Generally, either diagnostic or prognostic parameterizations of vegetation phenology are employed in these studies. Understanding crop phenology is fundamental to agricultural production, management, planning and decisionmaking. Qgis and r are covered by this textbook aimed at a practitioners who want to know how to obtain, process and analyse remotely sensed data. Remote sensing for phenology applications of landsat data paved the way for remote sensingbased phenology and these data are still used for some applications. Remote sensing for phenology usa national phenology network. The phenology viewer provides a dynamic online map interface that can be used to view usgs remote sensing phenology and other datasets. Li s h, xiao j t, ni p, zhang j, wang h s, wang j x. Intercomparison, interpretation, and assessment of spring phenology in north america estimated from remote sensing for 1982 to 2006. Remote sensing phenology is able to consistently generate estimates of the start, peak, duration, and end of the growing season over large areas. Phenological events are sensitive to climate variation.
Remote sensingbased quantification of spatial variation. Department of geological sciences, brown university, providence, rhode island, usa. They compared these field observations to satellite vegetation data to obtain a broader and more accurate interpretation of these startofseason signals. In fact, timeseries datasets of spectral indices obtained by satellite remote sensing have demonstrated its usefulness in detecting the. In the eagle master program at the department of remote sensing, the students get to know a wide range of topics and applications of earth observation. Regionalscale phenology modeling based on meteorological. Introduction remote sensing is an effective approach for tracking phenological changes such as leaf greenup and autumn coloring from the regional to the global scale 1. Phenology is the study of periodic lifecycle events for example, flowering, insect emergence, nesting, migration and how these stages are affected by climate and environment. Historical remote sensing phenology rsp image data and graphics for the conterminous u.
The use of remotely sensed vegetation indices to measure crop growth through phenological metrics has a high potential for use in agricultural management. Studies of vegetation phenology are of great significance to understand the. Satellite remote sensing and gis were once the preserves of a small number of wellfinanced groups, but the field has been democratised by opensource software. Tracking vegetation phenology across diverse biomes using. Short communication monitoring vegetation phenology using modis xiaoyang zhanga, mark a. Reedb, alfredo huetec adepartment of geography and center for remote sensing, boston university, 675 commonwealth avenue, boston, ma 02215, usa beros data center, sioux falls, sd 57198, usa. Our results suggest among the three budburst model, the simplest modelthe spring warming modelis the best. Remote sensing phenology uses satellites to track seasonal changes in vegetation on regional, continental, and global scales. Seasonal vegetation dynamics significantly impact the carbon cycle and weather surface energy balance, transpiration vapor fluxes. The products provide valuable spatiotemporal information for environmental variables such as leaf area index, canopy height, npp, phenology, and so on. Remote sensing of plant phenology depends on interactions between vegetation, regional climate, soil, and microclimate, and all of these factors can vary across a study area. So researchers must be able to distinguish smallerscale variability from largerscale changes.
However, current research using satellite sensors with a more frequent repeat cycle currently dominate the field. The timesat software package provides tools that allow modeling of seasonality patterns of vegetation and the investigation of the relationship between satellite derived parameters and. Canada centre for remote sensing ess challenges in. Remote sensingbased quantification of spatial variation in canopy phenology of four dominant tree species in europe qifei han, a,b geping luo, a and chaofan li a,b axinjiang institute of ecology and geography, chinese academy of sciences, state key laboratory of desert and oasis ecology, urumqi, xinjiang 830011, china.
Global monitoring of daily and seasonal changes in canopy structure and water status. Within the course from field measurements to geoinformation, the students learn how to collect field. Phytoplankton biomass is important to monitor in lakes due to its influence on water quality and lake productivity. In the continental united states, key phenological stages are strongly influenced by meteorological and climatological conditions. Remote sensing phenologythe use of satellites to track phenological eventscomplements ground observation networks. Land surface phenology and remote sensing lsprs usa. Analysis of crop phenology using timeseries modis data. Satellites provide a unique perspective of the planet and allow for regular, even daily, monitoring of the entire global land surface.
Us phenology network nasa usgs noaa tier 1 tier 2 tier 3 tier 4 george r. Remote sensing provides a way to monitor several key phenological phases including leaf expansion and leaf coloring at the landscape scale e. Vegetation phenology assessment using satellite radar remote sensing. Monitoring paddy rice phenology using time series modis. Phenology describes how organisms are specifically adapted to the environmental cycles that surround them and it applies to. We used rasterio to open big images in smallsized chuncks and therefore keep the memory usage low.
