scholarly journals The scale levels identification for the plowland topography organization

2019 ◽  
pp. 3-21
Author(s):  
N. V. Minayev ◽  
A. A. Nikitin ◽  
D. N. Kozlov
Keyword(s):  
Soil Properties ◽  
Land Surface ◽  
Large Scale ◽  
Spatial Organization ◽  
Soil Cover ◽  
Soil Mapping ◽  
Fourier Decomposition ◽  
Digital Elevation ◽  
Scale Levels ◽  
Elevation Model

The identification of factor and indicational features, which are characterized by the high informativity and field of view in relation to the soil cover organization, plays a very important role in the soil mapping. Such characteristics are more common for Unmanned Aerial Vehicles (UAV), which include spectrazonal imagery and digital elevation model (DEM) with ultrahigh spatial resolution, necessary for obtaining fine and large scale images. However, the agrogenic micro- and nanotopography is considered as a noise during the studies of the soil cover topographic differentiation under the conditions of plowland, as the genetic soil properties correlate with natural micro- and mesotopography. A filtration algorithm for the land surface roughness, which is not related to the spatial organization of the objective soil properties, is suggested in the paper. The stages of linear dimension identification for self-similar structures of the glacial and agrogenic topography based on two-dimensional Fourier decomposition are demonstrated using the example of a field topography digital model for the area of 125 hectares. Filtering in the frequency domain allowed restoring the natural field topography and substantiating the effective resolution of the DEM and the size of the area to calculate local morphometric specificities of the topography for digital soil mapping.

scholarly journals The use of morphometric indicators of the relief for soil mapping of around plants in the conditions of the middle taiga in the northern part of the Perm region

2021 ◽  
Vol 27 (4) ◽  
pp. 162-174
Author(s):  
Aleksey Chashchin ◽  
Iraida Samofalova ◽  
Natalya Mudrykh
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Agricultural Land ◽  
Soil Cover ◽  
Soil Mapping ◽  
Soil Map ◽  
Digital Elevation ◽  
Relief Elements ◽  
Elevation Model ◽  
Perm Region

The digital elevation model (DEM) matrix allows to reveal the relationship of the soil cover with morphometric parameters. Therefore, in the absence of the possibility of a large-scale field survey of soils, for territories with a high degree of erosion hazard, the data on the relief make it possible to carry out predictive large-scale soil maps. The aim of the work is to create a cartographic model of the soil cover of agricultural land based on the extrapolation of the results of DEM processing and to compare it with the existing large-scale soil map in similar natural conditions. The object of research is the territory of LLC “Selskoe” located in the Solikamsk urban district of the Perm region. Agricultural land use belongs to the northernmost agricultural lands in the region. The total area of research was 429 hectares of arable land. The plot includes 8 fields. For soil mapping, a digital elevation model ALOS 30 and a large-scale soil map of the key site were used, which characterizes part of the land use of the subsidiary farm “Voskhod”. Using the results of the classification of the relief according to the GIS SAGA TPI based landform classification algorithm as a contour base and the existing soil map of the key site, a soil map of LLC “Selskoe” was made by the extrapolation method. The steepness of the slopes and the topographic moisture index were used as auxiliary data. In conditions of complex relief, a clear dependence of the location of soils on relief elements has been established. By extrapolating data from a large-scale soil survey, 10 soil cartographic units were identified. According to the relief elements, podzolic, sod-podzolic, bog-podzolic and alluvial soils were identified. In terms of granulometric composition, light soils prevail, a small area is occupied by medium loamy soils.

Derivation of terrain covariates for digital soil mapping in Australia

Soil Research ◽  
2015 ◽  
Vol 53 (8) ◽  
pp. 895 ◽  
Author(s):  
John C. Gallant ◽  
Jenet M. Austin
Keyword(s):  
Soil Properties ◽  
Spatial Patterns ◽  
Data Access ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Data Discovery ◽  
Digital Elevation ◽  
The Creation ◽  
Elevation Model ◽  
Mapping Exercise

Digital soil mapping is founded on the availability of covariates that are used as surrogates for the spatial patterns in soil properties. One important subset of covariates represents the patterns due to terrain, and these are typically derived from a digital elevation model at a suitable resolution. When each digital soil mapping exercise requires the calculation of terrain covariates, there is a clear potential for inconsistent methods and for choosing the covariates that are easiest to derive rather than those that are most relevant. The creation of open repositories of relevant terrain covariates that are correctly derived avoids these problems and fosters the application of digital soil mapping and other modelling activities that benefit from landscape properties. This paper describes the creation of a suite of commonly used terrain covariates from the 1-arcsecond (~30 m) resolution digital elevation models for Australia that were released through CSIRO’s Data Access Portal and the TERN Data Discovery Portal. The methods used to derive the terrain covariates are described and their characteristics are identified.

