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Ecosystem Changes in Tibetan and Other Alpine Regions from Earth Observation

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 16360

Special Issue Editors

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: algorithm development; time-series remote sensing; vegetation phenology
Special Issues, Collections and Topics in MDPI journals
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Interests: plant phenology; climate change ecology; vegetation remote sensing; alpine ecosystem
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Bin Fu
E-Mail Website
Guest Editor
Institute of Mountain Hazards and Environment Chinese Academy of Sciences, Chengdu 610041, China
Interests: alpine ecosystem; global change

Special Issue Information

Dear Colleagues,

During the past few decades, climate change has substantially modified the structure, function, and service of various ecosystems, particularly in alpine regions where vegetation is sensitive to climate warming, having had a wide range of effects on land surface processes, with far-reaching ecological and climatical influences. Increasing investigations based on Earth observations focus on land surface changes in alpine ecosystems, such as grassland coverage, land surface vegetation phenology, vegetation biomass (gross primary productivity), and river conservation, regulated by intensive anthropogenic activities, e.g., grazing, engineering and urbanization. Better understanding these changing processes and underlying causes could improve our ability to predict future changes and manage alpine ecosystems in response to the projected climate warming. Currently, governments have taken part in activities regarding this aspect, such as the 2nd Scientific Expedition to the Qinghai–Tibet Plateau organized by the Chinese government.

In this context, a Special Issue entitled “Ecosystem Changes in Tibetan and Other Alpine Regions from Earth Observation” is being planned in the Remote Sensing journal. Research or review articles regarding observations and attributions of ecosystem changes and their impacts on ecosystem services, land surface and climate processes and land–atmosphere interactions are welcome. It should be noted that remote sensing data (satellite, drone or remote sensing instruments in field measurements) should be one of the main used data.

We look forward to receiving your contributions.

Dr. Ruyin Cao
Prof. Dr. Miaogen Shen
Prof. Dr. Bin Fu
Guest Editors

Manuscript Submission Information

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Keywords

  • alpine environment
  • alpine vegetation
  • anthropogenic activity
  • climate change
  • ecosystem structure and function
  • land surface processes
  • Tibetan plateau

Published Papers (9 papers)

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Editorial

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4 pages, 484 KiB  
Editorial
An Overview of Ecosystem Changes in Tibetan and Other Alpine Regions from Earth Observation
Remote Sens. 2022, 14(19), 4839; https://doi.org/10.3390/rs14194839 - 28 Sep 2022
Viewed by 867
Abstract
Alpine ecosystems have shown sensitive responses to climate change during the past few decades [...] Full article
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Research

