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Applications of Advanced Remote Sensing Technology for Sustainable Resource Exploration and Assessment

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (26 March 2023) | Viewed by 12163

Special Issue Editors

Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 10094, China
Interests: applications of SAR remote sensing
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 10094, China
Interests: remote sensing of the cryosphere

Special Issue Information

Dear Colleagues,

Sustainable resources, such as productive agriculture, clean water resources, healthy marine ecosystems, abundant forest area, clean energy, and so on are drawing cumulative international attention. Assessment and exploration of sustainable resource will drive discoveries and lay the foundation to achieve related Sustainable Development Goals (SDGs) which are proposed by the United Nations and have the aim of solving critical issues mankind faces and achieving sustainability on the Earth. It is specifically involved in SDG 2, SDG 6, SDG 14, and SDG 15. Remote sensing has improved dramatically over the past few decades. By providing large amount of observation data from planes, satellites, and even moon base in the near future, it can serve as a key technology to assess, explore and manage sustainable resources.

This special issue welcome original remote sensing studies on data products, methodologies, simulating models, policy-making support of sustainable resources. Related topics include, but not limited to, agriculture development, evapotranspiration, water protection, snow and glacier change, marine and coastal environment, pollution detection, carbon cycle, energy balance, land use, forest area, and wind and solar energy, among others. This special issue will be a contribution to the monitoring and evaluation of SDGs implementation.

Prof. Dr. Lu Zhang
Dr. Mingyang Lv
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. Sustainability 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 2400 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

  • sustainable resources
  • remote sensing
  • SDGs
  • exploration
  • assessment

Published Papers (6 papers)

