Shuttle Radar Topography Mission Digital Elevation Model Research Articles

Optimal Combination of Predictors and Algorithms for Forest Above-Ground Biomass Mapping from Sentinel and SRTM Data

Accurate forest above-ground biomass (AGB) mapping is crucial for sustaining forest management and carbon cycle tracking. The Shuttle Radar Topographic Mission (SRTM) and Sentinel satellite series offer opportunities for forest AGB monitoring. In this study, predictors filtered from 121 variables from Sentinel-1 synthetic aperture radar (SAR), Sentinal-2 multispectral instrument (MSI) and SRTM digital elevation model (DEM) data were composed into four groups and evaluated for their effectiveness in prediction of AGB. Five evaluated algorithms include linear regression such as stepwise regression (SWR) and geographically weighted regression (GWR); machine learning (ML) such as artificial neural network (ANN), support vector machine for regression (SVR), and random forest (RF). The results showed that the RF model used predictors from both the Sentinel series and SRTM DEM performed the best, based on the independent validation set. The RF model achieved accuracy with the mean error, mean absolute error, root mean square error, and correlation coefficient in 1.39, 25.48, 61.11 Mg·ha−1 and 0.9769, respectively. Texture characteristics, reflectance, vegetation indices, elevation, stream power index, topographic wetness index and surface roughness were recommended predictors for AGB prediction. Predictor variables were more important than algorithms for improving the accuracy of AGB estimates. The study demonstrated encouraging results in the optimal combination of predictors and algorithms for forest AGB mapping, using openly accessible and fine-resolution data based on RF algorithms.

On-Orbit Geometric Calibration and Validation of Luojia 1-01 Night-Light Satellite

The Luojia 1-01 Satellite (LJ1-01) is the first professional night-light remote-sensing satellite in China, and thus, it is of pioneering significance for the development of night-light remote sensing satellites in China and the application of remote sensing in the social and economic fields. To ensure the application of night-light remote-sensing data, several studies concerning on-orbit geometric calibration and accuracy verification have been carried out for the complementary metal oxide semiconductor (CMOS) rolling shutter camera of LJ1-01 since the launch of the satellite. Owing to the lack of high-precision nightlight geometric reference at home and abroad, it is difficult to directly calibrate the nighttime light image of LJ1-01. Based on the principle of rolling shutter dynamic imaging, a rigorous geometric imaging model of the time-sharing exposure of the rolling shutter of LJ1-01 is established, and a geometric calibration method for daytime imaging calibration and compensated nighttime light data is proposed. The global public Landsat digital orthophoto image (DOM) with a 15-m resolution and 90-m Shuttle Radar Topography Mission digital elevation model (SRTM-DEM) are used as control data. The images obtained in England, Venezuela, Caracas, Damascus, and Torreon (Mexico) were selected as experimental data. The on-orbit calibration and accuracy verification of LJ1-01 were carried out. Experiments show that after on-orbit geometric calibration, the daytime calibration parameters can effectively compensate for the systematic errors of night-light images. After compensation, the positioning accuracy of night-light images without geometric control points (GCPs) is improved from nearly 20 km to less than 0.65 km. The internal accuracy of the calibrated night-light images is better than 0.3 pixels, which satisfies the requirement of subsequent applications.

Improved Priority‐Flood method for depression filling by redundant calculation optimization in local micro‐relief areas

