be useful for decision makers when evaluating a regions geological heritage, planning the management of natural resources, or designating areas for conservation.

Evaluating positional accuracy of Pleiades 1A satellite imagery in exploiting foreign natural resources

In this research, we’ve carried out a geo-positioning accuracy test for the unaccessable area using Pleiades 1A satellite image which was captured in 2014 for the city of Yakutsk, Russia with 50 cm spatial resolution. The research area has been considered as a candidate site for the oversea resources development and on-site field surveying of the area has not been possible so far. There were two difficulties to use Pleiades 1A for the research area. First, we had to use inaccurate ground control points due to inaccessibility of research area. Second, there were huge differences between real-world terrain of Yakutsk and the calculated height range by the normalized offset and scale parameters of the vendor-provided rational polynomial coefficients (RPCs). We’ve tried to enhance geo-positioning accuracy by sorting out these two difficulties and finally tried to evaluate the usability of Pleiades 1A for the unaccessible area. We’ve applied the direct method for RPCs refinement by using control points captured from Google Earth and ASTER Global Digital Elevation Models (GDEM). As a result of this method, we were able to improve the vertical-accuracy significantly. However we also found that this method didn’t improve the horizontal-accuracy, because of low accuracy of reference points from Google Earth or GDEM. It is required to carry out additional research to improve the geo-positioning accuracy of Pleiades 1A image for the unaccessible area.

Pattern of NDVI-based vegetation greening along an altitudinal gradient in the eastern Himalayas and its response to global warming.

The eastern Himalayas, especially the Yarlung Zangbo Grand Canyon Nature Reserve (YNR), is a global hotspot of biodiversity because of a wide variety of climatic conditions and elevations ranging from 500 to > 7000 m above sea level (a.s.l.). The mountain ecosystems at different elevations are vulnerable to climate change; however, there has been little research into the patterns of vegetation greening and their response to global warming. The objective of this paper is to examine the pattern of vegetation greening in different altitudinal zones in the YNR and its relationship with vegetation types and climatic factors. Specifically, the inter-annual change of the normalized difference vegetation index (NDVI) and its variation along altitudinal gradient between 1999 and 2013 was investigated using SPOT-VGT NDVI data and ASTER global digital elevation model (GDEM) data. We found that annual NDVI increased by 17.58% in the YNR from 1999 to 2013, especially in regions dominated by broad-leaved and coniferous forests at lower elevations. The vegetation greening rate decreased significantly as elevation increased, with a threshold elevation of approximately 3000 m. Rising temperature played a dominant role in driving the increase in NDVI, while precipitation has no statistical relationship with changes in NDVI in this region. This study provides useful information to develop an integrated management and conservation plan for climate change adaptation and promote biodiversity conservation in the YNR.

Geomorphic and lithologic control on bedrock channels in drainage basins of the Western Arabian Peninsula

Hypsometric curves, their integrals and channel profiles have long been used as effective indicators of stages in topographic evolution. This work presents the geomorphic and lithologic aspects of the drainage basins in the Western Arabian Peninsula by analysing basin hypsometry and channel longitudinal profile steepness and concavity indices in order to understand the erosion regimes. A total of 36 drainage basins in the region were analysed in a geographic information system (GIS) environment with a 30-m ASTER Global Digital Elevation Model. Hypsometric curves display shapes resembling from S-shaped to concave curves. Hypsometric integral (HI) shows generally low values in the study area and varies between 0.13 and 0.5, with a mean of 0.27. From the main set of 36 drainage basins defined, three sets of sub-basins were derived for each Strahler order ranging from 4 to 6. Their HI varied between 0.08 and 0.66 with an average HI of 0.33. Then, the HI for each basin order was plotted against the distance from the central location of each basin from south to north. Results reveal that basin hypsometry is independent of spatial variation and spatial scale. Also no clear relations were found between HI and basin area and shape. Further, HI and hypsometric curves were analysed in terms of lithological control on landforms. Results indicate that basin hypsometry is sensitive to lithological variation in the study area. At the largest scale, the HI values can be divided into two populations. More evenly distributed erosion in crystalline rocks and relatively uneven erosion in volcanic rocks are suggested from the results. Channel longitudinal profile steepness and concavity indices provide the distribution of anomalously steep channels and also reflect variations in the locus and rate of differential erosion. High steepness and low concavity in a basin underlain by volcanic rocks and a reverse trend in crystalline rocks confirm the observation from the results of basin hypsometric analysis.

