Application of Normalized Difference Vegetation Index (NDVI) for the Detection of Extreme Precipitation Change

Remote sensing has frequently been employed to monitor extreme climatic events, especially droughts, by identifying the anomalies of vegetation activity from the regional to global scale. However, limited research has addressed the performance of remote sensing on detecting extreme precipitation events. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper examines the application of the satellite-derived normalized difference vegetation index (NDVI) for detecting the change of extreme precipitation events from 1982 to 2012. The performances of three NDVI-based indices, including minimum, mean, and maximum NDVIs, were examined to capture the sensibility of vegetation activity to changes in extreme precipitation events. The results show not only common enhanced trends, but also obvious spatial discrepancies between the intensity and frequency of extreme precipitation events in the MLR-YR. As to its application on terrestrial vegetation, changes in extreme precipitation intensity coincided with that of the vegetation activity, which was represented as the maximum and the minimum NDVIs, especially the maximum NDVI. In addition, similar patterns were found between the standard deviation of the maximum NDVI and the trend of extreme precipitation intensity. Furthermore, the correlation coefficients were relatively greater between the maximum NDVI and extreme precipitation intensity than that of the minimum NDVI. Our results support the hypothesis that maximum NDVI is more suited to capture the response of vegetation activity to extreme precipitation events in the MLR-YR region, in comparison to the other two NDVI indices.

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Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – Results from UAS based high resolution remote sensing

10.5194/bg-2021-26 ◽

2021 ◽

Author(s):

Marc Wehrhan ◽

Daniel Puppe ◽

Danuta Kaczorek ◽

Michael Sommer

Keyword(s):

Remote Sensing ◽

Soil Properties ◽

Spatial Patterns ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Plant Biomass ◽

Terrestrial Ecosystems ◽

Global Scale ◽

Promising Tool ◽

Technical Features

Abstract. Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most of these studies were performed at relatively small plots with an intended low heterogeneity in soils and plant canopy composition, and results were extrapolated to larger spatial units up to global scale implicitly assuming similar environmental conditions. However, the emergence of new technical features and increasing knowledge on details in Si cycling leads to a more complex picture at landscape or catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation, but its biomass distribution and related Si stocks. Maximum Likelihood (ML) classification was applied to multispectral imagery captured by an Unmanned Aerial System (UAS) aiming the identification of land cover classes (LCC). Subsequently, the Normalized Difference Vegetation Index (NDVI) and ground-based measurements of biomass were used to quantify aboveground Si stocks in two Si accumulating plants (Calamagrostis epigejos and Phragmites australis) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of C. epigejos and P. australis to be surprisingly high (maxima of Si stocks reach values up to 98 g Si m−2), i.e., comparable to or markedly exceeding reported values for the Si storage in aboveground vegetation of various terrestrial ecosystems. We further found spatial patterns of plant aboveground Si stocks to reflect spatial heterogeneities in soil properties. From our results we concluded that (i) aboveground biomass of plants seems to be the main factor of corresponding phytogenic Si stock quantities and (ii) a detection of biomass heterogeneities via UAS-based remote sensing represents a promising tool for the quantification of lifelike phytogenic Si pools at landscape scales.

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Remote Sensing

Environmental Science ◽

10.1093/obo/9780199363445-0018 ◽

2015 ◽

Author(s):

Frank D. Eckardt

Keyword(s):