AbstractDepression filling is a critical step in distributed hydrological modeling using digital elevation models (DEMs). The traditional Priority‐Flood (PF) approach is widely used due to its relatively high efficiency when dealing with a small‐sized DEM. However, it seems inadequate and inefficient when dealing with large high‐resolution DEMs. In this work, we examined the relationship between the PF algorithm calculation process and the topographical characteristics of depressions, and found significant redundant calculations in the local micro‐relief areas in the conventional PF algorithm. As such calculations require more time when dealing with large DEMs, we thus propose a new variant of the PF algorithm, wherein redundant points and calculations are recognized and eliminated based on the local micro‐relief water‐flow characteristics of the depression‐filling process. In addition, depressions and flatlands were optimally processed by a quick queue to improve the efficiency of the process. The proposed method was applied and validated in eight case areas using the Shuttle Radar Topography Mission digital elevation model (SRTM‐DEM) with 1 arc‐second resolution. These selected areas have different data sizes. A comparative analysis among the proposed method, the Wang and Liu‐based PF, the improved Barnes‐based PF, the improved Zhou‐based PF, and the Planchon and Darboux (P&D) algorithms was conducted to evaluate the accuracy and efficiency of the proposed algorithm. The results showed that the proposed algorithm is 43.2% (maximum) faster than Wang and Liu's variant of the PF method, with an average of 31.8%. In addition, the proposed algorithm achieved similar performance to the improved Zhou‐based PF algorithm, though our algorithm has the advantage of being simpler. The optimal strategies using the proposed algorithm can be employed in various landforms with high efficiency. The proposed method can also achieve good depression filling, even with large amounts of DEM data.

Evaluation and spatial distribution characteristics of freeze-thaw erosion intensity in the Yalu Tsangpo River basin on the basis of geographic information system

Freeze-thaw erosion is one of the main ways of soil erosion in three major erosion types, which are related to the development of regional economy and the protection of ecological environment. Therefore, its research is particularly important. This paper uses the Yalu Tsangpo River basin as the research area. The range of the freeze-thaw erosion area in the Yalu Tsangpo River basin was defined by using Shuttle Radar Topography Mission-Digital Elevation Model (STRM-DEM) data. Six factors, namely, annual temperature difference, annual precipitation, slope, aspect, vegetation coverage, and elevation, were selected as the evaluation indexes of the intensity of freeze-thaw erosion. Analytic hierarchy process (AHP) was used to determine the weight of each factor. A comprehensive evaluation index model was employed to obtain the range of freeze-thaw erosion intensity. The natural breaks method in ArcGIS was applied to grade the result. The classification chart of the freeze-thaw erosion intensity of the Yalu Tsangpo River basin was drawn to show the distribution of freeze-thaw erosion. Results showed that (1) the total area of freeze-thaw erosion in the Yalu Tsangpo River basin is 229,231.80 km2, which accounts for 93.5% of the total area of the Yalu Tsangpo River basin, with mild erosion and moderate erosion. (2) The distribution of freeze-thaw erosion intensity in spatial pattern is obvious; from west to east, the intensity of freeze-thaw erosion increases gradually. Severe erosion is mainly concentrated in the northeast and northern regions of the Yalu Tsangpo River basin. (3) The areas of freeze-thaw erosion are mainly distributed in the temperature zone with the annual temperature range of ≥40 °C, accounting for 86.4% of the total freeze-thaw erosion area. The freeze-thaw erosion area is mainly distributed in the slope ≥15° slope zone, which accounts for 62% of the total freeze-thaw erosion area, and has a severe effect on moderate erosion and severe erosion in this slope zone. Freeze-thaw erosion areas are mainly concentrated in vegetation belts with vegetation coverage less than 20%, accounting for 63.8% of the total freeze-thaw erosion area. With the increase in vegetation coverage, the proportion of freeze-thaw erosion area decreased. The freeze-thaw erosion area was mainly concentrated on the altitude zone of ≥4000 m, which accounted for 84.3% of the total freeze-thaw erosion area. Thus, the freeze-thaw erosion area increased with altitude.