A first calibration phase consisted of evaluating the three curvefitting models implemented in the timesat software i. Gis and remote sensing software software type any crowdsourcingvgi databaselibrary desktop gis desktop image processing remote sensing software raster data extension toolconverter web gis display only web processing cloud computing. In fact, timeseries datasets of spectral indices obtained by satellite remote sensing have demonstrated its usefulness in detecting the earlier shift in. The maximum reflectance values for 35, 66, 76, and 96 days which indicate vegetative. Postdoctoral research fellow remote sensing, phenology. Monitoring the long term vegetation phenology change in. Satellite remote sensing of phytoplankton phenology in. Because the most frequently used satellite sensors. Landsat and advanced very high resolution radiometer. Diagnostic phenology 5 satellite remote sensing vegetation indices exploiting. The remote sensing rs component of the usa national phenology network is critical for providing a means of scaling from ontheground observations of phenology to the ecosystem level and, ultimately, to walltowall estimates of phenology covering the entire country. Postdoctoral research fellow remote sensing, phenology, and data assimilation the george mason university department of civil, environmental, and infrastructure engineeringwithin the volgenau school of engineeringseeks a highly motivated postdoctoral research fellow to conduct research in the fields of remote sensing, phenology, and data assimilation. In this work, we compare the predictive power of remote sensing versus temperature.
The elements of phenology that can be estimated from. Phenology is the study of periodic lifecycle events for example, flower. Remote sensing of phenology usually works at the regional and global scales, which imposes considerable variations in the solar zenith angle sza across space and time. Conus 1 km avhrr rsp data, c5 eastern conus 250 m emodis rsp data, c6 eastern conus 250 m emodis rsp data, c5 western conus 250 m emodis rsp data. Seeing climate through the lives of plants earthdata. Scaling up spring phenology derived from remote sensing. However, the process from remote sensing data acquisition to relating vegetation index information to onground crop development and management is complex to even the most experienced user. Alpine grassland phenology as seen in avhrr, vegetation. Remote sensing of landsurface phenology is an important method for studying the patterns of plant and animal growth cycles.
Since remote monitoring is something new to phenology studies, there is a need to develop and improve methods for detecting changes in phenological series and. Short communication monitoring vegetation phenology using. Predictive power of remote sensing versus temperature. The ecosystem center, marine biological laboratory, woods hole, massachusetts, usa. Over the last decade, a complementary approach has been developed to monitor vegetation phenology. Scaling up observations of spring phenology from plotlevel or finer resolution to coarser resolution is important for the. Remote sensing has great potential for sampling leaf phenology across tropical landscapes but until now has been impeded by lack of groundtruthing, cloudiness, poor spatial resolution, and the cryptic nature of incremental leaf turnover in many tropical plants. Crop phenology study based on multispectral remote sensing. Challenges in monitoring arctic plant growth and canada centre for remote sensing ess phenology using longterm remote sensing datasets wenjun chen1, donald mclennan2, jean poitevin3, paul zorn3, jan z. The study identifies various growing stages of rice crop using multispectral data through red edge analysis.
Comparative studies of satellite and ground based phenology were performed in order to assess the interrelationship of both approaches e. The advantages of utilizing remote sensing for phenology applications are the ability to capture the continuous expression of phenology patterns across the landscape and the ability to retrospectively observe phenology from archived satellite data sets e. Vegetation phenology is an important indicator for monitoring changes in the climate and natural environment 1,2,3. Conus 1 km avhrr rsp data, eastern conus 250 m emodis rsp data, and western conus 250 m emodis rsp data. Home data remote sensing algorithms range of satellite data based products are available globally andor regionally. An integrated phenology modelling framework in r hufkens. Adamczewski4, bruno croft4, lori white1, and sylvain leblanc1 1canada centre for remote sensing 2canadian high arctic research station 3parks canada agency. Box 140, helsinki, fi00251, finland 2european commission joint research centre. Application of remote sensing datasets in modelling phenology of heterotrophic animals has received little attention. Gis and remote sensing software unspider knowledge portal. Time series analysis in remote sensing department of.
Remote sensing is an effective approach for tracking phenological changes such as leaf greenup and autumn coloring from the regional to the global scale. Applicability of greenred vegetation index for remote. Remote sensing of spring phenology in northeastern forests. Monitoring vegetation phenology using modis sciencedirect. We present the cropphenology package, which is designed to extract crop phenology metrics from a time series of vegetation index data which build upon those available from previous software and include new metrics suggested by the agricultural remote sensing literature. Request pdf remote sensing phenology remote sensing phenology is able to consistently generate estimates of the start, peak, duration, and end of the growing.
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