TY - JOUR
T1 - Spatio-temporal Analysis of Land Surface Temperature Changes in Java Island from Aqua and Terra MODIS Satellite Imageries Using Google Earth Engine
AU - Jaelani, L. M.
AU - Handayani, C. A.
N1 - Publisher Copyright:
© Geoinformatics International.
PY - 2022/10
Y1 - 2022/10
N2 - Java Island is the island with the most population globally, which is experiencing an increase in population from year to year. This population growth causes an increase in the use of natural resources, which can further increase the potential for climate change. One of the parameters of climate change in an area is Land Surface Temperature (LST). In situ LST observations in the field require a huge number of stations; for that reason, the use of satellites is the right choice. This study analyzes changes in LST spatially and temporally for 16 years, from January 2005 to December 2020, based on Terra and Aqua MODIS satellite imagery using Google Earth Engine as a data processing tool. LST processing was performed gradually to generate the average daily maximum LST of Terra and Aqua, monthly average LST, and annual average LST. This study found the correlation coefficient between the Terra and Aqua LST data and the BMKG weather station temperature data of 0.2599 to 0.8361. It indicated a moderate to very strong correlation. The most significant annual LST change occurred from 2015 to 2016 experiencing a temperature decrease of 1.6 °C and 2.0 °C, respectively, for Terra and Aqua. There was an area of 35105 km2 (2010-2011) and 65420 km2 (2015-2016) experiencing LST increases and decreases of at least 1.5°C, respectively. Areas experiencing a temperature increase were mainly in the northern part of East Java Province and the eastern part of Central Java Province. Meanwhile, the areas that experienced a temperature drop were mainly northern East Java, eastern Central Java, and West Java Province. Annual LST fluctuations indicate the changes in land used and land cover, both spatial and temporal.
AB - Java Island is the island with the most population globally, which is experiencing an increase in population from year to year. This population growth causes an increase in the use of natural resources, which can further increase the potential for climate change. One of the parameters of climate change in an area is Land Surface Temperature (LST). In situ LST observations in the field require a huge number of stations; for that reason, the use of satellites is the right choice. This study analyzes changes in LST spatially and temporally for 16 years, from January 2005 to December 2020, based on Terra and Aqua MODIS satellite imagery using Google Earth Engine as a data processing tool. LST processing was performed gradually to generate the average daily maximum LST of Terra and Aqua, monthly average LST, and annual average LST. This study found the correlation coefficient between the Terra and Aqua LST data and the BMKG weather station temperature data of 0.2599 to 0.8361. It indicated a moderate to very strong correlation. The most significant annual LST change occurred from 2015 to 2016 experiencing a temperature decrease of 1.6 °C and 2.0 °C, respectively, for Terra and Aqua. There was an area of 35105 km2 (2010-2011) and 65420 km2 (2015-2016) experiencing LST increases and decreases of at least 1.5°C, respectively. Areas experiencing a temperature increase were mainly in the northern part of East Java Province and the eastern part of Central Java Province. Meanwhile, the areas that experienced a temperature drop were mainly northern East Java, eastern Central Java, and West Java Province. Annual LST fluctuations indicate the changes in land used and land cover, both spatial and temporal.
KW - Aqua
KW - Drought
KW - Google Earth Engine
KW - Land Surface Temperature
KW - MODIS
KW - Sustainability
KW - Terra
UR - http://www.scopus.com/inward/record.url?scp=85141444635&partnerID=8YFLogxK
U2 - 10.52939/ijg.v18i5.2365
DO - 10.52939/ijg.v18i5.2365
M3 - Article
AN - SCOPUS:85141444635
SN - 1686-6576
VL - 18
SP - 1
EP - 12
JO - International Journal of Geoinformatics
JF - International Journal of Geoinformatics
IS - 5
ER -