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opencc-zeroDec 2023View details →

Data from: Geographic variations in eco-evolutionary factors governing urban birds: the case of university campuses in China

<ol> <li>Urbanization alters natural habitats, restructures biotic communities, and serves as a filter for selecting species from regional species pools. However, empirical evidence of the specific traits that allow species to persist in urban areas yields mixed results. More importantly, it remains unclear which traits are widespread for species utilizing urban spaces (urban utilizers) and which are environment-dependent traits. </li> <li>Using 745 bird species from 287 university/institute campuses in 74 cities and their species pools across China, we tested whether species that occur in urban areas are correlated with regards to their biological (body mass, beak shape, flight capacity, and clutch size), ecological (diet diversity, niche width, and habitat breadth), behavioral (foraging innovation), and evolutionary (diversification rate) attributes. </li> <li>We used Bayesian phylogenetic generalized linear mixed models to disentangle the relative roles of these predictors further and to determine the extent to which the effects of these predictors varied among different cities. </li> <li>We found that urban birds were more phylogenetically clustered than expected by chance, and were generally characterized by a larger habitat breadth, faster diversification rate, more behavioral innovation, and smaller body size. Notably, the relative effects of the attributes in explaining urban bird communities varied with city temperature and elevation, indicating that the filters used to determine urban species were environment-dependent. </li> <li>We conclude that, while urban birds are typically small-sized, generalists, innovative, and rapidly-diversifying, the key traits that allow them to thrive vary spatially, depending on the climatic and topographic conditions of the city. These findings emphasize the importance of studying species communities within specific cities to better understand the contextual dependencies of key traits that are filtered by urban environments.</li> </ol>

Data: On the role of water table depth, and urban and vegetation cover on groundwater dry period susceptibility

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opencc-by-4.0Apr 2023View details →

Air phyto-cleaning by an urban meadow – Filling the winter gap - DATA

Database of article: Air phyto-cleaning by an urban meadow – Filling the winter gap.

CoUDlabs_WP8_T811_UDC_002 Application of imaging velocimetry techniques for urban drainage applications

This dataset includes the data obtained during the installation of a camera system and development of a LSPIV methodology to determine the velocities of runoff generated in the BLOCK rainfall simulator located at the Universidade da Coruña. The dataset consists of raw and processed images and surface velocity maps obtained during the assessment of the full process. This data will help to improve and assess imaging techniques in urban environments with the presence of realistic rain, and test new preprocessing and postprocessing methods to optimize the different processes.This dataset is a result from the Joint Research Activity 3 (WP8, Improving Resilience and Sustainability in Urban Drainage solutions), Task 8.1.1. (Development of Scalable Hydrodynamic Performance Protocols.) within Co-UDlabs project, funded under the European Union's Horizon 2020 research and innovation programme under grant agreement No 101008626.

opencc-zeroDec 2023View details →

Data from: Uniqueness of tree stand composition and soil microbial communities are related across urban spruce-dominated forests

The dataset contains data obtained from urban spruce-dominated forests in southern Finland where we have measured tree stand composition, forest management history, soil chemical properties, and soil microbial communities. Data files include (1) microbial OTU tables describing microbial community composition (sequence read counts of Operational Taxonomic Units) across the study plots, (2) taxonomic assignments and other metadata related to OTUs, and (3) measured and calculated variables describing the characteristics of sites and their microbial assemblages (site metadata).

Reassessing the climate mitigation potential of Chinese ecological restoration: the undiscovered potential of urban areas