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Research

19 pages, 1498 KiB  
Article
Formulation of Radiometric Calibration for Azimuthal Multi-Angle Observation Space-Borne SAR
by Jianjun Huang, Jie Chen, Yanan Guo and Pengbo Wang
Sustainability 2022, 14(11), 6757; https://0-doi-org.brum.beds.ac.uk/10.3390/su14116757 - 31 May 2022
Viewed by 1182
Abstract
A novel space-borne SAR technique, azimuthal multi-angle observation (AMAO), has recently been proposed. It has highly flexible working modes and powerful capability of target information acquisition, but has challenges in achieving radiometric measurement accuracy. The larger the squint angle, the higher the resolution [...] Read more.
A novel space-borne SAR technique, azimuthal multi-angle observation (AMAO), has recently been proposed. It has highly flexible working modes and powerful capability of target information acquisition, but has challenges in achieving radiometric measurement accuracy. The larger the squint angle, the higher the resolution and the more variations involved. Radiometric calibration is a necessary approach to consistent and accurate SAR measurements, but has so far not been carefully considered for AMAO space-borne SAR. This paper addressed the new issues in radiometric calibration arising from the AMAO space-borne SAR system. The AMAO imaging modes are firstly been illustrated, based on which the influences of the AMAO on radiometric calibration are analyzed. To guarantee the accuracy of the radiometric calibration, an appropriate form of the SAR radar equation is derived for AMAO space-borne SAR. On these bases, the calibration models can be obtained by reformulating the novel AMAO SAR equation, and the corresponding normalization method is then proposed. The good experimental performance indicators verify the correctness of proposed models and the effectiveness of the correction method. Full article
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21 pages, 19041 KiB  
Article
Comparative Study on the Evaluation of Healthy City Construction in Typical Chinese Cities Based on Statistical Data and Land Use Data
by Zhuoran Lv, Huadong Guo, Lu Zhang and Dong Liang
Sustainability 2022, 14(5), 2519; https://0-doi-org.brum.beds.ac.uk/10.3390/su14052519 - 22 Feb 2022
Cited by 2 | Viewed by 1731
Abstract
The 17 Sustainable Development Goals of the United Nations propose to “ensure healthy lives and promote well-being for all at all ages”, and to achieve this goal requires that countries strengthen their capacity to manage health risks. As a concept to describe urban [...] Read more.
The 17 Sustainable Development Goals of the United Nations propose to “ensure healthy lives and promote well-being for all at all ages”, and to achieve this goal requires that countries strengthen their capacity to manage health risks. As a concept to describe urban construction, advocated by the World Health Organization, healthy cities can effectively solve the contradictions existing along the current urban development path at a macro level. A healthy city is a sustainable city that interacts with its environment, economy, population, services, and space, and realizes the well-being of its population from all perspectives. The construction of a healthy city is an important part of the transformation of Chinese urbanization. This article refers to the index systems of domestic and foreign government agencies, along with a literature research, to construct a healthy city evaluation index that takes into account the five aspects of environment, economy, population, service, and space, and selects Beijing (a policy-oriented city), Shanghai (an economy-oriented city), Nanchang (an industry-oriented city), Guiyang (a tourism-oriented city), Datong (resource-oriented city) as five cities according to type of urban development, using the entire-array-polygon method to analyze the construction level of these cities in terms of environment, economy, population, service, space and overall state of health from 2014 to 2018 based on statistical and land use data. The results of the study found that, in general, the construction of healthy cities in China currently experiences large year-to-year fluctuations and significant differences between cities. The construction and development of healthy cities are also closely related to factors such as urban economic strength, social welfare, and policy support. Full article
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15 pages, 3391 KiB  
Article
Root Zone Soil Moisture Assessment at the Farm Scale Using Remote Sensing and Water Balance Models
by Thanaporn Supriyasilp, Teerawat Suwanlertcharoen, Nudnicha Pongput and Kobkiat Pongput
Sustainability 2022, 14(3), 1123; https://0-doi-org.brum.beds.ac.uk/10.3390/su14031123 - 19 Jan 2022
Cited by 2 | Viewed by 1406
Abstract
Water resource planning and management necessitates understanding soil moisture changes with depth in the root zone at the farm scale. For measuring soil moisture, remote sensing methods have been relatively successful. Soil moisture is estimated from image data, using in situ moisture and [...] Read more.
Water resource planning and management necessitates understanding soil moisture changes with depth in the root zone at the farm scale. For measuring soil moisture, remote sensing methods have been relatively successful. Soil moisture is estimated from image data, using in situ moisture and an empirical scattering model via regression fit analysis. However, in situ sensor data are prone to misinterpretations, requiring verification. Herein, we aimed at investigating the application of soil moisture from the water balance model towards verification of in situ soil moisture sensor data before in situ data was assessed for its relationship with remote sensing data. In situ soil moisture sensor data was obtained at 10 and 30 cm, and CROPWAT8.0 furnished root zone soil moisture data. The correlation between the in situ soil moisture at 10 and 30 cm was 0.78; the correlation between the soil moisture from CROPWAT8.0 and the in situ soil moisture were 0.64 and 0.62 at 10 and 30 cm, respectively. The R2 between Sentinel-1 backscatter coefficients and in situ moisture were 0.74 and 0.68 at each depth, respectively. Therefore, the water balance model could verify sensor results before assessing in situ soil moisture data for relationship with remote sensing data. Full article
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14 pages, 16392 KiB  
Article
Urban Land-Use Efficiency Analysis by Integrating LCRPGR and Additional Indicators
by Chaopeng Li, Guoyin Cai and Zhongchang Sun
Sustainability 2021, 13(24), 13518; https://0-doi-org.brum.beds.ac.uk/10.3390/su132413518 - 07 Dec 2021
Cited by 7 | Viewed by 2168
Abstract
Sustainable Development Goal (SDG) target 11.3 is to enhance inclusive and sustainable urbanisation and capacity for participatory, integrated, and sustainable human settlement planning and management in all countries by 2030. Within that goal, the indicator SDG 11.3.1 is defined as the ratio of [...] Read more.
