The Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) is an active spaceborne remote sensing system that utilizes photon-counting LiDAR to capture highly detailed information about ...under-vegetation terrain and forest structure over vast spatial regions. It facilitates the accurate retrieval of terrain elevation and canopy height information, critical for assessing the global carbon budget and understanding the role of forests in climate change mitigation. However, challenges arise from the characteristics of the ICESat-2 photon-counting LiDAR data, such as their linear distribution, extensive spatial coverage, and substantial residual noise. These challenges hinder the performances of the state-of-the-art methods when applied on ICESat-2 data for extracting ground or top of canopy, while they perform well on airborne LiDAR that is featured with planar distribution, small coverage, and high signal-to-noise ratio. Consequently, this study proposes a novel algorithm termed Adaptive Linear Cloth Simulation Filtering (ALCSF), for the automated extraction of ground and top-of-canopy photons from ICESat-2 signal photons. The ALCSF algorithm innovatively introduces a cloth strip model as a reference to accommodate the distribution characteristics of ICESat-2 photons. Additionally, it employs a terrain-adaptive strategy to adjust the rigidity of the cloth strip by utilizing terrain slope information, thus making ALCSF applicable to large-scale areas with significant topographical changes. Furthermore, the proposed ALCSF addresses noise interference by simultaneously considering the movability of particles of the cloth strip model and the photon distribution during iterative adjustments of the cloth strip. The performance of the ALCSF is evaluated by comparing it with the ICESat-2 Land–Vegetation Along-Track Products (ATL08) across twelve datasets that encompass various times of day and scenes. In the results, the ALCSF exhibits notable improvements over ATL08 products, effectively reducing the root mean square error (RMSE) of ground elevation by 21.8% and canopy height by 25.8%, with superior performance in preserving terrain details. This highlights the significance of ALCSF as a valuable tool for enhancing the accuracy of ICESat-2 land and vegetation products, ultimately contributing to the estimation of the global carbon budget in future studies.
•Elevations are mapped by ICESat-2, Sentinel-1, and Sentinel-2 for the first time.•The proposed method exhibits high accuracy and resolution with different land covers.•Random forest can model the ...complex relationship of different remote sensing data.•A new method is provide for elevation estimation and updating at different scales.
Accurate mapping of terrain elevations at a large scale and fine resolution can characterize the detailed surface height and geomorphic changes and is very critical for the studies of the internal motions and external forces of the earth. The emergence of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) offers unprecedented possibilities for global elevation mapping with high vertical accuracy using three-dimensional photon points. However, the ICESat-2 photon points are still sparse in terms of spatial/horizontal resolution, making it unable to satisfy the high-resolution demand of terrain elevation mapping and digital elevation model production. A few previous studies have attempted to estimate elevations/topography in regions with single landscape and landcover (e.g., forest, shallow water, and polar regions) by combining ICESat-2 data with other passive satellite remotely sensed data. However, the potential and capability of ICESat-2 for mapping elevations for spatially continuous large regions with multiple complicated land cover types remains unknown. In this study, a spatially continuous large-scale terrain elevation estimation method is developed under multiple land covers based on the random forest model and the freely accessed satellite data of ICESat-2, Sentinel-1, and Sentinel-2. The core principle is to construct a random forest model that can characterize the complicated relationships of the ICESat-2 ATL03 terrain elevations and their corresponding land cover related polarization characteristics and spectral variables from Sentinel-1 and Sentinel-2, respectively. Integrating the superiorities of the data of these three different satellites enables the proposed method to extrapolate the terrain elevations with decimeter-level vertical accuracy and 10 m spatial/horizontal resolution simultaneously without any prior in situ data or manually set parameters. The proposed method is tested using the elevations from 2021 to 2022 at the third largest island (Chongming Island, Shanghai) in China. The estimated terrain elevations are locally validated with the airborne LiDAR-derived elevations. Moreover, they are compared with the ICESat-2 ATL08 height_terrain_bestfit data and Global Ecosystem Dynamics Investigation L2A elev_lowestmode data from the global perspectives. The predicted elevations exhibit a high correlation with the measured elevations from the two airborne LiDAR validation regions with root mean square errors (RMSE) of 0.34 and 0.59 m. The averaged RMSEs of the predicted elevations at different land covers are 1.26 and 1.18 m when compared with those derived from ATL08 and GEDI L2A, respectively. No remarkable abnormal predicted elevations are observed. This finding suggests the satisfactory robustness performance of the proposed method under different land covers and a relatively good consistency between the predicted elevations and the actual terrain of the entire island. As far as we know, the present work is the first to map elevations at 10 m resolution based only on the newly available satellite active and passive remotely sensed data without any ground truth surveys, manual intervention, and prior knowledge. Different with existing studies for terrain elevation mapping only at single landcovers, the proposed method demonstrates the capability and effectiveness of ICESat-2 for any landforms and landcovers and shows great potential for high-accuracy and high-resolution time-series terrain elevation estimation and updating at regional/national/global scales.
Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes ...in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo – at a site where 70‐m‐tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient‐depleted dip slopes – we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km2 of old‐growth forest. We found that subtle differences in elevation – which control soil chemistry and hydrology – profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape‐scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long‐standing ecological questions.
•An ICESat-2 vegetated terrain quality classification model with uncertainty measurement.•Extracted terrain can meet the different quality requirements with a high than 90% purity.•Suitable for the ...different vegetation cover areas including a high than 80% vegetation coverage Index.•With the potential for large-scale and even global-scale vegetated terrain applications.
The uncertainty of ICESat-2 terrain accuracy, especially in vegetated areas, limits its scientific application, and there is barely any comprehensive modeling evaluation for this uncertainty. In this study, we propose a terrain quality classification model with uncertainty measurement for extracting accurate vegetated terrain from ICESat-2 altimetry products, which includes two main parts: 1) training samples are used to construct a terrain elevation quality classification model; 2) the relationship between the vote entropy and elevation accuracy is analyzed to measure the uncertainty of the predicted results of the model. Compared with airborne LiDAR data from multiple areas of the world, it is confirmed that the extracted results can meet the different quality requirements for terrain elevation data in vegetated areas (95th percentile of the absolute error: 1 m, 2 m, and 3 m) with a higher than 90% purity (proportion of accurate terrain). The accuracy of the extracted results is ∼0.5–0.9 m, ∼0.9–1.3 m and ∼1.1–2.9 m, respectively, and that of the eliminated results is ∼1.2–3.8 m, ∼2.0–4.4 m and ∼3.4–5.8 m, respectively. The results also show that the method can extract high-accuracy terrain in high vegetation cover areas (where the tree cover index is higher than 80%), and has the potential of applying to large-scale and even global-scale vegetated terrain. Moreover, the method is also suitable for non-vegetated areas. The extracted results can meet the corresponding quality requirements for non-vegetated areas (root-mean-square error: 0.333 m, 0.667 m, and 1 m), and their purity is also high than 90%.
This paper addresses ground target tracking (GTT) for airborne radar. Digital terrain elevation data (DTED) are widely used for GTT as prior information under the premise that ground targets are ...constrained on terrain. Existing works fuse DTED to a tracking filter in a way that adopts only the assumption that the position of the target is constrained on the terrain. However, by kinematics, it is natural that the velocity of the moving ground target is constrained as well. Furthermore, DTED provides neither continuous nor accurate measurement of terrain elevation. To overcome such limitations, we propose a novel soft terrain constraint and a constraint-aided particle filter. To resolve the difficulties in applying the DTED to the GTT, first, we reconstruct the ground-truth terrain elevation using a Gaussian process and treat DTED as a noisy observation of it. Then, terrain constraint is formulated as joint soft constraints of position and velocity. Finally, we derive a Soft Terrain Constrained Particle Filter (STC-PF) that propagates particles while approximately satisfying the terrain constraint in the prediction step. In the numerical simulations, STC-PF outperforms the Smoothly Constrained Kalman Filter (SCKF) in terms of tracking performance because SCKF can only incorporate hard constraints.
