microclimate

There are 18 repositories under microclimate topic.

  • IBM/appmod-resorts

    Transform your traditional on-premise application and deploy it as a containerized app on public or private cloud environments

    Language:Java1322429
  • microclimate-dev2ops/microclimate-vscode-tools

    Extension for developing cloud-native, containerized applications from VS Code

    Language:TypeScript95486
  • ajijohn/ebm

    UI for Microclimatic data for ecological forecasting

    Language:EJS24260
  • ajijohn/microclimRapi

    Microclim.org R API Toolkit

    Language:R2520
  • ajijohn/notebook

    Research Notebook Journal - Micromet studies

  • bgcasey/climate_downscaling

    Workflow and code for refining ClimateNA temperature predictions using temperature data loggers and remote sensing.

    Language:RMarkdown1200
  • mgrover1/dunes_microclimate

    An Analysis of Microclimate Sensor data taken from the Indiana Dunes National Lakeshore, from the USGS

    Language:Jupyter Notebook1202
  • mmikhail2001/esp32_weather_station

    Микроконтроллерная система для измерения качества воздуха в помещении с информированием о текущих показателях удаленного сервера.

    Language:C1100
  • AZ-Trotters/Microclimate-Recorder

    Embedded software for a device that senses and records microclimate data

    Language:C++0000
  • EcoClimLab/vertical-thermal-review

    Manuscript and new analysis files for Vinod et al., 2022, New Phytologist

    Language:TeX011190
  • mires

    efernandezpascual/mires

    Code, data and manuscript for "Fernández-Pascual, E. & Correia-Álvarez., E. (2021). Mire microclimate: groundwater buffers temperature in waterlogged versus dry soils. International Journal of Climatology." https://doi.org/10.1002/joc.6893

    Language:R0100
  • Jeremy-borderieux/Article_microclim_vosges

    Reproducible analysis of a microclimate and community ecology paper

    Language:R0100
  • jon-terschan/microclimate-taitahills

    Supplementary material to the Master's thesis "Assessing the Impact of TLS-Derived Vegetation Structure on Microclimatic Variability in Taita Hills, Kenya" by Jonathan Terschanski.

    Language:R0100
  • jon-terschan/OREF_microclimate

    TLS processing pipeline creates for an ongoing microclimate investigation by the EDYSAN lab.

    Language:R0100
  • wind-microclimate

    lampssy/wind-microclimate

    Python tool for automation of running and post-processing multiple CFD simulations, generating colour map representing wind comfort categories based on simulation results and historical weather data.

    Language:Python0100
  • meaganng/microclimate

    Climate change is a key factor in how extreme weather events affect how ecosystems and species react to these changes in temperatures. University of British Columbia's (UBC) Botanical Garden is interested in improving microclimate information within the garden to understand how areas with shade create respite zones for species. Due to the recent extreme weather temperatures in Vancouver, the garden is interested in how to continue to adapt and mitigate to these extremes. Microclimates are important as they are cooler temperatures beneath the canopy. Looking at how canopy cover influences land surface temperature can give insight on microclimates. Using LiDAR metrics to calculate canopy cover and Landsat to calculate land surface temperature, a model was built to understand the significance of canopy cover and land surface temperature, with the addition of other LiDAR metrics. The model could only determine a 34% variation between the variables tested. Canopy cover showed to have a p-value of 0.0993 and maximum height had a p-value of 0.0034. To investigate the results further, an unpaired t-test was run to determine the relationship between areas with canopy cover and areas without canopy cover. The t-test showed there are significant differences as the p-value was 0.0035. With the results, they provide observations of how canopy cover currently influences microclimate within the garden. Areas found to have a high percentage of canopy cover reflected lower land surface temperatures. Currently, the model has the structure to predict canopy cover with LiDAR metrics. However, finer data is needed to accurately predict microclimate. Recommendations are provided to enhance the study area with future directions for research within UBC Botanical Garden to conduct a more intricate analysis.

    Language:R0100
  • trdougherty/tom.d

    Machine Learning analysis of micro climate interaction with building energy consumption in New York City

    Language:Julia0100
  • dmoutinho/hello-node-microclimate

    A generated IBM Cloud application from Microclimate.

    Language:HTML20