Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Multi-Sensor Techniques for Topographic Mapping

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (25 January 2021) | Viewed by 25722

Share This Special Issue

Special Issue Editors

Assoc. Prof. Dr. Yuichi S. Hayakawa

E-Mail Website
Guest Editor

Faculty of Environmental Earth Science, Hokkaido University, Hokkaido 060-0810, Japan
Interests: geomorphology; geoarchaeology; laser scanning; SfM; 3D representation

Assoc. Prof. Dr. Hitoshi Saito

E-Mail Website
Guest Editor

College of Economics, Kanto Gakuin University, Kanagawa 236-8501, Japan
Interests: geographical information science; landslide mapping; machine learning

Assis. Prof. Dr. Kotaro Iizuka

E-Mail Website
Guest Editor

Center for Spatial Information Science, The University of Tokyo, Chiba 277-8568, Japan
Interests: remote sensing; forestry; spatial information analysis

Special Issue Information

Dear Colleagues,

Topographic mapping is a fundamental procedure in various field-based studies, including in geomorphology, archaeology, ecology, and environmental sciences. A variety of sensors have recently been developed to perform mapping of landforms. For instance, unmanned aerial vehicles (UAVs) have been used to capture optical or infrared images to carry out three-dimensional and multiband mapping of the land surface. Aerial or terrestrial light detection and ranging (lidar) technology have often been applied to measure surficial objects on the land such as forests. With such techniques, detailed characteristics of the land surface morphology can be investigated, and time-series analysis with multitemporal measurements enables us to detect changes in the Earth surface by an excellent spatiotemporal resolution.

This Special Issue aims to present novel and innovative applications of multiple sensors and devices used for topographic mapping. For this, we call papers addressing the wide range of applications of sensors used for topographic mapping. Either review articles or original research papers or technical papers related to the application for topographic mapping are welcome.

Assoc. Prof. Dr. Yuichi S. Hayakawa
Assoc. Prof. Dr. Hitoshi Saito
Assis. Prof. Dr. Kotaro Iizuka
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Topographic mapping
Landforms
Forests
UAV
Lidar
Radar

Published Papers (7 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Other

19 pages, 2654 KiB

Open AccessArticle

Small All-Range Lidar for Asteroid and Comet Core Missions

by Xiaoli Sun, Daniel R. Cremons, Erwan Mazarico, Guangning Yang, James B. Abshire, David E. Smith, Maria T. Zuber, Mark Storm, Nigel Martin, Jacob Hwang, Jeff D. Beck, Nathan R. Huntoon and Dick M. Rawlings

Sensors 2021, 21(9), 3081; https://doi.org/10.3390/s21093081 - 28 Apr 2021

Cited by 7 | Viewed by 3960

Abstract

We report the development of a new type of space lidar specifically designed for missions to small planetary bodies for both topographic mapping and support of sample collection or landing. The instrument is designed to have a wide dynamic range with several operation modes for different mission phases. The laser transmitter consists of a fiber laser that is intensity modulated with a return-to-zero pseudo-noise (RZPN) code. The receiver detects the coded pulse-train by correlating the detected signal with the RZPN kernel. Unlike regular pseudo noise (PN) lidars, the RZPN kernel is set to zero outside laser firing windows, which removes most of the background noise over the receiver integration time. This technique enables the use of low peak-power but high pulse-rate lasers, such as fiber lasers, for long-distance ranging without aliasing. The laser power and the internal gain of the detector can both be adjusted to give a wide measurement dynamic range. The laser modulation code pattern can also be reconfigured in orbit to optimize measurements to different measurement environments. The receiver uses a multi-pixel linear mode photon-counting HgCdTe avalanche photodiode (APD) array with near quantum limited sensitivity at near to mid infrared wavelengths where many fiber lasers and diode lasers operate. The instrument is modular and versatile and can be built mostly with components developed by the optical communication industry. Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Figure 1

23 pages, 7312 KiB

Open AccessArticle

Evaluating the Ability of Multi-Sensor Techniques to Capture Topographic Complexity

by Hannah M. Cooper, Thad Wasklewicz, Zhen Zhu, William Lewis, Karley LeCompte, Madison Heffentrager, Rachel Smaby, Julian Brady and Robert Howard

