an official journal of: published by:
Editor in Chief: RAFFAELLO COSSU


  • Ignas Daugėla - Department of Geodesy and Cadastre, Vilnius Gediminas Technical University, Lithuania
  • Jurate Suziedelyte Visockiene - Department of Geodesy and Cadastre, Vilnius Gediminas Technical University, Lithuania
  • Jurate Kumpiene - Waste Science and Technology, Lulea University of Technology, Sweden

DOI 10.31025/2611-4135/2020.13942

Released under CC BY-NC-ND

Copyright: © 2019 CISA Publisher

Editorial History

  • Received: 26 Nov 2019
  • Revised: 11 Feb 2020
  • Accepted: 28 Feb 2020
  • Available online: 08 May 2020


Landfill operators must collect data on the topography of their landfills, their biological and hydrological characteristics, and local meteorological conditions. These data can be collected by satellite, using Unmanned Aerial Vehicles, or by traditional methods such as static flux chambers or modelling. They serve as the basis for landfill monitoring, including the identification and measurement of methane (CH4) gas emissions. Here, we present an approach for landfill mapping using sensor data from unmanned aerial drone systems (UADS) based on DJI Matrice 200 UAVs with Zenmuse X4S sensors and Trimble UX5 UAVs with Sony NEX-5R sensors. RGB (Red, Green, Blue) and near infrared (NIR) data from these sensors were processed using a Geographic Information System (GIS) to generate orthoimages, digital elevation models (DEMs), and normalized difference vegetation index (NDVI) maps. These were then used to evaluate changes in the surface structure and topography of the study area (Kariotiškės landfill, Lithuania). The NDVI maps were used to identify areas of sparse vegetation cover that may indicate localized CH4 emissions. Surface temperature maps based on thermal infrared (TIR) images were then prepared for analysis of these problematic areas. Finally, the presence of CH4 in these areas was investigated using a prototype lightweight gas sensor array. The structure of the Kariotiškės landfill site remained unchanged over three years, but there is evidence of possible CH4 gas influence at the landfill cover’s surface. The combination of UADS-mounted imaging systems and the prototype gas sensor array enabled rapid analysis of emission hotspots and of landfill topography.



Abichou, T., Kormi, T., Yuan, L., Johnson, T., Francisco, E., 2015. Modeling the effects of vegetation on methane oxidation and emissions through soil landfill final covers across different climates. Journal of Waste Manage 36, 230-240.
DOI 10.1016/j.wasman.2014.11.002

Abichou, T., Powelson, D., Chanton, J., Escoriaza, S., 2006. Characterization of methane flux and oxidation at a solid waste landfill. Journal of Environmental Engineering 132, 220-228.
DOI 10.1061/(ASCE)0733-9372(2006)132:2(220)

Allen, G., Hollingsworth, P., Kabbabe, K., Pitt, J.R., Mead, S.I., Robers, G., Bount, M., Shallcross, D.E., Percival, C.J., 2019. The development and trial of an unmanned aerial system for the measurement of methane flux from landfill and greenhouse gas emission hotspots. Journal of Waste Manage 87, 883-892.
DOI 10.1016/j.wasman.2017.12.024

Arif, M.A.S., Verstraete, W., 1995. Methane dosage to soil and its effect on plant growth. World J Microbiol Biotechnol 11(5), 529-35.
DOI 10.1007/BF00286368

Battaglini, R., Raco, B., Scozzari, A., 2013. Effective monitoring of landfills: flux measurements and thermography enhance efficiency and reduce environmental impact. J. Geophys. Eng. 10, 64002.
DOI 10.1088/1742-2132/10/6/064002

Bhandari, A.K., Kumar, A., 2012. Feature extraction using normalized difference vegetation index (NDVI): A Case Study of Jabalpur City. Proceedings of Communication, Computing & Security. Proc. Technol. 6, 612– 621

Bourn, M., Robinson, R., Innocenti, F., Scheutz, C., 2019. Regulating landfills using measured methane emissions: An English perspective. Journal of Waste Manage 87, 860-869,
DOI 10.1016/J.WASMAN.2018.06.032

Capodici, M., Ciraolo, G., Trapani, D.D.I., Viviani, G., 2015. Remote sensing analysis coupled to field measurements for the evaluation of methane emissions from a landfill site: a case study. In: Proceedings Sardinia 2015, Fifteenth International Waste Management and Landfill Symposium

Christensen, T. H., Cossu, R., Stegmann, R., 1996. Landfilling of Waste. Biogas, in: Christensen, T.H., Cossu, R., Stegmann, R. (Eds), New York, 860

