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••••••>What is the necessity of LiDAR data related to landscape?

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••••••>What is the necessity of LiDAR data related to landscape? Powered By Docstoc
					       ••••••>What is the necessity of LiDAR data related to
                            landscape?

The reason for LiDAR vegetation Mapping is to identify the reason for climate change. The climate
change is the one that happen due to reduced emission that occurs from forests due to deforestation and
degradation. So it is necessary to map and monitor tropical forest carbon stocks areas and emission
areas in the geographic area. LiDAR Mapping companies, by using satellite imaging, air borne light
detection and ranging and field plots the geography mapping can be done, to identify these areas. In
this way we can monitor key natural resources through geographic mapping and prevent them from
decaying.

How LiDAR map is done?

We had applied variety of multiple linear regression models and subset from a group of twenty six
predictor variables derived from discrete-return LiDAR data (two dimensional post spacing), advanced
land image (ALI), multi spectral (30m) and panchromatic (10m) data or variables from geographic X,
Y and Z locations to obtain a LiDAR Vegetation Mapping. Generally speaking, LiDAR-derived
variables had greater utility than ALI variables to predict the response variables especially to predict
the values in basal areas. The height variables of LiDAR are most useful for predicting basal areas.
LiDAR intensity variables are the one, for predicting free density. These above said variables in the
above statement can be said as LiDAR canopy cover variables.

LiDAR Mapping companies, apply Natural logarithm are applied to these variables modeled for
predicting basal area values. After the above research and applying variables and obtaining an
appropriate model we use the model with remote sensing technology.

We compared the utility of discrete-light return detection and images obtained through LiDAR and we
tried the integration of above concepts used in these above processes for modeling and mapping basal
landscape areas and landscape density areas of forest Using conventional remote sensing methods, by
means of reforestation and aerial photography by which a thick canopy can be established for mapping
basal landscape areas. In April 2004, ALS mapping mission acquired earth’s topographic data. This
was done to identify headwater channels and gullies in the forest and thereby to identify as a separate
identity in the morphological information. Comparisons are made with field traverses using differential
GPS and reference cross sections. LiDAR data provide accurate information. The ability of LiDAR data
is to map gullies and channels in a forested landscape and to improve channel network maps and
topological models. The purpose of LiDAR data is to extract gully cross-section morphologic
information under forest canopy. The LiDAR data is helpful for orienting flights over gullies. LiDAR
data helps to differentiate areas between vegetation and ground surfaces.


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