Deutsch Intern
Earth Observation Research Cluster

Dr. Hooman Latifi

   +98 (0)21 88877070-3 (Ext. 312)
   
 hooman.latifi@kntu.ac.ir

Faculty of Geodesy and Geomatics Engineering
K. N. Toosi University of Technology
No. 1346, Valiasr Str., Mirdamad crossing
19967-15433 Tehran- Iran

upon request

since 06/2012
Research associate in the Dept. of Remote Sensing, University of Wuerzburg

10/2011 – 11/2011
Research stay at Forest measurements and modeling laboratory, Dept. of Forestry, Michigan State University, USA.

10/2008 – 11/2011
Doctoral studies (Dr. rer. nat) at der Albert-Ludwigs- Universität Freiburg, funded by scholarship from German Academic Exchange Service (DAAD) (first supervisor: Prof. Dr. Barbara Koch)

10/2003 – 06/2005
M.Sc studies at the Faculty of Natural Resources, University of Mazandaran (Iran) (Title of M.Sc thesis: Evaluating Landsat ETM+ data for forest-ecotone-rangeland mapping in the timberline of northern forests of Iran )

10/1999 – 06/2003
B.Sc studies at the Faculty of Natural Resources, University of Guilan (Iran)

2016[ to top ]
  • Latifi, H. (2016): Remote sensing-assisted monitoring of bark beetle-induced tree mortality. In: Comprehensive monitoring of stand dynamics in Bialowieza forest supported with remote sensing
  • Hill, S.; Latifi, H.; Heurich, M.; Müller, J. (2016): LiDAR-gestützte Erfassung von einzelbaum- und bestandsbasierter Waldentwicklung nach natürlichen Störungsprozessen. In: FowiTa - Forstwirtschaftliche Tagungpage, 123.
2015[ to top ]
  • Latifi, H.; Heurich, M.; Hartig, F.; Müller, J.; Krzystek, P.; H, J.; Dech, S. (2015): Crown density of over- and understory in mixed forest stands as explained by airborne LiDAR metrics. In: The 36th International Symposium on Remote Sensing of Environment
  • Latifi, H.; Fassnacht, F.; Hartig, F.; Berger, C.; Hernandez, J.; Corvalan, P.; Koch, B. (2015): Does a post-stratification of ground units improve the forest biomass estimation by remote sensing data?. In: The 36th International Symposium on Remote Sensing of Environment
2014[ to top ]
  • Latifi, H.; Schumann, B.; Fassnacht, F.; Dech, S. (2014): Dead stands from the space: multi-date imagery to map bark beetle binfestations. In: Proceedings of ForestSATpages, 4-7.
  • Latifi, H.; Gaub, V.; Heurich, M.; Krzystek, P.; Müller, J.; Dech, S. (2014): A naive Bayes model to describe natural forest ground vegetation by waveform LiDAR metrics. In: Proceedings of GfÖ – Annual Meeting
  • Latifi, H. (2014): From 3D point cloud to the stand: Experiences on small-scale inventory of forest structure by airborne remote sensing. In: Proceedings of the International Workshop 3D Vegetation Mapping using Advanced Remote Sensing
2013[ to top ]
  • Fassnacht, F.; Hartig, F.; Latifi, H.; Berger, C.; Hernández, J.; Corvalán, P.; Koch, B. (2013): Combination of EO1-Hyperion and LiDAR data to estimate biomass in a highly complex second growth native forest in central Chile. In: Latin American Remote Sensing week (LARS2013). 23-25 October 2013, Santiago de Chile, Chile.
  • Fassnacht, F.; Hartig, F.; Latifi, H.; Berger, C.; Hernandez, J.; Corvalon, P.; Koch, B. (2013): Combination of EO1-Hyperion and LiDAR data to estimate biomass in a highly complex second growth native forest in central Chile. In: Latin American Remote Sensing week (LARS2013). 23-25 October 2013, Santiago de Chile, Chile.
2011[ to top ]
  • Latifi, H.; Koch, B. (2011): Generalized spatial models of forest structure using airborne multispectral and laser scanner data. In: Proceedings of ISPRS Workshop: High resolution earth imaging for geospatial information,International Archives of the Photogrammetry, Remote sensing and Spatial Information Sciences
2010[ to top ]
  • Latifi, H.; Nothdurft, A.; Koch, B. (2010): Using optical data and small footprint LiDAR for plot-level estimation of forest biomass in a central European landscape. In: Nternational Union of Forest Research Organisations (IUFRO) world congress, 23-27 August 2010, Seoul- Südkorea (Oral presentation). Abstracts in: International Forestry Reviews 12(5): 333
  • Latifi, H.; Nothdurft, A.; Straub, C.; Koch, B. (2010): Die Anwendung der optischen und LiDAR Merkmale für nicht-parametrische Modellierung der Waldstrukturattribute: Die Bedeutung eines geeigneten Variablenauswahlverfahrens. In: Forstwissenschaftliche Tagung 2010: "Forstwissenschaften: Grundlage nachhaltiger Waldbewirtschaftung". 22.-24. September 2010. Georg-August Universität Göttingen
  • Latifi, H.; Nothdurft, A.; Straub, C.; Koch, B. (2010): Optical/LiDAR feature search for nonparametric prediction of stratified forest attributes using an improved genetic procedure. In: International Conference on LiDAR Applications for Assessing Forest Ecosystems (Silvilaser) 2010, 4.-17. September 2010, Freiburg
2008[ to top ]
  • Latifi, H.; Fahimi, M.; Mozaffari, D. (2008): On the necessity and application of building a GIS-based data bank for Environmental Impact Assessments (case study: Lorestan and Ilam provinces). In: Proceedings of the 2nd Regional Congress on Advances in Agriculture and Natural Resources Research. University of Kurdistan, Sanandaj-Iran
2006[ to top ]
  • Adeli, K.; Latifi, H.; Oladi, D. (2006): Investigating Landsat ETM+ Data Potential for Forest Type Mapping in Southern Zagros- Iran. In: Proceedings of National Geomatics Conference
2005[ to top ]
  • Latifi, H.; {Oladi, D. S.; Jalilvand, H. (2005): Evaluating ETM+ Data to Produce Forest-Shrub land-Range maps in Neka- Zalemroud region, Northern Iran.. In: 2005 International Symposium on Remote Sensing (ISRS), Korean Society of Remote Sensing (KSRS), 12-14. Oktober 2005 Jeju-Südkorea

