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Showing results for: [ Climate Change ]
Processed global climate model outputs and derived analysis from ‘historical’ and RCP simulations from CMIP5 models. A set of up to 26 models were used for all PACCSAP reporting, but some other models... more are now processed as well as part of the NRM and ACCSP projects. Datasets are complete time series as well averages for 1986-2005, 2020-2039, 2040-2059, 2060-2079 and 2080-2099. Derived variables are: • Climatologies for each period • Changes between periods (absolute and %) • Expert Team on Climate Change Detection and Indices (ETCCDI) extremes indices (e.g. annual maximums) • Average recurrence interval (ARI) calculations of 1-year, 2-year, 5-year, 10-year, 20-year, 50-year and 100-year events fro rainfall and temperature extremes • Standardised precipitation index (SPI) of meteorological drought • Area-average means and changes for each partner nation and each NRM cluster region for all fieldsless
CLSD PCCSAP 3.3.1 CMIP5 Model Evaluation - Climate model evaluation - Published 14 Jun 2019
0.5m Contours maps as shape files 4903 tiled files (1km x1km) with DBF, PRJ and SHX support files
1177.2 Northern NERP - Remote Sensing - ALOS vegetation maps and LIDAR data - Published 02 Dec 2014
Model key points are statistically thinned data points that represent the main changes in a sampled surface. The Key Points are classified with code 8 in the LiDAR point classification scheme. Advanta... moreges in their use are significant reductions in data volume and reductions in data noise. There are disadvantages in using this data as has been a loss small features which may be potentially significant for certain applications. eg hydrology less
Intensity Mosaic in ECW format with .ecw.aux.xml, ERS, eww, prj and tab support files Intensity image as 4943 tiled files (1km x1km) in TIF format with PRJ & TFW support files
Digital Surface Model (DSM) 1metre ESRI Grid Float format as 4942 tiles. There is no common usage of the terms digital elevation model (DEM), digital terrain model (DTM) and digital surface model (D... moreSM) in scientific literature. In most cases the term digital surface model represents the earth's surface and includes all objects on it. In contrast to a DSM, the digital terrain model (DTM) represents the bare ground surface without any objects like plants and buildings. Digital Elevation Model (DEM) and Digital Terrain Model (DTM) appear to be used interchangeably. less
Digital Elevation Model (DEM) 1metre ESRI Grid Float format as 4942 tiles
LiDAR_Point_Clouds, Classified. AHD have been preocessed to conform to the Australian Height Datum and converted from files collected as swaths in to tiles of data. The file formats is LAS. LAS is ... morean industry format created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water less
1177.2 Northern NERP - Remote Sensing - ALOS vegetation maps and LIDAR data - Published 27 Nov 2014
Canopy Height Model (CHM) 2 metre ESRI Grid Float format as 4944 tiles
1177.2 Northern NERP - Remote Sensing - ALOS vegetation maps and LIDAR data - Published 17 Sep 2014
Forest Canopy Model (FCM) 10metre ESRI Grid Float format as 4944 tiles
LiDAR_Point_Clouds, Classified. ELL have been preocessed to from swaths in to tiles of data. Points are located by Elevation, Latitude and Longitude. The file formats is LAS. LAS is an industry form... moreat created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water less
LiDAR_Point_Clouds, UNClassified. ELL Files swaths of flight collected data. Points are located by Elevation, Latitude and Longitude. The file formats is LAS. LAS is an industry format created and m... moreaintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water less
