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Journal articles on the topic 'Phenology'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Macphie, Kirsty H., and Albert B. Phillimore. "Phenology." Current Biology 34, no. 5 (2024): R183—R188. http://dx.doi.org/10.1016/j.cub.2024.01.007.

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2

Colin Irvine. "Cognitive Phenology:." Interdisciplinary Literary Studies 16, no. 1 (2014): 160. http://dx.doi.org/10.5325/intelitestud.16.1.0160.

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3

Ma, Xin Ping, Hong Ying Bai, Ying Na He, and Shu Heng Li. "The Vegetation Remote Sensing Phenology of Qinling Mountains Based on the NDVI and the Response of Temperature to it." Applied Mechanics and Materials 700 (December 2014): 394–99. http://dx.doi.org/10.4028/www.scientific.net/amm.700.394.

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The acquisition vegetation phenology information by using time series of satellite data is an important aspect of the application of remote sensing and climate change research . Based on the MODOS NDVI time series of images in 2000-2010, Dynamic threshold method and GIS tools were used to extract the vegetation phenology parameters of Qinling Mountains in 2000-2010 , the accuracy of remote sensing phenology results was verified combined with the measured phenological data, And analyzed the characteristis of phenological variation and the relationship between temperature changes and the phenolo

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Xu, Lingling, Ben Niu, Xianzhou Zhang, and Yongtao He. "Dynamic Threshold of Carbon Phenology in Two Cold Temperate Grasslands in China." Remote Sensing 13, no. 4 (2021): 574. http://dx.doi.org/10.3390/rs13040574.

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Plant phenology, especially the timing of the start and the end of the vegetation growing season (SOS and EOS), plays a major role in grassland ecosystem carbon cycles. As the second-largest grassland country in the world, China’s grasslands are mainly distributed in the northern cold temperate climate zone. The accuracies and relations of plant phenology estimations from multialgorithms and data resources are poorly understood. Here, we investigated vegetation phenology in two typical cold temperate grasslands, Haibei (HB) and Inner Mongolia (NM) grasslands, in China from 2001 to 2017. Compar

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5

Wang, Cong, Yijin Wu, Qiong Hu, et al. "Comparison of Vegetation Phenology Derived from Solar-Induced Chlorophyll Fluorescence and Enhanced Vegetation Index, and Their Relationship with Climatic Limitations." Remote Sensing 14, no. 13 (2022): 3018. http://dx.doi.org/10.3390/rs14133018.

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Satellite-based vegetation datasets enable vegetation phenology detection at large scales, among which Solar-Induced Chlorophyll Fluorescence (SIF) and Enhanced Vegetation Index (EVI) are widely used proxies for detecting phenology from photosynthesis and greenness perspectives, respectively. Recent studies have revealed the divergent performances of SIF and EVI for estimating different phenology metrics, i.e., the start of season (SOS) and the end of season (EOS); however, the underlying mechanisms are unclear. In this study, we compared the SOS and EOS of natural ecosystems derived from SIF

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Ding, Haiyong, Luming Xu, Andrew J. Elmore, and Yuli Shi. "Vegetation Phenology Influenced by Rapid Urbanization of The Yangtze Delta Region." Remote Sensing 12, no. 11 (2020): 1783. http://dx.doi.org/10.3390/rs12111783.

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Impacts of urbanization and climate change on ecosystems are widely studied, but these drivers of change are often difficult to isolate from each other and interactions are complicated. Ecosystem responses to each of these drivers are perhaps most clearly seen in phenology changes due to global climate change (warming climate) and urbanization (heat island effect). The phenology of vegetation can influence many important ecological processes, including primary production, evapotranspiration, and plant fitness. Therefore, evaluating the interacting effects of urbanization and climate change on

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7

Zhang, Jing, Shouzhi Chen, Zhaofei Wu, and Yongshuo H. Fu. "Review of vegetation phenology trends in China in a changing climate." Progress in Physical Geography: Earth and Environment 46, no. 6 (2022): 829–45. http://dx.doi.org/10.1177/03091333221114737.

