scholarly journals Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

2013 ◽  
Vol 10 (10) ◽  
pp. 6657-6676 ◽  
Author(s):  
N. Andela ◽  
Y. Y. Liu ◽  
A. I. J. M. van Dijk ◽  
R. A. M. de Jeu ◽  
T. R. McVicar
Keyword(s):  
Land Surface ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Fire Regime ◽  
Linear Regression Analysis ◽  
Passive Microwave ◽  
Woody Encroachment ◽  
Woody Vegetation ◽  
Global Changes ◽  
Herbaceous Vegetation

Abstract. Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008) vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI) and the recently developed passive-microwave-based Vegetation Optical Depth (VOD). The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.

scholarly journals Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: combining a new passive microwave vegetation density record with reflective greenness data

2013 ◽  
Vol 10 (5) ◽  
pp. 8749-8797 ◽  
Author(s):  
N. Andela ◽  
Y. Y. Liu ◽  
A. I. J. M. van Dijk ◽  
R. A. M. de Jeu ◽  
T. R. McVicar
Keyword(s):  
Land Surface ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Fire Regime ◽  
Linear Regression Analysis ◽  
Passive Microwave ◽  
Woody Encroachment ◽  
Woody Vegetation ◽  
Global Changes ◽  
Herbaceous Vegetation

Abstract. Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite observed vegetation products were used to study the long-term (1988–2008) vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI) and the recently developed passive-microwave-based Vegetation Optical Depth (VOD). The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily use shallow soil water whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment seems to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information, bringing new insights on vegetation dynamics.

Fire regime impacts on post-fire diurnal land surface temperature change over North American boreal forest

2021 ◽  
Author(s):  
Jie Zhao ◽  
Chao Yue ◽  
Philippe Ciais ◽  
Xin Hou ◽  
Qi Tian
Keyword(s):  
Climate Change ◽  
Regression Analysis ◽  
Land Surface ◽  
Fire Regime ◽  
Fire Severity ◽  
Linear Regression Analysis ◽  
Fire Regimes ◽  
Fire Intensity ◽  
Surface Temperature Change ◽  
One Year

<p>Wildfire is the most prevalent natural disturbance in the North American boreal (BNA) forest and can cause post-fire land surface temperature change (ΔLST<sub>fire</sub>) through biophysical processes. Fire regimes, such as fire severity, fire intensity and percentage of burned area (PBA), might affect ΔLST<sub>fire</sub> through their impacts on post-fire vegetation damage. However, the difference of the influence of different fire regimes on the ΔLST<sub>fire</sub> has not been quantified in previous studies, despite ongoing and projected changes in fire regimes in BNA in association with climate change. Here we employed satellite observations and a space-and-time approach to investigate diurnal ΔLST<sub>fire</sub> one year after fire across BNA. We further examined potential impacts of three fire regimes (i.e., fire intensity, fire severity and PBA) and latitude on ΔLST<sub>fire</sub> by simple linear regression analysis and multiple linear regression analysis in a stepwise manner. Our results demonstrated pronounced asymmetry in diurnal ΔLST<sub>fire</sub>, characterized by daytime warming in contrast to nighttime cooling over most BNA. Such diurnal ΔLST<sub>fire</sub> also exhibits a clear latitudinal pattern, with stronger daytime warming and nighttime cooling one year after fire in lower latitudes, whereas in high latitudes fire effects are almost neutral. Among the fire regimes, fire severity accounted for the most (43.65%) of the variation of daytime ΔLST<sub>fire</sub>, followed by PBA (11.6%) and fire intensity (8.5%). The latitude is an important factor affecting the influence of fire regimes on daytime ΔLST<sub>fire</sub>. The sensitivity of fire intensity and PBA impact on daytime ΔLST<sub>fire</sub> decreases with latitude. But only fire severity had a significant effect on nighttime ΔLST<sub>fire</sub> among three fire regimes. Our results highlight important fire regime impacts on daytime ΔLST<sub>fire</sub>, which might play a critical role in catalyzing future boreal climate change through positive feedbacks between fire regime and post-fire surface warming.</p>

scholarly journals Vegetation dynamics and soil water balance in a water-limited Mediterranean ecosystem on Sardinia, Italy

2008 ◽  
Vol 12 (6) ◽  
pp. 1257-1271 ◽  
Author(s):  
N. Montaldo ◽  
J. D. Albertson ◽  
M. Mancini
Keyword(s):  
Soil Water ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Mediterranean Ecosystems ◽  
Surface Fluxes ◽  
Annual Rainfall ◽  
Woody Vegetation ◽  
Wide Range ◽  
Hydrometeorological Conditions

