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1,239 results for “Rural”
Carbon and Nitrogen Across Two ULTRA-Ex Urban to Rural Gradients in Massachusetts 2010
As part of the Boston University-led, Urban Long-Term Research Area - Exploratory Award (ULTRA-Ex), we established 135 circular, 15 m radius biometric plots extending across two Boston urban-to-rural gradients (Boston MA to Petersham MA and Boston MA to Worcester MA). The plots were stratified based on neighborhood (1 km2 surrounding area) characteristics for population density, impervious surface area fraction, and land cover. Within each plot we measured aboveground live and dead biomass, species characteristics, ground cover characteristics, and soil properties.
Community and Conservation Survey in Urban, Suburban and Rural Massachusetts 2013-2018
The dynamics of forest cover and the ecosystem services they provide are shaped by the land use and management decisions of thousands of individual landowners and the land use planning and conservation actions of towns and environmental organizations. Through an interdisciplinary investigation of the land use and forest conservation practices across two urban-to-rural transects between Boston and Central Massachusetts, we investigated the complex and coupled socio-ecological processes that shape the structure, function, and transformation of forested landscapes and how examine these processes may vary along urban-to-rural gradients. The survey data archived here is one element of this larger coupled natural-human systems project. The Community and Conservation Survey collected data regarding landowners’ attitudes and management practices on a variety of issues linked to conservation and the use of their own land. The objectives were to collect data that (a) increase our understanding of how landowners’ attitudes and behaviors vary across urban-to-rural gradients and (b) can be coupled with biogeochemical measurements across the study region to model variation in management behaviors.
Soil Respiration at Forest Edges along an Urban to Rural Gradient in Massachusetts 2018-2019
As urbanization and forest fragmentation increase around the globe, it is critical to understand how rates of respiration and carbon losses from soil carbon pools are affected by these processes. This study characterizes soils in fragmented forests along an urban to rural gradient, evaluating the sensitivity of soil respiration to changes in soil temperature and moisture near the forest edge. While previous studies found elevated rates of soil respiration at temperate forest edges in rural areas compared to the forest interior, we find that soil respiration is suppressed at the forest edge in urban areas. At urban sites, respiration rates are 25% lower at the forest edge relative to the interior, likely due to high temperature and aridity conditions near urban edges. While rural soils continue to respire with increasing temperatures, urban soil respiration rates asymptote as temperatures climb and soils dry. Soil temperature- and moisture-sensitivity modeling show that respiration rates in urban soils are less sensitive to rising temperatures than those in rural soils. Scaling these results to Massachusetts (MA), which encompasses 0.25 Mha of urban forest, we find that failure to account for decreases in soil respiration rates near urban forest edges leads to an overestimate of growing-season soil carbon fluxes of greater than 350,000 MgC. This difference is almost 2.5 times that for rural soils in the analogous comparison (underestimate of less than 143,000 MgC), even though rural forest area is more than four times greater than urban forest area in MA. While a changing climate may stimulate carbon losses from rural forest edge soils, urban forests may experience enhanced soil carbon sequestration near the forest edge. These findings highlight the need to capture the effects of forest fragmentation and land use context when making projections about soil behavior and carbon cycling in a warming and increasingly urbanized world. We provide soil respiration, soil temp
Soil Carbon at Forest Edges along an Urban to Rural Gradient in Massachusetts since 2018
Global proliferation of forest edges through anthropogenic land-use change and forest fragmentation is well documented, and while forest fragmentation has clear consequences for soil carbon (C) cycling, underlying drivers of belowground activity at the forest edge remain poorly understood. Increasing soil C losses via respiration have been observed at rural forest edges, but this process was suppressed at urban forest edges. We offer a comprehensive, coupled investigation of abiotic soil conditions and biotic soil activity from forest edge to interior at eight sites along an urbanization gradient to elucidate how environmental stressors are linked to soil C cycling at the forest edge. Despite significant diverging trends in edge soil C losses between urban and rural sites, we did not find comparable differences in soil % C or