Remote Sensing ◽

Real Time ◽

Vegetation Index ◽

Forest Cover ◽

Normalized Difference Vegetation Index ◽

Laser Pulses ◽

Global Scale ◽

Dynamic Topography ◽

Forest Cover Change ◽

Atmospheric Remote Sensing

This article on remote sensing or earth observation focuses on mapping and monitoring systems that produce global-scale data sets which are easily accessible to the wider public. It makes particular reference to low-earth-orbiting remote sensing platforms and sensors and associated image archives such as provided by the Landsat and Moderate-Resolution Imaging Spectroradiometer (MODIS) programs. It also draws attention to handheld space photography, synthetic aperture radar (SAR), and the high-spatial-resolution capability obtained from the commercial remote sensing sector. This entry examines applications that are of global interest and are facilitated through image and data portals. Particular emphasis is placed on products such as the normalized difference vegetation index, real-time fire mapping, forest cover change, geomorphology, and global elevation data as well as actual true- and false-color imagery. All of these can be readily imported as shape or raster files into a Geographic Information System (GIS). Key papers dealing with the global monitoring of the biosphere, dynamic topography, and gravity are being cited. Special emphasis is placed on current capabilities in monitoring recent and ongoing changes in the tropics as well as Arctic and Antarctic environment. Numerous remote sensing systems capture the state and dynamics of rainforests, ice caps, glaciers, and shelf and sea ice, some of which are available in near-real-time trend analysis. Not all sensors produce images; some measure passive microwaves, send laser pulses, or detect small fluctuations in gravitational attraction. Nevertheless, all instruments measure changes in earth’s surface state, indicative of seasonal cycles and long-term trends as well as human impact. This article also makes reference to historic developments, social benefits, and ethical considerations in remote sensing as well as the modern role of aerial photography and airborne platforms. Most people will never get to see a satellite or its instruments, they might not even get to see the available data or imagery, but these systems are directly informing the masses or indirectly shaping the perception of a changing and dynamic world. Future revisions to this article will consider oceanographic and atmospheric remote sensing capabilities.

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Assessing the Impacts of Extreme Precipitation Change on Vegetation Activity

Agriculture ◽

10.3390/agriculture11060487 ◽

2021 ◽

Vol 11 (6) ◽

pp. 487

Author(s):

Fengsong Pei ◽

Yi Zhou ◽

Yan Xia

Keyword(s):

Return Period ◽

Potential Risk ◽

Extreme Precipitation ◽

Period Analysis ◽

Extreme Climate Events ◽

Extreme Climate ◽

Extreme Precipitation Events ◽

Vegetation Activity ◽

Climate Events ◽

Precipitation Events

Extreme climate events frequently have more severe effects on terrestrial vegetation activity than long-term changes in climate averages. However, changes in extreme climate events as well as their potential risk on vegetation activity are still poorly understood. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper aims to understand the vegetation response to changes in extreme precipitation events from 1982 to 2012 using the maximum normalized difference vegetation index (NDVI) as an indicator. By applying extreme value theory (EVT), the potential risks of extreme precipitation events on vegetation activity were analyzed by conducting return period analysis. Results indicated that vegetation activity could be affected by extreme precipitation events, especially the combined effects of the frequency and intensity of precipitation extremes. For instance, vegetation activity could be enhanced in the regions with weakened intensity but increased occurrence of extreme precipitation events. In addition, we found potential risk of extreme precipitation events on vegetation activity from the results of precipitation extreme trend and return period analysis. These phenomena can be associated with the local occurrence of extreme precipitation events, different land cover types, and soil moisture cumulative effect on vegetation growth. This study stresses the importance of considering both current changes in and the potential risk of extreme precipitation events to understand their effects on vegetation activity.

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Temperature scaling of extreme precipitation events – an application of the new DWD event catalogue

10.5194/ems2021-452 ◽

2021 ◽

Author(s):

Tanja Winterrath ◽

Ewelina Walawender ◽

Katharina Lengfeld ◽

Elmar Weigl ◽

Andreas Becker

Keyword(s):

Extreme Precipitation ◽

Ambient Air ◽

Precipitation Intensity ◽

Convective Precipitation ◽

Precipitation Event ◽

Extreme Precipitation Events ◽

Precipitation Regimes ◽

Temperature Scaling ◽

First Results ◽

Precipitation Events

<p>According to the Clausius-Clapeyron equation on saturation vapour pressure a temperature increase of 1&#160;K allows an atmospheric air mass to hold approximately 7&#160;% more water vapour thus increasing its potential for heavy precipitation. Several published measurement studies on the relation between precipitation intensity and temperature, however, revealed an increase of even up to twofold the CC rate for short-term precipitation events. Model conceptions explain this scaling behaviour with increasing temperature by different intensification pathways of convective processes and/or a transition between stratiform and convective precipitation regimes that both can hardly be verified by point measurements alone. In this presentation, we present first results of the correlation between ambient air temperature and different attributes of the Catalogue of Radar-based Heavy Rainfall Events (CatRaRE) recently published by Deutscher Wetterdienst (DWD). This object-oriented event catalogue files and characterizes extreme precipitation events that have occurred on German territory since 2001. It is based on the high-resolution precipitation climate data set RADKLIM of DWD, i.e. contiguous radar-based reflectivity measurements adjusted to hourly station-based precipitation totals and corrected for typical measurement errors applying specific climatological correction methods. Our analysis gives new insights into potential explanations of the observed temperature scaling relating not only precipitation intensity but characteristic event properties like area, duration, and extremity indices with ambient temperature data. With this approach, extreme precipitation events can be analysed in a comprehensive way that is significant in the context of potential impact. The presented analysis moreover allows testing the hypothesis of regime changing based on objective precipitation event criteria that are typical for different precipitation types. We will briefly present the methodological background of CatRaRE with special focus on the event attributes used in the analysis of Clausius-Clapeyron scaling and give first results on the retrieved temperature dependencies of extreme precipitation events.</p>

