FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA

This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to...

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Main Authors: E. Nasanbat, S. Sharav, T. Sanjaa, O. Lkhamjav, E. Magsar, B. Tuvdendorj
Format: Article
Language:English
Published: Copernicus Publications 2018-04-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/1299/2018/isprs-archives-XLII-3-1299-2018.pdf
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spelling doaj-14bd027661dd4de989855e1b1b7e59092020-11-24T21:03:59ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-04-01XLII-31299130410.5194/isprs-archives-XLII-3-1299-2018FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIAE. Nasanbat0E. Nasanbat1S. Sharav2T. Sanjaa3O. Lkhamjav4E. Magsar5E. Magsar6B. Tuvdendorj7Information and Research Institute of Meteorology, Hydrology and Environment, Juulchiny street-5, Ulaanbaatar 15160, MongoliaMongolian Geospatial Association, P.O. Box 24/38, Ulaanbaatar 15141, MongoliaSchool of Applied Sciences, Mongolian University of Science and Technology, Ulaanbaatar, MongoliaSchool of Applied Sciences, Mongolian University of Science and Technology, Ulaanbaatar, MongoliaMongolian Geospatial Association, P.O. Box 24/38, Ulaanbaatar 15141, MongoliaMongolian Geospatial Association, P.O. Box 24/38, Ulaanbaatar 15141, MongoliaNational Agency for Meteorology and Environmental Monitoring, Juulchiny street-5, Ulaanbaatar 15160, MongoliaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth(RADI), Chinese Academy of Sciences Olympic Village Science Park,W. Beichen Road, Beijing 100101, ChinaThis study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/1299/2018/isprs-archives-XLII-3-1299-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author E. Nasanbat
E. Nasanbat
S. Sharav
T. Sanjaa
O. Lkhamjav
E. Magsar
E. Magsar
B. Tuvdendorj
spellingShingle E. Nasanbat
E. Nasanbat
S. Sharav
T. Sanjaa
O. Lkhamjav
E. Magsar
E. Magsar
B. Tuvdendorj
FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet E. Nasanbat
E. Nasanbat
S. Sharav
T. Sanjaa
O. Lkhamjav
E. Magsar
E. Magsar
B. Tuvdendorj
author_sort E. Nasanbat
title FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
title_short FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
title_full FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
title_fullStr FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
title_full_unstemmed FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
title_sort frequency analysis of modis ndvi time series for determining hotspot of land degradation in mongolia
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2018-04-01
description This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/1299/2018/isprs-archives-XLII-3-1299-2018.pdf
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