DOI: https://doi.org/10.14710/geoplanning.7.1.37-46

Utilization of MODIS Surface Reflectance to Generate Air Temperature Information in East Java - Indonesia

*Arif Faisol  -  Papua University, Indonesia
Indarto Indarto orcid  -  Universitas Jember, Indonesia
Elida Novita  -  Universitas Jember, Indonesia
Budiyono Budiyono  -  Universitas Papua, Indonesia

Citation Format:
Abstract

Ambient air temperature is main variable in climatological and hydrological analysis, however limited number of meteorological stations in Indonesia was becoming a problem to provide air temperature data for large areas.  The objective of this study is to generate air temparature using relationship of land surface temperature and vegetation index. A total of 6 climatological station and 84 MODIS Images for three years (2015 to 2017) were used for the analysis.  Research methods include: image georeferencing, band extraction from modis, derivation of NDVI, gererating ambient air temperature, calibrating using local meteorological station, and image interpretation. Results show that the accuracy of MODIS Surface Reflectance product to generate ambient air temperature in East Java at any periods is 86,37%. So MODIS Surface Reflectance product can be used as alternative solution to generate ambient air temperature.

Fulltext View|Download
Keywords: MODIS, air temperature, vegetation index
Funding: RISTEKDIKTI – Ministry of Research, Technology and Higher Education of The Republic of Indonesia

Article Metrics:

