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
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.
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.
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.
Schematic representation of plant diversity estimaiton by remote sensing approach
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.
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
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).
Directional area scattering factor (DASF) calculated based on spectral invariant theory for broadleaf, needle leaf, and mixed forest
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.
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.
Via an official proposal submitted to the ESA, multispectral and stereo panchromatic SPOT 6/7 and Pleiades scenes were achieved over a portion of dry deciduous western Hymalayan region of India. The data delivery include three multispectral SPOT 6, two multispectral SPOT 7, two multispectral Pleiades, two stereo panchromatic SPOT 6 and one stereo panchromatic SPOT 7 scenes. The total value of the granted scenes amounts to ca. 3100 EUR.
Stereo Pair Images and Multi-temporal multi spectral data of SPOT 6/7 (1.5 m spatial resolution)
The data has been granted and is currently being aplied under the project running title “Object Based approaches for remote sensing-assisted assessment of forest biodiversity focusing on plant species diversity and forest structural parameters”. The project serves as a part of the PhD work of Siddhartha Khare (Indian Institute of Technology Roorkee) supervised by Prof. S.K. Ghosh and Dr. Hooman Latifi from University of Würzburg.
On April 19 2016 Benewinde Jean-Bosco Zoungrana successfully defended his PhD “Vegetation cover response under rainfall variability and land use/cover change in the southwest of Burkina Faso” dealing with remote sensing for land cover and vegetation mapping in West Africa at the Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana– congratulations! Jean-Bosco is a member of the graduate school “Land use and climate change in West Africa” at KNUST. He visited our department during his Phd two times, altogether he stayed for 6 months. Dr. Michael Thiel was his mentor in Germany.
Dr. Zoungrana conducted an excellent research, out of which he already published two scientific papers. The third manuscript is almost ready for submission.
Anudari 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.