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Vegetation phenology is sensitive to climate change and has been defined as the footprint of ongoing climate change. Previous studies have shown that the spatial difference in China’s vegetation phenology varies substantially in both spring and autumn. Here, we reviewed phenological dynamics at the national and the regional scale of China over the period 1982−2020 using a remote sensing-based dataset and meta-analysis from phenological studies in China. We also explored the underlying mechanisms of both spring and autumn phenology and discussed potential phenological studies under future clima

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8

Wang, Xinwei, Jianhao Li, Jianghua Zheng, et al. "How Do Changes in Grassland Phenology and Its Responses to Extreme Climatic Events in Central Asia?" Land 14, no. 1 (2025): 160. https://doi.org/10.3390/land14010160.

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Extreme climate events have become more frequent under global warming, significantly affecting vegetation phenology and carbon cycles in Central Asia. However, the mediating effects of intensity of compound drought and heat events (CDHEs) and compound moisture and heat events (CMHEs) on grassland phenology and their trends in the relative contributions to grassland phenology over time have remained unclear. Based on the calculation results of grassland phenology and compound events (CEs), this study used trend analysis, partial least squares regression structural equation modeling (PLS-SEM), a

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9

Meier, Michael, and Christof Bigler. "Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections." Geoscientific Model Development 16, no. 23 (2023): 7171–201. http://dx.doi.org/10.5194/gmd-16-7171-2023.

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Abstract. Autumn leaf phenology marks the end of the growing season, during which trees assimilate atmospheric CO2. The length of the growing season is affected by climate change because autumn phenology responds to climatic conditions. Thus, the timing of autumn phenology is often modeled to assess possible climate change effects on future CO2-mitigating capacities and species compositions of forests. Projected trends have been mainly discussed with regards to model performance and climate change scenarios. However, there has been no systematic and thorough evaluation of how performance and p

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10

Harper, Geoffrey. "Lessons from Phenology." Sibbaldia: the International Journal of Botanic Garden Horticulture, no. 8 (October 31, 2010): 149–64. http://dx.doi.org/10.24823/sibbaldia.2010.143.

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Twenty provisional multiple-regression models based on a small data set are presented to account for the timing of first-flower date and other phenological events. Biological mechanisms are suggested to explain the pattern of temperature-dependent developmental stages. The implications for how plants and vegetation are likely to react to climate change are discussed, and attention is drawn to the importance of within-taxon variation in phenological behaviour.

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11

Meng, Lin. "Green with phenology." Science 374, no. 6571 (2021): 1065–66. http://dx.doi.org/10.1126/science.abm8136.

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12

Tooke, F., and N. H. Battey. "Temperate flowering phenology." Journal of Experimental Botany 61, no. 11 (2010): 2853–62. http://dx.doi.org/10.1093/jxb/erq165.

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13

White, J. W. "Predicting crop phenology." Agricultural Systems 39, no. 2 (1992): 229–30. http://dx.doi.org/10.1016/0308-521x(92)90110-a.

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14

Schwartz, Mark D. "Green-wave phenology." Nature 394, no. 6696 (1998): 839–40. http://dx.doi.org/10.1038/29670.

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15

Kalita, Himangshu, and Narayan Sharma. "Phenology: Nature’s Calendar." Resonance 28, no. 7 (2023): 1117–33. http://dx.doi.org/10.1007/s12045-023-1641-1.

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16

Pei, Jie, Shaofeng Tan, Yaopeng Zou, et al. "The role of phenology in crop yield prediction: Comparison of ground-based phenology and remotely sensed phenology." Agricultural and Forest Meteorology 361 (February 2025): 110340. https://doi.org/10.1016/j.agrformet.2024.110340.

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17

Wang, Bo, Yu Liu, Qinghong Sheng, Jun Li, Jiahui Tao, and Zhijun Yan. "Rice Phenology Retrieval Based on Growth Curve Simulation and Multi-Temporal Sentinel-1 Data." Sustainability 14, no. 13 (2022): 8009. http://dx.doi.org/10.3390/su14138009.

