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Earth Observations in Asia-Oceania
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Earth Observations in Asia-Oceania

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 15655

Special Issue Editors

Dr. Andy Steven

E-Mail Website
Guest Editor
CSIRO, Queensland Biosciences Precinct, University of Queensland, 306 Carmody Rd., St. Lucia, Brisbane, QLD 4067, Australia
Interests: coastal biogeochemistry; integrated information systems
Dr. Thomas Schroeder

E-Mail Website
Guest Editor
CSIRO, Oceans and Atmosphere, GPO Box 2583, Brisbane, QLD 4001, Australia
Interests: marine optics and ocean colour remote sensing
Dr. **ang Zhou

E-Mail
Guest Editor
The Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), No.20A Datun Road, Chaoyang District, Bei**g 100101, China
Interests: calibration and validation; terrestrial and montane; disaster risk reduction

Special Issue Information

Dear Colleagues,

Ranging from the mountaintops of the Himalayas to the small atoll nations in the Pacific Ocean, the Asia–Oceania (AO) region encompasses two-thirds of the world's population, with people living in more than 60 countries that vary in size, economy, development status, and environmental condition.With continuous development, particularly urbanization, the AO region is subject to rapid and widespread environmental changes, which result in environmental deterioration, habitat and biodiversity loss, and pollution, reaching the farthest waters for the Pacific. Climate-related extremes, including earthquakes, tsunamis, floods, and droughts, result in the highest levels of disaster of anywhere in the world, and further endanger the security of water, food, energy, health, and ecosystem services. Sustainable development must therefore be based on a comprehensive assessment of the disaster and environmental risks, along with their potential ramifications for environmental security and human well-being.

Earth observation data, information, and derived knowledge are critical for identifying these vulnerabilities, monitoring and assessing impacts and informing the decision-makers.

This Special Issue will highlight how remote sensing is being used across the Asia–Oceania region, to inform a diverse range of issues, including environmental change and conditions, food security, disaster management and surveillance, and to envisage what those needs will be in the future. We are inviting submissions including, but not limited to, the following:

  • Regional and ecosystem changes in montane coastal and ocean environments
  • Assessing climate change
  • Disaster-risk management
  • Food security
  • Survelliance of legal and illegal activities
  • User needs and capacity building
  • Collaboration and coordination efforts to better utilise Earth observation
  • Novel applications and emerging needs

Dr. Andy Steven
Dr. Thomas Schroeder
Dr. **ang Zhou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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. Remote Sensing 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 2700 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

  • Asia
  • Oceania
  • Pacific
  • Management
  • Monitoring
  • Surveliance
  • Food security
  • Disaster management
  • Land-use change
  • Biodiversity

Published Papers (5 papers)

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Research

18 pages, 5269 KiB  
Article
Remote Sensing-Guided Spatial Sampling Strategy over Heterogeneous Surface Ground for Validation of Vegetation Indices Products with Medium and High Spatial Resolution
by Tingting Lv, **ang Zhou, Zui Tao, **aoyu Sun, ** Wang, Ruoxi Li and Futai **e
Remote Sens. 2021, 13(14), 2674; https://doi.org/10.3390/rs13142674 - 7 Jul 2021
Cited by 4 | Viewed by 2817
Abstract
Remote sensing (RS)-derived vegetation indices (VIs) with medium and high spatial resolution have emerged as a promising dataset for fine-scale ecosystem modeling and agricultural monitoring at local or global scales. Before they can be used as reliable inputs for other research, conducting in [...] Read more.
Remote sensing (RS)-derived vegetation indices (VIs) with medium and high spatial resolution have emerged as a promising dataset for fine-scale ecosystem modeling and agricultural monitoring at local or global scales. Before they can be used as reliable inputs for other research, conducting in situ measurements for validation is very critical. However, the spatial heterogeneity due to the diversity of land cover and its spatial organization in the landscape increases the uncertainty of validation, so design of optimal sampling is an important basis for the reliability of the validation. In this paper, we propose an integrative stratified sampling strategy (INTEG-STRAT) based on normalized difference vegetation index (NDVI) data as prior knowledge. The basic idea is to realize a sampling optimization by determining the optimal combination of the spatial sampling method (e.g., simple random sampling (SRS), spatial system sampling (SYS), stratified sampling, generalized random tessellation stratified (GRTS), balanced acceptance sampling (BAS)) and spatial stratification scheme with an objective rule. The objective rule in this paper is to minimize the root mean square error (RMSE) of 10-fold cross validation between estimated values (sample are not included) and the corresponding values on prior knowledge. Relative precision, correlation coefficient, and RMSE are used to compare the effectiveness of the proposed sampling strategy with each sampling method without considering sampling optimization. After comparing, we find that the INTEG-STRAT requires fewer samples to become stable and has higher accuracy. At site 1, when the correlation coefficient between NDVI image and the simulated NDVI surface reached 80%, INTEG-STRAT needed only 70 sampling points while other methods require more sampling points. At the same time, INTEG-STRAT strategy has a smaller RMSE between the estimated values and the corresponding values on prior knowledge image. In general, INTEG-STRAT is an effective method in the selection of representative samples to support the validation of vegetation indices products with medium and high spatial resolution. Full article
(This article belongs to the Special Issue Earth Observations in Asia-Oceania)
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Graphical abstract

