​

​••••••>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.

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​••••••>Modern Technology in Transmission Lines​

​

As part of the federal Government's policy of modernizing the electrical grids, every transmission operator needs to asses the exact physical properties of their high voltage transmission lines. This assessment will help in achieving operational excellence by reducing the associated risks. Using modern technologies like LiDAR, it is possible to precisely map the transmission assets and predict changes based on various parameters. The vegetation risk can also be identified by using Transmission LiDAR.

​

​

​

​

​

​

​

​

​

​

According to the federal mandate, just identifying the vegetation risk will not be enough. The utility also needs to prioritize and plan to remove the vegetation which is a risk to the transmission lines. To ensure compliance, an audit able plan of action also needs to be created. Doing all these is not possible by the traditional methods.
 

On the other hand, modern remote sensing techniques in combination with state of the art analytics software help utilities to take the precise inventory including the accurate location of all substations, conductor and transmission towers with their exact geographical location. Moreover, Transmission LiDAR also helps in analyzing various on- field threats and provides the ways to remove those.

Modern technologies like airborne LiDAR are employed for the purpose of identification and mapping of the assets, ancillary structures and vegetation cover of a utility. But only data collection is not enough. So business analytics software is used to transpose this data into digital three dimensional models of the utility. This model is capable of determining line sag under different operating variables. As a result it is the perfect tool to detect unforeseen risks as well as realizing untapped potential of the utility.

The entire process is done in four stages. The first stage identifies the vegetation of the utility by Transmission LiDAR. It also involves preparation of the digital models from the collected data. The next step asses the risk by carefully analyzing the 3-D models. The measurement and prioritize of the risk factors are also done on this stage. In the third stage scheduling of risk removal is done. This stage also deals with executing the risk removal. The final stage involves documenting the entire procedure and auditing it. It is also checked if the work was done maintaining all the federal specifications.