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The accurate estimation and monitoring of phenology is necessary for modern agricultural industries. For crops with short phenology occurrence times, such as rice, Sentinel-1 can be used to effectively monitor the growth status in different phenology periods within a short time interval. Therefore, this study proposes a method to monitor rice phenology based on growth curve simulation by constructing a polarized growth index (PGI) and obtaining a polarized growth curve. A recursive neural network is used to realize the classification of phenology and use it as prior knowledge of rice phenology

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18

Li, Jiyuan, Xiao Feng, Jiangbin Yin, and Fang Chen. "Change Analysis of Spring Vegetation Green-Up Date in Qinba Mountains under the Support of Spatiotemporal Data Cube." Journal of Sensors 2020 (February 27, 2020): 1–12. http://dx.doi.org/10.1155/2020/6413654.

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In recent decades, global and local vegetation phenology has undergone significant changes due to the combination of climate change and human activities. Current researches have revealed the temporal and spatial distribution of vegetation phenology in large scale by using remote sensing data. However, researches on spatiotemporal differentiation of remote sensing phenology and its changes are limited which involves high-dimensional data processing and analysing. A new data model based on data cube technologies was proposed in the paper to efficiently organize remote sensing phenology and relat

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19

ZHU, Mengyao, Junhu DAI, Huanjiong WANG, Yulong HAO, Wei LIU, and Lijuan CAO. "A dataset of gridded phenology of woody plants in Europe from 1951 to 2021." China Scientific Data 9, no. 2 (2024): 1–5. http://dx.doi.org/10.11922/11-6035.csd.2023.0068.zh.

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Plant phenology records the timing of plant cyclic growth events, and stand as one of the most important indicators of climate change. The monitoring and research of plant phenology is of great significance for understanding the response of ecosystems to global changes and simulating the material and energy balance of terrestrial ecosystems. Based on the ground observation phenological data of six representative woody plants compiled by the Pan European Phenology Project (PEP725) in the past 70 years, this paper employed three phenology models (Unichill, Unified and TSC) to predict and upscale

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20

Cleland, Elsa E., and E. M. Wolkovich. "Effects of Phenology on Plant Community Assembly and Structure." Annual Review of Ecology, Evolution, and Systematics 55, no. 1 (2024): 471–92. http://dx.doi.org/10.1146/annurev-ecolsys-102722-011653.

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Phenology—the timing of critical stages of growth and reproduction and the transitions between them—determines environmental conditions and biotic interactions. Hence, phenology is a key functional trait influencing organisms’ survival and fitness; however, the role of phenology in community assembly processes has been less considered. Here we review the importance of phenology in environmental and biotic filtering, structuring priority effects, and species coexistence in the context of the assembly of native communities, as well as in invasions and restoration. We highlight the complexity of

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21

Medeiros, Rodolpho, João Andrade, Desirée Ramos, et al. "Remote Sensing Phenology of the Brazilian Caatinga and Its Environmental Drivers." Remote Sensing 14, no. 11 (2022): 2637. http://dx.doi.org/10.3390/rs14112637.

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The Caatinga is the largest nucleus of Seasonally Dry Tropical Forests (SDTF) in the Neotropics. The leafing patterns of SDTF vegetation are adapted to the current environmental and climate variability, but the impacts of climate change tend to alter plants’ phenology. Thus, it is necessary to characterise phenological parameters and evaluate the relationship between vegetation and environmental drivers. From this information, it is possible to identify the dominant forces in the environment that trigger the phenological dynamics of the Caatinga. In this way, remote sensing represents an essen

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22

Fu, Xuecheng, and Bao-Jie He. "Synergistic Impacts of Built-Up Characteristics and Background Climate on Urban Vegetation Phenology: Evidence from Beijing, China." Forests 15, no. 4 (2024): 728. http://dx.doi.org/10.3390/f15040728.

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Vegetation is an important strategy for mitigating heat island effects, owed to its shading and evaporative cooling functions. However, urbanization has significantly affected regional vegetation phenology and can potentially weaken the cooling potential of vegetation. Previous studies have mainly focused on national and regional vegetation phenology, but local-scale vegetation phenology and dynamic variations in built-up areas remain unclear. Therefore, this study characterized the vegetation phenology in the densely built-up area of Beijing, China over the period of 2000–2020 based on high-r

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23

Zhu, Enyan, Dan Fang, Lisu Chen, Youyou Qu, and Tao Liu. "The Impact of Urbanization on Spatial–Temporal Variation in Vegetation Phenology: A Case Study of the Yangtze River Delta, China." Remote Sensing 16, no. 5 (2024): 914. http://dx.doi.org/10.3390/rs16050914.

