The interrelationship between LST, NDVI, NDBI, and land cover change in a section of Lagos metropolis, Nigeria

Alademomi, Alfred Sunday; Okolie, Chukwuma J.; Daramola, Olagoke E.; Akinnusi, Samuel A.; Adediran, Elias; Olanrewaju, Hamed O.; Alabi, Abiodun; Salami, Tosin Julius; Odumosu, Joseph Olayemi

doi:10.1007/s12518-022-00434-2

Cited by 31 publications

(8 citation statements)

References 36 publications

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“…These results are important in terms of showing that vegetation areas decreased according to NDVI and SAVI calculations, water-covered areas decreased according to mNDWI calculations, and built areas increased according to NDBI calculations. The results of the negative and positive relationships of NDVI and NDBI with LST are in parallel with many studies in the literature (Chen & Zhang, 2017;Ranagalage et al, 2017;Malik et al, 2019;Jamei et al, 2019;Shahfahad et al, 2020;Halder et al, 2021;Yamak et al, 2021;Alademomi et al, 2022;Değerli & Çetin, 2022). The negative relationship between SAVI and LST also supports the study results of Akyürek (2020).…”

supporting

confidence: 88%

“…It is estimated that 66% of the world's population will live in urban areas by 2050 (United Nations, 2014). With the rapidly increasing population around the world, the need for new settlements arises, which causes a rapid land use / land cover (LULC) change (Alademomi et al, 2022). These changes and transformations bring serious environmental consequences.…”

Section: Introductionmentioning

confidence: 99%

“…These changes and transformations bring serious environmental consequences. Some of these problems are the increase in greenhouse gas emissions, the decrease in agricultural lands, the emergence of air and water pollution, the decrease in biological diversity, the deterioration of ecological cycles, regional climate changes, the increase of impermeable surfaces and the increase of urban heat island effects and the transformation of cities into unhealthy areas in terms of thermal comfort (Korkut et al, 2016;Zheng et al, 2021;Alademomi et al, 2022). The main reasons for the formation of the heat island effect in cities are changes in urban landscape composition and patterns.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation Of The Relationship Between Spatial-Temporal Changes Of Land Use/Land Cover (Lulc) And Land Surface Temperature (Lst): A Case Study Of Nilüfer, Bursa

ÜSTÜN TOPAL

2023

Türkiye Peyzaj Araştırmaları Dergisi

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This study was carried out in Nilüfer district of Bursa in order to reveal the extent of urbanization, to monitor the changes in landscape elements such as water, vegetation and agricultural lands, and to examine the effects of this on Land Surface Temperature (LST). For this purpose, images taken by Sentinel-2 satellites in 2017 and 2022 were used. With these images, NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index), mNDWI (Modified Normalized Difference Water Index) and NDBI (Normalized Difference Built-up Index), which are widely used in understanding terrain changes, were calculated. Time series analyzes were made between the relevant years The relationship between the changes in the field and the surface temperature was questioned by calculating the LST value with Landsat 8 OLI_TIRS images, and the relations between the indexes and the LST were evaluated by correlation analysis. The results show that NDVI, SAVI, and mNDWI are on a decreasing trend between 2017-2022, while NDBI is on an increasing trend. In other words, the results showed that the vegetation areas and water-covered surfaces decreased, while the built-up areas increased. It has been observed that the changes in Land Use/Land Cover (LULC) increase the LST in the west and south regions of the district.

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supporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation Of The Relationship Between Spatial-Temporal Changes Of Land Use/Land Cover (Lulc) And Land Surface Temperature (Lst): A Case Study Of Nilüfer, Bursa

ÜSTÜN TOPAL

2023

Türkiye Peyzaj Araştırmaları Dergisi

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“…The decrease in green space over the years has been revealed. In the light of recent studies, it has been revealed that bare soil areas, rocky areas and built-up areas affect LST in an upward direction, while wet areas and green areas have a decreasing effect on the contrary (Alademomi 2022;Alademomi 2020;Kulsum and Moniruzzaman 2022). ; Ghouri et al 2022;Khalis et al 2021).…”

Section: Discussionmentioning

confidence: 99%

Evaluation from Rural to Urban Scale for the Effect of NDVI-NDBI Indices on Land Surface Temperature, in Samsun, Türkiye

Degerli

Çetin

2022

Turkish JAF Sci.Tech.

