Geospatial Intelligence

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Now showing 1 - 9 of 9
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    China’s High-Altitude Heliports: Examining PLA Helicopter Force Changes
    (2023-05) Humphrys, Matt
    The Chinese People’s Liberation Army (PLA) continues to expand its heliport infrastructure throughout the Western Theater Command (WTC). The Western Theater, particularly Tibet and Xinjiang, host the highest average elevation in the world. Extreme elevation, coupled with harsh geographic and environmental conditions, demand a robustly equipped, trained, and resourced vertical lift program to be effective. While the PLA has begun to build the infrastructure to support a budding domestic helicopter fleet designed to face these challenges and provide an alternative to Russian equipment, it is unclear if the PLA can employ its equipment and train its force to execute its vision. Furthermore, the peculiar design and location of its heliports raise new questions about PLA capabilities in the region.
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    A GEOSPATIAL STRATEGY TO DETECT AND IDENTIFY POTENTIAL CLANDESTINE MASS GRAVES IN UKRAINE
    (2022-12) Hobbs, Tressa
    This study seeks to improve the understanding of how social media analysis and hyperspectral remote sensing can be applied in a multi-modal target-centric approach to detect and identify clandestine mass graves in Ukraine. Fifteen mass graves have been discovered in central, southern, and eastern Ukraine since the Russian invasion of Ukraine on 24 February 2022. This geospatial strategy recommends conducting retroactive searches for additional potential clandestine mass graves and prospective searches for suspicious activities that may be indicative of future or ongoing potential clandestine mass grave locations in areas currently under Russian control. This social media collection and analysis will direct targeted hyperspectral imagery collection on areas of interest. The resulting hyperspectral data will be further analyzed using spectral signature libraries, statistical methods, and vegetation indices to identify any vegetation anomalies with unusually high or low Nitrogen concentrations - a proxy signature for clandestine graves. This research will first present background information on the historical use of clandestine mass graves and the targeting of civilians in conflict. Second, it will examine the methodologies presented in this proof-of-concept. Third, it will evaluate the limitations of this geospatial strategy. This thesis provides new insights for detecting and identifying clandestine mass graves in Ukraine and provides potential audiences with another tool to locate and document these atrocities. Primary Reader and Advisor: Jack O’Connor Secondary Reader: Anonymous
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    Remote Sensing, Machine Learning, and Change Detection Applications for Land Cover Studies: A Geospatial Analysis of Two Liberian Proposed Protected Areas
    (2021-12) Burch Jones, Evelyn J.
    This study seeks to improve understanding of land use and land cover (LULC) change in two of Liberia’s proposed protected areas (PPAs), to characterize the existing and potential threats to the natural environment in these areas, and to examine the planning implications for establishing these PPAs as national parks. The PPAs—Zwedru and Gbi-Krahn Bassa—cover roughly 1,300 square kilometers of land in Grand Gedeh County, southeastern Liberia. Both PPAs are located within the Sapo-Tai Forest Complex in West Africa’s increasingly fragmented Upper Guinean Forest (UGF) ecoregion. Sentinel-2 multispectral satellite imagery from 2016 and 2020 collected by the European Space Agency (ESA) was used to conduct a support vector machine (SVM)-based classification of generalized land cover types in both PPAs in order to determine changes in land cover categories between the two time periods. Various spectral indices were incorporated to assess in detail areas where deforestation activity was detected, including after the LULC study period. Other sources of vector and raster data were integrated to analyze topography, accessibility, and anthropogenic change within the PPAs, to better understand the unique situation and challenges of each area. Additionally, a change detection case study of new bare soil detections identified between Normalized Difference Vegetation Index (NDVI) renderings of the 2016 and 2020 satellite imagery was conducted for Zwedru PPA. This research will first provide background information on Liberia and the factors driving land cover change in the remaining portions of the UGF ecoregion. Second, it will examine the approach and methodologies used in this study. Third, it will present the results and discuss their implications based on a geospatial assessment of the PPAs and their surroundings, and fourth, it will propose a strategy for monitoring change in Liberia’s existing and proposed protected areas across the country, based on the insight gained from this analysis. This thesis contributes new insight into necessary considerations for the potential establishment of the PPAs as national parks, offering reproducible methods that can be applied to additional PPAs within and beyond Liberia.
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    A Geospatial Strategy to Locate Future Chinese ICBM Silo Fields
    (2021-12) Faust, Jason G.
    This Capstone report analyzes two recently constructed missile silo fields in China in an effort to identify key geospatial and geological characteristics that can be used to define a search strategy for future silo field construction. This report incorporates statistical analysis techniques that will constrain the areas under consideration based on nearness to railroads which will then incorporate multiple raster layers that will characterize the region constrained region, and then remove parcels of land that do not have the adequate characteristics to accommodate rapid silo construction. Based on the size of the delivery system(s) the People’s Liberation Army Rocket Force (PLARF) are installing, the biggest factor in this study will be depth to bedrock. Other factors include surface slope, land cover classification, and whether a given site is within range of conventional US missiles. It is important to researchers and analysts in and outside the Intelligence Community to have a systematic method for defining search strategies, and this report serves as a foundational first step in that effort.