The upcoming Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) mission will offer prospects for mapping and monitoring biomass and carbon of terrestrial ecosystems over large areas using photon ...counting LiDAR data. In this paper, we aim to develop a methodology to derive terrain elevation and vegetation canopy height from test-bed sensor data and further pre-validate the capacity of the mission to meet its science objectives for the ecosystem community. We investigated a novel methodological framework with two essential steps for characterizing terrain and canopy height using Multiple Altimeter Beam Experimental LiDAR (MABEL) data and simulated ICESat-2 data with various vegetation conditions. Our algorithm first implements a multi-level noise filtering approach to minimize noise photons and subsequently classifies the remaining photons into ground and top of canopy using an overlapping moving window method and cubic spline interpolation. Results of noise filtering show that the design of the multi-level filtering process is effective to identify background noise and preserve signal photons in the raw data. Moreover, calibration results using MABEL and simulated ICESat-2 data share similar trends with the retrieved terrain being more accurate than the retrieved canopy height, and the nighttime results being better than corresponding daytime results. Compared to the results of simulated ICESat-2 data, MABEL data achieve lower accuracy for ground and canopy heights in terms of root mean square error (RMSE), which may partly result from the inconsistency between MABEL and reference data. Specifically, simulated ICESat-2 data using 115 various nighttime and daytime scenarios, yield average RMSE values of 1.83 m and 2.80 m for estimated ground elevation, and 2.70 m and 3.59 m for estimated canopy height. Additionally, the accuracy assessment of percentile heights of simulated ICESat-2 data further substantiates the robustness of the methodology from different perspectives. The methodology developed in this study illustrates plausible ways of processing the data that are structurally similar to expected ICESat-2 data and holds the potential to be a benchmark for further method adjustment once genuine ICESat-2 are available.
•An adaptive methodological framework was developed to process upcoming ICESat-2 data.•Basic algorithms for ground and canopy photon classification with ICESat-2-like data.•Terrain and canopy height measurements with MABEL and simulated ICESat-2 data.
Accurate measurements of terrain elevation are crucial for many ecological applications. In this study, we sought to assess new global three-dimensional Earth observation data acquired by the ...spaceborne Light Detection and Ranging (LiDAR) missions Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI). For this, we examined the “ATLAS/ICESat-2 L3A Land and Vegetation Height”, version 5 (20 × 14 m and 100 × 14 m segments) and the “GEDI Level 2A Footprint Elevation and Height Metrics”, version 2 (25 m circle). We conducted our analysis across four land cover classes (bare soil, herbaceous, forest, savanna), and six forest types (temperate broad-leaved, temperate needle-leaved, temperate mixed, tropical upland, tropical floodplain, and tropical secondary forest). For assessment of terrain elevation estimates from spaceborne LiDAR data we used high resolution airborne data. Our results indicate that both LiDAR missions provide accurate terrain elevation estimates across different land cover classes and forest types with mean error less than 1 m, except in tropical forests. However, using a GEDI algorithm with a lower signal end threshold (e.g., algorithm 5) can improve the accuracy of terrain elevation estimates for tropical upland forests. Specific environmental parameters (terrain slope, canopy height and canopy cover) and sensor parameters (GEDI degrade flags, terrain estimation algorithm; ICESat-2 number of terrain photons, terrain uncertainty) can be applied to improve the accuracy of ICESat-2 and GEDI-based terrain estimates. Although the goodness-of-fit statistics from the two spaceborne LiDARs are not directly comparable since they possess different footprint sizes (100 × 14 m segment or 20 × 14 m segment vs. 25 m circle), we observed similar trends on the impact of terrain slope, canopy cover and canopy height for both sensors. Terrain slope strongly impacts the accuracy of both ICESat-2 and GEDI terrain elevation estimates for both forested and non-forested areas. In the case of GEDI the impact of slope is, however, partly caused by horizontal geolocation error. Moreover, dense canopies (i.e., canopy cover higher than 90%) affect the accuracy of spaceborne LiDAR terrain estimates, while canopy height does not, when considering samples over flat terrains. Our analysis of the accuracy and precision of current versions of spaceborne LiDAR products for different vegetation types and environmental conditions provides insights on parameter selection and estimated uncertainty to inform users of these key global datasets.
