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

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

A recently publisher 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.

 

Mean NDVI values from April 2014 to June 2015 plotted for study site along with SAL tree
phenology.

 

Based on cross-validated statistics the paper concludes that  TNPI is a superior alternative for the analysis of temporal phenology cycle between two time steps of maximum and minimum vegetation growth periods. This could, in turn, reduce the requirement of large time-series remote-sensing data sets for studies on long-term vegetation phenology. The paper can be retrieved here.

Bibliography:

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. International Journal of Remote Sensing 38(15), 4418-4442.

Best practice tutorial on handling low-budget UAV finished

Best practice tutorial on handling low-budget UAV finished

Following the purchase and operaration of our two low-budget UAVs suring 2016 and 2017, a best practice tutorial of how to use the devices was written by Marius Röder, Steven Hill and Hooman Latifi, and it is now available in two English and German versions. This tutorial assumes no prior knowledge of the reader on handling low-budget Unmanned Aerial Vehicles in ecological and environmental contexts. It initially includes general infos on preperation and constellation of a typical UAV system, followed by instructions on planning and implementation of UAV flights using the available commercial software, importing the acquired imagery, relative orientation, optimization of camera parameters, generation of dense point clouds and finally digital surface modeling of the point clouds. The tutorial eventually includes lessons learned, tipps and tricks on further processing and potential applications of the UAV topographic products.
The tutorial can be retrieved here on Research Gate.

new PhD student Anudari Batsaikhan

new PhD student Anudari Batsaikhan

Anudari_Batsaikhan_remote-sensing_euAnudari Batsaikhan studied in Germany and Austria during her Master’s degree program and completed her degree in Cartography in 2015. At the Dept. of Remote Sensing, she works on her PhD project with the title of “Climatic impacts on phenology of grassland along a transect through altitudinal zones using remote sensing” in corporation with DLR (Dr. Doris Klein) and EURAC (Dr. Sarah Asam), supported by MICMoR where she is a fellow. With her PhD project, she aims to provide better understanding of grassland phenology in relation to its driving factors in the Alps and model grassland phenology through remote sensing.

Impressions from Phenology 2015 conference

Impressions from Phenology 2015 conference

From 5 – 8 October 2015, the 3rd international conference on Phenology was held at Kusadasi/Turkey. It was jointly hosted by the Humboldt-University of Berlin and the Adnan Menderes University Aydin. 86 contributions from scientists of 23 countries were presented on the topics “Phenological observations, networks, data collection”, “Climate variablilty, change and trends”, “Phenological modelling”, and “Challenges, new approaches and progress”.
Within the session “Remote Sensing and Phenology”, Carina Kübert presented ongoing work of her PhD thesis on “Deriving phenological layers for Germany from remote sensing data: spatio-temporal analysis and validity”. One of our MSc students, Jeroen Staab, co-authered a presentation given by our former colleague Sarah Asam (now EURAC, Italy), showing first results of phenological monitoring for the entire Alps. Jeroen helped to derive phenological metrics during his internship at EURAC.

More details in the programme and abstract book (published by the German Meteorological Service (DWD)) which can be downloaded from the conference homepage

More details can also be found on twitter using the hashtags: #phenology #phenology2015

New RapidEye datasets granted from RESA platform of DLR/Black Bridge

New RapidEye datasets granted from RESA platform of DLR/Black Bridge

The Dept. of Remote Sensing recently applied for a time series of 12 RapidEye scenes to support a PhD thesis by Siddhartha Khare (Indian Institute of Technology Roorkee, India). The proposal is now accepted, and th PhD work will be supported by a dense time series of RapidEye scenes acquired in 2013 over dry forests in Lesser Himalayan region of India.

The PhD thesis which will use these processed datasets is entitled  “Object Based approaches for remote sensing-assisted assessment of forest biodiversity focusing on invasive species”, supervised and advised by Prof. S.K. Ghosh (IIT Roorkee) and Dr. Hooman Latifi (University of Würzburg). Additional multisource datasets to be used within the work include time series of Landsat 8 data and Cartosat 2-derived terrain model.

RESA already published this project in RESA project map 2015 which can be found online HERE. The project area is flagged under No. 120 (project number 184) in the map.

resa_india

New RapidEye datasets granted from RESA platform of DLR/Black Bridge

The Department of Remote Sensing recently applied for a time series of RapidEye scenes to support a PhD thesis by Christian Bauer (Dep. of Remote Sensing, Würzburg) in the context of the project LaVaCCA. The proposal has recently been accepted, and the PhD work of Christian Bauer will be supported by a time series of RapidEye scenes acquired over two irrigated landscapes, Khorezm and Elliqkala, in Uzbekistan.