Evaluation of TanDEMx and SRTM DEM on watershed simulated runoff estimation

In hydrological models, digital elevation models (DEMs) are being used to extract stream network and delineation of the watershed. DEMs represent elevation surfaces of earth landscape. Spatial resolution refers to the dimension of the cell size representing the area covered on the ground. Spatial resolution is the main parameter of a DEM. The grid cell size of raster DEM has significant effects on derived terrain variables such as slope, aspect, curvature, the wetness index, etc. Selection of appropriate spatial resolution DEM depends on other input data being used in the model, type of application and analysis that needs to be performed, the size of the database and response time. Each DEM contains inherent errors due to the method of acquisition and processing. The accuracy of each DEM varies with spatial resolution. The present paper deals with Shuttle Radar Topography Mission (SRTM), TerraSAR-X add-on for Digital Elevation Measurements (TanDEM DEMs) and compares their watershed delineation, slope, stream network and height with ground control points. It was found that the coarse resolution DEM-derived attributes and terrain morphological characteristics were strongly influenced by DEM accuracy. The objective of the present study is to investigate the impact of DEM resolution on topographic parameters and runoff estimation using TanDEM-12, TanDEM-30 and SRTM-90 m with the Soil and Water Assessment Tool. The analysis of the results using different DEM resolutions gave a varied number of sub-basins, Hydrological Response Units (HRUs) and watershed areas. The results were optimum at a specific threshold value as extraction of drainage network has a significant influence on simulated results. The accuracy of DEM is important, as the source of construction of DEM is the main factor causing uncertainty in the output. The results showed variable amounts of runoff at the watershed level, which may be attributed to varied stream lengths, minimum and maximum elevations and sub-basin areas.

INTEGRATED FLOOD STUDY OF BAGMATI RIVER BASIN WITH HYDRO PROCESSING, FLOOD INUNDATION MAPPING & 1-D HYDRODYNAMIC MODELING USING REMOTE SENSING AND GIS

Abstract. Flood is one of the most the most re-occurring natural hazard in the state of Bihar, as well as in India. The major rivers responsible for flood in the state of Bihar are Kosi, Gandak, Ghagra and Bagmati, which are the tributary rivers of Ganges. The head water catchment area of these rivers lies in the Himalayan state of Nepal. The high rainfall in Nepal, siltation of hydraulic structures, rivers and low topography of North Bihar causes flood occurrence in these areas on regular basis. Remote sensing and GIS plays an important role in mapping, monitoring and providing spatial database for all flood related studies. The present work focuses on the use remote sensing based topography and images in GIS environment for integrated flood study of Bagmati River, which is one of the most flood prone rivers of North Bihar. The Digital Elevation Model (DEM) from shuttle radar topography mission (SRTM) was used to create detailed sub-basin and river network map of entire Bagmati basin. The floods of July–August 2002 were mapped using RADARSAT-1 data using threshold based method. The SRTM DEM and ground based river cross-section from Dheng to Benibad stretch of Bhagmati River were used to create 1-dimensional hydrodynamic (1-D HD) model for simulating flood water level, discharge and flood inundation. Validation of simulated flood flows was done using observed water level of central water commission (CWC) from Dheng to Runisaidpur stations, with coefficient of correlation of 0.85. Finally, an integrated framework for flood modelling and management system is proposed.

The role of pre-existing Precambrian structures in the development of Rukwa Rift Basin, southwest Tanzania

In this study, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) and aeromagnetic data are used to analyse the trends of pre-existing basement structures within the Rukwa Rift Basin. The NW-trending Rukwa Rift Basin on the western branch of the East African Rift System, southwest Tanzania, is developing on the NW-trending Paleoproterozoic Ubendian orogenic belt, a belt that experienced multiple orogenic collisions associated with subduction in Proterozoic time and comprises several distinct terranes bounded by faults or shear zones. The results obtained using magnetic edge enhancement (derivatives) methods highlight major magnetic domains identified based on their distinctive magnetic patterns in relation to geology and tectonic setting of the studied area. The results also highlight the Precambrian Chisi shear zone which trends in a NW-SE direction in the subsurface, below the Lake Beds Formation sedimentary succession of the Neogene Rukwa Rift Basin. The orientation of rift border faults and other major faults and their relationship with basement fabrics inferred from SRTM DEM and magnetic data trend mainly NW-SE, which is consistent with those of the NW-trending Paleoproterozoic Ubendian orogenic belt. Thus, Paleoproterozoic Ubendian orogenic belt structures have played a significant role on geometry and orientation of the Rukwa Rift Basin. These structures facilitated strain localisation within the border faults of the rift basin by exploiting the existence of inherited lithospheric heterogeneity. It can be concluded that the pre-existing faults and shear zones define a mechanical anisotropy in the basement of the Rukwa Rift Basin and facilitated the strain localisation within the border faults of the rift.

