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Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (15 August 2022) | Viewed by 50523

Special Issue Editors

Dr. Xuguang Tang

E-Mail Website
Guest Editor
Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou 311121, China
Interests: carbon cycling; water-carbon coupling relationship; ecosystem quality monitoring; remote sensing; vegetation phenology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hong Yang

E-Mail Website
Guest Editor
Department of Geography and Environmental Science, University of Reading, Reading RG6 6AB, UK
Interests: education for sustainable development; climate change; environmental pollution; RS applications in environmental and geographical sciences; AI for environmental science
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mingguo Ma

E-Mail Website1 Website2
Guest Editor
School of Geographical Sciences, Southwest University, Chongqing 400715, China
Interests: remote sensing; carbon cycle; climate change; land surface process simulation; water use efficiency; karst water resource
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yanlian Zhou

E-Mail Website
Guest Editor
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Interests: monitoring and modelling of land surface processes

Special Issue Information

Dear Colleagues,

Since its establishment in 2003, the US–China Carbon Consortium (USCCC) has brought together scientists from different institutions and universities in the United States, China, and other countries to participate in this important research area. Following the objectives to explore the mechanism of the disturbed ecosystem process and the changing trend in the context of global climate change, the 17th USCCC Annual Meeting will be held in Chongqing, the youngest municipality in China, from July 29  to August 2, 2021. This year's annual meeting will be based on the USCCC's mission to provide an open and collaborative academic exchange platform for research on ecosystems, including ecosystem water, heat, carbon flux processes, mechanisms, simulations, responses to climate change and human activities, as well as adaptive management.

This Special Issue celebrates the 17th Annual Meeting of USCCC, showcasing the depth and variety of research that it enables. We invite the following contributions based on various datasets (e.g., remote sensing such as optical remote sensing, microwave remote sensing, lidar, solar-induced chlorophyll fluorescence and field observation data such as eddy-covariance, transect sampling) and techniques (e.g., synergy and integration of various remotely sensed data, model–data fusion). Target variables include but are not limited to the following: net ecosystem exchange and its components including gross primary productivity and respiration, evapotranspiration and its partitioning in transpiration and evaporation, water use efficiency, or vegetation photosynthesis. In particular, manuscripts are encouraged to focus on the ecologically sensitive areas globally, not just in the United States or China. The topics may include but are not limited to the following:

  • Estimating land-surface carbon, water and energy fluxes across multiple spatiotemporal scales;
  • Intercomparison of multiple-source remote sensing products based on various ecosystem models;
  • Joint forcing by climate factors and human activities on terrestrial carbon, water, and energy cycles;
  • The impacts from extreme events (e.g., drought, flood, wildfire) to better understand and model ecosystem responses;
  • Remote-sensing analysis of the effect of land use/land cover changes on various land-surface mass and energy exchange;
  • Novel approaches to advance the field such as deep learning algorithms, combinations of data-driven and mechanistic models.

Prof. Dr. Xuguang Tang
Dr. Hong Yang
Prof. Dr. Mingguo Ma
Prof. Dr. Yanlian Zhou
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. 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

  • remote sensing
  • carbon fluxes
  • water fluxes
  • energy fluxes
  • ecosystem water-use efficiency
  • climate change
  • human activities/human disturbances
  • land use and land cover change
  • ecologically sensitive areas

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Published Papers (18 papers)

