Aguilar, H., Mora, R., Vargas, C. 2014. Metodología para la corrección atmosférica de imágenes Aster, Rapideye, Spot 2 y Landsat 8 con el módulo Flaash del software Envi. Revista Geográfica de América Central, 2(53), 39-59. https://doi.org/10.15359/rgac.2-53.2
Aguilar, J., Espinoza, R., Espinoza, J.C., Rojas, J., Willems, B.L., Leyva, W.M. 2019. Elevationdependent warming of land surface temperatures in the Andes assessed using MODIS LST time series (2000-2017). International Journal of Applied Earth Observation and Geoinformation, 77, 119- 128. https://doi.org/10.1016/j.jag.2018.12.013
Araghi, A., Mousavi-Baygi, M., Adamowski, J. 2017. Detecting soil temperature trends in Northeast Iran from 1993 to 2016. Soil and Tillage Research, 174, 177-192. https://doi.org/10.1016/j.still.2017.07.010
[+]
Aguilar, H., Mora, R., Vargas, C. 2014. Metodología para la corrección atmosférica de imágenes Aster, Rapideye, Spot 2 y Landsat 8 con el módulo Flaash del software Envi. Revista Geográfica de América Central, 2(53), 39-59. https://doi.org/10.15359/rgac.2-53.2
Aguilar, J., Espinoza, R., Espinoza, J.C., Rojas, J., Willems, B.L., Leyva, W.M. 2019. Elevationdependent warming of land surface temperatures in the Andes assessed using MODIS LST time series (2000-2017). International Journal of Applied Earth Observation and Geoinformation, 77, 119- 128. https://doi.org/10.1016/j.jag.2018.12.013
Araghi, A., Mousavi-Baygi, M., Adamowski, J. 2017. Detecting soil temperature trends in Northeast Iran from 1993 to 2016. Soil and Tillage Research, 174, 177-192. https://doi.org/10.1016/j.still.2017.07.010
Artis, D. A., Carnahan, W.H. 1982. Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12(4), 313-329. https://doi.org/10.1016/0034-4257(82)90043-8
Arvidson, T., Barsi, J., Jhabvala, M., Reuter, D. 2013. Landsat and Thermal Infrared Imaging. En C. Kuenzer & S. Dech (Eds.), Thermal Infrared Remote Sensing: Sensors, Methods, Applications (pp. 177-196). Springer Netherlands. https://doi.org/10.1007/978-94-007-6639-6_9
Avdan, U., Jovanovska, G. 2016. Algorithm for Automated Mapping of Land Surface Temperature Using Landsat 8 Satellite Data. Journal of Sensors, 2016, 1480307-1480307. https://doi.org/10.1155/2016/1480307
Carlson, T.N., Ripley, D.A. 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1
Caselles, E., Abad, F.J., Valor, E., Caselles, V. 2011. Automatic Generation of Land Surface Emissivity Maps. Climate Change - Research and Technology for Adaptation and Mitigation, 15. https://doi.org/10.5772/24968
Chi, Y., Sun, J., Sun, Y., Liu, S., Fu, Z. 2020. Multitemporal characterization of land surface temperature and its relationships with normalized difference vegetation index and soil moisture content in the Yellow River Delta, China. Global Ecology and Conservation, 23, e01092. https://doi.org/10.1016/j.gecco.2020.e01092
Dozier, J. 1989. Spectral signature of alpine snow cover from the Landsat thematic mapper. Remote Sensing of Environment, 28, 9-22. https://doi.org/10.1016/0034-4257(89)90101-6
Gutman, G., Ignatov, A. 1998. The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models. International Journal of Remote Sensing, 19(8), 1533- 1543. https://doi.org/10.1080/014311698215333
Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., Ferreira, L.G. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1), 195-213. https://doi.org/10.1016/S0034-4257(02)00096-2
ITT Visual Information Solutions. 2009. ENVI Atmospheric Correction Module: QUAC and FLAASH User's Guide, Version 4.7, pp. 44. http://www.harrisgeospatial.com/portals/0/pdfs/ envi/Flaash_Module.pdf
Jiménez-Muñoz, J.C., Sobrino, J.A., Skoković, D., Mattar, C., Cristóbal, J. 2014. Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data. IEEE Geoscience and Remote Sensing Letters, 11(10), 1840-1843. https://doi.org/10.1109/LGRS.2014.2312032
Mendoza, J.N. 2014. Implementación de un método operativo para la estimación de la temperatura superficial terrestre en la Región Callao usando datos de las imágenes satelitales. Universidad Nacional del Callao, 53. http://repositorio.unac.edu.pe/handle/UNAC/966
Moncada, W., Pereda, A., Aldana, C., Masias, M., Jiménez, J. 2015. Cuantificación hidrográfica de la cuenca del río Cachi-Ayacucho, mediante imágenes satelitales. Instituto de Investigación Científica e innovación Tecnológica de la UNSCH, II.
