TY  - JOUR
A1  - Khare, Suyash
A1  - Latifi, Hooman
A1  - Khare, Siddhartha
T1  - Vegetation growth analysis of UNESCO World Heritage Hyrcanian forests using multi-sensor optical remote sensing data
T2  - Remote Sensing
N2  - 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.
KW  - Hyrcanian forest
KW  - NDVI
KW  - phenology
KW  - Sentinel-2
KW  - TNPI
KW  - World Heritage Sites
KW  - Google Earth Engine
Y1  - 2021
UR  - https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/24839
UR  - https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-248398
SN  - 2072-4292
VL  - 13
IS  - 19
ER  -