The dataset includes urban climate mitigation benefit data for all 371 cities and 1,721 clusters in China, as well as aggregate data of different ecological restoration projects and climate backgrounds. Combining multi-source high-resolution remote sensing data sets and the reanalysis dataset, the absolute value standard deviation method of multiple linear regression is used to extract the largest dominant factor (pixel-by-pixel calculation) of daytime surface temperature in each city except NDVI (as a greening indicator). Then, the time trends of surface temperature, NDVI, and dominant factors were calculated based on the Theil-Sen Median slope estimation method. Finally, based on the linear statistical relationship of the three indicators, the surface temperature trend under the no-greening scenario was constructed, and the difference between the simulated and observed surface temperature trends was used to characterize the urban climate mitigation benefits of the ecological restoration project. The data details are as follows:  If you have any questions or comments, please feel free to contact Mr. Dong Xu via <a href="mailto:zhangh573@mail2.sysu.edu.cn">xu.dong@u.nus.edu.</a> <table> <tbody> <tr> <td> Data name </td> <td> Spatial resolution </td> <td> Time resolution </td> <td> Source </td> <td> Unit </td> <td> Note </td> </tr> <tr> <td> MOD13A2 </td> <td> 1000 m </td> <td> 16-Day </td> <td> USGS.a </td> <td> / </td> <td> UG index </td> </tr> <tr> <td> MOD11A1 </td> <td> 1000 m </td> <td> Daily </td> <td> USGS.a </td> <td> Kelvin </td> <td> UST index </td> </tr> <tr> <td> MOD09A1 </td> <td> 500 m </td> <td> 8-Day </td> <td> USGS.a </td> <td> / </td> <td> Calculate IBI index </td> </tr> <tr> <td> ERA5-Land reanalysis dataset </td> <td> 10000 m </td> <td> Day </td> <td> ECMWF.b </td> <td> / </td> <td> Sensitivity analysis </td> </tr> <tr> <td> Population density datasets </td> <td> 1000 m </td> <td> Annual </td> <td> WorldPop.c </td> <td> /   </td> <td> Sensitivity analysis </td> </tr> <tr> <td> Global Urban Boundaries </td> <td> 30 m </td> <td> Annual </td> <td> Li et al. </td> <td> / </td> <td> Delineate LUBs </td> </tr> <tr> <td> Note: a, United States Geological Survey (https://earthexplorer.usgs.gov/). b, European Centre for Medium-Range Weather Forecasts (https://www.ecmwf.int/). c, WordPop (https://www.worldpop.org/).   1. Li X, Gong P, Zhou Y, et al. Mapping global urban boundaries from the global artificial impervious area (GAIA) data[J]. Environmental Research Letters, 2020, 15(9): 094044. </td> </tr> </tbody> </table>

Supporting Data for "Local exposure misclassification in national models: relationships with urban infrastructure and demographics"

Overview: This dataset accompanies the recent publication "Local exposure misclassification in national models: relationships with urban infrastructure and demographics" (DOI: 10.1038/s41370-023-00624-z). It provides essential data for replicating and extending the analysis conducted in the study. The script for the analysis is available at https://github.com/SEChambliss-AQ/LD-analysis. The dataset consists of four key files. Files Included: <ol> <li> Gridded OSM and GSV Data (gridded_OSM_GSV.RDS): <ul> <li>This R object offers a 100mx100m grid covering select neighborhoods in the San Francisco Bay Area.</li> <li>Each grid cell includes average air pollution levels (Ultrafine Particle Count in thousand count per cubic meter; Nitrogen Dioxide in ppb) from mobile monitoring.</li> <li>The file also provides normalized z-scores of local density of urban infrastructure related to air pollutants based on OpenStreetMap (OSM) data.</li> <li>Further details can be found in the associated publication.</li> </ul> </li> <li> BartMachine Outputs (bartMachine R objects.zip): <ul> <li>A collection of R object outputs from the bartMachine package, an R-Java Bayesian Additive Regression Trees implementation.</li> <li>These objects, which can be regenerated using the provided script, are included to reduce computational requirements for future analyses.</li> <li>The script for generating these outputs is available at the above <a href="https://github.com/SEChambliss-AQ/LD-analysis">GitHub Repository</a>.</li> </ul> </li> <li> NO2 Predictions (CACES_criteria.csv): <ul> <li>Land Use Regression (LUR) data for Nitrogen Dioxide, provided by the Center for Air, Climate, and Energy Solutions.</li> <li>Methodologies for integrating these data with the gridded dataset are described in the publication and script.</li> </ul> </li> <li> UFP Predictions (CACES_UFP.csv): <ul> <li>Similar to the NO2 dataset, this file contains LUR data for Ultrafine Particle predictions.</li> <li>Methods for data integration are detailed in the publication and available script.</li> </ul> </li> </ol> Usage: These files are intended for researchers and analysts aiming to replicate or build upon the study's findings. They provide a source of data for exploring the complex interplay between air pollution, urban infrastructure, and demographic factors in urban environments. For detailed methodology and analysis, refer to the original publication and the accompanying GitHub repository.