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Research

22 pages, 11421 KiB  
Article
The Response of Land Surface Temperature Changes to the Vegetation Dynamics in the Yangtze River Basin
by Jinlian Liu, Shiwei Liu, Xuguang Tang, Zhi Ding, Mingguo Ma and Pujia Yu
Remote Sens. 2022, 14(20), 5093; https://doi.org/10.3390/rs14205093 - 12 Oct 2022
Cited by 16 | Viewed by 2334
Abstract
Land surface temperature (LST) is a key parameter in the study of surface energy balance and climate change from local through to global scales. Vegetation has inevitably influenced the LST by changing the surface properties. However, the thermal environment pattern in the Yangtze [...] Read more.
Land surface temperature (LST) is a key parameter in the study of surface energy balance and climate change from local through to global scales. Vegetation has inevitably influenced the LST by changing the surface properties. However, the thermal environment pattern in the Yangtze River Basin (YRB) still remains unclear after the implementation of large-scale ecological restoration projects. In this study, the temporal and spatial variation characteristics of LST were analyzed based on the Theil–Sen estimator, Mann–Kendall trend analysis and Hurst exponent from 2003 to 2021. The relationships between vegetation and LST were further revealed by using correlation analysis and trajectory-based analysis. The results showed that the interannual LST was in a state of fluctuation and rise, and the increasing rate at night time (0.035 °C·yr−1) was faster than that at day time (0.007 °C·yr−1). An obvious cooling trend could be identified from 2007 to 2012, followed by a rapid warming. Seasonally, the warming speed was the fastest in summer and the slowest in autumn. Additionally, it was found that autumn LST had a downward trend of 0.073 °C·yr−1 after 2015. Spatially, the Yangtze River Delta, Hubei province, and central Sichuan province had a significant warming trend in all seasons, except autumn. The northern Guizhou province and Chongqing showed a remarkable cooling trend only in autumn. The Hurst exponent results indicated that the spring LST change was more consistent than the other three seasons. It was found by studying the effect of land cover types on LST changes that sparse vegetation had a more significant effect than dense vegetation. Vegetation greening contributed 0.0187 °C·yr−1 to the increase in LST in winter, which was spatially concentrated in the central region of the YRB. For the other three seasons, vegetation greening slowed the LST increase, and the degree of the effect decreased sequentially in autumn, summer, spring and winter. These results improve the understanding of past and future variations in LST and highlight the importance of vegetation for temperature change mitigation. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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18 pages, 3941 KiB  
Article
Contributions of Climate Change, Vegetation Growth, and Elevated Atmospheric CO2 Concentration to Variation in Water Use Efficiency in Subtropical China
by Jianyong Xiao, Binggeng Xie, Kaichun Zhou, Junhan Li, Jing Xie and Chao Liang
Remote Sens. 2022, 14(17), 4296; https://doi.org/10.3390/rs14174296 - 31 Aug 2022
Cited by 11 | Viewed by 2151
Abstract
Ecosystem water use efficiency (WUE) plays an important role in maintaining the carbon assimilation–water transpiration balance in ecosystems. However, spatiotemporal changes in WUE in the subtropical region of China (STC) and the impact of driving forces remain unclear. In this study, we analyzed [...] Read more.
Ecosystem water use efficiency (WUE) plays an important role in maintaining the carbon assimilation–water transpiration balance in ecosystems. However, spatiotemporal changes in WUE in the subtropical region of China (STC) and the impact of driving forces remain unclear. In this study, we analyzed the spatiotemporal variation in WUE in the STC and used ridge regression combined with path analysis to identify direct and indirect effects of climate change, vegetation growth, and elevated atmospheric CO2 concentration (Ca) on the interannual trend in WUE. We then quantified the actual and relative contributions of these drivers to WUE change based on the sensitivity of these variables on WUE and the trends of the variables themselves. Results reveal a mean WUE of 1.57 g C/m2/mm in the STC. The annual WUE series showed a descending trend with a decline rate of 0.0006 g C/m2/mm/year. The annual average temperature (MAT) and leaf area index (LAI) had strong positive direct effects on the WUE, while the vapor pressure deficit (VPD) had a strong negative direct effect. Opposite direct and indirect effects offset each other, but overall there was a total positive effect of Ca and VPD on WUE. In terms of actual contribution, LAI, Ca, and VPD were the main driving factors; LAI caused WUE to increase by 0.0026 g C/m2/mm/year, while Ca and VPD caused WUE to decrease by 0.0021 and 0.0012 g C/m2/mm/year, respectively. In terms of relative contribution, LAI dominated the WUE trend, although Ca and VPD were also important factors. Other drivers contributed less to the WUE trend. The results of this study have implications for ecological management and restoration under environmental climate change conditions in subtropical regions worldwide. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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17 pages, 5690 KiB  
Article
Spatio-Temporal Characteristics of the Evapotranspiration in the Lower Mekong River Basin during 2008–2017
by Xin Pan, Suyi Liu, Yingbao Yang, Chaoshuai You, Zi Yang, Wenying Xie and Tengteng Li
Remote Sens. 2022, 14(11), 2609; https://doi.org/10.3390/rs14112609 - 29 May 2022
Cited by 5 | Viewed by 2320
Abstract
Droughts and floods have occurred frequently in the Lower Mekong River Basin in recent years. Obtaining the evapotranspiration (ET) in the basin helps people to better understand water cycle and water resources. In this study, we retrieved and validated ET in the Lower [...] Read more.
