Google Scholar Profile, > 6000 citations
Patent
[01] G. Mountrakis (Inventor). Multi-scale radial basis function neural network. Full patent (#7,577,626) Issued August 18, 2009. More…
Journal Papers
+ identifies current or former graduate student.
[60] Mountrakis, G. and Heydari+, S. (2023). Harvesting the Landsat archive for land cover land use classification using deep neural networks: Comparison with traditional classifiers and multi-sensor benefits, ISPRS Journal of Photogrammetry and Remote Sensing, 200, 106-119. [5.8MB pdf]
[59] Pede, T.+ , G. Mountrakis (2022). Towards daily maximum heat index estimation across the conterminous United States using satellite-derived products. International Journal of Remote Sensing, 43 (8), 2861-2884. [6.2MB pdf]
[58] H. Jin+, G. Mountrakis (2022). Fusion of optical, radar and waveform LiDAR observations for land cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 187, 171-190., [6.5MB pdf]
[57] Mountrakis G, and Yang S.+ (2021). Linking Population and Forest Dynamics over the Conterminous US for the 1990s and 2000s. Advances in Environmental and Engineering Research, 2(1):8. [0.5MB pdf]
[56] Khan, R.M.; Salehi, B.; Mahdianpari, M.; Mohammadimanesh, F.; Mountrakis, G.; Quackenbush, L.J (2021). A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective. Remote Sensing, 13, 4347. [49 MB pdf]
[55] Mountrakis G, Yang S.+ (2021). Contributing Factors to Forest Loss in Conterminous U.S. for the 1990s and 2000s. Advances in Environmental and Engineering Research, 2(4):17.[1MB pdf]
[54] Pede, T.+ , G. Mountrakis, S. Shaw (2019). Improving corn yield prediction across the US Corn Belt by replacing air temperature with daily MODIS land surface temperature. Agricultural and Forest Meteorology, 276, 10761. [3MB pdf]
[53] Paltsyn, M.Y. , J. Gibbs ,L.V. Iegorova, G. Mountrakis (2019). Integrating Traditional Ecological Knowledge and Remote Sensing for Monitoring Rangeland Dynamics in the Altai Mountain Region, Environmental Management, 64 (1), 40-51. [1MB pdf]
[52] Mountrakis, G., Li, J. ,Lu, X., Hellwich, O. (2018). Deep learning for remotely sensed data. ISPRS Journal of Photogrammetry and Remote Sensing, 145, 1-2. [0.4 MB pdf]
[51] Iegorova. L.V. , J. Gibbs, G. Mountrakis, et al. (2019). Rangeland vegetation dynamics in the Altai Mountain region of Mongolia, Russia, Kazakhstan and China: Effects of climate, topography, and socio-political context for livestock herding practices, Environmental Research Letters. [1MB pdf]
[50] Heydari+ S., G. Mountrakis (2019). A meta-analysis of deep neural networks in remote sensing: A comparative study to support vector machines, ISPRS Journal of Photogrammetry and Remote Sensing, 152, 192-210. [1MB pdf]
[49] Pede+, T., G. Mountrakis (2018). An empirical comparison of interpolation methods for MODIS 8-day land surface temperature composites across the conterminous United States, ISPRS Journal of Photogrammetry and Remote Sensing, 142, 137-150. [4MB pdf]
[48] Khatami+ R., G. Mountrakis (2018). The interacting effects of image acquisition date, number of images, classifier, and number of training samples on accuracy of binary classification of impervious cover. Remote Sensing Letters, 9(2): 189-198. . [1MB pdf]
[47] S. Heydari+, G. Mountrakis (2018). Effect of classifier selection, reference sample size, reference class distribution and scene heterogeneity in per-pixel classification accuracy using 26 Landsat sites. Remote Sensing of Environment, 204, 648-658. [0.9MB pdf]
[46] R. Khatami+, G. Mountrakis, S. Stehman (2017). Predicting individual pixel error in remote sensing soft classification. Remote Sensing of Environment, 199, 401-414. [2.0MB pdf]
[45] G. Mountrakis, Y. Lee+, (2017). A Linearly Approximated Iterative Gaussian Decomposition Method for waveform LiDAR processing. ISPRS Journal of Photogrammetry and Remote Sensing, 129, 200-211. [1.7MB pdf]
[44] M.Y. Paltsyn, J. Gibbs ,L.V. Iegorova, G. Mountrakis (2017). Estimation and Prediction of Grassland Cover in Western Mongolia using MODIS-derived Vegetation Indices. Rangeland Ecology & Management, 70 (6), 723-729. [link].