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The response of vegetation phenology to urbanization has become a growing concern. As impervious surfaces change as urbanization advances, the variation in vegetation phenology at the dynamic urbanization level was analyzed to significantly quantify the impact of urbanization processes on vegetation phenology. Based on the MOD13Q1 vegetation index product from 2001 to 2020, vegetation phenology parameters, including the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (GSL), were extracted, and the spatial–temporal variation in vegeta

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24

Li, Xuecao, Yuyu Zhou, Lin Meng, Ghassem R. Asrar, Chaoqun Lu, and Qiusheng Wu. "A dataset of 30 m annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States." Earth System Science Data 11, no. 2 (2019): 881–94. http://dx.doi.org/10.5194/essd-11-881-2019.

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Abstract. Medium-resolution satellite observations show great potential for characterizing seasonal and annual dynamics of vegetation phenology in urban domains from local to regional and global scales. However, most previous studies were conducted using coarse-resolution data, which are inadequate for characterizing the spatiotemporal dynamics of vegetation phenology in urban domains. In this study, we produced an annual vegetation phenology dataset in urban ecosystems for the conterminous United States (US), using all available Landsat images on the Google Earth Engine (GEE) platform. First,

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25

Basinger, Nicholas T., Katherine M. Jennings, Erin L. Hestir, David W. Monks, David L. Jordan, and Wesley J. Everman. "Phenology affects differentiation of crop and weed species using hyperspectral remote sensing." Weed Technology 34, no. 6 (2020): 897–908. http://dx.doi.org/10.1017/wet.2020.92.

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AbstractThe effect of plant phenology and canopy structure of four crops and four weed species on reflectance spectra were evaluated in 2016 and 2017 using in situ spectroscopy. Leaf-level and canopy-level reflectance were collected at multiple phenologic time points in each growing season. Reflectance values at 2 wk after planting (WAP) in both years indicated strong spectral differences between species across the visible (VIS; 350–700 nm), near-infrared (NIR; 701–1,300 nm), shortwave-infrared I (SWIR1; 1,301–1,900 nm), and shortwave-infrared II (SWIR2; 1,901–2,500 nm) regions. Results from t

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26

Cao, Heqin, Yan Hua, Xin Liang, et al. "Wavelet Analysis Reveals Phenology Mismatch between Leaf Phenology of Temperate Forest Plants and the Siberian Roe Deer Molting under Global Warming." Remote Sensing 14, no. 16 (2022): 3901. http://dx.doi.org/10.3390/rs14163901.

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Global warming is deeply influencing various ecological processes, especially regarding the phenological synchronization pattern between species, but more cases around the world are needed to reveal it. We report how the forest leaf phenology and ungulate molting respond differently to climate change, and investigate whether it will result in a potential phenology mismatch. Here, we explored how climate change might alter phenological synchronization between forest leaf phenology and Siberian roe deer (Capreolus pygargus) molting in northeast China based on a camera-trapping dataset of seven c

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27

Hartmann, Eva, Jan-Peter Schulz, Ruben Seibert, et al. "Impact of Environmental Conditions on Grass Phenology in the Regional Climate Model COSMO-CLM." Atmosphere 11, no. 12 (2020): 1364. http://dx.doi.org/10.3390/atmos11121364.

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Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by t

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28

Forrest, Jessica, and Abraham J. Miller-Rushing. "Toward a synthetic understanding of the role of phenology in ecology and evolution." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1555 (2010): 3101–12. http://dx.doi.org/10.1098/rstb.2010.0145.

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Phenology affects nearly all aspects of ecology and evolution. Virtually all biological phenomena—from individual physiology to interspecific relationships to global nutrient fluxes—have annual cycles and are influenced by the timing of abiotic events. Recent years have seen a surge of interest in this topic, as an increasing number of studies document phenological responses to climate change. Much recent research has addressed the genetic controls on phenology, modelling techniques and ecosystem-level and evolutionary consequences of phenological change. To date, however, these efforts have t

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29

Xie, Zhiying, Wenquan Zhu, Bangke He, Kun Qiao, Pei Zhan, and Xin Huang. "A background-free phenology index for improved monitoring of vegetation phenology." Agricultural and Forest Meteorology 315 (March 2022): 108826. http://dx.doi.org/10.1016/j.agrformet.2022.108826.

