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Heiko Balzter

Researcher at University of Leicester

Publications -  200
Citations -  6754

Heiko Balzter is an academic researcher from University of Leicester. The author has contributed to research in topics: Vegetation & Land cover. The author has an hindex of 39, co-authored 190 publications receiving 5336 citations. Previous affiliations of Heiko Balzter include University of Giessen.

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The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle

TL;DR: In this article, a P-band polarimetric SAR with interferometric capability is used to measure the magnitude and distribution of forest biomass globally to improve resource assessment, carbon accounting and carbon models, and to monitor and quantify changes in terrestrial forest biomass.
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Cellular automata models for vegetation dynamics

TL;DR: A short review of cellular automata models in ecology is given in this article, where the authors model population dynamics of three plant species on a lawn and compare two STMC models of different order.
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Markov chain models for vegetation dynamics

Heiko Balzter
- 28 Feb 2000 - 
TL;DR: It is concluded that the performance of the model varies between data sets, microdata generate a lower mean square error than aggregated macrodata, and time steps of one year are preferable to three months.
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Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

TL;DR: In this paper, a cellular automata (CA)-Markov chain model was used to predict future land use changes in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq.
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Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments

TL;DR: In this paper, LiDAR-retrieved canopy height and structural data are used to predict the breeding success of Great Tits and Blue Tits in broad-leaved woodland, and so have the potential to forecast the distribution of breeding Sky Larks in a farmed landscape.