Impact of Vegetation Types on Surface Temperature Change

2008 ◽  
Vol 47 (2) ◽  
pp. 411-424 ◽  
Author(s):  
Young-Kwon Lim ◽  
Ming Cai ◽  
Eugenia Kalnay ◽  
Liming Zhou
Keyword(s):  
Surface Temperature ◽  
Temperature Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Research Unit ◽  
Vegetation Types ◽  
Surface Temperature Change ◽  
The Impact ◽  
Surface Vegetation

Abstract The impact of different surface vegetations on long-term surface temperature change is estimated by subtracting reanalysis trends in monthly surface temperature anomalies from observation trends over the last four decades. This is done using two reanalyses, namely, the 40-yr ECMWF (ERA-40) and NCEP–NCAR I (NNR), and two observation datasets, namely, Climatic Research Unit (CRU) and Global Historical Climate Network (GHCN). The basis of the observation minus reanalysis (OMR) approach is that the NNR reanalysis surface fields, and to a lesser extent the ERA-40, are insensitive to surface processes associated with different vegetation types and their changes because the NNR does not use surface observations over land, whereas ERA-40 only uses surface temperature observations indirectly, in order to initialize soil temperature and moisture. As a result, the OMR trends can provide an estimate of surface effects on the observed temperature trends missing in the reanalyses. The OMR trends obtained from observation minus NNR show a strong and coherent sensitivity to the independently estimated surface vegetation from normalized difference vegetation index (NDVI). The correlation between the OMR trend and the NDVI indicates that the OMR trend decreases with surface vegetation, with a correlation < −0.5, indicating that there is a stronger surface response to global warming in arid regions, whereas the OMR response is reduced in highly vegetated areas. The OMR trend averaged over the desert areas (0 < NDVI < 0.1) shows a much larger increase of temperature (∼0.4°C decade−1) than over tropical forest areas (NDVI > 0.4) where the OMR trend is nearly zero. Areas of intermediate vegetation (0.1 < NDVI < 0.4), which are mostly found over midlatitudes, reveal moderate OMR trends (approximately 0.1°–0.3°C decade−1). The OMR trends are also very sensitive to the seasonal vegetation change. While the OMR trends have little seasonal dependence over deserts and tropical forests, whose vegetation state remains rather constant throughout the year, the OMR trends over the midlatitudes, in particular Europe and North America, exhibit strong seasonal variation in response to the NDVI fluctuations associated with deciduous vegetation. The OMR trend rises up approximately to 0.2°–0.3°C decade−1 in winter and early spring when the vegetation cover is low, and is only 0.1°C decade−1 in summer and early autumn with high vegetation. However, the Asian inlands (Russia, northern China with Tibet, and Mongolia) do not show this strong OMR variation despite their midlatitude location, because of the relatively permanent aridity of these regions.

scholarly journals Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

2021 ◽  
Vol 13 (2) ◽  
pp. 323
Author(s):  
Liang Chen ◽  
Xuelei Wang ◽  
Xiaobin Cai ◽  
Chao Yang ◽  
Xiaorong Lu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Maximum Temperature ◽  
Maximum Temperature Difference ◽  
Rapid Urbanization ◽  
The Impact ◽  
The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

scholarly journals Vegetation Dynamic Changes and Their Response to Ecological Engineering in the Sanjiangyuan Region of China

2020 ◽  
Vol 12 (24) ◽  
pp. 4035
Author(s):  
Xiaohui Zhai ◽  
Xiaolei Liang ◽  
Changzhen Yan ◽  
Xuegang Xing ◽  
Haowei Jia ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Positive Impact ◽  
Ecological Engineering ◽  
Scientific Basis ◽  
Vegetation Dynamic ◽  
Vegetation Growth ◽  
The Impact

In recent decades, the vegetation of the Sanjiangyuan region has undergone a series of changes under the influence of climate change, and ecological restoration projects have been implemented. In this paper, we analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the global inventory modeling and mapping studies (GIMMS) and moderate resolution imaging and spectroradiometer (MODIS) datasets during the past 34 years. Specifically, the characteristics of vegetation changes were analyzed according to the stage of implementation of different ecological engineering programs. The results are as follows. (1) The vegetation in 65.6% of the study area exhibited an upward trend, and in 53.0% of the area, it displayed a large increase, which was mainly distributed in the eastern part of the study area. (2) The vegetation NDVI increased to differing degrees during stages of ecological engineering. (3) The NDVI in the western part of the Sanjiangyuan region is mainly affected by temperature, while in the northeastern part, the NDVI is affected more by precipitation. In the southern part, however, vegetation growth is affected neither by temperature nor by precipitation. On the whole region, vegetation growing is more affected by temperature than by precipitation. (4) The impacts of human activities on vegetation change are both positive and negative. In recent years, ecological engineering projects have had a positive impact on vegetation growth. This study can help us to correctly understand the impact of climate change on vegetation growth, so as to provide a scientific basis for the evaluation of regional ecological engineering effectiveness and the formulation of ecological protection policies.

