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Monitoring Vegetation Phenology: Trends and Anomalies

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

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 33400

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Dr. Jordi Cristóbal Rosselló

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Department of Geography, Autonomous University of Barcelona, 08193 Cerdanyola del Vallès, Spain
Interests: surface energy balance; thermal infrared; time series analysis; hydrological modeling; radiometric correction; field spectroscopy; land cover and land use analysis; snow cover; water resources
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Dr. Xavier Pons

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Grumets Research Group, Departament de Geografia, Edifici B, Universitat Autònoma de Barcelona, 08193 Bellaterra, Catalonia, Spain
Interests: remote sensing; GIS; climatology; ecology; geography

Dr. Ricardo Díaz-Delgado

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LAST (Remote Sensing & GIS Lab), Doñana Biological Station-CSIC, Avda. Américo Vespucio 26, Isla de la Cartuja, 41092 Sevilla, Spain
Interests: multi and hyperspectral remote sensing for monitoring vegetation, wetlands and landscape changes; multitemporal analysis of remote sensing images; predictive mapping of species habitat distribution; landscape dynamics and interactions with wildfire regimes; plant regeneration trends under different disturbance regimes
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Dr. Marion Stellmes

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Freie Universität Berlin, Institute of Geographical Sciences, Remote Sensing and Geoinformatics, Malteserstraße 74-100, 12249 Berlin, Germany
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Dear Colleagues,

Monitoring vegetation phenology with satellite data is currently both easier and more common. Remote sensing of phenology is an important method for studying the patterns of vegetation growth cycles. Phenological events are sensitive to climate variation and provide baseline information to analyze trends in ecological processes or in climatology itself, allowing the detection of climate change impacts on multiple scales worldwide.

In a climate change perspective, warming trends have important phenology impacts over vegetation. For example, detecting changes in vegetation at high latitudes is vital for evaluating changes to carbon and energy budgets, so understanding terrestrial vegetation patterns of response to climate change can also help to focus on methods to mitigate land degradation. Over at least the past three decades, Arctic ecosystems have shown evidence of “greening”, with about a 14 % increase in peak vegetation for the Arctic tundra biome, while boreal forest is “browning” due to warmer temperatures, drier conditions and tree mortality. In Mediterranean and Atlantic ecosystems, extreme climate events such as droughts are also inducing changes in growth phenology, advancing spring growth phenology or shortening vegetation growing, amongst others.

This Special Issue seeks contributions on Monitoring Vegetation Phenology ranging from review papers to basic research giving innovative views. The focus will be on spatial-temporal analysis (patterns and/or anomalies) of annual greening/browning (year-round phenology) including and not limited to time series analysis of vegetation using optical spectrum and/or thermal remote sensing data (vegetation and/or stress indices, surface temperature, etc), as well as new or reviewed climate datasets.

Dr. Jordi Cristóbal Rosselló

Dr. Xavier Pons
Dr. Ricardo Díaz-Delgado
Dr. Marion Stellmes
Guest Editors

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Keywords

time series analysis
vegetation indices
surface temperature
greening
browning
vegetation/land cover change
phenology

Published Papers (8 papers)

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Research

14 pages, 19759 KiB

Open AccessArticle

Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe

by Boyi Liang, Hongyan Liu, Xiaoqiu Chen, Xinrong Zhu, Elizabeth L. Cressey and Timothy A. Quine

Remote Sens. 2020, 12(11), 1805; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12111805 - 03 Jun 2020

Cited by 8 | Viewed by 2312

Abstract

In this paper, cross-spectrum analysis was used to verify the agreement of periodicity between the global LAI (leaf area index) and climate factors. The results demonstrated that the LAI of deciduous forests and permanent wetlands have high agreement with temperature, rainfall and radiation over annual cycles. A low agreement between the LAI and seasonal climate variables was observed for some of the temperate and tropical vegetation types including shrublands and evergreen broadleaf forests, possibly due to the diversity of vegetation and human activities. Across all vegetation types, the LAI demonstrated a large time lag following variation in radiation (>1 month), whereas relatively short lag periods were observed between the LAI and annual temperature (around 2 weeks)/rainfall patterns (less than 10 days), suggesting that the impact of radiation on global vegetation growth is relatively slow, which is in accord with the results of previous studies. This work can provide a benchmark of the phenological drivers in global vegetation, from the perspective of periodicity, as well as helping to parameterize and refine the DGVMs (Dynamic Global Vegetation Models) for different vegetation types. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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19 pages, 3184 KiB

