Funzione Analisi LandTrendr

Disponibile con ArcGIS Image for ArcGIS Online.

Valuta le variazioni dei valori dei pixel nel corso del tempo utilizzando il metodo di rilevamento delle tendenze di disturbo e di recupero basato su Landsat (LandTrendr) e genera un raster di analisi delle variazioni contenente i risultati del modello.

Per informazioni sull'algoritmo LandTrendr, vedi Funzionamento di Analizza modifiche con LandTrendr.

Nota:

Questa funzione raster è supportata solo insieme alla funzione Rileva modifica tramite analisi delle modifiche. Usa il layer di output della funzione Analisi LandTendr come input della funzione Rileva modifica tramite analisi delle modifiche. Per produrre un output di dataset raster, collega la funzione Analisi LandTendr con la funzione Rileva modifica tramite analisi delle modifiche utilizzando Editor funzioni, salva come modello di funzione raster e utilizzalo come input per lo strumento di geoprocessing Genera raster da funzione raster.

Note

Questa funzione raster può essere utilizzata solo come input della funzione raster Rileva modifica tramite analisi delle modifiche. Per generare un output raster, collega la funzione Analisi LandTrendr alla funzione Rileva modifica tramite analisi delle modifiche in un modello di funzione raster e usa tale modello come input nello strumento di geoprocessing Genera raster da funzione raster. Il risultato è un raster contenente informazioni relative al tempo in cui sono cambiati i valori di pixel.

Lo strumento estrae i cambiamenti in una feature osservata, quindi l'immagine multidimensionale di input ideale dovrebbe catturare un'osservazione coerente nel tempo e non dovrebbe includere interferenze atmosferiche o dei sensori, nuvole o ombre di nuvole. La migliore pratica consiste nell'utilizzare dati che sono stati normalizzati e che possono essere mascherati utilizzando una banda QA, ad esempio i prodotti Landsat Collection 1 Surface Reflectance con una maschera per le nuvole.

The tool performs analysis on one image per year, and the number of yearly slices must be equal to or greater than the value specified in the Minimum Number of Observations parameter. It is recommended that you have at least six years of data.

If you have monthly, weekly, or daily data, it is recommended that you select several images from each year (preferably from the same season), remove clouds and cloud shadow, and combine the images to generate a single image that captures the observation well. If monthly, weekly, or daily data is provided as the input multidimensional raster, the tool will identify one slice for analysis based on the date closest to that provided in the Snapping Date parameter.

A feature in a landscape will often take time to recover from a nonpermanent change such as a forest fire or insect infestation. To control the rate of recovery recognized by the model, set the Recovery Threshold parameter. A distinct segment cannot have a recovery rate that is faster than 1/recovery threshold.

The recovery from a change in landscape can occur in the positive or negative direction. For example, when a landscape experiences forest loss, a time series of vegetation index values shows a drop in index values, and the recovery shows a gradual increase in vegetation index values, or a positive recovery trend. Specify the direction of recovery trend with the Recovery Has Increasing Trend parameter.

Parametri

Parametro	Descrizione
Raster	Il layer raster multidimensionale Landsat.
Nome banda di elaborazione	The image band name to use for segmenting the pixel value trajectories over time. Choose the band name that will best capture the changes in the feature you want to observe.
Data gestione delle tolleranze	The date used to identify a slice for each year in the input multidimensional dataset. The slice with the date closest to the snapping date will be used. This parameter is required if the input dataset contains sub-yearly data.
Numero massimo di segmenti	The maximum number of segments to be fitted to the time series for each pixel. The default is 5.
Oltrepasso conteggio vertici	The number of additional vertices beyond max_num_segments + 1 that can be used to fit the model during the initial stage of identifying vertices. Later in the modeling process, the number of additional vertices will be reduced to max_num_segments + 1. The default is 2.
Soglia di spike	The threshold to use for dampening spikes or anomalies in the pixel value trajectory. The value must range between 0 and 1 in which 1 means no dampening. The default is 0.9.
Soglia di recupero	The recovery threshold value in years. If a segment has a recovery rate that is faster than 1/recovery threshold, the segment is discarded and not included in the time series model. The value must range between 0 and 1. The default is 0.25.
Numero minimo di osservazioni	The minimum number of valid observations required to perform fitting. The number of years in the input multidimensional dataset must be equal to or greater than this value. The default is 6.
Soglia di valore P	The p-value threshold for a model to be selected. After the vertices are detected in the initial stage of the model fitting, the tool will fit each segment and calculate the p-value to determine the significance of the model. On the next iteration, the model will decrease the number of segments by one and recalculate the p-value. This will continue and, if the p-value is smaller than the value specified in this parameter, the model will be selected and the tool will stop searching for a better model. If no such model is selected, the tool will select a model with a p-value smaller than the lowest p-value × best model proportion value. The default is 0.01.
Migliore proporzione del modello	The best model proportion value. During the model selection process, the tool will calculate the p-value for each model and identify a model that has the most vertices while maintaining the smallest (most significant) p-value based on this proportion value. A value of 1 means the model has the lowest p-value but may not have a high number of vertices. The default is 1.25.
Previeni recupero di un anno	Specifies whether segments that exhibit a one year recovery will be excluded. Checked—Segments that exhibit a one year recovery will be excluded. This is the default. Unchecked—Segments that exhibit a one year recovery will be not be excluded.
Il recupero ha tendenza in aumento	Specifies whether the recovery has an increasing (positive) trend. Checked—The recovery has an increasing trend. This is the default. Unchecked—The recovery has a decreasing trend.
Emetti altre bande	Specifies whether other bands will be included in the results. Checked—Other bands will be included in the results. The segmentation and vertices information from the initial segmentation band specified in the Processing Band parameter will also be fitted to the remaining bands in the multiband images. The model results will include the segmentation band first, then the remaining bands. Unchecked—Other bands will not be included in the results. This is the default.