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30

Gao, Yu, Zhaoling Hu, Zhen Wang, et al. "Phenology Metrics for Vegetation Type Classification in Estuarine Wetlands Using Satellite Imagery." Sustainability 15, no. 2 (2023): 1373. http://dx.doi.org/10.3390/su15021373.

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While the efficiency of incorporating phenology features into vegetation type classification, in general, and coastal wetland vegetation classification, in particular, has been verified, it is difficult to acquire high-spatial-resolution (HSR) images taken at appropriate times for vegetation identification using phenology features because of the coastal climate and the HSR satellite imaging cycle. To strengthen phenology feature differences, in this study, we constructed vegetation phenology metrics according to vegetation NDVI time series curves fitted by samples collected from the Linhong Es

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31

Čehulić, Ivica, Krunoslav Sever, Ida Katičić Bogdan, Anamarija Jazbec, Željko Škvorc, and Saša Bogdan. "Drought Impact on Leaf Phenology and Spring Frost Susceptibility in a Quercus robur L. Provenance Trial." Forests 10, no. 1 (2019): 50. http://dx.doi.org/10.3390/f10010050.

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Research highlights: The susceptibility of oaks to late spring and early autumn frosts is directly related to their leaf phenology. Drought may alter the leaf phenology and therefore frost tolerance of oaks. However, the effects of drought on oak leaf phenology and frost resistance have not been thoroughly studied. Background and objectives: One of the consequences of climate change is an increase in the frequency of dry episodes during the vegetation period. Pedunculate oak (Quercus robur L.) is an economically and ecologically important forest tree species that prefers humid habitats. Theref

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32

Hou, Guanyu, Xiuliang Yuan, Shixin Wu, et al. "Phenological Changes and Driving Forces of Lake Ice in Central Asia from 2002 to 2020." Remote Sensing 14, no. 19 (2022): 4992. http://dx.doi.org/10.3390/rs14194992.

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Lake ice phenology is an indicator of past and present climate, it is sensitive to regional and global climate change. In the past few decades, the climate of Central Asia has changed significantly due to global warming and anthropogenic activities. However, there are few studies on the lake ice phenology in Central Asia. In this study, the lake ice phenology of 53 lakes in Central Asia were extracted using MODIS daily LST products from 2002 to 2020. The results show that MODIS-extracted lake ice phenology is generally consistent with Landsat-extracted and AVHRR-extracted lake ice phenology. G

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Tian, Jiaqi, Xiaolin Zhu, Jin Wu, Miaogen Shen, and Jin Chen. "Coarse-Resolution Satellite Images Overestimate Urbanization Effects on Vegetation Spring Phenology." Remote Sensing 12, no. 1 (2020): 117. http://dx.doi.org/10.3390/rs12010117.

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Numerous investigations of urbanization effects on vegetation spring phenology using satellite images have reached a consensus that vegetation spring phenology in urban areas occurs earlier than in surrounding rural areas. Nevertheless, the magnitude of this rural–urban difference is quite different among these studies, especially for studies over the same areas, which implies large uncertainties. One possible reason is that the satellite images used in these studies have different spatial resolutions from 30 m to 1 km. In this study, we investigated the impact of spatial resolution on the rur

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RAMÍREZ MARTÍNEZ, ADRIANA, DEMETRIA MARTHA MONDRAGÓN CHAPARRO, and RAÚL RIVERA GARCÍA. "VASCULAR EPIPHYTES: THE UGLY DUCKLING OF PHENOLOGICAL STUDIES." Acta Biológica Colombiana 26, no. 2 (2021): 247–61. http://dx.doi.org/10.15446/abc.v26n2.83473.