opencc-byApr 2021View details →

urban art - graffiti

Mural de street art localizado en Alicante, España. Modelo 3D a partir de fotogrametría con Agisoft Metashape. Source: Objaverse 1.0 / Sketchfab

Engaging urban residents in the appropriate actions to mitigate human–wildlife conflicts

Data that supports the following publication: Puri, M., Goode, K.O., Johannsen, K.L., and Pienaar, E.F. (2024) Engaging urban residents in the appropriate actions to mitigate human–wildlife conflicts. Conservation Science and Practice. Article DOI: 10.1111/csp2.13074

Addressing the Challenge of Wildlife Conservation in Urban Landscapes by Increasing Human Tolerance for Wildlife

Data that supports the journal manuscript: Puri, M., Johannsen, K.L., Goode, K.O., & Pienaar, E.F. (2024) Addressing the challenge of wildlife conservation in urban landscapes by increasing human tolerance for wildlife. People and Nature.

Extra-pair paternity enhances the reproductive fitness of urban Chinese blackbird

Urbanization is a human-induced process of rapid habitat change that can affect the reproductive success of animals. The occurrence of extra-partial paternity (EPP) may be sensitive to changes in urban ecological conditions. In this study, the Chinese blackbird (Turdus mandarinus), a common breeding bird in southern Chinese cities, was selected as the focus species to explore the EPP patterns of monogamous birds in developing cities and their relationship. Over four breeding seasons, 316 Chinese blackbird nestlings and 20 adults in both urban and rural areas were monitored and genotyped for 11 microsatellite loci to determine progeny affinity. We confirmed that both the brood size and hatching rate of EPP nests were significantly larger than those of within-pair paternity (WPP) nests. The body mass, beak length, head length, and body length of 12-day age extra-pair offspring (EPO) were significantly greater than those of within-pair offspring (WPO) suggesting important benefits of EPP. However, according to the analyses of nest ecological variables, we concluded that EPP occurs most often in areas with low urbanization levels indicating some constraints for this reproductive strategy in cities. Our findings provide interesting new insights into how this growing human-induced landscape change affects mating behavior in birds, an important aspect of avian ecology and evolution.

Butterfly community composition within a tropical urban landscape is influenced by habitat type and temperature

The specific factors that influence spatial community or population dynamics are often elusive, and even less known is the impact of tropical urban landscapes on diverse species community assemblages. To address this knowledge gap, we used a survey data set with 510 fruit‐feeding butterflies comprising 20 species across two heterogeneous habitats within a city in Nigeria. Next, we constructed generalised linear mixed models to understand the differential responses of the butterfly community to changes in environmental conditions across habitats. Butterfly species community assemblages significantly differed between the two urban habitats, with butterfly species significantly higher in the savannah woodland compared with the gallery forest due to the optimal daily temperatures of the savannah woodland. However, butterfly richness was lower in the gallery forest due to extreme environmental conditions. This study highlights that butterfly community changes in tropical urban landscapes are possibly responding to local microclimates and spatial heterogeneity across habitats. For evidence‐based conservation management of tropical butterfly biodiversity, there would be a need for a long‐term, extensive and systematic insect monitoring programme for butterflies across disturbed and undisturbed fragmented habitats harbouring diverse insect species.

Urban scavenging: Vertebrates display greater sensitivity to land-cover and garden vegetation cover than invertebrates

1. Scavenging removes carrion or littered food waste from the environment, providing ecosystem services including nutrient cycling, reduced pathogen spread, and reduced waste management costs. These services are particularly important in urban environments, where high human population densities result in increased littered food waste. It is unclear how the magnitude of scavenging across urban-rural gradients is influenced by agent (vertebrates and invertebrates), land-cover type and patch size. 2. We investigated scavenging provision by vertebrates and invertebrates across a gradient of urbanisation in 37 woodlands and 35 domestic gardens across Liverpool, UK. Sites were selected using random stratification across a gradient of urbanisation based on impervious surface cover. At each site, four different bait types were deployed either within vertebrate exclusion cages or exposed to vertebrates and invertebrates. The percentage dry weight loss of bait after 48 hours was used to quantify scavenging provision. 3. Data were analysed using general linear mixed effects models (Gaussian error distribution) and a full model approach to assess 1) the relative contributions of vertebrates and invertebrates across an urban-rural gradient; 2) variation in scavenging between woodlands and gardens; 3) the effects of semi-natural vegetation cover on scavenging provision. We also consider patch size as a preliminary assessment of how fragmentation influences scavenging. 4. Vertebrates contributed substantially more to scavenging provision than invertebrates across the urbanisation gradient. Vertebrate scavenging was substantially greater in woodlands than gardens, invertebrate scavenging was similar in both land-cover types. Scavenging increased with patch size in gardens, but not woodlands. Vertebrate scavenging increased with patch size, while invertebrate scavenging decreased. Within gardens, vertebrate scavenging increased with semi-natural vegetation cover. 5. Scavenging-mediated ecosystem services are important in urban areas where food littering is frequent, and efforts should be made to facilitate these services. Urban woodlands and gardens both make important contributions to scavenging-mediated ecosystem services in urban areas, but woodlands' contributions are much greater. There is a need to increase the cover of semi-natural vegetation in gardens to increase their contributions, and protect and expand woodlands, especially in areas with a high demand for ecosystem services reliant on scavenging.

