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Remote Sensing Monitoring of Resources and Ecological Environment
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Remote Sensing Monitoring of Resources and Ecological Environment

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 7784

Special Issue Editors

Prof. Dr. Ling Peng

E-Mail Website
Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: remote sensing image processing; deep learning; resources and environment survey; disaster emergency decision support
Dr. Jiakui Tang

E-Mail Website
Guest Editor
College of Resources and Environment (CRE), University of Chinese Academy of Sciences, Beijing 100049, China
Interests: environmental remote sensing; ecological remote sensing; remote sensing assessment of aerosol effects
Special Issues, Collections and Topics in MDPI journals
Dr. Qiaoyun Xie

E-Mail Website
Guest Editor
Faculty of Science, University of Technology Sydney, Ultimo, NSW 2007, Australia
Interests: vegetation monitoring; ecological forecasting; vegetation parameter retrieval; vegetation phenology; climate variability
Special Issues, Collections and Topics in MDPI journals
Dr. Yuxia Liu

E-Mail Website
Guest Editor
Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, USA
Interests: land surface phenology; climate–terrestrial ecosystem interaction; vegetation ecology; phenocam; planetScope

Special Issue Information

Dear Colleagues,

Humankind’s development has a significant impact on global resources, environment, ecology and climate. Remote sensing monitoring and assessment of regional- to global-scale ecological resources, ecosystem patterns, vegetation phenology and typical sustainable development trends is of great significance to the realization of the 2030 Sustainable Development Goals proposed by the United Nations. It can provide data and information for scientific research and policy making on global climate change, ecological environment protection and resource security issues.

This Special Issue focuses on the monitoring and application of remote-sensing-derived information from various platforms (satellites, UAVs/drones, digital repeat cameras) in dealing with regional to global scale resource and ecological environmental problems. Original, high-quality and innovative research articles and reviews are welcome. Potential topics may include (but are not limited to) the following:

  • Mechanism, modelling and method of remote sensing monitoring of ecological resources and the environment;
  • Remote sensing of terrestrial ecosystems;
  • Remote sensing of marine ecosystems;
  • Remote sensing of inland river and lake ecosystems;
  • Remote sensing of coastal ecosystems;
  • Remote sensing of smart agriculture;
  • Ecological resources and ecosystem monitoring sensor networks; 
  • Remote sensing monitoring of global or regional resources and ecology.

We look forward to receiving your contributions.

Prof. Dr. Ling Peng
Dr. Jiakui Tang
Dr. Qiaoyun Xie
Dr. Yuxia Liu
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

  • vegetation types
  • ecosystem patterns
  • physical models
  • parameter retrievals
  • biomass estimations
  • machine learning
  • sensor network monitoring
  • vegetation composition
  • vegetation structure

Published Papers (5 papers)