Jump to: Editorial

17 pages, 12694 KiB  
Article
Reconstructing High-Spatiotemporal-Resolution (30 m and 8-Days) NDVI Time-Series Data for the Qinghai–Tibetan Plateau from 2000–2020
Remote Sens. 2022, 14(15), 3648; https://doi.org/10.3390/rs14153648 - 29 Jul 2022
Cited by 13 | Viewed by 2421
Abstract
As the largest and highest alpine ecoregion in the world, the Qinghai–Tibetan Plateau (QTP) is extremely sensitive to climate change and has experienced extraordinary warming during the past several decades; this has greatly affected various ecosystem processes in this region such as vegetation [...] Read more.
As the largest and highest alpine ecoregion in the world, the Qinghai–Tibetan Plateau (QTP) is extremely sensitive to climate change and has experienced extraordinary warming during the past several decades; this has greatly affected various ecosystem processes in this region such as vegetation production and phenological change. Therefore, numerous studies have investigated changes in vegetation dynamics on the QTP using the satellite-derived normalized-difference vegetation index (NDVI) time-series data provided by the Moderate-Resolution Imaging Spectroradiometer (MODIS). However, the highest spatial resolution of only 250 m for the MODIS NDVI product cannot meet the requirement of vegetation monitoring in heterogeneous topographic areas. In this study, therefore, we generated an 8-day and 30 m resolution NDVI dataset from 2000 to 2020 for the QTP through the fusion of 30 m Landsat and 250 m MODIS NDVI time-series data. This dataset, referred to as QTP-NDVI30, was reconstructed by employing all available Landsat 5/7/8 images (>100,000 scenes) and using our recently developed gap-filling and Savitzky–Golay filtering (GF-SG) method. We improved the original GF-SG approach by incorporating a module to process snow contamination when applied to the QTP. QTP-NDVI30 was carefully evaluated in both quantitative assessments and visual inspections. Compared with reference Landsat images during the growing season in 100 randomly selected subregions across the QTP, the reconstructed 30 m NDVI images have an average mean absolute error (MAE) of 0.022 and a spatial structure similarity (SSIM) above 0.094. We compared QTP-NDVI30 with upscaled cloud-free PlanetScope images in some topographic areas and observed consistent spatial variations in NDVI between them (averaged SSIM = 0.874). We further examined an application of QTP-NDVI30 to detect vegetation green-up dates (GUDs) and found that QTP-NDVI30-derived GUD data show general agreement in spatial patterns with the 250 m MODIS GUD data, but provide richer spatial details (e.g., GUD variations at the subpixel scale). QTP-NDVI30 provides an opportunity to monitor vegetation and investigate land-surface processes in the QTP region at fine spatiotemporal scales. Full article
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26 pages, 58242 KiB  
Article
Analyzing the Spatiotemporal Vegetation Dynamics and Their Responses to Climate Change along the Ya’an–Linzhi Section of the Sichuan–Tibet Railway
Remote Sens. 2022, 14(15), 3584; https://doi.org/10.3390/rs14153584 - 26 Jul 2022
Cited by 8 | Viewed by 1525
Abstract
Vegetation dynamics and their responses to climate change are of significant spatial and temporal heterogeneity. The Sichuan–Tibet Railway (STR) is a major construction project of the 14th Five-Year Plan for Economic and Social Development of the People’s Republic of China that is of [...] Read more.
Vegetation dynamics and their responses to climate change are of significant spatial and temporal heterogeneity. The Sichuan–Tibet Railway (STR) is a major construction project of the 14th Five-Year Plan for Economic and Social Development of the People’s Republic of China that is of great significance to promoting the social and economic development of Sichuan–Tibet areas. The planned railway line crosses areas with a complex geological condition and fragile ecological environment, where the regional vegetation dynamics are sensitive to climate change, topographic conditions and human activities. So, analyzing the vegetation variations in the complex vertical ecosystem and exploring their responses to hydrothermal factors are critical for providing technical support for the ecological program’s implementation along the route of the planned railway line. Based on MOD13Q1 Normalized Difference Vegetation Index (NDVI) data for the growing season (May to October) during 2001–2020, a Theil-Sen trend analysis, Mann–Kendall test, Hurst exponent analysis and partial correlation analysis were used to detect the vegetation dynamics, predict the vegetation sustainability, examine the relationship between vegetation change and hydrothermal factors, regionalize the driving forces for vegetation growth and explore the interannual variation pattern of driving factors. The growing season NDVI along the Ya’an–Linzhi section of the STR showed a marked rate of increase (0.0009/year) during the past 20 years, and the vegetation’s slight improvement areas accounted for the largest proportion (47.53%). Among the three hydrothermal parameters (temperature, precipitation and radiation), the correlation between vegetation growth and the temperature was the most significant, and the vegetation response to precipitation was the most immediate. The vegetation changes were affected by the combined impact of climatic and non-climatic factors, and the proportion of hydrothermal factors’ combined driving force slightly increased during the study period. Based on the Hurst exponent, the future vegetation sustainability of the area along the Ya’an–Linzhi section of the STR faces a risk of degradation, and more effective conservations should be implemented during the railway construction period to protect the regional ecological environment. Full article