microbial enzyme activity, suggesting an unexpected decoupling of soil C fluxes and pools at forest edges. We demonstrate that across site types, soils at forest edges were less acidic than the forest interior (p less than 0.0001), and soil pH was positively correlated with soil calcium, magnesium and sodium content (adj R2 = 0.37), which were also elevated at the edge. Compared to forest interior, forest edge soils exhibited a 17.8% increase in sand content and elevated freeze-thaw frequency with probable downstream effects on root turnover and decomposition. Using these and other novel forest edge data, we demonstrate that significant variation in edge soil respiration (adj R2 = 0.46; p = 0.0002) and C content (adj R2 = 0.86; p less than 0.0001) can be explained using soil parameters often mediated by human activity (e.g., soil pH, trace metal and cation concentrations, soil temperature), and we emphasize the complex influence of multiple, simultaneous global change drivers at forest edges. Forest edge soils reflect legacies of anthropogenic land-use and modern human management, and this must be accounted for to understand soil activity and C
HOSENG trial – HOme-based oral SElf-testiNG for absent and refusing individuals during a door-to-door HIV testing campaign: a cluster randomised clinical trial in rural Lesotho
<p>These are pseudo-anonymised data from the HOSENG randomized trial: " HOSENG trial – HOme-based oral SElf-testiNG for absent and refusing individuals during a door-to-door HIV testing campaign: a cluster randomised clinical trial in rural Lesotho". The data dictionary explains the data available in the dataset. Between July 2018 and December 2018, 10516 eligible individuals from 106 consenting villages were enrolled from two districts of Lesotho, and followed up for a maximum of 120 days. Main manuscript reference, DOI: <a href="https://doi.org/10.1016/s2352-3018(20)30233-2">10.1016/S2352-3018(20)30233-2. </a>The protocol was published, DOI:10.1186/s13063-019-3469-2.</p>
Rural population count at 1 km for 2000-2020 based on WorldPop and GHS-SMOD urbanization level
<p>Rural population count at 1 km grid in EPSG:4326 for 2000-2020 (annual). This is only an estimate of the rural population. This probably misses many rural areas, especially in the tropics. The maps were derived using two data sources:</p> <ol> <li><a href="https://hub.worldpop.org/geodata/listing?id=64">WorldPop population counts at 1 km</a>;</li> <li><a href="https://human-settlement.emergency.copernicus.eu/download.php?ds=smod">GHS-SMOD urbanization levels at 1 km</a>;</li> </ol> <p>Rural population is estimated using the following translation rules for GHS-SMOD (note: these are arbitrary rules based on the GHS-SMOD documentation):</p> <ul> <li>Class 30: “Urban Centre grid cell” = 0% rural</li> <li>Class 23: “Dense Urban Cluster grid cell” = 0.5% rural</li> <li>Class 22: “Semi-dense Urban Cluster grid cell” = 2% rural</li> <li>Class 21: “Suburban or per-urban grid cell” = 15% rural</li> <li>Class 13: “Rural cluster grid cell” = 95% rural</li> <li>Class 12: “Low Density Rural grid cell” = 100% rural</li> <li>Class 11: “Very low density rural grid cell” = 100% rural</li> </ul> <p>The nighttime images are based on: <a href="https://doi.org/10.5281/zenodo.7750174">https://doi.org/10.5281/zenodo.7750174</a></p> <ul> <li>Schiavina, Marcello; Melchiorri, Michele; Pesaresi, Martino (2023): GHS-SMOD R2023A - GHS settlement layers,<br>application of the Degree of Urbanisation methodology (stage I) to GHS-POP R2023A and GHS-BUILT-S R2023A,<br>multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) [Dataset] doi:<br>10.2905/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA PID: <a href="http://data.europa.eu/89h/a0df7a6f-49de-46ea-%209bde-563437a6e2ba">http://data.europa.eu/89h/a0df7a6f-49de-46ea-</a><br><a href="http://data.europa.eu/89h/a0df7a6f-49de-46ea-%209bde-563437a6e2ba">9bde-563437a6e2ba</a></li> </ul>
DESIRA - inventory of digital tools for agriculture, forestry, and rural areas
<p>Inventory of digital tools for agriculture, forestry, and rural areas collected by the DESIRA consortium.</p>
Environmental Data for Soil, Leaf, and Root samples Boston Street Trees and Massachusetts Rural and Urban Forests in Summer 2021
This dataset provides detailed environmental and tree-level data and metadata for over 850 samples collected from 91 trees across an urban-to-rural gradient in Massachusetts. The dataset captures key variables characterizing urban environmental gradients, including soil moisture, pH, temperature, and nitrogen availability. Tree-level attributes include species identification, diameter at breast height (DBH), and growth rate based on previous tree census data. Geographic coordinates and site-specific context (urban forest, rural forest, street tree, forest edge, forest interior) are included to enable spatial analyses. The microbial sequence data associated with this environmental metadata can be found in the NCBI SRA under BioProject accession number PRJNA1297772.
