scholarly journals Estimating Terrain Slope from ICESat-2 Data in Forest Environments

2020 ◽  
Vol 12 (20) ◽  
pp. 3300
Author(s):  
Xiaoxiao Zhu ◽  
Sheng Nie ◽  
Cheng Wang ◽  
Xiaohuan Xi ◽  
Dong Li ◽  
...  
Keyword(s):  
Surface Topography ◽  
Ground Surface ◽  
The United States ◽  
Airborne Lidar ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Biophysical Parameters ◽  
Waveform Data ◽  
Terrain Slope ◽  
Slope Estimation

The global digital elevation measurement (DEM) products such as SRTM DEM and GDEM have been widely used for terrain slope retrieval in forests. However, the slope estimation accuracy is generally limited due to the DEMs’ low vertical accuracy over complex forest environments. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission shows excellent potential for slope estimation because of the high elevation accuracy and unique design of beam pairs. This study aimed to explore the possibility of ICESat-2 data for terrain slope retrieval in the United States forests. First, raw ICESat-2 data were processed to obtain accurate ground surfaces. Second, two different methods based on beam pairs were proposed to derive terrain slopes from the ground surfaces. Third, the estimated slopes were validated by airborne LiDAR-derived slopes and compared with SRTM-derived slopes and GDEM-derived slopes. Finally, we further explored the influence of surface topography and ground elevation error on slope estimation from ICESat-2 data. The results show that the ground surface can be accurately extracted from all scenarios of ICESat-2 data, even weak beams in the daytime, which provides the basis for terrain slope retrieval from ICESat-2 beam pairs. The estimated slope has a strong correlation with airborne LiDAR-derived slopes regardless of slope estimation methods, which demonstrates that the ICESat-2 data are appropriate for terrain slope estimation in complex forest environments. Compared with the method based on along- and across-track analysis (method 1), the method based on plane fitting of beam pairs (method 2) has a high estimation accuracy of terrain slopes, which indicates that method 2 is more suitable for slope estimation because it takes full advantage of more ground surface information. Additionally, the results also indicate that ICESat-2 performs much better than SRTM DEMs and GDEMs in estimating terrain slopes. Both ground elevation error and surface topography have a significant impact on terrain slope retrieval from ICESat-2 data, and ground surface extraction should be improved to ensure the accuracy of terrain slope retrieval over extremely complex environments. This study demonstrates for the first time that ICESat-2 has a strong capability in terrain slope retrieval. Additionally, this paper also provides effective solutions to accurately estimate terrain slopes from ICESat-2 data. The ICESat-2 slopes have many potential applications, including the generation of global slope products, the improvement of terrain slopes derived from the existing global DEM products, and the correction of vegetation biophysical parameters retrieved from space-borne LiDAR waveform data.

scholarly journals Application and Validation of a Model for Terrain Slope Estimation Using Space-Borne LiDAR Waveform Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1691 ◽  
Author(s):  
Xuebo Yang ◽  
Cheng Wang ◽  
Sheng Nie ◽  
Xiaohuan Xi ◽  
Zhenyue Hu ◽  
...  
Keyword(s):  
Surface Characteristics ◽  
Airborne Lidar ◽  
Estimation Accuracy ◽  
Estimation Model ◽  
Large Area ◽  
Waveform Data ◽  
Terrain Slope ◽  
Lidar Measurements ◽  
Slope Estimation ◽  
Study Sites

The terrain slope is one of the most important surface characteristics for quantifying the Earth surface processes. Space-borne LiDAR sensors have produced high-accuracy and large-area terrain measurement within the footprint. However, rigorous procedures are required to accurately estimate the terrain slope especially within the large footprint since the estimated slope is likely affected by footprint size, shape, orientation, and terrain aspect. Therefore, based on multiple available datasets, we explored the performance of a proposed terrain slope estimation model over several study sites and various footprint shapes. The terrain slopes were derived from the ICESAT/GLAS waveform data by the proposed method and five other methods in this study. Compared with five other methods, the proposed method considered the influence of footprint shape, orientation, and terrain aspect on the terrain slope estimation. Validation against the airborne LiDAR measurements showed that the proposed method performed better than five other methods (R2 = 0.829, increased by ~0.07, RMSE = 3.596°, reduced by ~0.6°, n = 858). In addition, more statistics indicated that the proposed method significantly improved the terrain slope estimation accuracy in high-relief region (RMSE = 5.180°, reduced by ~1.8°, n = 218) or in the footprint with a great eccentricity (RMSE = 3.421°, reduced by ~1.1°, n = 313). Therefore, from these experiments, we concluded that this terrain slope estimation approach was beneficial for different terrains and various footprint shapes in practice and the improvement of estimated accuracy was distinctly related with the terrain slope and footprint eccentricity.

