The classification model is created for two classes only. The following principles are currently implemented by GLAD Tools:Ī. The decision tree is a type of supervised classification which requires a set of training data for parameterization of the model. The GLAD Tools provide software for the application of a simple but powerful decision tree model for land cover mapping and change detection. Land Cover and Land Cover Change Classification Using Image Mosaics provides tools for stitching tiled data into multi-band image mosaics. Change Detection Metrics.Īfter creating a set of metrics, the data from different tiles must be mosaicked for visualization. Please, read the metrics methodology and select the metric types that better suit your needs here: 3.4. Several types of change detection metrics are designed for different applications. ![]() To generate this metric type, at least two complete years of 16-day data is required. The annual change detection metrics were designed to highlight inter-annual changes of spectral reflectance and are used as source data for change mapping. Please, read the metrics methodology and select the metric types that better suit your needs here: 3.3. The GLAD system is designed to provide different sets of phenological metrics for various applications. Several years of data are preferable to implement gap-filling. Phenological metrics may be calculated using a complete or incomplete set of 16-day ARD for at least one year. The annual land cover mapping is based on annual gap-filled phenological metrics which simplify the analysis of surface reflectance and land surface phenology. Two independent types of metrics may be created from 16-day time-series data using GLAD Tools: annual phenological metrics and annual change detection metrics. Metrics represent a set of statistics extracted from the normalized surface reflectance time-series within a calendar year. The ARD product is used to create multi-temporal metrics that serve as a consistent input for annual land cover mapping and change detection models. Additional GLAD tools may be added from the 3.2. The installation instructions are provided in the 3.1. To use the ARD tools, you need to install ActivePerl ( ), OSGeo4W (usually installed as QGIS-OSGeo4W package from here ) and the GLAD_1.0 package ( ). ![]() In this section, we provide tools for application of the ARD time-series for land cover and land cover change mapping and analysis of classification results. The ARD product does not represent actual surface reflectance and is not suitable for precise measurement of photosynthesis, water quality, and other variables that require actual surface reflectance. To facilitate classification model extrapolation, we have implemented globally consistent reflectance normalization. The primary purpose of the GLAD ARD is to simplify time-series analysis and to create multi-temporal metrics for land cover and land cover change mapping. ![]() GLAD Tools for Landsat ARD Applications GLAD Tools
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