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14 pages, 5006 KiB  
Article
Increasing Impact of Precipitation on Alpine-Grassland Productivity over Last Two Decades on the Tibetan Plateau
Remote Sens. 2022, 14(14), 3430; https://doi.org/10.3390/rs14143430 - 17 Jul 2022
Cited by 8 | Viewed by 1468
Abstract
Understanding the importance of temperature and precipitation on plant productivity is beneficial, to reveal the potential impact of climate change on vegetation growth. Although some studies have quantified the response of vegetation productivity to climate change at local, regional, and global scales, changes [...] Read more.
Understanding the importance of temperature and precipitation on plant productivity is beneficial, to reveal the potential impact of climate change on vegetation growth. Although some studies have quantified the response of vegetation productivity to climate change at local, regional, and global scales, changes in climatic constraints on vegetation productivity over time are not well understood. This study combines the normalized difference vegetation index (NDVI) and the net primary production (NPP) modeled by CASA during the plant-growing season, to quantify the interplay of climatic (growing-season temperature and precipitation, GST and GSP) constraints on alpine-grassland productivity on the Tibetan Plateau, as well as the temporal dynamics of these constraints. The results showed that (1) 42.2% and 36.3% of grassland NDVI and NPP on the Tibetan Plateau increased significantly from 2000 to 2019. GSP controlled grassland growth in dryland regions, while humid grasslands were controlled by the GST. (2) The response strength of the NDVI and NPP to precipitation (partial correlation coefficient RNDVI-GSP and RNPP-GSP) increased substantially between 2000 and 2019. Especially, the RNDVI-GSP and RNPP-GSP increased from 0.14 and 0.01 in the first 10year period (2000–2009) to 0.83 and 0.78 in the second 10-year period (2010–2019), respectively. As a result, the controlling factor for alpine-grassland productivity variations shifted from temperature during 2000–2009 to precipitation during 2010–2019. (3) The increase in precipitation constraints was mainly distributed in dryland regions of the plateau. This study highlights that the climatic constraints on alpine-grassland productivity might change under ongoing climate change, which helps the understanding of the ecological responses and helps predict how vegetation productivity changes in the future. Full article
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14 pages, 12551 KiB  
Article
Elevational Gradient of Climate-Driving Effects on Cropland Ecosystem Net Primary Productivity in Alpine Region of the Southwest China
Remote Sens. 2022, 14(13), 3069; https://doi.org/10.3390/rs14133069 - 26 Jun 2022
Cited by 2 | Viewed by 1347
Abstract
Investigating elevational gradient of climate driving effects on cropland ecosystem net primary productivity (NPP) plays an important role in food security in alpine region. We simulated cropland NPP by coupling a remote sensing model with an ecosystem process model and explored elevational gradient [...] Read more.
Investigating elevational gradient of climate driving effects on cropland ecosystem net primary productivity (NPP) plays an important role in food security in alpine region. We simulated cropland NPP by coupling a remote sensing model with an ecosystem process model and explored elevational gradient of climate driving effects on it in an alpine region of the southwest China during 1981–2014. The results showed that cropland NPP increased significantly with a rate of 3.85 gC m−2 year−1 year−1 under significant increasing solar radiation and climate warming and drying, among which the increasing solar radiation was the main driving factor of the increasing NPP. The driving effect of climate warming on cropland NPP shifted from negative at low elevations to positive at high elevations, which was caused by the fragile ecosystem characteristics and frequent drought at low elevations and a higher temperature sensitivity of cropland ecosystem at high elevations. Different effects of climate warming on NPP change at different elevations caused different results when we analyzed the climate-driving effects on cropland NPP at different spatial scales. These results reminded us that we should take the elevational gradient of climate driving effects into account when we manage food security in the alpine region. Full article
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22 pages, 3157 KiB  
Article
Characteristics of Greening along Altitudinal Gradients on the Qinghai–Tibet Plateau Based on Time-Series Landsat Images