scholarly journals Spatiotemporal Assessment of Vegetation Indices and Land Cover for Erbil City and Its Surrounding Using Modis Imageries

2017 ◽  
Vol 10 (1-2) ◽  
pp. 31-39 ◽  
Author(s):  
Shwan O. Hussein ◽  
Ferenc Kovács ◽  
Zalán Tobak
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Natural Vegetation ◽  
Visual Interpretation ◽  
Surrounding Areas ◽  
The Impact

Abstract The rate of global urbanization is exponentially increasing and reducing areas of natural vegetation. Remote sensing can determine spatiotemporal changes in vegetation and urban land cover. The aim of this work is to assess spatiotemporal variations of two vegetation indices (VI), the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), in addition land cover in and around Erbil city area between the years 2000 and 2015. MODIS satellite imagery and GIS techniques were used to determine the impact of urbanization on the surrounding quasi-natural vegetation cover. Annual mean vegetation indices were used to determine the presence of a spatiotemporal trend, including a visual interpretation of time-series MODIS VI imagery. Dynamics of vegetation gain or loss were also evaluated through the study of land cover type changes, to determine the impact of increasing urbanization on the surrounding areas of the city. Monthly rainfall, humidity and temperature changes over the 15-year-period were also considered to enhance the understanding of vegetation change dynamics. There was no evidence of correlation between any climate variable compared to the vegetation indices. Based on NDVI and EVI MODIS imagery the spatial distribution of urban areas in Erbil and the bare around it has expanded. Consequently, the vegetation area has been cleared and replaced over the past 15 years by urban growth.

scholarly journals Shading decreases and delays NDVI and flowering of prostrate arctic shrubs

2021 ◽  
Author(s):  
Jeremy May ◽  
Steve Oberbauer ◽  
Steven L. Unger ◽  
Matthew J. Simon ◽  
Katlyn R. Betway ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Surface Temperature ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Moisture Content ◽  
Trophic Levels ◽  
Food Sources ◽  
The Arctic ◽  
The Impact

Increases in shrub growth and canopy cover are well documented community responses to climate warming in the Arctic. An important consequence of larger deciduous shrubs is shading of prostrate plant species, many of which are important sources of nectar and berries. Here we present the impact of a shading experiment on two prostrate shrubs, Vaccinium vitis-idaea and Arctous alpina, in northern Alaska over two growing seasons. We implemented three levels of shading (no shade, 40% shade, and 80% shade) in dry heath and moist acidic tundra. Plots were monitored for soil moisture content, surface temperature, normalized difference vegetation index (NDVI), and flowering. Shading was shown to, on average, lower surface temperature (0.7 to 5.3 ˚C) and increase soil moisture content (0.5 to 5.6%) in both communities. Both species- and plot-level NDVI values were delayed in timing of peak values (7 to 13 days) and decreased at the highest shading. Flower abundance of both species was lower in shaded plots and peak flowering was delayed (3 to 8 days) compared to controls. Changes in timing may result in phenological mismatches and can impact other trophic levels in the Arctic as both the flowers and resulting berries are important food sources for animals.

scholarly journals Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

2018 ◽  
Vol 10 (12) ◽  
pp. 2034 ◽  
Author(s):  
Zengjing Song ◽  
Ruihai Li ◽  
Ruiyang Qiu ◽  
Siyao Liu ◽  
Chao Tan ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Air Pollutant ◽  
The Arctic ◽  
Composition Analysis ◽  
The Impact

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 μg/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72°N and 48°S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature.

scholarly journals Capturing the Impact of the 2018 European Drought and Heat across Different Vegetation Types Using OCO-2 Solar-Induced Fluorescence

2020 ◽  
Vol 12 (19) ◽  
pp. 3249
Author(s):  
Ankit Shekhar ◽  
Jia Chen ◽  
Shrutilipi Bhattacharjee ◽  
Allan Buras ◽  
Antony Oswaldo Castro ◽  
...  
Keyword(s):  
Forest Fires ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coniferous Forest ◽  
Mixed Forest ◽  
Terrestrial Ecosystem ◽  
Added Value ◽  
Summer Drought ◽  
Vegetation Types ◽  
The Impact