scholarly journals Terrain-Based Shadow Correction Method for Assessing Supraglacial Features on the Greenland Ice Sheet

2021 ◽  
Vol 2 ◽  
Author(s):  
Sasha. Z. Leidman ◽  
Åsa K. Rennermalm ◽  
Richard G. Lathrop ◽  
Matthew. G. Cooper
Keyword(s):  
Land Surface ◽  
Greenland Ice Sheet ◽  
Correction Method ◽  
Correction Coefficient ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Sediment Cover ◽  
Elevation Model ◽  
Uav Images ◽  
Gis Software

The presence of shadows in remotely sensed images can reduce the accuracy of land surface classifications. Commonly used methods for removing shadows often use multi-spectral image analysis techniques that perform poorly for dark objects, complex geometric models, or shaded relief methods that do not account for shadows cast on adjacent terrain. Here we present a new method of removing topographic shadows using readily available GIS software. The method corrects for cast shadows, reduces the amount of over-correction, and can be performed on imagery of any spectral resolution. We demonstrate this method using imagery collected with an uncrewed aerial vehicle (UAV) over a supraglacial stream catchment in southwest Greenland. The structure-from-motion digital elevation model showed highly variable topography resulting in substantial shadowing and variable reflectance values for similar surface types. The distribution of bare ice, sediment, and water within the catchment was determined using a supervised classification scheme applied to the corrected and original UAV images. The correction resulted in an insignificant change in overall classification accuracy, however, visual inspection showed that the corrected classification more closely followed the expected distribution of classes indicating that shadow correction can aid in identification of glaciological features hidden within shadowed regions. Shadow correction also caused a substantial decrease in the areal coverage of dark sediment. Sediment cover was highly dependent on the degree of shadow correction (k coefficient), yet, for a correction coefficient optimized to maximize shadow brightness without over-exposing illuminated surfaces, terrain correction resulted in a 49% decrease in the area covered by sediment and a 29% increase in the area covered by water. Shadow correction therefore reduces the overestimation of the dark surface coverage due to shadowing and is a useful tool for investigating supraglacial processes and land cover change over a wide variety of complex terrain.

scholarly journals Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster

2019 ◽  
Vol 11 (9) ◽  
pp. 1096 ◽  
Author(s):  
Hiroyuki Miura
Keyword(s):  
Debris Flow ◽  
Digital Elevation Model ◽  
Large Scale ◽  
Satellite Images ◽  
Erosion Depth ◽  
Digital Elevation ◽  
Elevation Model ◽  
Fusion Analysis ◽  
Optical Satellite Images ◽  
Debris Flow Disaster

Rapid identification of affected areas and volumes in a large-scale debris flow disaster is important for early-stage recovery and debris management planning. This study introduces a methodology for fusion analysis of optical satellite images and digital elevation model (DEM) for simplified quantification of volumes in a debris flow event. The LiDAR data, the pre- and post-event Sentinel-2 images and the pre-event DEM in Hiroshima, Japan affected by the debris flow disaster on July 2018 are analyzed in this study. Erosion depth by the debris flows is empirically modeled from the pre- and post-event LiDAR-derived DEMs. Erosion areas are detected from the change detection of the satellite images and the DEM-based debris flow propagation analysis by providing predefined sources. The volumes and their pattern are estimated from the detected erosion areas by multiplying the empirical erosion depth. The result of the volume estimations show good agreement with the LiDAR-derived volumes.

scholarly journals Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

2016 ◽  
Vol 13 (5) ◽  
pp. 1387-1408 ◽  
Author(s):  
Zhen Zhang ◽  
Niklaus E. Zimmermann ◽  
Jed O. Kaplan ◽  
Benjamin Poulter
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Spatiotemporal Dynamics ◽  
Fundamental Parameter ◽  
Data Set ◽  
Dynamic Global Vegetation Model ◽  
Wetland Dynamics ◽  
Cost Efficient ◽  
Elevation Model

Abstract. Simulations of the spatiotemporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate. Hydrologic inundation models, such as the TOPography-based hydrological model (TOPMODEL), are based on a fundamental parameter known as the compound topographic index (CTI) and offer a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains a large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl (Lund–Potsdam–Jena Wald Schnee und Landschaft version) Dynamic Global Vegetation Model (DGVM) and quantifies uncertainties by comparing three digital elevation model (DEM) products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland data set can help to successfully delineate the seasonal and interannual variation of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows the best accuracy for capturing the spatiotemporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is  ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of  ∼ 5.17 Mkm2 for 1980–2010. When integrated with wetland methane emission submodule, the uncertainty of global annual CH4 emissions from topography inputs is estimated to be 29.0 Tg yr−1. This study demonstrates the feasibility of TOPMODEL to capture spatial heterogeneity of inundation at a large scale and highlights the significance of correcting maximum wetland extent to improve modeling of interannual variations in wetland area. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.