scholarly journals WATER TURBIDITY ESTIMATION FROM LIDAR BATHYMETRY DATA BY FULL-WAVEFORM ANALYSIS – COMPARISON OF TWO APPROACHES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 681-688
Author(s):  
K. Richter ◽  
D. Mader ◽  
P. Westfeld ◽  
H.-G. Maas
Keyword(s):  
Measurement Data ◽  
Airborne Lidar ◽  
Waveform Analysis ◽  
Estimation Methods ◽  
Data Set ◽  
Water Turbidity ◽  
Waveform Data ◽  
Full Waveform ◽  
Novel Approach ◽  
Airborne Lidar Bathymetry

Abstract. Airborne LiDAR bathymetry is an efficient technique for surveying the bottom of shallow waters. In addition, the measurement data contain valuable information about the local turbidity conditions in the water body. The extraction of this information requires appropriate evaluation methods examining the decay of the recorded waveform signal. Existing approaches are based on several assumptions concerning the influence of the ALB system on the waveform signal, the extraction of the volume backscatter, and the directional independence of turbidity. The paper presents a novel approach that overcomes the existing limitations using two alternative turbidity estimation methods as well as different variants of further processed full-waveform data. For validation purposes, the approach was applied to a data set of a shallow inland water. The results of the quantitative evaluation show, which method and which data basis is best suited for the derivation of area wide water turbidity information.

Source depth estimation using multi-station waveform data

1984 ◽  
Vol 74 (5) ◽  
pp. 1623-1643
Author(s):  
Falguni Roy
Keyword(s):  
Depth Estimation ◽  
The United States ◽  
Digital Data ◽  
United States Geological Survey ◽  
Travel Times ◽  
Source Depth ◽  
Time Data ◽  
Waveform Data ◽  
Level Ii ◽  
Level I

Abstract A depth estimation procedure has been described which essentially attempts to identify depth phases by analyzing multi-station waveform data (hereafter called level II data) in various ways including deconvolution, prediction error filtering, and spectral analysis of the signals. In the absence of such observable phases, other methods based on S-P, ScS-P, and SKS-P travel times are tried to get an estimate of the source depth. The procedure was applied to waveform data collected from 31 globally distributed stations for the period between 1 and 15 October 1980. The digital data were analyzed at the temporary data center facilities of the National Defense Research Institute, Stockholm, Sweden. During this period, a total number of 162 events in the magnitude range 3.5 to 6.2 were defined by analyzing first arrival time data (hereafter called level I data) alone. For 120 of these events, it was possible to estimate depths using the present procedure. The applicability of the procedure was found to be 100 per cent for the events with mb > 4.8 and 88 per cent for the events with mb > 4. A comparison of level I depths and level II depths (the depths as obtained from level I and level II data, respectively) with that of the United States Geological Survey estimates indicated that it will be necessary to have at least one local station (Δ < 10°) among the level I data to obtain reasonable depth estimates from such data alone. Further, it has been shown that S wave travel times could be successfully utilized for the estimation of source depth.

scholarly journals Comparison of LAI Estimates from High Resolution Satellite Observations Using Different Biophysical Processors

2021 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Federico Filipponi
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Agricultural Land ◽  
Spectral Characteristics ◽  
Earth Observation ◽  
Estimation Accuracy ◽  
Landsat 8 ◽  
Biophysical Parameters ◽  
Area Index ◽  
Satellite Sensors

