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Measuring Primitive Accumulation: An Information-Theoretic Approach to Capitalist Enclosure in PIK2, Indonesia

Sandy Hardian Susanto Herho, Alfita Puspa Handayani, Karina Aprilia Sujatmiko, Faruq Khadami, Iwan Pramesti Anwar

Abstract

Large-scale land enclosure for speculative mega-development constitutes a non-equilibrium spatial process whose velocity, topology, and irreversibility remain poorly quantified. We study the Pantai Indah Kapuk 2 (PIK2) coastal mega-development north of Jakarta, Indonesia, using eight years (2017--2024) of Sentinel-2 land-use/land-cover (LULC) data at 10-meter resolution. The landscape is projected onto a Marxian probability simplex partitioning terrestrial pixels into Commons, Agrarian, and Capital fractions. Fisher-Rao (FR) geodesic distances on this simplex identify a transformation pulse of $0.405$~rad/yr during 2019--2020, coinciding with major construction activity. Absorbing Markov chain analysis yields expected absorption times into the built environment of $46.0$~years for cropland and $38.1$~years for tree cover, with a pooled built-area self-retention rate of $96.4\%$. Percolation analysis reveals that a giant connected component containing $89$--$95\%$ of all built pixels persists at occupation probabilities $p \in [0.096, 0.162]$, far below the random percolation threshold $p_c \approx 0.593$, indicating planned rather than stochastic spatial growth. The box-counting fractal dimension of the urban boundary increases from $d_f = 1.316$ to $1.397$, consistent with increasingly irregular frontier expansion. These results suggest that information-geometric and statistical-mechanical tools can characterize the kinematic and topological signatures of capitalist spatial accumulation with quantitative precision.

Measuring Primitive Accumulation: An Information-Theoretic Approach to Capitalist Enclosure in PIK2, Indonesia

Abstract

Large-scale land enclosure for speculative mega-development constitutes a non-equilibrium spatial process whose velocity, topology, and irreversibility remain poorly quantified. We study the Pantai Indah Kapuk 2 (PIK2) coastal mega-development north of Jakarta, Indonesia, using eight years (2017--2024) of Sentinel-2 land-use/land-cover (LULC) data at 10-meter resolution. The landscape is projected onto a Marxian probability simplex partitioning terrestrial pixels into Commons, Agrarian, and Capital fractions. Fisher-Rao (FR) geodesic distances on this simplex identify a transformation pulse of ~rad/yr during 2019--2020, coinciding with major construction activity. Absorbing Markov chain analysis yields expected absorption times into the built environment of ~years for cropland and ~years for tree cover, with a pooled built-area self-retention rate of . Percolation analysis reveals that a giant connected component containing -- of all built pixels persists at occupation probabilities , far below the random percolation threshold , indicating planned rather than stochastic spatial growth. The box-counting fractal dimension of the urban boundary increases from to , consistent with increasingly irregular frontier expansion. These results suggest that information-geometric and statistical-mechanical tools can characterize the kinematic and topological signatures of capitalist spatial accumulation with quantitative precision.
Paper Structure (10 sections, 16 equations, 6 figures)

This paper contains 10 sections, 16 equations, 6 figures.

Table of Contents

  1. Introduction
  2. Study area and data
  3. Methods
  4. Empirical probability distributions on the lattice
  5. Information-theoretic measures
  6. Markov chain formulation
  7. Percolation analysis
  8. Results
  9. Discussion
  10. Conclusion

Figures (6)

  • Figure 1: Geographic context of the study area. (a) Location of PIK2 within the Indonesian archipelago. (b) High-resolution (1 arc-second, ${\sim}30$ m) bathymetric and topographic relief of the PIK2 domain, showing the low-lying coastal substrate. Data derived from the Shuttle Radar Topography Mission (SRTM) Farr2007SRTM, rendered via PyGMT Wessel2019GMT.
  • Figure 2: Annual LULC classification of the PIK2 domain (2017--2024), showing the progressive expansion of Built Area (red) at the expense of Crops (yellow) and natural vegetation (green).
  • Figure 3: Trajectory of the terrestrial landscape on the Marxian ternary simplex (land pixels only, ocean excluded). Capital surpasses Agrarian between 2020 and 2021.
  • Figure 4: Information-theoretic analysis of the 7-class LULC distribution. (a) Shannon entropy $H(t)$. (b) Rényi entropy spectrum $H_\alpha(t)$. (c) KLD $D_{\mathrm{KL}}(\mathbf{p}(t{+}1)\|\mathbf{p}(t))$. (d) FR geodesic distance $d_{\mathrm{FR}}(\mathbf{p}(t), \mathbf{p}(t{+}1))$.
  • Figure 5: Markov chain analysis. (a) Pooled transition probability matrix. (b) Expected absorption time $\mathbb{E}[T_i]$ into Built Area under the absorbing chain formulation. (c) Stationary distribution $\boldsymbol{\pi}$ of the empirical (non-forced) pooled matrix. (d) Built Area self-retention probability $P(B \to B)$ by period, with leakage percentage annotated.
  • ...and 1 more figures