Article
Environmental Sciences
Mingshan Deng, Xianhong Meng, Yaqiong Lu, Zhaoguo Li, Lin Zhao, Hanlin Niu, Hao Chen, Lunyu Shang, Shaoying Wang, Danrui Sheng
Summary: Changes in vegetation dynamics are crucial for terrestrial ecosystems and environments. This study revised and validated a land surface biogeochemical dynamic vegetation model for the Tibetan Plateau, and found that temperature warming and precipitation enhancement are the dominant factors for increased vegetation productivity.
Article
Environmental Sciences
Salman Tariq, Hasan Nawaz, Zia Ul-Haq, Usman Mehmood
Summary: Using satellite data and climate model reanalysis, this study examines land use/land cover changes and related climate indicators in Pakistan. The findings show an increase in vegetation area in multiple regions of Pakistan, along with year-to-year variations in heat flux, rainfall, and aerosol index.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Tehseen Javed, Yi Li, Kai Feng, Olusola O. Ayantobo, Shakeel Ahmad, Xinguo Chen, Sadaf Rashid, Sovannaka Suon
Summary: The study found that air temperatures in all sub-regions of China were significantly increasing, with varying trends in precipitation. 2011 and 2016 were identified as extremely dry and wet years. Rapid changes in vegetation phenology and productivity were observed between these two years.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Review
Plant Sciences
Martha M. Farella, Joshua B. Fisher, Wenzhe Jiao, Kesondra B. Key, Mallory L. Barnes
Summary: This study emphasizes the untapped potential of remote sensing in plant ecology. Remote sensing in the thermal infrared domain can provide valuable information on plant behavior and stress conditions. It can evaluate plant species, traits, and structure, and offer unique insights into species distribution and phenology under changing climate conditions. Integrated understanding of processes and technology is crucial for scaling leaf traits, canopy structure, and regional patterns. The synergies between thermal remote sensing and other data sources provide a timely opportunity for ecologists to advance their understanding of plant physiology, ecology, and biogeography.
JOURNAL OF ECOLOGY
(2022)
Article
Environmental Sciences
Yu Bai, Shunlin Liang, Aolin Jia, Shenggong Li
Summary: Capturing the spatial and temporal dynamics of global GPP is crucial for understanding the carbon cycle and climate change. This study compared five GPP products to identify trends and sensitivities to environmental factors. Results showed inconsistent global trends and sensitivities among different products, highlighting the need for further investigation.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2023)
Article
Agronomy
Huiwen Li, Yiping Wu, Shuguang Liu, Jingfeng Xiao
Summary: The study showed that the humid region had the largest contribution to the national NPP IAV in China, accounting for 62%, primarily influenced by daily temperature range and precipitation. Water-limited regions, such as semi-humid, semi-arid, and arid areas, were mainly impacted by precipitation, high temperature days, and normal precipitation. In the Tibetan Plateau, daily temperature range and precipitation exerted the greatest influence on NPP IAV.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Article
Environmental Sciences
Sajjad Hussain, Shujing Qin, Wajid Nasim, Muhammad Adnan Bukhari, Muhammad Mubeen, Shah Fahad, Ali Raza, Hazem Ghassan Abdo, Aqil Tariq, B. G. Mousa, Faisal Mumtaz, Muhammad Aslam
Summary: In this study, the spatiotemporal variation of major crops in Vehari, Pakistan, was investigated using remote sensing technology. The results showed that the cultivation areas of wheat and cotton decreased, and temperature negatively affected crop production while precipitation had a positive impact.
Article
Ecology
Mei Wang, Peng Li, Changhui Peng, Jingfeng Xiao, Xiaolu Zhou, Yunpeng Luo, Cicheng Zhang
Summary: This study investigates the impacts of climate extremes on the end of the growing season (EOS) and finds that EOS exhibits different response patterns to different extreme climate events. Warm-related extremes delay EOS in high latitudes, while cold stress leads to advanced EOS in temperate biomes. EOS shows opposite response patterns to dry and wet extremes. Boreal biomes are more sensitive to extreme temperatures compared to temperate biomes, while water-restricted biomes are not sensitive to extreme drought. These findings highlight the importance of incorporating divergent extreme climate effects into vegetation phenological models and Earth system models.
