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Article

Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data

1
Department of Computer Science, GIS Division, NIIT University, Neemrana 301705, India
2
Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran
3
Department of Remote Sensing, University of Würzburg, D-97070 Würzburg, Germany
4
Department of Biology, McGill University, Montreal, QC H3A 1B1, Canada
*
Author to whom correspondence should be addressed.
Academic Editors: Nikos Koutsias, Alexandra Gemitzi and Sofia Bajocco
Remote Sens. 2021, 13(19), 3965; https://doi.org/10.3390/rs13193965
Received: 8 September 2021 / Revised: 28 September 2021 / Accepted: 29 September 2021 / Published: 3 October 2021
(This article belongs to the Special Issue Satellite Remote Sensing Phenological Libraries)
Freely available satellite data at Google Earth Engine (GEE) cloud platform enables vegetation phenology analysis across different scales very efficiently. We evaluated seasonal and annual phenology of the old-growth Hyrcanian forests (HF) of northern Iran covering an area of ca. 1.9 million ha, and also focused on 15 UNESCO World Heritage Sites. We extracted bi-weekly MODIS-NDVI between 2017 and 2020 in GEE, which was used to identify the range of NDVI between two temporal stages. Then, changes in phenology and growth were analyzed by Sentinel 2-derived Temporal Normalized Phenology Index. We modelled between seasonal phenology and growth by additionally considering elevation, surface temperature, and monthly precipitation. Results indicated considerable difference in onset of forests along the longitudinal gradient of the HF. Faster growth was observed in low- and uplands of the western zone, whereas it was lower in both the mid-elevations and the western outskirts. Longitudinal range was a major driver of vegetation growth, to which environmental factors also differently but significantly contributed (p < 0.0001) along the west-east gradient. Our study developed at GEE provides a benchmark to examine the effects of environmental parameters on the vegetation growth of HF, which cover mountainous areas with partly no or limited accessibility. View Full-Text
Keywords: Hyrcanian forest; NDVI; phenology; Sentinel-2; TNPI; World Heritage Sites; Google Earth Engine Hyrcanian forest; NDVI; phenology; Sentinel-2; TNPI; World Heritage Sites; Google Earth Engine
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MDPI and ACS Style

Khare, S.; Latifi, H.; Khare, S. Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data. Remote Sens. 2021, 13, 3965. https://doi.org/10.3390/rs13193965

AMA Style

Khare S, Latifi H, Khare S. Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data. Remote Sensing. 2021; 13(19):3965. https://doi.org/10.3390/rs13193965

Chicago/Turabian Style

Khare, Suyash, Hooman Latifi, and Siddhartha Khare. 2021. "Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data" Remote Sensing 13, no. 19: 3965. https://doi.org/10.3390/rs13193965

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