SILO is a Queensland Government database containing continuous daily climate data for Australia from 1889 to present, in a number of ready-to-use formats, suitable for modelling and research applications. The SILO database contains two major classes of data: point (station) time series and spatial grids, both based on observed data from the Bureau of Meteorology ADAM (Australian Data Archive for Meteorology) database. For point data, interpolated or derived values are used where observations are missing. Gridded data are spatially interpolated from observations.

SILO (Scientific Information for Land Owners) is a database of Australian climate data from 1889 (current to yesterday). It provides daily datasets for a range of climate variables in ready-to-use formats suitable for research and climate applications. SILO products provide national coverage with interpolated infills for missing data, which allows you to focus on your research or model development without the burden of data preparation. \r The SILO climate API (Application Programming Interface) allows you to query point datasets, as well as a range of metadata, in real time. \r Note: An API key is required to use this API. Please visit the SILO website to obtain your API key.

The Patched Point Dataset (PPD) combines observations and interpolations to provide daily data for a selected set of stations (locations). The term 'patched' means that if on any day a station does not have an observation then the gap in the record is 'patched' (ie. filled) with an estimate obtained by spatial interpolation of the daily data from surrounding stations. Consequently the Patched Point Data for a given location always contain a complete data record, or in other words, there are no missing data.

SILO (Scientific Information for Land Owners) is a daily time series of meteorological data at point locations, consisting of station records which have been supplemented by interpolated estimates where observed data are missing.
Patched Point Datasets for Queensland are available free of charge. To qualify for free access, the user must first register with SILO. For further information about SILO and registration, see the SILO webpage.

The solar radiation data provided by SILO are an estimate of the total incoming solar energy incident upon the Earth's surface at a given location. The estimate includes contributions from both the direct and diffuse components of solar exposure. It can be calculated from data measured directly by radiometers and indirectly from observational estimates of cloudiness and hours of sunshine duration.

The maximum and minimum temperatures are the highest and lowest temperatures (respectively) which occurred throughout the 24 hour period up to 9am. The observed minimum daily temperature is assigned to the date the observation was made, as the diurnal cycle typically reaches its minimum at approximately 5am. The observed maximum daily temperature is assigned to the day prior to the date the observation was made, as the diurnal cycle typically reaches its maximum at approximately 3pm. If the data are not recorded daily (for example, the instrument malfunctioned), the first observation following the no-report period is flagged as an accumulation.

Daily rainfall is the total rainfall accumulated over the 24 hour period up until 9am on the day of observation. Monthly rainfall is the total rainfall accumulated over all days in the given month.

Silo

## Overview

Silo is a dataset for object detection tasks - it contains Silp annotations for 1,885 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Evaporation is measured using a Class A evaporation pan which indicates the amount of water evaporating from bare ground or open water.

SILO (Scientific Information for Land Owners) is a database of Australian climate data from 1889 (current to yesterday). It provides daily datasets for a range of climate variables in ready-to-use formats suitable for research and climate applications. SILO products provide national coverage with interpolated infills for missing data, which allows you to focus on your research or model development without the burden of data preparation.

SILO is hosted by the Science and Technology Division of the Queensland Government's Department of Environment and Science (DES). The datasets are constructed from observational data obtained from the Australian Bureau of Meteorology.

In the context of meteorological data, vapour pressure is the partial pressure of water vapour in the atmosphere. It is calculated by the Bureau of Meteorology from the dew point temperature recorded at 9am.

Storage Tank or Silo Areas

Storage tank and silo areas categorization and details, sourced from USACE IENC

By Homeland Infrastructure Foundation [source]

About this dataset

To summarize the importance of this dataset: it serves as a reliable resource for exploring different types of storage tanks or silos present within specific areas. It enables users to identify specific products stored within these structures and access any additional available data sources related to them. By providing details about scale visibility on maps at varying zoom levels ensures proper contextual representation when displaying these features.

How to use the dataset

1. Get Familiar with the Columns

Take a moment to understand the different columns present in the dataset:

• Category_o: The category of the storage tank or silo area.
• Product: The type of product stored in the storage tank or silo area.
• Object_Nam: The name of the storage tank or silo area.
• Informatio: Additional information about the storage tank or silo area.
• Scale_Mini: The minimum scale at which the storage tank or silo area is visible.
• Source_Ind: The source indicator of the storage tank or silo area.
• Source_D_1: Additional source information about the storage tank or silo area.
• Shape_Leng: The length of the shape of the storage tank or silo area.
• Shape_Area: The area of the shape of

Research Ideas

• Environmental risk assessment: By analyzing the type of product stored in each storage tank or silo area, this dataset can be used to assess potential environmental risks in case of accidents or leaks. It can aid in identifying high-risk areas that require additional monitoring and mitigation measures.

