Phenological Maps Research Articles

Phenology from Landsat when data is scarce: Using MODIS and Dynamic Time-Warping to combine multi-year Landsat imagery to derive annual phenology curves

Green-leaf phenology describes the development of vegetation throughout a growing season and greatly affects the interaction between climate and the biosphere. Remote sensing is a valuable tool to characterize phenology over large areas but doing at fine- to medium resolution (e.g., with Landsat data) is difficult because of low numbers of cloud-free images in a single year. One way to overcome data availability limitations is to merge multi-year imagery into one time series, but this requires accounting for phenological differences among years. Here we present a new approach that employed a time series of a MODIS vegetation index data to quantify interannual differences in phenology, and Dynamic Time Warping (DTW) to re-align multi-year Landsat images to a common phenology that eliminates year-to-year phenological differences. This allowed us to estimate annual phenology curves from Landsat between 2002 and 2012 from which we extracted key phenological dates in a Monte-Carlo simulation design, including green-up (GU), start-of-season (SoS), maturity (Mat), senescence (Sen), end-of-season (EoS) and dormancy (Dorm). We tested our approach in eight locations across the United States that represented forests of different types and without signs of recent forest disturbance. We compared Landsat-based phenological transition dates to those derived from MODIS and ground-based camera data from the PhenoCam-network. The Landsat and MODIS comparison showed strong agreement. Dates of green-up, start-of-season and maturity were highly correlated (r 0.86-0.95), as were senescence and end-of-season dates (r>0.85) and dormancy (r>0.75). Agreement between the Landsat and PhenoCam was generally lower, but correlation coefficients still exceeded 0.8 for all dates. In addition, because of the high data density in the new Landsat time series, the confidence intervals of the estimated keydates were substantially lower than in case of MODIS and PhenoCam. Our study thus suggests that by exploiting multi-year Landsat imagery and calibrating it with MODIS data it is possible to describe green-leaf phenology at much finer spatial resolution than previously possible, highlighting the potential for fine scale phenology maps using the rich Landsat data archive over large areas.

FAO’s AVHRR-based Agricultural Stress Index System (ASIS) for global drought monitoring

ABSTRACTAgricultural production is highly dependent on climate variability in many parts of the world. In particular, drought may severely reduce crop yields, potentially affecting food availability at local, regional, and global scales. The Food and Agriculture Organization of the United Nations (FAO) operates the Global Early Warning System (GIEWS), which monitors global food supply and demand. One of the key challenges is to obtain synoptic information on a recurrent and timely basis about drought-affected agricultural zones. This is needed to quickly identify areas requiring immediate attention. The Agricultural Stress Index System (ASIS), based on imagery from the Advanced Very High Resolution Radiometer (AVHRR) sensors on board the National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational Satellite (METOP) satellites, was specifically developed to meet this need. The system is based on a methodology developed by Rojas, Vrieling, and Rembold over the African continent. This approach has been modified and adapted to the global scale to produce an agricultural stress index (ASI) representing, per administrative unit, the percentage of cropland (or pasture) areas affected by drought over the growing season. The vegetation health index (VHI), based on normalized difference vegetation index (NDVI) and temperature anomalies, is used as a drought indicator. A fused time series of AVHRR data from METOP and NOAA was used to produce a consistent time series of VHI at 1 km resolution. Global phenology maps, indicating the number of growing seasons and their start and end dates, were derived from a multi-annual image set of SPOT-Vegetation (1999–2011). The VHI time series and phenology maps were then combined to produce the ASI for the years 1984 to the present. This allowed evaluation of the suitability of the ASIS to identify drought using historical reports and ancillary data. As a result of this analysis, ASIS was positively evaluated to support the FAO early warning system.

Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations

Phytoplankton biomass is important to monitor in lakes due to its influence on water quality and lake productivity. Phytoplankton has also been identified as sensitive to environmental change, with shifts in the seasonality of blooms, or phenology, resulting from changing temperature and nutrient conditions. A satellite remote sensing approach to retrieving and mapping freshwater phytoplankton phenology is demonstrated here in application to Lake Balaton, Hungary. Chlorophyll-a (chl-a) concentration mapping using Medium Resolution Imaging Spectrometer (MERIS) allows new insights into such spatiotemporal dynamics for Lake Balaton as bloom start, peak and end timing, duration, maximum chl-a concentrations, spatial extent, rates of increase and decrease, and bloom chl-a concentration integral. TIMESAT software is used to extract and map these phenology metrics. Three approaches to time series smoothing are compared and mapped metrics are evaluated in comparison with phenology metrics of in situ chl-a. The high degree of both spatial and temporal variability is highlighted and discussed, as are methodological limitations and correlation between phenology metrics. Both the feasibility of and novel insights permitted through such phenology mapping are demonstrated, and priority topics for future research are suggested.