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Globally estimated precipitation extremes

10.5194/egusphere-egu2020-6996 ◽

2020 ◽

Author(s):

Gaby Gründemann ◽

Ruud van der Ent ◽

Hylke Beck ◽

Marc Schleiss ◽

Enrico Zorzetto ◽

...

Keyword(s):

Extreme Precipitation ◽

Global Scale ◽

Extreme Value ◽

Precipitation Extremes ◽

The Novel ◽

Extreme Value Distributions ◽

Extreme Precipitation Events ◽

Return Levels ◽

High Return ◽

Precipitation Events

<p>Understanding the magnitude and frequency of extreme precipitation events is a core component of translating climate observations to planning and engineering design. This research aims to capture extreme precipitation return levels at the global scale. A benchmark of the current climate is created using the global Multi-Source Weighted-Ensemble Precipitation (MSWEP-V2, coverage 1979-2017 at 0.1 arc degree resolution) data, by using both classical and novel extreme value distributions. Traditional extreme value distributions, such as the Generalized Extreme Value (GEV) distribution use annual maxima to estimate precipitation extremes, whereas the novel Metastatistical Extreme Value (MEV) distribution also includes the ordinary precipitation events. Due to this inclusion the MEV is less sensitive to local extremes and thus provides a more reliable and smoothened spatial pattern. The global scale application of methods allows analysis of the complete spatial patterns of the extremes. The generated database of precipitation extremes for high return periods is particularly relevant in otherwise data-sparse regions to provide a benchmark for local engineers and planners.</p>

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Global Occurrences of Extreme Precipitation and the Madden–Julian Oscillation: Observations and Predictability

Journal of Climate ◽

10.1175/3238.1 ◽

2004 ◽

Vol 17 (23) ◽

pp. 4575-4589 ◽

Cited By ~ 146

Author(s):

Charles Jones ◽

Duane E. Waliser ◽

K. M. Lau ◽

W. Stern

Keyword(s):

Extreme Precipitation ◽

General Circulation ◽

Circulation Model ◽

Global Scale ◽

Madden Julian Oscillation ◽

Potential Predictability ◽

The North ◽

Extreme Precipitation Events ◽

Realistic Representation ◽

Precipitation Events

Abstract This study investigates 1) the eastward propagation of the Madden–Julian oscillation (MJO) and global occurrences of extreme precipitation, 2) the degree to which a general circulation model with a relatively realistic representation of the MJO simulates its influence on extremes, and 3) a possible modulation of the MJO on potential predictability of extreme precipitation events. The observational analysis shows increased frequency of extremes during active MJO phases in many locations. On a global scale, extreme events during active MJO periods are about 40% higher than in quiescent phases of the oscillation in locations of statistically significant signals. A 10-yr National Aeronautics and Space Administration (NASA) Goddard Laboratory for the Atmospheres (GLA) GCM simulation with fixed climatological SSTs is used to generate a control run and predictability experiments. Overall, the GLA model has a realistic representation of extremes in tropical convective regions associated with the MJO, although some shortcomings also seem to be present. The GLA model shows a robust signal in the frequency of extremes in the North Pacific and on the west coast of North America, which somewhat agrees with observational studies. The analysis of predictability experiments indicates higher success in the prediction of extremes during an active MJO than in quiescent situations. Overall, the predictability experiments indicate the mean number of correct forecasts of extremes during active MJO periods to be nearly twice the correct number of extremes during quiescent phases of the oscillation in locations of statistically significant signals.

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TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

Revista da Casa da Geografia de Sobral (RCGS) ◽

10.35701/rcgs.v21n2.548 ◽

2019 ◽

Vol 21 (2) ◽

pp. 1310-1320

Author(s):

Cícera Celiane Januário da Silva ◽

Vinicius Ferreira Luna ◽

Joyce Ferreira Gomes ◽

Juliana Maria Oliveira Silva

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Temperature Measurement ◽

Rainy Season ◽

Satellite Images ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat 8 ◽

Low Density ◽

Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia. ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

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