2000-2018 SUHII and Rural LST Monthly Means used in Sismanidis et al. 2022
<p>This dataset provides the 2000-2018 SUHII and rural LST monhtly means used in Sismanidis et al. (2022). The source of the LST data is the the <a href="https://climate.esa.int/en/odp/#/project/land-surface-temperature">v1.0 Terra MODIS data product</a> created by the <a href="https://climate.esa.int/en/projects/land-surface-temperature/">ESA-CCI project on Land Surface Temperature (LST_cci)</a>.</p>
Geochemistry of soils and eroded suspended sediments from two large rural catchments in southern Brazil for studies on Suspended Sediment Fingerprinting
<p> <strong>1. Introduction</strong></p> <p>This dataset comes from a research project entitled "Water and pollutants, from cropfields to cities: evaluation and improved of soil management technologies in a catchment network " supported by the Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS) and National Council for Scientific and Technological Development (CNPq) (process n°10/0034-0). The project was carried out between 2010 and 2014 under the coordination of José Miguel Reichert and Danilo Rheinheimer dos Santos, professors at the Federal University of Santa Maria. One of the aims of this project was to understand the main pollutant transfer process from hillslopes to fluvial systems in large rural catchments representative of the agricultural production system in Southern Brazil. In this context, the Suspended Sediment Fingerprinting (SSF) was extremely useful for quantifying the origin of the sediment yield monitored at the outlet of these catchments. Among the various works carried out in this project, we highlight Tales Tiecher's doctoral thesis (Tiecher, 2015) that explored the SSF in many catchments, including the Conceição and Guaporé river basins.</p> <p><strong>2. Material and Methods</strong></p> <p>The catchments represent the magnitude of erosive and hydrological processes representative of Southern Brazil. The Conceição catchment has a drainage area of 804 km<sup>2</sup> (28°27′22″S and 53°58′24″ W). According to Köppen, the climate is Cfa type, with an annual rainfall between 1,750 and 2,000 mm. Geology is riodacithe basalt, with a formation of deep and highly weathered soils (Oxisols, Ultisols, and Alfisols). The relief is characterized by gentle slopes (6–9 %) on top and hillside slopes and higher steepness (10–14%) near the drainage channels. Farming based on the production of soybeans (<em>Glycine max</em>) in summer and wheat (<em>Triticumspp.</em>), oats (<em>Avena strigosa</em>), and ryegrass (<em>Lolium multiflorum</em>) in winter. The Guaporé catchment has a drainage area of 1,980 km<sup>2</sup> (28°54′41″S and 51°57′10″W), it covers part of the meridional plateau border. The climate is classified as Cfa, with annual rainfall varies between 1,400 and 2,000 mm. Geology is characterized by volcanic lava flows, and topography is undulating to hilly. Due to variations in landscape, several classes of soils (Entisols, Luvisol, Cambisol, Oxisol, Ultisol, and Chernosol). The land use is highly heterogeneous. In the upper third of the catchment, there is a predominance of soybean cultivated under no-tillage soil management. In the other two-thirds (middle and lower parts), land use and soil management are very heterogeneous. The main land uses are tobacco (<em>Nicotiana tabacum</em>) and maize (<em>Zea mays</em>) crops, Eucalyptus (<em>Eucalyptus</em> spp.), as well as pastures for dairy cattle. The contribution of unpaved roads is relevant to the sediment yield in both catchments (Didoné et al., 2014). Composite samples of potential sediment sources (cropland, unpaved roads, and stream channel banks) were collected. Sediment source samples were taken from the surface soil layer (0–0.05 m) of cropland and unpaved roads and on exposed sites located along the river channel network. Each sample was composed of at least 10 subsamples. To obtain