Author: Hooman Latifi

New publication: Mapping oak dieback severity using Worldview-2 data

A new paper published by Iranian Journal of Forest and Poplar Research presents novel results on comparative analysis of multiple approaches for mapping Persian Oak (Quercus brantii) dieback across a portion of Zagros forests of Iran. The research features Hooman Latifi from University of Würzburg  and uses very-high-resolution optical data from Worldview-2 together with design-based inventory of oak dieback. The results revealed that the artificial neural network comparatively better performed than other classification methods with its overall accuracy of 72.83%. Moreover, our results confirmed that the Worldview-2 satellite data can illustrate the severity of oak decline as well as its spatial extension. An English summary of the work can be retrieved here. 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). Iranian Journal of Forest and Poplar Research 25(3), 452-462. DOI:...

Read More

M.Sc thesis: Deciduous forest parameter retrieval using polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) and LIDAR approaches

Earth observation methods have been important tools for forest management applications for several decades. Nevertheless, it is necessary to improve existing processes on the local and regional scales, in particular for retrieving biophysical forest attributes. TanDEM-X data with high spatial resolution are predestinated information sources for precise estimation of forest parameters such as tree height and aboveground biomass. Once the tree-scale estimates are validated across relevant forest types (e.g. deciduous forests, coniferous or mixed), these can be extrapolated to larger plot, watershed, regional or even national scales. The utilization of three-dimensional remote sensing data sources like TanDEM-X and LIDAR...

Read More

New publication: Influential factors on the quality of LiDAR-based Digital Terrain Models across temperate forest sites

A recently published paper featuring Hooman Latifi from Dept. of Remote Sensing presents a method comparison combined with a statistical analysis on the Impact of terrain topograpghy and habitat types on LiDAR-derived Digital Terrain Models in temperate Forest sites. The study addresses essential questions raised by how data and site-driven factors such as spatial resolution, topography  and variation in forest habitat types  might affect the DTM accuracy. These factors can also play a more pronounced role added by processing steps like ground filtering and interpolation of ground points. The results of a factorial analysis as ewll as a thorough...

Read More

Extended deadline for abstract submission to IBS-DR workshop 2017

The deadline for abstract submission to joint IBS-DR  (German Region of the International Biometric Society) and DVFFA (Gerrman Association of Forest Research Institutions) in Hannover was extended to the end of September 2017. The workshop will be held from 7th to 8th of December 2017. The aim of the workshop is to provide a space for presentations and discussions of recent developments in spatial modeling and Bayesian methodology. Methods and applications in answering environmental, ecological, epidemiological or other research questions will be discussed. We welcome contributions on both interesting applications and methodological work. The workshop will host Dr. Cornelia...

Read More

New publication: vegetation response to environmental variables in the mountainous forests of Western Himalaya

A recently published paper featuring Hooman Latifi and Thorsten Dahms from Dept. of Remote Sensing presents novel results on phenological behaviour of the moist deciduous forests Hymalayan foothills in India during 2013–2015 using Landsat 8 time series data. The paper has been published in International Journal of Remote Sensing, and additionally suggests a new vegetation index called the temporal normalized phenology index (TNPI) to quantify the change in trajectories of Landsat 8 OLIderived normalized difference vegetation index (NDVI) during two time steps of the vegetation growth cycle.     Based on cross-validated statistics the paper concludes that  TNPI is...

Read More

news blog by

the Remote Sensing Department
at the University of Würzburg
Institute of Geography and Geology
Oswald Külpe Weg 86
97074 Würzburg

University Webpage

Recent Tweets