Prediction of aboveground grassland biomass on the Loess Plateau, China, using a random forest algorithm
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Lei Deng | Wenyi Sun | Kaibo Wang | Lei Deng | Zhuangsheng Tang | Z. Shangguan | Wenyi Sun | Yinyin Wang | Gaolin Wu | Zhuangsheng Tang | Zhouping Shangguan | Kaibo Wang | Gaolin Wu | Yinyin Wang
[1] Q. Wang,et al. A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China , 2019, Journal of Mountain Science.
[2] M. Boschetti,et al. Assessment of pasture production in the Italian Alps using spectrometric and remote sensing information , 2007 .
[3] Ping Wang,et al. The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues , 2013, Int. J. Appl. Earth Obs. Geoinformation.
[4] D. Flanagan,et al. Spatial distribution and temporal trends of extreme temperature and precipitation events on the Loess Plateau of China during 1961–2007 , 2010 .
[5] Ho Tong Minh Dinh,et al. Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data , 2016, Int. J. Appl. Earth Obs. Geoinformation.
[6] N. Keenlyside,et al. Optimising assimilation of hydrographic profiles into isopycnal ocean models with ensemble data assimilation , 2017 .
[7] Kelly K. Caylor,et al. On soil moisture–vegetation feedbacks and their possible effects on the dynamics of dryland ecosystems , 2007 .
[8] Kelly K. Caylor,et al. An ecohydrological approach to predicting hillslope‐scale vegetation patterns in dryland ecosystems , 2012 .
[9] Nancy F. Glenn,et al. Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass , 2016 .
[10] Min Liu,et al. Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches , 2016 .
[11] J. A. Schell,et al. Monitoring vegetation systems in the great plains with ERTS , 1973 .
[12] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[13] W. Hong. RESEARCH ADVANCES OF VEGETATION EFFECT ON SOIL AND WATER CONSERVATION IN CHINA , 2002 .
[14] Michele Meroni,et al. Revisiting the concept of a symmetric index of agreement for continuous datasets , 2016, Scientific Reports.
[15] E. Vivoni,et al. Forest ecohydrological response to bimodal precipitation during contrasting winter to summer transitions , 2014 .
[16] F. Baret,et al. Assessing the biomass dynamics of Andean bofedal and totora high-protein wetland grasses from NOAA/AVHRR , 2003 .
[17] Y. Lü,et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits , 2016 .
[18] Hongjie Xie,et al. Multi-factor modeling of above-ground biomass in alpine grassland: A case study in the Three-River Headwaters Region, China , 2016 .
[19] F. Zhang,et al. Runoff and soil loss characteristics on loess slopes covered with aeolian sand layers of different thicknesses under simulated rainfall , 2017 .
[20] Lei Deng,et al. Species Composition, Richness and Aboveground Biomass of Natural Grassland in Hilly-Gully Regions of the Loess Plateau, China , 2014 .
[21] Li Wang,et al. Effects of vegetation and slope aspect on water budget in the hill and gully region of the Loess Pla , 2011 .
[22] Saurabh Das,et al. A random forest algorithm for nowcasting of intense precipitation events , 2017 .
[23] Gwangseob Kim,et al. Space-time characterization of soil moisture from passive microwave remotely sensed imagery and ancillary data , 2002 .
[24] Robin P. White,et al. Pilot analysis of global ecosystems: grassland ecosystems. , 2000 .
[25] Andrew K. Skidmore,et al. Estimation of grassland biomass and nitrogen using MERIS data , 2012, Int. J. Appl. Earth Obs. Geoinformation.
[26] Ronghua Ma,et al. Modeling grassland aboveground biomass using a pure vegetation index , 2016 .
[27] L. 't Mannetje,et al. Grasslands of the world , 2006 .
[28] R. Crabtree,et al. Hyperspectral One-Meter-Resolution Remote Sensing in Yellowstone National Park, Wyoming: I. Forage Nutritional Values , 2005 .
[29] B. Hodson,et al. The effect of passage in vitro and in vivo on the properties of murine fibrosarcomas. II. Sensitivity to cell-mediated cytotoxicity in vitro. , 1985, British Journal of Cancer.
[30] Xinhua He,et al. Balancing green and grain trade , 2015 .
[31] Jordi Cristóbal,et al. Estimating above-ground biomass on mountain meadows and pastures through remote sensing , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[32] O. Mutanga,et al. Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas , 2015 .
[33] Bin Xu,et al. Remote Sensing-Based Biomass Estimation and Its Spatio-Temporal Variations in Temperate Grassland, Northern China , 2014, Remote. Sens..
[34] Thomas Alexandridis,et al. Data assimilation of satellite-based actual evapotranspiration in a distributed hydrological model of a controlled water system , 2017, Int. J. Appl. Earth Obs. Geoinformation.
[35] A. Porporato,et al. Interplay of climate seasonality and soil moisture‐rainfall feedback , 2014 .
[36] T. Jackson,et al. Field observations of soil moisture variability across scales , 2008 .
[37] Jing Wang,et al. Estimating near future regional corn yields by integrating multi-source observations into a crop growth model , 2013 .
[38] S. E. Haupt,et al. Short-term wind forecast of a data assimilation/weather forecasting system with wind turbine anemometer measurement assimilation , 2017 .
[39] Panteleimon Xofis,et al. Factors affecting distribution of vegetation types on abandoned cropland in the hilly-gullied Loess Plateau region of China , 2008 .
[40] Qi Jing,et al. Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data , 2016, Int. J. Appl. Earth Obs. Geoinformation.
[41] Jack E. Norland,et al. Hyperspectral One-Meter-Resolution Remote Sensing in Yellowstone National Park, Wyoming: II. Biomass , 2005 .
[42] O. Mutanga,et al. Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa , 2015 .
[43] Terje Gobakken,et al. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision , 2016 .
[44] O. Sala. Grassland Ecosystems , 2012 .
[45] Maosheng Zhao,et al. Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.
[46] Long-qi Sun,et al. Effects of incorporated plant litter on soil resistance to flowing water erosion in the Loess Plateau of China , 2016 .
[47] J. Morrison,et al. Distribution mapping of world grassland types , 2014 .
[48] Mingyue Zhao,et al. Spatial Heterogeneity of Soil Moisture and the Scale Variability of Its Influencing Factors: A Case Study in the Loess Plateau of China , 2013 .
[49] Saguna Saguna,et al. Applied machine learning: Forecasting heat load in district heating system , 2016 .
[50] Rui Guo,et al. Spatial and Temporal Variability of Annual Precipitation during 1958-2007 in Loess Plateau, China , 2010, CCTA.
[51] Zhuo Feng,et al. The effects of N and P additions on microbial N transformations and biomass on saline-alkaline grassland of Loess Plateau of Northern China , 2014 .