Literature DB >> 27562030

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland.

Shilong Ren1, Xiaoqiu Chen2, Shuai An1.   

Abstract

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Entities:  

Keywords:  Grassland phenology; Plant senescence reflectance index; Remote sensing; Spatiotemporal pattern; Spatiotemporal response; Temperature and precipitation

Mesh:

Year:  2016        PMID: 27562030     DOI: 10.1007/s00484-016-1236-6

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  8 in total

1.  An analysis of relationships among plant community phenology and seasonal metrics of Normalized Difference Vegetation Index in the northern part of the monsoon region of China.

Authors:  X Chen; C Xu; Z Tan
Journal:  Int J Biometeorol       Date:  2001-11       Impact factor: 3.787

2.  Determining the growing season of land vegetation on the basis of plant phenology and satellite data in Northern China.

Authors:  X Chen; Z Tan; M D Schwartz; C Xu
Journal:  Int J Biometeorol       Date:  2000-08       Impact factor: 3.787

3.  Ecology. Phenology feedbacks on climate change.

Authors:  Josep Peñuelas; This Rutishauser; Iolanda Filella
Journal:  Science       Date:  2009-05-15       Impact factor: 47.728

4.  Modeling greenup date of dominant grass species in the Inner Mongolian Grassland using air temperature and precipitation data.

Authors:  Xiaoqiu Chen; Jing Li; Lin Xu; Li Liu; Deng Ding
Journal:  Int J Biometeorol       Date:  2013-09-25       Impact factor: 3.787

5.  Phenological responses of Ulmus pumila (Siberian Elm) to climate change in the temperate zone of China.

Authors:  Xiaoqiu Chen; Lin Xu
Journal:  Int J Biometeorol       Date:  2011-07-30       Impact factor: 3.787

6.  Grassland vegetation changes and nocturnal global warming

Authors: 
Journal:  Science       Date:  1999-01-08       Impact factor: 47.728

7.  Changes in Spectral Properties, Chlorophyll Content and Internal Mesophyll Structure of Senescing Populus balsamifera and Populus tremuloides Leaves.

Authors:  Karen L Castro; G Arturo Sanchez-Azofeifa
Journal:  Sensors (Basel)       Date:  2008-01-09       Impact factor: 3.576

8.  Leaf onset in the northern hemisphere triggered by daytime temperature.

Authors:  Shilong Piao; Jianguang Tan; Anping Chen; Yongshuo H Fu; Philippe Ciais; Qiang Liu; Ivan A Janssens; Sara Vicca; Zhenzhong Zeng; Su-Jong Jeong; Yue Li; Ranga B Myneni; Shushi Peng; Miaogen Shen; Josep Peñuelas
Journal:  Nat Commun       Date:  2015-04-23       Impact factor: 14.919

  8 in total
  9 in total

1.  Detecting the onset of autumn leaf senescence in deciduous forest trees of the temperate zone.

Authors:  Bertold Mariën; Manuela Balzarolo; Inge Dox; Sebastien Leys; Marchand J Lorène; Charly Geron; Miguel Portillo-Estrada; Hamada AbdElgawad; Han Asard; Matteo Campioli
Journal:  New Phytol       Date:  2019-07-23       Impact factor: 10.151

Review 2.  Soybean cyst nematode detection and management: a review.

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Journal:  Plant Methods       Date:  2022-09-07       Impact factor: 5.827

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Journal:  Environ Model Softw       Date:  2020-03-10       Impact factor: 5.471

4.  Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression.

Authors:  Matías Salinero-Delgado; José Estévez; Luca Pipia; Santiago Belda; Katja Berger; Vanessa Paredes Gómez; Jochem Verrelst
Journal:  Remote Sens (Basel)       Date:  2021-12-29       Impact factor: 5.349

5.  Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring.

Authors:  Santiago Belda; Luca Pipia; Pablo Morcillo-Pallarés; Jochem Verrelst
Journal:  Agronomy (Basel)       Date:  2020-04-27       Impact factor: 3.949

6.  Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery.

Authors:  Katja Berger; Tobias Hank; Andrej Halabuk; Juan Pablo Rivera-Caicedo; Matthias Wocher; Matej Mojses; Katarina Gerhátová; Giulia Tagliabue; Miguel Morata Dolz; Ana Belen Pascual Venteo; Jochem Verrelst
Journal:  Remote Sens (Basel)       Date:  2021-11-21       Impact factor: 5.349

7.  Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm.

Authors:  Changwei Tan; Xinxing Zhou; Pengpeng Zhang; Zhixiang Wang; Dunliang Wang; Wenshan Guo; Fei Yun
Journal:  PLoS One       Date:  2020-03-11       Impact factor: 3.240

8.  Multispectral Optical Remote Sensing for Water-Leak Detection.

Authors:  Jean-Claude Krapez; Javier Sanchis Muñoz; Christophe Mazel; Christian Chatelard; Philippe Déliot; Yves-Michel Frédéric; Philippe Barillot; Franck Hélias; Juan Barba Polo; Vincent Olichon; Guillaume Serra; Céline Brignolles; Alexandra Carvalho; Duarte Carreira; Anabela Oliveira; Elsa Alves; André B Fortunato; Alberto Azevedo; Paolo Benetazzo; Alessandro Bertoni; Isabelle Le Goff
Journal:  Sensors (Basel)       Date:  2022-01-29       Impact factor: 3.576

9.  Monitoring the long term vegetation phenology change in Northeast China from 1982 to 2015.

Authors:  Lingxue Yu; Tingxiang Liu; Kun Bu; Fengqin Yan; Jiuchun Yang; Liping Chang; Shuwen Zhang
Journal:  Sci Rep       Date:  2017-11-07       Impact factor: 4.379

  9 in total

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