Mapping the Invisible: Integrating Nighttime Light and Social Sensing to Explore Hidden Cross-Border Economies

Abstract

Against the backdrop of the continuing spread of cross-border telecommunications fraud and the scarcity of conventional data, this study examines how publicly accessible multi-source data can be used to monitor and characterize the spatiotemporal evolution of known or suspected fraud compounds under data-scarce conditions. Focusing on eight representative and manually delineated fraud compounds in Myanmar’s border regions, it develops a three-dimensional “space–time–representation” framework that integrates 2017–2025 VIIRS nighttime lights (NTL), Sentinel-1/2-derived built-up area (BUA) expansion, and Baidu Index time series as a proxy for Chinese-language public attention. Dynamic time warping (DTW) is used to examine temporal alignment between NTL dynamics and public attention, while spatial autocorrelation and exploratory grouping based on DTW dissimilarity are applied to characterize spatial clustering and heterogeneous temporal patterns. The results show that BUA expansion and nighttime brightness are not uniformly coupled across compounds and years. After excluding partial-year 2025 observations, the complete-year 2017–2024 park–year analysis indicates weak aggregate associations between BUA and annual mean NTL, highlighting the need to interpret the two indicators as complementary but non-equivalent proxies. NTL changes do not necessarily evolve synchronously with changes in public attention, suggesting potential value for monitoring and prioritization rather than direct early-warning or verification of illicit activities. The global Moran’s I of 0.2476 indicates significant spatial clustering of nighttime-light values within the defined compound–buffer analysis units. DTW alignment reveals stronger consistency between nighttime lights and Baidu Index attention in the Daxiang and Dingsheng compounds, whereas KK Park and Yatai City show weaker public-search responses relative to observed NTL dynamics. Exploratory grouping identifies three patterns of NTL–public attention correspondence, highlighting heterogeneous relationships between observed nighttime-light dynamics and external information visibility. The study demonstrates the complementarity of remote sensing and social sensing data under data scarcity and proposes a replicable approach for remote monitoring, typological characterization, and evidence-informed governance prioritization of known or suspected fraud compounds. The proposed approach should be interpreted as a screening and analytical framework that provides directional evidence rather than as direct verification of illicit activity or compound-specific operational status.