scholarly journals Analysis of the Relationship between Land Surface Temperature and Wildfire Severity in a Series of Landsat Images

2014 ◽  
Vol 6 (7) ◽  
pp. 6136-6162 ◽  
Author(s):  
Lidia Vlassova ◽  
Fernando Pérez-Cabello ◽  
Marcos Mimbrero ◽  
Raquel Llovería ◽  
Alberto García-Martín
2021 ◽  
Vol 52 (4) ◽  
pp. 793-801
Author(s):  
Al-Jbouri & Al-Timimi

Agriculture is the most important and most dependent economic activity and influenced by climatic conditions as the climate elements represented by solar radiation, temperature, wind and relative humidity. Therefore, is necessary that analyze and understand the relationship between climate and agriculture. The aim of this study to assessment the relationship between land surface temperature (LST) and normalized difference vegetation index (NDVI) for three regions of Diyala Governorate in Iraq (Al Muqdadya, Baladrooz, and Baquba) by through using of remote sensing techniques and geographic information system (GIS).The Normalized difference vegetation index NDVI and land surface temperature (LST) were used in two of the Landsat-5 ETM + and Landsat-8 OLI satellite imagery during the years 1999 and 2019.  The results showed that increased in NDVI and decreased in LST for 2019, while for 1999 increased in LST and decreased in NDVI for the three regions. Finally, the regression was used to obtain that correlation between LST and NDVI. It was concluded that the correlation coefficient between NDVI and LST is negative, where the strongest correlation was 0.76 for Baquba and weakest correlation was 0.55 for Muqdadyia.


2019 ◽  
Vol 11 (20) ◽  
pp. 5672 ◽  
Author(s):  
Du ◽  
Liu ◽  
Pan ◽  
Yang ◽  
Wang

Fast-growing crops have been evolved in North China, accompanied by intense paddy expansion, leading to dramatic impacts on the agricultural environment. Among these environmental issues, the impact of paddy expansion on land surface temperature is still unclear. In the present study, based on Landsat images and MODIS land surface temperature (LST) products, the crop pattern and monthly LST in the northern Sanjiang Plain are obtained. A 1 km scale grid unit is built to investigate the relationship between LST and paddy expansion. The results obtained from the study are as follows. Firstly, for crop patterns, cropland planting is given priority to paddy fields, accompanied by an aggregated pattern, while upland crops present a discrete pattern. Secondly, for LST changes during the growing season, the maximum LST occurs in June, and the lowest values occur in October across the whole region. In addition, the LST of paddy fields is lower compared with that of upland crops for the whole growing season. Thirdly, at the 1 km grid scale, the relationship between monthly LST and paddy field ratio is significantly negative, and better represented by a cubic function rather than a linear fit. Finally, LST decreases with the increased fraction of the rice paddy area more rapidly when rice paddy is aggregated and accounted for by more than 80% of each study grid. The findings of this study are important to guide agricultural production and to better understand the environmental effects of paddy expansion in cold regions.


2020 ◽  
Vol 12 (24) ◽  
pp. 4067
Author(s):  
Thanhtung Dang ◽  
Peng Yue ◽  
Felix Bachofer ◽  
Michael Wang ◽  
Mingda Zhang

Global warming-induced climate change evolved to be one of the most important research topics in Earth System Sciences, where remote sensing-based methods have shown great potential for detecting spatial temperature changes. This study utilized a time series of Landsat images to investigate the Land Surface Temperature (LST) of dry seasons between 1989 and 2019 in the Bac Binh district, Binh Thuan province, Vietnam. Our study aims to monitor LST change, and its relationship to land-cover change during the last 30 years. The results for the study area show that the share of Green Vegetation coverage has decreased rapidly for the dry season in recent years. The area covered by vegetation shrank between 1989 and 2019 by 29.44%. Our findings show that the LST increase and decrease trend is clearly related to the change of the main land-cover classes, namely Bare Land and Green Vegetation. For the same period, we find an average increase of absolute mean LST of 0.03 °C per year for over thirty years across all land-cover classes. For the dry season in 2005, the LST was extraordinarily high and the area with a LST exceeding 40 °C covered 64.10% of the total area. We expect that methodological approach and the findings can be applied to study change in LST, land-cover, and can contribute to climate change monitoring and forecasting of impacts in comparable regions.


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