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50 results for “Urban agriculture”
North Temperate Lakes LTER: Patterns of Soil Phosphorus Across an Urbanizing Agricultural Landscape 2000 - 2001
Understanding the magnitude and location of soil phosphorus (P) accumulation in watersheds is a critical step toward managing runoff of this pollutant to aquatic ecosystems. Here, we examined the usefulness of urban-rural gradients (URGs), an emerging paradigm in urban ecology, for predicting soil P concentrations across a rapidly urbanizing agricultural watershed in southern Wisconsin. We compared several measures of an urban-rural gradient to predictors of soil P such as soil type, slope, topography, land use, land cover, and fertilizer and manure use. Most of the factors that were expected to drive differences in soil P concentrations were not found to be good predictors of soil P; while there were several significant relationships, most explained only a small proportion of the variation. There was a significant relationship between soil P concentration and each of the urban-rural gradients, but these relationships explained only a small amount of the variation in soil P concentrations. Soil P concentration, unlike some other ecosystem properties, is not well predicted by urban-rural gradients Additional Chemical Analyses: These additional analyses were done to provide comparisons to Bray-1 P. Specifically, we wanted to know whether, in Dane County, there was a consistent relationship between total P and Bray-1 P. For sample sites on private property, specific site location information, such as GPS coordinates, is not included in these datasets. If you have a need for this information, please get in touch with the contact person listed above Number of sites: 334; 20 of these sites with additional chem analyses
Milan (ITALY) - Urban Agriculture spatial dataset (years 2007 and 2014)
<p>The data in this dataset is a spatial inventory of <strong>urban agriculture</strong> (UA) carried out in the city of Milan (Italy). UA areas where identified with a multi-step and iterative procedure by using different web-mapping tools, especially multitemporal Google Earth images, and ancillary data such as Google Street View and Bing Maps.</p> <p><strong>License</strong></p> <p>Creative Commons CC-BY</p> <p><strong>Disclaimer</strong></p> <p>Despite our best efforts to validate the data, some information may be incorrect.</p> <p><strong>Description of the dataset</strong></p> <p><em><strong>Typologies of UA</strong></em></p> <ul> <li><strong>Residential garden: </strong>Private parcel near single houses (e.g. backyard), villas, buildings, industrial and commercial activities, generally managed by property owners. Cultivation is diversified ranging from leafy vegetables to herbs and fruit trees. Production is intended for self-consumption and/or for hobby purposes.</li> <li><strong>Community garden: </strong>A large area subdivided into multipleplots managed individually (i.e. allotment) or collectively by a group of people. Crop production is intended for self-consumption. Land is assigned by the Municipality; several cases of land cultivated without authorization are also common.</li> <li><strong>Urban farm: </strong>Parcel managed by professional farmers with an intensive and an advanced cropping system. The cultivation can be specialized or oriented to high diversity vegetables. The production is intended for market. The mapping procedure focus on arable crops, horticulture, vineyard, olive groves and orchard.</li> <li><strong>Institutional garden: </strong>Parcel managed by institutions or organizations like schools, religious center, prisons and non-profit organizations. The production is generally intended for self-consumption and less frequently for trade. Several gardens in this category are intended for social purposes (e.g. recreation,education, etc.).</li> <li><strong>Illegal garden: </strong>Parcel isolated, cultivated without authorization organized and managed individually or by a few people. Localization occurs on unused or abandoned areas owned by public bodies or private subjects. The production is intended for self-consumption.</li> <li><strong>Nurseries: </strong>A large area subdivided into multiple plots managed for growing ornamental plants and flowers.</li> </ul> <p><em><strong>Land use typologies</strong></em></p> <ul> <li><strong>Horticulture: </strong>annual crops generally seed sown in spring or summer (tomatoes, lettuce, zucchini, cucumbers, peppers).</li> <li><strong>Vineyard: </strong>grape vines grown in order to produce wine or table grape.</li> <li><strong>Olive groves: </strong>olive trees grown in order to produce olive oil or table olives.</li> <li><strong>Orchards: </strong>mixed trees such as orange, stone fruit, pome fruit, olive trees.</li> <li><strong>Mixed crops: </strong>an area grown with a mix of horticulture crops and fruit trees, not divisible.</li> <li><strong>Nurseries: </strong>ornamental plants, trees, flowers.</li> </ul> <p><strong>Credit</strong></p> <p>Pulighe G., Lupia F. (2019) <em>Multitemporal Geospatial Evaluation of Urban Agriculture and (Non)-Sustainable Food Self-Provisioning in Milan, Italy. </em><strong>Sustainability </strong>2019, <em>11</em>(7), 1846</p> <p>https://www.mdpi.com/2071-1050/11/7/1846</p>