Open AccessArticle

Trend Evolution of Vegetation Phenology in China during the Period of 1981–2016

by Fusheng Jiao, Huiyu Liu, Xiaojuan Xu, Haibo Gong and Zhenshan Lin

Remote Sens. 2020, 12(3), 572; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12030572 - 08 Feb 2020

Cited by 30 | Viewed by 3426

Abstract

The trend of vegetation phenology dynamics is of crucial importance for understanding vegetation growth and its responses to climate change. However, it remains unclear how the trends of vegetation phenology changed over the past decades. By analyzing phenology data including start (SOS), end (EOS) and length (LOS) of growth season with the Ensemble empirical mode decomposition (EEMD), we revealed the trend evolution of vegetation phenology in China during 1981-2016. Our study suggests that: (1) On the national scale, with EEMD method, the change rates of SOS and LOS were increasing with time, while that of EOS was decreasing. Moreover, the EEMD rates of SOS and LOS exceeded the linear rates in the early-2000s, while that of EOS dropped below the linear rate in the mid-1980s. (2) For each phenological event, the shifted trends took up a large area (~30%), which was close to the sum of all monotonic trends, but more than any monotonic trend type. The shifted trends mainly occurred in the north-eastern China, eastern Qinghai-Tibetan Plateau, eastern Sichuan Basin, North China Plain and Loess Plateau. (3) For each phenological event, the areas in the high-latitude experienced the contrary trends to the other. The amplitude and frequencies of phenology variation in the mid-latitude were stronger than those in the high-latitude and low-latitude. Meanwhile, LOS in the high-latitude was induced by SOS. (4) For each phenological event, the trend evolution varying with longitudes can be divided into eastern region (east of 121°E), central region (92°E–121°E) and western region (west of 92°E) based on the evolution of trends varying with longitudes. The east experienced a delayed SOS and a shorten LOS, which was different from the other areas. The magnitude of delayed trends in EOS and the prolonged trends in LOS were stronger from east to west as longitudes changes. The variation characteristics of LOS with longitude were mainly caused by SOS in the eastern region and by SOS and EOS together in the western and central region. (5) Each land cover types, except Needleleaf Forests, experienced the same trends. For most land cover types, the advance of SOS, delay of EOS and extension of LOS began in the 1980s, the 1990s, and the 1990s, respectively and enhanced several times. Moreover, the magnitudes of Grasslands in SOS and Evergreen Broadleaf Forest in EOS were much greater than the others, while that of croplands was the smallest in each phenological event. Our results showed that the analysis of trend evolution with nonlinear method is very important to accurately reveal the variation characteristics of phenology trends and to extract the inherent trend shifts. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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23 pages, 10310 KiB

Open AccessArticle

Assessment of the Biomass Productivity Decline in the Lower Mekong Basin

by Quyet Manh Vu, Venkat Lakshmi and John Bolten

Remote Sens. 2019, 11(23), 2796; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11232796 - 26 Nov 2019

Cited by 4 | Viewed by 3052

Abstract

This study aimed to delineate the geographic hotspots of negative trends in biomass productivity in the Lower Mekong Basin countries (Vietnam, Cambodia, Laos, and Thailand) and identify correlated regional environmental and anthropogenic factors. A long-term time-series (1982–2015) of Normalized Difference Vegetation Index at a resolution of approximately 9.16 km × 9.16 km was used to specify the areas with significant decline or increase in productivity. The relationships between vegetation changes and land attributes, such as climate, population density, soil/terrain conditions, and land-cover types, were examined. Rainfall time-series maps were used to identify areas that might have been affected by land degradation from those correlated with rainfall. Most of the detected potentially degraded areas were found in Cambodia, the Northwest and the Highland of Vietnam, the Northern Mountains of Thailand and Laos, and the mountainous border between Laos, Vietnam, and Cambodia. About 15% of the total land area of these four countries experienced a reduction in biomass productivity during the 34-year study period. The map of hotspots of changes in productivity can be used to direct further studies, including those at finer spatial resolution that may support policy makers and researchers in targeting the strategies for combating land degradation. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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21 pages, 7029 KiB

Open AccessArticle

Asymmetric Behavior of Vegetation Seasonal Growth and the Climatic Cause: Evidence from Long-Term NDVI Dataset in Northeast China

by Yuke Zhou

Remote Sens. 2019, 11(18), 2107; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11182107 - 10 Sep 2019