19 pages, 2566 KiB  
Article
A Prediction Model of Water In Situ Data Change under the Influence of Environmental Variables in Remote Sensing Validation
by Futai **e, Zui Tao, **ang Zhou, Tingting Lv, ** Wang and Ruoxi Li
Remote Sens. 2021, 13(1), 70; https://doi.org/10.3390/rs13010070 - 27 Dec 2020
Cited by 4 | Viewed by 2825
Abstract
Validation is an essential process to evaluate the quality of waterbody remote sensing products, and the reliability and effective application of the in situ data of waterbody parameters are an important part of validation. Based on the in situ data of chlorophyll-a (Chl-a), [...] Read more.
Validation is an essential process to evaluate the quality of waterbody remote sensing products, and the reliability and effective application of the in situ data of waterbody parameters are an important part of validation. Based on the in situ data of chlorophyll-a (Chl-a), total suspended solids (TSS) and other environmental variables (EVs) measured at the fixed station in Taihu Lake, we attempt to develop a prediction model to determine whether the in situ measurement has enough representativeness for validating waterbody remote sensing products. Key EVs that affect the changes of Chl-a and TSS are firstly identified by using correlation analysis, which participate in modeling as variables. In addition, three multi-parameter modeling approaches are selected to simulate the daily changes of Chl-a and TSS under different EVs configurations. The results indicate that the highest prediction accuracy can be achieved through the generalized regression neural network (GRNN) based model. In the all-valid dataset, the testing absolute average relative errors (AEs) of GRNN-based Chl-a and TSS prediction model are 11.4% and 11.3%, respectively, and in the sunny-day dataset, the testing AEs are 8.6% and 8.2%, respectively. Meanwhile, the application example proves that the prediction model in this paper can be effectively used to screen the in situ data and determine the time window for satellite-ground data matching. Full article
(This article belongs to the Special Issue Earth Observations in Asia-Oceania)
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17 pages, 10163 KiB  
Article
Preliminary Research on a Comparison and Evaluation of FY-4A LMI and ADTD Data through a Moving Amplification Matching Algorithm
by Pengfei Li, Guofu Zhai, Wen**g Pang, Wen Hui, Wenjuan Zhang, **g Chen and Liting Zhang
Remote Sens. 2021, 13(1), 11; https://doi.org/10.3390/rs13010011 - 22 Dec 2020
Cited by 12 | Viewed by 2144
Abstract
In this study, a new moving amplification matching algorithm was proposed, and then the temporal and spatial differences and correlation were analysed and evaluated by comparing the FengYun-4A Lightning Map** Imager (FY-4A LMI) data and the China Meteorological Administration Lightning Detection Network Advanced [...] Read more.
In this study, a new moving amplification matching algorithm was proposed, and then the temporal and spatial differences and correlation were analysed and evaluated by comparing the FengYun-4A Lightning Map** Imager (FY-4A LMI) data and the China Meteorological Administration Lightning Detection Network Advanced TOA and Direction (CMA-LDN ADTD) system data of southwest China in July 2018. The results are as follows. Firstly, the new moving amplification matching algorithm could effectively reduce the number of invalid operations and save the operation time in comparison to the conventional ergodic algorithms. Secondly, LMI has less detection efficiency during the daytime, using ADTD as a reference. The lightning number detected by ADTD increased from 5:00 AM UTC (13:00 PM BJT, Bei**g Time) and almost lasted for a whole day. Thirdly, the trends of lightning data change of LMI and ADTD were the same as the whole. The average daily lightning matching rate of the LMI in July was 63.23%. The average hourly lightning matching rate of the LMI in July was 75.08%. Lastly, the mean value of the spherical surface distance in the matched array was 35.49 km, and roughly 80% of the matched distance was within 57 km, indicating that the spatial threshold limit was relatively stable. The correlation between LMI lightning radiation intensity and ADTD lighting current intensity was low. Full article
(This article belongs to the Special Issue Earth Observations in Asia-Oceania)
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Graphical abstract