Droughts and floods have occurred frequently in the Lower Mekong River Basin in recent years. Obtaining the evapotranspiration (ET) in the basin helps people to better understand water cycle and water resources. In this study, we retrieved and validated ET in the Lower Mekong Basin over multiple years (from 2008 to 2017) using remote sensing products. Based on the retrieval ET, we analyzed the spatial-temporal variation of ET and influencing factors at the monthly, seasonal, and inter-annual scale respectively. The results revealed that the overall variation trend of ET at annual scale slightly increased during 2008 to 2017, with the highest annual ET being 1198 mm/year in 2015 and the lowest annual ET being 949 mm/year in 2008. At the seasonal scale, ET in the rainy season was lower than the dry season; at the monthly scale, March had the highest monthly ET (101 mm/month) while July had the lowest monthly ET (73 mm/month). Spatial analyzing showed that ET in the margin of this region was higher (with on average about 1250 mm/year) and lower in the middle (with on average about 840 mm/year), and monthly ET changed mostly in forest areas with the difference of 60 mm/month. Influencing analyzing results showed that ET was mainly driven by solar radiation and near-surface temperature, and precipitation had an inhibitory effect on ET in the rainy season months. The study also showed that forests in the basin are very sensitive to solar radiation, with a correlation coefficient of 0.89 in March (the month with the highest ET) and 0.45 in July (the month with the lowest ET). Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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13 pages, 3503 KiB  
Article
Ozone Profiles, Precursors, and Vertical Distribution in Urban Lhasa, Tibetan Plateau
by Jiayan Yu, Lingshuo Meng, Yang Chen, Huifang Zhang and Jianguo Liu
Remote Sens. 2022, 14(11), 2533; https://doi.org/10.3390/rs14112533 - 25 May 2022
Cited by 7 | Viewed by 2166
Abstract
Near-surface ozone is one of the significant issues in the troposphere. Recently, ozone pollution in Lhasa at an altitude of 3600 m has caused attention. The current knowledge of ozone formation in Lhasa city is still minimal. In this work, the profile of [...] Read more.
Near-surface ozone is one of the significant issues in the troposphere. Recently, ozone pollution in Lhasa at an altitude of 3600 m has caused attention. The current knowledge of ozone formation in Lhasa city is still minimal. In this work, the profile of VOCs during early summer was investigated, and alkanes were the most critical group of VOCs. The urban areas of Lhasa are under transition conditions and controlled by both VOCs and NOx. Moreover, the most effective way to decrease ozone formation is to reduce the emissions of anthropogenic VOCs and NOx. The vertical distribution of tropospheric ozone was investigated using differential absorption lidar (DIAL). The results show that ozone concentrations decreased with the elevation of altitudes over Lhasa. The vertical distribution showed clear diurnal trends and that a high ozone concentration appeared at night because of the afternoon’s accumulated O3 generated by photochemical reactions. Ozone in Lhasa is mainly distributed between 0.4 km and 0.6 km. Local generation, overnight accumulation, and NOx titration were identified as three ozone distribution modes. This work helps to understand ozone formation and distribution in the Tibetan Plateau. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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17 pages, 9220 KiB  
Article
Spatiotemporal Dynamics of Terrestrial Vegetation and Its Driver Analysis over Southwest China from 1982 to 2015
by Chunhui Duan, Jinghao Li, Yanan Chen, Zhi Ding, Mingguo Ma, Jing Xie, Li Yao and Xuguang Tang
Remote Sens. 2022, 14(10), 2497; https://doi.org/10.3390/rs14102497 - 23 May 2022
Cited by 7 | Viewed by 2706
Abstract
Global environmental changes have been dramatic recently, exerting substantial effects on the structures and functions of terrestrial ecosystems, especially for the ecologically-fragile karst regions. Southwest China is one of the largest karst continuum belts around the world, which also contributes about 1/3 of [...] Read more.
Global environmental changes have been dramatic recently, exerting substantial effects on the structures and functions of terrestrial ecosystems, especially for the ecologically-fragile karst regions. Southwest China is one of the largest karst continuum belts around the world, which also contributes about 1/3 of terrestrial carbon sequestration to China. Therefore, a deep understanding of the long-term changes of vegetation across Southwest China over the past decades is critical. Relying on the long time series of Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies normalized difference vegetation index (GIMMS NDVI3g) data set, this study examined the spatial and temporal patterns of vegetation conditions in Southwest China from 1982 to 2015, as well as their response to the environmental factors including temperature, precipitation and downward shortwave radiation. Multi-year mean NDVI showed that except the northwestern region, the NDVI of Southwest China was large, ranging from 0.5 to 0.8. Meanwhile, nearly 43.7% of the area experienced significant improvements in NDVI, whereas only 3.47% of the area exhibited significant decreases in NDVI. Interestingly, the NDVI in karst area increased more quickly with 1.035 × 10−3/a in comparison with that in the non-karst area with about 0.929 × 10−3/a. Further analysis revealed that temperature is the dominant environmental factor controlling the interannual changes in NDVI, accounting for 48.19% of the area, followed by radiation (3.71%) and precipitation (3.09%), respectively. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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20 pages, 5800 KiB  
Article
Dynamics of the Evaporation of Intercepted Precipitation during the Last Two Decades over China
by Lingyun Yan, Jilong Chen, Lei He, Yongyue Ji, Qingqing Tang, Yuanchao Fan and Daming Tan
Remote Sens. 2022, 14(10), 2474; https://doi.org/10.3390/rs14102474 - 21 May 2022
Cited by 5 | Viewed by 2131
Abstract
The evaporation of intercepted precipitation (Ei) is an important component of evapotranspiration. Investigating the spatial and temporal variations of Ei and its driving factors can improve our understanding of water and energy balance in the context of China’s greening. This study investigated the [...] Read more.