Earth observation provides timely and spatially explicit information about crop phenology and vegetation dynamics that can support decision making and sustainable agricultural land management. Vegetation spectral indices calculated from optical multispectral satellite sensors have been largely used to monitor vegetation status. In addition, techniques to retrieve biophysical parameters from satellite acquisitions, such as the Leaf Area Index (LAI), have allowed to assimilate Earth observation time series in numerical modeling for the analysis of several land surface processes related to agroecosystem dynamics. More recently, biophysical processors used to estimate biophysical parameters from satellite acquisitions have been calibrated for retrieval from sensors with different high spatial resolution and spectral characteristics. Virtual constellations of satellite sensors allow the generation of denser LAI time series, contributing to improve vegetation phenology estimation accuracy and, consequently, enhancing agroecosystems monitoring capacity. This research study compares LAI estimates over croplands using different biophysical processors from Sentinel-2 MSI and Landsat-8 OLI satellite sensors. The results are used to demonstrate the capacity of virtual satellite constellation to strengthen LAI time series to derive important cropland use information over large areas.

Discovering the Polaris Fault, Martis Creek Dam, Truckee, California

2018 ◽  
Vol 24 (1) ◽  
pp. 111-120
Author(s):  
Lewis E. Hunter ◽  
Ronn S. Rose ◽  
Bruce Hilton ◽  
William McCormick ◽  
Todd Crampton
Keyword(s):  
Flood Control ◽  
Late Quaternary ◽  
Ground Surface ◽  
Lake Tahoe ◽  
The United States ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Vegetation Canopy ◽  
History Of ◽  
Control Purpose

Abstract Martis Creek Dam, located in the Truckee Basin north of Lake Tahoe, CA, was initially rated as one of the U.S. Army Corps of Engineers’ highest risk dams in the United States. While the dam has performed its flood control purpose, a history of excessive seepage during even moderate reservoir levels has prevented it from also fulfilling its potential water storage function. During seepage and seismic studies to assess and mitigate deficiencies, high-resolution light detection and ranging (LiDAR) data were obtained. This imagery provides an unprecedented representation of the ground surface that allows evaluation of geomorphology even in areas with a dense vegetation canopy. At Martis Creek Dam, this geomorphic analysis resulted in the recognition of a previously unknown and through-going lineament between the spillway and dam embankment. This feature extends to the southeast, where several lineament splays are exposed on the East Martis Creek Fan. These lineaments were subsequently explored by paleo-seismic trenching at two locations and confirmed as faults with Late Quaternary to Holocene displacement. Faulting was confirmed in both trenches as unique splays of a fault zone with several feet of apparent normal (vertical) slip and an unknown magnitude, but a potentially significant, strike-slip component. Faulting was observed near the ground surface in both cases, and multiple fault events (a minimum of two) are interpreted as at least latest Pleistocene in age, and probably active in the Holocene.

scholarly journals Joint Use of PROSAIL and DART for Fast LUT Building: Application to Gap Fraction and Leaf Biochemistry Estimations over Sparse Oak Stands

2020 ◽  
Vol 12 (18) ◽  
pp. 2925
Author(s):  
Thomas Miraglio ◽  
Karine Adeline ◽  
Margarita Huesca ◽  
Susan Ustin ◽  
Xavier Briottet
Keyword(s):  
Mean Squared Error ◽  
Approximation Error ◽  
High Sensitivity ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Leaf Mass Per Area ◽  
Approximation Model ◽  
Equivalent Water Thickness ◽  
Gap Fraction ◽  
Chlorophylls A And B

