REMOTE SENSING ANALYSIS OF NITROGEN DIOXIDE GHG EMISSIONS SUPPORTS RAP FOR MITIGATING CLIMATE CHANGE IMPACTS IN SITUBONDO REGENCY - Thohiron, Mochamad; Suryaningsih, Dwie Retna; Susilo, Achmadi; Sari, Pipin Yunita; Hassan, Faez M. (Yayasan Education and Social Center, 2026)
The study aims to inventory and analyse GHG Nitrogen Dioxide (NO2) emissions to support regional action plans (RAP in the mitigation and adaptation of PI (climate change) in Situbondo Regency. It is hoped that the research output can be used by regional governments to implement mitigation and adaptation actions. The research area in Situbondo Regency was carried out for five months. The analysis method uses a remote sensing system through exploration of Sentinel- 5P satellite data for GHG NO2 gas numerical spatial data on a cloud-based digital platform, JavaScript Google Earth Engine (GEE) and Google Colaboratory Research (GColab) 2023, image digitization and outlasting in QGIS software. Research data is remote sensing data access to the NO2 gas datasets Sentinel_5P OFFL_ NO2 Offline, MOD 11A1.061_Terra LST, and EDG 1km. Statistical data analysis using SAS v.jmp and Genstat v.18. The results show that the highest NO2 density variable in 2017 was 0,66 – 2,12 g/m2, then decreased to 0,65 – 2,01 g/m2 in 2019 and to 0,63 – 1,94 g/m2 in 2021, with the highest NO2 density in the Banyuglugur sub-district. The highest range of LST variables in 2017 was 19 – 39 0C, then increased to 21 – 40 0C in 2019, and in 2021 decreased again to 18 – 38 0C. Regional variables The highest LST distribution in 2017 and 2019 was relatively the same in each sub-district, namely Situbondo, Panarukan, Panji, Kapongan and Jangkar. NO2 and LST density variables in 2017 and 2019 were lowly correlated (r = 0.55), but in 2021, they were not correlated.