The evaporation of intercepted precipitation (Ei) is an important component of evapotranspiration. Investigating the spatial and temporal variations of Ei and its driving factors can improve our understanding of water and energy balance in the context of China’s greening. This study investigated the spatial and temporal variation of Ei across China during 2001−2020 using PML ET product with a temporal resolution of 8 days and a spatial resolution of 500 m. The results showed that Ei generally decreased from southeast to northwest, which was contributed by the coupled effect of precipitation and vegetation coverage variation across China. Generally, Ei showed an increasing trend over the last two decades with an average changing rate of 0.45 mm/year. The changing rate varied greatly among different regions, with the most obvious change occurring in tropical and humid regions. Precipitation was the most important climatic factor driving the interannual change of Ei over the past two decades, with an average contribution rate of 30.18~37.59%. Relative humidity was the second most important climatic factor following precipitation. Temperature showed contracting contribution in different thermal regions. The contribution rates of NDVI and LAI followed a similar spatial pattern. Both the contribution rates of NDVI and LAI generally increased along the moisture gradient from east to west and generally increased from south to north. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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17 pages, 6513 KiB  
Article
Analysis of Water Yield Changes from 1981 to 2018 Using an Improved Mann-Kendall Test
by Han Gao and Jiaxin Jin
Remote Sens. 2022, 14(9), 2009; https://doi.org/10.3390/rs14092009 - 22 Apr 2022
Cited by 10 | Viewed by 2706
Abstract
Water yield (WY) refers to the difference between precipitation and evapotranspiration (ET), which is vital for available terrestrial water. Climate change has led to significant changes in precipitation and evapotranspiration on a global scale, which will affect the global WY. Nevertheless, how terrestrial [...] Read more.
Water yield (WY) refers to the difference between precipitation and evapotranspiration (ET), which is vital for available terrestrial water. Climate change has led to significant changes in precipitation and evapotranspiration on a global scale, which will affect the global WY. Nevertheless, how terrestrial WY has changed during the past few decades and which factors dominated the WY changes are not fully understood. In this study, based on climate reanalysis and remote sensing data, the spatial and temporal patterns of terrestrial WY were revisited from 1981 to 2018 globally using an improved Mann-Kendall trend test method with a permutation test. The response patterns of WY to precipitation and ET are also investigated. The results show that the global multi-year mean WY is 297.4 mm/a. Based on the traditional Mann-Kendall trend test, terrestrial WY showed a significant (p < 0.05) increase of 5.72% of the total valid grid cells, while it showed a significant decrease of 7.68% of those. After correction using the calibration method, the significantly increasing and decreasing areas are reduced by 10.52% and 10.58% of them, respectively. After the correction, the confirmed increase and decrease in WY are mainly located in Africa, eastern North America and Siberia, and parts of Asia and Oceania, respectively. The dominant factor for increasing WY is precipitation, while that for decreasing WY was the combined effect of precipitation and evapotranspiration. The achievements of this study are beneficial for improving the understanding of WY in response to hydrological variables in the context of climate change. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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20 pages, 7070 KiB  
Article
Simulation of Soil Organic Carbon Content Based on Laboratory Spectrum in the Three-Rivers Source Region of China
by Wei Zhou, Haoran Li, Shiya Wen, Lijuan Xie, Ting Wang, Yongzhong Tian and Wenping Yu
Remote Sens. 2022, 14(6), 1521; https://doi.org/10.3390/rs14061521 - 21 Mar 2022
Cited by 7 | Viewed by 2842
Abstract
Soil organic carbon (SOC) changes affect the land carbon cycle and are also closely related to climate change. Visible-near infrared spectroscopy (Vis-NIRS) has proven to be an effective tool in predicting soil properties. Spectral transformations are necessary to reduce noise and ensemble learning [...] Read more.
Soil organic carbon (SOC) changes affect the land carbon cycle and are also closely related to climate change. Visible-near infrared spectroscopy (Vis-NIRS) has proven to be an effective tool in predicting soil properties. Spectral transformations are necessary to reduce noise and ensemble learning methods can improve the estimation accuracy of SOC. Yet, it is still unclear which is the optimal ensemble learning method exploiting the results of spectral transformations to accurately simulate SOC content changes in the Three-Rivers Source Region of China. In this study, 272 soil samples were collected and used to build the Vis-NIRS simulation models for SOC content. The ensemble learning was conducted by the building of stack models. Sixteen combinations were produced by eight spectral transformations (S-G, LR, MSC, CR, FD, LRFD, MSCFD and CRFD) and two machine learning models of RF and XGBoost. Then, the prediction results of these 16 combinations were used to build the first-step stack models (Stack1, Stack2, Stack3). The next-step stack models (Stack4, Stack5, Stack6) were then made after the input variables were optimized based on the threshold of the feature importance of the first-step stack models (importance > 0.05). The results in this study showed that the stack models method obtained higher accuracy than the single model and transformations method. Among the six stack models, Stack 6 (5 selected combinations + XGBoost) showed the best simulation performance (RMSE = 7.3511, R2 = 0.8963, and RPD = 3.0139, RPIQ = 3.339), and obtained higher accuracy than Stack3 (16 combinations + XGBoost). Overall, our results suggested that the ensemble learning of spectral transformations and simulation models can improve the estimation accuracy of the SOC content. This study can provide useful suggestions for the high-precision estimation of SOC in the alpine ecosystem. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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15 pages, 7996 KiB  