Display omitted
•ICESat-2 and GEDI terrain height products were validated for various land covers.•Mean error of both datasets is less than 1 m, except in tropical forests.•Terrain slope strongly impacts the accuracy of both products.•Over flat terrain, terrain height accuracy was impacted by dense canopy cover.•Our study provides insights on parameter selection and estimated uncertainty.
In this paper, we use the correlation between the average wind speed and the elevation above sea level to present a regression model for calculating the average wind speed and evaluating the wind ...potential in the southern region of Ecuador. After obtaining the regression model, an adjustment factor based on the topographic slope has been included, mainly since the wind speed could vary largely as it blows across the lower slope regions or intermediate hills of mountains. Once the wind speed was obtained, both at 10 m and 100 m, the wind power density was calculated, which includes the impact of wind speed and air density. Finally, the model accuracy was obtained by comparing other free access data sources including actual data from meteorological stations, using statistical parameters to quantify the error. According to the results obtained, we find that wind speed has a good correlation with the terrain elevation of the southern region of Ecuador. The simulated wind speed compared to the actual data has errors between 7.75% and 16.89%, which indicates that the model can predict with > 83% accuracy. In addition, both the root means square error and the standard deviations have around 1 m/s of error.
This study aims to evaluate the accuracy of a method proposed for passive localization of radar emitters around irregular terrains with a single receiver in Electronic Support Measures systems. ...Previously, the authors targeted only the theoretical development of the localization method. In fact, this could be a serious concern in practice since there is no evidence regarding its accuracy under the real data gathered from realistic scenarios. Therefore, an accurate ray-tracing algorithm is adapted to enable the implementation of the method in practice. Then, realistic scenarios are determined based on the geographic information system map generated to collect high-resolution digital terrain elevation data, as well as realistic localization problems for radar emitters. Next, simulations are performed to test the localization method. Thus, the performance of the method is verified for practical implementation in the electronic warfare context for the first time. Lastly, the performance bounds of the method are discussed.
Although essential for reconstructing hominin behaviour during the Early Palaeolithic, only a handful of Acheulean sites have been dated in the Eastern Sahara region. This is due to the scarcity of ...sites for this time period and the lack of datable material. However, recent excavations in the Atbara region (Sudan) have provided unique opportunities to analyse and date Acheulean stone tools. We report here on EDAR 7, part of a cluster of Acheulean and Middle Stone Age (MSA) sites that were recently discovered in the Eastern Desert Atbara River (EDAR) region, located in the Eastern Desert (Sudan) far from the Nile valley. At EDAR 7, a 3.5 metre sedimentary sequence was excavated, allowing an Acheulean assemblage to be investigated using a combination of sedimentology, stone tool studies and optically stimulated luminescence dating (OSL). The site has delivered a complete Acheulean knapping chaine opératoire, providing new information about the Saharan Acheulean. The EDAR 7 site is interpreted as a remnant of a campsite based on the co-occurrence of two reduction modes: one geared towards the production of Large Cutting Tools (LCTs), and the other based on the flaking of small debitage and production of flake tools. Particularly notable in the EDAR 7 assemblage is the abundance of cleavers, most of which display evidence of flake production. Implementation of giant Kombewa flakes was also observed. A geometric morphometric analysis of hand-axes was conducted to verify a possible Late Acheulean assemblage standardisation in the Nubian Sahara. In addition, the analysis of micro-traces and wear on the artefacts has provided information on the use history of the Acheulean stone tools. Sediment analyses and OSL dating show that the EDAR 7 sequence contains the oldest Acheulean encampment remains in the Eastern Sahara, dated to the MIS 11 or earlier. This confirms that Homo erectus occupied the EDAR region during Middle Pleistocene humid periods, and demonstrates that habitable corridors existed between the Ethiopian Highlands, the Nile and the Red Sea coast, allowing population dispersals across the continent and out of it.
PDF
