Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform

Qasimi Abdul Baser; Isazade Vahid; Kaplan Gordana; Nadry Zabihullah

doi:10.2205/2022ES000812

ГРНТИ 37.01 ГРНТИ 37.15 ГРНТИ 37.25 ГРНТИ 37.31 ГРНТИ 38.01

Ещё 5 Свернуть

SPATIOTEMPORAL AND MULTI-SENSOR ANALYSIS OF SURFACE TEMPERATURE, NDVI, AND PRECIPITATION USING GOOGLE EARTH ENGINE CLOUD COMPUTING PLATFORM Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform

АА Аа

Опубликовано в Russian Journal of Earth Sciences · Том 22, Номер 6 · Страницы 1–12 · Рубрика: ОРИГИНАЛЬНЫЕ СТАТЬИ

DOI: https://doi.org/10.2205/2022ES000812

Получено: 18.04.2022 Одобрено: 26.09.2022 Опубликовано: 05.12.2022 Язык публикаций: ENG

Авторы

Qasimi Abdul Baser

ORCID

Isazade Vahid

ORCID

Kaplan Gordana

ORCID

Nadry Zabihullah

Qasimi Abdul Baser

Samangan University Афганистан · Samangan

ORCID

Isazade Vahid

University of Tehran Иран · Tehran

ORCID

Kaplan Gordana

Institute of Earth and Space Sciences, Eskisehir Technical University Турция · Eskisehir

ORCID

Nadry Zabihullah

Samangan University Афганистан · Samangan

АННОТАЦИЯ

Vegetation, precipitation, and surface temperature are three important elements of the environment. By increasing the concerns about climate change and global warming, monitoring vegetation dynamics are considered to be crucial. In this study, the cross-relationship between vegetation, surface temperature, and precipitation, and their fluctuations over the past 21 years are evaluated. Day time LST from Terra sensor of MODIS, nir and red bands of Landsat 7 ETM+ and Landsat 8 OLI, and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) are used in this research. Data were evaluated and processed using the google earth engine cloud processing platform. According to the results, it was concluded that the correlations between the annual average of normalized difference vegetation index and precipitation are not significant. Evaluation of the cross-seasonal correlations exhibited the availability of the strong and significant correlation with a value of r2 = 0.82 between vegetation thickness and precipitation, during the spring and summer, especially from April to August. Moreover, surface temperature exposed an inverse correlation with precipitation and NDVI with the values of r2= 0.776 and r2= 0.68 respectively, these relationships are highly significant. According to the results of this study, vegetation declined sharply in particular years, and this decrease occurred due to insufficient rainfalls.

КЛЮЧЕВЫЕ СЛОВА

Land surface temperature, Landsat, NDVI, Balkh Province

Финансирование

The research does not receive any funding.

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ГОСТ

Qasimi A., Isazade V., Kaplan G., Nadry Z. Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform // Russian Journal of Earth Sciences. 2022. № 6. С. 1-12. DOI: https://doi.org/10.2205/2022ES000812. (дата обращения: 09.10.2026).

MLA

Qasimi Abdul Baser, Isazade V., Kaplan G., Nadry Z.. "Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform." Russian Journal of Earth Sciences 22.6 (2022): 1-12. DOI: https://doi.org/10.2205/2022ES000812.

APA

Qasimi A., Isazade V., Kaplan G., Nadry Z. (2022). Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform. Russian Journal of Earth Sciences, 22(6), 1-12. https://doi.org/10.2205/2022ES000812

Chicago

Qasimi Abdul Baser, Isazade V., Kaplan G., Nadry Z.. "Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform." Russian Journal of Earth Sciences 22, no. 6 (2022): 1-12. https://doi.org/10.2205/2022ES000812.

WIKI

{{cite journal | author = Qasimi A., Isazade V., Kaplan G., Nadry Z. | title = Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform | journal = Russian Journal of Earth Sciences | year = 2022 | volume = 22 | issue = 6 | pages = 1-12 | doi = 10.2205/2022ES000812 }}

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SPATIOTEMPORAL AND MULTI-SENSOR ANALYSIS OF SURFACE TEMPERATURE, NDVI, AND PRECIPITATION USING GOOGLE EARTH ENGINE CLOUD COMPUTING PLATFORM Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform

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