In lbusett/phenoriceR: Routines for analysis of PhenoRice outputs

knitr::opts_chunk$set(echo = TRUE)
library(sprawl)
library(ggspatial)
library(ggplot2)

Introduction

This document briefly illustrate the results of exploratory analysis conducted using the PhnoRice algorithm to map rice area and estimate some agro-practices indicator (number of rie seasons, Sowing and harvesting dates), starting from time series of MODIS 250m images

Methods

The PhenoRice algorithm was applied to the

1. What is "Maturity" ?

Maturity is the length of season. Not clear however what MATURITYS and MATURITYE are. Bhogendra will check.

1. What is "seed_age" ?

Understood. Information is probably not relevant for our purposes

1. Where are the areas reported ?

Areas are on the right-most columns of RiceProduction.

Processing needed

To facilitate processing and comparison with PhenoRice results, it would be good if the dataset could be reshaped as follows:

1. Remove all areas outside of the current PhenoRice analysis

2. Reshape the DB in a more "processing-friendly" format. I am thinking of something like this:

3. "Location" columns to be kept as is: OBJECTID, ISO, COUNTRY, REGION, SUB_REGION

4. "Location" columns to be added (if/where possible): ISO_SUB, corresponding to the ISO code of the SUB_REGION

5. Reshape the "data" columns to long format. What I'm thinking of is something on these lines:

   | OBJECTID | ISO | ... | nseas |season | seas_cat |pheno_var | start | peak | end | ricearea | totarea | rice_fc |riceprod | | :------: |:----:| :---:| :---: |:-------------:| :---------:|:--------:|:-------:|:-------:|:---:|:-------: |:-------:|:------:|:------: | 1 | VNM | ... | 2 | Winter-spring | first | sow | 10 | 20 | 30 | 2500 | 5000 | 0.5 | 2.1 | | 1 | VNM | ... | 2 | Summer | second | sow | 100 | 110 | 120 | 1000 | 5000 | 0.5 | 1.1 | | 1 | VNM | ... | 2 | NA | third | sow | NA | NA | NA | NA | 5000 | 0.5 | NA | | 1 | VNM | ... | 2 | Winter-spring | first | harv | 100 | 110 | 120 | 2500 | 5000 | 0.5 | 2.1 | | 1 | VNM | ... | 2 | Summer | second | harv | 190 | 200 | 210 | 1000 | 5000 | 0.5 | 1.1 | | 1 | VNM | ... | 2 | NA | third | harv | NA | NA | NA | NA | 5000 | 0.5 | NA | | 1 | VNM | ... | 2 | Winter-spring | first | mat | 60 | 70 | 80 | 2500 | 5000 | 0.5 | 2.1 | | 1 | VNM | ... | 2 | Summer | second | mat | 150 | 160 | 170 | 1000 | 5000 | 0.5 | 1.1 | | 1 | VNM | ... | 2 | NA | third | mat | NA | NA | NA | NA | 5000 | 0.5 | NA | | 2 | VNM | ... | 3 | Winter-spring | first | sow | 15 | 25 | 35 | 2500 | 5000 | 0.5 | 3 | | 2 | VNM | ... | 3 | Summer | second | sow | 105 | 115 | 125 | 1000 | 5000 | 0.5 | 2 | | 2 | VNM | ... | 3 | Off | third | sow | 200 | 205 | 210 | 500 | 5000 | 0.5 | 1 |

6. This could be done either manually or in R by importing the dataset to a sf object and then using either functionalities from reshape2::melt or tidyr::gather. I'd suggest the second solution, which is less error-prone and recyclable/reproducible (and can be modified if we decide that we need something more/less/different. The function could be added to PhenoriceR package.

7. For Bhogendra: Is it possible for you to work onthis re-sahping ?

lbusett/phenoriceR documentation built on May 18, 2019, 9:17 p.m.