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Storage_Tank_or_Silo_Areas_USACE_IENC.csv | Column name | Description | |:---------------|:--------------------------------------------------------------------------------------------| | Category_o | The category of each storage tank or silo area. (Categorical) | | Product | The type of product stored in each facility. (Categorical) | | Object_Nam | The name assigned to each storage tank or silo area. (Text) | | Informatio | Additional information about each facility. (Text) | | Scale_Mini | The minimum scale at which each facility becomes visible on a map display. (Numeric) | | Source_Dat | The date of the source data used for each facility. (Date) | | Source_Ind | The indicator of the source materials used for each facility. (Text) | | Source_D_1 | Additional information or references to the source materials used for each facility. (Text) | | Shape_Leng | The length and shape of each storage tank or silo area. (Numeric) | | Shape_Area | The surface area of each storage tank or silo area. (Numeric) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Homeland Infrastructure Foundation.

Observed air pressure is the atmospheric air pressure at the location of the recording station. The spatial variation in observed pressure can be reduced if the topographic component is removed. The observed 9am station level pressure is converted into mean sea level pressure to support biophysical modeling, using the expression given in Jeffrey et al (2001).

Overview

This dataset provides spatially and temporally complete daily climate time series for point locations across Australia. It is sourced from SILO (Scientific Information for Land Owners), a database managed by the Queensland Government. The data are constructed from official Bureau of Meteorology (BoM) observations and use sophisticated interpolation and infilling techniques to create continuous, model-ready datasets for research and applications in agriculture, hydrology, ecology, and environmental modelling.

Key Features

• Spatial Coverage: Continental Australia.
• Data Completeness: Gaps in the original observational records have been infilled using interpolation methods, resulting in continuous time series.
• Variables: Includes rainfall, maximum and minimum temperature, solar radiation, vapour pressure, and derived evaporation/evapotranspiration metrics (e.g., Class A pan evaporation, FAO56 reference evapotranspiration).
• Provenance Tracking: Each datum includes a code indicating its source (e.g., direct observation, interpolated, synthetic).

Data Structure

• Location Identifiers: Station ID, Latitude, Longitude, Elevation.
• Temporal Identifier: Date (YYYY-MM-DD).
• Climate Variables: Columns for each daily climate measurement.
• Data Code: A crucial integer column (e.g., source_code) that explains how each value was derived (see table below).

Data Codes (Source of Each Value)

Understanding the source_code is essential for assessing data quality and suitability for your analysis.

Important Notes & Limitations

• Interpolated Data is not purely observational data. It is a reconstructed product designed for continuity. Spatial and temporal accuracy varies.
• Accuracy depends on the climate variable and the density of the station network at the time.
• Temperature generally reliable over distance.
• Rainfall, highly variable ("patchy"); interpolation has higher uncertainty.

Not for Climate Trend Detection SILO explicitly advises against using this dataset for detecting climate change signals. Use the Bureau of Meteorology's ACORN-SAT or High-Quality datasets for that purpose.

Suspect Values Removed The interpolation process identifies and removes suspect raw values. Therefore, point data at station locations may differ slightly from the interpolated grid.

CLIMARC Interpolation (Code 35) Represents a significant improvement over long-term averages but should be used with caution, understanding its limitations in early years and sparse regions.

Intended Use

Ideal for: - Biophysical modelling (e.g., crop, hydrological, or ecosystem models). - Agricultural planning and drought assessment. - Research requiring long, continuous daily time series. - Historical climate analysis at specific points (with caveats).

About this dataset

Context

The dataset tabulates the Silo Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Silo, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Silo.

Key observations

Among the Hispanic population in Silo, regardless of the race, the largest group is of Mexican origin, with a population of 12 (100% of the total Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Silo
• Population: The population of the specific origin for Hispanic or Latino population in the Silo is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Silo total Hispanic or Latino population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Silo Population by Race & Ethnicity. You can refer the same here

Synthetic evaporation data are used to supplement observed Class A pan evaporation data. Synthetic data are required owing to the limited availability of observed data, particularly in the years prior to 1970. Multiple regression was used to construct a model for estimating evaporation from a linear combination of solar radiation and vapour pressure deficit. The model was fitted using observational records from 1975-2003 which had been analysed to eliminate suspect data.

The size of the Silo Installation market was valued at USD 1319 million in 2024 and is projected to reach USD 1957.24 million by 2033, with an expected CAGR of 5.8 % during the forecast period.

Train Silo

## Overview

Train Silo is a dataset for object detection tasks - it contains Ball Silo annotations for 600 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset provides information about the number of properties, residents, and average property values for Silo Road cross streets in Dover, NC.

The Global Silo Bags Market Report is Segmented by Material Type (Polyethylene (PE), Polypropylene (PP)), Application (Grains and Oilseeds Storage, Dried Fruits Storage, Forage Storage, Fertilizer Storage), and Geography (North America, Europe, Asia-Pacific, South America, and Middle East & Africa). The Report Offers Market Sizing and Forecasts in Value (USD).