Spatiotemporal analysis of olive flowering using geostatistical techniques

Analysis of flowering patterns in the olive (Olea europaea L.) are of considerable agricultural and ecological interest, and also provide valuable information for allergy-sufferers, enabling identification of the major sources of airborne pollen at any given moment by interpreting the aerobiological data recorded in pollen traps. The present spatiotemporal analysis of olive flowering in central Spain combined geostatistical techniques with the application of a Geographic Information Systems, and compared results for flowering intensity with airborne pollen records. The results were used to obtain continuous phenological maps which determined the pattern of the succession of the olive flowering.The results show also that, although the highest airborne olive-pollen counts were recorded during the greatest flowering intensity of the groves closest to the pollen trap, the counts recorded at the start of the pollen season were not linked to local olive groves, which had not yet begin to flower. To detect the remote sources of olive pollen several episodes of pollen recorded before the local flowering season were analysed using a HYSPLIT trajectory model and the findings showed that western, southern and southwestern winds transported pollen grains into the study area from earlier-flowering groves located outside the territory.

The effect of urban morphology on Tilia × europaea flowering

Urban planners need tools to manage urban growth without compromising the citizens’ quality of life. Urban vegetation plays an important role in regulating local climate and improving air quality. Further, urban vegetation provides non quantifiable psychological and aesthetic benefits. On the other hand, vegetation also has negative impacts, such as allergen risk due to pollen dispersion. This paper investigates the effects of urbanization on tree phenology, exploring the intra-urban variability of Tilia×europaea L. flowering in Florence (Italy). Phenological observations were related to local air temperature, distance from the city center, impervious surfaces and building density. Data collected were used to test whether urban characteristics could be used to describe phenophase timing differences in the city. These differences are explained both by seasonal temperature variation as well as by impervious surface density. In fact T.×europaea flowering occurred first in the areas with a higher percentage of impervious surfaces. Both the start and end of flowering advanced by 1.4 days with a 10% increase in impervious surfaces. Our results suggest a potential application of the “impervious surfaces” urban morphology indicator to predict phenological shifts in an urban environment. These indicators can be processed by geographic information system tools to produce phenological maps of a specific urban area or future urban planning scenarios. This information can be used to improve the evaluation of the benefits and drawbacks of trees, such as their impact on local temperatures, the aesthetic improvement of the urban landscape or the negative effects on human health due to the risk of pollen allergy during the flowering period.

A Novel Land Cover Classification Map Based on a MODIS Time-Series in Xinjiang, China

Accurate mapping of land cover on a regional scale is useful for climate and environmental modeling. In this study, we present a novel land cover classification product based on spectral and phenological information for the Xinjiang Uygur Autonomous Region (XUAR) in China. The product is derived at a 500 m spatial resolution using an innovative approach employing moderate resolution imaging spectroradiometer (MODIS) surface reflectance and the enhanced vegetation index (EVI) time series. The classification results capture regional scale land cover patterns and small-scale phenomena. By applying a regionally specified classification scheme, an extensive collection of training data, and regionally tuned data processing, the quality and consistency of the phenological maps are significantly improved. With the ability to provide an updated land cover product considering the heterogenic environmental and climatic conditions, the novel land cover map is valuable for research related to environmental change in this region.

Modelling and mapping of plant phenological stages as bio-meteorological indicators for climate change

In Hesse, a federal state in central Germany, the average air temperature of the period 1991 to 2009 was by 0.9°C higher compared to that of 1961 to 1990. A further rise in air temperature of up to 3.7°C compared to the reference period 1971 to 2000 is expected until the end of the twenty-first century. This may affect the beginning and length of phenological stages of plants. Hence, this project should analyse and model spatiotemporal trends of plant phenology as being an indicator for climate change-related biological effects. Meteorological data together with data on 35 phenological phases of plants indicating different phenological seasons and observed at 6,500 sites in Germany (553 in Hesse) between 1961 and 2009 were analysed in a GIS. Estimations on phenological developments in the future periods 2031 to 2060 and 2071 to 2100 were based on data from four regional climate models. Thirty-one out of 35 phases started earlier in the years 1991 to 2009 compared with 1961 to 1990. These shifts were stronger in Hesse (8 days) than in Germany (6 days). As winter phases tend to shift towards the end of the year, a prolongation of the vegetation period of up to 3 weeks was observed. More than 70% of the phases were correlated with air temperature by r ≥ 0.5, more than 50% even by r ≥ 0.7. Since the 1990s, phenological shifts and regional differences in phase onsets amplified. In many cases, the shifts between 2071 to 2100 and 1961 to 1990 are expected to be at least twice as high as those between 1991 to 2009 and 1961 to 1990. The presented approach allows revealing statistical relationships between air temperatures and phenological onsets. Thus, shifts in plant phenology are an appropriate bioindicator to map early signs of ecosystem transitions under climate change. The phenological records allow estimating future trends of plant phenological development. Using phenological maps as presented in this article, efficient adaption strategies may be planned and implemented in terms of, e.g. adjusting delineation, shape and allocation of protected areas.