2022[ to top ]
  • Kanmegne Tamga, D.; Latifi, H.; Ullmann, T.; Baumhauer, R.; Bayala, J.; Thiel, M. (2022): Estimation of Aboveground Biomass in Agroforestry Systems over Three Climatic Regions in West Africa Using Sentinel-1, Sentinel-2, ALOS, and GEDI Data. In: Sensors, 23 (349), 18.
2021[ to top ]
  • Khare, S.; Latifi, H.; Rossi, S. (2021): A 15-year spatio-temporal analysis of plant β-diversity using Landsat time series derived Rao’s Q index. In: Ecological Indicators, 121, 107105.
  • Shafeian, E.; Fassnacht, F. E.; Latifi, H. (2021): Mapping fractional woody cover in an extensive semi-arid woodland area at different spatial grains with Sentinel-2 and very high-resolution data. In: International Journal of Applied Earth Observation and Geoinformation, 105, 102621.
2020[ to top ]
  • Hosseini, Z.; Latifi, H.; Naghavi, H.; Bakhtiarvand Bakhtiari, S.; Fassnacht, F. E. (2020): Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery. In: Forestry: An International Journal of Forest Research.
  • Elham Karimzadeh, J.; Hamed, N.; Kamran, A.; Latifi, H. (2020): A nondestructive, remote sensing-based estimation of the economic value of aboveground temperate forest biomass (case study: Hyrcanian forests, Nowshahr-iran). In: Journal of Sustainable Forestry
  • Sangdehi, S. M. R.; Asghar, F.; Jafar, O.; Latifi, H. (2020): Effect of Altitude Gradient on Quantitative Characteristics of Forest Stands (Case Study: District-3 of Sangdeh Forests).. In: Journal of Wood and Forest Science Technology, 27 (1)
  • Stere{{ń}}czak, K.; Laurin, G. V.; Chirici, G.; Coomes, D. A.; Dalponte, M.; Latifi, H.; Puletti, N. (2020): Global Airborne Laser Scanning Data Providers Database ({GlobALS}){\textemdash}A New Tool for Monitoring Ecosystems and Biodiversity. In: Remote Sensing, 12 (11), 1877.
2019[ to top ]
  • Khare, S.; Latifi, H.; Rossi, S.; Ghosh, S. K. (2019): Fractional Cover Mapping of Invasive Plant Species by Combining Very High-Resolution Stereo and Multi-Sensor Multispectral Imageries. In: Forests, 10 (7), 540.
  • Latifi, H.; Heurich, M. (2019): Multi-Scale Remote Sensing-Assisted Forest Inventory: A Glimpse of the State-of-the-Art and Future Prospects. In: Remote Sensing, 11 (11), 1260.
  • Khare, S.; Latifi, H.; Rossi, S. (2019): Forest beta-diversity analysis by remote sensing: How scale and sensors affect the Rao’s Q index. In: Ecological Indicators, 106, 105520.
  • Ataee, M. S.; Maghsoudi, Y.; Latifi, H.; Fadaie, F. (2019): Improving Estimation Accuracy of Growing Stock by Multi-Frequency {SAR} and Multi-Spectral Data over Iran’s Heterogeneously-Structured Broadleaf Hyrcanian Forests. In: Forests, 10 (8), 641.
  • Latifi, H.; Valbuena, R. (2019): Current Trends in Forest Ecological Applications of Three-Dimensional Remote Sensing: Transition from Experimental to Operational Solutions?. In: Forests, 10 (10), 891.
  • Hosseini, Z.; Naghavi, H.; Latifi, H.; Bakhtiarvand, S. B. (2019): Estimating biomass and carbon sequestration of plantations around industrial areas using very high resolution stereo satellite imagery. In: {iForest} - Biogeosciences and Forestry, 12 (6), 533-41.
  • Leila, S.; Amir, E. B.; Ramin, N.; Latifi, H. (2019): Classification of quantitative attributes of Zagros forest using Landsat 8-OLI and Random Forest algorithm (Case study: protected area of Manesht forests).. In: Journal of Forest Research and Development, 4 (4), 415-34.