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The phenology of vascular epiphytes, which represent account for about 10 % of the world’s flowering plants and perform important ecological functions, has been just partially explored. Since phenology is a key tool for the management and conservation of species, the objective of this review was to synthesize the information published so far about the phenology of vascular epiphytes, detect gaps of knowledge, and suggest future lines of investigation to understand the underlying mechanisms. We conducted an online search for articles in Google Scholar and in the ISI Web of Science database from

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35

Garroutte, Erica, and Andrew Hansen. "Using Field Data to Validate Satellite Models of Elk Forage in the Upper Yellowstone River Basin." UW National Parks Service Research Station Annual Reports 36 (January 1, 2013): 134–37. http://dx.doi.org/10.13001/uwnpsrc.2013.4003.

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Spatial and temporal variations in grassland phenology are thought to play a critical role in migration patterns of large herbivores in the Greater Yellowstone Ecosystem. Phenology, referring to the timing of green-up in this study, is directly related to biomass and forage quality. Migratory elk (Cervus elaphus), therefore, are believed to follow phenology across an elevation gradient during the growing season to maximize their access to high quality and quantity of forage. Concern that climate change and human land use alterations of phenology may impact the benefits of elk migration highlig

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Zhang, Yi, Guangchao Cao, Meiliang Zhao, Qian Zhang, and Liyuan Huang. "Integrated Effects of Climate, Topography, and Greenhouse Gas on Grassland Phenology in the Southern Slope of the Qilian Mountains." Atmosphere 16, no. 6 (2025): 653. https://doi.org/10.3390/atmos16060653.

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Understanding vegetation phenology dynamics is essential for evaluating ecosystem responses to environmental changes. While previous studies have primarily focused on the correlation between vegetation phenology and climate variables, the integrated effects of meteorological factors, topography, and greenhouse gas (GHG) have often been overlooked. This study aims to analyze the spatiotemporal variations in grassland phenology on the southern slopes of the Qilian Mountains from 2002 to 2022, investigating the combined effects of these environmental factors. Our findings reveal significant spati

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Niu, Quandi, Xuecao Li, Jianxi Huang, et al. "A 30 m annual maize phenology dataset from 1985 to 2020 in China." Earth System Science Data 14, no. 6 (2022): 2851–64. http://dx.doi.org/10.5194/essd-14-2851-2022.

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Abstract. Crop phenology indicators provide essential information on crop growth phases, which are highly required for agroecosystem management and yield estimation. Previous crop phenology studies were mainly conducted using coarse-resolution (e.g., 500 m) satellite data, such as the moderate resolution imaging spectroradiometer (MODIS) data. However, precision agriculture requires higher resolution phenology information of crops for better agroecosystem management, and this requirement can be met by long-term and fine-resolution Landsat observations. In this study, we generated the first nat

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Chen, Zhizhong, Mei Zan, Jingjing Kong, Shunfa Yang, and Cong Xue. "Phenology of Vegetation in Arid Northwest China Based on Sun-Induced Chlorophyll Fluorescence." Forests 14, no. 12 (2023): 2310. http://dx.doi.org/10.3390/f14122310.

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The accurate monitoring of vegetation phenology is critical for carbon sequestration and sink enhancement. Vegetation phenology in arid zones is more sensitive to climate responses; therefore, it is important to conduct research on phenology in arid zones in response to global climate change. This study compared the applicability of the enhanced vegetation index (EVI), which is superior in arid zones, and global solar-induced chlorophyll fluorescence (GOSIF), which has a high spatial resolution, in extracting vegetation phenology in arid zones, and explored the mechanism of the differences in

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Stucky, Brian, Ramona Walls, John Deck, Ellen Denny, Kjell Bolmgren, and Robert Guralnick. "An Update on the Plant Phenology Ontology and Plant Phenology Data Integration." Biodiversity Information Science and Standards 1 (August 21, 2017): e20487. https://doi.org/10.3897/tdwgproceedings.1.20487.

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The study of plant phenology is concerned with the timing of plant life-cycle events, such as leafing out, flowering, and fruiting. Today, thanks to data digitization and aggregation initiatives, phenology monitoring networks, and the efforts of citizen scientists, more phenologically relevant plant data is available than ever before. Until recently, combining these data in large-scale analyses was prohibitively difficult because no standardized plant phenology terms and concepts were available to facilitate data interoperability. We have recently completed the first public release of The Plan

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40

Su, Lei, Tao Che, and Liyun Dai. "Variation in Ice Phenology of Large Lakes over the Northern Hemisphere Based on Passive Microwave Remote Sensing Data." Remote Sensing 13, no. 7 (2021): 1389. http://dx.doi.org/10.3390/rs13071389.

