The Rising Cost of IMINT and a Future Prospectus - Research Paper Example

Section/# The Rising Cost of IMINT and a Future Prospectus Introduction: Regardless of the metric that is analyzed, it is without question that the growth, proliferation, and constant change of technology have provided a definitive and measurable impact with respect to the way in which military intelligence is conducted. A litany of examples of course exists with regard to this dynamic; however, the one that will be analyzed and discussed in depth in this particular analysis is contingent upon the changes with respect to technology, and the corresponding costs associated with this, that are related to image intelligence (IMINT). Whereas all types of intelligence that can be gathered has a distinctive purpose and subset of potential users, the growth and proliferation, as well as increasing extent of cutting-edge technology, has created a situation by which IMINT faces a fundamental crisis. Ultimately, this particular branch of intelligence is one that has increasing relevance and potential within the current world. As such, the rising costs associated with maintaining on cups of relevance and technology with regard to IMINT has been steadily increasing over the past several decades; seemingly with no end in sight. Accordingly, this particular analysis will not only seek to analyze the current exhibition of this particular form of intelligence but also to denote the underlying reasons for why costs have been rising so exponentially as well as provide for potential levels of remedy that might be directed towards reducing these costs. Furthermore, shortcomings and drawbacks with respect to other proposed remedies will also be referenced in the hopes of providing a full and nuanced understanding of the problem at hand as well as the ways in which it might potentially be engaged. Hypothesis: The rising cost of technology has impacted the ability to process and analyze images and is affecting the exploitation of imagery intelligence. Body and Analysis: The rapid rate of technological growth and expansion has created undue difficulty for aspects of image intelligence. In much the same way that the average cost of a single fighter jet has risen exponentially over the past several decades, the cost of gathering and analyzing potentially salient intelligence information form of images is tracking along the same path. Even an individual that does not have formal training with respect to finance and accounting could realize the fact that such a path is unsustainable; especially considering the limited resources that the United States government will be able to provide to achieve a specific goals that image intelligence might exhibit within the coming years. As such, one of the key recommendations that have been made with respect to seeking to ameliorate the overall cost of image intelligence analysis and collection has to do with an approach that is contingent upon developing systems that are not in and of themselves final or complete. Although this might seem as a shortsighted strategy, individuals that promote this particular end indicate that this is one of the most salient approaches with regard to decreasing costs.1 The underlying reason behind this is contingent upon the understanding that incomplete systems, or in other words those that are functional yet allow for upgrades, are the most likely to reduce the overall cost of initial technological investment that will be evidenced in the coming years For instance, a system that is bought and a half page and is determined to fulfill a specific goal could likely be obsolete if the goals and metrics for intelligence analysis were to shift. As such, individuals that promote the strategy that has been denoted above indicate that image intelligence must be open to development and changes with respect to technology; facet of the current era that is all but guaranteed. Moreover, the high cost of initial technology and start up with respect to image analysis in the past has oftentimes been attributed to the fact that paradigms shifts with respect to technology are required virtually constantly. Additionally, scholars that analyze this particular situation indicate that the number and type of imagery that is expected to be exhibited within the future is likely to increase exponentially. Thus, the types of analysis that will need to be directed to these must improve commensurately without directly impacting upon overall cost.2 Naturally, this seems like an impossible situation. With changes in technology and the need to upgrade and refit systems both upstream and downstream of the data collection and analysis process, one could reasonably wonder how expense might be saved within the process and how changes in technology need not reflect a damaging impact upon the productivity, utility, or cost of the image intelligence community. As indicated above, the approach of ensuring that the technology of image intelligence is not too far down one specific road and at the same time is up to date yet reactive is a core consideration that must be made and necessarily implemented if the above dynamic is to be eventually realized. Conclusions: Another approach that has been put forward, and is particularly salient, at least in the mind of this particular analyst, has to do with balancing collection and analysis. When broken down to their most basic level, image intelligence is contingent upon to specific types of cost: the cost of original collection and the cost of analysis. As such, one of the most relevant means of decreasing costs and providing for future technological change within the arena of image intelligence is to seek to decrease the overall cost of collection of the intelligence and certainly preparing for an increased cost of data analysis; both in the form of individual employees and in the form of advanced technological packages, hardware, and software. The analysis has indicated up until this point that the changes in technology necessarily reflect a higher cost with respect to image intelligence. However, analysts also indicate that technology in and of itself need not necessarily reflect higher cost with respect to image collection. The reason that is provided for this has to do with the belief that improvement in technology could drastically reduce collection costs by providing further coverage of specific areas and