ASSESSMENT OF REFERENCE HEIGHT MODELS ON QUALITY OF TANDEM-X DEM

Abstract. The aim of this study is to investigate the effect of various Global Digital Elevation Models (GDEMs) in producing high-resolution topography model using TanDEM-X (TDX) Coregistered Single Look Slant Range Complex (CoSSC) images. We selected an image acquired on Jun 12th, 2012 over Doroud region in Lorestan, west of Iran and used 4 external digital elevation models in our processing including DLR/ASI X-SAR DEM (SRTM-X, 30m resolution), ASTER GDEM Version 2 (ASTER-GDEMV2, 30m resolution), NASA SRTM Version 4 (SRTM-V4, 90m resolution), and a local photogrammetry-based DEM prepared by National Cartographic Center (NCC DEM, 10m resolution) of Iran. InSAR procedure for DEM generation was repeated four times with each of the four external height references. The quality of each external DEM was initially assessed using ICESat filtered points. Then, the quality of, each TDX-based DEM was assessed using the more precise external DEM selected in the previous step. Results showed that both local (NCC) DEM and SRTM X-band performed the best (RMSE< 9m) for TDX-DEM generation. In contrast, ASTER GDEM v2 and SRTM C-band v4 showed poorer quality.

Earth observation data based rapid flood-extent modelling for tsunami-devastated coastal areas

Earth observation (EO)-based mapping and analysis of natural hazards plays a critical role in various aspects of post-disaster aid management. Spatial very high-resolution Earth observation data provide important information for managing post-tsunami activities on devastated land and monitoring re-cultivation and reconstruction. The automatic and fast use of high-resolution EO data for rapid mapping is, however, complicated by high spectral variability in densely populated urban areas and unpredictable textural and spectral land-surface changes. The present paper presents the results of the SENDAI project, which developed an automatic post-tsunami flood-extent modelling concept using RapidEye multispectral satellite data and ASTER Global Digital Elevation Model Version 2 (GDEM V2) data of the eastern coast of Japan (captured after the Tohoku earthquake). In this paper, the authors developed both a bathtub-modelling approach and a cost-distance approach, and integrated the roughness parameters of different land-use types to increase the accuracy of flood-extent modelling. Overall, the accuracy of the developed models reached 87–92%, depending on the analysed test site. The flood-modelling approach was explained and results were compared with published approaches. We came to the conclusion that the cost-factor-based approach reaches accuracy comparable to published results from hydrological modelling. However the proposed cost-factor approach is based on a much simpler dataset, which is available globally.

A morphometric comparison of the Namib and southwest Kalahari dunefields using ASTER GDEM data

The increased availability of digital elevation models and satellite image data enable testing of morphometric relationships between sand dune variables (dune height, spacing and equivalent sand thickness), which were originally established using limited field survey data. These long-established geomorphological hypotheses can now be tested against very much larger samples than were possible when available data were limited to what could be collected by field surveys alone. This project uses ASTER global digital elevation model (GDEM) data to compare morphometric relationships between sand dune variables in the southwest Kalahari dunefield to those of the Namib sand sea, to test whether the relationships found in an active sand sea (Namib) also hold for the fixed dune system of the nearby southwest Kalahari. The data show significant morphometric differences between the simple linear dunes of the Namib sand sea and the southwest Kalahari; the latter do not show the expected positive relationship between dune height and spacing. The southwest Kalahari dunes show a similar range of dune spacings, but they are less tall, on average, than the Namib sand sea dunes. There is a clear spatial pattern to these morphometric data; the tallest and most closely spaced dunes are towards the southeast of the Kalahari dunefield; and this is where the highest values of equivalent sand thickness result. We consider the possible reasons for the observed differences and highlight the need for more studies comparing sand seas and dunefields from different environmental settings.