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Ice phenology data of 22 large lakes of the Northern Hemisphere for 40 years (1979–2018) have been retrieved from passive microwave remote sensing brightness temperature (Tb). The results were compared with site-observation data and visual interpretation from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectivity products images (MOD09GA). The mean absolute errors of four lake ice phenology parameters, including freeze-up start date (FUS), freeze-up end date (FUE), break-up start date (BUS), and break-up end date (BUE) against MODIS-derived ice phenology were 2.50, 2.33, 1.

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Yang, Fan, Chao Liu, Qianqian Chen, Jianbin Lai, and Tiegang Liu. "Earlier Spring-Summer Phenology and Higher Photosynthetic Peak Altered the Seasonal Patterns of Vegetation Productivity in Alpine Ecosystems." Remote Sensing 16, no. 9 (2024): 1580. http://dx.doi.org/10.3390/rs16091580.

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Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPPmax) affected seasonal

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Zhu, Mengyao, Junhu Dai, Huanjiong Wang, et al. "Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020." Earth System Science Data 16, no. 1 (2024): 277–93. http://dx.doi.org/10.5194/essd-16-277-2024.

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Abstract. Plant phenology refers to cyclic plant growth events, and is one of the most important indicators of climate change. Integration of plant phenology information is crucial for understanding the ecosystem response to global change and modeling the material and energy balance of terrestrial ecosystems. Utilizing 24 552 in situ phenological observations of 24 representative woody plant species from the Chinese Phenology Observation Network (CPON), we have developed maps delineating species phenology (SP) and ground phenology (GP) of forests over China from 1951 to 2020. These maps offer

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Tian, Yu, Lei Wang, Bingxi Liu, Yunlong Yao, and Dawei Xu. "Phenological Spatial Divergences Promoted by Climate, Terrain, and Forest Height in a Cold Temperate Forest Landscape: A Case Study of the Greater Khingan Mountain in Hulun Buir, China." Forests 16, no. 3 (2025): 490. https://doi.org/10.3390/f16030490.

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Vegetation phenology has attracted considerable attention as one of the most sensitive indicators of global climate change. Remote sensing has significantly expanded our understanding of the spatial divergences of vegetation phenology. However, the current understanding of the reasons behind spatial divergences of vegetation phenology is not yet complete, and there is an urgent need to unravel the landscape processes driving spatial divergences of vegetation phenology. In light of this, the present study focused on montane forests of the cold temperate zone as its study area, collecting datase

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Dodonov, P., C. B. Zanelli, and D. M. Silva-Matos. "Effects of an accidental dry-season fire on the reproductive phenology of two Neotropical savanna shrubs." Brazilian Journal of Biology 78, no. 3 (2017): 564–73. http://dx.doi.org/10.1590/1519-6984.174660.

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Abstract Fire is a recurrent disturbance in savanna vegetation and savanna species are adapted to it. Even so, fire may affect various aspects of plant ecology, including phenology. We studied the effects of a spatially heterogeneous fire on the reproductive phenology of two dominant woody plant species, Miconia albicans (Melastomataceae) and Schefflera vinosa (Araliaceae), in a savanna area in South-eastern Brazil. The study site was partially burnt by a dry-season accidental fire in August 2006, and we monitored the phenolology of 30 burnt and 30 unburnt individuals of each species between S

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Bibi, Adeela. "STUDY OF PHENOLOGICAL BEHAVIOR OF PLANTS OF LOWER TANAWAL, ABBOTTABAD, PAKISTAN." International Journal of Research -GRANTHAALAYAH 9, no. 12 (2021): 133–45. http://dx.doi.org/10.29121/granthaalayah.v9.i12.2021.4415.

