Executive Summary

This deliverable is the second version of the Data Management Plan (DMP) and
describes the updated DMP for the CANDELA project. The goal of this document
is to provide an overview of all datasets used by the project.

The first DMP version D5.4 [15]) follows the guidelines of the template
provided by the European Commission (Template Horizon 2020 Data Management
Plan [1] [2]). The Data Management task (T5.3) is included within the Project
Management and Coordination work package (WP5).

The second DMP has been updated including a new sub-section in chapter “2.1
FAIR data” in order to clarify the current project status concerning to the
needs for cataloguing on the data produced by CANDELA processing services.

In addition, the CANDELA project datasets (section 3) have also been updated
including detailed information for each of the project use cases. Following
the structure of DMP v1, this document includes dataset information for the
project subcases (see deliverables [3][13] and [4][14], Urbanization,
Vineyard, Forest Disaster and Forest Health). The information for each project
dataset has been provided with the same structure:

  * Dataset reference 

  

  * Dataset Description 

  

  * Standards and metadata 

  

  * Data Sharing 

  

  * Archiving and preservation 

  

Section 4 has also been updated including details of the Additional datasets
used by CANDELA following the Data Warehouse mechanism (DWH)[5].

Finally, the conclusions have also been updated including related information
about the use of data in the context of the aforementioned project use cases.

#  1 Introduction

##  1.1 Purpose of the document

The purpose of the DMP is to provide an analysis of the main elements of the
data management policy that will be used by the project [6]. Following the DMP
template, this document provides for each dataset:

  * Identifier and description 

  

  * Reference to existing suitable standards 

  

  * Description about data sharing and preservation 

  

During the project lifetime, the document needs to be updated, so it has been
planned the release of three versions of the CANDELA DMP.

  * D5.4 DMP v1: the first version of the document based on the DMP template provided by the European Commission [1][2]. 

  

  * D5.5 DMP v2: the DMP will evolve and will be updated in October 2019 (M18). 

  

  * D5.6 DMP v3: the final version of the document is planned in October 2020 (M30) 

  

##  1.2 Relation to other project work

CANDELA project has planned reports about the request of Additional Datasets
thorough the Data Warehouse mechanism managed by ESA. The different versions
of the DMP will include the reference to these reports.

##  1.3 Structure of the document

This document is structured in four major chapters described below:

  * **Chapter 2** presents the Data Management Plan (FAIR data principle) 

  

  * **Chapter 3** presents the CANDELA project Datasets 

  

  * **Chapter 4** presents Additional Datasets 

  

  * **Chapter 5** presents the conclusions 

  

#  2 Data management Plan

This section has been configured following the DMP template [1][2] in order to
achieve the FAIR principle for the project datasets.

##  2.1 FAIR data

According to the DMP template, the CANDELA research data should be “FAIR”:
Findable, Accessible, Interoperable and Re-usable. This section describes the
procedures to follow the FAIR principle.

###  2.1.1 Making data findable, including provisions for metadata

The CANDELA platform is built upon the CreoDIAS basis platform. Most of the
dataset used in the context of CANDELA are or will be directly retrieved
through API provided by CreoDIAS: Sentinel 1 and 2 images, Landsat images,
other Copernicus data...

CreoDIAS provides a catalogue service containing information about:

  * scenes/tiles 

  

  * orbits 

  

  * all available meta-data for individual scene and orbit 

  

  * link to quick-look images 

  

  * support for various processing levels (L1C, L2A, etc.) 

  

  * information about planned future acquisitions with a rich number of criteria (including at least satellite unit, instrument mode, polarisation, geographical area, time window) The catalogue service supports querying based on number of criteria: 

  

  * geographical area 

    * bounding box (rectangle) 

  

    * geometry (e.g. for agriculture fields) 

  

  

  * mission/sensor 

  

  * cloud coverage 

    * based on scene meta-data 

  

    * if more detailed cloud data are available, also based on location 

  

  

  * time interval 

    * absolute based on "date" or "date and time" ranges defined using ISO8601 standard (from, to, from/to) 

  

    * relative time intervals ("last week", "last month", last 2 months", "from last 6 months up to last 3 months", etc.) 

  

    * advanced time intervals ("months May-August in from 1985 to 2016) 

  

  

  * mosaicking priority (most recent/least recent/least cloudy) INSPIRE and GEOSS compatibility is ensured for relevant data-sets. 

  

Dataset produced in the frame of CANDELA will also be catalogued to make them
findable. In the beginning, data will be referenced in a CANDELA specific
catalogue but extending the referencing to the CreoDIAS catalogue is an
interesting option. A GeoServer [7] tool instance is used to run processing
task on the platform and can be used to manage data. A dedicated catalogue
such as GeoNetwork [8] can also be used to manage the metadata.

