" ... The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist's most cited papers and the number of citations that they have received in other publications....."
The h-index is an indicator of a researcher's lifetime impact in their field; or, a measure of impact across many fields.
When one scientist publishes n articles and gets cited n times, an h-index or h-factor of n results. This rewards the publication of many good articles (but few poor ones).
It is difficult to increase your h-index through self-citation (a common problem). One or a few "hits" will not alone improve your H-factor.
The h-index will become reliable once you have a substantial production of research output; it is important to emphasize a single number cannot describe any scholar, and the h-index is only one measure of their impact.
Since Hirsch introduced the h-index in 2005, this measure of academic impact has garnered widespread interest as well as proposals for other indices based on analyses of publication data such as the g index, h (2) index, m quotient, r index, to name a few. Several commonly used databases, such as Elsevier’s SciVerse Scopus, Thomson Reuters’ Web of Science, Google Scholar’s Citations and Microsoft’s Academic Search, provide h-index values for authors.
The h-index can be manually determined using citation databases such as Scopus and the Web of Science.