Above-ground biomass estimation based on NPP time-series ? A novel approach for biomass estimation in semi-arid Kazakhstan |
| |
| Institution: | 1. Department of Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran;2. Department of Plant Sciences and Medicinal Plants, University of Mohaghegh Ardabili, Ardabil, Iran;3. School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada;1. Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China;2. School of Environment, Northeast Normal University, Changchun 130024, China;3. School of Geographical Sciences, Inner Mongolia Normal University, Hohhot 010022, China;4. School of Natural Resource, University of Missouri, Columbia, MO 65211, USA;1. College of Urban and Environmental Science and MOE Laboratory for Earth Surface Processes, Peking University, Beijing, China;2. Geography, College of Life & Environmental Sciences, University of Exeter, Exeter EX4 4RJ, United Kingdom;1. GAMMA Remote Sensing, 3073 Gümligen, Switzerland;2. Max Planck Institute for Biogeochemistry, Hans Knöll Strasse 10, 07745 Jena, Germany;3. South Pole, Digital Innovation, Fred. Roeskestraat 115, Amsterdam, the Netherlands;4. Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal;5. Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, 6708 PB Wageningen, the Netherlands;6. Helmholtz GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing and Geoinformatics, Telegrafenberg, Potsdam 14473, Germany;7. Forest Advanced Computing and Artificial Intelligence Lab, Department of Forestry and Natural Resources, Purdue University, USA;8. University of Zagreb, Faculty of Forestry and Wood Technology, Department of Forest Inventory and Management, Svetosimunska cesta 23, 10000 Zagreb, Croatia;9. European Space Research Institute, European Space Agency, 00044 Frascati, Italy |
| |
| Abstract: | Biomass is a sensitive indicator of environmental change and ecological functioning. Quantification of biomass is essential to identify and monitor those areas threatened by degradation and desertification. This is especially important in arid and semi-arid environments. However, robust techniques to monitor carbon stocks over large areas and through time are still missing. The major objective of the presented study is to develop a novel approach for biomass estimation in semi-arid environments using remote-sensing based Net Primary Productivity (NPP) data.The developed methodical concept aims at derivation of above-ground grass and shrub biomass for natural environments. It is based on NPP time-series and plants’ relative growth rates. Fractional cover data provide information about grass and shrub coverage. The developed approach has been applied to three study areas in Kazakhstan, in which field data were collected for validation.Biomass maps were derived that show the spatial distribution of grass and shrub biomass. Validation revealed a moderate correlation (R = 0.68) with field data for grass biomass. For shrub biomass, a high correlation (R = 0.83) is retrieved when fractional cover information from field observations is used.The presented novel approach for biomass estimation is based on remote sensing derived NPP time-series and is thus potentially transferable in space and time. This is a great advantage compared to commonly applied empirical relationships. The presented concept can be adapted to be applied to other vegetation communities. Providing the necessary data about fractional vegetation cover is available, the method will allow for repeated and large-area biomass estimation for natural semi-arid environments as needed for observing changes in biomass and support sustainable land management. |
| |
| Keywords: | Biomass Fractional cover Net primary productivity Kazakhstan Semi-arid environments Relative growth rates |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
