Published February 28, 2020 | Version v1
Dataset Open

Raster files catalog to forest growth simulation performed by r.recovery module (Grass Gis).

Description

This repository contains all publicly available raster files to calibrate/validate the  parameters of the Diffusive-logistic growth (DLG) model and generate prognostics by means of the GRASS-GIS module r.recovery (Richit et al., 2019).

Three .tiff files are needed for perform calibration/validation: two are EVI raster maps (two time-lapsed conditions of forest density) and a soil use file. In the repository the example files are:

Calibration_EVI_2000;

Calibration_EVI_2011 and

Calibration_soil_use_2000, respectively.

The others files in the repository are four EVI .tiff files and their respectively soil use .tiff files that were used to perform simulations by the means of calibrated parameters of the  DGL model. The files are:

AMNP_EVI_2016 and AMNP_soil_use_2016;

FPSP_EVI_2016 and FPSP_soil_use_2016;

MDRB_EVI_2016 and MDRB_soil_use_2016;

MNPTS_EVI_2016 and MNPTS_soil_use_2016.

For more details on r.recovery module please check  

Richit, L.A., Bonatto, C., da Silva, R.V., Grzybowski, J.M.V., 2019. Prognostics of forest recovery with r.recovery grass-gis module: an open source forest growth simulation model based on the diffusive-logistic equation. Environmental modelling & software 111, 108–120.

Files

AMNP_EVI_2016.tiff

Files (2.0 MB)

Name Size Download all
md5:6740e8b84cbd2729d58b356d80779247
29.4 kB Preview Download
md5:6f9a75d730c84a393b2f8069780ea876
6.7 kB Preview Download
md5:ba4aa40ff02e1057f3496ee09c90891a
7.4 kB Preview Download
md5:a1d6dbe9659bc7c6844f608fc74a2ea3
7.4 kB Preview Download
md5:8abe964451136ece88e45f1118eadc54
29.8 kB Preview Download
md5:e19a3c132790e5e84f6f898787cb8f88
768.4 kB Preview Download
md5:b0d835d83b8eab05449244612c26fd70
191.4 kB Preview Download
md5:ce6786145be3bbf87473e9d06ce3d77c
462.0 kB Preview Download
md5:39606de59f4e3a7f8020742124b38ab0
110.7 kB Preview Download
md5:f30b2cdada2b716141e3371540888c6e
282.4 kB Preview Download
md5:7e6d1c77169e6c5b21f328c421ab5111
69.9 kB Preview Download