Formalizing Objectives and Criteria for Urban Agriculture Sustainability with a Participatory Approach
<p>The last few years have seen an exponential development of urban agriculture projects within global North countries, especially professional intra-urban farms which are professional forms of agriculture located within densely settled areas of city. Such projects aim to cope with the challenge of sustainable urban development and today the sustainability of the projects is questioned. To date, no set of criteria has been designed to specifically assess the environmental, social and economic sustainability of these farms at the farm scale. Our study aims to identify sustainability objectives and criteria applicable to professional intra-urban farms. It relies on a participatory approach involving various stakeholders of the French urban agriculture sector comprising an initial focus group, online surveys and interviews. We obtained a set of six objectives related to environmental impacts, link to the city, economic and ethical meaning, food and environmental education, consumer/producer connection and socio-territorial services. In addition, 21 criteria split between agro-environmental, socio-territorial and economic dimensions were identified to reach these objectives. Overall, agro-environmental and socio-territorial criteria were assessed as more important than economic criteria, whereas food production was not mentioned. Differences were identified between urban farmers and decision makers, highlighting that decision makers were more focused on projects' external sustainability. They also pay attention to the urban farmer agricultural background, suggesting that they rely on urban farmers to ensure the internal sustainability of the farm. Based on our results, indicators could be designed to measure the sustainability criteria identified, and to allow the sustainability assessment of intra-urban farms.</p>
Urban Agriculture and Health: Insights from Anonymized Expert Interviews on Spatial Planning in Greater Lomé, Togo
<p>Transcripts of anonymized interviews with 11 urban planning experts in Greater Lomé on the subject of urban agriculture, health and spatial planning.</p>
Dataset for publications "Willingness to pay for urban agriculture in Oslo" and "The Value of Urban Farming in Oslo, Norway: Community Gardens, Aquaponics and Vertical Farming"
<p>Dataset for publications “(Willingness to pay for urban agriculture in Oslo)[https://zenodo.org/record/6510590#.Y851cXbMLfs]" and “The Value of Urban Farming in Oslo, Norway: Community Gardens, Aquaponics and Vertical Farming”. The data was collected as a contingent valuation study of urban agriculture in Oslo, Norway.</p>
Urban Agriculture and Health in Africa. A Review
<p>The Excel table is raw data containing publications from the systematic literature review on urban agriculture's impacts on health and urban planning research.</p> <p>This work was totally funded by the Swiss National Science Foundation (SNF#18357) Sinergia Project – African Contribution to Global Health: Circulating Knowledge and Innovations.</p>
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15
Bulk atmospheric deposition data along an agricultural-to-urban transect, central Ohio, 2021-2022
As precipitation acidity in the United States has decreased dramatically over the past forty years, new questions have emerged about the role of base cations and nitrogen (N) species in regulating precipitation pH. To address these questions, we studied precipitation chemistry in Ohio, a state with high N deposition and a mix of urban, industrial, and agricultural land use. This dataset contains precipitation chemistry and the flux of particulate matter collected at four sites along an agricultural-urban transect in central Ohio over the summers of 2021 and 2022. Samples were collected weekly from three or five replicate passive bulk deposition collectors at each site. In the lab, we filtered the samples and calculated the flux of total particulate matter. Liquid samples were measured for pH, nitrate, ammonium, and major ions. This dataset is complete and will not be added to in the future.
