Application of aerial hyperspectral images in monitoring tree biophysical parameters in urban areas

Anna Jarocińska; Małgorzata Białczak; Łukasz Sławik

doi:10.1515/mgrsd-2017-0034

Abstract

Monitoring of trees in urban areas can be conducted using remote sensing, but should be supported by field measurements. The article aims to present the research method used to evaluate discolouration and defoliation of trees and tree damage in the city of Białystok in Poland. The analyses were done using AISA hyperspectral images. Field measurements encompassed determining the locations, species and levels of discolouration and defoliation of trees. Remote sensing indices of vegetation were calculated and correlated with the field-measured values of discolouration and defoliation. Based on that, values of discolouration and defoliation were calculated and evaluated against the field studies. The RMSE of the acquired data was around 16%. Using parameter values, a map of tree damage was drawn up. Based on the analysis, it can be stated that a significant number of trees is undamaged, although a large portion of the trees falls into the warning class.

References

Alonzo, M, Bookhagen, B & Roberts, DA 2014, ‘Urban tree species mapping using hyperspectral and lidar data fusion’, Remote Sensing of Environment, vol. 148, pp. 70–83. 10.1016/j.rse.2014.03.018.
Open DOI Search in Google Scholar Back to article
Datt, B 1999, ‘A new reflectance index for remote sensing of chlorophyll content in higher plants test using eucalyptus leaves’, Journal of Plant Physiology, vol. 154, pp. 30–36. 10.1016/S0176-1617(99)80314-9.
Open DOI Search in Google Scholar Back to article
Dian, Y, Pang, Y, Dong, Y & Li, Z 2016, ‘Urban Tree Species Mapping Using Airborne LiDAR and Hyperspectral Data’, Journal of the Indian Society of Remote Sensing, vol. 44(4), pp. 595–603. 10.1007/s12524-015-0543-4.
Open DOI Search in Google Scholar Back to article
Ferreira, MP, Zortea, M, Zanotta, DC, Shimabukuro, YE & de Souza Filho, CR 2016, ‘Mapping tree species in tropical seasonal semi-deciduous forests with hyperspectral and multispectral data’, Remote Sensing of Environment, vol. 179. pp. 66–78. 10.1016/j.rse.2016.03.021.
Open DOI Search in Google Scholar Back to article
Fraser, RH & Latifovic, R 2005, ‘Mapping insect-induced tree defoliation and mortality using coarse spatial resolution satellite imagery’, International Journal of Remote Sensing, vol. 26, no. 1, pp. 193–200. 10.1080/01431160410001716923.
Open DOI Search in Google Scholar Back to article
Gamon, JA, Panuelas, J & Field, CB 1992, ‘A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency’, Remote Sensing of Environment, vol. 41, pp. 35–44. 10.1016/0034-4257(92)90059-S.
Open DOI Search in Google Scholar Back to article
Gitelson, AA & Merzlyak, MN 1994, ‘Spectral reflectance changes associated with Autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral Features and Relation to Chlorophyll Estimation’, Journal of Plant Physiology, vol. 143, pp. 286–292. 10.1016/S0176-1617(11)81633-0.
Open DOI Search in Google Scholar Back to article
Gitelson, AA, Zur, Y, Chivkunova, OB & Merzlyk, MN 2002, ‘Assessing carotenoid content in plant leaves with reflectance spectroscopy’, Photochemistry and Photobiology, vol. 75, pp. 272–281. 10.1562/0031-8655(2002)0750272ACCIPL2.0.CO2.
Open DOI Search in Google Scholar Back to article
Hanuš, J, Malenowský Z, Homolová, L, Kaplan, V, Lukeš, P & Cudlín, P 2008, ‘Potentials of the VNIR airborne hyperspectral system AISA EAGLE’, GIS Ostrava 2008, 27.-30.1.2008. pp. 1–6.
Search in Google Scholar Back to article
Huang, C, Davis, LS & Townshend, JRG 2002, ‘An assessment of Support Vector Machine for land cover classification’, International Journal of Remote Sensing, vol. 23, pp. 725–749. 10.1080/01431160110040323.