On the other hand, a GeoNetwork catalogue provides capabilities to describe
data standards (Inspire and ISO). It also allows searching data with keywords
or geographical extents. The following information can be used to create
metadata files:

  * Metadata file creation date. 

  

  * Version of the data. 

  

  * Projection. 

  

  * Acquisition date. 

  

  * Resolution. 

  

  * Acquisition sensor. 

  

The previous information will help making the data discoverable.

###  2.1.2 Making data openly accessible

Once the datasets are on the CANDELA platform, access permissions (who can
access what) can be defined. Depending on the willingness of the data owner, a
data sharing strategy will be drawn. Possible access permissions can be:

  * Data without any restriction: all users can visualize, edit and download data without constraints. 

  

  * Protected data: rights will be defined for users in order to visualize, edit or download the data. 

  

###  2.1.3 Making data interoperable

Datasets on the CANDELA platform will be interoperable due to their compliance
with international standards such as Web Feature Service (WFS), Web Map
Service (WMS) and Web Coverage Service (WCS). GeoServer and OWSLib [9] Python
library are used as implementation of these protocols.

It is worth noting that additional standards can be defined in the life cycle
of the project. For example, all satellite images will be in JPEG2000 or
GeoTIFF format and they will be associated with metadata and provided through
WMS services.

###  2.1.4 Increase data re-use (through clarifying licenses)

For open source data such as Sentinel images, used licenses are indicated in
the metadata files. Users need to check these licenses before using or sharing
the data. On the other hand, use strategies will be defined for data and
services that will be produced as part of the project.

###  2.1.5 Current status on CANDELA project

At this time of the project, each processing service decides on the
publication or not of the produced data on GeoServer. The needs for
cataloguing on the data resulting from CANDELA processing services depends on
the dissemination strategy and will be discussed internally between the
partners before setting up the GeoNetwork catalogue according to these needs.

#  3 CANDELA project datasets

##  3.1 SUC1_Urbanization

This sub-use case is concerned with studying the effect of urban expansion on
agricultural areas due to the continuous development of human settlements and
climatic changes in the regions of Sicoval, Bordeaux and Milan. These regions
of interest are well known for the continuous build-up of urban areas and
richness and agricultural zones. Hence, the following datasets have been
identified:

  * Sentinel-2 images are used for the change detection pipeline developed by TAS FR. 

  

  * Sentinel-1 images are used for the change detection pipeline developed by TAS IT. 

  

  * Sentinel-1 and Sentinel-2 images are used for the data mining modules developed by DLR. 

  

  * Sentinel-1 and Sentinel-2 images are used for the semantic search tool developed by IRIT. 

  

  * Very High-Resolution optical images are used to validate the results of the change detection pipelines. 

  

Please note the deviation of the used datasets in this sub-use case. For
instance, the VHR datasets are limited to optical Pleaides images coming from
the DWH mechanism and only for the region of Bordeaux in France due to quota
limitation. Additionally, no VHR SAR images were found for the Bordeaux
region.

###  3.1.1 Dataset reference and name  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Summary**

</th> </tr>  
<tr>  
<td>

Sentinel-2

</td>  
<td>

Sentinel-2 satellite images are optical datasets produced as part of the EU
Copernicus program.

These data are collected from Sentinel-2 mission that comprises a
constellation of two polar-orbiting satellites.

Images coming from Sentinel-2 mission are characterized with a rich spectral
resolution (13 bands), a high spatial resolution (10m panchromatic band) and a
high acquisition frequency (5 days in cloudfree conditions). Hence, they are
very suitable for monitoring variability in land surface.

The datasets are in ESA SAFE format and contain inside one tile with all
spectral bands.

</td> </tr>  
<tr>  
<td>

SPOT6/7

</td>  
<td>

Sentinel-1 satellite images are SAR datasets produced as part of the EU
Copernicus program. The Sentinel-1 mission consists of two satellites
operating day and night to perform C-band synthetic aperture radar imaging and
allow an acquisition frequency of 6 days for the same place. Data are acquired
according to different modes and the one that will be used for this use case
is the Interferometric Wideswath mode (IW). This mode exists at a different
level of correction, namely, the Single Look Complex (SLC) and the Ground
Range Detected (GRD).

</td> </tr>  
<tr>  
<td>

Pleiades

</td>  
<td>

Pleiades is a constellation of two very high-resolution sensors that is able
to acquire any point on earth in under 24 hours. Pleaides has a narrower field
of view when compared to SPOT6/7. However, it

</td> </tr>  
<tr>  
<td>

</td>  
<td>

provides images with a finer spatial resolution (50 cm). Pleiades images also
have 4 spectral bands at 2 m and a panchromatic band at 50 cm.