WRF-Chem output- concentrations for the 4 simulations: reference, urbanization, extension of agricultural areas and more urban parks
<p>We use the WRF-Chem air-quality model with an urban canopy scheme to investigate how land use (urban, agriculture, parks) affects the urban climate and chemical processes (dry deposition, biogenic emissions), resulting in changes in air quality for scenarios proposed by the Urban Master Plan of the Metropolitan Area of Barcelona. We selected a heatwave period, 4th-7th July 2015, with maximum temperatures reaching 40 °C in the interior of the AMB and 35 °C on the coast. Here we provide averaged model output for the heatwave period for the different pollutants, surface temperature, wind speed, PBLH, deposition, and biogenic emissions under different urban scenarios: reference (REF), urbanization (URB), extension of agriculture (AGR), and increase in urban parks (PARK).<br><br>The results for a period before the heatwave (1-3 July 2015), with temperatures 3-4 degrees lower than during the heatwave, are also provided. <br><br>Land-use and irrigation is also provided for each scenaio. </p>
Rome (ITALY) - Urban Agriculture spatial dataset (years 2007 and 2013)
<p><strong>Motivation</strong></p> <p>The data in this dataset is a spatial inventory of <strong>urban agriculture</strong> (UA) carried out in the city of Rome (Italy) (Grande Raccordo Anulare (GRA)). UA areas where identified with a multi-step and iterative procedure by using different web-mapping tools, especially multitemporal Google Earth images, and ancillary data such as Google Street View and Bing Maps.</p> <p><strong>License</strong></p> <p>Creative Commons CC-BY</p> <p><strong>Disclaimer</strong></p> <p>Despite our best efforts to validate the data, some information may be incorrect.</p> <p><strong>Description of the dataset</strong></p> <p><em><strong>Typologies of UA</strong></em></p> <ul> <li><strong>Residential garden: </strong>Private parcel near single houses (e.g. backyard), villas, buildings, industrial and commercial activities, generally managed by property owners. Cultivation is diversified ranging from leafy vegetables to herbs and fruit trees. Production is intended for self-consumption and/or for hobby purposes.</li> <li><strong>Community garden: </strong>A large area subdivided into multipleplots managed individually (i.e. allotment) or collectively by a group of people. Crop production is intended for self-consumption. Land is assigned by the Municipality; several cases of land cultivated without authorization are also common.</li> <li><strong>Urban farm: </strong>Parcel managed by professional farmers with an intensive and an advanced cropping system. The cultivation can be specialized or oriented to high diversity vegetables. The production is intended for market. The mapping procedure focus exclusively on horticulture, vineyard, olive groves and orchard.</li> <li><strong>Institutional garden: </strong>Parcel managed by institutions or organizations like schools, religious center, prisons and non-profit organizations. The production is generally intended for self-consumption and less frequently for trade. Several gardens in this category are intended for social purposes (e.g. recreation,education, etc.).</li> <li><strong>Illegal garden: </strong>Parcel isolated, cultivated without authorization organized and managed individually or by a few people. Localization occurs on unused or abandoned areas owned by public bodies or private subjects. The production is intended for self-consumption.</li> </ul> <p><em><strong>Land use typologies</strong></em></p> <ul> <li><strong>Horticulture: </strong>annual crops generally seed sown in spring or summer (tomatoes, lettuce, zucchini, cucumbers, peppers).</li> <li><strong>Vineyard: </strong>grape vines grown in order to produce wine or table grape.</li> <li><strong>Olive groves: </strong>olive trees grown in order to produce olive oil or table olives.</li> <li><strong>Orchards: </strong>mixed trees such as orange, stone fruit, pome fruit, olive trees.</li> <li><strong>Mixed crops: </strong>an area grown with a mix of horticulture crops and fruit trees, not divisible.</li> </ul> <p><strong>Credit</strong></p> <p>Pulighe G., Lupia F. (2016) <em>Mapping spatial patterns of urban agriculture in Rome (Italy) using Google Earth and web-mapping services. </em><strong>Land Use Policy</strong> 59(2016) 49-58.</p> <p><a href="http://www.sciencedirect.com/science/article/pii/S0264837716300059"><em>www.sciencedirect.com/science/article/pii/S0264837716300059</em></a></p>
SiEUGreen_Dataset_for_Monitoring_the_contribution_of_urban_agriculture_to_urban_sustainability:_an_indicator-based_framework
<p>The data was collected for scientific publication: Tapia, C., Randall, L., Wang, S.; Borges, L. A. (2021): Monitoring the contribution of urban agriculture to urban sustainability: an indicator-based framework. <em>Sustainable Cities and Society</em>. In press, <a href="https://doi.org/10.1016/j.scs.2021.103130">https://doi.org/10.1016/j.scs.2021.103130</a></p> <p>This dataset includes the data from the survey in Brabrand Fallaesgartneriet, which is the study case reported in the article.</p>