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Research

16 pages, 3213 KiB  
Article
Remote Sensing Classification of Temperate Grassland in Eurasia Based on Normalized Difference Vegetation Index (NDVI) Time-Series Data
by Xuefeng Xu, Jiakui Tang, Na Zhang, Anan Zhang, Wuhua Wang and Qiang Sun
Sustainability 2023, 15(20), 14973; https://doi.org/10.3390/su152014973 - 17 Oct 2023
Viewed by 930
Abstract
The Eurasian temperate grassland is the largest temperate grassland ecosystem and vegetation transition zone globally. The spatiotemporal distribution and changes of grassland types are vital for grassland monitoring and management. However, there is currently a lack of a unified classification method and standard [...] Read more.
The Eurasian temperate grassland is the largest temperate grassland ecosystem and vegetation transition zone globally. The spatiotemporal distribution and changes of grassland types are vital for grassland monitoring and management. However, there is currently a lack of a unified classification method and standard distribution map of Eurasian temperate grassland types. The Normalized Difference Vegetation Index (NDVI) from remote sensing data is commonly used in grassland monitoring. In this paper, the Accumulated Rate of NDVI Change Index (ARNCI) was proposed to characterize the annual NDVI trend of different temperate grassland types, and four transitional categories were introduced to account for the overlap between them. Based on survey data on the distribution of Eurasian temperate grassland types in the 1980s, the study area was divided into three sub-regions: Northern China, Central Asia, and Mongolia. Regionally, pixel-based ARNCI maps in the 1980s and 1990s were successfully calculated from using NOAA’s AVHRR NDVI time-series products. The ARNCI classification thresholds for different sub-regions were determined, and classification experiments and validation were conducted for each sub-region. The overall accuracies of grasslands types classification for Northern China, Central Asia, and Mongolia in the 1980s were 75.3%, 64.2%, and 84.6%, respectively, which demonstrated that there were variations in classification accuracy in the three sub-regions, and the overall performance was favorable. Finally, distribution maps of Eurasian temperate grassland types in the 1980s and 1990s were obtained, and the spatiotemporal changes of grassland types were analyzed and discussed. The ARNCI method is simple to operate and easy to obtain data, and it can be conveniently used in grassland type classification. The maps firstly address the lack of remote sensing classification maps of Eurasian temperate grassland types, and provide a promising tool for monitoring grassland degradation, management, and utilization. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring of Resources and Ecological Environment)
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20 pages, 4380 KiB  
Article
Analysis and Dynamic Evaluation of Eco-Environmental Quality in the Yellow River Delta from 2000 to 2020
by Dongling Ma, Qingji Huang, Baoze Liu and Qian Zhang
Sustainability 2023, 15(10), 7835; https://doi.org/10.3390/su15107835 - 10 May 2023
Cited by 8 | Viewed by 1503
Abstract
With the rapid development of urbanization and population growth, the ecological environment in the Yellow River Delta has undergone significant changes. In this study, Landsat satellite data and Google Earth Engine (GEE) were utilized to dynamically evaluate the changes in eco-environmental quality in [...] Read more.
With the rapid development of urbanization and population growth, the ecological environment in the Yellow River Delta has undergone significant changes. In this study, Landsat satellite data and Google Earth Engine (GEE) were utilized to dynamically evaluate the changes in eco-environmental quality in the Yellow River Delta region using the remote sensing ecological index (RSEI). Additionally, the CASA model was used to estimate net primary productivity (NPP) and explore the relationship between vegetation NPP, land-use and land-cover change (LUCC), and eco-environmental quality to reveal the complexity and related factors of eco-environmental quality changes in this region. The results show that: (1) Over the past 20 years, the eco-environmental quality in the Yellow River Delta region has changed in a “V” shape. The eco-environmental quality near the Yellow River Basin is relatively better, forming a diagonal “Y” shape, while the areas with poorer eco-environmental quality are mainly distributed in the coastal edge region of the Yellow River Delta. (2) The response of vegetation NPP to eco-environmental quality in the Yellow River Delta region is unstable. (3) Urban construction land in the Yellow River Delta region is strongly correlated with RSEI, and the absolute value of the dynamic degree of land use is as high as 8.78%, with significant land transfer changes. The correlation between arable land and RSEI is weak, while coastal mudflats are negatively correlated with RSEI, with the minimum absolute value of the dynamic degree of land use being −1.01%, and significant land transfer changes. There is no correlation between forest land and RSEI. Our research results can provide data support for the eco-environmental protection and sustainable development of the Yellow River Delta region and help local governments to take corresponding measures. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring of Resources and Ecological Environment)
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20 pages, 7201 KiB  
Article
Establishment of an Ecological Security Pattern under Arid Conditions Based on Ecological Carrying Capacity: A Case Study of Arid Area in Northwest China
by Xiaoyan Cao, Jizong Jiao, Xiuli Liu, Wanyang Zhu, Haoran Wang, Huiqing Hao and Jingtao Lu
Sustainability 2022, 14(23), 15799; https://doi.org/10.3390/su142315799 - 28 Nov 2022
Cited by 2 | Viewed by 1260
Abstract
With the expansion of the social economy and adjustment of environmental policies, particularly with the onset of development policies for the western region, ecosystems in the arid areas of Northwest China have undergone profound changes. This study collected soil, topographical, climate, and nighttime [...] Read more.