Gap Fraction, leaf pigment contents (content of chlorophylls a and b (Cab) and carotenoids content (Car)), Leaf Mass per Area (LMA), and Equivalent Water Thickness (EWT) are considered relevant indicators of forests’ health status, influencing many biological and physical processes. Various methods exist to estimate these variables, often relying on the extensive use of Radiation Transfer Models (RTMs). While 3D RTMs are more realistic to model open canopies, their complexity leads to important computation times that limit the number of simulations that can be considered; 1D RTMs, although less realistic, are also less computationally expensive. We investigated the possibility to approximate the outputs of a 3D RTM (DART) from a 1D RTM (PROSAIL) to generate in very short time numerous extensive Look-Up Tables (LUTs). The intrinsic error of the approximation model was evaluated through comparison with DART reference values. The model was then used to generate LUTs used to estimate Gap Fraction, Cab, Car, EWT, and LMA of Blue Oak-dominant stands in a woodland savanna from AVIRIS-C data. Performances of the approximation model for estimation purposes compared to DART were evaluated using Wilmott’s index of agreement (dr), and estimation accuracy was measured with coefficients of determination (R2) and Root Mean Squared Error (RMSE). The low approximation error of the proposed model demonstrated that the model could be considered for canopy covers as low as 30%. Gap Fraction estimations presented similar performances with either DART or the approximation (dr 0.78 and 0.77, respectively), while Cab and Car showed improved performances (dr increasing from 0.65 to 0.77 and 0.34 to 0.65, respectively). No satisfying estimation methods were found for LMA and EWT using either models, probably due to the high sensitivity of the scene’s reflectance to Gap Fraction and soil modeling at such low LAI. Overall, estimations using the approximated reflectances presented either similar or improved accuracy. Our findings show that it is possible to approximate DART reflectances from PROSAIL using a minimal number of DART outputs for calibration purposes, drastically reducing computation times to generate reflectance databases: 300,000 entries could be generated in 1.5 h, compared to the 12,666 total CPU hours necessary to generate the 21,840 calibration entries with DART.

scholarly journals Modeling Wildland Firefighter Travel Rates by Terrain Slope: Results from GPS-Tracking of Type 1 Crew Movement

Fire ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 52
Author(s):  
Patrick R. Sullivan ◽  
Michael J. Campbell ◽  
Philip E. Dennison ◽  
Simon C. Brewer ◽  
Bret W. Butler
Keyword(s):  
Airborne Lidar ◽  
Gps Tracking ◽  
Escape Route ◽  
Terrain Slope ◽  
Precise Understanding ◽  
Rate Functions ◽  
Wildland Firefighting ◽  
Upper Third ◽  
Travel Rate

Escape routes keep firefighters safe by providing efficient evacuation pathways from the fire line to safety zones. Effectively utilizing escape routes requires a precise understanding of how much time it will take firefighters to traverse them. To improve this understanding, we collected GPS-tracked travel rate data from US Interagency Hotshot “Type 1” Crews during training in 2019. Firefighters were tracked while hiking, carrying standard loads (e.g., packs, tools, etc.) along trails with a precisely-measured terrain slope derived from airborne lidar. The effects of the slope on the instantaneous travel rate were assessed by three models generated using non-linear quantile regression, representing low (bottom third), moderate (middle third), and high (upper third) rates of travel, which were validated using k-fold cross-validation. The models peak at about a −3° (downhill) slope, similar to previous slope-dependent travel rate functions. The moderate firefighter travel rate model mostly predicts faster movement than previous slope-dependent travel rate functions, suggesting that firefighters generally move faster than non-firefighting personnel while hiking. Steepness was also found to have a smaller effect on firefighter travel rates than previously predicted. The travel rate functions produced by this study provide guidelines for firefighter escape route travel rates and allow for more accurate and flexible wildland firefighting safety planning.

scholarly journals SAR Observation Error Estimation Based on Maximum Relative Projection Matching

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Y. Zhang ◽  
B. P. Wang ◽  
Y. Fang ◽  
Z. X. Song
Keyword(s):  
Error Estimation ◽  
Estimation Method ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Reconstruction Method ◽  
Observation Error ◽  
Estimation Model ◽  
Reconstruction Process ◽  
Single Observation ◽  
Imaging Results

The existing sparse imaging observation error estimation methods are to usually estimate the error of each observation position by substituting the error parameters into the iterative reconstruction process, which has a huge calculation cost. In this paper, by analysing the relationship between imaging results of single-observation sampling data and error parameters, a SAR observation error estimation method based on maximum relative projection matching is proposed. First, the method estimates the precise position parameters of the reference position by the sparse reconstruction method of joint error parameters. Second, a relative error estimation model is constructed based on the maximum correlation of base-space projection. Finally, the accurate error parameters are estimated by the Broyden–Fletcher–Goldfarb–Shanno method. Simulation and measured data of microwave anechoic chambers show that, compared to the existing methods, the proposed method has higher estimation accuracy, lower noise sensitivity, and higher computational efficiency.

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