Sensors 2021, 21(6), 2105; https://doi.org/10.3390/s21062105 - 17 Mar 2021

Cited by 5 | Viewed by 3359

Abstract

This study provides an evaluation of multiple sensors by examining their precision and ability to capture topographic complexity. Five different small unmanned aerial systems (sUAS) were evaluated, each with a different camera, Global Navigation Satellite System (GNSS), and Inertial Measurement Unit (IMU). A lidar was also used on the largest sUAS and as a mobile scanning system. The quality of each of the seven platforms were compared to actual surface measurements gathered with real-time kinematic (RTK)-GNSS and terrestrial laser scanning. Rigorous field and photogrammetric assessment workflows were designed around a combination of structure-from-motion to align images, Monte Carlo simulations to calculate spatially variable error, object-based image analysis to create objects, and MC32-PM algorithm to calculate vertical differences between two dense point clouds. The precision of the sensors ranged 0.115 m (minimum of 0.11 m for MaRS with Sony A7iii camera and maximum of 0.225 m for Mavic2 Pro). In a heterogenous test location with varying slope and high terrain roughness, only three of the seven mobile platforms performed well (MaRS, Inspire 2, and Phantom 4 Pro). All mobile sensors performed better for the homogenous test location, but the sUAS lidar and mobile lidar contained the most noise. The findings presented herein provide insights into cost–benefit of purchasing various sUAS and sensors and their ability to capture high-definition topography. Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Figure 1

21 pages, 14628 KiB

Open AccessArticle

Quantifying Debris Flood Deposits in an Alaskan Fjord Using Multitemporal Digital Elevation Models

by Matthew Balazs, Anupma Prakash and Gabriel Wolken

Sensors 2021, 21(6), 1966; https://doi.org/10.3390/s21061966 - 11 Mar 2021

Cited by 1 | Viewed by 1752

Abstract

Six DEMs over a 10-year period were used to estimate flood-related sedimentation in the Japanese Creek drainage located in Seward, Alaska. We analyze two existing LiDAR DEMs and one GNSS-derived DEM along with three additional DEMs that we generated using differential Global Navigation Satellite System (dGNSS) and Structure from Motion (SfM) techniques. Uncertainties in each DEM were accounted for, and a DEMs of Difference (DoD) technique was used to quantify the amount and pattern of sediment introduced, redistributed, or exiting the system. Through correlating the changes in sediment budget with rainfall data and flood events, the study demonstrates that the major flood events in 2006 and 2012—the 7th and 5th highest precipitation events on record—resulted in an increased sedimentation in the drainage as a whole. At a minimum the 2006 and 2012 events increased the sediment in the lower reaches by 70,100 and 53,900 cubic meters, respectively. The study shows that the DoD method and using multiple technologies to create DEMs is effective in quantifying the volumetric change and general spatial patterns of sediment redistribution between the acquisition of DEMs. Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Figure 1

24 pages, 11310 KiB

Open AccessArticle

A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models

by Ayub Mohammadi, Sadra Karimzadeh, Shazad Jamal Jalal, Khalil Valizadeh Kamran, Himan Shahabi, Saeid Homayouni and Nadhir Al-Ansari

Sensors 2020, 20(24), 7214; https://doi.org/10.3390/s20247214 - 16 Dec 2020

Cited by 19 | Viewed by 4619

Abstract

Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs’ performance, such as 90-meters’ TanDEM-X and 30-meters’ SRTM, are better than Sentinel-1 DEM (with a better spatial resolution). Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Figure 1

16 pages, 8905 KiB

Open AccessArticle

Volumetric Change Detection in Bedrock Coastal Cliffs Using Terrestrial Laser Scanning and UAS-Based SfM

by Yuichi S. Hayakawa and Hiroyuki Obanawa

Sensors 2020, 20(12), 3403; https://doi.org/10.3390/s20123403 - 16 Jun 2020

Cited by 18 | Viewed by 3793

Abstract

Three-dimensional (3D) morphological changes in rocky coasts need to be precisely measured for protecting coastal areas and evaluating the associated sediment dynamics, although volumetric measurements of bedrock erosion in rocky coasts have been limited due to the lack of appropriate measurement methods. Here we carried out repeat surveys of the 3D measurements of a small coastal island using terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetry with an unmanned aerial system (UAS) for 5 years. The UAS-SfM approach measures the entire shape of the island, whereas the TLS measurement enables to obtain more accurate morphological data at a scale of centimeters on the land side. The multitemporal TLS-derived data were first aligned in timeline by the iterative closest point (ICP) method and they were used as positionally correct references. The UAS-SfM data were then aligned to each of the TLS-derived data by ICP to improve its positional accuracy. The changed areas for each period was then extracted from the aligned UAS-derived point clouds and were converted to 3D mesh polygons, enabling a differential volume estimate (DVE). The DVE for each period was revealed to be from 3.1 to 77.2 m³/month. These changes are rapid enough to force the coastal bedrock island to disappear in 30 years. The temporal variations in the DVE is roughly associated with those in the frequency of high tidal waves. Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Graphical abstract

