In order to enable monitoring of the sequestered and emitted carbon quantities as well as changes, both positive and negative, in the carbon pool size (sink), it is necessary to develop fast and simple methods that can be used to collect large amounts of data on vast areas in order to calculate these parameters. The aforementioned can be achieved by implementing LIDAR technology for the calculation of above-ground biomass in vast areas and, consequently, for the calculation of sequestered carbon i.e. carbon dioxide, which is the first research of this kind in the Republic of Croatia. One of the goals of this research is to create a model for determining above-ground biomass of degraded forest areas in thicket stadium (hypothesis 1), which is one of the main missing data for determining sequestered carbon quantities and changes in carbon sinks needed to create the Greenhouse Gasses National Inventory Report. Also, the influence of thinner point cloud to the final result (in comparison to the initial one) shall be established (hypothesis 2). Lower density LIDAR cloud utilization with the aim of achieving satisfactory and precise enough data directly correlates to the costs of scanning that is the single highest cost in such projects. A part of this research was conducted in the lowland area with altitude of approximately 120 m, whilst the other part of research was conducted in the hilly area with altitudes ranging from 250 to 550 m. Through field data collection (68 plots), processing of LIDAR data (average denstiy of 1.38 points/m2) and in the end regression analyses, regression models for the assessment of degraded forests biomass of lowland and hilly vegetation zone were developed. It was determined that the model for the lowland area had determination coefficient (R2) of 0.75, whilst for hilly area this coefficient was 0.60. The results also show that cloud point density does not affect appropriateness of the model to a certain extent (up to 0.4 points/m2) which successfully confirms both hypotheses. The application of created models to the entire area enabled calculation of forest above-ground biomass values for the whole researched area. Also, the comparison of appropriateness of thinner point cloud based models for the implementation on the entire area was conducted. Finally, apart from the list of practical conclusions and limitations that have arisen during the research (time incompliance of LIDAR and field data, lack of local models for the assessment of above-ground tree biomass, etc.), recommendations for further researches are stated ie. overcoming existing restrictions, repeating this kind of the research for the bio-geographic areas that were not encompassed with this research and introduction of additional data.