Abstract. Mediterranean ecosystems are commonly heterogeneous savanna-like ecosystems, with contrasting plant functional types (PFTs, e.g. grass and woody vegetation) competing for water. Mediterranean ecosystems are also commonly characterized by strong inter-annual rainfall variability, which influences the distributions of PFTs that vary spatially and temporally. An extensive field campaign in a Mediterranean setting was performed with the objective to investigate interactions between vegetation dynamics, soil water budget and land-surface fluxes in a water-limited ecosystem. Also a vegetation dynamic model (VDM) is coupled to a 3-component (bare soil, grass and woody vegetation) Land surface model (LSM). The case study is in Orroli, situated in the mid-west of Sardegna within the Flumendosa river basin. The landscape is a mixture of Mediterranean patchy vegetation types: trees, including wild olives and cork oaks, different shrubs and herbaceous species. Land surface fluxes, soil moisture and vegetation growth were monitored during the May 2003–June 2006 period. Interestingly, hydrometeorological conditions of the monitored years strongly differ, with dry and wet years in turn, such that a wide range of hydrometeorological conditions can be analyzed. The coupled VDM-LSM model is successfully tested for the case study, demonstrating high model performance for the wide range of eco-hydrologic conditions. Results demonstrate also that vegetation dynamics are strongly influenced by the inter-annual variability of atmospheric forcing, with grass leaf area index changing significantly each spring season according to seasonal rainfall amount.

scholarly journals The Response of Land Surface Temperature to the Changing Land-Use Land-Cover in a Mountainous Landscape under the Influence of Urbanization: Gilgit City as a case study in the Hindu Kush Himalayan Region of Pakistan

2019 ◽  
Vol 10 (3) ◽  
pp. 40-49
Author(s):  
Aftab Ahmed Khan ◽  
Syed Najam ul Hassan ◽  
Saranjam Baig ◽  
Muhammad Zafar Khan ◽  
Amin Muhammad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Linear Regression Analysis ◽  
Northern Region ◽  
Google Earth ◽  
Landsat Images

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes.

scholarly journals The Response of Land Surface Temperature to the Changing Land-Use Land-Cover in a Mountainous Landscape under the Influence of Urbanization: Gilgit City as a case study in the Hindu Kush Himalayan Region of Pakistan

2019 ◽  
Vol 10 (3) ◽  
pp. 40-49
Author(s):  
Aftab Ahmed Khan ◽  
Syed Najam ul Hassan ◽  
Saranjam Baig ◽  
Muhammad Zafar Khan ◽  
Amin Muhammad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Linear Regression Analysis ◽  
Northern Region ◽  
Google Earth ◽  
Landsat Images

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes.

scholarly journals Vegetation dynamics and soil water balance in a water-limited Mediterranean ecosystem on Sardinia, Italy

2008 ◽  
Vol 5 (1) ◽  
pp. 219-255 ◽  
Author(s):  
N. Montaldo ◽  
J. D. Albertson ◽  
M. Mancini
Keyword(s):  
Soil Water ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Mediterranean Ecosystems ◽  
Surface Fluxes ◽  
Annual Rainfall ◽  
Woody Vegetation ◽  
Wide Range ◽  
Hydrometeorological Conditions

Abstract. Mediterranean ecosystems are commonly heterogeneous savanna-like ecosystems, with contrasting plant functional types (PFTs, e.g., grass and woody vegetation) competing for the water use. Mediterranean ecosystems are also commonly characterized by strong inter-annual rainfall variability, which influences the distributions of PFTs that vary spatially and temporally. With the objective to investigate interactions between vegetation dynamics, soil water budget and land-surface fluxes in a water-limited ecosystem, an extensive field campaign in a Mediterranean setting was performed. Also a vegetation dynamic model (VDM) is coupled to a 3-component (bare soil, grass and woody vegetation) Land surface model (LSM). The case study is in Orroli, situated in the mid-west of Sardegna within the Flumendosa river basin. The landscape is a mixture of Mediterranean patchy vegetation types: trees, including wild olives and cork oaks, different shrubs and herbaceous species. Land surface fluxes, soil moisture and vegetation growth were monitored during the May 2003–June 2006 period. Interestingly, hydrometeorological conditions of the monitored years strongly differ, with dry and wet years in turn, such that a wide range of hydrometeorological conditions can be analyzed. The coupled VDM-LSM model is successfully tested for the case study, demonstrating high model performance for the wide range of eco-hydrologic conditions. The use of the VDM in the LSM is demonstrated to be essential when studying the climate-soil-vegetation interactions of these water-limited ecosystems. Results demonstrate also that vegetation dynamics are strongly influenced by the inter-annual variability of atmospheric forcing, with grass leaf area index changing significantly each spring season according to seasonal rainfall amount.