Heat knock-down times of urban and rural Chiasmia clathrata moth larvae and adults

Urbanization and its urban‐heat‐island effect (UHI) have expanding footprints worldwide. The UHI means that urban habitats experience a higher mean and more frequent extreme high temperatures than rural habitats, impacting the ontogeny and resilience of urban biodiversity. However, many organisms occupy different microhabitats during different life stages and thus may experience the UHI differently across their development. While evolutionary changes in heat tolerance in line with the UHI have been demonstrated, it is unknown whether such evolutionary responses can vary across development. Here, using common‐garden‐reared Chiasmia clathrata moths from urban and rural populations from three European countries, we tested for urban evolution of heat shock tolerance in two life stages: larvae and adults. Our results indicate widespread urban evolution of increased heat tolerance in the adult stage only, suggesting that the UHI may be a stronger selective agent in adults. We also found that the difference in heat tolerance between urban and rural populations was similar to the difference between Mid‐ and North‐European regions, suggesting similarity between adaptation to the UHI and natural, latitudinal temperature variation. Our observations incentivize further research to quantify the impact of these UHI adaptations on fitness during urbanization and climate change, and to check whether life‐stage‐specific adaptations in heat tolerance are typical of other ectothermic species that manage to survive in urbanized settings.

Local habitat complexity and its effects on herbivores and predators in urban agroecosystems

In urban community gardens, cultivated vegetation provides variable levels of habitat complexity, which can suppress pests by promoting predator diversity and improving pest control. In this study, we examine three components of the structural complexity of garden vegetation (cover, diversity, and connectivity) to investigate whether higher garden vegetation complexity leads to fewer herbivores, more predators, and higher predation. We worked in eight community gardens where we quantified vegetation complexity, sampled the arthropod community, and measured predation on cornworm eggs. We found that plots with high vegetation cover supported higher species richness and greater abundance of predatory insects. High vegetation cover also supported a greater abundance and richness of spiders. In contrast, high vegetation diversity was negatively associated with predator abundance. While high predator abundance was positively associated with egg predation, greater predator species richness had a negative impact on egg predation, suggesting that antagonism between predators may limit biological control. Community gardeners may thus manipulate vegetation cover and diversity to promote higher predator abundance and diversity in their plots. However, the species composition of predators and the prevalence of interspecific antagonism may ultimately determine subsequent impacts on biological pest control.

