Impacts of Thermal Time on Land Surface Phenology in Urban Areas

Urban areas alter local atmospheric conditions by modifying surface albedo and consequently the surface radiation and energy balances, releasing waste heat from anthropogenic uses, and increasing atmospheric aerosols, all of which combine to increase temperatures in cities, especially overnight, compared with surrounding rural areas, resulting in a phenomenon called the “urban heat island effect. Recent rapid urbanization of the planet has generated calls for remote sensing research related to the impacts of urban areas and urbanization on the natural environment. Spatially extensive, high spatial resolution data products are needed to capture phenological patterns in regions with heterogeneous land cover and external drivers such as cities, which are comprised of a mixture of land cover/land uses and experience microclimatic influences. Here we use the 30 m normalized difference vegetation index (NDVI) product from the Web-Enabled Landsat Data (WELD) project to analyze the impacts of urban areas and their surface heat islands on the seasonal development of the vegetated land surface along an urban–rural gradient for 19 cities located in the Upper Midwest of the United States. We fit NDVI observations from 2003–2012 as a quadratic function of thermal time as accumulated growing degree-days (AGDD) calculated from the Moderate-resolution Imaging Spectroradiometer (MODIS) 1 km land surface temperature product to model decadal land surface phenology metrics at 30 m spatial resolution. In general, duration of growing season (measured in AGDD) in green core areas is equivalent to duration of growing season in urban extent areas, but significantly longer than duration of growing season in areas outside of the urban extent. We found an exponential relationship in the difference of duration of growing season between urban and surrounding rural areas as a function of distance from urban core areas for perennial vegetation, with an average magnitude of 669 AGDD (base 0°C) and the influence of urban areas extending greater than 11 km from urban core areas. At the regional scale, relative change in duration of growing season does not appear to be significantly related to total area of urban extent, population, or latitude. The distance and magnitude that urban areas exert influence on vegetation in and near cities is relatively uniform

Modificaciones del comportamiento fenológico de algunas especies forestales como consecuencia de cambios en el clima de la ciudad de Buenos Aires (Argentina)

Carnelos, Danilo Alejandro. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.Fernández Zapiola, Gonzalo Martín. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.Peretti, Mercedes. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.Fernández Long, María Elena. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.105-118Los fenómenos biológicos presentan en la naturaleza un ritmo estacional de ocurrencia variable que depende de las condiciones meteorológicas o climáticas. La observación fenológica regular de especies vegetales permite detectar esas variaciones. Se evaluó si los cambios en el clima de la Ciudad Autónoma de Buenos Aires en los últimos 60 años afectaron la fecha de comienzo de brotación de un grupo de especies forestales ornamentales.Se determinó la nueva secuencia de brotación y las fechas medias de comienzo, plenitud y fin de la fase. A partir de la información de los boletines fenológicos de la Sección de Fenología de la División de Bioclimatología Agrícola del Departamento de Meteorología Agrícola del Servicio Meteorológico Nacional se seleccionaron 12 especies forestales presentes en el predio de la Facultad de Agronomía de la Universidad de Buenos Aires, de diferentes características con el fin de abarcar un amplio espectro de exigencias bioclimáticas. Se realizaron observaciones fenológicas desde el año 2014 hasta el 2017, las que se compararon con las realizadas entre 1947 y 1956 publicadas en los boletines mencionados. En la mayoría de las plantas se adelantó la fecha de brotación al comparar con los registros históricos, aunque se mantuvieron dentro del rango de variación del período antiguo. En el 2015, en general, las plantas manifestaron un atraso en el comienzo de brotación; mientras que en el 2016 algunas especies adelantaron su fecha de brotación y muchas de ellas, además, redujeron la duración de la fase; y en el 2017, la mayoría de las plantas brotaron alrededor de las fechas medias, aunque muchas requirieron mayor número de días para culminar la fase

Modificaciones del comportamiento fenológico de algunas especies forestales como consecuencia de cambios en el clima de la ciudad de Buenos Aires (Argentina)