Article
Farmland Shelterbelt Age Mapping Using Landsat Time Series Images
by Rongxin Deng, Zhengran Xu, Ying Li, Xing Zhang, Chunjing Li and Lu Zhang
Remote Sens. 2022, 14(6), 1457; https://doi.org/10.3390/rs14061457 - 18 Mar 2022
Cited by 2 | Viewed by 2043
Abstract
The age of a shelterbelt is not only an important parameter for determining the function of a shelterbelt, it is also strongly related to the biomass and carbon flux of shelterbelt ecosystems. Therefore, timely and accurate identifications of shelterbelt ages are key for [...] Read more.
The age of a shelterbelt is not only an important parameter for determining the function of a shelterbelt, it is also strongly related to the biomass and carbon flux of shelterbelt ecosystems. Therefore, timely and accurate identifications of shelterbelt ages are key for shelterbelt monitoring and management. This study developed a method for estimating shelterbelt age (i.e., years after planting) from a time series of remote sensing images. Firstly, the shelterbelts were divided into three states based on a single remote sensing image of each. Then, a three-stage growth process was established by analysis. Finally, the shelterbelt ages were determined based on time series remote sensing images over a two-year monitoring period in the study area. The actual shelterbelt ages based on field measurements were used to analyze the accuracy of the results. The total number of samples was 243. The results showed that the age identification accuracy was 68.7%. The main factors affecting the identification accuracy were missing images, cloud cover, and the length of the monitoring period. Despite some uncertainties, the proposed method may be used to obtain critical data for shelterbelt management and conducting quick surveys of current shelterbelt conditions over a large area. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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17 pages, 6535 KiB  
Article
Solar-Induced Chlorophyll Fluorescence Trends and Mechanisms in Different Ecosystems in Northeastern China
by Meng Guo, Jing Li, Jianuo Li, Chao Zhong and Fenfen Zhou
Remote Sens. 2022, 14(6), 1329; https://doi.org/10.3390/rs14061329 - 9 Mar 2022
Cited by 4 | Viewed by 3444
Abstract
Solar-induced chlorophyll fluorescence (SIF), when used as a proxy for plant photosynthesis, can provide an indication of the photosynthesis rate and has the potential to improve our understanding of carbon exchange mechanisms within an ecosystem. However, the relationships between SIF and vegetation indices [...] Read more.
Solar-induced chlorophyll fluorescence (SIF), when used as a proxy for plant photosynthesis, can provide an indication of the photosynthesis rate and has the potential to improve our understanding of carbon exchange mechanisms within an ecosystem. However, the relationships between SIF and vegetation indices (VIs) operating within different ecological contexts and the effect of other environmental factors on SIF remain unclear. This study focused on three ecosystems (cropland, forest, and grassland), with different ecological characteristics, located in Northeast China. These areas provide case studies where numerous relationships can be explored, including the correlations between the Orbiting Carbon Observatory-2 (OCO-2) SIF and MODIS products, meteorological factors, and the differences in the relationships between the three different ecosystems. Some interesting results and conclusions were obtained. First, in different ecosystems, the relationships between SIF and MODIS products show different correlations, whereby the enhanced vegetation index (EVI) has a close relationship with SIF in all the three ecosystems of forest, cropland, and grassland. Second, forest-type ecosystems appear to be sensitive to changes in daily temperature, whereas cropland and grassland areas respond more closely to changes in previous 16-day daily minimum temperature. Compared with forest and cropland areas, grasslands were more sensitive to precipitation (although the R2 value was small). Third, different ecosystems have different mechanisms of photosynthesis. Hence, we suggest that it is better to use SIF in areas exhibiting different ecological characteristics, and different models should be employed while simulating SIF. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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17 pages, 5833 KiB  
Article
Remotely Monitoring Vegetation Productivity in Two Contrasting Subtropical Forest Ecosystems Using Solar-Induced Chlorophyll Fluorescence
by Guihua Liu, Yisong Wang, Yanan Chen, Xingqing Tong, Yuandong Wang, Jing Xie and Xuguang Tang
Remote Sens. 2022, 14(6), 1328; https://doi.org/10.3390/rs14061328 - 9 Mar 2022
Cited by 5 | Viewed by 2701
Abstract
Subtropical forests can sequester a larger amount of atmospheric carbon dioxide (CO2) relative to other terrestrial ecosystems through photosynthetic activity and act as an important role in mitigating global climate warming. Compared with the model-based gross primary production (GPP) products, satellite-derived [...] Read more.
Subtropical forests can sequester a larger amount of atmospheric carbon dioxide (CO2) relative to other terrestrial ecosystems through photosynthetic activity and act as an important role in mitigating global climate warming. Compared with the model-based gross primary production (GPP) products, satellite-derived solar-induced fluorescence (SIF) opens a new window for quantification. Here, we used the remotely sensed SIF retrievals, two satellite-driven GPP products including MODIS (GPPMOD) and BESS (GPPBESS), and tower-based GPP measurements at two contrasting subtropical forests to provide a systematic analysis. Our results revealed that GPP and the associated environmental factors exhibited distinct seasonal patterns. However, the peak GPP values had large differences, with stronger GPP in the evergreen needleleaf forest site (8.76 ± 0.71 g C m−2 d−1) than that in the evergreen broadleaf forest site (5.71 ± 0.31 g C m−2 d−1). The satellite-derived SIF retrievals showed great potential in quantifying the variability in GPP, especially for the evergreen needleleaf forest with r reaching up to 0.909 (p < 0.01). GPPMOD and GPPBESS showed distinctly different performances for the two subtropical forests, whereas the GPP estimates by exclusive use of satellite-based SIF data promised well to the tower-based GPP observations. Multi-year evaluation again confirmed the good performance of the SIF-based GPP estimates. These findings will provide an alternative framework for quantifying the magnitude of forest GPP and advance our understanding of the carbon sequestration capacity of subtropical forest ecosystems. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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21 pages, 10149 KiB  