2018[ to top ]
  • Ramiro Silveyra, G.; Latifi, H.; Holger, W.; Matthias, D.; Marco, H.; Barbara, K. (2018): Integrating LiDAR and high-resolution imagery for object-based mapping of forest habitats in a heterogenuous temperate forest landscape.. In: International Journal of Remote Sensing
  • Kortmann, M.; Heurich, M.; Latifi, H.; Rösner, S.; Seidl, R.; Müller, J.; Thorn, S. (2018): Forest structure following natural disturbances and early succession provides habitat for two avian flagship species, capercaillie (Tetrao urogallus) and hazel grouse (Tetrastes bonasia). In: Biological Conservation, 226, 81-91.
  • Fassnacht, F. E.; Latifi, H.; Hartig, F. (2018): Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR. In: Remote Sensing of Environment, 213, 115-28.
  • Bae, S.; Müller, J.; Lee, D.; Vierling, K. T.; Vogeler, J. C.; Vierling, L. A.; Hudak, A. T.; Latifi, H.; Thorn, S. (2018): Taxonomic, functional, and phylogenetic diversity of bird assemblages are oppositely associated to productivity and heterogeneity in temperate forests. In: Remote Sensing of Environment, 215, 145-56.
  • Latifi, H.; Dahms, T.; Beudert, B.; Heurich, M.; Kübert, C.; Dech, S. (2018): Synthetic RapidEye data used for the detection of area-based spruce tree mortality induced by bark beetles. In: GIScience & Remote Sensing, 55 (6), 839-59.
  • Latifi, H.; Dahms, T.; Beuders, B.; Heurich, M.; Kuebert, C.; Dech, S. (2018): Synthetic RapiidEye data used for the detection of area-based spruce tree mortality induced by bark beetles.. In: GIScience and Remote Sensing
  • Röder, M.; Latifi, H.; Hill, S.; Jan, W.; Miroslav, S.; Josef, B.; Martin, M.; Nováková, M. H.; Eberhard, G.; Marco, H. (2018): Application of optical unmanned aerial vehicle-based imagery for the inventory of natural regeneration and standing deadwood in post-disturbed spruce forests.. In: International Journal of Remote Sensing
2017[ to top ]
  • Wang, Z.; Skidmore, A. K.; Wang, T.; Darvishzadeh, R.; Heiden, U.; Heurich, M.; Latifi, H.; Hearne, J. (2017): Canopy foliar nitrogen retrieved from airborne hyperspectral imagery by correcting for canopy structure effects. In: International Journal of Applied Earth Observation and Geoinformation, 54, 84-94.
  • Hill, S.; Latifi, H.; Heurich, M.; Müller, J. (2017): Individual-tree- and stand-based development following natural disturbance in a heterogeneously structured forest: A LiDAR-based approach. In: Ecological Informatics, 38, 12-25.
  • Karami, O.; Fallah, A.; Shataee, S.; Latifi, H. (2017): Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests). In: Iranian Journal of Forest and Poplar Research, 25 (3), 452-62.
  • Khare, S.; Ghosh, S. K.; Latifi, H.; Vijay, S.; Dahms, T. (2017): Seasonal-based analysis of vegetation response to environmental variables in the mountainous forests of Western Himalaya using Landsat 8 data. In: International Journal of Remote Sensing, 38 (15), 4418-42.
  • Khare, S.; Latifi, H.; Ghosh, S. K. (2017): Multi-scale assessment of invasive plant species diversity using Pléiades 1A, RapidEye and Landsat-8 data. In: Geocarto International, 1-18.
