Land Surface Temperature and Miombo forest canopy phenophases: what induces leaf fall and leaf flush?

Author(s):  
Henry Zimba ◽  
Miriam Coenders-Gerrits ◽  
Banda Kawawa ◽  
Imasiku Nyambe ◽  
Hubert Savenije ◽  
...  

<p>Miombo woodland is the most widespread tropical seasonal woodland and dry forest formation in Africa covering between 2.7 and 3.6 million km<sup>2</sup> in eleven countries. Leaf fall and leaf flush during the dry season is a major characteristic feature of the various Miombo species. However, the question on what induces the leaf fall process is by far inconclusive. Different studies indicate either moisture or temperature or both elements as inducers for leaf fall. Knowing what induces leaf fall is important for studying the consequence of e.g., climate change on the Miombo forest. To better understand the driver of leaf fall in Miombo forest we employed a simple remote sensing and statistical analysis approach using long term averages (2009 – 2018) of Land Surface Temperature (LST) of the Miombo forest, various vegetation indices (VI), actual evaporation (E<sub>a</sub>), and root zone soil moisture (SM). The vegetation indices (VI) included the Normalised Difference Water Index (NDWI) as indicator of vegetation water content and the Normalised Difference Vegetation Index (NDVI) as indicator of plant photosynthetic activities and leaf cover. Results showed that the NDWI, NDVI, E<sub>a</sub> and SM begun to decline immediately following the end of the rainy season in early April while the LST remained relatively constant before it began to decline in May when leaf fall in some Miombo species begins. Hysteresis graphs revealed that vegetation water content (i.e. NDWI) responded quicker to changes in both LST and SM. Furthermore, high rates of decrease in NDWI and NDVI values were observed between July and September the same period when LST increased. This is also the same period when leaf fall intensifies in Miombo forest. Correlation analysis revealed strong season-dependent LST relationship with VI and SM with the rainy season exhibiting strong negative linear correlations (R<sup>2</sup> = 0.77, 0.91, 0.88; for the NDWI, NDVI and SM respectively). In the dry season relatively weaker negative correlations (R<sup>2</sup> = 0.52, 0.60, 0.55; for NDWI, NDVI and SM respectively) were observed. On the other hand SM showed strong positive linear correlations (R<sup>2</sup> > 0.6) with NDWI and NDVI (for the rainy and dry seasons respectively). The correlations imply that in Miombo forest soil water content (i.e. SM), vegetation water content (i.e. NDWI) and the photosynthetic activities and leaf cover (i.e. NDVI) declines with increase in LST. These relationships show the possibility of land surface temperature being a major inducing element of leaf fall and changes in canopy structure in the Miombo woodland.</p>

2007 ◽  
Vol 20 (22) ◽  
pp. 5593-5606 ◽  
Author(s):  
Seungbum Hong ◽  
Venkat Lakshmi ◽  
Eric E. Small

Abstract Vegetation is an important factor in global climatic variability and plays a key role in the complex interactions between the land surface and the atmosphere. This study focuses on the spatial and temporal variability of vegetation and its relationship with land–atmosphere interactions. The authors have analyzed the vegetation water content (VegWC) from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), the leaf area index (LAI), the normalized difference vegetation index (NDVI), the land surface temperature (Ts), and the Moderate Resolution Imaging Spectroradiometer (MODIS). Three regions, which have climatically differing characteristics, have been selected: the North America Monsoon System (NAMS) region, the Southern Great Plains (SGP) region, and the Little River Watershed in Tifton, Georgia. Temporal analyses were performed by comparing satellite observations from 2003 and 2004. The introduction of the normalized vegetation water content (NVegWC) derived as the ratio of VegWC and LAI corresponding to the amount of water in individual leaves has been estimated and this yields significant correlation with NDVI and Ts. The analysis of the NVegWC–NDVI relationship in the above listed three regions displays a negative exponential relation, and the Ts–NDVI relationship (TvX relationship) is inversely proportional. The correlation between these variables is higher in arid areas such as the NAMS region, and becomes less correlated in the more humid and more vegetated regions such as the area of eastern Georgia. A land-cover map is used to examine the influence of vegetation types on the vegetation biophysical and surface temperature relationships. The regional distribution of vegetation reflects the relationship between the vegetation biological characteristics of water and the growing environment.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9115 ◽  
Author(s):  
Muhammad Amir Siddique ◽  
Liu Dongyun ◽  
Pengli Li ◽  
Umair Rasool ◽  
Tauheed Ullah Khan ◽  
...  

Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990–2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990–2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r =  − 0.155 (p > 0.005), −0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (−12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world.


2021 ◽  
Vol 333 ◽  
pp. 01004
Author(s):  
Dmitriy Emelyanov ◽  
Irina Botvich ◽  
Anatoly Shevyrnogov

The study aims to study changes in land surface temperature (LST) of soil and vegetation on agricultural land planted with barley based on unmanned LST data. Simultaneously with the LST data, the spectral characteristics (NDVI) of crops were measured using the DJI P4 Multispectral. The paper shows the variability of vegetation indices and radiation temperature during the growing season. A significant relationship was found between the dynamics of NDVI and the dynamics of radiation temperature. The features of the variability of the spatial distribution of temperatures depending on precipitation are shown. The paper gives an example of a temperature map of the studied areas in the middle of the growing season, which shows the features of the spatial distribution of temperatures.


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