A new method for supporting interpretation of paleochannels in a large scale — Detrended Digital Elevation Model Interpretation

Geomorphology ◽  
2020 ◽  
Vol 369 ◽  
pp. 107374
Author(s):  
Shuyan Zhang ◽  
Yong Ma ◽  
Fu Chen ◽  
Jianbo Liu ◽  
Fulong Chen ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Large Scale ◽  
New Method ◽  
Model Interpretation ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals A Semiautomatic Pixel-Object Method for Detecting Landslides Using Multitemporal ALOS-2 Intensity Images

2020 ◽  
Vol 12 (3) ◽  
pp. 561 ◽  
Author(s):  
Bruno Adriano ◽  
Naoto Yokoya ◽  
Hiroyuki Miura ◽  
Masashi Matsuoka ◽  
Shunichi Koshimura
Keyword(s):  
Disaster Response ◽  
Large Scale ◽  
Reference Data ◽  
Mass Movement ◽  
Recovery Planning ◽  
Additional Information ◽  
Digital Elevation ◽  
Before And After ◽  
Intensity Images ◽  
Elevation Model

The rapid and accurate mapping of large-scale landslides and other mass movement disasters is crucial for prompt disaster response efforts and immediate recovery planning. As such, remote sensing information, especially from synthetic aperture radar (SAR) sensors, has significant advantages over cloud-covered optical imagery and conventional field survey campaigns. In this work, we introduced an integrated pixel-object image analysis framework for landslide recognition using SAR data. The robustness of our proposed methodology was demonstrated by mapping two different source-induced landslide events, namely, the debris flows following the torrential rainfall that fell over Hiroshima, Japan, in early July 2018 and the coseismic landslide that followed the 2018 Mw6.7 Hokkaido earthquake. For both events, only a pair of SAR images acquired before and after each disaster by the Advanced Land Observing Satellite-2 (ALOS-2) was used. Additional information, such as digital elevation model (DEM) and land cover information, was employed only to constrain the damage detected in the affected areas. We verified the accuracy of our method by comparing it with the available reference data. The detection results showed an acceptable correlation with the reference data in terms of the locations of damage. Numerical evaluations indicated that our methodology could detect landslides with an accuracy exceeding 80%. In addition, the kappa coefficients for the Hiroshima and Hokkaido events were 0.30 and 0.47, respectively.

scholarly journals Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

2016 ◽  
Vol 40 (0) ◽  
Author(s):  
Jean Michel Moura-Bueno ◽  
Ricardo Simão Diniz Dalmolin ◽  
Alexandre ten Caten ◽  
Luis Fernando Chimelo Ruiz ◽  
Priscila Vogelei Ramos ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals The Retrieval of Land Surface Pressure from MERIS Measurements in the Oxygen A Band

2009 ◽  
Vol 26 (7) ◽  
pp. 1367-1377 ◽  
Author(s):  
Rasmus Lindstrot ◽  
Rene Preusker ◽  
Jürgen Fischer
Keyword(s):  
Surface Pressure ◽  
Land Surface ◽  
Sea Level Pressure ◽  
Imaging Spectrometer ◽  
Medium Resolution ◽  
Digital Elevation ◽  
Sensitivity Studies ◽  
Ice Surfaces ◽  
Elevation Model ◽  
Digital Elevation Model Data

Abstract Measurements of the Medium-Resolution Imaging Spectrometer (MERIS) on the Environmental Satellite (Envisat) are used for the retrieval of surface pressure above land and ice surfaces. The algorithm is based on the exploitation of gaseous absorption in the oxygen A band at 762 nm. The strength of absorption is directly related to the average photon pathlength, which in clear-sky cases above bright surfaces is mainly determined by the surface pressure, with minor influences from scattering at aerosols. Sensitivity studies regarding the influences of aerosol optical thickness and scale height and the temperature profile on the measured radiances are presented. Additionally, the sensitivity of the retrieval to the accuracy of the spectral characterization of MERIS is quantified. The algorithm for the retrieval of surface pressure (SPFUB) is presented and validated against surface pressure maps constructed from ECMWF sea level pressure forecasts in combination with digital elevation model data. The accuracy of SPFUB was found to be within 10 hPa above ice surfaces at Greenland and 15 hPa above desert and mountain scenes in northern Africa and southwest Asia. In a case study above Greenland the accuracy of SPFUB could be enhanced to be better than 3 hPa by spatial averaging over areas of 40 km × 40 km.

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