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The purpose of this research study to explore the phonological behavior of plants of Lower Tanawal, Pakistan. The phenology of the 286 plants species belonging to 86 families from 80 stands of the Lower Tanawal Pakistan were documented during the different season of the year. It was observed that maximum flowering were recorded in March-April whereas maximum fruiting was noted in June-July. Plant phenology provides knowledge about the effects of environment on flowering and fruiting behavior. This is the first research work on phenology of plants of Lower Tanawal because no work was done on th

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Yang, Yi, Lei Yao, Xuecheng Fu, Ruihua Shen, Xu Wang, and Yingying Liu. "Spatial and Temporal Variations of Vegetation Phenology and Its Response to Land Surface Temperature in the Yangtze River Delta Urban Agglomeration." Forests 15, no. 8 (2024): 1363. http://dx.doi.org/10.3390/f15081363.

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In the Yangtze River Delta urban agglomeration, which is the region with the highest urbanization intensity in China, the development of cities leads to changes in land surface temperature (LST), while vegetation phenology varies with LST. To investigate the spatial and temporal changes in vegetation phenology and its response to LST in the study area, this study reconstructed the time series of the enhanced vegetation index (EVI) based on the MODIS EVI product and extracted the vegetation phenology indicators in the study area from 2002 to 2020, including the start of the growing season (SOS)

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Shi, Dandan, Yuan Jiang, Minghao Cui, Mengxi Guan, Xia Xu, and Muyi Kang. "Comparison of Spring Phenology from Solar-Induced Chlorophyll Fluorescence, Vegetation Index, and Ground Observations in Boreal Forests." Remote Sensing 17, no. 4 (2025): 627. https://doi.org/10.3390/rs17040627.

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Spring phenology (start of growing season, SOS) in boreal forests plays a crucial role in the global carbon cycle. At present, more and more researchers are using solar-induced chlorophyll fluorescence (SIF) to evaluate the land surface phenology of boreal forests, but few studies have utilized the primary SIF directly detected by satellites (e.g., GOME-2 SIF) to estimate phenology, and most SIF datasets used are high-resolution products (e.g., GOSIF and CSIF) constructed by models with vegetation indices (VIs) and meteorological data. Thus, the difference and consistency between them in detec

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Zhou, Y. K. "ANALYZING THE VELOCITY OF VEGETATION PHENOLOGY OVER THE TIBETAN PLATEAU USING GIMMS NDVI3g DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (May 2, 2018): 2575–78. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2575-2018.

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Global environmental change is rapidly altering the dynamics of terrestrial vegetation, and phenology is a classic proxy to detect the response of vegetation to the changes. On the Tibetan Plateau, the earlier spring and delayed autumn vegetation phenology is widely reported. Remotely sensed NDVI can serve as a good data source for vegetation phenology study. Here GIMMS NDVI3g data was used to detect vegetation phenology status on the Tibetan Plateau. The spatial and temporal gradients are combined to depict the velocity of vegetation expanding process. This velocity index represents the insta

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Yu, Meng, Yunfeng Cao, Jiaxin Tian, and Boyu Ren. "Increased Contribution of Extended Vegetation Growing Season to Boreal Terrestrial Ecosystem GPP Enhancement." Remote Sensing 17, no. 1 (2024): 83. https://doi.org/10.3390/rs17010083.

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Rapid Arctic warming is driving significant changes in boreal vegetation phenology and productivity. The potentially asynchronous response of these processes could substantially alter the relative impacts of phenological shifts on variations in gross primary productivity (GPP), but this remains poorly understood. The objective of this study is to quantify the impact of phenology extension on boreal ecosystem GPP changes across different periods from 1982 to 2018. To achieve this, we developed a statistical model that integrates vegetation phenology and physiology, and introduced a new metric,

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Visser, Marcel E., Samuel P. Caro, Kees van Oers, Sonja V. Schaper, and Barbara Helm. "Phenology, seasonal timing and circannual rhythms: towards a unified framework." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1555 (2010): 3113–27. http://dx.doi.org/10.1098/rstb.2010.0111.

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Phenology refers to the periodic appearance of life-cycle events and currently receives abundant attention as the effects of global change on phenology are so apparent. Phenology as a discipline observes these events and relates their annual variation to variation in climate. But phenology is also studied in other disciplines, each with their own perspective. Evolutionary ecologists study variation in seasonal timing and its fitness consequences, whereas chronobiologists emphasize the periodic nature of life-cycle stages and their underlying timing programmes (e.g. circannual rhythms). The (ne

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