Avdan, U., & Jovanovska, G. (2016). Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data. Journal of Sensors, 2016, 1–8.
Bosilovich, M. G. (2006). A comparison of MODIS land surface temperature with in situ observations. Geophysical Research Letters, 33, L20112.
Coll, C., Wan, Z., & Galve, J. M. (2009). Temperature-based and radiance-based validations of the V5 MODIS land surface temperature product. Journal of Geophysical Research Atmospheres, 114, D20102.
Duan, S.-B., Li, Z.-L., Tang, B.-H., Wu, H., & Tang, R. (2014). Generation of a time-consistent land surface temperature product from MODIS data. Remote Sensing of Environment, 140, 339–349.
Emelyanova, I. V., McVicar, T. R., Van Niel, T. G., Li, L. T., & van Dijk, A. I. J. M. (2013). Assessing the accuracy of blending Landsat-MODIS surface reflectances in two landscapes with contrasting spatial and temporal dynamics: A framework for algorithm selection. Remote Sensing of Environment, 133, 193–209.
Feng Gao, Masek, J., Schwaller, M., & Hall, F. (2006). On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 44, 2207–2218.
Feng, M., Huang, C., Channan, S., Vermote, E. F., Masek, J. G., & Townshend, J. R. (2012). Quality assessment of Landsat surface reflectance products using MODIS data. Computers & Geosciences, 38, 9–22.
Feng, M., Sexton, J. O., Huang, C., Masek, J. G., Vermote, E. F., Gao, F., … Townshend, J. R. (2013). Global surface reflectance products from Landsat: Assessment using coincident MODIS observations. Remote Sensing of Environment, 134, 276–293.
Fu, D., Chen, B., Wang, J., Zhu, X., & Hilker, T. (2013a). An Improved Image Fusion Approach Based on Enhanced Spatial and Temporal the Adaptive Reflectance Fusion Model. Remote Sensing, 5, 6346–6360.
Fu, D., Chen, B., Wang, J., Zhu, X., & Hilker, T. (2013b). An Improved Image Fusion Approach Based on Enhanced Spatial and Temporal the Adaptive Reflectance Fusion Model. Remote Sensing, 5, 6346–6360.
Guan, X., Liu, G., Huang, C., Liu, Q., Wu, C., Jin, Y., & Li, Y. (2017a). An Object-Based Linear Weight Assignment Fusion Scheme to Improve Classification Accuracy Using Landsat and MODIS Data at the Decision Level. IEEE Transactions on Geoscience and Remote Sensing, 55, 6989–7002.
Guan, X., Liu, G., Huang, C., Liu, Q., Wu, C., Jin, Y., & Li, Y. (2017b). An Object-Based Linear Weight Assignment Fusion Scheme to Improve Classification Accuracy Using Landsat and MODIS Data at the Decision Level. IEEE Transactions on Geoscience and Remote Sensing, 55, 6989–7002.
Guillevic, P. C., Bork-Unkelbach, A., Gottsche, F. M., Hulley, G., Gastellu-Etchegorry, J.-P., Olesen, F. S., & Privette, J. L. (2013). Directional Viewing Effects on Satellite Land Surface Temperature Products Over Sparse Vegetation Canopies—A Multisensor Analysis. IEEE Geoscience and Remote Sensing Letters, 10, 1464–1468.
Hazaymeh, K., Hassan, Q. K., Pinheiro, A., Xiong, Y., & Qiu, G. (2015). Fusion of MODIS and Landsat-8 Surface Temperature Images: A New Approach. PLOS ONE, 10, e0117755.
Hilker, T., Wulder, M. A., Coops, N. C., Linke, J., McDermid, G., Masek, J. G., … White, J. C. (2009). A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS. Remote Sensing of Environment, 113, 1613–1627.
Hulley, G. C., & Hook, S. J. (2009). Intercomparison of versions 4, 4.1 and 5 of the MODIS Land Surface Temperature and Emissivity products and validation with laboratory measurements of sand samples from the Namib desert, Namibia. Remote Sensing of Environment, 113, 1313–1318.
Inamdar, A. K., French, A., Hook, S., Vaughan, G., & Luckett, W. (2008). Land surface temperature retrieval at high spatial and temporal resolutions over the southwestern United States. Journal of Geophysical Research, 113, D07107.
Kustas, W. P., Norman, J. M., Anderson, M. C., & French, A. N. (2003). Estimating subpixel surface temperatures and energy fluxes from the vegetation index–radiometric temperature relationship. Remote Sensing of Environment, 85, 429–440.
Liu, H. (2012). Enhancing temporal resolution of satellite imagery for public health studies: A case study of West Nile Virus outbreak in Los Angeles in 2007. Remote Sensing of Environment, 117, 57–71.