GLOBAL ECOLOGY AND BIOGEOGRAPHY
(2022)
Article
Engineering, Multidisciplinary
Mingshun Xiang, Qiuchi Deng, Linsen Duan, Jin Yang, Chunjian Wang, Jiashuo Liu, Mengli Liu
Summary: This study uses remote sensing and Geographic Information System (GIS) techniques to investigate the spatiotemporal differentiation of vegetation coverage in the earthquake stricken area of Beichuan County, Sichuan Province. The results show that the overall vegetation coverage in Beichuan County is high, and the earthquake has caused severe damage to areas with high vegetation coverage. From 2007 to 2020, the vegetation coverage gradually recovered with noticeable spatiotemporal differences. Elevation is found to be the most influential factor on vegetation coverage.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Multidisciplinary Sciences
Chao Wu, Stephen Sitch, Chris Huntingford, Lina M. Mercado, Sergey Venevsky, Gitta Lasslop, Sally Archibald, A. Carla Staver
Summary: Fire is a significant climate-driven disturbance in terrestrial ecosystems, whose changes can affect the global carbon cycle and climate change. Changes in human demography tend to suppress global fire activity and attenuate warming.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Environmental Sciences
Xiang Fan, Yongze Song, Chuxin Zhu, Heiko Balzter, Zhongke Bai
Summary: This study reveals significant differences in vegetation-climate relationships between reclaimed and unmined lands using remote-sensing data. Vegetation on reclaimed lands responds to a wider range of climatic variables and shows a higher sensitivity to climatic variability compared to undisturbed vegetation. The legacy effects of surface mining can critically impact on-site vegetation-climate relationships and the overall structure, functions, and stability of reclaimed ecosystems.
Article
Environmental Sciences
Marco Piragnolo, Francesco Pirotti, Carlo Zanrosso, Emanuele Lingua, Stefano Grigolato
Summary: This paper presents a semi-automated workflow for detecting and quantifying forest damage in the Alpine region, utilizing remote sensing data and machine learning algorithms for severity prediction. The study demonstrates that combining multiple vegetation indices can significantly improve the estimation of severity, while also highlighting the importance of considering the impact of understorey vegetation on the results.
Article
Environmental Sciences
Husheng Fang, Moquan Sha, Yichun Xie, Wenjuan Lin, Dai Qiu, Jiangguang Tu, Xicheng Tan, Xiaolei Li, Zongyao Sha
Summary: Green vegetation in terrestrial ecosystems plays a crucial role in energy flows and matter cycles. Vegetation phenology, influenced by climate changes and also affecting climate through active feedback, has important implications for gross primary productivity (GPP). Using satellite remote sensing imagery and FLUXNET observations, we mapped the shift of vegetation phenological events globally and investigated their response to climate fluctuations and feedback on GPP. The results showed significant advances in the start of season (SOS) in 11.5% of the global vegetated area, while only 5.2% exhibited significantly delayed end of season (EOS), resulting in a lengthening of the season (LOS) in 12.6% of the vegetated area. Climate factors, such as temperature and precipitation, contributed to the shifts in vegetation phenology with high spatial and temporal variability. LOS was positively correlated with GPP in 20.2% of the total area, indicating that a longer LOS promotes vegetation productivity. This feedback mechanism of shifted vegetation phenology on GPP may serve as an adaptation strategy for terrestrial ecosystems to mitigate global warming.
Article
Geography, Physical
Helen Hallang, Sietse O. Los, John F. Hiemstra
Summary: Northern high-alpine regions are experiencing rapid warming, resulting in the degradation of permafrost and the advancement of vegetation. This study combines remote sensing data and observed temperatures to model the thermal and vegetational dynamics in NE Jotunheimen, Norway. The results show significant warming trends and increased vegetation, with non-uniform spatial and temporal patterns.
PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT
(2022)
Article
Environmental Sciences
Wenxu Cao, Hang Xu, Zhiqiang Zhang
Summary: Global climate change has a profound impact on vegetation growth patterns. However, regional climate characteristics tend to weaken the disparities in vegetation responses observed in large-scale studies. Additionally, different vegetation types exhibit distinct reactions to climate variability, making it challenging to detect and attribute changes in vegetation growth. This study used the normalized difference vegetation index (NDVI) dataset to investigate the spatiotemporal distribution and dynamic characteristics of climate change effects on vegetation growth from 2000 to 2020. The findings revealed a continuous greening trend, with precipitation identified as the dominant climatic factor influencing this trend. Continued warming, however, has led to a slowdown in vegetation growth. Solar radiation was also found to correspond to the vegetation trend. These findings highlight the nonlinearity of long-term vegetation growth trends with climate variation and provide valuable insights into forecasting vegetation responses to future climate change.
Article
Environmental Sciences
Wei He, Fei Jiang, Mousong Wu, Weimin Ju, Marko Scholze, Jing M. Chen, Brendan Byrne, Junjie Liu, Hengmao Wang, Jun Wang, Songhan Wang, Yanlian Zhou, Chunhua Zhang, Ngoc Tu Nguyen, Yang Shen, Zhi Chen
Summary: The magnitude and distribution of China's terrestrial carbon sink remains uncertain, and this study uses satellite data to provide two estimates of the carbon sink. The results suggest that the carbon sinks are mainly located in central and eastern China and are vital for characterizing terrestrial net carbon fluxes at regional scales.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2022)
Article
Plant Sciences
Ning Dong, Ian J. Wright, Jing M. Chen, Xiangzhong Luo, Han Wang, Trevor F. Keenan, Nicholas G. Smith, Iain Colin Prentice
Summary: Nitrogen limitation is considered a constraint on terrestrial carbon uptake, but this study suggests that the decline in leaf-level photosynthetic N and leaf N content may not necessarily signify increasing N limitation, but rather be related to the rising CO2 concentration and temperature.
Article
Environmental Sciences
Xiaoping Wang, Jing M. Chen, Weimin Ju, Yongguang Zhang
Summary: The maximum carboxylation rate (Vcmax) of plant leaves, particularly at 25 degrees C (Vm25 degrees), shows significant seasonal variations and is influenced by various environmental and physiological factors. Air temperature and soil water content are the most important determinants of Vm25 degrees, while leaf chlorophyll content also affects its seasonal variation. These findings are important for better parameterization of Vm25 degrees in ecosystem models.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2022)
Article
Environmental Sciences
Xinyao Xie, Ainong Li, Jing M. Chen, Xiaobin Guan, Jiye Leng
Summary: Accurate estimation of gross primary productivity (GPP) is crucial for understanding the terrestrial carbon budget. Current estimates often lack consideration for subpixel heterogeneity, resulting in scaling errors. This study investigated the key upscaling processes causing errors and the contributions of various heterogeneity factors. Results showed that any aggregation of surface heterogeneity from fine to coarse resolutions can cause GPP scaling errors, with the aggregation from medium to coarse resolutions being the largest source. These findings highlight the importance of considering surface heterogeneity, particularly elevation information, in modeling GPP in mountainous regions at coarse resolutions.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2022)
Article
Plant Sciences
Mauricio Tejera-Nieves, Michael Abraha, Jiquan Chen, Stephen K. Hamilton, G. Philip Robertson, Berkley Walker James
Summary: Leaf photosynthesis of perennial grasses declines from early to late summer, and water availability is associated with this decline. Despite reduced water availability, the photosynthetic decline is similar in grasses with and without rainfall exclusion, suggesting water deficit is not the sole driver of the decline. Rhizome starch accumulation and sink activity likely explain the observed photosynthetic declines towards the end of the growing season.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Geography
Tenaw Geremew, Alemu Gonsamo, Worku Zewdie, Petri Pellikka
Summary: The Global Ecosystem Dynamics Investigation (GEDI) is a full waveform lidar sensor that collects samples of the terrain and vegetation structures. To estimate spatial continuity, canopy height and cover metrics from GEDI L2A and L2B were extrapolated using support vector regression models and explanatory variables derived from multiple remotely sensed datasets. The accuracy of canopy height prediction for GEDI data was validated to be RMSE = 3.83 m (R2 = 0.84) when compared to a subset of GEDI data, but decreased to RMSE = 7.98 m (R2 = 0.65) when validated with field-measured canopy heights. The accuracy of forest canopy cover prediction from GEDI L2B remains generally poor with RMSE = 0.14 (R2 = 0.53).
