Species observation data of eland (Taurotragus oyx) in Sneeuberg Nature Reserve, SA.Content:All_obs_long_latitude.csv = csv-file of all eland herd observation (longitude and latitue)Eland_projected_UTM.xls = All data/meta data collected during ground census, with projected coordinated (WGS_1984_UTM_ZONE_35s)MaxEnt input data.csv = eland observation data as was used to run MaxEnt (without duplicates)CPE_ELAND.kmz = Google Earth file of eland observations

As part of the mFUND project ADIS, test flights and trips with various UAVs were recorded. The data was collected using the ADIS downlink. These are provided as a KMZ file (or CSV). There are three test flights and two test drives. The drones used are described in the PDF ADIS-Copter, pictures of the RC buggy are in the PDF file ADIS-Rover. The drones were flown in the Hold Height mode, so their data only includes the height changes to the set height. ADIS1 was flown at an altitude of about 60 m.ADIS2 and ADIS3 at a height of approx. 40 m. The height of ADIS4 corresponds to the height above NN. The received data contains the following information: Name: Identification of the UV Lat = Latitude Long = longitude Speed = instantaneous speed [km/h] Alt = Altitude Height [m] Hdg = Magnetic heading (tax rate) RSSI = Received Signal Strength Indication [dBm] mFUND project: ADIS, FKZ: 19F2173A

Full-range (350 - 2500 nm) leaf and canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including species-level leaf reflectance, canopy-scale species endmember spectra, plot-scale spectra, and transect spectra as well as non-vegetated surface (NVS) spectra. The datasets were collected at the three core NGEE-Arctic watersheds, Kougarok, Teller, and Council within the larger Seward Peninsula, Alaska region. The data were collected in the months of July and August of 2017 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Leaf-level spectra were collected with the original SVC leaf clip/plant probe connected to the spectrometer through a 1.15 meter long fiber optic cable, while canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see associated dataset). This data package includes 26 files in a variety of formats including processed canopy and leaf spectra (.csv), processed dGPS locations (.csv and .kmz), digital photographs of spectral targets (.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA110_flmd.csv. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Learn the step-by-step process to start downloading the open data of the City of Mendoza. To access and download the open data of the City of Mendoza, you do not need to register or create a user account. Access to the repository is free, and all datasets can be downloaded free of charge and without restrictions. The homepage has access buttons to 14 data categories and a search engine where you can directly enter the topic you want to access. Each data category refers to a section of the platform where you will find the various datasets available, grouped by theme. As an example, if we enter the Security section, we find different datasets within. Once you enter the dataset, you will find a list of resources. Each of these resources is a file that contains the data. For example, the dataset Security Dependencies includes specific information about each of the dependencies and allows you to access the information published in different formats and download it. In this case, if you want to open the file with the Excel program, you must click on the download button of the second resource that specifies that the format is CSV. Likewise, in other sections, there are datasets with information in various formats, such as XLS and KMZ. Each of the datasets also contains a file with additional information where you can see the last update date, the update frequency, and which government area is generating this information, among other things. To access and download the open data of the City of Mendoza, you do not need to register or create a user account. Access to the repository is free, and all datasets can be downloaded free of charge and without restrictions. The homepage has access buttons to 14 data categories and a search engine where you can directly enter the topic you want to access. Each data category refers to a section of the platform where you will find the various datasets available, grouped by theme. As an example, if we enter the Security section, we find different datasets within. Once you enter the dataset, you will find a list of resources. Each of these resources is a file that contains the data. For example, the dataset Security Dependencies includes specific information about each of the dependencies and allows you to access the information published in different formats and download it. In this case, if you want to open the file with the Excel program, you must click on the download button of the second resource that specifies that the format is CSV. Likewise, in other sections, there are datasets with information in various formats, such as XLS and KMZ. Each of the datasets also contains a file with additional information where you can see the last update date, the update frequency, and which government area is generating this information, among other things. Translated from Spanish Original Text: Conocé el paso a paso para empezar a descargar los datos abiertos de la Ciudad de Mendoza. Para acceder y descargar los datos abiertos de la Ciudad de Mendoza, no necesitás realizar ningún tipo de registro ni crear un usuario. El acceso al repositorio es libre y todos los datasets se pueden descargar de manera gratuita y sin restricciones. La página de inicio cuenta con botones de acceso a 14 categorías de datos y un buscador en donde podés ingresar directamente al tema al que quieras acceder. Cada categoría de datos, refiere a una sección de la plataforma en donde vas a encontrar los distintos datasets disponibles agrupados por temática. A modo de ejemplo, si ingresamos en la sección Seguridad, dentro encontramos diferentes datasets. Una vez que ingresas al dataset, encontrarás una lista de recursos. Cada uno de estos recursos es un archivo que contiene los datos. Por ejemplo, el dataset Dependencias de Seguridad incluye información específica sobre cada una de las dependencias y te permite acceder a la información publicada en distintos formatos y descargarla. En este caso, si quieres abrir el archivo con el programa Excel deberás hacer clic sobre el botón descargar del segundo recurso que especifica que el formato es CSV. Así como también, en otras secciones hay datasets con la información en diversos formatos, como XLS y KMZ Cada uno de los datasets, contiene además una ficha con información adicional en donde podés ver la última fecha de actualización, la frecuencia de actualización y qué área de gobierno es la generadora de esta información, entre otros. Para acceder y descargar los datos abiertos de la Ciudad de Mendoza, no necesitás realizar ningún tipo de registro ni crear un usuario. El acceso al repositorio es libre y todos los datasets se pueden descargar de manera gratuita y sin restricciones. La página de inicio cuenta con botones de acceso a 14 categorías de datos y un buscador en donde podés ingresar directamente al tema al que quieras acceder. Cada categoría de datos, refiere a una sección de la plataforma en donde vas a encontrar los distintos datasets disponibles agrupados por temática. A modo de ejemplo, si ingresamos en la sección Seguridad, dentro encontramos diferentes datasets. Una vez que ingresas al dataset, encontrarás una lista de recursos. Cada uno de estos recursos es un archivo que contiene los datos. Por ejemplo, el dataset Dependencias de Seguridad incluye información específica sobre cada una de las dependencias y te permite acceder a la información publicada en distintos formatos y descargarla. En este caso, si quieres abrir el archivo con el programa Excel deberás hacer clic sobre el botón descargar del segundo recurso que especifica que el formato es CSV. Así como también, en otras secciones hay datasets con la información en diversos formatos, como XLS y KMZ Cada uno de los datasets, contiene además una ficha con información adicional en donde podés ver la última fecha de actualización, la frecuencia de actualización y qué área de gobierno es la generadora de esta información, entre otros.