Cited by 12 | Viewed by 3059

Abstract

Land surface phenology is a response of vegetation to local climate and to climate change, leading to crucial impacts on plant growth rhythm and productivity. Differences in vegetation growth activities in earlier and latter parts of the growing season are tightly correlated to phenological changes and the temporal distribution of plant productivity. However, its spatiotemporal pattern and climatic constraints are poorly understood. For Northeast China (NEC), long-term remotely-sensed vegetation greenness records (NDVI) were employed to quantify seasonally asymmetrical characteristics of vegetation growth in detail, which consists of asymmetry in growing rate (AsyR), mean vegetation greenness (AsyV), and growing period length (AsyL) during vegetation green up and senescence stages (simply termed as spring and autumn). Furthermore, the impact of temperature and precipitation on these indices were examined using relative importance analysis. The results indicate these asymmetric metrics present a pronounced interannual variability profile with a potential cycle of ten years (significant in AsyV and AsyR) for the entire NEC. AsyV is changing synchronously with AsyL but asynchronously with AsyR. The geographical distribution of asymmetric indices shows a similar pattern to identified vegetation cover types, especially in distinguishing crops from natural vegetation. Spatial-averaged asymmetric indices indicate spring production is greater than autumn production (reflected by negative AsyV) across most vegetation types in NEC, yet autumn is longer than spring in all vegetation types, which is identified by positive AsyL. Negative AsyR is mainly found in forests implying there is rapid green up and slow senescence in trees. From a temporal perspective, AsyV decreases with time in forested regions but increases in cropland and grassland, which is similar to the pattern for AsyL. AsyR primarily exhibits a positive trend in forest and a negative trend in cropland and grassland. A relative importance analysis indicates that asymmetries of temperature (AsyTemp) and precipitation (AsyPrcp) play an equal role in significantly affecting vegetation asymmetries in greenness and growth rate but are insignificant to growing season length. AsyTemp mainly presents an obvious contribution to changes in AsyR and AsyV over cropland and grassland. AsyPrcp shows a more widespread controlling effect on AsyR and AsyV over the NEC, except in eastern broad-leaved forest. For the entire NEC, asymmetries of temperature and precipitation are negatively correlated with AsyR but are positively correlated with AsyV and AsyL. This finding may imply that a warmer (positive AsyTemp) autumn tends to improve the length and intensity of vegetation activity. Thus, the long-term change in vegetation growth asymmetries may provide insights for the altering functions of ecosystems and provide information to more accurately build plant growth models in the context of global climate change. Additionally, when combined with other information, asymmetric indices can serve as a supporting tool in classification of vegetation types. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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18 pages, 16150 KiB

Open AccessArticle

Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology

by Guorong Deng, Hongyan Zhang, Xiaoyi Guo, Yu Shan, Hong Ying, Wu Rihan, Hui Li and Yangli Han

Remote Sens. 2019, 11(14), 1651; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11141651 - 11 Jul 2019

Cited by 19 | Viewed by 4555

Abstract

Vegetation phenology is the most intuitive and sensitive biological indicator of environmental conditions, and the start of the season (SOS) can reflect the rapid response of terrestrial ecosystems to climate change. At present, the model based on mean temperature neglects the role of the daytime maximum temperature (TMAX) and the nighttime minimum temperature (TMIN) in providing temperature accumulation and cold conditions at leaf onset. This study analyzed the spatiotemporal variations of spring phenology for the boreal forest from 2001 to 2017 based on the moderate-resolution imaging spectro-radiometer (MODIS) enhanced vegetation index (EVI) data (MOD13A2) and investigated the asymmetric effects of daytime and nighttime warming on the boreal forest spring phenology during TMAX and TMIN preseason by partial correlation analysis. The results showed that the spring phenology was delayed with increasing latitude of the boreal forest. Approximately 91.37% of the region showed an advancing trend during the study period, with an average advancement rate of 3.38 ± 0.08 days/decade, and the change rates of different land cover types differed, especially in open shrubland. The length of the TMIN preseason was longer than that of the TMAX preseason and diurnal temperatures showed an asymmetrical increase during different preseasons. The daytime and nighttime warming effects on the boreal forest are asymmetrical. The TMAX has a greater impact on the vegetation spring phenology than TMIN as a whole and the effect also has seasonal differences; the TMAX mainly affects the SOS in spring, while TMIN has a greater impact in winter. The asymmetric effects of daytime and nighttime warming on the SOS in the boreal forest were highlighted in this study, and the results suggest that diurnal temperatures should be added to the forest terrestrial ecosystem model. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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21 pages, 6376 KiB