Carnelos, Danilo Alejandro. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.Fernández Zapiola, Gonzalo Martín. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.Peretti, Mercedes. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.Fernández Long, María Elena. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Cátedra de Climatología y Fenología Agrícola. Buenos Aires, Argentina.105-118Los fenómenos biológicos presentan en la naturaleza un ritmo estacional de ocurrencia variable que depende de las condiciones meteorológicas o climáticas. La observación fenológica regular de especies vegetales permite detectar esas variaciones. Se evaluó si los cambios en el clima de la Ciudad Autónoma de Buenos Aires en los últimos 60 años afectaron la fecha de comienzo de brotación de un grupo de especies forestales ornamentales.Se determinó la nueva secuencia de brotación y las fechas medias de comienzo, plenitud y fin de la fase. A partir de la información de los boletines fenológicos de la Sección de Fenología de la División de Bioclimatología Agrícola del Departamento de Meteorología Agrícola del Servicio Meteorológico Nacional se seleccionaron 12 especies forestales presentes en el predio de la Facultad de Agronomía de la Universidad de Buenos Aires, de diferentes características con el fin de abarcar un amplio espectro de exigencias bioclimáticas. Se realizaron observaciones fenológicas desde el año 2014 hasta el 2017, las que se compararon con las realizadas entre 1947 y 1956 publicadas en los boletines mencionados. En la mayoría de las plantas se adelantó la fecha de brotación al comparar con los registros históricos, aunque se mantuvieron dentro del rango de variación del período antiguo. En el 2015, en general, las plantas manifestaron un atraso en el comienzo de brotación; mientras que en el 2016 algunas especies adelantaron su fecha de brotación y muchas de ellas, además, redujeron la duración de la fase; y en el 2017, la mayoría de las plantas brotaron alrededor de las fechas medias, aunque muchas requirieron mayor número de días para culminar la fase

Augmenting Land Cover/Land Use Classification by Incorporating Information from Land Surface Phenology: An Application to Quantify Recent Cropland Expansion in South Dakota

Understanding rapid land change in the U.S. NGP region is not only critical for management and conservation of prairie habitats and ecosystem services, but also for projecting production of crops and biofuels and the impacts of land conversion on water quality and rural transportation infrastructure. Hence, it raises the need for an LCLU dataset with good spatiotemporal coverage as well as consistent accuracy through time to enable change analysis. This dissertation aims (1) to develop a novel classification method, which utilizes time series images from comparable sensors, from the perspective of land surface phenology, and (2) to apply the land cover/land use dataset generated from the phenometrically-based classification approach to quantify crop expansion in South Dakota. A novel classification approach from the perspective of land surface phenology (LSP) uses rich time series datasets. First, surface reflectance products at 30 m spatial resolution from Landsat Collection-1, its newer structure—Landsat Analysis Ready Data, and the Harmonized Landsat Sentinel-2 (HLS) data are used to construct vegetation index time series, including the Enhanced Vegetation Index (EVI), and the 2-band EVI (EVI2), and various spectral variables (spectral band and normalized ratio composites). MODIS Level-3 Land Surface Temperature & Emissivity 8-day composite products at 1 km spatial resolution from both the Aqua and Terra satellites are used to compute accumulated growing degree-days (AGDD) time series. The EVI/EVI2 and AGDD time series are then fitted by two different land surface phenology models: the Convex Quadratic model and the Hybrid Piecewise Logistic Model. Suites of phenometrics are derived from the two LSP models and spectral variables and input to Random Forest Classifiers (RFC) to map land cover of sample areas in South Dakota. The results indicate that classifications using only phenometrics can accurately map major crops in the study area but show limited accuracy for non-vegetated land covers. RFC models using the combined spectralphenological variables can achieve higher accuracies than those using either spectral variables or phenometrics alone, especially for the barren/developed class. Among all sampling designs, the “same distribution” models—proportional distribution of the sample is like proportional distribution of the population—tends to yield best land cover prediction. A “same distribution” random sample dataset covering approximately 0.25% or more of the study area appears to achieve an accurate land cover map. To characterize crop expansion in South Dakota, a trajectory-based analysis, which considers the entire land cover dataset generated from the LSP-based classifications, is proposed to improve change detection. An estimated cropland expansion of 5,447 km2 (equivalent to 14% of the existing cropland area) occurred between 2007 and 2015, which matches more closely the reports from the National Agriculture Statistics Service—NASS (5,921 km2) and the National Resources Inventory—NRI (5,034 km2) than an estimation from a bi-temporal change approach (8,018 km2). Cropland gains were mostly concentrated in 10 counties in northern and central South Dakota. An evaluation of land suitability for crops using the Soil Survey Geographic Database—SSURGO indicates a scarcity in high-quality arable land available for cropland expansion