representative samples of suspended sediment transported in the catchment’s outlet were used three strategies: (1) to collect flood suspended sediments (FSS) through the manual sampling (USDH-48) at different periods during the rising and falling stages of floods; (2) to deploy time-integrated suspended sediment samplers (TISS), by installing the device developed by Phillips et al. (2000) at different sites within the catchments; to collect fine-bed sediment (FBS) with a suction stainless sampler limiting the loss of fine material at the bed river. Source and sediment samples were oven‐dried at 50 °C, gently disaggregated using a pestle and mortar, and then sieved to 62,5 μm. The geochemical tracers evaluated were total organic carbon estimated by wet oxidation (K<sub>2</sub>Cr<sub>2</sub>O<sub>7</sub> + H<sub>2</sub>SO<sub>4</sub>) and the total concentration of Al, Ba, Be, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, and Zn using inductively coupled plasma optical emission spectrometry after microwave‐assisted digestion with concentrated HCl and HNO<sub>3</sub> (ratio 3:1) for 9.5 min at 182 °C (Tiecher, 2015; Tiecher et al. 2017, 2018).</p> <p> <strong>3. Final remarks</strong></p> <p> The SSF results provided by this dataset (Tiecher, 2015) combined with sediment yield monitoring were very important for the assessment and modeling studies in these two catchments that took place after that (Didoné et al., 2015; 2017). In addition, other studies have explored the same sample bank, expanding upon the array of tracer properties and increasing our understanding about the mechanisms of sediment and pollutant transfer in these catchments (Le Gall et al. 2017; Zafar et al., 2017; Ramon et al., 2020).</p> <p> <strong>4. References</strong></p> <p> Didoné, E. J., Minella, J. P. G., Reichert, J. M., Merten G. H., Dalbianco, L., Barros, C. A. P., Ramon, R. (2014) Impact of no-tillage agricultural systems on sediment yield in two large catchments in southern Brazil. J Soils Sediments 14:1287–1297.</p> <p>Didoné, E.J., Minella, J.P.G., Evrard, O. (2017). Measuring and modelling soil erosion and sediment yields in a large cultivated catchment under no-till of Southern Brazil. Soil Tillage Res. 174, 24-33. https://doi.org/10.1016/j.still.2017.05.011</p> <p>Didoné, E. J.; Minela, J. P. G.; Merten, G. H. (2015). Quantifying soil erosion and sediment yield in a catchment in southern Brazil and implications for land conservation. J. Soils Sediments 11, 2334-2346. https://doi.org/10.1007/s11368-015-1160-0</p> <p>le Gall, M., Evrard, O., Dapoigny, A., Tiecher, T., Zafar, M., Minella, J. P. G., Laceby, J. P., & Ayrault, S. (2017). Tracing sediment sources in a subtropical agricultural catchment of southern Brazil cultivated with conventional and conservation farming practices. Land Degradation and Development, 28(4). https://doi.org/10.1002/ldr.2662</p> <p>Ramon, R., Evrard, O., Laceby, J. P., Caner, L., Inda, A. v., Barros, C. A. P., Minella, J. P. G., & Tiecher, T. (2020). Combining spectroscopy and magnetism with geochemical tracers to improve the discrimination of sediment sources in a homogeneous subtropical catchment. Catena, 195, 104800. https://doi.org/10.1016/j.catena.2020.104800</p> <p>Tiecher, T. (2015). Fingerprinting sediment sources in agricultural catchments in Southern Brazil. Doctoral Dissertation in Soil Science. Universidade Federal de Santa Maria, Santa Maria, RS.</p> <p>Tiecher, T., Minella, J. P. G., Caner, L., Evrard, O., Zafar, M., Capoane, V., le Gall, M., & Santos, D. R. D. (2017). Quantifying land use contributions to suspended sediment in a large cultivated catchment of Southern Brazil (Guaporé River, Rio Grande do Sul). Agriculture, Ecosystems and Environment, 237. https://doi.org/10.1016/j.agee.2016.12.004</p> <p>Tiecher, T., Minella, J. P. G., Evrard, O., Caner, L., Merten, G. H., Capoane, V., Didoné, E. J., & dos Santos, D. R. (2018). Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Conceição River). Land Degradation and Development, 29(4). https://doi.org/10.1002/ldr.2917.</p> <p>Zafar, M., Tiecher, T., Capoane, V., Troian, A., dos Santos, D.R. (2017). Characteristics, lability and distribution of phosphorus in suspended sediment from a subtropical catchment under diverse anthropic pressure in Southern Brazil. Ecol. Eng. 100, 28–45.</p>