Open AccessArticle

Identification of Natural and Anthropogenic Drivers of Vegetation Change in the Beijing-Tianjin-Hebei Megacity Region

by Yinbing Zhao, Ranhao Sun and Zhongyun Ni

Remote Sens. 2019, 11(10), 1224; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11101224 - 23 May 2019

Cited by 20 | Viewed by 3272

Abstract

Identifying the natural and anthropogenic mechanisms of vegetation changes is the basis for adapting to climate change and optimizing human activities. The Beijing-Tianjin-Hebei megacity region, which is characterized by significant geomorphic gradients, was chosen as the case study area. The ordinary least squares (OLS) method was used to calculate the NDVI trends and related factors from 2000 to 2015. A geographic weighted regression (GWR) model of NDVI trends was constructed using 14 elements of seven categories. Combined with the GWR calculation results, the mechanisms of the effects of explanatory variables on NDVI changes were analyzed. The findings suggest that the overall vegetation displayed an increasing trend from 2000 to 2015, with an NDVI increase of ca. 0.005/year. Additionally, the NDVI fluctuations in individual years were closely related to precipitation and temperature anomalies. The spatial pattern of the NDVI change was highly consistent with the gradients of geomorphology, climate, and human activities, which have a tendency to gradually change from northwest to southeast. The dominant climate-driven area accounted for only 5.98% of the total study area. The vegetation improvement areas were regionally concentrated and had various driving factors, and vegetation degradation exhibited strong spatial heterogeneity. The vegetation degradation was mainly caused by human activities. Natural vegetation was improved because of natural factors and reductions in human activities. Moreover, cropland vegetation as well as urban and built-up area improvements were related to increased human actions and decreased natural effects. This study can assist in ecological restoration planning and ecological engineering implementation in the study area. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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14 pages, 2656 KiB

Open AccessArticle

Heat and Drought Stress Advanced Global Wheat Harvest Timing from 1981–2014

by Shilong Ren, Qiming Qin, Huazhong Ren, Juan Sui and Yao Zhang

Remote Sens. 2019, 11(8), 971; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11080971 - 23 Apr 2019

Cited by 10 | Viewed by 4108

Abstract

Studying wheat phenology can greatly enhance our understanding of how wheat growth responds to climate change, and guide us to reasonably confront its influence. However, comprehensive global-scale wheat phenology–climate analysis is still lacking. In this study, we extracted the wheat harvest date (WHD) from 1981–2014 from satellite data using threshold-, logistic-, and shape-based methods. Then, we analyzed the effects of heat and drought stress on WHD based on gridded daily temperature and monthly drought data (the Palmer drought severity index (PDSI) and the standardized precipitation evapotranspiration index (SPEI)) over global wheat-growing areas. The results show that WHD was generally delayed from the low to mid latitudes. With respect to variation trends, we detected a significant advancement of WHD in 32.1% of the world’s wheat-growing areas since 1981, with an average changing rate of −0.25 days/yr. A significant negative correlation was identified between WHD and the prior three months’ normal-growing-degree-days across 50.4% of the study region, which implies that greater preseason effective temperature accumulation may cause WHD to occur earlier. Meanwhile, WHD was also found to be significantly and negatively correlated with the prior three months’ extreme-growing-degree-days across only 9.6% of the study region (mainly located in northern South Asia and north Central-West Asia). The effects of extreme heat stress were weaker than those of normal thermal conditions. When extreme drought (measured by PDSI/SPEI) occurred in the current month, in the month prior to WHD, and in the second month prior to WHD, it forced WHD to advance by about 9.0/8.1 days, 13.8/12.2 days, and 10.8/5.3 days compared to normal conditions, respectively. In conclusion, we highlight the effects that heat and drought stress have on advancing wheat harvest timing, which should be a research focus under future climate change. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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23 pages, 9879 KiB

Open AccessArticle

Spatio-Temporal Analysis of Vegetation Dynamics as a Response to Climate Variability and Drought Patterns in the Semiarid Region, Eritrea

by Simon Measho, Baozhang Chen, Yongyut Trisurat, Petri Pellikka, Lifeng Guo, Sunsanee Arunyawat, Venus Tuankrua, Woldeselassie Ogbazghi and Tecle Yemane

Remote Sens. 2019, 11(6), 724; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11060724 - 26 Mar 2019

Cited by 62 | Viewed by 8618

Abstract

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services. Full article

(This article belongs to the Special Issue Monitoring Vegetation Phenology: Trends and Anomalies)

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