Anomalous Glacier Changes in the Southeast of Tuomuer‐Khan Tengri Mountain Ranges, Central Tianshan

AbstractCentral Tianshan (CTS) plays a prominent role in maintaining the vulnerable ecosystem in Central Asia. Rivers originating from it have high proportions of the runoffs contributed by glacier meltwater. In this study, the glacier mass balance in the catchments of Muzart and Karayulun rivers, CTS, was estimated by a geodetic method based on Advanced Land Observing Satellite/Panchromatic Remote‐sensing Instrument for Stereo Mapping images and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). The results revealed that at the west and east glacial centers in the study area, the 2000–2011 mass loss rates were −0.03 ± 0.17 and −0.06 ± 0.17 m w.e./a, respectively, considerably lower than other CTS zones. In order to ascertain this stable glacier state, we also performed a geodetic measurement based on TerraSAR‐X add‐on for Digital Elevation Measurement (TanDEM‐X) images and SRTM DEM (2000–2012), and the results are similar (0.01 ± 0.17 and −0.04 ± 0.17 m w.e./a, respectively). The glacier thickness change around the regional snowline was close to zero. The strong capability of cold storage and the temperature drop in the early 21st century may account for the anomalous mass changes. Despite slight overall mass changes, obvious thinning was observed on many exposed glacier feet. This study indicates that the glacier melting can be effectively controlled if the rising trend of temperatures is reversed; furthermore, the land surface hydrological model should be calibrated with geodetic glacier mass balance measurement when it is used to simulate the streamflow trend in the headwater basin.

InSAR Baseline Estimation for Gaofen-3 Real-Time DEM Generation.

For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affects the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination results in a large baseline error, leads to a modulation error in azimuth and a slope error in the range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a novel baseline estimation approach based on Shuttle Radar Topography Mission (SRTM) DEM is proposed in this paper. Firstly, the orbit fitting is executed to remove the non-linear error factor, which is different from traditional methods. Secondly, the height errors are obtained in a slant-range plane between SRTM DEM and the GF-3 generated DEM, which can be used to estimate the baseline error with a linear variation. Then, the real-time orbit can be calibrated by the baseline error. Finally, the DEM generation is performed by using the modified baseline and orbit. This approach has the merit of spatial and precise orbital free ability. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively.

On the use of global DEMs in ecological modelling and the accuracy of new bare-earth DEMs

It is now widely acknowledged that the increasing availability of remotely sensed data facilitates ecological modelling. Digital elevation models (DEMs) are arguably one of the most common remote sensing products used in this context. Topographic indices (e.g. slope, orientation, rugosity) derived from DEMs are widely used as surrogates for field-measured environmental variables. Available global DEMs, such as those from the shuttle radar topography mission (SRTM), however, do not provide information on bare-earth elevation as they measure elevation of the highest objects above the ground (e.g. canopy). This affects the derived topographic indices and limits the use of global DEMs in ecological modelling. Unfortunately, most ecological studies ignore this limitation despite the fact that methods to remove the vegetation offset have been developed. We used high resolution LiDAR DTM to assess the accuracy of two newly available global bare-earth DEMs where such methods were applied and to compare them with the SRTM DEM. Furthermore, we assessed the effect of DEMs’ vertical error on species distribution models (SDMs) by calculating slope and topographic wetness index (TWI) from these different models and evaluating their suitability for SDMs by adopting a virtual species approach. We simulated virtual species based on slope and TWI derived from accurate LiDAR DTM at three resolutions (30 m, 90 m and 900 m) and developed univariate generalized models to assess the performance of the bare-earth and SRTM DEMs. Our results show that the vertical error in both newly available, vegetation-corrected global DEMs is indeed successfully reduced. The overall vertical root mean squared error (RMSE) was 10.52 m for SRTM, while it was 6.80 m and 6.25 m for the two global bare-earth DEMs. The effect of the vertical error on SDMs was most significant at finer spatial resolutions. Using SRTM DEM, as opposed to a more accurate bare-earth DEM, led to a decline in area under curve (AUC) values from 0.94 to 0.77. SDMs fitted with slope and TWI derived from new global bare-earth DTMs performed slightly better than SRTM. Since methods for vegetation-offset removal in DEMs exist and corrected DEMs are freely available, we argue that the vertical accuracy of DEMs should be more consistently considered. Local, high-accuracy DEMs should be used where available; in remaining instances, however, global DEMs where vertical bias was minimized should be used in ecological modelling. Further improvement of global DEMs at 30 m and better resolutions are needed to enhance accuracy of derived indices and ecological models.