Remote Sens. 2022, 14(10), 2408; https://doi.org/10.3390/rs14102408 - 17 May 2022
Cited by 11 | Viewed by 1743
Abstract
The Qinghai–Tibet Plateau (QTP) is ecologically fragile and is especially sensitive to climate change. Previous studies have shown that the vegetation on the QTP is undergoing overall greening with variations along altitudinal gradients. However, the mechanisms that cause the differences in the spatiotemporal [...] Read more.
The Qinghai–Tibet Plateau (QTP) is ecologically fragile and is especially sensitive to climate change. Previous studies have shown that the vegetation on the QTP is undergoing overall greening with variations along altitudinal gradients. However, the mechanisms that cause the differences in the spatiotemporal patterns of vegetation greening among different types of terrain and vegetation have not received sufficient attention. Therefore, in this study, we used a Landsat NDVI time-series for the period 1992–2020 and climate data to observe the effects of terrain and vegetation types on the spatiotemporal patterns in vegetation greening on the QTP and to analyze the factors driving this greening using the geographical detector and the velocity of the vertical movement of vegetation greenness isolines. The results showed the following: (1) The vertical movement of the vegetation greenness isolines was affected by the temperature and precipitation at all elevations. The precipitation had a more substantial effect than the temperature below 3000 m. In contrast, above 3000 m, the temperature had a greater effect than the precipitation. (2) The velocity of the vertical movement of the vegetation greenness isolines of woody plants was higher than that of herbaceous plants. (3) The influence of slope on the vertical movement of vegetation greenness isolines was more significant than that of the aspect. The results of this study provided details of the spatiotemporal differences in vegetation greening between different types of terrain and vegetation at a 30-m scale as well as of the underlying factors driving this greening. These results will help to support ecological protection policies on the QTP. Full article
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20 pages, 4913 KiB  
Article
Driving Climatic Factors at Critical Plant Developmental Stages for Qinghai–Tibet Plateau Alpine Grassland Productivity
Remote Sens. 2022, 14(7), 1564; https://doi.org/10.3390/rs14071564 - 24 Mar 2022
Cited by 11 | Viewed by 1860
Abstract
Determining the driving climatic factors at critical periods and potential legacy effects is crucial for grassland productivity predictions on the Qinghai–Tibet Plateau (QTP). However, studies with limited and ex situ ground samples from highly heterogeneous alpine meadows brought great uncertainties. This study determined [...] Read more.
Determining the driving climatic factors at critical periods and potential legacy effects is crucial for grassland productivity predictions on the Qinghai–Tibet Plateau (QTP). However, studies with limited and ex situ ground samples from highly heterogeneous alpine meadows brought great uncertainties. This study determined the key climatic factors at critical plant developmental stages and the impact of previous plant growth status for interannual aboveground net primary productivity (ANPP) variations in different QTP grassland types. We hypothesize that the impact of climatic factors on grassland productivity varies in different periods and different vegetation types, while its legacy effects are not great. Pixel-based partial least squares regression was used to associate interannual ANPP with precipitation and air temperature at different developmental stages and prior-year ANPP from 2000 to 2019 using remote sensing techniques. Results indicated different findings from previous studies. Precipitation at the reproductive stage (July–August) was the most prominent controlling factor for ANPP which was also significantly affected by precipitation and temperature at the withering (September–October) and dormant stage (November–February), respectively. The influence of precipitation was more significant in alpine meadows than in alpine steppes, while the differentiated responses to climatic factors were attributed to differences in water consumption at different developmental stages induced by leaf area changes, bud sprouting, growth, and protection from frost damage. The prior-year ANPP showed a non-significant impact on ANPP of current year, except for alpine steppes, and this impact was much less than that of current-year climatic factors, which may be attributed to the reduced annual ANPP variations related to the inter-annual carbon circulation of alpine perennial herbaceous plants and diverse root/shoot ratios in different vegetation types. These findings can assist in improving the interannual ANPP predictions on the QTP under global climate change. Full article
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19 pages, 7388 KiB  
Article
Evaluation of Reasonable Stocking Rate Based on the Relative Contribution of Climate Change and Grazing Activities to the Productivity of Alpine Grasslands in Qinghai Province
Remote Sens. 2022, 14(6), 1455; https://doi.org/10.3390/rs14061455 - 18 Mar 2022
