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30 results for “imperviousness”
Long-term composited and land cover-adjusted Enhanced Normalized Difference Impervious Surface Index (ENDISI) for the greater Phoenix, Arizona, USA, metropolitan area and the surrounding Sonoran desert derived from annual and seasonal Landsat imagery, 1998 to 2020
This data package consists of multiple decades of Enhanced Normalized Difference Impervious Surface Index (ENDISI) raster data across the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) study area within metropolitan Phoenix, Arizona, USA, temporally aggregated by year and by four meteorological seasons (winter, spring, summer, fall). To serve as a proxy measurement of impervious surface and urbanization across years and seasons, we derived values of ENDISI – following the methods of Chen et al. 2019 from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. Next, we corrected the underestimated ENDISI values of dark impervious surface cover and the overestimated ENDISI values of bright bare soils based on visible Landsat bands and 2020 land cover (Sabu et al. 2023). Finally, we exported images as individual GeoTIFF raster files, each with five bands corresponding values summarized annually (band 1) and seasonally (bands 2-5). All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of the spectral index, can be found in the data package metadata (see 'Methods and Protocols') and accompanying Javascript code. ### citations - Gorelick N, Hancher M, Dixon M, et al. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202:18–27. https://doi.org/10.1016/j.rse.2017.06.031 - Sabu, S., Frazier, A., & Rashid, B. (2023). Land use and land cover (LULC) classification of the CAP LTER study area (central Arizona, USA) using Landsat imagery: 2015 and 2020 [Dataset]. Environmental Data Initiative. https://doi.org/10.6073/PASTA/BF18E5856215BD2D4DAB3B024BA87A7E
Long-term composited Enhanced Normalized Difference Impervious Surface Index (ENDISI) for the greater Phoenix, Arizona, USA, metropolitan area and the surrounding Sonoran desert derived from annual and seasonal Landsat imagery, 1998 to 2023
This data package consists of multiple decades of Enhanced Normalized Difference Impervious Surface Index (ENDISI) raster data across the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) study area within metropolitan Phoenix, Arizona, USA, temporally aggregated by year and by four meteorological seasons (winter, spring, summer, fall). To serve as a proxy measurement of impervious surface and urbanization across years and seasons, we derived values of ENDISI – following the methods of Chen et al. 2019 – from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. Finally, we exported images as individual GeoTIFF raster files, each with five bands corresponding values summarized annually (band 1) and seasonally (bands 2-5). All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of the spectral index, can be found in the data package metadata (see 'Methods and Protocols') and accompanying Javascript code. ### citations - Gorelick N, Hancher M, Dixon M, et al. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202:18–27. https://doi.org/10.1016/j.rse.2017.06.031
Impervious surface and race in Los Angeles County, 2019
This dataset was used to analyze differences in impervious surface levels by race while also accounting for other sociodemographic factors and land use in Los Angeles County. Data was downloaded from the websites of the U.S. Geological Survey, U.S. Census Bureau, and Southern California Association of Governments. Due to redlining and disinvestment in neighborhoods of color, there are generally fewer green spaces and greater urban heat island effects in neighborhoods of color throughout the U.S., as documented in the environmental justice literature. Replacing impervious surfaces like concrete and asphalt with green stormwater infrastructure can help increase green space and reduce urban heat while also meeting local stormwater goals. This research supports existing findings and ties it to the local stormwater context in Los Angeles County. Based on the results of this research, local decision-makers should consider racial demographics when prioritizing where to remove impervious surface and replacing with green stormwater infrastructure.