STUDY ON SITE CONDITIONS BASED ON TOPOGRAPHIC SLOPE

Abstract. The travel-time averaged shear-wave velocity to a depth of 30m (Vs30) below the Earth’s surface is widely used to classify sites in many building codes. Vs30 is also used to estimate site classification in recent ground-motion prediction equations (GMPEs), and the distribution of Vs30 has been mapped in a region or country. An alternative method has recently been proposed for evaluating global seismic site conditions or Vs30, from the SRTM (Shuttle Radar Topography Mission) DEMs (digital elevation models). The basic premise of the method is that the topographic slope can be used as a reliable proxy for Vs30 in the absence of geologically and geotechnically based site-condition maps through correlations between Vs30 measurements and topographic gradient. Here, we use different resolutions (3 arcsec, 30 arcsec) DEM data to get Vs30 data separately, analyze and compare the difference of Vs30 data and site conditions obtained from different resolution DEM data. Shandong Province in eastern China and Sichuan Province in Western China are studied respectively. It is found that the higher resolution data is better at defining spatial topographic features than the 30c data, but less improvement in its correlation with Vs30.

Brief communication: Unabated wastage of the Juneau and Stikine icefields (southeast Alaska) in the early 21st century

Abstract. The large Juneau and Stikine icefields (Alaska) lost mass rapidly in the second part of the 20th century. Laser altimetry, gravimetry and field measurements suggest continuing mass loss in the early 21st century. However, two recent studies based on time series of Shuttle Radar Topographic Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation models (DEMs) indicate a slowdown in mass loss after 2000. Here, the ASTER-based geodetic mass balances are recalculated carefully avoiding the use of the SRTM DEM because of the unknown penetration depth of the C-band radar signal. We find strongly negative mass balances from 2000 to 2016 (−0.68 ± 0.15 m w.e. a−1 for the Juneau Icefield and −0.83 ± 0.12 m w.e. a−1 for the Stikine Icefield), in agreement with laser altimetry, confirming that mass losses are continuing at unabated rates for both icefields. The SRTM DEM should be avoided or used very cautiously to estimate glacier volume change, especially in the North Hemisphere and over timescales of less than ∼ 20 years.

A method for combining SRTM DEM and ASTER GDEM2 to improve topography estimation in regions without reference data

Digital Elevation Models (DEMs) such as Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Models (ASTER GDEM), or Shuttle Radar Topography Mission DEM (SRTM) are widely used in remote areas and non-industrial countries because of their availability rather than their accuracy. Although a global DEM can be considerably enhanced using additional reference information such as higher resolution DEMs or ground truth points, improving accuracy in areas without reference data remains a challenge. This paper develops an approach to improve the accuracy of the estimated topography by combining two complementary DEMs (ASTER GDEM 1 arc-second and SRTM DEM 1 arc-second) in regions missing reference data. The combination approach is based on formulating relationships between slopes and weights in sites with reference data. Then the developed relationships are applied to sites with similar geomorphology to determine the combination weight for each DEM without using reference data. The results indicate that combined DEMs offer significant improvements of 47% and 20% in mean bias over a mountainous site, and 16% and 58% at a low-relief site when compared with the SRTM and ASTER GDEM products, respectively. DEM-derived drainages were also found to be more accurate for the combined DEMs than the near-global DEMs in areas where reference data is not available.