Urban Agriculture and Farmers Well-Being In Dar Es Salaam And Greater Lomé
<p>Primary data collected on Urban Agriculture and Farmers Well-Being In Dar Es Salaam And Greater Lomé.</p>
Dancing bees evaluate central urban forage resources as superior to agricultural land
<p class="ColorfulList-Accent11CxSpFirst">Recent evidence suggests that flower-rich areas within cities could play an important role in pollinator conservation, but direct comparison of floral resources within agricultural and urban areas has proved challenging to perform over large scales.</p> <p class="ColorfulList-Accent11CxSpMiddle">Here we use the waggle dances of honeybees (<i>Apis mellifera</i> L.) to perform large-scale landscape surveys at heavily urban or agricultural sites for a key pollinator of wild and crop plants. We analyzed 2827 dances that were performed by 20 colonies in SE England.</p> <p class="ColorfulList-Accent11CxSpMiddle">We show that hive median foraging trip distance is consistently lower at urban sites across the entire season. The sucrose content of collected nectar did not significantly differ between urban and agricultural land, ruling out the possibility that longer foraging distances in agricultural sites were driven by distant but nectar-rich resources.</p> <p class="ColorfulList-Accent11CxSpMiddle">Within cities, bees preferentially targeted residential areas on foraging trips, while trips to mass-flowering crops overwhelmingly dominated at agricultural sites. For both land-use types, distances flown increased in the summer, but there was high variation in temporal patterns between individual sites</p> <p class="ColorfulList-Accent11CxSpLast"><i>Policy implications: </i>From the self-reported perspective of a generalist pollinator, forage was easier to find in heavily urbanized areas than in the modern agricultural landscapes that we studied. A focus on continuous spatial and temporal provision within agricultural environments is key to redressing this imbalance.</p>
Survey data of an integrative evaluation framework for assessing the sustainability of different types of urban agriculture
<p>In this dataset we present core data of an integrative evaluation framework for assessing the environmental, social, and economic sustainability of urban agriculture. The multi-criteria analysis is conducted by an Analytic Hierarchy Process and a participatory approach. The data integrate the selection and weighting of sub-criteria based on two online surveys:</p> <p>1) Survey 1: The selection of suitable sub-criteria for assessing the sustainability of urban agriculture was done by European scientific experts.</p> <p>2) Survey 2: The weighting of the selected sub-criteria was done on the example of vertical farming and community supported agriculture. Therefore, we involved stakeholders representing key actors for the implementation of urban agriculture: city administrations and non-governmental organizations (NGOs) of ten German case study cities, practitioners and technical-scientific experts.</p> <p> </p> <p><strong>List of data and content</strong></p> <p>1) Survey_1 (*.zip):</p> <ul> <li>Survey_1_Criteria_Selection_English: Online survey in English (*.pdf)</li> <li>Survey_1_Information_Sub-criteria_English: Information about the sub-criteria provided in the survey (in English) (*.pdf)</li> <li>Survey_1_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)</li> </ul> <p>2) Survey_2 (*.zip):</p> <ul> <li>Survey_2_AHP_City_Administrations_German: Online survey for city administrations in German (*.pdf)</li> <li>Survey_2_AHP_Practitioners_German: Online survey for practitioners and technical-scientific experts in German (*.pdf)</li> <li>Survey_2_AHP_NGOs_German: Online survey for NGOs in German (*.pdf)</li> <li>Survey_2_Information_Sub-Criteria_German: Information about the sub-criteria provided in the survey (in German) (*.pdf)</li> <li>Survey_2_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)</li> <li>rdata_CA_AHP_edible_Cities_2022-03-18_10-28: Results of the survey for city administrations (*.csv)</li> <li>rdata_NGO_AHP_edible_Cities_2022-03-18_10-40: Results of the survey for NGOs (*.csv)</li> <li>rdata_PE_AHP_edible_Cities_2022-03-18_10-41: Results of the survey for practitioners and technical-scientific experts (*.csv)</li> <li>rdata_all_AHP_edible_Cities_2022-03-18_09-53: Total results of the survey</li> </ul> <p> </p> <p><strong>Data acquisition and processing</strong></p> <p>The methods are described in this linked publication:</p> <p><span>John, H., & Artmann, M. (2024). Introducing an integrative evaluation framework for assessing the sustainability of different types of urban agriculture. </span><span>I<em>nternational Journal of Urban Sustainable Development, </em></span>16 (1), 35-52<em><span>. </span></em><span>doi:<em> </em>10.1080/19463138.2024.2317795</span></p> <p>The methodology of the performed analytic hierarchy process (AHP) is published in a separate repository on GitHub including a paper that systematically explains the AHP by means of code examples, starting with the raw data, through their adaptation to the software functions of the ahpsurvey R-package, and finally, execution of the AHP up to the visualization of the results.