Scale-dependent interactions between tree canopy cover and impervious surfaces reduce daytime urban heat during summer
As cities warm and the need for climate adaptation strategies increases, a more detailed understanding of the cooling effects of land-cover across a continuum of spatial scales will be necessary to guide management decisions. We asked how tree canopy cover and impervious surface cover interact to influence daytime and nighttime summer air temperature, and how effects vary with the spatial scale at which land-cover data are analyzed (10, 30, 60 and 90-m radii). A bicycle-mounted measurement system was used to sample air temperature every 5 m along 10 transects (about 7 km length, sampled 3-12 times each) spanning a range of impervious and tree canopy cover (0 to 100%, each) in a mid-sized city in the Upper Midwest, USA. Variability in daytime air temperature within the urban landscape averaged 3.5 degreeC (range 1.1 to 5.7 degreeC). Temperature decreased nonlinearly with increasing canopy cover, with the greatest cooling when canopy cover exceeded 40%. The magnitude of daytime cooling also increased with spatial scale, and was greatest at the size of a typical city block (60-90 m). Daytime air temperature increased linearly with increasing impervious cover, but the magnitude of warming was less than the cooling associated with increased canopy cover. Variation in nighttime air temperature averaged 2.1C (range 1.2 to 3.0 degreeC), and temperature increased with impervious surface. Effects of canopy were limited at night; thus, reduction of impervious surfaces remains critical for reducing nighttime urban heat. Results suggest strategies for managing urban land-cover patterns to enhance resilience of cities to climate warming.
Spectral Library of Impervious Urban Materials
<p>The radiative response of impervious urban materials is a highly influential surface property, due to its impacts on the radiation balance of incoming and outgoing long- and short-wave fluxes. Information about the material composition can be determined with data resolved to the wavelength level. Spectral reflectance in the visible- to short-wave infrared (VIS-SWIR) region is widely used in remote sensing-based land cover classification and spectral long-wave infrared (LWIR) emissivity is required for the observation of surface temperatures. The Spectral Library of impervious Urban Materials (SLUM) available from the London Urban Micromet data Archive (LUMA) includes LWIR emissivity spectra of 74 samples of impervious surfaces derived using measurements made by a portable Fourier Transform InfraRed (FTIR) spectrometer and matching short-wave reflectance spectra observed for each urban sample.</p> <p>The documentation (<a href="http://www.met.reading.ac.uk/micromet/documents/LUMA_SLUM.pdf">pdf</a>) contains photos, meta information for all 74 samples and plots of the short-wave reflactance (300-2500 nm) and long-wave (8-14 um) emissivity spectra.</p> <p>Data are provided in csv format for short-wave reflectance (LUMA_SLUM_SW.csv) and long-wave emissivity (LUMA_SLUM_LW.csv).</p> <p>Further details (including integrated broadband values of emissivity and albedo), methods and data analysis are presented in</p> <p>Kotthaus, S, TEL Smith, MJ Wooster, and CSB Grimmond 2014: Derivation of an urban materials spectral library through emittance and reflectance spectroscopy, <em>ISPRS Journal of Photogrammetry and Remote Sensing</em>, 94, 194–212. doi:10.1016/j.isprsjprs.2014.05.005</p> <p><strong>Please cite both this site and the paper above if you use this data</strong></p>
Concrete habitat: Impervious surface in nest vicinity is associated with avian fitness decline in two urban adapters
<p>The conversion of natural habitats to impervious surfaces in cities affects biotic and abiotic attributes of urban ecosystems. Detailed information on the gradual influence of impervious surfaces on reproductive success, however, is lacking. Using five years of nestbox-breeding great tit and blue tit breeding data collected across various habitat types within and outside a Central-Eastern European capital city, we quantified the impact of impervious surfaces on avian reproductive success. Impervious surfaces strongly and negatively covaried with the number of fledged young in both species: a 50% increase in impervious surface resulted in 2.93 (95% CI: -4.27; -1.58) fewer blue tit offspring fledging the nest, and 3.51 (95% CI: -4.79; -2.23) fewer great tit offspring fledging the nest, thus halving the reproductive output of two widespread urban species. These results provide benchmark values of avian productivity for ecologists and urban policy makers, and for the management of urban areas.</p>
Improving 30-meter global impervious surface area (GISA) mapping: New method and dataset