Glacier mass balance in the Qinghai–Tibet Plateau and its surroundings from the mid-1970s to 2000 based on Hexagon KH-9 and SRTM DEMs

In the context of global warming, glacier changes in the Qinghai–Tibet Plateau (QTP) and its surroundings have attracted a great amount of public attention. To date, there have been many studies of glacier mass balance across the QTP. However, given that most of the previous studies have focused on a short observation period (2000–2015), and that long-term mass change measurements are available only for some local regions, we utilized declassified KH-9 images and 1 arc-second Shuttle Radar Topography Mission (SRTM) digital elevation models (DEMs) to provide the region-wide mass balance (from the mid-1970s to 2000) for a larger scale (including 11 sample regions) across the QTP and its surroundings. The final results indicate that the glaciers in the northwest of the QTP have shown a less negative or near-zero mass balance, ranging from −0.11 ± 0.13 m w.e. a−1 to 0.02 ± 0.10 m w.e. a−1, compared to those in the southeast part, with a mass balance range of −0.30 ± 0.12 m w.e. a−1 to −0.11 ± 0.14 m w.e. a−1. The most serious mass loss has emerged in the central-eastern Himalaya. Integrating our results with the observations after 2000 suggests that, over the past four decades (mid-1970s to the mid-2010s), the glaciers in the Himalaya, Nyainqêntanglha, and Tanggula mountains, as a whole, have exhibited accelerated mass loss, and the most significant acceleration has occurred in the eastern Nyainqêntanglha. Moreover, the Hindu Raj glaciers have shown a stable rate of continuous mass loss, while a nearly stable or slight mass gain state in the western Kunlun region can be dated back to at least as far as the mid-1970s.

Physical evolution of the Three Gorges Reservoir using advanced SVM on Landsat images and SRTM DEM data.

The Three Gorges Reservoir (TGR) is one of the largest hydropower reservoirs in the world. However, changes of the important physical characteristics of the reservoir covering pre-, during-, and post- dam have not been well studied. This study analyzed the lengths and water surface areas of the TGR using advanced support vector machine method (SVM) combined Landsat images with the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), which showed an increasing trend of lengths and surface areas with variable growth rates from pre-dam period to post-dam period. The highest water level (ca. 171.5m) was reported in 1st Jan, 2015, with the longest length of 687.8km and largest water surface area of 1106.2km2 during the study period. The lowest increasing magnitude of the reservoir length occurred in the first stage (2000-2005) but with the fastest magnitude of water surface area increase. The third stage (2010-2015) showed highest increase magnitude of length and lowest increase magnitude of water surface area. Meanwhile, the increased reservoir areas were mainly from cultivated land, forest land, and building land, with the biggest increase rate of cultivated land regardless of periods. Specifically, cultivated land contributed 39.1-46.0% to increased reservoir water area; the proportions were 22.6-29.6%, 22.1-24.1%, and 5.6-9.4% for forest, building land, and grassland, respectively. The study provides important data for the TGR physical evolution in the Holocene.