[43] M.A. Petrov, T.Y. Sabitov, I.G. Tomashevskaya, G.E. Glazirin, S.S. Chernomorets, E.A. Savernyuk, O.V. Tutubalina, D.A. Petrakov, L.S. Sokolov, M.D. Dokukin, G. Mountrakis, V. Ruiz-Villanueva, M. Stoffel (2017). Glacial lake inventory and lake outburst potential in Uzbekistan, Science of The Total Environment, 592, 228-242. [link].
[42] S. Yang+, G. Mountrakis (2017). Forest dynamics in the U.S. indicate disproportionate attrition in western forests, rural areas and public lands. PLoS ONE 12(2): e0171383. doi:10.1371/journal.pone.0171383. [2.3MB pdf]. See NY Times and Washington Post coverage here.
[41] R. Khatami+, G. Mountrakis, S. Stehman (2017). Mapping per-pixel predicted accuracy of classified remote sensing images. Remote Sensing of Environment, 191, 156–167. [3.4MB pdf]
[40] Z. Xu+, G. Mountrakis and L.J. Quackenbush (2017). Impervious surface extraction in imbalanced datasets: integrating partial results and multi-temporal information in an iterative one-class classifier. International Journal of Remote Sensing, 38(1), 43-63. [2.9MB pdf]
[39] R. Khatami+, G. Mountrakis, S. Stehman (2016). A meta-analysis of remote sensing research on land-cover image classification processes: A guide for practitioners and directions for future research. Remote Sensing of Environment, 177, 89–100.[0.8MB pdf]
[38] A. Endres+, G. Mountrakis, H. Jin+, W. Zhuang+, I. Manakos, J.J. Wiley Jr and C.M. Beier (2016). Relative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation. European Journal of Remote Sensing, 49, 795-807.[0.4MB pdf]
[37] K. Pandit, E. Bevilacqua, G. Mountrakis, R. W. Malmsheimer (2016). Spatial Analysis of Forest Crimes in Mark Twain National Forest, MI. Journal of Geospatial Applications in Natural Resources, 1(1), 3.[2.0MB pdf]
[36] G. Grekousis+, G. Mountrakis, M. Kavouras (2016). Linking MODIS-derived forest and cropland land cover 2011 estimations to socioeconomic and environmental indicators for the European Union’s 28 countries. GIScience and Remote Sensing, 53(1), 122-146.[2.2MB pdf]
[35] I. Manakos, E. Technitou, Z. Petrou, C. Karydas, V. Tomaselli, G. Veronico, and G. Mountrakis (2016). Multi-modal knowledge base generation from very high resolution satellite imagery for habitat mapping. European Journal of Remote Sensing, 49, 1033 – 1060.[1.6MB pdf]
[34] G. Grekousis+, G. Mountrakis, M. Kavouras (2015). An overview of 21 global and 43 regional land cover mapping products. International Journal of Remote Sensing, 36(21), 5309-5335. [1.1MB pdf]
[33] S. Yousefi, R. Khatami+, G. Mountrakis, S. Mirzaee, H.R. Pourghasemi, M. Tazeh (2015). Accuracy assessment of land cover/land use classifiers in dry and humid areas of Iran. Environmental Monitoring and Assessment, October 2015, 187:641. [1.4MB pdf]
[32] G. Grekousis+, G. Mountrakis (2015). Sustainable development under population pressure: Lessons from Developed Land Consumption in the Conterminous U.S. PLoS ONE 10(3): e0119675. doi:10.1371/journal.pone.0119675. [pdf and more]
[31] W. Zhuang+, G. Mountrakis, J. Wiley, C. Beier (2015). Estimation of Aboveground Forest Biomass Using Metrics Based on Gaussian Decomposition of Waveform Lidar Data. International Journal of Remote Sensing, 36(7), 1871-1889.[2.6MB pdf]