Article
Monitoring of Extreme Agricultural Drought of the Past 20 Years in Southwest China Using GLDAS Soil Moisture
by Xupeng Sun, Peiyu Lai, Shujing Wang, Lisheng Song, Mingguo Ma and Xujun Han
Remote Sens. 2022, 14(6), 1323; https://doi.org/10.3390/rs14061323 - 9 Mar 2022
Cited by 26 | Viewed by 3828
Abstract
Drought can cause severe agricultural economic losses and hinder social and economic development. To manage drought, the process of drought events needs to be described with the help of an effective drought indicator. As a comprehensive variable, soil moisture is an essential indicator [...] Read more.
Drought can cause severe agricultural economic losses and hinder social and economic development. To manage drought, the process of drought events needs to be described with the help of an effective drought indicator. As a comprehensive variable, soil moisture is an essential indicator for describing agricultural drought. In this work, the extreme drought events in southwest China were analysed by the Global Land Data Assimilation System (GLDAS) root zone soil moisture data set. To define the drought quantitatively, a Standardized Soil Moisture Drought Index (SSMI) was calculated using the soil moisture data, then used to get the duration, frequency, and severity of drought events in southwest China. The results showed that the frequency and intensity of drought in southwest China had an apparent upward trend before 2014 and an apparent downward trend since 2014. Moreover, there are apparent differences in the frequency and intensity of drought in various regions of southwest China. Yunnan Province is prone to spring drought events. Guangxi Province and Guizhou Province are prone to spring, autumn and winter droughts, and the intensity of autumn and winter droughts is significantly higher than that of spring droughts. The Sichuan-Chongqing border area is prone to summer drought. We found that the monthly variation of soil moisture in different provinces in southwest China is consistent, but the seasonal variation of drought is different. Meanwhile, the performance of the SSMI was compared to the commonly used drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI). The results showed that the SSMI is more sensitive to drought than both SPEI and PDSI in southwest China. The results also demonstrate that GLDAS soil moisture data can be used to study drought at a small regional scale. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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21 pages, 5292 KiB  
Article
The Impact of Climate Change on Hydrological Processes of the Glacierized Watershed and Projections
by Jing Liu, Aihua Long, Xiaoya Deng, Zhenliang Yin, Mingjiang Deng, Qiang An, Xinchen Gu, Shuoyang Li and Guihua Liu
Remote Sens. 2022, 14(6), 1314; https://doi.org/10.3390/rs14061314 - 9 Mar 2022
Cited by 14 | Viewed by 2956
Abstract
Under the influence of climate change, the hydrological processes of glaciers have undergone significant changes, a fact which is seriously affecting agricultural production in the downstream region of the Tianshan Mountains, China. In order to explore the intrinsic relationship between climate change and [...] Read more.
Under the influence of climate change, the hydrological processes of glaciers have undergone significant changes, a fact which is seriously affecting agricultural production in the downstream region of the Tianshan Mountains, China. In order to explore the intrinsic relationship between climate change and hydrological elements, we proposed an “evaluation-driving-prediction” system to study it. First, we constructed a glacier-enhanced soil and water assessment tool model (GE-SWAT) and used a two-stage calibration method to optimize the model parameters. Next, a scenario analysis was used to evaluate the driving factors of historical runoff changes. Finally, we projected future runoff changes using bias-corrected regional climate model (RCM) outputs. The results of the case study on the Jinghe River Basin in the Tianshan Mountains show that from 1963 to 2016, total runoff increased by 13.3%, 17.7% of which was due to increasing precipitation and 1.8% of which was negated by rising temperatures. The glacier runoff increased by 14.5%, mainly due to the rising temperatures. A 3.4% reduction in snowmelt was caused by a lower snowfall/precipitation ratio, which significantly reduced the snowfall from June to August. The RCM projection indicated that the warming and humidification phenomenon in the study area will continue at least through to the mid-21st century. A consistent increase in glacier runoff and total runoff is projected, but the contribution rate of the glacier runoff will have little to no change under the RCP4.5 and RCP8.5 emission scenarios. Our research demonstrates the simulation performance of the GE-SWAT model in a basin with moderate glacier cover. This method is shown to be efficient in quantifying the impact of climate change on glacier hydrological processes and predicting future streamflow changes, providing a good research reference for similar regions. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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24 pages, 6051 KiB  
Article
Attributions of Evapotranspiration and Gross Primary Production Changes in Semi-Arid Region: A Case Study in the Water Source Area of the Xiong’an New Area in North China
by Sidong Zeng, Hong Du, Jun Xia, Jian Wu and Linhan Yang
Remote Sens. 2022, 14(5), 1187; https://doi.org/10.3390/rs14051187 - 28 Feb 2022
Cited by 7 | Viewed by 2449
Abstract
Investigating the attributions of evapotranspiration (ET) and gross primary production (GPP) changes is of great importance for regional, sustainable water resources and ecological management in semi-arid regions. Based on the simulation conducted during 2000–2019 by improving water-carbon coupling Distributed Time Variant Gain Model, [...] Read more.
