Spatiotemporal phenomena of urban growth and land use/cover changes in the metropolitan area of São Paulo (1985–2023): MASP LULCC TRAZ CA

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Teixeira, Fabrício Rodrigues; Pérez-Martinez, Pedro José, 2026, "Spatiotemporal phenomena of urban growth and land use/cover changes in the metropolitan area of São Paulo (1985–2023): MASP LULCC TRAZ CA", https://doi.org/10.25824/redu/UIJPWA, Repositório de Dados de Pesquisa da Unicamp , V1
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# Dataset: Spatiotemporal Phenomena of Urban Growth and Land Use/Cover Changes in the Metropolitan Area of São Paulo (1985–2023) ## Dataset Abstract / Description This dataset contains spatial and spectral information generated from surface reflectance and surface temperature data acquired from the Landsat satellite series (Collection 2, Level 2). The spatial coverage encompasses the Metropolitan Area of São Paulo (MASP/RMSP), bounded by the following coordinates (SIRGAS 2000 geodetic datum): * **Northwest (NW) corner:** Latitude 23.140000° S, Longitude 47.270000° W * **Southeast (SE) corner:** Latitude 24.354020° S, Longitude 45.650000° W The temporal scope spans from 1985 to 2011 for the Landsat TM sensor, and from 2013 to 2023 for the Landsat OLI sensor. **Keywords:** Landsat, Time series analysis, Cellular automata, Mathematical model, Spatiotemporal phenomena, Land use, Land cover, Urban growth, Surface reflectance, São Paulo. --- ## Data Processing / Lineage The primary imagery was acquired via the USGS EarthExplorer platform. Level 2 processing was performed using the Landsat Surface Reflectance Code (LaSRC) algorithm for Landsat 8 OLI data, and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) for Landsat 4–7 TM data, both ensuring rigorous atmospheric correction. For spectral extraction, pixel values were sampled at specific point locations using ArcGIS and ENVI software. The Quality Assessment band (QA_Pixel) served as a reference to identify and mask out pixels affected by clouds, cloud shadows, or radiometric saturation. --- ## Nature / Purpose To map and monitor the spatiotemporal phenomena of environmental, urban growth, and land use and land cover changes across the São Paulo metropolitan area over nearly four decades (1985–2023). This dataset is specifically designed to develop, calibrate, and validate the TRAZ CA cellular automata model. --- ## Methodology Data processing included atmospheric attenuation and spectral characterization to ensure the temporal consistency of target signatures. The Normalized Difference Built-Up Index (NDBI) was applied for continuous analysis of land cover dynamics. The dataset utilizes original GeoTIFF files from the Near-Infrared (NIR) and Shortwave Infrared 1 (SWIR1) spectral bands of the TM and OLI sensors, alongside quality assessment files to correct for cloud and cloud shadow interferences within the observed time series. --- ## Research Outputs / Generated Data 1. **Spectral characterization plots** of major natural and artificial materials, validated using the ECOSTRESS spectral library. 2. **Spectral response function charts** identifying bandwidths for target discretization. 3. **Land cover change maps** for the São Paulo metropolitan area spanning 1985–2011 (Landsat TM) and 2013–2023 (Landsat OLI). 4. **Scatter plots** of reflectance values within the NIR–SWIR1 spectral space. 5. **Plots and tables** displaying NDBI separability for high-frequency temporal analysis. 6. **Classified raster files** optimized for input into the TRAZ CA dynamic model. 7. **Algorithm files** for the TRAZ CA cellular automata model and its transport submodel, including calibration parameters and urban growth drivers. (2026-05-19)
Subject Engineering
Keyword Landsat, Time series analysis, Cellular automata, Mathematical model, Spatiotemporal phenomena, Land use, Land cover, Urban growth, Surface reflectance, São Paulo
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MASP_LULCC_TRAZ_CA_DATA.rar
Tese/Compressed Archive - 103.2 MB
Published Sep 24, 2026
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MD5: 708f1ec345bee711544d833b6233f6d0
Spectral Data Land Use and Transport MASP
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