Offering ART refill through community health workers versus clinic-based follow-up after home-based same-day ART initiation in rural Lesotho: The VIBRA cluster-randomised clinical trial
<p>These are pseudo-anonymised data from the VIBRA randomized trial: "Offering ART refill through community health workers versus clinic-based follow-up after home-based same-day ART initiation in rural Lesotho: The VIBRA cluster-randomised clinical trial". The data dictionary explains the data available in the dataset. Between August 2018 and May 2019, 257 eligible individuals from 117 consenting villages were enrolled from two districts of Lesotho, and followed up for a maximum of 15 months. The protocol was published, doi: 10.1186/s13063-019-3510-5</p>
Awareness, treatment, and control among adults living with arterial hypertension or diabetes mellitus in two rural districts in Lesotho
<p>These are pseudo-anonymised data from the ComBaCaL survey and belong to the manuscript "Awareness, treatment, and control among adults living with arterial hypertension or diabetes mellitus in two rural districts in Lesotho". </p> <p>The data dictionary explains the critical data available in the dataset. Between November 2021 and August 2022 , 6061 participants over 18 years old were visited in their households in two districts of Lesotho. Of these, data from those who were diagnosed with either hypertension or diabetes were further analysed and are documented here.</p>
Dust geochemistry and lead isotopes along an urban-rural transect in central Ohio, 2021
This data package contains geochemical concentrations and stable lead isotope ratios for dust samples collected along an urban-rural land use gradient in central Ohio during 2021. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, to see how much dust varies across land use and by season. At four sites along an urban-rural transect in central Ohio, we collected weekly bulk deposition samples and analyzed the geochemical composition (47 elements including major elements, trace metals, and rare earth elements) and stable lead isotopes (208Pb, 207Pb, 206Pb, and 204Pb) of the particulate matter. This study demonstrates the tight connection between land use and anthropogenic dust composition in a region where land use is changing rapidly as development encroaches into farmland. This dataset is complete and will not be updated.
Air mass back-trajectory modeling output along an urban-rural transect in central Ohio, 2021
This data package contains modeled air parcel back-trajectories generated using the Stochastic Time-Inverted Lagrangian Transport model (STILT) via the R interface. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, and to connect the geochemistry of deposited dust to air mass trajectories. Back-trajectories are three-dimensional paths of air parcels from a receptor site (the dust collection site) backwards in time and space for the duration of the tracking interval, calculated iteratively using wind fields from high-resolution gridded meteorological data. To calculate a probability of potential pathways, rather than a single back-trajectory, STILT introduces small random perturbations into the wind fields during each time step. For four sites along an urban-rural transect in central Ohio for June-July 2021, we generated weekly footprints of potential sources for the dust deposited at each site. These back-trajectories can be paired with geochemical data to establish a connection between land use and anthropogenic dust composition. This dataset is complete and will not be updated.
