DETERMINATION OF VEGETATION INDEX, LAND SURFACE TEMPERATURE AND PRECIPITATION AMOUNTS USING REMOTE SENSING DATA

2020 ◽  
Vol 5 (2) ◽  
pp. 4-10
Author(s):  
Rashid Jaksibaev ◽  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Temperature And Precipitation

scholarly journals Exploring the Relationship between LST, LULC and NDVI in Saïss Plain using Geospatial Techniques

2021 ◽  
Vol 314 ◽  
pp. 04001
Author(s):  
Manal El Garouani ◽  
Mhamed Amyay ◽  
Abderrahim Lahrach ◽  
Hassane Jarar Oulidi
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Arable Land ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Sensing Data

Land use/land cover (LULC) change has been confirmed that have a significant impact on climate through various pathways that modulate land surface temperature (LST) and precipitation. However, there are no studies illustrated this link in the Saïss plain using remote sensing data. Thus, the aim of this study is to monitor the LST relationship between LULC and vegetation index change in the Saïss plain using GIS and Remote Sensing Data. We used 18 Landsat images to study the annual and interannual variation of LST with LULC (1988, 1999, 2009 and 2019). To highlight the effect of biomass on LST distribution, the Normalized Difference Vegetation Index (NDVI) was calculated, which is a very good indicator of biomass. The mapping results showed an increase in the arboriculture and urbanized areas to detriment of arable lands and rangelands. Based on statistical analyzes, the LST varies during the phases of plant growth in all seasons and that it is diversified due to the positional influence of LULC type. The variation of land surface temperature with NDVI shows a negative correlation. This explains the increase in the surface temperature in rangelands and arable land while it decreases in irrigated crops and arboriculture.

scholarly journals Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Osman Orhan ◽  
Semih Ekercin ◽  
Filiz Dadaser-Celik
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Remote Sensing ◽  
Vegetation Index ◽  
Salt Lake ◽  
Remote Sensing Data ◽  
Lake Basin ◽  
Sensing Data

The main purpose of this paper is to investigate multitemporal land surface temperature (LST) changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI), vegetation condition index (VCI), and temperature vegetation index (TVX) were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable within situmeasurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about2∘C) in the Salt Lake Basin area during the 28-year period (1984–2011). Analysis of air temperature data also showed increases at a rate of 1.5–2∘Cduring the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

scholarly journals Method of drought evaluation for a territory by the land surface temperature and vegetation relationship from remote sensing data

2020 ◽  
Vol 2 (4) ◽  
pp. First
Author(s):  
Van Tran-Thi ◽  
Ha Nguyen Ngan ◽  
Viet Ha Quoc ◽  
Long Nguyen Hoang ◽  
Bao Ha Duong Xuan
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Current Trend ◽  
Remote Sensing Data ◽  
Food Sources ◽  
Sensing Data ◽  
Vegetation Characteristics

Facing the current trend of climate change, which is difficult to control, human life, as well as food sources, are increasingly seriously threatened by droughts that occur more frequently. Understanding the region's drought will help people avoid risks. The paper presents research on the method of assessing drought situations based on the integration of land surface temperature and vegetation characteristics in the drought index according to the Temperature Vegetation Dryness Index TVDI from remote sensing data. Landsat satellite images were used with image processing methods to test the drought assessment method for the test area of Di Linh district, Lam Dong province. The study period was the dry season in 2018. Reflective bands were used to determine vegetation cover as representative of soil moisture supplying water to crops. Vegetation characteristics are represented by Normalized Differential Vegetation Index NDVI. In contrast, the thermal infrared band is used to calculate the surface temperature. The results showed that the bare land and sparsely populated areas exhibited a higher level of drought than the vegetated areas. The research results demonstrate the ability of remote sensing technology to support the monitoring of drought in a space for a region, in order to help people make the right management decisions in planning.  

Study on the Application and Comparative Analysis of Land Surface Temperature Retrieval Method Based on Multi-Sensor Remote Sensing Data

2014 ◽  
Vol 1010-1012 ◽  
pp. 1276-1279 ◽  
Author(s):  
Yin Tai Na
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Urban Heat ◽  
Split Window Algorithm ◽  
Temperature Retrieval

The three commonly used remote sensing land surface temperature retrieval methods are described, namely single-window algorithm, split window algorithm and multi-channel algorithm, which have their advantages and disadvantages. The land surface temperature (LST) of study area was retrieved with multi-source remote sensing data. LST of study area was retrieved with the split window algorithm on January 10, 2003 and November 19, 2003 which is comparatively analyzed with the LST result of ETM+data with the single-window algorithm and the LST result of ASTER data with multi channel algorithm in the same period. The results show that land surface temperature of different land features are significantly different, where the surface temperature of urban land is the highest, and that of rivers and lakes is the lowest, followed by woodland. It is concluded that the expansion of urban green space and protection of urban water can prevent or diminish the urban heat island.

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