Investigating the attributions of evapotranspiration (ET) and gross primary production (GPP) changes is of great importance for regional, sustainable water resources and ecological management in semi-arid regions. Based on the simulation conducted during 2000–2019 by improving water-carbon coupling Distributed Time Variant Gain Model, the trends of ET and GPP were estimated and the driving factors were identified via 10 experimental scenarios in the water source area of the Xiong’an New Area in North China. The results show significant increases both in ET and GPP by 2.4 mm/a and 6.0 gC/m2/a in the region, respectively. At the annual scale, increasing precipitation dominates the ET uptrend. Air temperature, humidity and the interactive effects also contribute to the ET uptrend, and the contributions are 12.8%, 2.0% and 2.3%, respectively, while elevated atmospheric CO2 concentration (eCO2) and solar dimming lead to ET changes of about −7.2% and −12.4%, respectively. For the GPP changes, the increase in GPP is mainly caused by eCO2, increasing precipitation and rising temperature with the contributions of 56.7%, 34.8% and 27.8%, respectively. Solar dimming, humidity and windspeed contribute −6.8%, −4.8% and −3.5% of the GPP changes. Compared to climate change, land use and cover change has smaller effects on both ET and GPP for the few changes in land coverage. At the seasonal scale, ET and GPP increase to a greater extent during the growing season in spring and summer than in autumn and winter. Precipitation, temperature and eCO2 are generally the main causes for ET and GPP changes. Meanwhile, the decreasing humidity and rising temperature are dominant factors for ET and GPP increases, respectively, in winter. Furthermore, solar dimming has strong effects on ET reduction in autumn. The contribution of the interactive effects is much higher on a seasonal scale than annual scale, contributing to considerable decreases in ET and GPP in spring, increases in ET in autumn and winter, and an increase in GPP in winter. This study highlights the importance of considering water-carbon coupling on the attributions of ET and GPP changes and the differentiation of the effects by the abovementioned influential factors at annual and seasonal scales. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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18 pages, 5605 KiB  
Article
Intra-Annual Variability of Evapotranspiration in Response to Climate and Vegetation Change across the Poyang Lake Basin, China
by Ying Wang, Yuanbo Liu, Jiaxin Jin and Xingwang Fan
Remote Sens. 2022, 14(4), 885; https://doi.org/10.3390/rs14040885 - 12 Feb 2022
Cited by 2 | Viewed by 2338
Abstract
Improving understanding of changes in intra-annual variability (IAV) of evapotranspiration (ET) and the underlying drivers is an essential step for modeling hydrological processes in response to global change. Previous studies paid special attention to climatic regulations of IAV of ET. However, ignoring the [...] Read more.
Improving understanding of changes in intra-annual variability (IAV) of evapotranspiration (ET) and the underlying drivers is an essential step for modeling hydrological processes in response to global change. Previous studies paid special attention to climatic regulations of IAV of ET. However, ignoring the role of landscape characteristics (e.g., vegetation coverage) can introduce great uncertainty in the explanation of ET variance. In this work, the Poyang Lake Basin, which is a typical humid basin in China, was taken as the study area. It has experienced an obvious climate change and revegetation since the 1980s. Here, trends of IAV of ET and their responses to four climatic variables (i.e., air temperature, precipitation, downward shortwave radiation and wind speed) and vegetation coverage were explored from 1983 to 2014. The results show that IAV of ET exhibited contrary trends during the past decades. It significantly (p < 0.05) declined with a significant linear slope of −0.52 mm/year before 2000, and then slightly increased (slope = 0.06 mm/year, p > 0.05) over the basin, which was generally consistent with the IAV of temperature and radiation. The proposed variables could well capture the change in IAV of ET, while their dominators were different during the two contrasting phases mentioned above. The IAV of radiation and temperature dominated the change of the IAV of ET over 77.82% and 35.14% of the basin, respectively, before and after the turning point. Meanwhile, the rapid increase in vegetation coverage, which was associated with afforestation, significantly (p < 0.05) reduced IAV of ET over about 35% of the study area. The achievements of this study should be beneficial for a sophisticated awareness of responses of intra-annual variability of ET to climate and land cover changes at the basin scale. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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24 pages, 3517 KiB  
Article
Global Vegetation Photosynthetic Phenology Products Based on MODIS Vegetation Greenness and Temperature: Modeling and Evaluation
by Xiaojun Xu, Yan Tang, Yiling Qu, Zhongsheng Zhou and Junguo Hu
Remote Sens. 2021, 13(24), 5080; https://doi.org/10.3390/rs13245080 - 14 Dec 2021
Cited by 4 | Viewed by 2829
Abstract
Land surface phenology (LSP) products that are derived from different data sources have different definitions and biophysical meanings. Discrepancies among these products and their linkages with carbon fluxes across plant functional types and climatic regions remain somewhat unclear. In this study, to differentiate [...] Read more.