Baltimore Ecosystem Study: Soil moisture and temperature along an urban to rural gradient, 2011 - present
Soil temperature and soil moisture have been measured at multiple locations in and around Baltimore Maryland to provide data on these variables in forests and lawns across an urban to rural gradient. In July 2011, we installed one Decagon Em50 Datalogger with five 5TM VWC/Temperature probes at four established forested, upslope, 20 x 20-m plots, two rural (ORU1, ORU2) and two urban (LEA1, LEA2), at 2 forested riparian sites at two transects along a stream (ORUR, ORLR), and two lawn plots on the campus of the University of Maryland Baltimore County campus (UMBC1, UMBC 2). Probes were buried horizontally at 10cm depth (except UMBC1 and UMBC2 where the five probes are mounted horizontally at a single location at depths of 50, 40, 30, 20 and 10 cm depth). At the upslope forested plots, the five probes are replicates. At the two riparian sites, probes are deployed in either "hummocks (drier, higher)" or in "hollows (lower, wetter)". Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in July 2011. In March 2017, an additional data logger was installed at Hillsdale Park (HD1) in a forested urban area. The five probes at HD1 were buried horizontally at 10cm depth and are replicates. Earlier soil moisture data were collected monthly (1999-2011), and can be found in https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=417
Urban-Rural Temperature Data-relation between land-cover and the Urban Heat Island in San Juan, Puerto Rico
Our objective in this study is to quantify the UHI created by the San Juan Metropolitan Area over space and time using temperature data collected by mobile and fixed-station measurements. We used the fixed-station measurements to examine the relation between average temperature at a given location and the density of vegetation located upwind. We then regressed temperatures against regional land-cover to predict future temperature with projected land-cover change. Our data show the existence of a nocturnal UHI, with average nighttime urban-rural temperature differences (ΔTU-R) of up to 3.02°C. Each of the stations listed in this excel file were used to calculate the urban heat island created by the San Juan Metropolitan Area. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Source apportionment of highly time-resolved elements during a firework episode from a rural freeway site in Switzerland
<p>Data to accompany "Source apportionment of highly time-resolved elements during a firework episode from a rural freeway site in Switzerland" publication in Atmospheric Chemistry and Physics. This repository contains measurement data in Härkingen, Switzerland, a permanent station of the Swiss National Air Pollution Monitoring Network (NABEL). Sampling was performed from 23 July to 13 August 2015. This repository has excel file (all data.xlsx) for all the raw data measured during campaign. In addition, it has data corresponding to each figures presented in main text published version.</p>
Survey of open data and information seeking in Kenya's Urban Slums and Rural Settlements
<p>This dataset provides survey responses from 240 people surveyed as part of the "Investigating the Impact of Kenya’s Open Data Initiative on Marginalized Communities: Case Study of Urban Slums and Rural Settlements" project.</p> <p>The data, collected in mid-2013 looks at issues of where citizens look for data, and how successful they have been in getting government information from different sources, as well as their awareness of the Kenya open data portal, and their interest in getting information through different digital channels in future.</p> <p>Descriptive statistics have been analysed in the publication "Open Government Data for Effective Public Participation: Findings of a Case Study Research Investigating The Kenya's Open Data Initiative in Urban Slums and Rural Settlements", but no further analysis has yet been carried out.</p> <p><strong>Data descriptions</strong></p> <p>The Codebook.csv file lists variable names and the questions asked to elicit each response.</p> <p>JHC-Data.csv contains the results from the questionnaires collected through structured in-person interview in the three locations. The questionnaires were administered at chiefs centres, community resource centres, constituency development fund office and religious centres). The questionnaires were filled in by every 2nd these centres.</p> <p><strong>More information</strong></p> <p>More information on the research project can be found at http://opendataresearch.org/project/2013/jhc</p>
