We present a code which identifies individual clouds in crowded region using IMFORT interface within Image Reduction and Analysis Facility (IRAF). We define a cloud as an object composed of all pixels in longitude, latitude, and velocity that are simply connected and that lie above some threshold temperature. The code searches the whole pixels of the data cube in efficient way to isolate individual clouds. Along with identification of clouds it is designed to estimate their mean values of longitudes, latitudes, and velocities. In addition, a function of generating individual images (or cube data) of identified clouds is added up. We also present identified individual clouds using a 12CO survey data cube of Galactic Anticenter Region (Lee et al. 1997) as a test example. We used a threshold temperature of 5σ 5σ rms noise level of the data With a higher threshold temperature, we isolated subclouds of a huge cloud identified originally. As the most important parameter to identify clouds is the threshold value, its effect to the size and velocity dispersion is discussed rigorously.

We have reviewed three different techniques to estimate molecular cloud mass, and discussed the uncertainties involved. We found that determination of the most important parameter, the 13CO 13CO abundance, is not very sensitive to the real LTE conditions, and that any possible error in deriving LTE column density may not introduce an error in the total gas column density, as far as the visual extinction is established for the object cloud. The virial technique always endows the largest mass estimate as there are several uncertainties, even if the cloud is in virial equilibrium. The strong indicator of the cloud perturbation is the centroid velocity dispersion. The mass using CO luminosity is based on the empirical law, but weakly dependent on the virial assumption, thus it still gives a larger mass estimate. The mass discrepancy is likely to be inevitable, and a factor of two or three difference between mass estimates could easily be attributed to the uncertainties mentioned above. The LTE mass estimate may be the most reliable one if we use the relation visual extinction and 13CO 13CO column density of the object cloud, and the intercept is included.

We present two codes which estimates virial mass and LTE mass using IMFORT interface within IRAF (Image Reduction and Analysis Facility). It is discussed that threshold value (temperature or CO integrated intensity), which defines a reasonable cloud boundary and size, is the most important parameter determining accurate results. Several virial masses are to be obtained using the vir task, as well as three velocity dispersions including the centroid velocity dispersion, a turbulence indicator. LTE mass is to be estimated by using task lte as well as three by-product images. The 13CO 13CO abundance and threshold temperature of 13CO 13CO and 12CO 12CO peak temperatures are the most critical parameters in LTE technique.