IPHEN—a real-time network for phenological monitoring and modelling in Italy

This paper aims to describe the Italian PHEnology Network (IPHEN), a cooperative project started in 2006 with the aim of producing nationwide maps of analysis and forecast of plants phenological stages mainly used to satisfy the needs of agriculture, health and environmental care. Iphen is a data processing system composed of the following main segments (a) collection of atmospheric and phenological data, (b) processing of data with suitable phenological and geo-statistical models and (c) phenological maps of analysis and forecast. In more detail, IPHEN maps of analysis (featuring phenological stages reached at the date of processing) are produced with models based on a Normal Heat Hours approach which weighs hourly air temperature effectiveness for plant phenological progression applied to national grids of hourly temperature derived from the operational agro-meteorological network of CRA-CMA. A correction scheme based on phenological surveys provided by volunteer observers is applied to the first guess maps of analysis to obtain final maps. Forecast maps (prediction of the days of occurrence of relevant phenological stages) are produced on the basis of GFS model medium range forecasts and climatic data. Freeware IPHEN maps for grapevine, common and Arizona cypress, black elder, olive and locust trees are broadcasted weekly on the CRA-CMA website. The positive operational results of IPHEN are testified by 150 maps broadcasted during the 2011 season for the above-mentioned species. The system performances and reliability have been analysed focusing on the analysis of phenological simulation errors and on the sensitivity of phenological maps to anomalous atmospheric circulation patterns. The error analysis shows that phenological models are characterized by advances/delays that justify the adoption of an observation based correction scheme. The sensitivity analysis highlights that the system is responsive to the effects of circulation blocking systems leading to phenological advances and delays.

The Use of Geostatistics in the Study of Floral Phenology ofVulpia geniculata(L.) Link

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

The reliability of geostatistic interpolation in olive field floral phenology

Floral phenology, as most of natural phenomena, shows, as an inherent feature, a high degree of spatial continuity. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating no monitored sampling points. The combined use of Geographical Information Systems (GIS) and geostatistics can be an essential tool for spatial analysis in phenological and aerobiological studies. In the present work, Kriging interpolation by using linear geostatistic analysis has allow us to estimate phenological data of a wide olive crop area of the province of Cordoba (Andalusia, Southern Spain), on the basis of a limited number of␣phenology sampling points. The main a priori hypothesis was that 7 traditionally observed sampling points (with 10 olive trees in each site) uniformly distributed through the main olive crop areas could be enough for interpolating phenological information of the whole Cordoba olive area. Geostatistical results reject this hypothesis. The optimum/minimum number and location of sampling points was determined in 13 sites (including the original 7 sites and 6 new sites). The obtained phenological maps will improve␣olive pollen aerobiological information and forecasting in the area. The application of such new combined space analysis tools on floral phenology allows optimising human and economic resources on field phenology campaigns. Moreover, an appropriate use of GIS and geostatistic software to create phenological maps will be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

Phenological maps of Europe

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 18:249-257 (2001) - doi:10.3354/cr018249 Phenological maps of Europe Thomas Rötzer*, Frank-M. Chmielewski Institute of Crop Sciences, Subdivision of Agricultural Meteorology, College of Agriculture and Horticulture, Humboldt-University of Berlin, Albrecht-Thaer-Weg 5, 14195 Berlin-Dahlem, Germany *E-mail: thomasroetzer@web.de ABSTRACT: The geographical distribution of the timings of phenological phases is a precondition for detecting regional trends of the annual timings of phenological phases and finding their relationships to climate changes. Therefore phenological maps of Europe have been computed showing long-term means, trends and annual timings of extreme years. In this article maps of the beginning, the end and the length of the growing season as means over the years 1961-1998 as well as for the warm year 1990 are presented. Strong dependences on altitude, longitude and latitude were computed both for single phenological phases and the beginning and end of the growing season. The goodness of fit for the regression equation was between 32% for the end and 83% for the beginning of growing season. The results were consistent with those of similar investigations. KEY WORDS: Phenology · Maps · Growing season · GIS · Europe Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 18, No. 3. Online publication date: November 02, 2001 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2001 Inter-Research.