23 pages, 8707 KiB  
Article
Preliminary Observations from the China Fengyun-4A Lightning Map** Imager and Its Optical Radiation Characteristics
by Wen Hui, Wenjuan Zhang, Weitao Lyu and Pengfei Li
Remote Sens. 2020, 12(16), 2622; https://doi.org/10.3390/rs12162622 - 14 Aug 2020
Cited by 22 | Viewed by 4004
Abstract
The Fengyun-4A (FY-4A) Lightning Map** Imager (LMI) is the first satellite-borne lightning imager developed in China, which can detect lightning over China and its neighboring regions based on a geostationary satellite platform. In this study, the spatial distribution and temporal variation characteristics of [...] Read more.
The Fengyun-4A (FY-4A) Lightning Map** Imager (LMI) is the first satellite-borne lightning imager developed in China, which can detect lightning over China and its neighboring regions based on a geostationary satellite platform. In this study, the spatial distribution and temporal variation characteristics of lightning activity over China and its neighboring regions were analyzed in detail based on 2018 LMI observations. The observation characteristics of the LMI were revealed through a comparison with the Tropical Rainfall Measuring Mission (TRMM)-Lightning Imaging Sensor (LIS) and World Wide Lightning Location Network (WWLLN) observations. Moreover, the optical radiation characteristics of lightning signals detected by the LMI were examined. Factors that may affect LMI detection were discussed by analyzing the differences in optical radiation characteristics between LMI and LIS flashes. The results are as follows. Spatially, the flash density distribution pattern detected by the LMI was similar to those detected by the LIS and WWLLN. High-flash density regions were mainly concentrated over Southeastern China and Northeastern India. Temporally, LMI flashes exhibited notable seasonal and diurnal variation characteristics. The LMI detected a concentrated lightning outbreak over Northeastern India in the premonsoon season and over Southeastern China in the monsoon season, which was consistent with LIS and WWLLN observations. LMI-observed diurnal peak flash rates occurred in the afternoon over most of the regions. There was a “stepwise” decrease in the LMI-observed optical radiance, footprint size, duration, and number of groups per flash, from the ocean to the coastal regions to the inland regions. LMI flashes exhibited higher optical radiance but lasted for shorter durations than LIS flashes. LMI observations are not only related to instrument performance but are also closely linked to onboard and ground data processing. In future, targeted improvements can be made to the data processing algorithm for the LMI to further enhance its detection capability. Full article
(This article belongs to the Special Issue Earth Observations in Asia-Oceania)
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Graphical abstract

17 pages, 5054 KiB  
Article
Micro-Pulse Lidar Cruising Measurements in Northern South China Sea
by Yuan Li, Baomin Wang, Shao-Yi Lee, Zhijie Zhang, Ye Wang and Wenjie Dong
Remote Sens. 2020, 12(10), 1695; https://doi.org/10.3390/rs12101695 (registering DOI) - 25 May 2020
Cited by 7 | Viewed by 3187
Abstract
A shipborne micro-pulse lidar (Sigma Space Mini-MPL) was used to measure aerosol extinction coefficient over the northern region of the South China Sea from 9 August to 7 September 2016, the first time a mini-MPL was used for aerosol observation over the cruise [...] Read more.
A shipborne micro-pulse lidar (Sigma Space Mini-MPL) was used to measure aerosol extinction coefficient over the northern region of the South China Sea from 9 August to 7 September 2016, the first time a mini-MPL was used for aerosol observation over the cruise region. The goal of the experiment was to investigate if the compact and affordable mini-MPL was usable for aerosol observation over this region. The measurements were used to calculate vertical profiles of volume extinction coefficient, depolarization ratio, and atmospheric boundary layer height. Aerosol optical depth (AOD) was lower over the southwest side of the cruise region, compared to the northeast side. Most attenuation occurred below 3.5 km, and maximum extinction values over coastal areas were generally about double of values offshore. The extinction coefficients at 532 nm (aerosol and molecular combined) over coastal and offshore areas were on average 0.04 km−1 and 0.02 km−1, respectively. Maximum values reached 0.2 km−1 and 0.14 km−1, respectively. Vertical profiles and back-trajectory calculations indicated vertical and horizontal layering of aerosols from different terrestrial sources. The mean volume depolarization ratio of the aerosols along the cruise was 0.04. The mean atmospheric boundary layer height along the cruise was 653 m, with a diurnal cycle reaching its mean maximum of 1041 m at 12:00 local time, and its mean minimum of 450 m at 20:00 local time. Unfortunately, only 11% of the measurements were usable. This was due to ship instability in rough cruise conditions, lack of stabilization rig, water condensation attached to the eye lens, and high humidity attenuating the echo signal. We recommend against the use of the mini-MPL in this cruise region unless substantial improvements are made to the default setup, e.g., instrument stabilization, instrument protection cover, and more theoretical work taking into account atmospheric gas scattering or absorption. Full article
(This article belongs to the Special Issue Earth Observations in Asia-Oceania)
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