Quantitative Morphometric Analysis of Bhadar River Basin, India using ASTER (GDEM) Data and GIS

The present study highlights the morphometric parameters of Bhadar River, located in state of Gujarat, India. In this study, ASTER Global Digital Elevation Model (GDEM) and Geographical Information System (GIS) have been taken to evaluate Linear and Areal aspects of different morphometric parameters using ArcGIS software. The study is mainly focused on morphometric analysis which revealed that the Bhadar River Basin is from first to seventh orders with dendritic type of drainage pattern. The results show that the drainage density of the Basin has been obtained low which indicates drainage texture is very coarse in nature. The result of Elongation ratio explore that the Basin is less elongated. Bifurcation ratio values of Bhadar River Basin have experience minimum structural disturbances.

Macro-Level Assessment of Seismically Induced Landslide Hazard for the State of Sikkim, India Based On GIS Technique

This paper presents a macro-level seismic landslide hazard assessment for the entire state of Sikkim, India, based on the Newmark's methodology. The slope map of Sikkim was derived from ASTER Global Digital Elevation Model (GDEM). Seismic shaking in terms of peak horizontal acceleration (PHA) at bedrock level was estimated from deterministic seismic hazard analysis (DSHA), considering point source model. Peak horizontal acceleration at the surface level for the study area was estimated based on nonlinear site amplification technique, considering B-type NEHRP site class. The PHA at surface was considered to induce driving forces on slopes, thus causing landslides. Knowing the surface level PHA and slope angle, the seismic landslide hazard assessment for each grid point was carried out using Newmark's analysis. The critical static factor of safety required to resist landslide for the PHA (obtained from deterministic analysis) was evaluated and its spatial variation throughout the study area is presented. For any slope in the study area, if the in-situ (available) static factor of safety is greater than the static factor of safety required to resist landslide as predicted in the present study, that slope is considered to be safe.

Glacial geomorphology of the Parlung Zangbo Valley, southeastern Tibetan Plateau

ABSTRACTWe present a glacial geomorphological map (1:825,000) of the Parlung Zangbo Valley in the southeastern Tibetan Plateau based on Google Earth imagery and the 30 m ASTER Global Digital Elevation Model (ASTER GDEM). The mapped region covers 2.9 × 104 km2, including abundant glacial landforms such as glacial valleys, marginal moraines (including terminal moraines and lateral moraines), and hummocky moraines. Glacial valleys are distributed mainly above 2100 m a.s.l. with lengths from 1 to 130 km. Multiple marginal moraines occur along the glacial valleys, indicating the presence of multiple glacial events. The lowest moraines are distributed mainly at the mouth of each valley between 2400 and 4000 m a.s.l. Hummocky moraines are mainly distributed in the two main tributary valleys: the Bodui Zangbo Valley and the Yigong Zangbo Valley. One ice-dammed paleolake was mapped with a surface area of 12.5 km2. The mapped glacial features (including contemporary glaciers) cover 1.2 × 104 km2, about 40% of the mapped area, representing the minimum extent of maximum glaciation. This map provides a useful data set for reconstructing the timing and extent of paleoglaciations in this area.

Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images

A large-area map of the spatial distribution of rice is important for grain yield estimations, water management and an understanding of the biogeochemical cycling of carbon and nitrogen. In this paper, we developed the Normalized Weighted Difference Water Index (NWDWI) for identifying the unique characteristics of rice during the flooding and transplanting period. With the aid of the ASTER Global Digital Elevation Model and the phenological data observed at agrometeorological stations, the spatial distributions of single cropping rice and double cropping early and late rice in the Yangtze River Delta region were generated using the NWDWI and time-series Enhanced Vegetation Index data derived from MODIS/Terra data during the 2000–2010 period. The accuracy of the MODIS-derived rice planting area was validated against agricultural census data at the county level. The spatial accuracy was also tested based on a land use map and Landsat ETM+ data. The decision coefficients for county-level early and late rice were 0.560 and 0.619, respectively. The MODIS-derived area of late rice exhibited higher consistency with the census data during the 2000–2010 period. The algorithm could detect and monitor rice fields with different cropping patterns at the same site and is useful for generating spatial datasets of rice on a regional scale.