With the expansion of the social economy and adjustment of environmental policies, particularly with the onset of development policies for the western region, ecosystems in the arid areas of Northwest China have undergone profound changes. This study collected soil, topographical, climate, and nighttime light data to develop a set of ecological vulnerability assessment indexes based on the background ecological characteristics of the arid areas of Northwest China. The spatiotemporal evolution of ecological carrying capacity was analyzed by our team using Spatial Principal Component Analysis (SPCA) in 2000, 2007, 2012, and 2018 to construct an ecological security pattern. The results revealed that the ecological carrying capacities of the arid areas in the northwest were primarily weak, albeit decreasing, while those areas with strong carrying capacities were increasing. In terms of spatial distribution, the ecological carrying capacities of the Hexi, Northern Xinjiang, and Western Inner Mongolia regions were on the rise, while those of the Southern Xinjiang region were declining. The Minimum Cumulative Resistance (MCR) model was used to extract 51 road-type, river-type, and green corridors with a total length of 7285.43 km. A total of 71 nodes representing important patches, wet rivers, and ecologically fragile areas were extracted. According to the calculated results, the arid region of the northwest was divided into 16 ecological security patterns, which were optimized according to changes in their ecological carrying capacities. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring of Resources and Ecological Environment)
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15 pages, 4785 KiB  
Article
Vegetation Dynamics and Climate from A Perspective of Lag-Effect: A Study Case in Loess Plateau, China
by Chunyang Liu, Chao Liu, Qianqian Sun, Tianyang Chen and Ya Fan
Sustainability 2022, 14(19), 12450; https://doi.org/10.3390/su141912450 - 30 Sep 2022
Cited by 4 | Viewed by 1450
Abstract
With global warming, the law of climate change is more and more complex, so it is of great significance to analyze the response mechanism of vegetation change to climate change. The Loess Plateau (LP) is a vulnerable area, but we must explore the [...] Read more.
With global warming, the law of climate change is more and more complex, so it is of great significance to analyze the response mechanism of vegetation change to climate change. The Loess Plateau (LP) is a vulnerable area, but we must explore the mechanism between climate and vegetation for decision-makers to make adequate plans to better govern this population-intensive but ecological-fragile area. Our study analyzed the vegetation variation in a long-term period from 1982 to 2015 and its relationship with precipitation and temperature. We innovatively leverage the weighted time-lag method to detect the different contributions of a specific climatic factor from different months to vegetation growth. Moreover, we used such weighted accumulated climatic factors to find the relationships between precipitation/temperature and different types of vegetation. The main findings are as follows: (i) For different degrees of temperature and precipitation, different vegetation has different performance characteristics in different months from 1982 to 2015. Moreover, precipitation is the major driver of vegetation growth in the LP. (ii) The response of vegetation possesses some time-lag effect on climate and exhibits spatial heterogeneity in the LP, which may be related to the characteristics of different climate zones and different vegetation. (iii) The effect of the same climatic factor on different vegetation accounts for a certain proportion of different months in the LP. Climate possesses a cumulative effect in three months on vegetation and different climatic factors have different time lags to the same vegetation type. It has a complicated interaction between vegetation growth and climate change. This paper uses the weighted time-lag method to investigate the relationship between vegetation growth and climatic factors, whilst considering how the time-lag effect can explain the changes that occur in the process of vegetation growth to a large extent. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring of Resources and Ecological Environment)
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19 pages, 3933 KiB  
Article
Assessment of Ecosystem Services: Spatio-Temporal Analysis and the Spatial Response of Influencing Factors in Hainan Province
by Binyu Ren, Qianfeng Wang, Rongrong Zhang, Xiaozhen Zhou, Xiaoping Wu and Qing Zhang
Sustainability 2022, 14(15), 9145; https://doi.org/10.3390/su14159145 - 26 Jul 2022
Cited by 10 | Viewed by 1814
Abstract
The impact of human activities on ecosystems is receiving increasing attention because their mechanisms of action are complex; the spatial response of ecosystem service drivers still needs to be explored further. This study evaluated three ecosystem services—water yield, soil conservation, and carbon storage—in [...] Read more.
The impact of human activities on ecosystems is receiving increasing attention because their mechanisms of action are complex; the spatial response of ecosystem service drivers still needs to be explored further. This study evaluated three ecosystem services—water yield, soil conservation, and carbon storage—in Hainan Province from 2000 to 2020; we analyzed the spatial and temporal changes of the ecosystem services, and the spatial heterogeneity of the influencing factors. The results were as follows: (1) The average water yield, soil conservation and carbon storage of Hainan Province from 2000 to 2020 were 42.36 billion, 8.01×108 t and 1.52 × 107 t, respectively. Overall, the ecosystem services were relatively weak at lower elevations. (2) There were obvious hot spots and cold spots in the water yield and soil conservation, and the hot spot distribution of carbon storage was not obvious. (3) There were differences between the ecosystem services for different land use types; trade-off relationships only appeared between unused land and ecosystem services. (4) The precipitation, normalized difference vegetation index and elevation factors had great impacts on the ecosystem services. Most of the human activity factors showed a significant nonlinear enhancement effect during their interaction. Population and elevation had obvious spatial differentiation effects on the water yield and carbon storage services. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring of Resources and Ecological Environment)
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