Literature DB >> 30338385

Differentiating carbon sinks versus sources on a university campus using synergistic UAV NIR and visible signatures.

Seong-Il Park1, Jung-Sup Um2.   

Abstract

This research proposes a framework for quantitatively differentiating carbon sinks versus sources, utilizing synergistic NIR (near-infrared) and visible signatures acquired from UAV (unmanned aerial vehicle). UAV NIR and visible imagery acquired at 70-m flying altitude identified the major types of carbon sinks versus sources, such as vegetation and constructed surfaces (e.g., road and buildings) for representative section of the university campus at the level of almost field-survey standpoint. Our findings show that the NIR reflectance for the sink was distributed in the range of 9.46-44.65%, whereas the emission sources had shown NIR response, ranging from 16.74 to 22.67%. The visible green reflectance showed a significantly higher range for emission sources (23.6-52.3%) than the sink (13.50-26.74%). The emission source in visible red showed a wider range of reflectance (17.05-38.49%), while the sink was observed in the narrow range of 9.36-17.75%. It was confirmed that synergistically combining NIR and visible signatures offers a viable method for measuring and comparing campus-wide carbon sinks versus sources due to extremely hyper-spatial resolution. It is anticipated that this research will be used as a valuable reference to investigate hyper-localized carbon sources and sinks in university campuses as cities within cities.

Entities:  

Keywords:  Carbon emission sources; Carbon sink; Cities within cities; Synergism; Unmanned aerial vehicle

Mesh:

Substances:

Year:  2018        PMID: 30338385     DOI: 10.1007/s10661-018-7003-x

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  9 in total

1.  Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system.

Authors:  Adrien Michez; Hervé Piégay; Jonathan Lisein; Hugues Claessens; Philippe Lejeune
Journal:  Environ Monit Assess       Date:  2016-02-05       Impact factor: 2.513

2.  Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR.

Authors:  Ioannis Angelidis; Gregor Levin; Ramón Alberto Díaz-Varela; Radek Malinowski
Journal:  Environ Monit Assess       Date:  2017-08-05       Impact factor: 2.513

3.  Spatial 3D distribution of soil organic carbon under different land use types.

Authors:  A Amirian Chakan; R Taghizadeh-Mehrjardi; R Kerry; S Kumar; S Khordehbin; S Yusefi Khanghah
Journal:  Environ Monit Assess       Date:  2017-02-28       Impact factor: 2.513

4.  Variation of biomass and carbon pool with NDVI and altitude in sub-tropical forests of northwestern Himalaya.

Authors:  D R Bhardwaj; Muneesa Banday; Nazir A Pala; Bhalendra Singh Rajput
Journal:  Environ Monit Assess       Date:  2016-10-24       Impact factor: 2.513

5.  Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data.

Authors:  Laxmi Kant Sharma; Mahendra Singh Nathawat; Suman Sinha
Journal:  Environ Monit Assess       Date:  2013-04-20       Impact factor: 2.513

6.  Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle.

Authors:  R A Diaz-Varela; P J Zarco-Tejada; V Angileri; P Loudjani
Journal:  J Environ Manage       Date:  2014-01-29       Impact factor: 6.789

7.  Spatial and temporal distribution of carbon dioxide gas using GOSAT data over IRAN.

Authors:  Samereh Falahatkar; Seyed Mohsen Mousavi; Manochehr Farajzadeh
Journal:  Environ Monit Assess       Date:  2017-11-09       Impact factor: 2.513

8.  Greenhouse Gas Emissions from Asphalt Pavement Construction: A Case Study in China.

Authors:  Feng Ma; Aimin Sha; Ruiyu Lin; Yue Huang; Chao Wang
Journal:  Int J Environ Res Public Health       Date:  2016-03-22       Impact factor: 3.390

9.  The Greenhouse Gas Emission from Portland Cement Concrete Pavement Construction in China.

Authors:  Feng Ma; Aimin Sha; Panpan Yang; Yue Huang
Journal:  Int J Environ Res Public Health       Date:  2016-06-24       Impact factor: 3.390

  9 in total

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