Land surface phenology (LSP) products that are derived from different data sources have different definitions and biophysical meanings. Discrepancies among these products and their linkages with carbon fluxes across plant functional types and climatic regions remain somewhat unclear. In this study, to differentiate LSP related to gross primary production (GPP) from LSP related to remote sensing data, we defined the former as vegetation photosynthetic phenology (VPP), including the starting and ending days of GPP (SOG and EOG, respectively). Specifically, we estimated VPP based on a combination of observed VPP from 145 flux-measured GPP sites together with the vegetation index and temperature data from MODIS products using multiple linear regression models. We then compared VPP estimates with MODIS LSP on a global scale. Our results show that the VPP provided better estimates of SOG and EOG than MODIS LSP, with a root mean square error (RMSE) for SOG of 12.7 days and a RMSE for EOG of 10.5 days. The RMSE was approximately three weeks for both SOG and EOG estimates of the non-forest type. Discrepancies between VPP and LSP estimates varied across plant functional types (PFTs) and climatic regions. A high correlation was observed between VPP and LSP estimates for deciduous forest. For most PFTs, using VPP estimates rather than LSP improved the estimation of GPP. This study presents a useful method for modeling global VPP, investigates in detail the discrepancies between VPP and LSP, and provides a more effective global vegetation phenology product for carbon cycle modeling than the existing ones. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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15 pages, 6323 KiB  
Article
Response of Mangrove Carbon Fluxes to Drought Stress Detected by Photochemical Reflectance Index
by Yaqing Lu and Xudong Zhu
Remote Sens. 2021, 13(20), 4053; https://doi.org/10.3390/rs13204053 - 11 Oct 2021
Cited by 8 | Viewed by 2872
Abstract
The photochemical reflectance index (PRI) has been often used as a physiology-based remote sensing indicator of ecosystem carbon fluxes. However, the assessments of PRI in tracking long-term carbon fluxes with climatic anomalies in mangroves are very limited. In this study, four-year (2017–2020) continuous [...] Read more.
The photochemical reflectance index (PRI) has been often used as a physiology-based remote sensing indicator of ecosystem carbon fluxes. However, the assessments of PRI in tracking long-term carbon fluxes with climatic anomalies in mangroves are very limited. In this study, four-year (2017–2020) continuous time series measurements from tower-based eddy covariance and spectral systems in a subtropical mangrove were used to explore the ability of PRI in tracking the response of mangrove carbon fluxes to climate fluctuations and drought stress. The results showed that the temporal dynamics of daily PRI and carbon fluxes shared similar variation patterns over the study period, experiencing simultaneously decreasing trends under drought stress. Compared with the first three years, annual mean values of NEE in 2020 decreased by 10.7% and PRI decreased by 29.0%, correspondingly. PRI and carbon fluxes were significantly correlated across diurnal, seasonal, and annual time scales with better fitness under drought stress. Dark-state PRI (PRI0), the constitutive component of PRI variation due to seasonally changing pigment pool size, showed similar temporal variation as PRI in response to drought stress, while delta PRI (ΔPRI), the facultative component of PRI variation due to diurnal xanthophyll cycle, showed no response to drought stress. This study confirms the ability of PRI to track temporal dynamics of mangrove carbon fluxes on both short-term and long-term scales, with the temporal variation of PRI largely affected by the long-term constitutive pigment pool size. This study highlights the potential of PRI to serve as an early and readily detectable indicator to track the response of the mangrove carbon cycle to climatic anomalies such as drought stress. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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15 pages, 6729 KiB  
Article
Disentangling Climatic Factors and Human Activities in Governing the Old and New Forest Productivity
by Shanshan Chen, Zhaofei Wen, Maohua Ma and Shengjun Wu
Remote Sens. 2021, 13(18), 3746; https://doi.org/10.3390/rs13183746 - 18 Sep 2021
Cited by 5 | Viewed by 2724
Abstract
Forest ecosystem plays a vital role in the global carbon cycle and maintaining climate stability. However, how net primary productivity (NPP) dynamics of different stand ages of forest respond to climatic change and residual (being other climate factors or human activities) still remain [...] Read more.
Forest ecosystem plays a vital role in the global carbon cycle and maintaining climate stability. However, how net primary productivity (NPP) dynamics of different stand ages of forest respond to climatic change and residual (being other climate factors or human activities) still remain unclear. In this study, firstly, forests are divided into two categories based on their stand age: forests appeared before appeared before the research period (Fold), and forests appeared during the research period (Fnew). Secondly, we improved a quantitative method of basic partial derivatives to disentangle the relative contributions of climatic factors, other climate factors, and human activities to the NPP of Fold and Fnew. Then, different scenarios were simulated to identify the dominant drivers for forest restoration and degradation. In this study, we hypothesized the residual of Fold was other climate factors rather than human activities. Our results revealed that from 2000 to 2019, Fold and Fnew of NPP in Yangtze River Basin showed a significant increment trend and precipitation was the major positive contributor among all of the climatic factors. We found that, in Fold, climate change and other climate factors contributed 9.77% and 28.33%, respectively, in explaining NPP. This finding unsupported our initial hypothesis and implied that residuals should be human activities for Fold. Furthermore, we found that human activities dominate either restoration or degradation of Fnew. This result may be due to the attenuated human disturbances and strengthened forest management, such as ecological policies, forest tending, closing the land for reforestation, etc. Therefore, based on disentangling the two types of factors, we concluded that human activities govern the forest change, and imply that the environment-friendly forest managements may favorite to improving the forest NPP against the impacts of climate change. Thus, effective measures and policies are suggested implement in controlling forest degradation in facing climate change. Full article
(This article belongs to the Special Issue Remotely Monitoring Terrestrial Carbon, Water and Energy Fluxes in Ecologically Sensitive Areas)
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