Linganisha mbinu

	Environmental Justice Spatial Analysis	Land-Change Driver Analysis
Nyanja	Environmental Sociology	Environmental Sociology
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2006	2002
Mwanzilishi	Robert D. Bullard; Paul Mohai & Robin Saha	Eric F. Lambin & Helmut J. Geist
Aina	Spatial pipeline for testing demographic disparities in hazard proximity	Spatial-and-causal pipeline for explaining land-cover change
Chanzo asilia	Mohai, P., & Saha, R. (2006). Reassessing Racial and Socioeconomic Disparities in Environmental Justice Research. Demography, 43(2), 383-399.	Geist, H. J., & Lambin, E. F. (2002). Proximate Causes and Underlying Driving Forces of Tropical Deforestation. BioScience, 52(2), 143-150.
Majina mbadala	EJ Spatial Coincidence Analysis, Distance-Based Environmental Justice Assessment, Hazard-Demographic Proximity Analysis, Disparate Siting Analysis	LUCC Analysis, Land-Change Science, Land Use/Land Cover Change Analysis, Proximate-and-Underlying Driver Analysis
Zinazohusiana	4	3
Muhtasari	Environmental justice spatial analysis tests whether environmentally hazardous facilities are located disproportionately near poor and minority communities by comparing the demographics of populations close to hazards with those farther away. The field grew out of Robert Bullard's foundational documentation in Dumping in Dixie that African American communities in the U.S. South systematically bore the burden of noxious land uses. A central methodological turning point came with Paul Mohai and Robin Saha's 2006 Demography article, which showed that the long-dominant 'unit-hazard coincidence' method, comparing only the host tract or zip code, badly understated disparities, and that distance-based methods reveal larger and more consistent inequities. The modern analysis therefore treats proximity explicitly, drawing buffers or distance bands around hazard sites and apportioning population within them. It then asks whether race and income predict who lives in the burdened zone, controlling for plausible confounders. The result is a spatially explicit test of the disparate-burden hypothesis at the heart of the environmental justice movement.	Land-use and land-cover change (LUCC) analysis is the land-change-science method for detecting how the Earth's surface is being transformed and explaining why, with particular attention to the social drivers behind the change. Its defining move, formalized by Eric Lambin and Helmut Geist, is to separate proximate causes, the direct human activities such as agricultural expansion, wood extraction, and infrastructure that physically alter land cover, from underlying driving forces, the demographic, economic, technological, institutional, and cultural factors that operate at a distance and push the proximate causes. Their meta-analysis of tropical deforestation showed that single-factor explanations are rare and that change is usually produced by synergistic combinations of drivers. The analysis chains remote sensing of cover change to a structured causal attribution, giving social scientists a rigorous way to link maps of deforestation or urbanization to the human forces that produce them.