Author: Hooman Latifi

New publication: Remote sensing solutions for monitoring species diversity as affected by invasive plants

A new published work featuring Hooman Latifi from Dept. of Remote Sensing and Siddhartha Khare from Indian Institute of Technology Roorkee presents a full remote sensing-based approach to assess the vegetation diversity across the areas affected and invaded by Lantana camara, an invasive plant species. The study comprises two main steps  utilizing  multi-source satellite earth observation data. The process starts with a supervised classification applied on ery high spatial resolution Pléiades 1A data, and continues with comparing Pléiades 1A, RapidEye and Landsat-8 OLI – assessed plant species diversities. With detailed mathematical formulation combined with an straightforward methodology solely based on optical remote sensing data, the study is expected to add a new baseline to the existing studies on solutions for remote and rapid estimation of biodiversity attributes in mountaineuous forest areas. Further informaiton on the published paper can be retrieved here. Bibliography: Khare, S., Latifi, H., Ghosh, S.K., 2017. Multi-scale assessment of invasive plant species diversity using Pléiades 1A, RapidEye and Landsat-8 data. Geocarto International . DOI: 10.1080/10106049.2017.1289562...

Read More

New publication: Further progress in model-based estimation of forest understorey by LiDAR data

In a recently-published paper in Forestry featuring Hooman Latifi, Steven Hill and Stefan Dech from the Dept. of Remote Sensing, further advancements have been reported in developing unbiased statistical models for area-based estimation of forest understorey layers using LiDAR point cloud information. The study leveraged an original high-density LiDAR point cloud, which was further processed to simulate two lower-density datasets by applying a thining approach. The data were then combnined with three statistical modeling approaches to estimate the proportions of shrub, herb and moss layers in temperate forest stands in southeastern Germany.   Despite the differences between our simulated data and the real-world LiDAR point clouds of different point densities, the results of this study are thought to mostly reflect how LiDAR and forest habitat data can be combined for deriving ecologically relevant information on temperate forest understorey vegetation layers. This, in turn, increases the applicability of prediction results for overarching aims such as forest and wildlife management. Further informaiton on the published paper can be retrieved here. Bibliography: 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. Forestry, DOI:10.1093/forestry/cpw066...

Read More

New publication: LiDAR-based simulation of tree-and stand development after bark beetle disturbances

In a newly-published paper featuring Steven Hill and Hooman Latifi from Dept. of Remote Sensing, very high resolution remote sensing (laser scanner data and aerial orthophotos) were used in a full remote sensing-based framework to study post-disturbance tree and stand development, particularly in its early seral stages.   The first step involved extraction of single trees and their allometric attributes form LiDAR-based canopy height models, after which the extracted tree locations were additionally validated by a sample based scheme implemented on aerial photos. The single tree based forest  growth simulator SILVA ver. 2.2 was then used to simulate the stand development during a 80 year simulation period. In addition, landscape and spatial point pattern metrics were calculated to assess the structural heterogeneity. The results approve that natural regeneration of post disturbed forest  stands reveal structural heterogeneity even at the early-seral stages. Furthermore, the study showed that the structural heterogeneity might already be determined in the early successional stages. following the bark beetle disturbances. This study open up interesting horizons in how remote sensing data and methods can be combined with spatial statistics to investigate early-phase forest dynamics in natural stands. Further information on the published material can be found here. Bibliography: 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. Ecological Informatics 38, 12-25....

Read More

Invited talk @ ForBioSensing conference

Dr. Hooman Latifi from the Dept. of Remote Sensing held an invited speech on “Remote sensing-assisted mapping of bark beetle-induced tree mortality” at the first conference on comprehensive monitoring of stand dynamics in Białowieża forest supported by remote sensing (ForBioSensing) in Białowieża, Poland, from November 30th to December 2nd, 2016. The conference also hosted different generations and forestry-related disciplines from Polish and international research institutions. The ForBioSensing is a project funded by the LIFE program of the European Union, and its activities are focused on providing a comprehensive illustration of changes in forest stands and their dynamics (by using of several different time series of remote sensing data) and moving from the point scale monitoring (field measurements on sample plots) to the large scale area monitoring....

Read More

New Publication: Canopy structure-corrected retrieval of foliar nitrogen by hyperspectral data

A new review paper has been recently published by International Journal of Applied Earth Observation and Geoinformation. The paper is amongst the outputs of a PhD thesis by Zhihui Wang from the University of Twente, and focuses on retrieval of forest canopy foliar nitrogen from hyperspectral imagery by additionally correcting for canopy structure effects. Te main research question arose from the fact that the interaction between leaf properties and canopy structure confounds the estimation of foliar nitrogen, which can be corrected for by using the canopy scattering coefficient (the ratio of BRF and the directional area scattering factor, DASF).   The results of the research conducted across the Bavarian Forest National Park confirm that %N can be retrieved using the scattering coefficient aftercorrecting for canopy structural effect. With the aid of  upcoming space-borne hyperspectral imagery, large-scale foliar nitrogen maps can be generated to improve the modeling ofecosystem processes as well as ecosystem-climate feedbacks. Further information on this paper can be found here. Source: Wang, Z., Skidmore, A. K., Wang, T., Darvishzadeh, R., Heiden, U., Heurich, M., Latifi, H., Hearne, J. 2016. Canopy foliar nitrogen retrieved from airborne hyperspectral imagery by correcting for canopy structure effects. International Journal of Applied Earth Observation and Geoinformation 54(2017): 84-94....

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