AFRICAN GEOGRAPHICAL REVIEW
(2023)
Article
Environmental Sciences
Dean Qiu, Yunjian Liang, Rong Shang, Jing M. M. Chen
Summary: Forest disturbance detection is important for understanding forest dynamics. The LandTrendr algorithm, based on Landsat data, is commonly used for this purpose. However, LandTrendr has limitations in terms of temporal coverage and mapping accuracy. To address these limitations, we modified LandTrendr (mLandTrendr) by using multi-season observations and multispectral indices for forest disturbance mapping in China. The validation results showed that these modifications significantly improved the overall accuracy of forest disturbance detection by 21%. The mLandTrendr algorithm can efficiently and accurately detect forest disturbance and has the potential for national and global forest disturbance mapping.
Article
Multidisciplinary Sciences
Zhaoying Zhang, Alessandro Cescatti, Ying-Ping Wang, Pierre Gentine, Jingfeng Xiao, Luis Guanter, Alfredo R. Huete, Jin Wu, Jing M. Chen, Weimin Ju, Josep Penuelas, Yongguang Zhang
Summary: Photosynthesis and evapotranspiration in Amazonian forests have significant impacts on global carbon and water cycles. However, their diurnal patterns and responses to atmospheric warming and drying at regional scale are still not well understood. Using proxies from the International Space Station, we found a significant decrease in afternoon photosynthesis and evapotranspiration during the dry season, while morning photosynthesis showed a positive response to vapor pressure deficit (VPD) and afternoon photosynthesis showed a negative response. Furthermore, we projected that the decrease in afternoon photosynthesis will be compensated by an increase in the morning in future dry seasons. These findings provide new insights into the complex interplay between climate and carbon and water fluxes in Amazonian forests and improve the reliability of future projections.
Article
Biodiversity Conservation
Jessica Currie, Will Merritt, Chris Liang, Camile Sothe, Craig R. Beatty, Nancy Shackelford, Kristen Hirsh-Pearson, Alemu Gonsamo, James Snider
Summary: Ecosystem restoration is essential for achieving climate and biodiversity goals. We conducted a spatial analysis in Canada to identify areas with the highest potential for restoration. Our results show that forest and grassland restoration would yield the greatest biodiversity benefits, while wetland and forest restoration have the highest potential for carbon storage. Forest restoration in certain regions, such as St. Lawrence and Lake Erie Lowlands, is consistently prioritized in our optimization framework. This analysis will help decision-makers in Canada make informed choices for restoring converted lands and achieving climate and biodiversity objectives simultaneously.
