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Integrating Multi-Source Remote Sensing to Assess Forest Aboveground Biomass in the Khingan Mountains of North-Eastern China Using Machine-Learning Algorithms

Xiaoyi Wang, Caixia Liu, Guanting Lv, Jinfeng Xu, Guishan Cui
2022 Remote Sensing  
The datasets used were obtained from the LiDAR-based Geoscience Laser Altimeter System onboard the Ice, Cloud, and land Elevation satellite (ICESat/GLAS), the optical-based Moderate Resolution Imaging  ...  Spectroradiometer (MODIS), and the SAR-based Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR).  ...  Acknowledgments: The authors would like to thank the National Snow and Ice Data Center for the free use of Geoscience Laser Altimeter System (GLAS) data, the Consortium for Spatial Information for distributing  ... 
doi:10.3390/rs14041039 fatcat:gefgbi4hsbdkzjamhvtu4tsuje

Tropical Forest Remote Sensing Services for the Democratic Republic of Congo inside the EU FP7 ReCover Project (Final Results 2000-2012)

J. Haarpaintner, D. de la Fuente Blanco, F. Enßle, P. Datta, A. Mazinga, C. Singa, L. Mane
2015 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
/non-forest maps, a multi-sensor forest change map (2000-2010) and a biomass map (based on 2003-2009 ICESat GLAS) o he user of he De ocr ic Repub ic of Congo DRC), he Observatoir Satellitale des Forê s  ...  of ground reference data collected in March 2013 for classification training.  ...  Satellite data has been provided through a GSC-DA grant from ESA and JAXA, Landsat from USGS and ICESat GLAS from NSIDC.  ... 
doi:10.5194/isprsarchives-xl-7-w3-397-2015 fatcat:3laf6nmccfdsjflzkycsln43ii

Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana

Ibrahim Fayad, Nicolas Baghdadi, Valery Gond, Jean-Stephane Bailly, Nicolas Barbier, Mahmoud El Hajj, Frederic Fabre
2014 2014 IEEE Geoscience and Remote Sensing Symposium  
Next, a Random Forest (RF) classifier was used to analyze the coupling potential of GLAS and SRTM in the discrimination of forest landscape types in French Guiana.  ...  Discrimination of the five forest landscape types in French Guiana was possible, with an overall classification accuracy of 81.3% and a kappa coefficient of 0.75.  ...  Acknowledgments The authors wish to thank the National Snow and Ice Data Center (NSDIC) for the distribution of the ICESat/GLAS data.  ... 
doi:10.1109/igarss.2014.6946866 dblp:conf/igarss/FayadBGBBHF14 fatcat:yl3l5ykdk5fpbnuhj4xjxkymxy

Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana

I. Fayad, N. Baghdadi, V. Gond, J.S. Bailly, N. Barbier, M. El Hajj, F. Fabre
2014 International Journal of Applied Earth Observation and Geoinformation  
Next, a Random Forest (RF) classifier was used to analyze the coupling potential of GLAS and SRTM in the discrimination of forest landscape types in French Guiana.  ...  Discrimination of the five forest landscape types in French Guiana was possible, with an overall classification accuracy of 81.3% and a kappa coefficient of 0.75.  ...  Acknowledgments The authors wish to thank the National Snow and Ice Data Center (NSDIC) for the distribution of the ICESat/GLAS data.  ... 
doi:10.1016/j.jag.2014.04.005 fatcat:xo4vhuj5zncormeybr4lrhwwsq

Light detection and ranging and hyperspectral data for estimation of forest biomass: a review

Qixia Man, Pinliang Dong, Huadong Guo, Guang Liu, Runhe Shi
2014 Journal of Applied Remote Sensing  
From local to global scales, remote sensing has been extensively used for forest biomass estimation.  ...  Forests are one of the most important sinks for carbon. Estimating the amount of carbon stored in forests is a major task for understanding the global carbon cycle.  ...  modeling methods, such as SVM, RF, and object-based classification.  ... 
doi:10.1117/1.jrs.8.081598 fatcat:hdvyjfwl3jbrflvrk5lko2xj4u

Analyzing the Uncertainty of Estimating Forest Aboveground Biomass Using Optical Imagery and Spaceborne LiDAR

Xiaofang Sun, Guicai Li, Meng Wang, Zemeng Fan
2019 Remote Sensing  
vector machines were used to estimate forest AGB in Jiangxi Province, China, by combining Geoscience Laser Altimeter System (GLAS) data, Moderate Resolution Imaging Spectroradiometer (MODIS) data, and  ...  Finally, the wall-to-wall forest AGB map over the study area was generated using the random forest model.  ...  Acknowledgments: The authors would like to express gratitude to Tianyu Hu and Yanjun Su from Institute of Botany, the Chinese Academy of Sciences, who provide much help and instruction in GLAS data processing  ... 
doi:10.3390/rs11060722 fatcat:ljzm3h7y2fcynnlrqekrjgrw2u

Mapping Annual Forest Change Due to Afforestation in Guangdong Province of China Using Active and Passive Remote Sensing Data

Wenjuan Shen, Mingshi Li, Chengquan Huang, Xin Tao, Shu Li, Anshi Wei
2019 Remote Sensing  
Annual forest maps (1986–2016) of Guangdong, China were generated using time series Landsat images and PALSAR data. Initially, four PALSAR-based classifiers were used to classify land cover types.  ...  Next, an accurate identification of forest and non-forest was carried out by combining Landsat-based phenological variables and PALSAR-based land cover classifications.  ...  The authors also thank the Guangdong Provincial Center for Forest Resources Monitoring for providing field inventories.  ... 
doi:10.3390/rs11050490 fatcat:u26tw7sgpjap7koa3okgv3tl3u

Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

Kai Wang, Steven E. Franklin, Xulin Guo, Marc Cattet
2010 Sensors  
Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification  ...  vector machines (SVMs), one-class classifier, object-oriented classification, and fuzzy classifications.  ...  Helmer et al. proposed the combination of Landsat time series and the GLAS to estimate the biomass accumulation of the Amazonian secondary forest, and the estimation agreed well with ground-based studies  ... 
doi:10.3390/s101109647 pmid:22163432 pmcid:PMC3231003 fatcat:fioutsgar5aqnn76elireshjpm

Approaches of Satellite Remote Sensing for the Assessment of Above-Ground Biomass across Tropical Forests: Pan-tropical to National Scales

Sawaid Abbas, Man Sing Wong, Jin Wu, Naeem Shahzad, Syed Muhammad Irteza
2020 Remote Sensing  
; time steps used to map forest cover change and post-deforestation land cover land use (LCLU)-type mapping.  ...  Aside from these limitations, the estimation of biomass and carbon balance can be enhanced by taking account of post-deforestation forest recovery and LCLU type; land-use history; diversity of forest being  ...  [107] produced global LAI and VFP (Vertical Foliage Profile) from GLAS/ICESat LiDAR data integrated with pre-processed MODIS LAI and another GLAS-based estimate using the Geometric Optical-Radiative  ... 
doi:10.3390/rs12203351 fatcat:rvfj5oyvrjbnllbhnv527pe6jq

Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges

Tien Pham, Naoto Yokoya, Dieu Bui, Kunihiko Yoshino, Daniel Friess
2019 Remote Sensing  
A wide range of studies is based on optical imagery (aerial photography, multispectral, and hyperspectral) and synthetic aperture radar (SAR) data.  ...  Additionally, some aspects of the mangrove ecosystem remain poorly characterized compared to other forest ecosystems due to practical difficulties in measuring and monitoring mangrove biomass and their  ...  Recently, object-based image classification approaches using image segmentation such as object-based image analysis (OBIA) have been frequently employed for mapping mangrove species.  ... 
doi:10.3390/rs11030230 fatcat:xgxftojh5vdfhgkpqcwehgbkwa

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

Dengsheng Lu, Qi Chen, Guangxing Wang, Lijuan Liu, Guiying Li, Emilio Moran
2014 International Journal of Digital Earth  
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades.  ...  This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issuescollection of field-based biomass reference data, extraction and selection  ...  The authors acknowledge the support from the Zhejiang A& F University's Research and Development Fund for the talent startup project (2013FR052), Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest  ... 
doi:10.1080/17538947.2014.990526 fatcat:bkc3syq3pfgzxkawig2pog7i3y

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

Angela Lausch, Stefan Erasmi, Douglas King, Paul Magdon, Marco Heurich
2017 Remote Sensing  
We found that ST/STV can be used to record indicators of FH based on RS.  ...  Long-term monitoring based on forest inventories provides valuable information about changes and trends of FH.  ...  Concluded that better consistency and calibration between data types is needed to conduct such temporal analysis; (2) Multi-temporal canopy height derived from SRTM C-band InSAR and IceSAT GLAS LiDAR used  ... 
doi:10.3390/rs9020129 fatcat:zxyfarzipbaerejj4a3kmp3qca

Review of the use of remote sensing for biomass estimation to support renewable energy generation

Lalit Kumar, Priyakant Sinha, Subhashni Taylor, Abdullah F. Alqurashi
2015 Journal of Applied Remote Sensing  
This paper provides a comprehensive review of biomass assessment techniques using remote sensing in different environments and using different sensing techniques.  ...  It covers forests, savannah, and grasslands/rangelands, and for each of these environments, reviews key work that has been undertaken and compares the techniques that have been the most successful. © The  ...  For broad-scale applications, space-borne LiDAR (ICESat GLAS) was found useful for biomass estimation.  ... 
doi:10.1117/1.jrs.9.097696 fatcat:vb6fitx52rbyxprbf2c6c7nu3i

Characterizing forest canopy structure with lidar composite metrics and machine learning

Kaiguang Zhao, Sorin Popescu, Xuelian Meng, Yong Pang, Muge Agca
2011 Remote Sensing of Environment  
Using coincident lidar and field data over an Eastern Texas forest in USA, we conducted a case study to demonstrate the ubiquitous power of the lidar composite metrics in predicting multiple forest attributes  ...  This study aims to improve lidar-based canopy characterization with airborne laser scanners through the combined use of lidar composite metrics and machine learning models.  ...  Duncan Lutes at the Rocky Mountain Research Station of US Forest service for their help in instructing on the use of FuelCalc.  ... 
doi:10.1016/j.rse.2011.04.001 fatcat:h5rr3urjnzhkxbdztasnhnfs64

Spatial Scaling of Forest Aboveground Biomass Using Multi-Source Remote Sensing Data

Xinchuang Wang, Haiming Jiao
2020 IEEE Access  
Satellite-borne ICESat GLAS lidar data are widely used to estimate canopy height [53] - [55] .  ...  One was to classify land cover categories based on NDVI in combination with forest types, and the other was to use only forest types without any additional parameters. ).  ... 
doi:10.1109/access.2020.3027361 fatcat:pyoekoaywzannlrxfjm3iyxejm
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