Journal ArticleDOI
Synergistic evaluation of Sentinel 1 and 2 for biomass estimation in a tropical forest of India
Ramandeep Kaur M. Malhi,Sultanova Umida Rustamovna,Akash Anand,Prashant K. Srivastava,Sumit Kumar Chaudhary,Manish Kumar Pandey,Mukund Dev Behera,Amit Kumar,Prachi Singh,G. Sandhya Kiran +9 more
TLDR
In this paper, two nonparametric machine learning algorithms viz Support Vector Machines (SVMs) with different kernel functions were employed for the prediction of above ground biomass using different combinations of VV, VH, Normalized Difference Vegetation Index (NDVI) and Incidence Angle (IA).About:
This article is published in Advances in Space Research.The article was published on 2021-04-08. It has received 18 citations till now. The article focuses on the topics: Normalized Difference Vegetation Index & Random forest.read more
Citations
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Journal ArticleDOI
Moderate resolution LAI prediction using Sentinel-2 satellite data and indirect field measurements in Sikkim Himalaya
S. D. Mudi,Somnath Paramanik,Mukunda Dev Behera,A. Prakash,Nikhil Raj Deep,Manish Kale,Shubham Kumar,Narpati Sharma,Prerna Pradhan,Manoj Eknath Chavan,P. Roy,D. G. Shrestha +11 more
Assessing the niche of Rhododendron arboreum using entropy and machine learning algorithms: role of atmospheric, ecological, and hydrological variables
Akash Anand,Prashant K. Srivastava,Prem Chandra Pandey,Mohammed Latif Khan,Mukunda Dev Behera +4 more
TL;DR: In this article , four machine learning and regression-based algorithms, namely, generalized linear model, maximum entropy, boosted regression tree, and random forest (RF) are used to model the geographical distribution of Rhododendron arboreum, which is economically and medicinally important species found in the fragile ecosystem of Himalayas.
AVIRIS-NG hyperspectral data for biomass modeling: from ground plot selection to forest species recognition
TL;DR: In this paper , an airborne hyperspectral data of airborne visible infrared imaging spectrometer-next generation data was demonstrated to estimate above ground biomass (AGB) of a tropical dry deciduous forest.
Journal ArticleDOI
Spectral Mixture Analysis Of Aviris-Ng Data For Grouping Plant Functional Types
Ramandeep Kaur M. Malhi,G. Sandhya Kirana,Prashant K. Srivastava,Bimal K.Bhattacharya,Agradeep Mohanta +4 more
TL;DR: In this article , the spectral mixture analysis was applied to identify and map plant functional types (PFTs) in the AVIRIS-NG campaign site, namely Shoolpaneshwar Wildlife Sanctuary (site id 67), using AVIRis-NG data combined with spectral mixture analyses that accounts for endmember variability.
References
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Book
Pattern Recognition and Machine Learning
TL;DR: Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.
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Classification and Regression Trees.
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C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
TL;DR: In this paper, the authors describe the important ideas in these areas in a common conceptual framework, and the emphasis is on concepts rather than mathematics, with a liberal use of color graphics.
Journal ArticleDOI
Tree allometry and improved estimation of carbon stocks and balance in tropical forests
Jérôme Chave,C. Andalo,Sandra Brown,Michael A. Cairns,Jeffrey Q. Chambers,Derek Eamus,H. Fölster,François Fromard,Niro Higuchi,T. Kira,J. P. Lescure,Bruce Walker Nelson,H. Ogawa,H. Puig,B. Riera,Takuo Yamakura +15 more
TL;DR: A critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ≥ 5 cm diameter, directly harvested in 27 study sites across the tropics, is provided.