Cited by 9 | Viewed by 1745
Abstract
An accurate assessment of the stocking rate is crucial for maintaining the stable function and the sustainable use of the alpine grassland ecosystem. A new scenario design method to evaluate the reasonable stocking rate is presented in the current work. First, climate change [...] Read more.
An accurate assessment of the stocking rate is crucial for maintaining the stable function and the sustainable use of the alpine grassland ecosystem. A new scenario design method to evaluate the reasonable stocking rate is presented in the current work. First, climate change is quantified by potential net primary productivity (NPPp) and measured by adopting the Zhou Guangsheng model, and the NPP generated by anthropogenic activities (NPPh) is estimated by the distinction between NPPp and actual NPP (NPPa) calculated with the application of the Carnegie–Ames–Stanford Approach (CASA) model. Second, using the NPPh and actual grassland productivity consumed by livestock (NPPac), the reasonable stocking rate is obtained. Finally, the driving factors of NPP change in alpine grassland and the reasonable stocking rate are clarified in Qinghai Province during 2005–2018. The results reveal that the temperature of alpine grassland in Qinghai Province has a slight upward trend from 2005 to 2018, and precipitation displays a downward trend. The overall NPPp of alpine grassland demonstrated a downward trend, and precipitation is regarded as the major influencing factor. In addition, the overall NPPh of alpine grassland exhibited a downward trend. The NPPa demonstrated an overall upward trend, where 58.32% of the regional NPPa is in a state of growth, and 41.68% of the regional NPPa is in a state of degradation. According to contribution analysis, anthropogenic activities provided the primary driving factor to promote the restoration of alpine grassland in Qinghai Province. Moreover, the stocking rate must be reduced in 60.77% of the alpine grasslands in Qinghai Province, mostly situated in the eastern and southwestern parts of Qinghai Province, and the other areas must not increase future stocking rates. The current study can theoretically and technically support the construction of Qinghai as the green organic agricultural and livestock product demonstration province and the creation of an ecological civilization highland. Full article
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18 pages, 5340 KiB  
Article
Precipitation Dominates the Relative Contributions of Climate Factors to Grasslands Spring Phenology on the Tibetan Plateau
Remote Sens. 2022, 14(3), 517; https://doi.org/10.3390/rs14030517 - 21 Jan 2022
Cited by 10 | Viewed by 1810
Abstract
Temperature and precipitation are the primary regulators of vegetation phenology in temperate zones. However, the relative contributions of each factor and their underlying combined effect on vegetation phenology are much less clear, especially for the grassland of the Tibetan Plateau To quantify the [...] Read more.
Temperature and precipitation are the primary regulators of vegetation phenology in temperate zones. However, the relative contributions of each factor and their underlying combined effect on vegetation phenology are much less clear, especially for the grassland of the Tibetan Plateau To quantify the contribution of each factor and the potential interactions, we conducted redundancy analysis for grasslands spring phenology on the Tibetan Plateau during 2000–2017. Generally, the individual contribution of temperature and precipitation to grasslands spring phenology (the start of growing season (SOS)) was lower, despite a higher correlation coefficient, which further implied that these factors interact to affect the SOS. The contributions of temperature and precipitation to the grasslands spring phenology varied across space on the Tibetan Plateau, and these spatial heterogeneities can be mainly explained by the spatial gradient of long-term average precipitation during spring over 2000–2017. Specifically, the SOS for meadow was dominated by the mean temperature in spring (Tspring) in the eastern wetter ecoregion, with an individual contribution of 24.16% (p < 0.05), while it was strongly negatively correlated with the accumulated precipitation in spring (Pspring) in the western drier ecoregion. Spatially, a 10 mm increase in long-term average precipitation in spring resulted in an increase in the contribution of Tspring of 2.0% (p < 0.1) for meadow, while it caused a decrease in the contribution of Pspring of −0.3% (p < 0.05). Similarly, a higher contribution of Pspring for steppe was found in drier ecoregions. A spatial decrease in precipitation of 10 mm increased the contribution of Pspring of 1.4% (p < 0.05). Considering these impacts of precipitation on the relative contribution of warming and precipitation to the SOS, projected climate change would have a stronger impact on advancing SOS in a relatively moist environment compared to that of drier areas. Hence, these quantitative interactions and contributions must be included in current ecosystem models, mostly driven by indicators with the direct and the overall effect in response to projected climate warming. Full article
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