[30] H. Jin+, G. Mountrakis, S. Stehman (2014). Assessing integration of intensity, polarimetric scattering, interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 98:70–84.[3.2MB pdf]
[29] W. Zhuang+, G. Mountrakis (2014). Ground peak identification in dense shrub areas using large footprint waveform LiDAR and Landsat images. International Journal of Digital Earth, 1-44. [1.1MB pdf]
[28] W. Zhuang+, G. Mountrakis (2014). An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing, 95:81-92. [2.9MB pdf]
[27] L.M. Giencke, M.Dovciak, G. Mountrakis, J.A. Cale, M.J. Mitchell (2014). Beech bark disease: spatial patterns of thicket formation and disease spread in an aftermath forest in the northeastern United States. Canadian Journal of Forest Research, 44:1042–1050. [1.1MB pdf]
[26] H. Jin+, S. Stehman, G. Mountrakis (2014). Assessing the impact of training sample selection on accuracy of an urban classification: a case study in Denver, Colorado. International Journal of Remote Sensing, 35(6): 2067-2081. [0.6MB pdf]
[25] G. Mountrakis , B. Xi+ (2013). Assessing Reference Dataset Representativeness through Confidence Metrics based on Information Density. ISPRS Journal of Photogrammetry and Remote Sensing, 78:129-147. [4.1MB pdf]
[24] H. Jin+, G. Mountrakis (2013). Integration of urban growth modeling products to image-based urban change analysis. International Journal of Remote Sensing, 34(15): 5468-5486. [4.1MB pdf]
[23] R. Khatami+, G. Mountrakis (2012). Implications of Classification Methodological Decisions in Flooding Analysis from Hurricane Katrina. Remote Sensing, 4(12), 3877-3891. [4.9MB pdf]
[22] D. Triantakonstantis+, G. Mountrakis, (2012). Urban growth prediction: A review of computational models and human perceptions. Journal of Geographic System, 4(6): 555-587. [0.5MB pdf]
[21] G. Mountrakis , W. Zhuang+ (2012). Integrating Local and Global Error Statistics for Multi-Scale RBF Network Training: An Assessment on Remote Sensing Data. Public Library of Science (PLOS One), 7(8): e40093. doi:10.1371/journal.pone.0040093.[1.1MB pdf],[link]
[20] H. Jin+, G. Mountrakis , P. Li (2012). A super-resolution mapping method using local indicator variograms. International Journal of Remote Sensing, 33(24): 7747–7773.[3.1MB pdf]
[19] G. Mountrakis, D. Triantakonstantis+ (2012). Inquiry-based learning in remote sensing: A space balloon educational experiment. Journal of Geography in Higher Education, 36(3): 385-401.[0.4MB pdf]
[18] B. Hong, K. Limburg, M. Hall, G. Mountrakis, P. Groffman, K. Hyde, L. Luo+, V. Kelly, S. Myers (2012). An integrated monitoring/modeling framework for assessing human-nature interactions in urbanizing watersheds: Wappinger and Onondaga Creek watersheds, New York, USA. Environmental Modelling & Software, 32:1-15.[3.2MB pdf]
[17] L. Luo+, G. Mountrakis (2012). A multi-process model of adaptable complexity for impervious surface detection. International Journal of Remote Sensing, 33(2):365-381.[1.8MB pdf]
[16] G. Mountrakis, A. Stefanidis (2011). Moving Towards Personalized Geospatial Queries. Journal of Geographic Information System, 3(4): 334-344.[1.0MB pdf]