scholarly journals Mapping Soil Moisture as an Indicator of Wildfire Risk Using Landsat 8 Images in Sri Lanna National Park, Northern Thailand

2016 ◽  
Vol 8 (10) ◽  
pp. 107 ◽  
Author(s):  
Kansuma Burapapol ◽  
Ryota Nagasawa
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Linear Regression Analysis ◽  
Landsat 8 ◽  
Fuel Moisture ◽  
Wildfire Risk ◽  
Dry Conditions ◽  
Scatter Plots

<p>Severely dry climate plays an important role in the occurrence of wildfires in Thailand. Soil water deficits increase dry conditions, resulting in more intense and longer burning wildfires. The temperature vegetation dryness index (TVDI) and the normalized difference drought index (NDDI) were used to estimate soil moisture during the dry season to explore its use for wildfire risk assessment. The results reveal that the normalized difference wet index (NDWI) and land surface temperature (LST) can be used for TVDI calculation. Scatter plots of both NDWI/LST and the normalized difference vegetation index (NDVI)/LST exhibit the triangular shape typical for the theoretical TVDI. However, the NDWI is more significantly correlated to LST than the NDVI. Linear regression analysis, carried out to extract the maximum and minimum LSTs (LST<sub>max</sub>, LST<sub>min</sub>), indicate that LST<sub>max </sub>andLST<sub>min</sub> delineated by the NDWI better fulfill the collinearity requirement than those defined by the NDVI. Accordingly, the NDWI-LST relationship is better suited to calculate the TVDI. This modified index, called TVDI<sub>NDWI-LST</sub>, was applied together with the NDDI to establish a regression model for soil moisture estimates. The soil moisture model fulfills statistical requirements by achieving 76.65% consistency with the actual soil moisture and estimated soil moisture generated by our model. The relationship between soil moisture estimated from our model and leaf fuel moisture indicates that soil moisture can be used as a complementary dataset to assess wildfire risk, because soil moisture and fuel moisture content (FMC) show the same or similar behavior under dry conditions. <strong></strong></p>

scholarly journals PHENOLOGY ANALYSIS OF FOREST VEGETATION TO ENVIRONMENTAL VARIABLES DURING PRE- AND POST-MONSOON SEASONS IN WESTERN HIMALAYAN REGION OF INDIA

2016 ◽  
Vol XLI-B2 ◽  
pp. 15-19
Author(s):  
S. Khare ◽  
H. Latifi ◽  
K. Ghosh
Keyword(s):  
Land Surface ◽  
Environmental Variables ◽  
Large Scale ◽  
Vegetation Index ◽  
Linear Regression Analysis ◽  
Himalayan Region ◽  
Landsat 8 ◽  
Post Monsoon ◽  
Western Himalayan Region ◽  
Landsat 7

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVI<sub>change</sub>) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVI<sub>change</sub> values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p < 0.05) amongst the environmental variables and the NDVI<sub>change</sub> between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous forests could be explained.

scholarly journals PHENOLOGY ANALYSIS OF FOREST VEGETATION TO ENVIRONMENTAL VARIABLES DURING PRE- AND POST-MONSOON SEASONS IN WESTERN HIMALAYAN REGION OF INDIA

2016 ◽  
Vol XLI-B2 ◽  
pp. 15-19 ◽  
Author(s):  
S. Khare ◽  
H. Latifi ◽  
K. Ghosh
Keyword(s):  
Land Surface ◽  
Environmental Variables ◽  
Large Scale ◽  
Vegetation Index ◽  
Linear Regression Analysis ◽  
Himalayan Region ◽  
Landsat 8 ◽  
Post Monsoon ◽  
Western Himalayan Region ◽  
Landsat 7

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVI&lt;sub&gt;change&lt;/sub&gt;) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVI&lt;sub&gt;change&lt;/sub&gt; values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p &lt; 0.05) amongst the environmental variables and the NDVI&lt;sub&gt;change&lt;/sub&gt; between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous forests could be explained.

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