The application of the Water Erosion Prediction Project (WEPP) model for the estimation of runoff and sediment on a monthly time resolution

The Water Erosion Prediction Project (WEPP) model is utilized to simulate the sediment and runoff processes. According to previous studies, WEPP model provides impressive results in watersheds of diverse climates and scales. It is also capable of modeling the sediment transportation processes and consequently predicting subsequent deposition sites. In this study, the geo-spatial interface for WEPP (GeoWEPP) was employed as a GIS framework to extract the data required from the ASTER Global Digital Elevation Model (ASTER-GDEM) dataset which was subsequently used as the model input. The case study was based on monthly data consisting of average sediment and runoff estimation from the Emameh sub-basin, in northern Iran. The model estimations were validated through field measurements. Two statistical measures of co-efficiency including the Nash–Sutcliffe Efficiency (NSE), and the coefficient of determination (R 2) were considered to evaluate how well the model predictions could explain the variability of observations in the field. The model performed favorably as corroborated by a reasonably high NSE of 0.99 and an R 2 value of 0.92 for sediment. In the case of runoff, the results were slightly inferior, but still acceptable with an NSE of 0.76 and R 2 value of 0.62.

Morphometric Characteristics and the Relation of Stream Orders to Hydraulic Parameters of River Goro: An Ephemeral River in Dire-dawa, Ethiopia

Major morphometric parameters of Goro watershed were derived from Aster Global Digital Elevation Model (GDEM) using ArcGIS10.1 extension, Arc Hydro Tool 2.0 in order to characterize it quantitatively. The study also assessed the relation of stream orders to selected channel hydraulic parameters (width, depth, channel bed slope, velocity and discharge) at bankfull flow condition. Channel geometry data and grain size samples collected from 14 representative cross-sections used as input to compute hydraulic parameters using equations appropriate for ungauged streams. The analysis of morphometric parameters indicate that pattern of stream networks is less controlled by structural condition though the area is situated in the rim of the great east African rift valley; and its geomorphic development is at late youth stage. Though hydraulic components of the channel do have a positive relation with stream orders, only channel cross-section area and discharge well related to stream orders (each increased at the rate of 0.86 and 1 on average with R 2 of 0.92 and 0.8 respectively with increasing in stream orders). However, depth, velocity and bed slope of the channel are less explained by stream order, which may indicate us these hydraulic parameters are rather affected by other local channel factors.

Implication of surface fractal analysis to evaluate the relative sensitivity of topography to active tectonics, Zagros Mountains, Iran

Fractal geometry is increasingly becoming a useful tool for modeling and quantifying the complex patterns of natural phenomena. The Earth's topography is one of these phenomena that have fractal characteristics. This paper investigates the relative sensitivity of topography to active tectonics using ASTER Global Digital Elevation Model. The covering divider method was used for direct extraction of surface fractal dimension (Dsurf) to estimate the roughness-surface of topography with aid of geographic information system (GIS) techniques. This evaluation let us highlight the role of the geomorphic and tectonic processes on the spatial variability of fractal properties of natural landforms. Geomorphic zones can be delineated using fractal dimension mapping in which variability of surface fractal dimension reflects the roughness of the landform surface and is a measure of topography texture. Obtained results showed this method can be a quick and easy way to assess the distribution of land surface deformation in different tectonic settings. The loose alluvial deposits and irregularities derived by tectonic activity have high fractal dimensions whereas the competent formations and higher wavelength folded surfaces have lower fractal dimensions. According to the obtained results, the Kazerun Fault Zone has a crucial role in the separation of the Zagros Mountain Ranges into the different lithological, geomorphological and structural zones.