opencc-by-4.0Jun 2023View details →

Biogeochemical data from urban ponds in Brussels

The dataset comprises two files, each containing geo-referenced information with corresponding timestamps.The names of the ponds are written in French according to the official name defined by Brussels Environment (BE). <ul> <li>Brussels_ponds_all.xlsx contains pH, Conductivity, dissolved oxygen saturation,  CO2, CH4, N2O dissolved concentrations, chlorophyll-a concentrations, inorganic nutrients (NO3-, NO2-, NH4+, PO43-) concentrations, total phosphorus and total suspended matter concentrations collected during four surveys (November 2021, February 2022, May 2022 and August 2022) on 22 ponds</li> <li>Brussels_ponds_Chla_temporal.xlsx  contains chlorophyll-a concentration of two ponds monitored on a recurring basis (1-2 times a month) from June 2021 to December 2022.</li> </ul> All ponds have pontoons, raised above the water surface, which allow sampling at least 2m further from the banks. Water pH, temperature, conductivity and oxygen saturation level (%O2) were measured by a VWR MU 6100 H probe. Water was collected in 2L polypropylene bottles for subsequent analysis of chlorophyll a (Chl-a), total suspended matter (TSM) and dissolved nutrients (ammonium (NH4+), nitrite (NO2-), nitrate (NO3-), soluble reactive phosphorus (SRP)). Three 50mL falcons were filled with unfiltered water and stabilised with 200µL HNO3 (65%) for total phosphorus (Ptot) analysis. Filtration on Whatman filters 0.7µm GF/F glass microfibres with diameter of 47mm was carried out. For TSM, 1 pre-weighed filter was weighed after drying at 100°C for 48h in order to obtain the TSM concentration. For Chl-a, a filter was placed after filtration in 90% acetone to extract the Chl-a, which was then measured by fluorimetry (Kontron SFM 25 model) at an excitation length of 430nm and emission length of 664nm (Yentsch and Menzel, 1963). Nutrient concentrations were determined spectrophotometrically (Perkin-Elmer Lambda 650 S model) by coloration of the filtrates obtained after filtration through 0.7µm Whatman GF/F filters. NH4+ was determined by coloration with nitroprusside-hypochlorite-phenol (Grasshoff and Johannsen, 1972) at 630nm. NO2- and NO3- are determined before and after reduction of NO3- to NO2- by passage through a cadmium-copper column. The NO2- is then reacted with Griess' reagent in acidic medium (Grasshoff et al., 1983) at 540nm. The SRP is determined after colorimetric reaction with ammonium molybdate, ascorbic acid and potassium antimony tartrate (Koroleff, 1983) at 885nm. Ptot was determined by inductively coupled plasma spectroscopy (ICP) on an ICP-OES Perkin Elmer Avio 200 model. The assay protocol was based on the US EPA (1994)  method 200.7 for analysis of metals and trace elements in water by ICP with prior microwave acid digestion based on US EPA, (2007) method 3015A. CO2 measurements were carried out on the field with a Li-Cor Li-840 IR-CO2/H2O gas analyser calibrated before each campaign, using the headspace technique with 4 polypropylene syringes (Abril et al., 2015). Samples for CH4 and N2O were collected via a silicone tube into 60mL borosilicate serum bottles and poisoned with 200µL of saturated HgCl2 solution. The vials were sealed with a butyl stopper and crimped with an aluminium cap. Measurements were carried out using the headspace technique (Weiss, 1974) and a gas chromatography measurement (model SRI 8610C) with a flame ionisation detector (FID) for CH4 and an electron capture detector (ECD) for N2O.     References: Abril, G., Bouillon, S., Darchambeau, F., Teodoru, C.R., Marwick, T.R., Tamooh, F., Omengo, Ochieng Omengo, F., Geeraert, N., Deirmendjian, L., Polsenaere, P., Borges, A.V., (2015). Technical Note : Large overestimation of p CO2 calculated from pH and alkalinity in acidic , organic-rich freshwaters Biogeosciences 12, 67–78. <a href="https://doi.org/10.5194/bg-12-67-2015">https://doi.org/10.5194/bg-12-67-2015</a> Grasshoff, K., & Johannsen, H. (1972). A new sensitive and direct method for the automatic determination of ammonia in sea water. ICES Journal of Marine Science, 34(3), 516-521. <a href="https://doi.org/10.1093/icesjms/34.3.516">https://doi.org/10.1093/icesjms/34.3.516</a> Grasshoff, K., Kremling, K., & Ehrhardt, M. (Eds.). (1983). Methods of seawater analysis : Determination of nitrite. John Wiley & Sons Koroleff, J. (1983). Determination of total phosphorus by alkaline persulphate oxidation. Methods of Seawater Analysis. Verlag Chemie, Wienheim, 136-138. U.S. EPA. 1994. “Method 200.7: Determination of Metals and Trace Elements in Water and Wastes by Inductively Coupled Plasma-Atomic Emission Spectrometry,” Revision 4.4. Cincinnati, OH. <a href="https://www.epa.gov/esam/method-2007-determination-metals-and-trace-elements-water-and-wastes-inductively-coupled">https://www.epa.gov/esam/method-2007-determination-metals-and-trace-elements-water-and-wastes-inductively-coupled</a> U.S. EPA. 2007. “Method 3015A (SW-846): Microwave Assisted Acid Digestion of Aqueous Samples and Extracts,” Revision 1. Washington, DC <a href="https://www.epa.gov/esam/epa-method-3015a-microwave-assisted-acid-digestion-aqueous-samples-and-extracts">https://www.epa.gov/esam/epa-method-3015a-microwave-assisted-acid-digestion-aqueous-samples-and-extracts</a> Weiss, R. (1974). Carbon dioxide in water and seawater: the solubility of a non-ideal gas. Marine chemistry, 2(3), 203-215. <a href="https://doi.org/10.1016/0304-4203(74)90015-2">https://doi.org/10.1016/0304-4203(74)90015-2</a> Yentsch, C. S., & Menzel, D. W. (1963, July). A method for the determination of phytoplankton chlorophyll and phaeophytin by fluorescence. In Deep Sea Research and Oceanographic Abstracts (Vol. 10, No. 3, pp. 221-231). Elsevier. <a href="https://doi.org/10.1016/0011-7471(63)90358-9">https://doi.org/10.1016/0011-7471(63)90358-9</a>