Cosyn, P., Miller, R., 2013. Trimble UX5 aerial imaging solution. A new standard in accuracy, robustness and performance for photogrammetric aerial mapping, in: Trimble Navigation Limited, Westminster, USA

Daugela, I., Suziedelyte Visockiene, J., Aksamitauskas, Č.V., 2018. RPAS and GIS for landfill analysis. Tenth Conference on Interdisciplinary Problems in Environmental Protection and Engineering EKO-DOK 2018, Centrum Zdrowia i Wypoczynku Nowy Zdrój, Polanica-Zdrój, 16–18 April 2018

De la Cruz, F.B., Green, R.B., Hater, G.R., Chanton, J.P., Thoma, E.D., Harvey, T.A., Barlaz, M.A., 2016. Comparison of field measurements to methane emissions models at a new landfill. Environ. Sci. Technol. 50, 9432–9441.
DOI 10.1021/acs.est.6b00415

Desideri, U., Leonardi, D., Proietti, S., 2007. Application of infrared thermography to study behaviour of biogas captation wells. In: Proceedings Sardinia 2007, Eleventh International Waste Management and Landfill Symposium

Environmental Protection Agency, 2000. Landfill manuals. Landfill site design. Wexford, Ireland. (accessed 25 February 2019)

El-Fadel, M., Khoury, R., 2000. Modeling settlement in MSW landfills: a critical review. Crit Rev Environ Sci Technol. 30, 327–361

Feng, S, Leung, A.K., Ng, C.W.W., Liu, H.W., 2017. Theoretical analysis of coupled effects of microbe and root architecture on methane oxidation in vegetated landfill covers. Sci Total Environ. 599–600, 1954–1964

Fjelsted, L., Christensen, A.G., Larsen, J. E. Kjeldsen, P., Scheutz, C., 2019. Assessment of a landfill methane emission screening method using an unmanned aerial vehicle mounted thermal infrared camera – A field study. Journal of Waste Manage 87, 893-904.
DOI 10.1016/J.WASMAN.2018.05.031

Fredenslund, A. M., Mønster, J., Kjeldsen, P., Scheutz, Ch., 2019. Development and implementation of a screening method to categorize the greenhouse gas mitigation potential of 91 landfills. Journal of Waste Manage 87, 915-923.
DOI 10.1016/j.wasman.2018.03.0050956-053X/

Förstner, W., Wrobel, B.P., 2016. Photogrammetric Computer Vision. Statistics, Geometry, Orientation and Reconstruction. EBook, ISBN 978-3-319-11550-4

Gandhi, G.M., Parthiban, S., Thummalu, N., Cristy, A., 2015. NDVI: vegetation change detection using remote sensing and GIS – A Case Study of Vellore Distric. Procedia Comput. Sci. 57, 1199-1210

Gebert, J., Groengroeft, A., 2006. Passive landfill gas emission – influence of atmospheric pressure and implications for the operation of methane-oxidising biofilters. Waste Manage 26, 245–251.
DOI 10.1016/J.WASMAN.2005.01.022

Gendebien, A., Pauwels, M., Constant, M., Ledrut-Damanet, M.J., Nyns, E.J., Fabry, R., Ferrero, G.L., Willumsen, H.C., Butson, J., 1992. Landfill gas from environment to energy (EUR--14017/1). Commission of the European Communities (CEC)

Hildmann, H., Kovacs, E., 2019. Review: Using Unmanned Aerial Vehicles (UAVs) as Mobile Sensing Platforms (MSPs) for Disaster Response, Civil Security and Public Safe. Drones 3, 59.
DOI 10.3390/drones3030059

Innocenti, F., Robinson, R., Gardiner, T., Finlayson, A., Connor, A., 2017. Differential absorption lidar (DIAL) measurements of landfill methane emissions. Remote Sens. 9, 953

Ishigaki, T., Yamada, M., Nagamori, M., Ono, Y., Inoue, Y., 2005. Estimation of methane emission from whole waste landfill site using correlation between flux and ground temperatures. Environ. Geol. 48, 845–853.
DOI 10.3390/RS9090953

Kamieniak, J., Randviir, E.P., Banks, C.E., 2015. The latest developments in the analytical sensing of methane. Trends Analyt Chem. 73, 146–157

Kastek, M., Sosnowski, T., Orżanowski, T., Kopczyński, K., Kwaśny, M., 2009. Multispectral gas detection method. WIT Trans. Ecol. Envir. 123, 227-236.
DOI 10.2495/AIR09021

Lando, A.T., Nakayama, H., Shimaoka, T., 2017. Application of portable gas detector in point and scanning method to estimate spatial distribution of methane emission in landfill. Waste Manage. 59, 255–266.
DOI 10.1016/J.WASMAN.2016.10.033