reductions in the overall initial investment that would be required for this coverage. One specific remedy that is put forward has to do with the slow yet gradual reduction in the cost of satellite imagery collection. Within the past, sophisticated, complex, and exorbitantly expensive satellites were required as a function of performing image gathering from around the globe. Due to the limited scope and coverage that these satellites could provide any given time, it was necessary to blanket the earth with many of these extremely high cost satellites. As a function of continuing to provide up-to-date and relevant image collection. Naturally, the drawback that was experience with respect to this has to do with the fact that the maintenance and sustainment, as well as the creation of further such satellites, created a dynamic by which costs of intelligence gathering were disproportionately directed towards initial intelligence gathering; not towards the analysis of these images. Point to the belief that yet, individuals that believe that technology can provide for a reduced cost of image collection point to the fact that small satellite, fulfilling a variety of different functions within the private sector, have indicated that the cost of operating a particularly complex satellite over a period of time, and seeking to blanket the earth with a particular service, has dropped significantly.3 With this in mind, the hope is that the extraordinarily expensive satellites that are limited in scope and require continual upkeep and sustainment can be exchanged for small satellite that can have a wider reach and a greatly reduced cost. The underlying benefit of all of this is of course the fact that a greater percentage of the overall monetary allotments that image intelligence received each and every year and in turn be devoted towards image analysis and the technologies that can be utilized as a function of this. In tandem with the understanding that has been presented above, the expectation that the cost of image analysis will continue to rise is a fair indication that seeking to reduce the cost of image collection is a relevant approach to addressing the broader issues that are evidenced within this particular field of the intelligence community.4 Another inherent issue that has been discussed at length within the intelligence community and by experts that have sought to analyze it is with regard to the fragmented nature of research and development that this particular branch of intelligence is prone to reveal. Due to the fact that a handful of government agencies all have aspect of image intelligence, nearly each and every one of them as a certain level of research and development that is currently being performed as a function of improving image intelligence and analysis. However, as illustrated above, these programs are not communicating with one another and exhibit strong levels of fragmentation; leaving some industry analysts to point to the fact that singularity with regards to image intelligence should be performed. However, the flip side of this singularity is that you image intelligence were brought under a single agency, such as the NSA, the overall ability of such an entity to speak to the unique needs by which each of the different image intelligence agencies had originally been established, would likely be greatly reduced – at least as compared to the paradigm that is currently exhibited. Instead, a far better approach would be to ensure that research and development with respect to image intelligence be forwarded on to a central and overarching committee that would seek to compare and contrast the differences between the ways in which these agencies and entities of government intelligence sought to promote the process. According to a staff study presented to the House of Representatives with regard to technology, cost, and issues relating to Image Intelligence, the following was indicated: “The main problem areas we see with the current structure is that the process of imagery program management/planning, research and development (R&D), collection, processing, dissemination, and standards is highly fragmented amongst the entities that are tasked with such goals.5 Additionally, it is also recommended that at least some small component of centralization is affected with respect to the many different agencies that are currently tasked with image gathering and analysis. By means of accomplishing this, it is at least tangentially possible for these entities to operate in a more effective manner. Nevertheless, the loss of efficiency and hardships of accomplishing such a dynamic shift would likely be profound and create undue hardships with respect to the way in which intelligence is gathered and analyzed. Finally, the process as it exists within the current era is untenable. The rate of technological change and the rising expense of engaging with new technologies to effect the goals of IMINT represents a situation in which vital components of the way in which this process must be altered to ensure that the intelligence needs of the United States can continue to be met; even as technology and its costs represent pressures on the way that this is conducted. The recommendations and conclusions that have been drawn in the analysis above help to indicate how this process might take place; however, this should not serve as a full and complete overview of the process by itself. The reason behind this is of course the fact that the process of data and image collection, and all its ancillary parts within different agencies, is immeasurably complex; and thus, tweaking any one part of it in the hopes of making it better is not necessarily something that is guaranteed to give an immediately positive result. However, by considering the costs and benefits of the scenarios that have been indicated, the reader can be more informed with regard to the way in which dynamics of this problem can be addressed and a slow and gradual shift towards a more sustainable platform and approach to image collection and analysis can be engendered within these respective agencies in the coming years. Bibliography Fulghum, David A. 1997. "DARPA looks anew at hidden targets." Aviation Week & Space Technology 146, no. 1: 56. Academic Search Complete, EBSCOhost (accessed August 23, 2014). Macarescu, Andrei. 2011. 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