An Evaluation of MODIS Global Evapotranspiration Product as Satellite-Based Evapotranspiration Data for Supporting Precision Agriculture in West Papua - Indonesia
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Aguilar AL, H Flores, G Crespo, MI Mar, I Campos and A Calera. 2018. Performance assessment of MOD16 in evapotranspiration evaluation in Northwestern Mexico. Water 10: 14p. https://doi.org/10.3390/w10070901
Allen RG, LS Pereira, D Raes and M Smith. 1998. Fao Irrigation and Drainage Paper No 56/ : Crop Evapotranspiration (1st ed.). FAO. 300p.
Bonemberger BdS, E Mercante, MAV Boas, SC Wrublack and LV Oldoni. 2018. Satellite-based ET estimation using landsat 8 Images and SEBAL model1. Rev Ciênc Agron 49: 221-227. https://doi.org/10.5935/1806-6690.20180025
Ceron CN, AM Melesse, R Price, SB Dessu and HP Kandel. 2015. Operational actual wetland evapotranspiration estimation for South Florida using MODIS imagery. Remote Sens 7: 3613-3632. https://doi.org/10.3390/rs70403613
Courault D, B Seguin and A Olioso. 2005. Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches. Irrig Drain Syst 19: 223-249.
Faisol A, B Budiyono, I Indarto and E Novita. 2020. Comparison of Terra MODIS Surface Reflectance (TMSR) and Terra MODIS Global Evapotranspiration (TMGE) as Satellite Image-Based Evapotranspiration (ET) in East Java-Indonesia. Agrociencia J 54: 2020-2054.
Faisol A, I Indarto, E Novita and B Budiyono. 2020. An evaluation of modis global evapotranspiration product (MOD16A2) as terrestrial evapotranspiration study in Manokwari-West Papua-Indonesia. ARPN J Eng Appl Sci 15: 510-513.
Guzinski R and H Nieto. 2019. Evaluating the feasibility of using Sentinel-2 and Sentinel-3 satellites for high-resolution evapotranspiration estimations. Remote Sens Environ 221: 157-172. https://doi.org/10.1016/j.rse.2018.11.019
Jiang L, S Islam and TN Carlson. 2004. Uncertainties in latent heat flux Measurement and estimation/ : implications for using a simplified approach with remote sensing data. Can J Remote Sens 30: 769-787. https://doi.org/10.5589/m04-038
Junior PF, AM Sousa, MI Vitorino, EB De Souza and PJOP De Souza. 2013. Estimativa de evapotranspiração, no leste da Amazônia utilizando SEBAL. Amazonian J Agr Env Sci 56: 33-39.
Kalma JD, TR McVicar and MF McCabe. 2008. Estimating land surface evaporation/ : A review of methods using remotely sensed surface temperature data. Surv Geophys 29: 421-469. https://doi.org/10.1007/s10712-008-9037-z
Kim HW, K Hwang, Q Mu, SO Lee and M Choi. 2012. Validation of MODIS 16 global terrestrial evapotranspiration products in various climates and land cover types in Asia. KSCE J Civ Eng 16: 229-238. https://doi.org/10.1007/s12205-012-0006-1
Li Y, C Huang, J Hou, J Gu, G Zhu and X Li. 2017. Mapping daily evapotranspiration based on spatiotemporal fusion of ASTER and MODIS images over irrigated agricultural areas in the Heihe River Basin, Northwest China. Agric For Meteorol 244-245: 82-97. https://doi.org/10.1016/j.agrformet.2017.05.023
Miranda RDQ, JD Galvíncio, MSB de Moura, CA Jones and R Srinivasan. 2017. Reliability of MODIS evapotranspiration products for heterogeneous dry forest/ : A study case of caatinga. Adv Meteorol 2017: 14p. https://doi.org/10.1155/2017/9314801
Mu Q, M Zhao and SW Running. 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ 115: 1781-1800. https://doi.org/10.1016/j.rse.2011.02.019
Mu Q, M Zhao and SW Running. 2013. MODIS global terrestrial evapotranspiration (ET) product (NASA MOD16A2/A3): Algorithm Theoretical Basic Document. NASA. 66p.
Nouri H, M Faramarzi, B Sobhani and SH Sadeghi. 2017. Estimation of evapotranspiration based on surface energy balance algorithm for land (SEBAL) using Landsat 8 and MODIS images. Appl Ecol Env Res 15: 1971-1982.
Omranian E, HO Sharif and AA Tavakoly. 2018. How well can global precipitation measurement (GPM) capture hurricanes? case study/ : hurricane harvey. Remote Sens: 14p. https://doi.org/10.3390/rs10071150
Pierce FJ and P Nowak. 1999. Aspect of precision agriculture. Adv Agron 67: 1-85. https://doi.org/https://doi.org/10.1016/S0065-2113(08)60513-1
Shekar NCS and L Nandagiri. 2016. Actual Evapotranspiration Estimation Using a Penman-Monteith Model. Int J Adv Agr Environ Engg. 3: 161-164.
Thenkabail P. 2016. Remote Sensing Handbook/ : Land resources monitoring, modeling, and mapping with remote sensing: Vol. II (1st ed.). CRC Press. London. 849p.
WMO [World Meteorological Organization]. 2008. Guide to Hydrological Practices. Volume I: Hydrology–From Measurement to Hydrological Information. In Journal of the Nepal Medical Association: Vol. I (6th ed., Issue 168). World Meteorological Organization. https://doi.org/10.1080/02626667.2011.546602
Zhang Q. 2016. Precision Agriculture Technology for Crop Farming (1st ed.). CRC Press. London. 368p.
DOI: http://dx.doi.org/10.5400/jts.2021.v26i1.43-49
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