Impact of landscape features on spring phenological phases of maple and bird cherry in Estonia

We analysed the spatial distribution of the pollinationof maple (Acer platanoides L.) and bird cherry (Prunus padus L.) in Estonia on the basis of phenological data from the time series for 1948–1995, in 27 observation points, and from the special field observation programme 1996–1999, in 46 observation points. Phenological maps show that these springtime phenophases spread in the landscape at a rate of 3–6 days per 100 km, with different rates in early and late springs. The maple has a steeper gradient on northeastern islands and the bird cherry on the western islands; the values of standard deviation have a similar spatial pattern. The distribution of phenological phases in Estonia is influenced by differences between the temperature regimes of the Baltic Sea and inland areas, different climatic conditions in north-eastern Estonia, local altitude-impact of uplands with an absolute height of 150–300 m asl, and the effects of bigger lakes and wetland areas. On the basis of spring phenology, three seasonally different landscape types can be determined in Estonia: (1) Relatively continental South-East Estonian Plain and uplands – have the earliest spring with the smallest deviations and stable intervals between phases, (2) Central, western and northern Estonian plains – with temperate influence of the temperature regime of the Baltic Sea, and big variations from year to year. Large variability is caused by the presence and duration of ice cover on the sea in cold springs, and direct access by warm air masses in early springs. (3) North-east Estonia – has the most boreal climate with longer snow cover and very late spring, influenced by arctic air masses, local influence of the Baltic Sea, uplands, and large wetlands.

Predictive modeling of the potential natural vegetation pattern in the Podyjí National Park, Czech Republic

The relationships between 10 types of potential natural vegetation and several environmental factors derived from a topographical map (altitude, slope inclination, curvature, potential direct solar irradiation, sky view factor), a geological map and a spring phenological map, were modeled for the Podyji National Park (Czech Republic). Different vegetation pattern models were made using spatial predictive modeling together with the Bayes formula. Compared with the field-based vegetation map, the model which included geology as a factor and all the factors derived from the topographic map, yielded an overall correspondence (i.e. percentage of grid cells in which vegetation types in the field-based map and in the model matched) of 56.8%. This measure of correspondence, however, is not dependable in areas, such as the Podyji National Park, where one vegetation type prevails. Therefore, correspondence within vegetation types, i.e. the average of correspondences calculated for each vegetation type separately, was used, thus yielding a value of 39.4%. The most important factors in this model were the sky view factor, representing the differences between the valleys and the gently undulating uplands, and altitude, as a surrogate for the macroclimatic gradient. By replacing altitude and irradiation variables related to the macroclimate and mesoclimate respectively, with the spring phenological map, overall correspondence with the original map was increased to 62.6% and correspondence within vegetation types to 50.5%. This result shows that phenological maps, which are relatively easy to create and provide a surrogate for unavailable local climatic maps, might be a powerful tool for predicting vegetation pattern on landscape scale.

Phenological mapping in a topographically complex landscape by combining field survey with an irradiation model

Abstract. A phenological map has been prepared for the Podyjí/Thayatal National Park, located on the border between the Czech Republic and Austria. The area is characterized by V‐shaped river valleys deeply incised into a gently undulating landscape. Five stages of phenological development were defined, based upon phenological spectra of plant communities in late April; 96 sites, more or less regularly spaced over the area, were assigned to one of these stages using field observations of these spectra. Potential direct solar irradiation was calculated from a digital elevation model for a 25 m x 25 m grid extending over the study area. A method was developed for interpolation of phenological observations by weighted regression of phenology on the irradiation model. This interpolation enables the prediction of the local stage of phenological development across the study area without levelling out phenological patterns dependent upon small‐scale topographic variation. Spring phenological events appear to be more advanced in the valleys (except for steep north‐facing slopes) than in the adjacent landscape. Possible climatic processes underlying this pattern are discussed with emphasis on temperature inversions in the river valleys. Cold‐air‐drainage inversions reported from the valleys are probably too infrequent and of too short duration to delay plant phenology. The combined effects of advanced phenology and the increased risk of spring frost injury due to these inversions in the valleys may be an explanation for local distributional patterns of flora and vegetation.

Methods in phenological mapping

Phenological maps of flowering provide useful information about both spatial and temporal patterns of pollen emission, and their use could bring a substantial improvement of aerobiological forecasts. This paper presents a method for preparing flowering maps by computer on the basis of phenological data and topography. Data drawn from topographic maps are processed with the aid of an empirical model, based on the relationships between phenology and environment, for obtaining a phenological delay matrix. From this matrix it is possible to derive automatically various kinds of maps (chronological, synoptical and differential). An application is described, relating to the blooming patterns of a set of wild plants in a mountainous area of Northern Italy.