<p>Timely and accurate monitoring of impervious surface areas (ISA) is crucial for effective urban planning and sustainable development. Recent advances in remote sensing technologies have enabled global ISA mapping at fine spatial resolution (<30 m) over long time spans (>30 years), offering the opportunity to track global ISA dynamics. However, existing 30 m global long-term ISA datasets suffer from omission and commission issues, affecting their accuracy in practical applications. To address these challenges, we proposed a novel global longterm ISA mapping method and generated a new 30 m global ISA dataset from 1985 to 2021, namely GISA-new. Specifically, to reduce ISA omissions, a multi-temporal Continuous Change Detection and Classification (CCDC) algorithm that accounts for newly added ISA regions (NA-CCDC) was proposed to enhance the diversity and representativeness of the training samples. Meanwhile, a multi-scale iterative (MIA) method was proposed to automatically remove global commissions of various sizes and types. Finally, we collected two independent test datasets with over 100,000 test samples globally for accuracy assessment. Results showed that GISA-new out performed other existing global ISA datasets, such as GISA, WSF-evo, GAIA, and GAUD, achieving the highest overall accuracy (93.12 %), the lowest omission errors (10.50 %), and the lowest commission errors (3.52 %). Furthermore, the spatial distribution of global ISA omissions and commissions was analyzed, revealing more mapping uncertainties in the Northern Hemisphere. In general, the proposed method in this study effectively addressed global ISA omissions and removed commissions at different scales. The generated high-quality GISAnew can serve as a fundamental parameter for a more comprehensive understanding of global urbanization.</p>
Mapping 10-m global impervious surface area (GISA-10m) using multi-source geospatial data
<p>Artificial impervious surface area (ISA) documents human footprints. Accurate, timely, and detailed ISA datasets are therefore essential for global climate change and urban planning. However, due to the lack of sufficient training samples and operational mapping methods, global ISA mapping at 10-m resolution is still lacking. To this end, we proposed a global ISA mapping method leveraging multi-source geospatial data. Based on the existing satellite-derived ISA maps and the crowdsourcing OpenStreetMap (OSM), 58 million training samples were extracted via a series of temporal, spatial, spectral, and geometric rules. Combined with over 2.7 million Sentinel optical and radar images on the Google Earth Engine, we produced the 10 m global ISA dataset (GISA-10m). Based on the test samples that are independent to the training set, GISA-10m embraced an overall accuracy greater than 86%. In addition, the GISA-10m was comprehensively compared with the existing global ISA datasets, and the superiority of GISA-10m was demonstrated. </p>
Generating Imperviousness Maps from Multispectral Sentinel-2 Satellite Imagery
<p>This dataset contains a list of Sentinel-2 tiles covering Italy for the year 2017. For each tile, a corresponding ground truth GeoTIFF is present which contains a clip of the soil consumption provided by ISPRA (<a href="https://www.isprambiente.gov.it">https://www.isprambiente.gov.it</a>).</p> <p>Dataset can be used to train a Machine Learning model to extract imperviousness maps using Sentinel-2 satellite images.</p> <p>More details can be found reading the paper: </p> <p>Giacco, G., Marrone, S., Langella, G., & Sansone, C. (2022). ReFuse: Generating Imperviousness Maps from Multi-Spectral Sentinel-2 Satellite Imagery. <em>Future Internet</em>, <em>14</em>(10), 278.</p>
Concrete habitat: Impervious surface and avian fitness decline in two urban adapters
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Data for "Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system"
<p>The data set corresponds the data used in the paper : “Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system”, published in 2017 in the Journal “Hydrology and Earth System Sciences” (http://www.hydrol-earth-syst-sci.net/).</p> <p>More precisely it corresponds to the matrices that are used in the fractal and multi-fractal analysis of the ten urban areas investigated in the paper.</p> <p> </p> <p>For each catchment, it is organised as follow:</p> <p>- catchment_name_conduit.asc : the matrix describing the sewer system.</p> <p>- catchment_name_OSM.asc : the matrix describing the impervious areas (roads and buildings) obtained via Open Street Map (www.openstreetmap.org)</p> <p>- catchment_name_OSM_house_only.asc : the matrix describing the “building” areas obtained via Open Street Map (www.openstreetmap.org)</p> <p>- catchment_name_imperviousness.asc : the matrix describing the representation of imperviousness in operational semi-distributed models.</p> <p> </p> <p>More details can be found in the paper.</p>
Data for "How to use scale invariant properties of imperviousness in urban areas to handle missing data ?"