The European heatwave of 2018 led to record-breaking temperatures and extremely dry conditions in many parts of the continent, resulting in widespread decrease in agricultural yield, early tree-leaf senescence, and increase in forest fires in Northern Europe. Our study aims to capture the impact of the 2018 European heatwave on the terrestrial ecosystem through the lens of a high-resolution solar-induced fluorescence (SIF) data acquired from the Orbiting Carbon Observatory-2 (OCO-2) satellite. SIF is proposed to be a direct proxy for gross primary productivity (GPP) and thus can be used to draw inferences about changes in photosynthetic activity in vegetation due to extreme events. We explore spatial and temporal SIF variation and anomaly in the spring and summer months across different vegetation types (agriculture, broadleaved forest, coniferous forest, and mixed forest) during the European heatwave of 2018 and compare it to non-drought conditions (most of Southern Europe). About one-third of Europe’s land area experienced a consecutive spring and summer drought in 2018. Comparing 2018 to mean conditions (i.e., those in 2015–2017), we found a change in the intra-spring season SIF dynamics for all vegetation types, with lower SIF during the start of spring, followed by an increase in fluorescence from mid-April. Summer, however, showed a significant decrease in SIF. Our results show that particularly agricultural areas were severely affected by the hotter drought of 2018. Furthermore, the intense heat wave in Central Europe showed about a 31% decrease in SIF values during July and August as compared to the mean over the previous three years. Furthermore, our MODIS (Moderate Resolution Imaging Spectroradiometer) and OCO-2 comparative results indicate that especially for coniferous and mixed forests, OCO-2 SIF has a quicker response and a possible higher sensitivity to drought in comparison to MODIS’s fPAR (fraction of absorbed photosynthetically active radiation) and the Normalized Difference Vegetation Index (NDVI) when considering shorter reference periods, which highlights the added value of remotely sensed solar-induced fluorescence for studying the impact of drought on vegetation.

scholarly journals Seasonal Variation of Surface Temperature Change during the Last Several Decades

2011 ◽  
Vol 24 (15) ◽  
pp. 3817-3821 ◽  
Author(s):  
Syukuro Manabe ◽  
Jeffrey Ploshay ◽  
Ngar-Cheung Lau
Keyword(s):  
Seasonal Variation ◽  
Surface Temperature ◽  
Arctic Ocean ◽  
Temperature Change ◽  
Surface Air Temperature ◽  
Recent Change ◽  
The Arctic ◽  
Climatic Research Unit ◽  
Surface Temperature Change ◽  
The Arctic Ocean

Abstract Using the historical surface temperature dataset compiled by Climatic Research Unit of the University of East Anglia and the Hadley Centre of the United Kingdom, this study examines the seasonal and latitudinal profile of the surface temperature change observed during the last several decades. It reveals that the recent change in zonal-mean surface air temperature is positive at practically all latitudes. In the Northern Hemisphere, the warming increases with increasing latitude and is large in the Arctic Ocean during much of the year except in summer, when it is small. At the Antarctic coast and in the northern part of the circumpolar ocean (near 55°S), where limited data are available, the changes appear to be small during most seasons, though the warming is notable at the coast in winter. However, this warming is much less than the warming over the Arctic Ocean. The seasonal variation of the surface temperature change appears to be broadly consistent with the result from a global warming experiment that was conducted some time ago using a coupled atmosphere–ocean–land model.

scholarly journals Analisis Pengaruh Perubahan Kerapatan Vegetasi Terhadap Suhu Permukaan Karena Kegiatan Pertambangan Menggunakan Citra Satelit Multiwaktu (studi kasus: PT. AMMAN MINERAL NUSA TENGGARA)

2020 ◽  
Vol 3 (1) ◽  
pp. 7
Author(s):  
Bayu Wisnu Putra ◽  
Djurdjani Djurdjani
Keyword(s):  
Surface Temperature ◽  
Satellite Imagery ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mining Area ◽  
Extraction Process ◽  
Index Formula ◽  
Mining Activities ◽  
Vegetation Density ◽  
The Impact

PT.Amman Mineral Nusa Tenggara (PT.AMNT) is an Indonesian mining company that operates the Batu Hijau mine. Mining activities can cause a decrease in vegetation cover and can have an impact on increasing surface temperature. This study aims to determine how the impact of mining activities on vegetation density and surface temperature. The change in vegetation density and surface temperature in the mining area can be detected by processing of remote sensing satellite imagery with different data recording times. The data used are five Landsat satellite imagery in 1998, 2004, 2008, 2014 and 2018. Vegetation index extraction process is carried out using the NDVI (Normalized Difference Vegetation Index) formula. While surface temperature extraction process is carried out using the Mono-window Brightness Temperature method. The results of the extraction process are then used to analyze the effect of vegetation density changes on surface temperature. The results of this study indicate that the vegetation density in the mining area has decreased and the average surface temperature has increased. The results of the correlation analysis showed that the decrease in the level of vegetation density caused the increase in surface temperature in the mining area of  PT.AMNT.

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

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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