Bersoft Image Measurement (BIM) is designed as a flexible tool for acquiring, measuring and analyzing digital images. The measurements may be done by pointing and clicking or in an automated way, when doing statistical or analytical measurements. BIM can load many different types of images, including DICOM files, and also supports image acquisition from most TWAIN scanners. Angle, distance, perimeter, area, point and line measurements may be done using by using the tools in the Tools Palette. Spatial calibration is available to provide real world dimensional measurements such as kilometers, centimeters, millimeters, nanometers, microns, cm, miles, etc,. for both linear and The measurements are drawn over a measurement layer, so the original image is not altered in any way.
Now includes an image Database.
For convenient further statistical analysis the measurements can be exported as CVS, HTML, DOC or ASCII file formats. They also can be send directly to Excel or copied and pasted to any other program.
Statistical measurement can be done either on a selected image area, the full image, or on several images at once.
Count, mean, median, minimum, maximum, range, variance, standard deviation, standard error, coefficient of variation, skew, kurtosis and frequencies are supported.
Images can be visualized and compared in different ways, using histograms (from images or selections), generating false color images, subtracting image backgrounds, merging images, adjusting brightness, gamma and contrast, inverting image colors, manipulating channels, applying spatial convolutions with user-defined convolution masks and morphing filters.

A meteorological drought can be seen as a result of a precipitation shortage or which is defined as the lack of precipitation over a region for a period of time. It is usually region-specific because the atmospheric conditions in different areas are highly variable in space and time. Depending of the duration of meteorological drought, the soil humidity will be reduced (shorter term) and the groundwater table can be dropped (longer term). Meteorological drought is signaled by indicators intrinsic to weather data and precedes the onset of specic impacts, i.e. additional kinds of drought. There are different indices for monitoring and assessing the amount of meteorological droughts. Through the rain-based meteorological drought, we can track the amount of drought We developed the MDM (Meteorological Drought Monitoring) software application for calculating eight rain-based meteorological drought indices, namely: SPI (Standardized Precipitation Index), DI (deciles index), PN (Percent of Normal Index), RAI (Rainfall Anomaly Index), EDI (effective drought index), CZI (China-Z index), MCZI (modified CZI), and ZSI (Z-Score Index) in form of yearly, seasonally, monthly and moving average for 3, 6, 9, 12, 18, 24, and 48 months. Because using different drought indices at a given time can show drier or wetter than usual conditions (Smakhtin and Hughes, 2007), user-friendly software is a critical tool for calculating and comparing multiple locations, time periods, and data source influences efficiently. The MDM software package currently bases calculations on two sources of data. The first is a synoptic station data file, which includes daily precipitation in excel format. The second one is a database of daily precipitation from AgMERRA, available for the Middle-East region. The user can click the map on the desired point in the package and calculate all indices for that 0.25 degree grid location. There is a complete help file in the package, which describes all setup steps.

In order to estimate flammability in forest and wild land areas of USA, Keetch and Byram (1968) developed a drought index namely Keetch-Byram drought index (KBDI). Conceptually, using daily precipitation and daily maximum temperature, KBDI has the potential to describe moisture deficiency in upper soil layer (Keetch and Byram 1968). KBDI that use minimum number of meteorological parameters (precipitation, maximum temperature), was originally developed for the southeastern forest of the United States and has been extensively used for re potential assessment in the U.S. (Keetch and Byram 1968). This index, which conceptually describes the soil moisture (Dolling et al. 2005) with several simple criteria, is based on the amount of daily precipitation, daily maximum temperature and mean annual precipitation. The output varies from 0 to 800, where 0 represents the soil saturation and 800 indicates the most severe drought. Generally, the output is categorized into four classes with 200 intervals. Each class represents a particular concept. More detailed explanation for the calculations of this index can be found in Keetch and Byram (1968) and Janis et al. (2002). We’ve developed the KBDIS (Keetch-Byram Drought Index Software) for calculating Keetch-Byram Index as a drought index. You can import your data as excel file and calculate KBDI in yearly, seasonally, monthly, and daily Formats. This software can draw linear, Columnar, and box-plot graphs. The user can easily determine the field capacity option in this tool.