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iForest - Biogeosciences and Forestry

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Estimation of forest cover change using Sentinel-2 multi-spectral imagery in Georgia (the Caucasus)

Giorgi Mikeladze (1)   , Alexander Gavashelishvili (1), Ilia Akobia (2), Vasil Metreveli (1)

iForest - Biogeosciences and Forestry, Volume 13, Issue 4, Pages 329-335 (2020)
doi: https://doi.org/10.3832/ifor3386-013
Published: Aug 07, 2020 - Copyright © 2020 SISEF

Research Articles


Our objective was to use Sentinel-2A multispectral data in order to cost-effectively detect change in forest cover in Georgia (the Caucasus). Generalized additive models (GAMs) were used to fit forest cover measures to Sentinel-2A spectral band values modified using different topographic correction methods. Canopy closure (calculated from upward-looking fisheye photographs taken beneath forest canopy) was the best forest cover measure accounted for by the Sentinel-2 spectral data that were topographically corrected using the Minnaert Correction (R2 = 0.882). Spectral bands best explaining canopy closure were Band 3 (Green), Band 8 (NIR) and Band 12 (SWIR). Our model is able to reasonably detect spatial and temporal changes in canopy closure, even in highly rugged terrain and diverse vegetation cover, and it has potential to be improved to the extent that it can be applied by managers of natural resources. Based on free open source applications in combination with cheap gadgets our approach might play an important role in monitoring the forests of countries with low economic indicators.

  Keywords


Generalized Additive Models, Forest Cover, Satellite Imagery, Sentinel-2, Fisheye, Topographic Correction

Authors’ address

(1)
Giorgi Mikeladze 0000-0003-4972-0562
Alexander Gavashelishvili 0000-0001-9677-6038
Vasil Metreveli 0000-0002-9558-0655
Center of Biodiversity Studies, Institute of Ecology, Ilia State University, Cholokashvili Str. 5, 0162 Tbilisi (Georgia)
(2)
Ilia Akobia
Department of Geoinformatics, Institute of Botany, Ilia State University, Botanical Str. 1, 0105 Tbilisi (Georgia)

Corresponding author

 
Giorgi Mikeladze
gmikeladze@gis-lab.ge

Citation

Mikeladze G, Gavashelishvili A, Akobia I, Metreveli V (2020). Estimation of forest cover change using Sentinel-2 multi-spectral imagery in Georgia (the Caucasus). iForest 13: 329-335. - doi: 10.3832/ifor3386-013

Academic Editor

Maurizio Marchi

Paper history

Received: Feb 25, 2020
Accepted: Jun 03, 2020

First online: Aug 07, 2020
Publication Date: Aug 31, 2020
Publication Time: 2.17 months

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List of the papers citing this article based on CrossRef Cited-by.

