Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform
Author:
Baser Qasimi Abdul1, Isazade Vahid2, Kaplan Gordana3, Nadry Zabihullah1
Affiliation:
1. Samangan University 2. University of Tehran 3. Institute of Earth and Space Sciences, Eskisehir Technical University
Abstract
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.
Publisher
Geophysical Center of the Russian Academy of Sciences
Subject
General Earth and Planetary Sciences
Reference40 articles.
1. Alan, S., Groninger, J. W., & Myers, O. (2012). Rebuilding Afghanistan’s Agricultural Economy: Vegetable Production in Balkh Province. 41(1), 7–13. https://doi.org/10.5367/OA.2012.0073, Alan, S., Groninger, J. W., & Myers, O. (2012). Rebuilding Afghanistan’s Agricultural Economy: Vegetable Production in Balkh Province. 41(1), 7–13. https://doi.org/10.5367/OA.2012.0073 2. Campos-Taberner, M., Moreno-Martínez, Á., García-Haro, F. J., Camps-Valls, G., Robinson, N. P., Kattge, J., & Running, S. W. (2018a). Global estimation of biophysical variables from Google Earth Engine platform. Remote Sensing, 10(8). https://doi.org/10.3390/rs10081167, Campos-Taberner, M., Moreno-Martínez, Á., García-Haro, F. J., Camps-Valls, G., Robinson, N. P., Kattge, J., & Running, S. W. (2018a). Global estimation of biophysical variables from Google Earth Engine platform. Remote Sensing, 10(8). https://doi.org/10.3390/rs10081167 3. Campos-Taberner, M., Moreno-Martínez, Á., García-Haro, F. J., Camps-Valls, G., Robinson, N. P., Kattge, J., & Running, S. W. (2018b). Global estimation of biophysical variables from Google Earth Engine platform. Remote Sensing, 10(8). https://doi.org/10.3390/rs10081167, Campos-Taberner, M., Moreno-Martínez, Á., García-Haro, F. J., Camps-Valls, G., Robinson, N. P., Kattge, J., & Running, S. W. (2018b). Global estimation of biophysical variables from Google Earth Engine platform. Remote Sensing, 10(8). https://doi.org/10.3390/rs10081167 4. Ding, M., Zhang, Y., Liu, L., Zhang, W., Wang, Z., & Bai, W. (2007). The relationship between NDVI and precipitation on the Tibetan Plateau. Journal of Geographical Sciences, 17(3), 259–268. https://doi.org/10.1007/s11442-007-0259-7, Ding, M., Zhang, Y., Liu, L., Zhang, W., Wang, Z., & Bai, W. (2007). The relationship between NDVI and precipitation on the Tibetan Plateau. Journal of Geographical Sciences, 17(3), 259–268. https://doi.org/10.1007/s11442-007-0259-7 5. Dinku, T., Funk, C., Peterson, P., Maidment, R., Tadesse, T., Gadain, H., & Ceccato, P. (2018). Validation of the CHIRPS satellite rainfall estimates over eastern Africa. Quarterly Journal of the Royal Meteorological Society, 144, 292–312. https://doi.org/10.1002/qj.3244, Dinku, T., Funk, C., Peterson, P., Maidment, R., Tadesse, T., Gadain, H., & Ceccato, P. (2018). Validation of the CHIRPS satellite rainfall estimates over eastern Africa. Quarterly Journal of the Royal Meteorological Society, 144, 292–312. https://doi.org/10.1002/qj.3244
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