Open DOI Search in Google Scholar Back to article
Huete, AR, Liu, H, Batchily, K & van Leeuwen, W 1997, ‘A Comparison of Vegetation Indices Over a Global Set of TM Images for EOS-MODIS’, Remote Sensing of Environment, vol. 59, no. 3, pp. 440–451. 10.1016/S0034-4257(96)00112-5.
Open DOI Search in Google Scholar Back to article
Innes, JL 1990, ‘Assessment of Tree Condition’, Forestry Commission Archive, vol. 12, pp. 1–96.
Search in Google Scholar Back to article
Jarocinska, A 2014, ‘Radiative Transfer Model parametrization for simulating the reflectance of meadow vegetation’, Miscellanea Geographica – Regional Studies on Development, vol. 18, no. 2, pp. 5–9. 10.2478/mgrsd-2014-0001.
Open DOI Search in Google Scholar Back to article
Jarocińska, A, Kacprzyk, M, Marcinkowska-Ochtyra, A, Ochtyra, A, Zagajewski, B & Meuleman, K 2016, ‘The application of APEX images in the assessment of the state of non-forest vegetation in the Karkonosze Mountains’, Miscellanea Geographica – Regional Studies on Development, vol. 20, no. 1, pp. 21–27. 10.1515/mgrsd-2016-0009.
Open DOI Search in Google Scholar Back to article
Jung, A, Kardevan, P & Tokei, L 2005, ‘Detection of urban effect on vegetation in a less built-up Hungarian city by hyperspectral remote sensing’, Physics and Chemistry of the Earth, vol. 30, pp. 255–259. 10.1016/j.pce.2004.08.041.
Open DOI Search in Google Scholar Back to article
Karpouzli, E & Malthus, T 2003, ‘The empirical line method for the atmospheric correction of IKONOS imagery’, International Journal of Remote Sensing, vol. 24, pp. 1143–1150. 10.1080/0143116021000026779.
Open DOI Search in Google Scholar Back to article
Kaufman, YJ & Tanre, D 1992, ‘Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS’, IEEE Transactions on Geoscience and Remote Sensing, vol. 30, pp. 261–270. 10.1109/36.134076.
Open DOI Search in Google Scholar Back to article
Kupková, L, Červená, L, Suchá, R, Jakešová, L, Zagajewski, B, Březina, S & Albrechtová, J 2017, ‘Classification of Tundra Vegetation in the Krkonoše Mts. National Park Using APEX, AISA Dual and Sentinel-2A Data’, European Journal of Remote Sensing, vol. 50, no. 1, pp. 29–46. 10.1080/22797254.2017.1274573.
Open DOI Search in Google Scholar Back to article
Kycko, M, Zagajewski, B, Zwijacz-Kozica, M, Cierniewski, J, Romanowska, E, Orłowska, K, Ochtyra, A & Jarocińska, A 2017, ‘Assessment of Hyperspectral Remote Sensing for Analyzing the Impact of Human Trampling on Alpine Swards’, Mountain Research and Development, vol. 37, no. 1, pp. 66–74. 10.1659/MRD-JOURNAL-D-15-00050.1.
Open DOI Search in Google Scholar Back to article
Leckie, GD, Cloney, E & Joyce, SP 2005, ‘Automated detection and mapping of crown discolouration caused by jack pine budworm with 2.5 m resolution multispectral imagery’, International Journal of Applied Earth Observation and Geoinformation, vol. 7, pp. 61–77. 10.1016/j.jag.2004.12.002.
Open DOI Search in Google Scholar Back to article
Liu, L, Coops, NC, Aven, NW & Pang, Y 2017, ‘Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data’, Remote Sensing of Environment, vol. 200, pp. 170–182. 10.1016/j.rse.2017.08.010.
Open DOI Search in Google Scholar Back to article
Marcinkowska, A, Zagajewski, B, Ochtyra, A, Jarocińska, A, Raczko, E, Kupková, L, Stych, P & Meuleman, K 2014, ‘Mapping vegetation communities of the Karkonosze National Park using APEX hyperspectral data and SVM’, Miscellanea Geographica – Regional Studies on Development, vol. 18, no. 2, pp. 23–29. 10.2478/mgrsd-2014-0007.
Open DOI Search in Google Scholar Back to article