Mapping boreal forest biomass from a SRTM and TanDEM-X based on canopy height model and Landsat spectral indices

We propose a method for mapping above-ground biomass (AGB) (Mg ha−1) in boreal forests based predominantly on Landsat 8 images and on canopy height models (CHM) generated using interferometric synthetic aperture radar (InSAR) from the Shuttle Radar Topographic Mission (SRTM) and the TanDEM-X mission. The original SRTM digital elevation model (DEM) was corrected by modelling the respective effects of landform and land cover on its errors and then subtracted from a TanDEM-X DSM to produce a SAR CHM. Among all the landform factors, the terrain curvature had the largest effect on SRTM elevation errors, with a r2 of 0.29. The NDSI was the best predictor of the residual SRTM land cover error, with a r2 of 0.30. The final SAR CHM had a RMSE of 2.45 m, with a bias of 0.07 m, compared to a lidar-based CHM. An AGB prediction model was developed based on a combination of the SAR CHM, TanDEM-X coherence, Landsat 8 NDVI, and other vegetation indices of RVI, DVI, GRVI, EVI, LAI, GNDVI, SAVI, GVI, Brightness, Greenness, and Wetness. The best results were obtained using a Random forest regression algorithm, at the stand level, yielding a RMSE of 26 Mg ha−1 (34% of average biomass), with a r2 of 0.62. This method has the potential of creating spatially continuous biomass maps over entire biomes using only spaceborne sensors and requiring only low-intensity calibration.

SRTM‐assisted block adjustment for stereo pushbroom imagery

AbstractThis paper proposes a stereo‐image block‐adjustment algorithm without ground control points (GCPs) by adopting a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) as a height assistant. Using dense, evenly distributed tie points on images used in the block adjustment, the initial height values of tie points are derived directly from the SRTM DEM. In the subsequent block‐adjustment iterative computation, the height correction value for tie points is rigorously restricted by the SRTM DEM elevation. A total of 509 ZY‐3 satellite stereo‐images across 190 000 km2 of China's Hubei Province were used for this block‐adjustment experiment. The results show that the vertical root mean square errors (RMSEs) are improved from 7·2 to 2·3 m without GCPs, while the RMSEs in flat and mountainous terrain are improved to 1·5 and 2·8 m, respectively, fulfilling the vertical accuracy requirement of China's 1:25 000 scale mapping.

A global corrected SRTM DEM product for vegetated areas

ABSTRACTIt has been found that the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is systematically higher than the actual land surface in vegetated areas. This study developed a new globally corrected SRTM DEM through reducing its systematic bias in vegetated areas. Over 150, 000 km2 airborne light detection and ranging (LiDAR) data along with spaceborne LiDAR, global canopy height data, global canopy cover data and global land cover data were collected to correct the SRTM DEM. A linear regression based method was used to estimate the original SRTM DEM error and therefore correct the SRTM DEM data. The results show that the original SRTM DEM data is around 6 m higher than the actual land surfaces on average across all vegetation types. Our corrected SRTM DEM data can significantly reduce the significant bias to near zero, and can also reduce the root-mean-square error by 1 m.

Assessment of environmental impact of solid waste dumpsites using remote sensing

This study presents a remote sensing approach of using freely available Landsat 8 satellite Indicators ( Land Surface Temperature ( LST ), Soil Adjusted Vegetation Index ( SAVI )) and Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) geospatial data to assess the impact of dumpsites on the environment in Benin City, Nigeria. The finding reveals that the average derived LST at the dumpsites were higher than the immediate surrounding, and the average SAVI values were lower than the immediate surrounding. The high values of LST at the dumpsites depict the effect of gases released because of decomposition activities, while low values of SAVI indicate vegetation response to soil and ground water contamination due to leachate infiltration. The average elevation within the dumpsite area derived from SRTM DEM was also applied as a proxy to estimate disposed waste quantity, and related closely with LST that depict biodegradation activities. The result presented here shows that bacterial and fungal counts correlate strongly with the LST and SAVI values at each of the dumpsites R 2 : LST vs Bacteria Count = 0.982, LST vs Fungi Count = 0.951; SAVI vs Bacteria Count = 0.745, SAVI vs Fungi Count = 0.664, thereby suggesting remote sensing can be applied to aid longterm dumpsite monitoring and management. http://dx.doi.org/10.4314/njt.v37i1.36

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture, groundwater, and digital elevation data

AbstractInadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.