Global urban and rural settlement dataset from 2000 to 2020
<p>Data Update (v2.1): Added WGS84 coordinate-referenced datasets with longitude/latitude gridded partitions for localized access.</p>
Thermal changes along the urban-rural continuums in Southeast Asia
<p>This research has been published in Environmental Research Letters. Please cite it as shown below when using this dataset:</p> <p>Citation:<strong> Zhu, Y., Myint, S., Chen, J., Fan, P., Seto, K., Jain, A. K., Qi, J., & Wang, J. (2025). Thermal changes along the urban-rural continuums in Southeast Asia. Environmental Research Letters. <a href="https://doi.org/10.1088/1748-9326/adcad2">https://doi.org/10.1088/1748-9326/adcad2</a>.</strong></p> <p> </p> <p>Our study focused on 19 cities across 8 countries: Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. The cities included Phnom Penh, Siem Reap, Jakarta, Surabaya, Denpasar, Vientiane, Pakse, KL, Putrajaya, Yangon, NPT, Quezon City, Iloilo, Taytay, Bangkok, Chiang Rai, HCMC, Hanoi, Cantho. </p> <p>To assess the impact of urbanization over the past two decades, we examined the patterns of Land Surface Temperature (LST) changes with Land Use and Land Cover (LULC) changes across 19 cities in SEA along the urban-rural continuums (URCs). These cities include major urban hubs such as Jakarta, Bangkok, and Ho Chi Minh City, as well as medium and smaller cities like Vientiane and Chiang Rai, reflecting a diversity of urban environments and providing a comprehensive sample of SEA’s rapid urban expansion and associated thermal impacts. The boundaries of URCs for each city were defined as an area centered within a 30 km radius from its city center point. This ensured that all cities had the same extent so that the URCs could make the comparison. The city center point was defined as either the center of the central business district or the geometric center of the city’s administrative limits (Estoque et al., 2017). We created 30 ring buffer zones around each city center point at 1 km intervals to analyze LULC and the associated LST change gradient along the URCs. After establishing these buffer zones, we excluded (1) large water bodies or oceans, (2) continuous urban areas beyond the city boundaries—for cities located close to one another, such as Kuala Lumpur and Putrajaya, and Quezon City and Taytay, the city’s URCs were adjusted to exclude overlapping administrative boundaries from neighboring cities, ensuring that the analysis was confined to each city’s specific URCs, and (3) mountains with elevations exceeding 100 m above the mean elevation of each city buffer to minimize the confounding effects of topography on LST variations to ensure that the LST changes we observed were more directly attributable to urban development rather than elevation-related climatic variations. (C. Wang et al., 2016; Z. Wang et al., 2020). These exclusions were implemented to ensure a fair comparison, avoid confusion, and reduce the influence of elevation on the analysis.</p> <p>For URCs, we retrieved LST and NDVI data for the summer months (June, July, and August) between 2000 and 2022 at a 30-meter resolution based on the Google Earth Engine Platform. This period was chosen due to peak heat-related mortality and morbidity (Hsu et al., 2021; Johnson et al., 2009). A total of 5,805 Landsat 5/7/8/9 scenes were collected to ensure full coverage of all 19 cities. Contaminated pixels (e.g., clouds and cloud shadows) were removed via quality assessment bands and Landsat-7 SLC-off stripes were eliminated. NDVI was calculated from the surface reflectance of the Red and Near-Infrared (NIR) bands. LST retrieval from Landsat data was conducted using the Statistical Mono-Window (SMW) algorithm developed by the Climate Monitoring Satellite Application Facility (CM-SAF) (Duguay-Tetzlaff et al., 2015; Freitas et al., 2013; Sun et al., 2004). Further details are provided in the Supplemental materials.</p> <p>The final datasets are LST in 2022, LST Sen's Slope (2000-2022), and NDVI Sen's Slope (2000-2022) and are shared.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.