  • Latifi, H.; Hill, S.; Schumann, B.; Heurich, M.; Dech, S. (2017): Multi-model estimation of understorey shrub, herb and moss cover in temperate forest stands by laser scanner data. In: Forestry
  • Fassnacht, F. E.; Mangold, D.; Schäfer, J.; Immitzer, M.; Kattenborn, T.; Koch, B.; Latifi, H. (2017): Estimating stand density, biomass and tree species from very high resolution stereo-imagery {\textendash} towards an all-in-one sensor for forestry applications?. In: Forestry: An International Journal of Forest Research, 1-19.
  • Aryal, R. R.; Latifi, H.; Heurich, M.; Hahn, M. (2017): Impact of Slope, Aspect, and Habitat-Type on LiDAR-Derived Digital Terrain Models in a Near Natural, Heterogeneous Temperate Forest. In: PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science
  • Latifi, H.; Koch, B. (2017): Editorial for the Special Issue "Remote Sensing-assisted forest inventory". In: Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85 (4), 211-12.
2016[ to top ]
  • Khare, S.; Latifi, H.; Ghosh, K. (2016): Phenology Analysis of Forest Vegetation to Environmental Variables during pre-and Post-Monsoon Seasons in Western Himalayan Region of India. In: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., {XLI}-B2, 15-19.
  • Fassnacht, F. E.; Latifi, H.; Stereńczak, K.; Modzelewska, A.; Lefsky, M.; Waser, L. T.; Straub, C.; Ghosh, A. (2016): Review of studies on tree species classification from remotely sensed data. In: Remote Sensing of Environment, 186, 64-87.
  • Latifi, H.; Heurich, M.; Hartig, F.; Müller, J.; Krzystek, P.; Jehl, H.; Dech, S. (2016): Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data. In: Forestry, 89 (1), 69-81.
2015[ to top ]
  • Heurich, M.; Krzystek, P.; Polakowski, F.; Latifi, H.; Krauss, A.; Müller, J. (2015): Erste Waldinventur auf Basis von Lidardaten und digitalen Luftbildern im Nationalpark Bayerischer Wald. In: Forstliche Forschungsberichte München, 2015 (214), 101-3.
  • Latifi, H.; Fassnacht, F. E.; Hartig, F.; Berger, C.; Hernández, J.; Corvalán, P.; Koch, B. (2015): Stratified aboveground forest biomass estimation by remote sensing data. In: International Journal of Applied Earth Observation and Geoinformation, 38, 229-41.
  • Latifi, H.; Fassnacht, F. E.; Müller, J.; Tharani, A.; Dech, S.; Heurich, M. (2015): Forest inventories by LiDAR data: A comparison of single tree segmentation and metric-based methods for inventories of a heterogeneous temperate forest. In: International Journal of Applied Earth Observation and Geoinformation, 162-74.
2014[ to top ]
  • Fassnacht, F.; Hartig, F.; Latifi, H.; Berger, C.; Hernández, J.; Corvalán, P.; Koch, B. (2014): Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass. In: Remote Sensing of Environment, 154, 102-14.
  • Naghavi, H.; Fallah, A.; Shataee, S.; Latifi, H.; Soosani, J.; Ramezani, H.; Conrad, C. (2014): Canopy cover estimation across semi-Mediterranean woodlands: application of high-resolution earth observation data. In: Journal of Applied Remote Sensing, 8 (1), 083524.
  • Wegmann, M.; Santini, L.; Leutner, B.; Safi, K.; Rocchini, D.; Bevanda, M.; Latifi, H.; Dech, S.; Rondinini, C. (2014): Role of African protected areas in maintaining connectivity for large mammals. In: Philosophical Transactions of the Royal Society B: Biological Sciences, 369 (1643)