The Highway Information Database of the Highway Bureau exports data of steep slopes on provincial highways, and in addition to CSV format, the Bureau also provides KMZ format for reference.

The data on provincial highway speed limit signs (Category 5 signs) is exported from the Highway Basic Data Database of the Highway Bureau. In addition to CSV format, the bureau also provides the facility information in KMZ format for reference.

The Broadcasting Services Act 1992 mandates that Commercial and Community broadcasting services are licensed to serve specific geographic areas. \r These geographic areas are referred to as Licence Areas, and are determined by the Australian Communications and Media Authority (ACMA) in Licence Area Plans (LAPs). \r The ACMA defines Licence Areas in terms of areas defined by the\r Australian Bureau of Statistics (ABS) for the\r purposes of the Australian Census. The smallest area unit currently defined\r by the ABS is the Collection District (CD).\r \r This dataset comprises the collection of current broadcast Licence Areas, and\r is made available in five forms:\r \r * the list of Australian Bureau of Statistics CD numbers making up the Licence Area definition, distributed in a comma separated value (CSV) format text file;\r * a translation of the ABS CD numbers into the names of the Local Government Areas (LGAs) and Statistical Division (SDs) within the area boundary, known as the Licence Area Description, rendered as an HTML page;\r * a geographic map displaying the Licence Area, distributed as a Portable Document Format (PDF) file;\r * a spatial dataset for use in GIS software, distributed as a ZIP archive containing ESRI Shapefile Format data files; and\r * a Google Earth Placemark (.KMZ) file viewable in the Google Earth application and other software that can display Placemark data.\r \r

This dataset contains:

A kmz file for Penmanshiel wind farm in the UK (for opening in e.g. Google Earth)

Static data including turbine coordinates and turbine details (rated power, rotor diameter, hub height, etc.)

10-minute SCADA and events data from the 14 Senvion MM82's at Penmanshiel wind farm, grouped by year from 2016 to mid-2021, which was extracted from our secondary SCADA system (Greenbyte). Note not all signals are available for the entire period, and there is no turbine WT03

Data mappings from primary SCADA to csv signal names

Site substation/PMU meter data where available for the same period

Site fiscal/grid meter data where available for the same period

The dataset has been released by Cubico Sustainable Investments Ltd under a CC-BY-4.0 open data license and is provided as is. However, please provide any feedback you might have on the dataset and format of the data. I'll try and add or link to additional file formats that might be easier to work with (e.g. for use with specific analysis software), and update this dataset periodically (e.g. twice a year), but please prompt me as required.

Feel free to use the data according to the license, however, it would be helpful to me if you could let me know where, how and why you are using the data, so that I can highlight this to the business (and renewables industry) and hopefully promote similar data sharing initiatives. I am particularly interested in performance analysis/improvement opportunities, how the dataset can be augmented with other (open) datasets, and sharing more generally within the renewables industry.