Mahmood, K., Batool, S. A., Chaudhry, M. N. 2016. Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS. Waste Manage. 55, 118-128

Manzo, C., Mei, A., Zampetti, E., Bassani, C., Paciucci, L., Manetti, P., 2017. Top-down approach from satellite to terrestrial rover application for environmental monitoring of landfills. J. Sci. Total Environ. 584-585, 1333-1348.
DOI 10.1016/J.SCITOTENV.2017.01.033

Maurice, C., Bergman, A., Ecke, H., Lagerkvist, A., 1995. Vegetation as a biological indicator for landfill gas emissions: initial investigations. In: Proceedings: Sardinia 1995, Fifth International Landfill Symposium

Mønster, J., Kjeldsen, P., Scheutz, C., 2019. Methodologies for measuring fugitive methane emissions from landfills – a review. Waste Manage,
DOI 10.1016/J.WASMAN.2018.12.047

Ndanga, T.M., Bradley, R.L., Cabral, A.R., 2015. Does vegetation affect the methane oxidation efficiency of passive biosystems? Waste Manage, 38, 240-249

NASA, 2018. Normalized Difference Vegetation Index (NDVI). Retrieved from The Earth Observatory: (accessed 25 February 2019)

Remote Sensing Phenology, 2018. NDVI – the foundation. Retrieved from USGS: (accessed 25 February 2019)

Scheutz, C., Cassini, F., De Schoenmaeker, Jan, Kjeldsen, P., 2017. Mitigation of methane emissions in a pilot-scale biocover system at the AV Miljø Landfill, Denmark: 2. Methane oxidation. Waste Manage 63, 203–212

Scheutz, C., Fredenslund, A.M., Nedenskov, J., Samuelsson, J., Kjeldsen, P., 2011. Gas production, composition and emission at a modern disposal site receiving waste with a low organic content. Waste Manage 31, 946–955

Scheutz, C., Bogner, J., Chanton, J.P., Blake, D., Morcet, M., Aran, C., Kjeldsen, P., 2008. Atmospheric emissions and attenuation of non-methane organic compounds in cover soils at a French landfill. Waste Manage 28, 1892–1908

Scheutz, C., Bogner, J., Chanton, J., Blake, D., Morcet, M., Kjeldsen, P., 2003. Comparative oxidation and net emissions of methane and selected nonmethane organic compounds in landfill cover soils. Environ. Sci. Technol. 37, 5150–5158

Spokas, K., Bogner, J., 2011. Limits and dynamics of methane oxidation in landfill cover soils. Waste Manage. 31, 823–832.
DOI 10.1016/j.wasman.2009.12.018

Stern, J. C., Chanton, J., Abichou, T., Powelson, D., Yuan, L., Escoriza, S., Bogner, J., 2007. Use of a biologically active cover to reduce landfill methane emissions and enhance methane oxidation. Waste Manage 27, 248-1258

Tanteri, L., Rossi, G., Tofani, V., Vannocci, P., Moretti, S. and Casagli, N., 2017. Multitemporal UAV survey for mass movement detection and monitoring. In: Workshop on World Landslide Forum. Springer, Cham

Thenkabail, P.S., 2015. Remotely Sensed Data Characterization, Classification, and Accuracies. Remote Sensing Handbook. First ed. CRC Press. Boca Raton

Thomasen, T.B., Scheutz, C., Kjeldsen, P., 2019. Treatment of landfill gas with low methane content by biocover systems. Waste Manage 84, 29-37

USEPA, 2006. EPA Test Method (OTM 10), (accessed June 2018)

Xu, L., Lin, X., Amen, J., Welding, K., McDermitt, D., 2014. Impact of changes in barometric pressure on landfill methane emission. Global Biogeochem. Cy. 28, 679–695.
DOI 10.1002/2013GB004571

Xie, Y., Sha, Z., Yu, M., 2008. Remote sensing imagery in vegetation mapping: review. Plant Ecol. 1, 9-23

Zhang, H., Hu, H., Yao, X., Zheng, K., Gan, Y., 2009. Estimation of above-ground biomass using HJ-1 hyperspectral images in Hangzhou Bay, China. In: International Conference on Information, Engineering and Computer Science.
DOI 10.1109/ICIECS.2009.5364800

Yuan, H., Xiao, Ch., Zhan, W., Wang, Y., Shi, Ch., Ye, H., Jiang, K., •ChunhuiZhou, Z., •Wen, Y., Li, Q. 2019. Target Detection, Positioningand Tracking Using New UAV Gas Sensor Systems: Simulation and Analysis. Journal of Intelligent & Robotic Systems 94, 871–882.
DOI 10.1007/s10846-018-0909-2