Adding Spatial Context to the April 17, 1975 Evacuation of Phnom Penh: How Spatial Video Geonarratives Can Geographically Enrich Genocide Testimony

Abstract

Between 1975 and 1979, upwards of two million men, women, and children perished from starvation, disease, exhaustion, inadequate medical care, torture, murder, and execution during the Cambodian genocide. Within this context, the forced evacuation of Phnom Penh has figured prominently in the literature, especially with regard to the violence encountered on the route. To date, however, there has been no empirical reconstruction of the evacuation. Here we address this deficiency, while simultaneously presenting a novel geospatial approach that can be utilized to collect, map and analyze interviews in a more appropriate manner than by more traditional geographic information systems (GIS) use. We utilize a spatial video geonarrative to provide a geographically-supported reconstruction of the forced evacuation of Phnom Penh through the collection of first-hand accounts taken while retracing the route. We add previously unavailable, contextualized, spatial insights to this forced evacuation, including findings on why the bridges acted as choke points, leading to increased violence. Moreover, in some instances the direction of the march turned back towards the city because of the road configuration which again led to a choke point as two columns merged. In presenting these types of contextualized, spatial details we contribute to both the specifics of the Cambodian genocide, and to how thick mapping and inductive visualization can enrich similar research in the humanities Key Words: Cambodian genocide, forced evacuation, GIS, spatial video geonarrative. Genocide testimony is vital in terms of remembering, understanding, prosecuting, and then archiving horrific events (Caswell 2014; Weld 2014). Yet while the focus on these testimonies is, understandably, the perspective of the individual, what receives less attention is the detailing of the spatial-specifically, understanding the places of importance and the geographic context in which events occurred. For example, between 1975 and 1979 upwards of two million men, women, and children perished from starvation, disease, exhaustion, inadequate medical care, torture, murder, and execution during the Cambodian genocide (de Walque 2006; Heuveline 1998; Vickery 1988). One of the beginning phases of this genocide was the forced evacuation of Phnom Penh and other cities. Figure 1 displays the generalized movement of people away from urban centers under Khmer Rouge rule and in so doing it appears to support the perspective of urbicide, which is the deliberate targeting and destruction of urban forms (cf. Coates 2005; McIntyre 1996).

Classifying crime places by neighborhood visual appearance and police geonarratives: a machine learning approach

“…It is the location of a geographic story that involves a narrative of the victim, perpetrator, other actors, society, and the physical environment. These types of spatial [ 39 ] or “Go along” interviews have proven useful in adding depth for this and other topics notoriously missing or lacking richness in official data sources such as genocide spaces, homelessness, drug overdoses, and infectious disease spread [ 25 , 26 ]. SVG is a qualitative GIS [ 43 ], and mixed-method [ 48 , 80 ] that lends richness to more traditional spatial data and methods.…”

“…To achieve this, granular detailed primary data needs to be collected in the form of environmental audits or participant observations [ 31 , 52 ]. To this end, this paper will leverage previously collected geonarratives to acquire fine-scale multi-time period contextualized data, an approach which has successfully been used to understand the heterogeneous variations in a variety of different environments [ 2 , 21 , 25 , 26 , 41 , 49 , 55 ]. Advancing this body of work, and addressing the topic of transferability of findings, this paper will present an automatic classification of contextualized locations deemed to be important to explain negative localized events and then transfer these findings to other test locations.…”

The health-trash nexus in challenging environments: A spatial mixed methods analysis of Accra, Ghana

“…While the dominance of "rubbish" (meaning trash), "gutter" (meaning drainage) is evident, these and related themes are contextualized by other phrases which help explain the perceived impact on the "environment", or other societally relevant outcomes such as food sources (especially shing). While the use of Wordmapper helped identify themes, the next step was to return to the narratives for deeper contextualization (Curtis, Tyner, et al, 2019), for example how the combination of dumping and ooding contaminated local sh resources. In other words, the deeper reading of the text helped explain how each keyword was used by the subject and in what context.…”

“…This means that spatially speci c comments, such as describing the proximity of trash to food vendors, can be easily mapped along with their contextual description. A combination of spatial queries (for example what is mentioned within X meters of every trash dump) and thematic mining of words (for example where are drains and trash mentioned) can be combined with the video visuals for a more in-depth understanding of the topic under investigation (Ajayakumar et al, 2019;Curtis, Tyner, et al, 2019). The output of this includes Keyhole Markup Language (KML) for viewing in Google Earth engine, shape les for cartographic analysis in GIS, and Comma Separated Value (CSV).…”

Critical Physical Geography and the Study of Genocide: Lessons from Cambodia

“…First, the violence of the Khmer Rouge from 1975 to 1979-as well as violence in other genocides-must be understood as directly tied to changing land uses and ecologies, rather than, for example, supposed changes in governmental ideology. And second, by integrating empirically grounded, qualitative means with remote sensing to assess this period in Cambodia's history, we contribute also to the recent trend in the use of geospatial technologies in understanding the Holocaust and other genocides (Curtis et al, 2019;Knowles et al, 2014;Madden & Ross, 2009;Tyner et al, 2018aTyner et al, , 2018b.…”