CONSERVATION SCIENCE AND PRACTICE
(2023)
Article
Agronomy
Mengmiao Yang, Jane Liu, Yong Wang, Jing M. Chen, Zeyu Cui, Zhanjie Zhang, Zhixiong Chen, Xugeng Cheng
Summary: Rainfall variations on a diurnal scale have significant impacts on ecosystem evapotranspiration and gross primary productivity. More daytime rainfall, especially occurring around noon, leads to decreased daily total evapotranspiration and gross primary productivity, while more unevenly distributed rainfall away from noon results in increased daily total evapotranspiration and gross primary productivity. Consideration of diurnal rainfall variations in observations and models is crucial for improving our understanding of atmosphere-biosphere interactions.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Agronomy
Lelia Weiland, Cheryl A. Rogers, Camile Sothe, M. Altaf Arain, Alemu Gonsamo
Summary: Soil respiration, a key ecosystem process, can be estimated using satellite-derived land surface temperature and soil moisture. This study evaluated three empirical models and a Random Forest algorithm, which were calibrated using in-situ measurements and validated against soil CO2 fluxes from automatic chambers. The results showed that satellite observations can explain over 70% of the variability in soil respiration and provide comparable accuracy to in-situ measurements.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Geography, Physical
Jingru Zhang, Alemu Gonsamo, Xiaojuan Tong, Jingfeng Xiao, Cheryl A. Rogers, Shuhong Qin, Peirong Liu, Peiyang Yu, Pu Ma
Summary: Accurate characterization of plant phenology is crucial for monitoring global carbon, water, and energy cycling. Satellite observations, particularly the solar-induced chlorophyll fluorescence (SIF) observations, provide a valuable tool to monitor the seasonality of plant growth. This study evaluated the performance of TROPOMI SIF-derived phenology metrics using flux tower GPP and PhenoCam Gcc data as benchmarks. The results showed that SIF-derived phenology had stronger agreements and less error compared to other satellite-derived phenology metrics. The spatial distribution of SIF-derived phenology closely reflected the expected patterns. These findings highlight the importance and potential of TROPOMI SIF in tracking photosynthesis seasonality and land surface phenology.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Yongxian Su, Chaoqun Zhang, Philippe Ciais, Zhenzhong Zeng, Alessandro Cescatti, Jiali Shang, Jing Ming Chen, Jane Liu, Ying-Ping Wang, Wenping Yuan, Shushi Peng, Xuhui Lee, Zaichun Zhu, Lei Fan, Xiaoping Liu, Liyang Liu, Raffaele Lafortezza, Yan Li, Jiashun Ren, Xueqin Yang, Xiuzhi Chen
Summary: Changes in tree cover can affect surface temperatures due to asymmetric direct biophysical effects. The cooling effect of tree cover gain is greater in magnitude than the warming effect of tree cover loss in most forests. Neglecting this asymmetric temperature effect of fine-scale tree cover change ignores the fact that biophysical feedbacks continue to cause surface temperature changes even under net-zero tree cover changes. Thus, it is necessary to account for gross, rather than net, tree cover changes when quantifying the biophysical effects of forests.
NATURE CLIMATE CHANGE
(2023)
Article
Environmental Sciences
Jingfeng Xiong, Hongda Zeng, Guo Cai, Yunfei Li, Jing M. Chen, Guofang Miao
Summary: This study aimed to measure aboveground biomass and stand growth using UAV-LiDAR. Two methods for detecting crown height were evaluated, and the voxel method based on point cloud segmentation was found to be more accurate. The effective crown area extracted using crown height was strongly correlated with annual biomass growth. The rapid and accurate monitoring of Chinese fir growth can be achieved using UAV-LiDAR and effective crown information.
Article
Environmental Sciences
Xinyao Xie, Jing M. Chen, Wenping Yuan, Xiaobin Guan, Huaan Jin, Jiye Leng
Summary: Vegetation in mountainous areas contributes significantly to global gross primary productivity (GPP), but the effects of topography on radiation and water redistributions have been overlooked in existing global GPP data sets. This study developed a topographical correction index (TCI) based on simulated soil water redistribution, radiation redistribution, and redistribution of climate factors, and applied it to four GPP data sets. Results showed that integrating topography-induced interactions improved the accuracy of GPP estimation, with reduced mean-bias-error (MBE) and Root-Mean-Square-Error (RMSE). This study highlights the importance of considering topographical effects in GPP estimation to understand carbon budgets in mountain ecosystems.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2023)
