Affiliation:
1. Ramkhamhaeng University, Faculty of Education, Department of Geography, Bangkok, Thailand
Abstract
This work focused on Chiang Mai Province, Thailand, had 2 targets which were
1) to analyse spatial distribution patterns of hotspot and 2) to analyse a
relationship between hotspot and vegetation indices in the area. The
hotspots data of 2016 - 2020 which had a significant level > 70% were
gathered from MODIS satellite images, was provided by Fire Information for
Resource Management System (FIRMS). An analyse method was performed by
Nearest Neighbour Index (NNI) with Moran? s I to present spatial
distribution patterns and density of hotspot. Analysis of Getis - Ord Gi* statistic was for identify heat of hotspot comparing with surrounding area.
Moreover, vegetation indices values (Normalized Difference Vegetation
Index: NDVI, Soil Adjustment Vegetation Index: SAVI and Normalized
Difference Water Index: NDWI) was examined by satellite images of the same
period from Landsat 8 OLI to analyse a relationship between hotspot and each
vegetation index. The results illustrated that there were different number
of hotspots over 5 studying years, especially in 2016 which had the most
hotspot. The spatial distribution of hotspot patterns was classified as
clustered type (Getis - Ord Gi* statistic with Z-Score > 1.96) with
different hotspot density in each year. The area which had high heat was
found in upper and west area with medium to high hotspots density. The
hotspot and NDVI had relationship in contrast by a correlation coefficient
value at -.887 (r = -.887) with a significant level at .05. However, SAVI
and NDWI had no relationship with hotspot.
Publisher
National Library of Serbia
Subject
Atmospheric Science,Geology,Education,Geography, Planning and Development,Global and Planetary Change