Urban peregrine falcon (Falco peregrinus) breeding season diet in UK, 2020–2022

Diets of urban peregrine falcons in UK were monitored via nest cameras during the breeding season (March-June) from 2020–2022. All prey items were then identified to species level where possible, by Ed Drewitt. This dataset contains the prey items recorded during each year of the study and location of the sites.

Arthropods in urban agroecosystems Seattle 2019

Like other urban green spaces, urban community gardens can act as biodiversity refugees, especially for small organisms like arthropods. In turn, arthropods can provide important ecosystem pest control services to these agroecosystems. Thus, an often-asked question among urban gardeners is how to improve gardens and surrounding areas for natural enemies and associated pest control services. We examine how local vegetation and garden characteristics, as well as the surrounding landscape composition affect ground-dwelling beetles (Coleoptera: Carabidae and Staphylinidae), spiders (Aranea), opilionids (Opilionida), and ladybird beetles (Coleoptera: Coccinellidae), all of which are important predators. In the summer 2019, we collected predators, vegetation, ground cover, and garden and landscape characteristic data of ten community gardens in the city of Seattle, Washington. We found that different groups of natural enemies are associated with different environmental variables and at different scales; probably related to differences in their dispersal capabilities, habits, and diets. Floral variables (# of flowers, # of species in flower) had a negative effect on non-flying natural enemies (spiders, opilionids, and ground-dwelling beetles), but not on flying ones (ladybird beetles). The only taxa that was significantly affected by a landscape-scale variable was Opilionida, the only group examined that exclusively disperses by ground. Our results show contrasting results to similar studies in different regions and highlight the need to expand the taxa and regions of study.

GLobAl building MOrphology dataset for URban climate modelling

GLobAl building MOrphology dataset for URban climate modelling (GLAMOUR) offers the building footprint and height files at the resolution of 100 m in global urban centers. <ul> <li>the `BH_100m` contains the building height files where each file is named as `BH_{lon_start}_{lon_end}_{lat_start}_{lat_end}.tif`.</li> <li>the `BF_100m` contains the building footprint files where each file is named as `BF_{lon_start}_{lon_end}_{lat_start}_{lat_end}.tif`.</li> </ul> Here `lon_start`, `lon_end`, `lat_start`, `lat_end` denote the starting and ending positions of the longitude and latitude of target mapping areas. To avoid possible confusion, it should be clarified that the 'building footprint' in GLAMOUR represents the 'building surface fraction', i.e., the ratio of building plan area to total plan area.   We also offer the snapshot of source code used for the generation of the GLAMOUR dataset including: <ul> <li>`GC_ROI_def.py` defines regions of interest (ROI) used in the mapping of the GLAMOUR dataset.</li> <li>`GC_user_download.py` retrieves satellite images including Sentinel-1/2, NASADEM and Copernicus DEM from Google Earth Engine and exports them into Google Cloud Storage.</li> <li>`GC_master_pred.py` downloads exported data records from Google Cloud Storage and then performs the estimation of building footprint and height using Tensorflow-based models.</li> <li>`GC_postprocess.py` performs postprocessing on initial estimations by pixel masking with the World Settlement Footprint layer for 2019 (WSF2019).</li> <li>`GC_postprocess_agg.py` aggregates masked patches into larger tiles contained in the GLAMOUR dataset.</li> </ul>