 
(1)
Achard F, DeFries R, Eva H, Hansen M, Mayaux P, Stibig HJ (2007)
Pan-tropical monitoring of deforestation. Environmental Research Letters 2: 045022.
CrossRef | Gscholar
(2)
Asner GP, Keller M, Lentini M, Merry F, Souza C (2009a)
Selective logging and its relation to deforestation. Geophysical Monograph Series 186: 25-42.
CrossRef | Gscholar
(3)
Asner GP, Knapp D, Balaji A, Páez-Acosta B (2009b)
Automated mapping of tropical deforestation and forest degradation: CLASlite. Journal of Applied Remote Sensing 3: 033543.
CrossRef | Gscholar
(4)
Brusa A, Bunker DE (2014)
Increasing the precision of canopy closure estimates from hemispherical photography: blue channel analysis and under-exposure. Agricultural and Forest Meteorology 195-196: 102-107.
CrossRef | Gscholar
(5)
Chianucci F, Cutini A (2012)
Digital hemispherical photography for estimating forest canopy properties: current controversies and opportunities. iForest - Biogeosciences and Forestry 5: 290-295.
CrossRef | Gscholar
(6)
Chopping M, North M, Chen JQ, Schaaf CB, Blair JB, Martonchik JV, Bull MA (2012)
Forest canopy cover and height from MISR in topographically complex Southwestern US landscapes assessed with high quality reference data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5: 44-58.
CrossRef | Gscholar
(7)
Civco DL (1989)
Topographic normalization of Landsat thematic mapper digital imagery. Photogrammetric Engineering and Remote Sensing 55: 1303-1309.
Gscholar
(8)
Crowther TW, Glick HB, Covey KR, Bettigole C, Maynard DS, Thomas SM, Smith JR, Hintler G, Duguid MC, Amatulli G, Tuanmu MN, Jetz W, Salas C, Stam C, Piotto D, Tavani R, Green S, Bruce G, Williams SJ, Wiser SK, Huber MO, Hengeveld GM, Nabuurs GJ, Tikhonova E, Borchardt P, Li CF, Powrie LW, Fischer M, Hemp A, Homeier J, Cho P, Vibrans AC, Umunay PM, Piao SL, Rowe CW, Ashton MS, Crane PR, Bradford MA (2015)
Mapping tree density at a global scale. Nature 525 (7568): 201-205.
CrossRef | Gscholar
(9)
Curtis PG, Slay CM, Harris NL, Tyukavina A, Hansen MC (2018)
Classifying drivers of global forest loss. Science 361: 1108-1111.
CrossRef | Gscholar
(10)
Fan W, Li J, Liu Q, Zhang Q, Yin G, Li A, Zeng Y, Xu B, Xu X, Zhou G, Du H (2018)
Topographic correction of forest image data based on the canopy reflectance model for sloping terrains in multiple forward mode. Remote Sensing 10: 717.
CrossRef | Gscholar
(11)
Fournier RA, Mailly D, Walter JMN, Soudani K (2003)
Indirect measurement of forest canopy structure from in situ optical sensors. In: “Remote Sensing of Forest Environments” (Wulder MA, Franklin SE eds). Springer, Boston, MA, USA, pp. 77-113.
Gscholar
(12)
Frazer GW, Canham CD, Lertzman KP (1999)
Gap Light Analyzer (GLA), version 2.0: imaging software to extract canopy structure and gap light transmission indices from true-color fisheye photographs. Simon Fraser University, Burnaby, BC, and the Institute of Ecosystem Studies, Millbrook, New York, USA.
Online | Gscholar
(13)
Gao Y, Zhang W (2009)
A simple empirical topographic correction method for ETM+ imagery. International Journal of Remote Sensing 20: 2259-2275.
CrossRef | Gscholar
(14)
Gao B (1996)
NDWI - a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment 58: 257-266.
CrossRef | Gscholar
(15)
Gitelson A, Gritz Y, Merzlyak M (2003)
Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology 160: 271-282.
CrossRef | Gscholar
(16)
Goyal SK, Seyfried MS, Neill PE (1998)
Effect of digital elevation model resolution on topographic correction of airborne SAR. International Journal of Remote Sensing 19: 3075-3096.
CrossRef | Gscholar
(17)
Halperin J, LeMay V, Coops N, Verchot L, Marshall P, Lochhead K (2016)
Canopy cover estimation in Miombo woodlands of Zambia: comparison of Landsat OLI versus RapidEye imagery using parametric, nonparametric, and semiparametric methods. Remote Sensing of Environment 179: 170-182.
CrossRef | Gscholar
(18)
Hansen MC, DeFries R, Townshend JR, Sohlberg R, Dimiceli C, Carroll M (2002)
Towards an operational MODIS continuous field of percent tree cover algorithm: examples using AVHRR and MODIS data. Remote Sensing of Environment 83: 303-319.
CrossRef | Gscholar
(19)
Hansen MC, Egorov A, Roy DP, Potapov P, Ju J, Turubanova S, Loveland TR (2010)
Continuous fields of land cover for the conterminous United States using Landsat data: first results from the Web-Enabled Landsat Data (WELD) project. Remote Sensing Letters 2: 279-288.
CrossRef | Gscholar
(20)
Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman SV, Goetz SJ, Loveland TR, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG (2013)
