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
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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
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Effect of vegetation structure on above ground biomass in tropical deciduous forests of Central India
Preet Lal,Amit Kumar,Purabi Saikia,Anup Das,C. Patnaik,Gajendra Kumar,Arvind Chandra Pandey,Parul Srivastava,Chandra Shekhar Dwivedi,Mohammed Latif Khan +9 more
TL;DR: In this article, the above ground biomass (AGB) of tropical deciduous forests in Central India using field-based techniques and spaceborne quad-pol ALOS PALSAR-2 L-band and dual-pol Sen...
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Monitoring landscape fragmentation and aboveground biomass estimation in Can Gio Mangrove Biosphere Reserve over the past 20 years
TL;DR: In this article , the temporal and spatial changes of landscape pattern of land use/land cover (LULC) over the past 20 years in Can Gio Mangrove Biosphere Reserve (MBR), southern Vietnam were analyzed based on remote sensing data.
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Remote sensing-based biomass estimation of dry deciduous tropical forest using machine learning and ensemble analysis.
TL;DR: In this article , the authors proposed a framework to monitor above-ground biomass (AGB) at finer scales using open-source satellite data, which integrated four machine learning (ML) techniques with field surveys and satellite data to provide continuous spatial estimates of AGB at finer resolution.
Journal ArticleDOI
Optimal band characterization in reformation of hyperspectral indices for species diversity estimation
Akash Anand,Sultanova Umida Rustamovna,Ramandeep Kaur M. Malhi,Prashant K. Srivastava,Prachi Singh,Ashwini N. Mudaliar,George P. Petropoulos,G. Sandhya Kiran +7 more
TL;DR: In this article, the authors provided modified hyperspectral indices through detection of optimum bands for estimating species diversity within Shoolpaneshwar Wildlife Sanctuary (SWS) in India.
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Estimating Individual Tree Above-Ground Biomass of Chinese Fir Plantation: Exploring the Combination of Multi-Dimensional Features from UAV Oblique Photos
TL;DR: Wang et al. as discussed by the authors proposed an approach to estimate IT-AGB by introducing the color space intensity information into a regression-based model that incorporates three-dimensional point cloud and two-dimensional spectrum feature variables, and the accuracy was evaluated using a leave-one-out cross-validation approach.
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Journal ArticleDOI
Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest-savanna boundary region of central Africa using multi-temporal L-band radar backscatter
Edward T. A. Mitchard,Sassan Saatchi,Simon L. Lewis,Ted R. Feldpausch,Iain Woodhouse,Bonaventure Sonké,Clare S. Rowland,Patrick Meir +7 more
TL;DR: In this paper, the relationship between the radar backscatter and aboveground biomass (AGB) was found to be strong and the root mean square error (RMSE) associated with AGB estimation varied from ~ 25% for AGB 100 Mg ha− 1 for the ALOS HV data.
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Biomass estimations and carbon stock calculations in the oil palm plantations of African derived savannas using IKONOS data
Prasad S. Thenkabail,Nicholas L. Stucky,Bronson W. Griscom,Mark S. Ashton,J. Diels,B. van der Meer,Eden A Enclona +6 more
TL;DR: In this paper, the authors developed biomass models to calculate carbon stock levels of the West African oil palms (Elaeis guineensis) using multi-date wet and dry season IKONOS images.
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Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR
Jose Gonzalez de Tanago,Jose Gonzalez de Tanago,Alvaro Lau,Alvaro Lau,Harm Bartholomeus,Martin Herold,Valerio Avitabile,Pasi Raumonen,Christopher Martius,Rosa C. Goodman,Mathias Disney,Mathias Disney,Solichin Manuri,Andrew Burt,Kim Calders,Kim Calders +15 more
TL;DR: In this article, the authors proposed a method to estimate AGB of large tropical trees by 3D tree modeling of TLS point clouds, which can account for individual tree biophysical structure more effectively than allometric models.
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Estimating aboveground carbon in a catchment of the Siberian forest tundra: Combining satellite imagery and field inventory
TL;DR: In this paper, the authors combined multispectral high-resolution remote sensing imagery and sample based field inventory data by means of the k -nearest neighbor (k-NN) technique and linear regression.
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Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa)
TL;DR: In this paper, the authors compared a semi-empirical and machine learning algorithm, with the latter based on bagging stochastic gradient boosting (BagSGB), for retrieving the AGB of woody vegetation thereby supporting estimation of national carbon stocks.