If you would like to get access to other datasets we may hold (e.g. more recent data, data from our other sites, ~30s resolution data, etc.), please let me know, and, if you have any questions or want to discuss open data and this or other initiatives, please contact me and I will endeavour to help.

I would like to thank Cubico's Senior Legal Advisor & Compliance Officer, IT Director, UK Asset Management Team, Executive Committee and my manager for supporting this initiative, as well as our partners GLIL for agreeing to release this data under an open license. I would also like to thank those I have talked to during the process of releasing this data under an open license and the encouragement and advice I have had on the way.

For contact my email address is charlie.plumley@cubicoinvest.com.

You can also access data from Kelmarsh wind farm here.

This preliminary landslide database lists 6502 features with assigned landslide and material type (surficial vs. rock). Where known, the date of occurrence, trigger, and reference are provided. The landslides have mostly been identified using Google Earth and publicly available lidar. Previously published landslide databases have also been incorporated and referenced. Landslide type attribution should be considered preliminary.

Version 6.1 includes the addition of 500 landslide features over version 6.0. This version also marks the addition of Pierre Friele as a co-author.

Data is provided as .csv file which can be imported in GIS software and as .kmz file for visualization in Goggle Earth.

Summary statistics are provided in a separate spreadsheet.

This preliminary landslide database lists 6002 features with assigned landslide and material type (surficial vs. rock). Where known, the date of occurrence, trigger, and reference are provided. The landslides have mostly been identified using Google Earth and publicly available lidar. Previously published landslide databases have also been incorporated and referenced. Landslide type attribution should be considered preliminary.

Version 6.0 includes the addition of approximately 1000 landslide features over version 5.0.

Data is provided as .csv file which can be imported in GIS software and as .kmz file for visualization in Goggle Earth.

Summary statistics are provided in a separate spreadsheet.

Skin temperature data over the East Antarctic pack ice zone were recorded by the RAPPLS airborne instrument package using a KT-19II infrared pyrometer. The KT-19II infrared pyrometer was manufactured by heitronics, and sees a spectrum of 8-12um. IR and location data were logged to a Windows PC using a serial port logger developed by AAD science technical support. Due to some logging issues, substantial post-processing work was done by the AAD sea ice science group to ensure that recorded temperatures were correctly geolocated. Skin temperature data were not collected on two flights: Alpha [12 September 2007] and Foxtrot [14 September 2007] On two further flights, data were collected but the raw log files were so badly munged that we could not confidently tie locations to temperatures. These were: Tango [30 September 2007] and Uniform [1 October 2007] The data are presented in .csv files for each flight showing time and date. lat, lon, recorded temp [deg K], temp converted to C. To visualise the data, .kmz files that can be viewed in Google Earth or NASA's worldwind virtual globes are provided, one for each flight. Skin temperature is represented by a coloured dot at each measurement point. Clicking on each poijt will show its location and recorded temperature. The description field of each .kmz file provides a colour scale.

Most lockers are part of the Bike Locker Users' Club (BLUC), but one or two locations are not BLUCs.

Data available in .csv, MapInfo .tab, Google .kmz, and ESRI .shp file formats.

Please acknowledge the source of this information using the following attribution statement:

Contains Transport for Greater Manchester data. Contains OS data © Crown copyright and database right 2017.

This preliminary landslide database includes 11,135-point features with assigned landslide type, material (surficial, rock, anthropogenic) type, point location type (headscarp vs. deposit), and qualitative location confidence (low, moderate, high). Where known, volume estimate, the date of occurrence, trigger, contributing factor, and reference are provided. The inventory contains both landslide events (discrete recorded period of movement) and landslide features (slope with morphology consistent with past or ongoing movement). No characterization of the current level of activity or hazard is provided.

The landslides have mostly been identified using Google Earth and publicly available lidar. Previously published landslide databases have also been incorporated and referenced. Landslide type attribution should be considered preliminary. Version 10.1 includes the addition of approximately 431 landslide features over version 10.0.

Point location and attribute data are provided as .csv file which can be imported in GIS software and as .kmz file for visualization in Google Earth. The .kmz file of version 10.1 also reverts to the landslide type symbology used in version 9.0.

Summary statistics are provided in a separate spreadsheet.

This dataset contains lines for all highways in the state of New Mexico. It is in a vector digital data structure digitized from a USGS 1:500,000 scale map of the state of New Mexico to which highways: Interstate, U.S., and State have been added. The source was ARC/INFO 5.0.1. and the conversion software was ARC/INFO 7.0.3. The size of the file is .36 Mb, compressed.