Marcinkowska-Ochtyra, A, Zagajewski, B, Ochtyra, A, Jarocińska, A, Wojtuń, B, Rogass, C, Mielke, C & Lavender, S 2017, ‘Subalpine and alpine vegetation classification based on hyperspectral APEX and simulated EnMAP images’, International Journal of Remote Sensing, vol. 38, pp. 1839–1864. 10.1080/01431161.2016.1274447.
Open DOI Search in Google Scholar Back to article
Milton, EJ, Schaepman, ME, Anderson, K, Kneubühler, M & Fox, N 2009, ‘Progress in field spectroscopy’, Remote Sensing of Environment, vol. 113, pp. 92–109. 10.1016/j.rse.2007.08.001
Open DOI Search in Google Scholar Back to article
Ochtyra, A, Zagajewski, B, Kozlowska, A, Marcinkowska-Ochtyra, A & Jarocinska, A 2016, ‘Ocena kondycji drzewostanów Tatrzańskiego Parku Narodowego za pomocą metody drzewa decyzyjnego oraz wielospektralnych obrazów satelitarnych Landsat 5 TM’, Sylwan, vol. 160, no. 3, pp. 256–264.
Search in Google Scholar Back to article
Panigada, C, Rossini, M, Busetto, L, Meroni, M, Fava, F & Colombo, R 2010, ‘Chlorophyll concentration mapping with MIVIS data to assess crown discoloration in the Ticino Park oak forest’, International Journal of Remote Sensing, vol. 31, no. 12, pp. 3307–3332. 10.1080/01431160903193497.
Open DOI Search in Google Scholar Back to article
Peñuelas, J, Baret, F & Fiella, I 1995, ‘Semi–empirical indices to assess carotenoids/chlorophyll–a ratio from leaf spectral reflectance’, Photosynthetica, vol. 31, pp. 221–230.
Search in Google Scholar Back to article
Pu, R & Liu, D 2011, ‘Segmented canonical discriminant analysis of in situ hyperspectral data for identifying 13 urban tree species’, International Journal of Remote Sensing, vol. 32, no. 8, pp. 2207–2226. 10.1080/01431161003692040.
Open DOI Search in Google Scholar Back to article
Raczko, E & Zagajewski, B 2017, ‘Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images’, European Journal of Remote Sensing, vol. 50, no. 1, pp. 144–154. 10.1080/22797254.2017.1299557.
Open DOI Search in Google Scholar Back to article
Raczko, E, Zagajewski, B, Ochtyra, A, Jarocińska, A, Marcinkowska-Ochtyra, A & Dobrowolski, M 2015, ‘Określenie składu gatunkowego lasów Góry Chojnik (KPN) z wykorzystaniem lotniczych danych hiperspektralnych’, Sylwan, vol. 159, no. 7, pp. 593–599.
Search in Google Scholar Back to article
Rouse, JW, Haas, RH, Schell, JA & Deering, DW 1973, ‘Monitoring vegetation systems in the great plains with ERTS’, Third ERTS Symposium’, NASA SP–351 V I NASA Washington, DS, pp. 309–317.
Search in Google Scholar Back to article
Small, Ch & Lu, J 2006, ‘Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis’, Remote Sensing of Environment, vol. 100, pp. 441–456. 10.1016/j.rse.2005.10.023.
Open DOI Search in Google Scholar Back to article
Townsend, PA, Singh, A, Foster, JR, Rehberg, NJ, Kingdon, CC, Eshleman, KN & Seagle, SW 2012, ‘A general Landsat model to predict canopy defoliation in broadleaf deciduous forests’, Remote Sensing of Environment, vol. 119, pp. 255–265. 10.1016/j.rse.2011.12.023.
Open DOI Search in Google Scholar Back to article
Vogelmann, JE, Rock, BN & Moss, DM 1993, ‘Red Edge Spectral Measurements from Sugar Maple Leaves’, International Journal of Remote Sensing, vol. 14, pp. 1563–1575. 10.1080/01431169308953986.
Open DOI Search in Google Scholar Back to article
Wawrzyniak, J 2014, ‘Stan uszkodzenia lasów w Polsce w 2013 roku na podstawie badań monitoringowych’, Instytut Badawczy Leśnictwa, Zakład Zarzadzania Zasobami Leśnymi, Sękocin Stary.
Search in Google Scholar Back to article
Zagajewski, B & Jarocinska, A 2009, ‘Analysis of plant condition of the Bystrzanka catchment’, in Remote Sensing for a Changing Europe, eds D Maktav, Millpress Science Publishers, Istanbul, pp. 498–504. 10.3233/978-1-58603-986-8-498.
Open DOI Search in Google Scholar Back to article

Application of aerial hyperspectral images in monitoring tree biophysical parameters in urban areas

Abstract

Paradigm

My account