How are Interannual Variations of Land Surface Phenology in the Highland Pastures of Kyrgyzstan Modulated by Terrain, Snow Cover Seasonality, and Climate Oscillations? An Investigation Using Multi-Source Remote Sensing Data

In the semiarid, continental climates of montane Central Asia, with its constant moisture deficit and low relative humidity, agropastoralism constitutes the foundation of the rural economy. In Kyrgyzstan, an impoverished, landlocked republic in Central Asia, herders of the highlands practice vertical transhumance—the annual movement of livestock to higher elevation pastures to take advantage of seasonally available forage resources. Dependency on pasture resource availability during the short mountain growing season makes herds and herders susceptible to changing weather and climate patterns. This dissertation focuses on using remote sensing observations over the highland pastures in Kyrgyzstan to address five interrelated topics: (i) changes in snow cover and its seasonality from 2002 through 2016; (ii) pasture phenology from the perspective of land surface phenology using multi-scale data from 2001 through 2017; (iii) relationships between snow cover seasonality and subsequent land surface phenology; (iv) terrain effects on the snow-phenology interrelations; and (v) the influence of atmospheric teleconnections on modulating the relationships between snow cover seasonality, growing season duration, and pasture phenology. Results indicate that more territory has been experiencing earlier snow onset than earlier snowmelt, and around equivalent areas with longer and shorter duration of snow seasons. Significant shifts toward earlier snow onset (snowmelt) occurred in western and central (eastern) Kyrgyzstan, and significant duration of the snow season shortening (extension) across western and eastern (northern and southwestern) Kyrgyzstan. Below 3400 m, there was a general trend of significantly earlier snowmelt, and this area of earlier snowmelt was 15 times greater in eastern than western rayons. In terms of land surface phenology, there was a predominant and significant trend of increasing peak greenness, and a significant positive relationship between snow covered dates and modeled peak greenness. While there were more negative correlations between snow cover onset and peak greenness, there were more positive correlations between snowmelt timing and peak greenness, meaning that a longer snow cover season increased the amplitude of peak greenness. The amount of thermal time (measured in accumulated growing degree-days) to reach peak greenness was significantly negatively correlated both with the number of snow covered dates and the snowmelt date. Thus, more snow covered dates translated into fewer growing degree-days accumulated to reach peak greenness in the subsequent growing season. Terrain features influenced the timing of snowmelt more strongly than the number of snow covered dates. Slope was more important than aspect, but the strongest effect appeared from the interaction of aspect and the steepest slopes. The influence of atmospheric teleconnection arising from climate oscillation modes was marginal at the spatial resolutions of this study. Thermal time accumulation could be largely explained with Partial Least Squares (PLS) regression models by elevation and snow cover metrics. However, explanation of peak greenness was less susceptible to terrain and snow cover variables. This research study provides a comprehensive evaluation of the spatial variation of interannual phenology in the highland pastures that serve as the foundation of rural Kyrgyz economy. Finally, it contributes to a better understanding of recent environmental changes in remote highland Central Asia

Vegetation Phenology as a Function of Plant Functional Type and Urbanization

Urban land cover contributes to higher temperatures in urban areas compared to adjacent rural areas, which can cause an earlier start of the growing season for urban vegetation. Variations in plant community characteristics between urban and rural areas also produce intra-urban differences in vegetation phenophases, although few studies have investigated differences in phenology between plant functional types in multiple urban environments. In this study I used an exploratory analysis based on the Landsat Phenology Algorithm and weather station data to quantify differences in leaf-onset dates for different plant functional types in the New York City Metropolitan Area. The results demonstrate that Landsat can be used to identify urban-rural variations in leaf-onset for different plant functional types, and that these variations are driven by different climate variables depending on plant functional type. Furthermore, results from such analyses suggest that long-term changes in leaf onset vary across different plant functional types—i.e., grasslands may be advancing at a different rate than forests