<p>The data set corresponds the data presented in the data paper : “How to use scale invariant properties of imperviousness in urban areas to handle missing data ?“ which has been submitted to Water Resources Research ” (https://agupubs.onlinelibrary.wiley.com/journal/19447973).</p> <p>It corresponds to :</p> <p>- the rainfall data collected on 2019-06-02 with 5 min and 30 s time steps by a disdrometer installed on the roof of Ecole des Ponts ParisTech building.</p> <p>- land use distribution for the Jouy-en-Josas catchment (1 = forest, 2= road, 3=Grass, 4=building, 5=Gully, 6=missing data), with pixel size of 10 m and 2 m.</p> <p>More details can be found in the file and in the paper.</p>
Development of a global 30-m impervious surface map using multi-source and multi-temporal remote sensing datasets with the Google Earth Engine platform
<p>An accurate global impervious surface map at a resolution of 30-m for 2015 by combining Landsat-8 OLI optical images, Sentinel-1 SAR images and VIIRS NTL images based on the Google Earth Engine (GEE) platform.</p>
urban impervious surface area (UISA) data in Shanghai in 2015 and 2018
<p>This data cite from Kuang, W., Zhang, S., Li, X., and Lu, D. (2000–2018). A 30 M Resolution Dataset of China’s Urban Impervious Surface Area and green Space, 2000-2018. Earth Syst. Sci. Data 13, 63–82. doi:10.5194/essd-13-63-2021</p>
Impervious surface cover and number of restaurants shape diet variation in an urban carnivore
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Data from: Parasitism of urban bumble bees influenced by pollinator taxonomic richness, local garden management, and surrounding impervious cover
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The formation process, mechanism, and attribution of urban impervious surface thermal runoff
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GISD30: global 30-m impervious surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform
<p>A novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral generalization method and time-series Landsat imagery, on the Google Earth Engine cloud-computing platform.</p>
Data from: Herbivory on the pedunculate oak along an urbanization gradient in Europe: effects of impervious surface, local tree cover and insect feeding guild
<p><span>Urbanization is recognized as an important driver of the diversity and abundance of tree associated insect herbivores, but its consequences for insect herbivory are controversial. A likely source of variability among studies is the insufficient consideration of intra-urban variability in forest cover. W</span>ith the help of citizen scientists, we investigated the independent and interactive effect of urbanization and local canopy cover on insect herbivory in the pedunculate oak (<em>Quercus robur</em>) throughout most of its geographic range in Europe. We found that the damage caused by chewing insect herbivores as well as the incidence of leaf-mining and gall-inducing herbivores consistently decreased with increasing urbanization around focal oaks. Herbivory by chewing herbivores increased with increasing forest cover, regardless of urbanization. In contrast, an increase in local canopy cover buffered the negative effect of urbanization on leaf-miners and strengthened its effect on gall-inducers. These results show the complexity of plant-herbivore interactions in urbanized areas, highlighting that the presence of local canopy cover within cities has the potential to attenuate or modify the effect of urbanization on biotic interactions.</p>
RAre, But Not aLone: a Large Italian Network to Empower the Impervious diaGNostic Pathway of Rare cerEbrovascular Diseases (ALIGNED)
ClinicalTrials.gov study NCT06935578. IPD Sharing: NO. Countries: 1. Publications: 10.
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