Other

Jump to: Research

25 pages, 7404 KiB

Open AccessTechnical Note

Conformity of the NASADEM_HGT and ALOS AW3D30 DEM with the Altitude from the Brazilian Geodetic Reference Stations: A Case Study from Brazilian Cerrado

by Giovana Maranhão Bettiol, Manuel Eduardo Ferreira, Luiz Pacheco Motta, Édipo Henrique Cremon and Edson Eyji Sano

Sensors 2021, 21(9), 2935; https://doi.org/10.3390/s21092935 - 22 Apr 2021

Cited by 10 | Viewed by 2516

Abstract

The Brazilian Cerrado (tropical savanna) is the second largest biome in South America and the main region in the country for agricultural production. Altitude is crucial information for decision-makers and planners since it is directly related to temperature that conditions, for example, the climatic risk of rainfed crop plantations. This study analyzes the conformity of two freely available digital elevation models (DEMs), the NASADEM Merged Digital Elevation Model Global 1 arc second (NASADEM_HGT) version 1 and the Advanced Land Observing Satellite Global Digital Surface Model (ALOS AW3D30), version 3.1, with the altitudes provided by 1695 reference stations of the Brazilian Geodetic System. Both models were evaluated based on the parameters recommended in the Brazilian Cartographic Accuracy Standard for Digital Cartographic Products (PEC-PCD), which defines error tolerances according to eight different scales (from 1:1000 to 1:250,000) and classes A (most strict tolerance, for example, 0.17 m for 1:1000 scale), B, C, and D (least strict tolerance, for example, 50 m for 1:250,000 scale). Considering the class A, the NASADEM_HGT meets 1:250,000 and lower scales, while AW3D30 meets 1:100,000 and lower scales; for class B, NASADEM_HGT meets 1:100,000 scale and AW3D30 meets 1:50,000. AW3D30 presented lower values of root mean square error, standard deviation, and bias, indicating that it presents higher accuracy in relation to the NASADEM_HGT. Within eight of Cerrado’s municipalities with the highest grain production, the differences between average altitudes, measured by the Cohen’s effect size, were statistically insignificant. The results obtained by the PEC-PCD for the Cerrado biome indicate that both models can be employed in different DEM-dependent applications over this biome. Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Figure 1

11 pages, 4361 KiB

Open AccessLetter

Portable LiDAR-Based Method for Improvement of Grass Height Measurement Accuracy: Comparison with SfM Methods

by Hiroyuki Obanawa, Rena Yoshitoshi, Nariyasu Watanabe and Seiichi Sakanoue

Sensors 2020, 20(17), 4809; https://doi.org/10.3390/s20174809 - 26 Aug 2020

Cited by 17 | Viewed by 4414

Abstract

Plant height is a key indicator of grass growth. However, its accurate measurement at high spatial density with a conventional ruler is time-consuming and costly. We estimated grass height with high accuracy and speed using the structure from motion (SfM) and portable light detection and ranging (LiDAR) systems. The shapes of leaf tip surface and ground in grassland were determined by unmanned aerial vehicle (UAV)-SfM, pole camera-SfM, and hand-held LiDAR, before and after grass harvesting. Grass height was most accurately estimated using the difference between the maximum value of the point cloud before harvesting, and the minimum value of the point cloud after harvesting, when converting from the point cloud to digital surface model (DSM). We confirmed that the grass height estimation accuracy was the highest in DSM, with a resolution of 50–100 mm for SfM and 20 mm for LiDAR, when the grass width was 10 mm. We also found that the error of the estimated value by LiDAR was about half of that by SfM. As a result, we evaluated the influence of the data conversion method (from point cloud to DSM), and the measurement method on the accuracy of grass height measurement, using SfM and LiDAR. Full article

(This article belongs to the Special Issue Multi-Sensor Techniques for Topographic Mapping)

► Show Figures

Journal Menu

Journal Browser

Multi-Sensor Techniques for Topographic Mapping

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (7 papers)

Research

Other

Further Information

Guidelines

MDPI Initiatives

Follow MDPI