</p> <p> </p> <p><strong>Acknowledgments</strong></p> <p>The authors thank Mabel Killinger and Marie Herzig for their help in stakeholder identification as well as all experts and stakeholders for their participation in the two online surveys and their helpful comments. Data processing and analysis by means of an Analytic Hierarchy Process in R would not have been possible without the help of Björn Kasper.</p>
Datasets and analysis for: Microclimatic buffering in forest, agricultural and urban landscapes through the lens of a grass-feeding insect
<p>Using this dataset, we aimed to identify the microclimatic offsets that accurately represent the environment in which a small arthropod spends most of its life. As a case study, we selected grassy sites that corresponded to the microhabitat of grass-feeding insects in general, and larvae of the butterfly <em>Pararge</em> <em>aegeria</em> in particular, as this insect recently expanded its habitat use from forest (edges) to agricultural and urban environments. We tested to what extent local microclimates and microclimatic buffering capacity differed between tufts of grass in forest and in two anthropogenic (i.e. agricultural and urban) landscape settings by measuring microclimatic variables with sensors at the level of the grasses. We compared temperature, relative humidity and vapour pressure deficit (VPD) during an exceptionally warm and dry summer period with parallel data from weather stations and tested for differences between microclimatic profiles among the three landscape settings. Using this approach, our findings stress the functional implications of landscape-specific microclimatic profiles at the appropriate organism-centred scale.</p>
Validating NISAR's cropland mapping approach and the USDA/NASS Cropland Data Layer against ground truth data in a fragmented urban agricultural region
<p>Field data used in manuscript:</p> <p>1 shapefile containing the ROI outline for which Sentinel-1 data was cropped</p> <p>1 shapefile containing the 93 fields investigated with their names, types and sizes as attributes </p> <p>8 annual csv data for active fields, consisting of 3 harvest dates and 5 planting dates. This list is after translating data from Farmlogic Report (not conducive to analysis in the format) and filtering for fields greater 1 acre. The study lateron further screened to use only fields greater than 2 acreas (0.81 hectares). </p> <p> </p>
A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change
<p class="MsoNormal"><span>Identifying environmental characteristics that limit species' distributions is important for contemporary conservation and inferring responses to future environmental change. The Tasmanian native hen is an island-endemic flightless rail and a survivor of a prehistoric extirpation event. Little is known about the regional-scale environmental characteristics influencing the distribution of native hens, or how their future distribution might be impacted by environmental shifts (e.g., climate change). </span><span>Using a combination of local fieldwork and species distribution modelling, we assess environmental factors shaping the contemporary distribution of the native hen, and project future distribution changes under predicted climate change. We find 37.2% of Tasmania is currently suitable for the native hens, owing to low summer precipitation, low elevation, human-modified vegetation, and urban areas. <span>Moreover</span>, in unsuitable regions, </span><span>urban areas can create 'oases' of habitat, able to support populations with high breeding activity by providing resources and buffering against environmental constraints. Under climate change predictions, </span><span>native hens were predicted to lose only 5% of their occupied range by 2055. We conclude that the species is resilient to climate change and benefits overall from anthropogenic landscape modifications. As such, this constitutes a rare example of a flightless rail to have adapted to human activity.</span></p>
A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change
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Dancing bees evaluate central urban forage resources as superior to agricultural land
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Agriculture-urban interfaces, social vulnerability, and climate change shape West Nile virus risk across the United States
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Allen Brain Atlas
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International Brain Laboratory public data
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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.