[15] D. Triantakonstantis+, G. Mountrakis, J. Wang+ (2011). A Spatially Heterogeneous Expert Based (SHEB) Urban Growth Model using Model Regionalization, Journal of Geographic Information System, 3(3):195-210.[3.5MB pdf]
[14] L. Luo+, G. Mountrakis (2011). Converting local spectral and spatial information from a priori classifiers into contextual knowledge for impervious surface classification. ISPRS Journal of Photogrammetry and Remote Sensing, 66(5): 579–587.[1.4MB pdf]
[13] J. Wang+, G. Mountrakis (2011). Developing a multi-network urbanization (MuNU) model: A case study of urban growth in Denver, Colorado. International Journal of Geographical Information Science, 25(2):229-253.[3.9MB pdf]
[12] G. Mountrakis, L. Luo+ (2011). Enhancing and replacing spectral information with intermediate structural inputs: A case study on impervious surface detection. Remote Sensing of Environment, 115(5):1162-1170.[1.8MB pdf]
[11] B. Gong, J. Im, G. Mountrakis (2011). An Artificial Immune Network Approach to Multi-Sensor Land Use/Land Cover Classification. Remote Sensing of Environment, 115(2):600-614. [link]
[10] K. Gunson+, G. Mountrakis, L. Quackenbush (2011). Spatial wildlife-vehicle collision models: A review of current work and their application to transportation mitigation projects. Journal of Environmental Management, 92(4):1074-1082. [317KB pdf]
[09] G. Mountrakis, J. Im, C. Ogole+ (2011). Support vector machines in remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 66(3):247-259. [803KB pdf]
[08] L. Luo+, G. Mountrakis (2010). Integrating intermediate inputs from partially classified images within a hybrid classification framework: An impervious surface estimation example. Remote Sensing of Environment, 114(6):1220-1229. [2.4MB pdf]
[07] G. Mountrakis, K. Gunson+ (2009). Multi-scale spatiotemporal analyses of moose-vehicle collisions: A case study in northern Vermont. International Journal of Geographical Information Science, 23(11):1389-1412. [911KB pdf]
[06] G. Mountrakis, R. Watts, L. Luo+, J. Wang+ (2009). Developing Collaborative Classifiers using an Expert-based Model. Photogrammetric Engineering and Remote Sensing, 75(7):831-844. [944KB pdf]
[05] G. Mountrakis, A. Stefanidis (2008, not refereed). Foreword for Special Issue: Artificial Intelligence in Remote Sensing, Photogrammetric Engineering and Remote Sensing, 74(10):1199. [link]
[04] G. Mountrakis (2008, not refereed). Next generation classifiers: Focusing on integration frameworks. Highlight article for Photogrammetric Engineering and Remote Sensing, 74(10):1178-1180. [694KB pdf]
[03] G. Mountrakis, P. Agouris, A. Stefanidis (2005). Adaptable User Profiles for Intelligent Geospatial Queries. Transactions in GIS, Vol. 9, No. 4, pp. 561-583. [597KB pdf]
[02] G. Mountrakis, P. Agouris, I. Schlaisich, A. Stefanidis (2004). Supporting Quality-Based Image Retrieval Through User Preference Learning. Photogrammetric Engineering and Remote Sensing, Vol. 70, No. 8, pp. 973-981. [2.1MB pdf]
[01] P. Agouris, K. Beard, G. Mountrakis, A. Stefanidis (2000). Capturing and Modeling Geographic Object Change: A Spatio-Temporal Gazetteer Framework. Photogrammetric Engineering and Remote Sensing, Vol. 66, No. 10, pp. 1224-1250. [203KB pdf]
+ identifies current or former advisee.