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Improving the Accuracy of Vegetation Index Retrieval for Biomass by Combining Ground-UAV Hyperspectral Data-A New Method for Inner Mongolia typical grasslands

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Phyton-International Journal of Experimental Botany 2024年第2期93卷 387-411页

作者： Ruochen Wang Jianjun Dong Lishan Jin Yuyan Sun Taogetao Baoyin Xiumei Wang The College of Resources and Environmental Engineering Inner Mongolia University of TechnologyHohhot010000China The College of Ecology and Environment Inner Mongolia UniversityHohhot010000China Key Laboratory of Environmental Pollution Control and Remediation at Universities of Inner Mongolia Autonomous Region Inner Mongolia University of TechnologyHohhot010000China

grassland biomass is an important parameter of grassland *** complexity of the grassland canopy vegetation spectrum makes the long-term assessment of grassland growth a *** studies have explored the original spectral information of typical grasslands in Inner Mongolia and examined the influence of spectral information on aboveground biomass(AGB)*** order to improve the accuracy of vegetation index inversion of grassland AGB,this study combined ground and Unmanned Aerial Vehicle(UAV)remote sensing technology and screened sensitive bands through ground hyperspectral data transformation and correlation *** narrow band vegetation indices were calculated,and ground and airborne hyperspectral inversion models were ***,the accuracy of the model was *** results showed that:(1)The vegetation indices constructed based on the ASD FieldSpec 4 and the UAV were significantly correlated with the dry and fresh weight of AGB.(2)The comparison between measured R^(2) with the prediction R^(2) indicated that the accuracy of the model was the best when using the Soil-Adjusted Vegetation Index(SAVI)as the independent variable in the analysis of AGB(fresh weight/dry weight)and four narrow-band vegetation *** SAVI vegetation index showed better applicability for biomass monitoring in typical grassland areas of Inner Mongolia.(3)The obtained ground and airborne hyperspectral data with the optimal vegetation index suggested that the dry weight of AGB has the best fitting effect with airborne hyperspectral data,where y=17.962e^(4.672x),the fitting R^(2) was 0.542,the prediction R^(2)was 0.424,and RMSE and REE were 57.03 and 0.65,***,established vegetation indices by screening sensitive bands through hyperspectral feature analysis can significantly improve the inversion accuracy of typical grassland biomass in Inner *** with ground monitoring,airborne hyperspectral monitoring better reflec

关键词： Aboveground biomass inversion model vegetation index unmanned aerial vehicle typical grassland

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Environmental filtering does not necessarily prevent trait divergence: a case study of the Xilin River Basin in Inner Mongolia, China

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Journal of Plant Ecology 2017年第3期10卷 497-509页

作者： Saruul Kang Jianming Niu Qing Zhang Dan Li Haijuan Ren Jing Ren Xuefeng Zhang Jianjun Dong School of Life Sciences Inner Mongolia University235 University West RoadHohhot 010021China Sino-US Center for Conservation Energyand Sustainability ScienceInner Mongolia University235 University West RoadHohhot 010021China

Aims Understanding how environmental factors and human activity drive plant community assembly remains a major challenge in community *** opposing processes,namely determinis-tic environmental filtering and nondeterministic elements such as interspecies competition,can be quantified by analyzing trait distri-butions in the community-assembly *** We examined the trait-mediated effects of environmental filtering and stochastic process and the distribution over time of nine traits related to vegetative growth,regenerative phase,dispersal capability,decom-position and interspecific competition in plant communities along a degradation gradient in the Xilin River Basin,Inner Mongolia,*** analyzed the turnover of environmental trait filtering and the diver-gence/convergence of different traits along the degradation *** Findings Our results showed the following.(i)The patterns of trait distribu-tion and filtering were strongly dependent upon the degradation gradient and trait *** traits were filtered intensely in degraded grasslands.(ii)Plants with two different strategies showed contrasting trait-distribution *** traits that were related to biological matter cycling showed divergent pat-terns in highly degraded grasslands,while convergent patterns along the overall gradient were demonstrated in traits associated with other plant *** suggests that the coexistence of multiple‘biological matter cycling-related niches’might be a basic structuring pattern of plant communities in our study area.(iii)The simultaneous occurrence of strong filtering and diver-gence revealed that environmental filtering does not necessar-ily prevent competition,and that different traits show different signatures.

关键词： community assembly convergence degradation grazing intensity plant traits typical grassland

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Soil Respiration Dynamics and Influencing Factors in typical Steppe of Inner Mongolia under Long-term Nitrogen Addition

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Journal of Resources and Ecology 2019年第2期10卷 155-162页

作者： DU Wei WU Shanmei NIE Cheng LI Yue SHAO Rui LIU Yinghui SUN Nan State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical Science Beijing Normal University Beijing 100875China Department of Geography Ghent University Ghent 9000 Belgium Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences/National Engineering Laboratory for Improving Quality of Arable Land Beijing 100081 China

We investigated soil respiration(Rs)dynamics and influencing factors under different nitrogen(N)addition levels(0,2,4,8,16,32 g m^–2 yr^–1)on typical grassland plots in Inner *** measured soil respiration,temperature,moisture and *** found that N addition did not change dynamic characteristics of Rs;daily and seasonal dynamics followed a single peak curve.N addition reduced Rs during the growing *** under N2,N4,N8,N16 and N32 treatments decreased by 24.00%,21.93%,23.49%,30.78%and 28.20%in the growing season,respectively,compared to the N0 ***,Rs in the non-growing season was not different across *** was significantly positively correlated with soil temperature and moisture and these two factors accounted for 72%–97% and 74%–82% of variation in Rs,*** soil respiration temperature sensitivity (Q10) was between 2.27 and 4.16 and N addition reduced Q10 except in the N8 treatment.

关键词： soil respiration nitrogen addition soil temperature and moisture soil nutrients typical grassland

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