  • Latifi, H.; Fassnacht, F.; Schumann, B.; Dech, S. (2014): Object-based extraction of bark beetle (Ips typographus L.) infestations using multi-date Landsat and SPOT satellite imagery. In: Progress in Physical Geography, 1–31.
  • Latifi, H.; Schumann, B.; Kautz, M.; Dech, S. (2014): Spatial characterization of bark beetle infestations by a multi-date synergy of SPOT and Landsat imagery. In: Environmental Monitoring and Assessment, 186, 441-56.
  • Fassnacht, F.; Latifi, H.; Ghosh, A.; Joshi, P.; Koch, B. (2014): Assessing the potential of hyperspectral imagery to map bark beetle-induced tree mortality. In: Remote Sensing of the Environment, 140, 533-48.
2012[ to top ]
  • Latifi, H.; Fassnacht, F.; Koch, B. (2012): Forest structure modeling with combined airborne hyperspectral and LiDAR data. In: Remote Sensing of Environment, 121, 10-25.
  • Latifi, H.; Nothdurft, A.; Straub, C.; Koch, B. (2012): Modelling stratified forest attributes using Optical/LiDAR features in a central European landscape. In: International Journal of Digital Earth, 5(2), 106-32.
  • Latifi, H.; Koch, B. (2012): Evaluation of most similar neighbour and random forest methods for imputing forest inventory variables using data from target and auxiliary stands. In: International Journal of Remote Sensing, 33 (21), 6668-94.
  • Fassnacht, F. E.; Latifi, H.; Koch, B. (2012): An angular vegetation index for imaging spectroscopy data. Preliminary results on forest damage detection in the Bavarian National Park, Germany. In: International Journal of Applied Earth Observation and Geoinformation, 19, 308-21.
2010[ to top ]
  • Latifi, H.; Nothdurft, A.; Koch, B. (2010): Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: application of multiple optical/LiDAR-derived predictors. In: Forestry, 83 (4), 395-407.
  • Latifi, H.; Galos, B. (2010): Remote sensing-supported vegetation parameters for regional climate models: a brief review. In: IForest - Biogeosciences and Forestry, (4), 98-101.
2009[ to top ]
  • Sohrabi Saraj, B.; Yachkaschi, A.; Oladi, D.; Fard Teimouri, S.; H, L. (2009): The recreational valuation of a natural forest park using travel cost method in Iran. In: IForest - Biogeosciences and Forestry, (3), 85-92.
2008[ to top ]
  • Fadaei, F.; Fallah, A.; Latifi, H.; Mohammadi, K. (2008): Determining the best form factor formula for Loblolly Pine (Pinus taeda L.) plantations at the age of 18, in Guilan-northern Iran. In: Caspian Journal of Environmental Sciences, 6 (1), 19-24.
2007[ to top ]
  • Latifi, H.; Oladi, D.; Saroei, S.; Jalilvand, H. (2007): An Evaluation of ETM+ Data Capability to Provide "Forest- Shrubland- Range" Map. A Case Study of Neka-Zalemroud, Mazandaran- Iran). In: Journal of Science and Technology of Agriculture and Natural Resources, 11(2), 439-47.
2006[ to top ]
  • Latifi, H.; Oladi, D. (2006): Evaluating Landsat ETM+ Data Capability to Produce Forest Cover type Maps in the Timberline of Northern Forests of Iran. In: Taiwan Journal of Forest Science, 21(3), 363-75.
  • Latifi, H.; Adeli, K. (2006): Forest type mapping using Landsat ETM+ data in southern Zagros. In: Naghsheh Bardari (Surveying), 83, 31-35.
2005[ to top ]
  • Latifi, H.; {Oladi, D. S. (2005): An Introduction to Multi Sensor Data Fusion Techniques and the Application in Satellite Image Analysis.. In: Jangal \& Martaa (Forests and Rangelands), 68\& 69, 26-31.