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In this study, in order to evaluate the change of LST from rural to urban scale in 20 years, a zoonal statistical analysis was performed by separating the urban and rural districts located on the coastline. Algorithms were applied to the raw data of Landsat 8 and Landsat 7 satellite images, using the Arc Gis 10.2 and Q Gis 3.16 utilities. In this way, NDVI, NDBI and LST data were compared and evaluated in terms of rural and urban districts. The correlation coefficient between the parameters was calculated. In the study, the land change between the years 2000-2020 was also determined to reveal the land change. As a result of the analyzes made, the amount of green areas decreased by 14.1% between 2000 and 2020 in the study area, which includes the central districts of Samsun, İlkadım and Atakum, and in the rural areas, Bafra and Ondokuz Mayıs. It has been observed that this rate is shared as 7.1% in built up areas and 7.33% in bare soil areas. Considering the effect of the decrease in green areas on the LST value, in 2000, max. While LST is 41.75 C, in 2020 max. It is seen that LST has increased to 43.44 C. When the districts were analyzed separately, it was seen that LST established a strong correlation with NDBI (positive) and NDVI (negative) for all four districts. However, the correlation was stronger in rural districts. It was observed that the correlation strength weakened in urban districts due to heterogeneous land surface cover.

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“…Previous study conducted by Alademomi, Okolie, Daramola, Akinnusi, Adediran, Olanrewaju, Alabi, Salami and Odumosu [10] has tested the relationship among spectral indices such as vegetation index (NDVI), built up index (NDBI), and LST. The results of those studies indicate that NDVI is inversely proportional to LST, while NDBI is directly proportional to LST.…”

Section: Introductionmentioning

confidence: 99%

Assessing Performance of Modified Spectral Indices as Land Surface Temperature Indicators in Tropical Urban Areas

Hadibasyir

Firdaus

Fikriyah

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Spectral indices derived from remote sensing data such as NDVI, SAVI, NDBI, NDWI, and MNDWI were modified using various mathematical operations to enhance the overall accuracy of the automated mapping built-up (BU) areas. Although some of the modified spectral indices succeed in improving the accuracy of mapping BU areas, their performance as land surface temperature (LST) indicators needs to be investigated. Hence, this paper aims 1) to assess the performance of various spectral indices as LST indicators and 2) to investigate the relationship between performance of spectral indices as LST indicators and their accuracy for mapping BU areas. Research locations were located in Yogyakarta and Surakarta City, Indonesia. Spectral indices and LST were derived from Landsat 8. Results showed that NDBI, NDBI*MNDWI, NDVI*NDBI, and NDBI*SAVI were good LST indicators both in Yogyakarta and Surakarta proven by moderate to strong coefficient of Pearson correlation. The relationship between the performance of various spectral indices as LST indicators and their accuracy for mapping BU areas showed strong positive Spearman correlation by 0.69 and 0.73 for Yogyakarta and Surakarta, respectively. In other words, spectral indices, for both original and modified indices, with good accuracy for automated mapping BU areas tended to be good LST indicators.

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The interrelationship between LST, NDVI, NDBI, and land cover change in a section of Lagos metropolis, Nigeria

Cited by 31 publications

References 36 publications

Evaluation Of The Relationship Between Spatial-Temporal Changes Of Land Use/Land Cover (Lulc) And Land Surface Temperature (Lst): A Case Study Of Nilüfer, Bursa

Evaluation Of The Relationship Between Spatial-Temporal Changes Of Land Use/Land Cover (Lulc) And Land Surface Temperature (Lst): A Case Study Of Nilüfer, Bursa

Evaluation from Rural to Urban Scale for the Effect of NDVI-NDBI Indices on Land Surface Temperature, in Samsun, Türkiye

Assessing Performance of Modified Spectral Indices as Land Surface Temperature Indicators in Tropical Urban Areas

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