Mercurial > repos > ecology > srs_process_data
comparison comparison_div.xml @ 0:cf69ad260611 draft default tip
planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
author | ecology |
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date | Mon, 09 Jan 2023 13:36:02 +0000 |
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1 <tool id="srs_process_data" name="Compare diversity indicators" version="@VERSION@" profile="20.01"> | |
2 <description>with remote sensing data</description> | |
3 <macros> | |
4 <import>macro.xml</import> | |
5 </macros> | |
6 <expand macro="SRS_requirements"/> | |
7 <command detect_errors="exit_code"><![CDATA[ | |
8 #import re | |
9 #if $method.type == 'envi_bil': | |
10 #set input_raster = $method.input_raster | |
11 #set input_raster_identifier = re.sub('[^\s\w\-]', '_', str($input_raster.element_identifier)) | |
12 #set input_header = $method.input_header | |
13 #set input_header_identifier = re.sub('[^\s\w\-]+[^.hdr]', '_', str($input_header.element_identifier)) | |
14 cp '${input_raster}' '${input_raster_identifier}' && | |
15 cp '${input_header}' '${input_header_identifier}' && | |
16 #end if | |
17 Rscript | |
18 '$__tool_directory__/comparison_div.r' | |
19 #if $method.type == 'envi_bil': | |
20 '$input_raster_identifier' | |
21 '$input_header_identifier' | |
22 '' | |
23 #else: | |
24 '' | |
25 '' | |
26 '$method.input' | |
27 #end if | |
28 '$input_plot' | |
29 '$choice' | |
30 '$__tool_directory__/functions.r' | |
31 '$typepca' | |
32 '$output_div' | |
33 '$output_beta' | |
34 '$plots' | |
35 ]]> | |
36 </command> | |
37 <inputs> | |
38 <conditional name="method"> | |
39 <param name="type" type="select" label="In which format are your data ?"> | |
40 <option value="zipper">The data you are using are in a zip folder Reflectance</option> | |
41 <option value="envi_bil">Your already have the files in ENVI BIL format</option> | |
42 </param> | |
43 <when value="zipper"> | |
44 <param name="input" type="data" format="zip" multiple="true" label="Input data"/> | |
45 </when> | |
46 <when value="envi_bil"> | |
47 <param name="input_raster" type="data" format="bil" label="Input raster" help="It can be the raw data in bil or the PCA raster layer in bil"/> | |
48 <param name="input_header" type="data" format="hdr" label="Input header"/> | |
49 </when> | |
50 </conditional> | |
51 <param name="input_plot" type="data" format="data" label="Plots folder zip"/> | |
52 <param name="choice" type="select" label="Do you want to compute beta diversity (needs mutliple locations) ?" display="radio"> | |
53 <option value="Y">Yes</option> | |
54 <option value="N">No</option> | |
55 </param> | |
56 <param name="typepca" type="select" label="Do you want to do a PCA or a SPCA ?" display="radio" help="If you choose PCA there is no rescaling of the data as oppposed as if you choose SPCA"> | |
57 <option value="SPCA">SPCA</option> | |
58 <option value="PCA">PCA</option> | |
59 </param> | |
60 </inputs> | |
61 <outputs> | |
62 <data name="output_div" from_work_dir="Diversity.tabular" format="tabular" label="Global diversity"> | |
63 </data> | |
64 <data name="output_beta" from_work_dir="BrayCurtis.tabular" format="tabular" label="Bray Curtis"> | |
65 <filter>choice == 'Y'</filter> | |
66 </data> | |
67 <collection type="list" name="plots" label="Comparison plot"> | |
68 <discover_datasets pattern="(?P<designation>.+)\.png" visible="false" format="png"/> | |
69 <filter>choice =='Y'</filter> | |
70 </collection> | |
71 </outputs> | |
72 <tests> | |
73 <test> | |
74 <param name="type" value="envi_bil"/> | |
75 <param name="input_raster" value="S2A_Subset"/> | |
76 <param name="input_header" value="S2A_Subset.hdr"/> | |
77 <param name="input_plot" value="S2A_T33NUD_Plots.zip"/> | |
78 <param name="choice" value="Y"/> | |
79 <output name="output_div"> | |
80 <assert_contents> | |
81 <has_n_lines n="25"/> | |
82 </assert_contents> | |
83 </output> | |
84 <output name="output_beta"> | |
85 <assert_contents> | |
86 <has_n_lines n="25"/> | |
87 </assert_contents> | |
88 </output> | |
89 <output_collection name="plots" type="list" count="1"/> | |
90 </test> | |
91 </tests> | |
92 <help><![CDATA[ | |
93 ======================================================================== | |
94 Process satellite remote sensing data to produce biodiversity indicators | |
95 ======================================================================== | |
96 | |
97 | |
98 **What it does** | |
99 | |
100 Féret and Asner (2014) developed a method for **tropical forest** diversity mapping based on very high spatial resolution airborne imaging spectroscopy. | |
101 | |
102 The goal of this tool using the package biodivMapR is to compute diversity indices over each spatial polygon of a shapefile of plots, if available, in order to compare field inventories with diversity indices estimated from remotely-sensed images. | |
103 | |
104 **Input description** | |
105 | |
106 It expects an image file as input, with a specific data format. ENVI HDR image with BIL interleave required. | |
107 The image is an ENVI raster including : | |
108 | |
109 - A binary file (which has no extension here). | |
110 | |
111 - A header file (with .hdr extension). | |
112 | |
113 The header file is a text file including all necessary metadata which can be read with a text editor. It includes image dimensions, projection, and the name and central wavelength for each spectral band. | |
114 | |
115 In order to get such input we advise to use the tool preprocessing sentinel 2 data. | |
116 | |
117 +--------------+----------+--------------+ | |
118 | BIL | ENVI HDR | Shapefiles | | |
119 +==============+==========+==============+ | |
120 | raster stack | Metadata | plots.zip | | |
121 +--------------+----------+--------------+ | |
122 | ... | ... | ... | | |
123 +--------------+----------+--------------+ | |
124 | |
125 **Output** | |
126 | |
127 - Two tabulars : | |
128 - One matrix for Bray-Curtis indicator | |
129 - One table for the following indicators; Species richness, shannon, fisher, simpson, richness, eveness, divergence | |
130 | |
131 - One comparison png plot in the Pcoa space that summarizes α- and β-diversity in scatterplots and illustrates that the combination of the three components computed with PCoA allows proper differentiation among vegetation types: | |
132 - PCoA#1 allows differentiating medium and high diversity forests from low diversity forest and low vegetation, but does not discriminate medium and high diversity forests. | |
133 - PCoA#2 allows differentiating low diversity forest from medium/high diversity forests and low vegetation | |
134 - PCoA#3 allows differentiating medium diversity forests from high diversity forests and low vegetation. | |
135 | |
136 ]]> </help> | |
137 <expand macro="SRS_BDMRref"/> | |
138 </tool> |