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    A Strategy to Detect and Monitor Coca Production in Colombia, Peru, and Bolivia
    (2021-08) Ford, Aaron
    South America produces 90% of the world’s cocaine supply. Cocaine is the third most consumed illicit substance behind marijuana and abused pharmaceutical opiates. Trends in top consumer countries are pointing toward marijuana legalization, making cocaine more important to narcotic organizations as they compete with legitimate marijuana producers. Cocaine production itself is under threat due to the efforts of the Colombian government to reduce coca/cocaine production within their borders. Potential expansion in production and continued concealment efforts will require reliable means of identification by technical means. Identification and tracking efforts would focus on the three primary producer countries: Colombia, Peru, and Bolivia. This paper puts forth a framework for coca detection that limits costs and manpower. The primary method utilizes hyperspectral sensors, which obtain images across spectral bands. Spectra derived from technical sensors identifies and catalogs signatures associated with cocaine production. Utilizing a library of signatures, a substance can be identified with high fidelity. Utilizing the primary method areas of interest can be narrowed down the highest yielding regions. Adhering to a strict HIS collection window and acquisition of commercial imagery will yield the best results. The resulting data can be displayed in easily digestible products that can be disseminated rapidly. These results will alert the customer of any nefarious activity allowing them to act in a timely manner. An estimated budget of the first year's expenses is included along with operational recommendations to include hardware, software, and personnel.
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    Predicting Locations of Emerging Hate Groups in Maryland Utilizing Social Identity Theory
    (2020-12) McAvoy, Shannon
    In this analysis, principles behind Social Identity Theory were utilized as a basis to determine whether or not the demographic factors of income and racial diversity can predict where a hate group will likely emerge. This thesis will be tested using the state of Maryland. Specifically, the paper will help identify whether or not areas with a low income and a high diversity will become a breeding ground for hate organizations. To answer this question, the 2010 US census data on income and race dispersion throughout this state were collected. After the race dispersion was converted into a diversity index, it was concluded that areas of low income and high diversity could not explain why hate groups existed in their 2010 locations. However, these two demographic factors did correlate with the 2019 locations of these organizations. Therefore, it was concluded the Social Identity Theory could be utilized to anticipate and possibly predict where hate groups may emerge in Maryland in the future. The paper will also identify additional questions that it is hoped can be addressed by the 2020 census data when it is made available.
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    Geospatial Intelligence and Reducing and Mitigating the Spread of the Coronavirus in Marion County Indiana
    (2020-08) Valverde, Isabel
    This Capstone report assesses real-time data and presents current concerns the city of Indianapolis is facing today with the spread of the Coronavirus. Geospatial intelligence is also incorporated to provide mitigation procedures to reduce continual spread of the virus and dispersion of vaccines. Additionally, a business plan has been designed to describe and identify procedures necessary for an organization to answer intelligence requirement questions. This project will use the intelligence cycle to properly evaluate factors to prevent, protect, mitigate, and respond to decrease the spread of the virus. Implementing the intelligence cycle will also provide a better understanding on the spread of the Coronavirus in the city of Indianapolis and surrounding counties.
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    An Unclassified Geospatial Intelligence Analysis of the Capabilities of the Iranian Revolutionary Guard Corps Navy Using Google Earth
    (2020-08) Green, Thomas A.
    This paper aims to determine whether or not Google Earth is a useful tool to conduct geospatial intelligence analysis at an unclassified level over an area that poses a threat to U.S. National Security. This study leverages existing high-resolution commercial imagery to analyze port facilities within the southern Persian Gulf, Strait of Hormuz, and Gulf of Oman that maintains a possible Islamic Revolutionary Guards Corps (IRGCN) presence. It was found Google Earth could be a useful alternative to conduct temporal analysis over an area of interest, but not recommended for timely review. The gaps in imagery did, however, assist in determining three key findings based on imagery observations. These three findings are: construction remains on-going at likely most IRGCN ports, civilian ports are near or are part of a possible IRGCN port, and gaps in imagery collection preclude complete construction chronologies for all the targets on the list. There is moderate confidence with these findings that Iran will leverage the IRGCN within the southern Persian Gulf and Strait of Hormuz to gain naval superiority within the region. The geospatial evidence for this strategy includes a continuation of bolstering defenses at port facilities to improve infrastructure and an increase in naval presence. Open-source reporting also assists imagery observations with identifying a layered defense strategy, including the presence of anti-ship and hybrid air-to-air defense weapons and an increase of fast-attack small boats at several port facilities. The baseline descriptions of these facilities support key findings and implications about the extent of Iranian construction efforts to possible IRGCN port facilities. There is moderate confidence these construction efforts will allow Iran to use IRGCN to employ the country’s passive defense theory. This theory consists of the employment of hybrid warfare, which allows a naval force to mobilize, intimate, and provoke neighboring countries and potentially overcome more superior naval forces without direct conflict. Despite the key findings, implications, and facility descriptions observed in imagery, there remains a large amount of uncertainty. The exclusive usage of Google Earth as a tool to conduct geospatial intelligence analysis is inadequate for timely imagery analysis; however, it is useful for a multi-year study.