Moncada, W., Willems, B., Rojas, J. 2020. Estimación de estadíos estacionales a partir de parámetros climáticos medidos en la estación meteorológica de la microcuenca Apacheta, Región Ayacucho, 2000 al 2018. Revista de Investigación de Física. UNMSM, 23(2), 17-25. https://fisica.unmsm.edu.pe/ rif/previo_files/2020-2/03moncada.pdf
Pereda, A., Moncada, W., Verde, L. 2018. Respuesta nival de la cabecera de cuenca Cachi-Apacheta de Ayacucho: Vol. I. Editorial Académica Española. https://www.morebooks.shop/store/es/book/ respuesta-nival-de-la-cabecera-de-cuenca-cachiapacheta-de-ayacucho/isbn/978-620-2-12620-5
Quispe, B.J., Révolo, R.H. 2020. Temperatura superficial y estado de la vegetación del bosque de Polylepis spp, distrito de San Marcos de Rocchac, Huancavelica - Perú. Enfoque UTE, 11(3), 69-86. https://doi.org/10.29019/enfoque.v11n3.592
Rudjord, Due, 2012. Evaluation of FLAASH atmospheric correction (SAMBA/10/12; p. 24). Norwegian Computing Center. http://publications. nr.no/1338298623/Rudjord-Trier_FLAASH_2012. pdf
Santos, B. 2016. Cubierta Nival y Temperaturas de Superficie en Sierra Nevada a través del tratamiento digital de imágenes de satélite [Tesis Doctoral, Universitat de Barcelona]. http://diposit.ub.edu/dspace/handle/2445/108441
Sayão, V.M., Demattê, J.A.M., Bedin, L.G., Nanni, M.R., Rizzo, R. 2018. Satellite land surface temperature and reflectance related with soil attributes. Geoderma, 325, 125-140. https://doi.org/10.1016/j.geoderma.2018.03.026
Sobrino, J., Jiménez, J., Paolini, L. 2004. Land surface temperature retrieval from Landsat TM 5. Remote Sensing of Environment, 90(4), 434-440. https://doi.org/10.1016/j.rse.2004.02.003
Solman, S.A., Nuñez, M.N., Cabré, M.F. 2008. Regional climate change experiments over southern South America. I: Present climate. Climate Dynamics, 30(5), 533-552. https://doi.org/10.1007/s00382-007-0304-3
USGS, Landsat Collections, Landsat Missions. Consultado el 14 de octubre de 2019, de https://www.usgs.gov/land-resources/nli/landsat.
Vuille, M., Bradley, R.S. 2000. Mean annual temperature trends and their vertical structure in the tropical Andes. Geophysical Research Letters, 27(23), 3885- 3888. https://doi.org/10.1029/2000GL011871
Weng, Q., Lu, D., Schubring, J. 2004. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467-483. https://doi.org/10.1016/j.rse.2003.11.005
Xu, C., Qu, J.J., Hao, X., Zhu, Z., Gutenberg, L. 2020. Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements. International Journal of Applied Earth Observation and Geoinformation, 91, 102156. https://doi.org/10.1016/j.jag.2020.102156
Zhang, A., Liu, X., Di, W. 2009. Derivation of the green vegetation fraction from TM data of three gorges area. Procedia Earth and Planetary Science, 1(1), 1152- 1157. https://doi.org/10.1016/j.proeps.2009.09.177
[-]