High-resolution global maps of 21st-century forest cover change. Science 342: 850-853.
CrossRef | Gscholar
(21)
Hijmans RJ (2016)
Raster: geographic data analysis and modeling. R package version 2.5-8.
Online | Gscholar
(22)
Kawata Y, Ueno S, Kusaka T (1988)
Radiometric correction for atmospheric and topographic effects on Landsat MSS images. International Journal of Remote Sensing 9: 729-748.
CrossRef | Gscholar
(23)
Kennedy RE, Yang Z, Cohen WB (2010)
Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr temporal segmentation algorithms. Remote Sensing of Environment 114: 2897-2910.
CrossRef | Gscholar
(24)
Korhonen L, Saputra DH, Packalen P, Rautiainen M (2017)
Comparison of Sentinel-2 and Landsat 8 in the estimation of boreal forest canopy cover and leaf area index. Remote Sensing of Environment 195: 259-274.
CrossRef | Gscholar
(25)
Köhl M, Baldauf T, Plugge D, Krug J (2009)
Reduced emissions from deforestation and forest degradation (REDD): a climate change mitigation strategy on a critical track. Carbon Balance and Management 4: 10.
CrossRef | Gscholar
(26)
Lehmann EA, Wallace JF, Caccetta PA, Furby SL, Zdunic K (2013)
Forest cover trends from time series Landsat data for the Australian continent. International Journal of Applied Earth Observation 21: 453-462.
CrossRef | Gscholar
(27)
Liang S (2005)
Topographic correction methods. In: “Quantitative Remote Sensing of Land Surfaces” (Kong JA eds). John Wiley and Sons, Hoboken, NJ, USA, pp. 231-245.
CrossRef | Gscholar
(28)
Lorenzen B, Jensen A (1988)
Reflectance of blue, green, red and near infrared radiation from wetland vegetation used in a model discriminating live and dead above ground biomass. New Phytologist 108: 345-355.
CrossRef | Gscholar
(29)
Meyer LH, Heurich M, Beudert B, Premier J, Pflugmacher D (2019)
Comparison of Landsat-8 and Sentinel-2 data for estimation of leaf area index in temperate forests. Remote Sensing 11: 1160.
CrossRef | Gscholar
(30)
Pickell PD, Hermosilla T, Frazier RJ, Coops NC, Wulder MA (2016)
Forest recovery trends derived from Landsat time series for North American boreal forests. International Journal of Remote Sensing 37: 138-149.
CrossRef | Gscholar
(31)
QGIS Development Team (2019)
QGIS Geographic Information System. Open Source Geospatial Foundation Project, Web site.
Online | Gscholar
(32)
R Core Team (2018)
R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Online | Gscholar
(33)
Schleppi P, Paquette A (2017)
Solar radiation in forests: theory for hemispherical photography. In: “Hemispherical Photography in Forest Science: Theory, Methods, Applications” (Fournier RA, Hall RJ eds). Series “Managing Forest Ecosystems”. Springer, Netherlands, pp. 15-52.
Gscholar
(34)
Sexton JO, Noojipady P, Song X-P, Feng M, Song D-X, Kim D-H, Anand A, Huang C, Channan S, Pimm SL, Townshend JR (2015)
Conservation policy and the measurement of forests. Nature Climate Change 6: 192-196.
CrossRef | Gscholar
(35)
Smith JA, Lin TL, Ranson KJ (1980)
The Lambertian assumption and Landsat data. Photogrammetric Engineering and Remote Sensing 46: 1183-1189.
Gscholar
(36)
Tan B, Masek JG, Wolfe R, Gao F, Huang C, Vermote E, Sexton JO, Ederer G (2013)
Improved forest change detection with terrain illumination corrected Landsat images. Remote Sensing of Environment 136: 469-483.
CrossRef | Gscholar
(37)
Teillet PM, Guindon B, Goodenough DG (1982)
On the slope-aspect correction of multispectral scanner data. Canadian Journal of Remote Sensing 8: 84-106.
CrossRef | Gscholar
(38)
Tucker CJ (1977)
Asymptotic nature of grass canopy spectral reflectance. Applied Optics 16: 1151-1156.
CrossRef | Gscholar
(39)
Umarhadi DA, Danoedoro P, Wicaksono P, Widayani P, Nurbandi W, Juniansah A (2018)
The comparison of canopy density measurement using UAV and hemispherical photography for remote sensing based mapping. In: Proceedings of the “4th International Conference on Science and Technology”. Yogyakarta (Indonesia) 7-8 Aug 2018. Institute of Electrical and Electronics Engineers - IEEE, IEEEXplore, pp. 1-5.
CrossRef | Gscholar
(40)
Warnes GR, Bolker B, Lumley T (2015)
gtools: various R programming tools. R package version 3.5.0.
Online | Gscholar
(41)
Weston S (2017)
foreach: provides foreach looping construct for R. R package version 1.4.4.
Online | Gscholar
(42)
Weston S (2018)
doParallel: foreach parallel adaptor for the “parallel” package. R package version 1.0.14.
Online | Gscholar
(43)
Wood SN (2011)
Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 73: 3-36.
CrossRef | Gscholar
 

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