Article Info
Section: Original Research
Language : EN
Recent articles
Flood Hazard Mapping in Residential Area Using Hydrodynamic Model HEC-RAS 5.0 TimeFun-InSAR Algorithm to Investigate Physical Changes at Bromo Volcano by Using ALOS/PALSAR Data Sets Mapping of Waste Management Planning Based on Society and Geographic Conditions More recent articles
Most cited articles
POTENTIAL OF BIG DATA FOR PRO-ACTIVE PARTICIPATORY LAND USE PLANNING Evaluation of MODIS-Derived LST Products with Air Temperature Measurements in Cyprus ACCURACY ASSESSMENT OF HEIGHTS OBTAINED FROM TOTAL STATION AND LEVEL INSTRUMENT USING TOTAL LEAST SQUARES AND ORDINARY LEAST SQUARES METHODS LAND USE CHANGE IN SUBURBAN AREA: A CASE OF MALANG CITY, EAST JAVA PROVINCE A SPATIAL ANALYSIS FOR ASSESSING THE SUITABILITY OF ELEMENTARY SCHOOL AS SOCIAL INFRASTRUCTURE AT THE NEIGHBOURHOOD UNIT SCALE IN SUPPORTING CHILD-FRIENDLY SURAKARTA More cited articles
  1. Allen, R.G., Pereira. L.S., Raes, D., Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO, Rome, Italy
  2. Bachour, R. (2013). Evapotranspiration Modelling and Forecasting for Efficient Management of Irrigation Command Areas. Dissertation. Department of Civil and Environmental Engineering, Utah State University
  3. Bastiaanssen,W., Ralf, W., Richard, A., Masahiro, T., Ricardo, T. (2002). SEBAL: Surface Energy Balance Algorithms for Land, version 1.0. The Idaho Department of Water Resource – University of Idaho, Kimberly, USA
  4. Faisol, A. (2015). An Application of Remote Sensing to Analysis Crop Water Requirement. Thesis, Department of Agriculture Engineering, Gadjah Mada University
  5. Faisol, A. (2016). An Application of Moderate Resolution Imaging Spektroradiometer to Optimize Water Allocation in Irrigation Area. In Proceedings of AESAP, 136-139. Bogor, Indonesia: The 1st International Conference on the Role of Agricultural Engineering for Sustainable Agriculture Production
  6. Faisol, A., Atekan, Rizatus, S., Budiyono. (2017). An Utilization of Multispectral Satellite Remote Sensing to Generate Evapotranspiration Information to Support Precision Farming in Manokwari. In Proceedings of Indonesian Agency for Agricultural Research and Development – Ministry of Agriculture. Manokwari, Indonesia : National Conference on Realizing of Food Sovereignty by Innovation of Specific Location Technology
  7. Flores, F., & Lillo, M. (2010). Simple Air Temperature Estimation Method from MODIS Satellite Images on a Regional Scale. Chilean Journal of Agricultural Research, 70 (3), 436 – 445
  8. Hong, S. (2008). Mapping Regional Distribution of Energy Balance Components using Optical Remotely Sensed Imagery. PhD Dissertation, New Mexico Institute of Minning and Technology
  9. Huntington, J.L., & Allen, R.G. (2010). Evapotranspiration and Net Irrigation Water Requirement for Nevada. Division of Water Resource – Departement of Conservation and Natural Resource – State of Nevada
  10. Indonesian Geospatial Information Agency (BIG). (March 10th 2018). http://tanahair.indonesia.go.id/portal-web
  11. Laosuwan, T., Gomasathit, T., Rotjanakusol, T. (2017). Application of Remote Sensing for Temperature Monitoring: The Technique for Land Surface Temperature Analsis. Journal of Ecological Engineering, 18 (3), 53-60, doi: 10.12911/22998993/69358
  12. Muñoz, J.C.J., & Sobrino, J.A. (2010). A Single-Channel Algorithm for Land-Surface Temperature Retrieval from ASTER Data. IEEE Geoscience and Remote Sensing Letter, 7 (1), 176 – 179, doi: 10.1109/LGRS.2009.2029534
  13. National Aeronautic and Space Administration Administration. (March 9th 2018). https://lpdaac.usgs.gov/
  14. National Aeronautic and Space Administration Administration. (March 30th 2018). https://modis.gsfc.nasa.gov/data/dataprod/dataproducts.php?MOD_NUMBER=09
  15. Noi, P.T., Kappas, M., Degener, J. (2016). Estimating Daily Maximum and Minimum Land Air Surface Temperature Using MODIS Land Surface Temperature Data and Ground Truth Data in Northern Vietnam. Remote Sensing, 8, 1002 – 10025, doi: 10.3390/rs8121002
  16. Paparrizos, S., Maris, F., Matzarakis, A. (2014). Estimation and Comparison of Potential Evapotranspiration Based on Daily and Monthly Data from Sperchios Valley in Central Greece. Global NEST, 16(2), 204-217
  17. Savtchenko, A., Ouzounov, D., Ahmad, S., Acker, J., Leptoukh, G., Koziana, J., Nickless, D. (2004). Terra and Aqua MODIS Product Available from NASA GES DAAC. Advances in Space Research, 34 (4), 710-714, doi: 10.1016/j.asr.2004.03.012
  18. Shen, S., & Leptoukh, G.G. (2011). Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature. Environmental Research Letters, 6, 45206-45213, doi: 10.1088/1748-9236/6/4/045206
  19. Shuttle Radar Topography Mission. (March 5th 2018). https://earthexplorer.usgs.gov/
  20. The Meteorology, Climatology and Geophysics Agency (BMKG). (March 5th 2018). http://www.bmkg.go.id/
  21. U.S. Geological Survey. (2016). Landsat 8 (L8) Data Users Handbook version 2.0. Earth Resources Observation and Sciences, Greenbelt, Maryland
  22. Vermote, E.F., & Vermeulen, A. (1999). Atmospheric Correction Algorithm: Spectral Reflectance (MOD09), version 4.0. University of Maryland, College Park, USA
  23. Vermote, E.F., Kotchenova, S.Y., Ray, J.P. (2015). MODIS Surface Reflectance User’s Guide, version 1.4. NASA, Greenbelt, USA
  24. Yonghui, Y., & Baiping, Z. (2012). MODIS-based Air Temperature Estimating in The Southeastern Tibetan Plateau and Neighboring Areas. Journal of Geographical Sciences, 22 (1), 152-166, doi: 10.1007/s11442-012-0918-1
  25. Zeng, L., Wardlow, B.D., Tadesse, T., Shan, J., Hayes, M.J., Li, D., Xiang, D. (2015). Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Product over the Corn Belt in The US. Remote Sensing, 7, 951 – 970, doi: 10.3390/rs70100951

Last update:

No citation recorded.

Last update: 2024-11-20 19:42:22

No citation recorded.