TY - JOUR
T1 - Using remote sensing and spatial analysis of trees characteristics for long-term monitoring in arid environments
AU - Isaacson, Sivan
AU - Blumberg, Dan G.
AU - Rachmilevitch, Shimon
AU - Ephrath, Jhonathan E.
AU - Maman, Shimrit
PY - 2016/4/1
Y1 - 2016/4/1
N2 - Trees play a significant role in the desert ecosystem by moderating the
extreme environmental conditions including radiation, temperature, low
humidity and small amount of precipitation. Trees In arid environments
such an Acacia are considered to be `keystone species', because they
have major influence over both plants and animal species. Long term
monitoring of acacia tree population in those areas is thus essential
tool to estimate the overall ecosystem condition. We suggest a new
remote sensing data analysis technique that can be integrated with field
long term monitoring of trees in arid environments and improve our
understanding of the spatial and temporal changes of these populations.
In this work we have studied the contribution of remote sensing methods
to long term monitoring of acacia trees in hyper arid environments. In
order to expand the time scope of the acacia population field survey, we
implemented two different approaches: (1) Trees individual based change
detection using Corona satellite images and (2) Spatial analysis of
trees population, converting spatial data into temporal data. A map of
individual acacia trees that was extracted from a color infra-red (CIR)
aerial photographs taken at 2010 allowed us to examine the distribution
pattern of the trees size and foliage health status (NDVI). Comparison
of the tree sizes distribution and NDVI values distribution enabled us
to differentiate between long-term (decades) and short-term (months to
few years) processes that brought the population to its present state.
The spatial analysis revealed that both tree size and NDVI distribution
patterns were significantly clustered, suggesting that the processes
responsible for tree size and tree health status (i.e., flash-floods
spatial spreading) have a spatial expression. The distribution of the
trees in the Wadi (ephemeral river) was divided into three distinct
parts: large trees with high NDVI values, large trees with low NDVI
values and small trees with medium NDVI values. Using these results, we
divided the Wadi into three sections, each representing a unique
combination of long and short-term geo-hydrologic processes affecting
the acacia trees. The next phase of the temporal data extraction
procedure was to implement change detection regarding each of the Wadi
sections defined by the spatial analysis result. For this purpose we
used a corona image from 1968 and applied individual based change
detection. The result of the change detection supported our findings of
changes in the geo-hydrology regime from long to short term scale.
AB - Trees play a significant role in the desert ecosystem by moderating the
extreme environmental conditions including radiation, temperature, low
humidity and small amount of precipitation. Trees In arid environments
such an Acacia are considered to be `keystone species', because they
have major influence over both plants and animal species. Long term
monitoring of acacia tree population in those areas is thus essential
tool to estimate the overall ecosystem condition. We suggest a new
remote sensing data analysis technique that can be integrated with field
long term monitoring of trees in arid environments and improve our
understanding of the spatial and temporal changes of these populations.
In this work we have studied the contribution of remote sensing methods
to long term monitoring of acacia trees in hyper arid environments. In
order to expand the time scope of the acacia population field survey, we
implemented two different approaches: (1) Trees individual based change
detection using Corona satellite images and (2) Spatial analysis of
trees population, converting spatial data into temporal data. A map of
individual acacia trees that was extracted from a color infra-red (CIR)
aerial photographs taken at 2010 allowed us to examine the distribution
pattern of the trees size and foliage health status (NDVI). Comparison
of the tree sizes distribution and NDVI values distribution enabled us
to differentiate between long-term (decades) and short-term (months to
few years) processes that brought the population to its present state.
The spatial analysis revealed that both tree size and NDVI distribution
patterns were significantly clustered, suggesting that the processes
responsible for tree size and tree health status (i.e., flash-floods
spatial spreading) have a spatial expression. The distribution of the
trees in the Wadi (ephemeral river) was divided into three distinct
parts: large trees with high NDVI values, large trees with low NDVI
values and small trees with medium NDVI values. Using these results, we
divided the Wadi into three sections, each representing a unique
combination of long and short-term geo-hydrologic processes affecting
the acacia trees. The next phase of the temporal data extraction
procedure was to implement change detection regarding each of the Wadi
sections defined by the spatial analysis result. For this purpose we
used a corona image from 1968 and applied individual based change
detection. The result of the change detection supported our findings of
changes in the geo-hydrology regime from long to short term scale.
M3 - Meeting Abstract
SN - 1029-7006
VL - 18
JO - Geophysical Research Abstracts
JF - Geophysical Research Abstracts
ER -