Sustainable Development Goal (SDG) target 11.3 is to enhance inclusive and sustainable urbanisation and capacity for participatory, integrated, and sustainable human settlement planning and management in all countries by 2030. Within that goal, the indicator SDG 11.3.1 is defined as the ratio of land consumption rate to population growth rate (LCRPGR). This ratio is primarily used to measure urban land-use efficiency and reveal the relationship between urban land consumption and population growth. The LCRPGR indicator is aimed at representing overall urban land-use efficiency. This study added compactness, urban expansion speed, and urban expansion intensity to better reflect the impact of built-up area changes on the overall urban land-use efficiency. In addition, this study combined LCRPGR and the land consumption per capita rate (LCPC) to comprehensively analyse the relationship between land consumption and population growth in existing built urban areas, expanded built urban areas, and total built areas. This study employed three years of urban built-up and population data for 2010, 2015, and 2020 for 338 cities along the Belt and Road region to analyse land-use efficiency. The results show that the average LCRPGR for the period 2010–2015 was 1.01, which is close to the recommended ideal LCRPGR value of 1.0 in the United Nations Human Settlements Programme. For 2015–2020, the LCRPGR was 0.71, indicating that the overall urban land consumption in the study area decreased. This is also supported by the fact that the urban expansion intensity in 2020 was weaker than that in 2015. In addition, according to research on the tendency of changes in the entire urban built-up area, the smaller the urban population, the slower the urban expansion speed, the smaller the compactness, and the increasingly complex the urban borders. In cities where the overall LCRPGR is far from the ideal value of 1, the entire built-up area is divided into existing and expanded urban regions. It was found that the average LCPC value in expanded built-up areas was higher than that of existing built-up areas, showing that as cities developed, the LCPC of the newly developed urban areas was greater than that of existing built-up areas. Meanwhile, the LCPC in the expanded built-up areas showed a decreasing trend over time from 2010 to 2015 to 2020, indicating that land use in the expanded built-up regions tended to be efficient. These findings provide helpful information in decision making for balancing urban land consumption with population growth. Full article
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17 pages, 3976 KiB  
Article
Tropical Forests Classification Based on Weighted Separation Index from Multi-Temporal Sentinel-2 Images in Hainan Island
by Qi Zhu, Huadong Guo, Lu Zhang, Dong Liang, Xvting Liu, Xiangxing Wan and Jinlong Liu
Sustainability 2021, 13(23), 13348; https://0-doi-org.brum.beds.ac.uk/10.3390/su132313348 - 02 Dec 2021
Cited by 2 | Viewed by 1618
Abstract
Tropical forests play a vital role in biodiversity conservation and the maintenance of sustainability. Although different time-series spatial resolution satellite images have provided opportunities for tropical forests classification, the complexity and diversity of vegetation types still pose challenges, especially for distinguishing different vegetation [...] Read more.
Tropical forests play a vital role in biodiversity conservation and the maintenance of sustainability. Although different time-series spatial resolution satellite images have provided opportunities for tropical forests classification, the complexity and diversity of vegetation types still pose challenges, especially for distinguishing different vegetation types. In this paper, we proposed a Spectro-Temporal Feature Selection (STFS) method based on the Weighted Separation Index (WSI) using multi-temporal Sentinel-2 data for mapping tropical forests in Jianfengling area, Hainan Province. The results showed that the tropical forests were classified with an overall accuracy of 93% and an F1 measure of 0.92 with multi-temporal Sentinel-2 data. As our results also revealed, the WSI based STFS method could be efficient in tropical forests classification by using a fewer feature subset compared with Variable Selection Using Random Forest (14 features and all 40 features, respectively) to achieve the same accuracy. The analysis also showed it was not advisable to only pursue a higher WSI value while ignoring the heterogeneity and diversity of features. This study demonstrated that the WSI can provide a new feature selection method for multi-temporal remote sensing image classification. Full article
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14 pages, 4359 KiB  
Article
Localizing Indicators of SDG11 for an Integrated Assessment of Urban Sustainability—A Case Study of Hainan Province
by Chi Zhang, Zhongchang Sun, Qiang Xing, Jialong Sun, Tianyu Xia and Hao Yu
Sustainability 2021, 13(19), 11092; https://0-doi-org.brum.beds.ac.uk/10.3390/su131911092 - 07 Oct 2021
Cited by 13 | Viewed by 2677
Abstract
Rapid urbanization has brought many problems, including housing shortages, traffic congestion, air pollution, and lack of public space. To solve these problems, the United Nations proposed “The 2030 Agenda for Sustainable Development”, which contains 17 Sustainable Development Goals covering three dimensions: economy, society, [...] Read more.
Rapid urbanization has brought many problems, including housing shortages, traffic congestion, air pollution, and lack of public space. To solve these problems, the United Nations proposed “The 2030 Agenda for Sustainable Development”, which contains 17 Sustainable Development Goals covering three dimensions: economy, society, and environment. Among them, Sustainable Development Goal 11 (SDG11), “Make cities and human settlements inclusive, safe, resilient and sustainable”, can be measured at the city level. So far SDG11 still lacks three-quarters of the data required to accurately assess progress towards the goal. In this paper, we localized the indicators of SDG11 and collected Earth observation data, statistical data, and monitoring data at the city and county levels to build a better urban sustainable development assessment framework. Overall, we found that Haikou and Sanya were close to achieving sustainable development goals, while other cities were still some distance away. In Hainan Province, there was a spatial distribution pattern of high development levels in the north and south, but low levels in the middle and west. Through the Moran’s I Index of Hainan Province, we found that the sustainable development of Hainan Province did not yet form part of integrated development planning. The sustainable development assessment framework and localization methods proposed in this paper at the city and county levels provide references for the sustainable development of Hainan. At the same time, it also provides a reference for the evaluation of county-level sustainable development goals in cities in China and even the world. Full article
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