Liu, X., Deng, C., Wang, S., Huang, G.-B., Zhao, B., & Lauren, P. (2016). Fast and Accurate Spatiotemporal Fusion Based Upon Extreme Learning Machine. IEEE Geoscience and Remote Sensing Letters, 13, 2039–2043.
Maimaitiyiming, M., Ghulam, A., Tiyip, T., Pla, F., Latorre-Carmona, P., Halik, Ü., … Caetano, M. (2014). Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation. ISPRS Journal of Photogrammetry and Remote Sensing, 89, 59–66.
Meng, J., Du, X., & Wu, B. (2013). Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation. International Journal of Digital Earth, 6, 203–218.
Moosavi, V., Talebi, A., Mokhtari, M. H., Shamsi, S. R. F., & Niazi, Y. (2015). A wavelet-artificial intelligence fusion approach (WAIFA) for blending Landsat and MODIS surface temperature. Remote Sensing of Environment, 169, 243–254.
Nichol, J. (2009). An Emissivity Modulation Method for Spatial Enhancement of Thermal Satellite Images in Urban Heat Island Analysis. Photogrammetric Engineering & Remote Sensing, 75, 547–556.
Oguro, Y., Ito, S., & Tsuchiya, K. (2011). Comparisons of Brightness Temperatures of Landsat-7/ETM+ and Terra/MODIS around Hotien Oasis in the Taklimakan Desert. Applied and Environmental Soil Science, 2011, 1–11.
Olivera-Guerra, L., Mattar, C., Merlin, O., Durán-Alarcón, C., Santamar’ia-Artigas, A., & Fuster, R. (2017). An operational method for the disaggregation of land surface temperature to estimate actual evapotranspiration in the arid region of Chile. ISPRS Journal of Photogrammetry and Remote Sensing, 128, 170–181.
Roy, D. P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M., & Lindquist, E. (2008). Multi-temporal MODIS–Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data. Remote Sensing of Environment, 112, 3112–3130.
Shen, H., Wu, P., Liu, Y., Ai, T., Wang, Y., & Liu, X. (2013). A spatial and temporal reflectance fusion model considering sensor observation differences. International Journal of Remote Sensing, 34, 4367–4383.
Singh, D. (2011). Generation and evaluation of gross primary productivity using Landsat data through blending with MODIS data. International Journal of Applied Earth Observation and Geoinformation, 13, 59–69.
Son, N. T., Chen, C. F., Chen, C. R., Chang, L. Y., & Minh, V. Q. (2012). Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18, 417–427.
Srivastava, P. K., Han, D., Ramirez, M. R., & Islam, T. (2013). Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application. Water Resources Management, 27, 3127–3144.
Volcani, A., Karnieli, A., & Svoray, T. (2005). The use of remote sensing and GIS for spatio-temporal analysis of the physiological state of a semi-arid forest with respect to drought years. Forest Ecology and Management, 215, 239–250.
Wan, Z., Zhang, Y., Zhang, Q., & Li, Z.-L. (2004). Quality assessment and validation of the MODIS global land surface temperature. International Journal of Remote Sensing, 25, 261–274.
Wan, Zhengming. (2008). New refinements and validation of the MODIS Land-Surface Temperature / Emissivity products. Remote Sensing of Environment, 112, 59–74.
Wan, Zhengming. (2014). New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote Sensing of Environment, 140, 36–45.
Wang, K., Wan, Z., Wang, P., Sparrow, M., Liu, J., & Haginoya, S. (2007). Evaluation and improvement of the MODIS land surface temperature/emissivity products using ground-based measurements at a semi-desert site on the western Tibetan Plateau. International Journal of Remote Sensing, 28, 2549–2565.
Zakšek, K., & Oštir, K. (2012). Downscaling land surface temperature for urban heat island diurnal cycle analysis. Remote Sensing of Environment, 117, 114–124.
Zhan, W., Chen, Y., Zhou, J., Wang, J., Liu, W., Voogt, J., … Li, J. (2013). Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats. Remote Sensing of Environment, 131, 119–139.
Zhang, W., Li, A., Jin, H., Bian, J., Zhang, Z., Lei, G., … Huang, C. (2013). An Enhanced Spatial and Temporal Data Fusion Model for Fusing Landsat and MODIS Surface Reflectance to Generate High Temporal Landsat-Like Data. Remote Sensing, 5, 5346–5368.
Zhu, X., Chen, J., Gao, F., Chen, X., & Masek, J. G. (2010). An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions. Remote Sensing of Environment, 114, 2610–2623.
Zhu, X., Helmer, E. H., Gao, F., Liu, D., Chen, J., & Lefsky, M. A. (2016). A flexible spatiotemporal method for fusing satellite images with different resolutions. Remote Sensing of Environment, 172, 165–177.