</td> </tr> </table>

###  3.1.2 Dataset description  
  
<table>  
<tr>  
<th>

**ROI**

</th>  
<th>

**Dataset**

</th>  
<th>

**Description**

</th> </tr>  
<tr>  
<td>

_Sicoval_

</td>  
<td>

_Sentinel-2_

</td>  
<td>

  * _Period: Images acquired in the period between 2016 and 2019._

  

  * _Surface: 700 km2._

  

  * _Coordinates: xMin,yMin 1.39661,43.3902 : xMax,yMax_

  

_1.71621,43.5669 (WGS84)._

  * _S2 tilles: 31TCJ._

  

</td> </tr>  
<tr>  
<td>

_Sentinel-1_

</td>  
<td>

  * _Period: Images acquired in the period between 2016 and 2019._

  

  * _Surface: 700 km2._

  

  * _Coordinates: xMin,yMin 1.39661,43.3902 : xMax,yMax_

  

_1.71621,43.5669 (WGS84)._

</td> </tr>  
<tr>  
<td>

_Bordeaux_

</td>  
<td>

_Sentinel-2_

</td>  
<td>

  * _Period: Images acquired in the period between 2016 and 2019._

  

  * _Surface: 500 km2._

  

  * _Coordinates: xMin,yMin -0.703984,44.7483 : xMax,yMax -_

  

_0.46762,44.9188 (WGS84)._

  * _S2 tilles: 30TXQ._

  

</td> </tr>  
<tr>  
<td>

_Optical VHR (Pleiades)_

</td>  
<td>

  * _Period: Images acquired in the period between summer 2013 and summer 2019._

  

  * _Surface: 500 km2._

  

  * _Coordinates: xMin,yMin -0.703984,44.7483 : xMax,yMax -_

  

_0.46762,44.9188 (WGS84)._

</td> </tr>  
<tr>  
<td>

_Sentinel-1_

</td>  
<td>

  * _Period: Images acquired in the period between 2016 and 2019._

  

  * _Surface: 500 km2._

  

  * _Coordinates: xMin,yMin -0.703984,44.7483 : xMax,yMax -_

  

_0.46762,44.9188 (WGS84)._

</td> </tr>  
<tr>  
<td>

_Milan_

</td>  
<td>

_Sentinel-2_

</td>  
<td>

  * _Period: Images acquired in the period between 2016 and 2019._

  

  * _Surface: 500 km2._

  

  * _Coordinates: xMin,yMin 9.05816,45.3628 : xMax,yMax_

  

_9.29786,45.5361 (WGS84)._

  * _S2 tilles: 32TNR._

  

</td> </tr>  
<tr>  
<td>

_Sentinel-1_

</td>  
<td>

  * _Period: Images acquired in the period between 2016 and 2019._

  

  * _Surface: 500 km2._

  

  * _Coordinates: xMin,yMin 9.05816,45.3628 : xMax,yMax_

  

_9.29786,45.5361 (WGS84)._

</td> </tr> </table>

###  3.1.3 Standards and metadata  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Standards**

</th>  
<th>

**Metadata**

</th> </tr>  
<tr>  
<td>

Sentinel-2  _https://sentinel.esa.int/web/se_ _ntinel/user-
guides/sentinel-2msi/data-formats_

</td>  
<td>

13 JPEG2000 images, one for each band.

</td>  
<td>

XML file

</td> </tr>  
<tr>  
<td>

Pleiades  _https://www.intelligenceairbusds.com/en/8723pleiades-and-
spot-6-7-formatdelivery_

</td>  
<td>

2 JPEG2000 images, one for the B,G,R and NIR bands at 2 m spatial resolution
and the other for the panchromatic band at 0.5 m spatial resolution.

</td>  
<td>

XML file

</td> </tr>  
<tr>  
<td>

Sentinel-1  _https://earth.esa.int/web/sent_ _inel/technical-guides/sentinel-_

_1-sar/products-_

_algorithms/level-1-productformatting_

</td>  
<td>

Image data are stored in a Geotiff format.

</td>  
<td>

XML file and Geotiff SAR image

</td> </tr> </table>

###  3.1.4 Data Sharing

Sentinel-1 and Sentinel-2 data are free of charge and can be downloaded from
Copernicus Open Access Hub upon subscription. However, Pleaides images are
commercial data and can only be accessed by project partners.

###  3.1.5 Archiving and preservation

All the data described above will be conserved on the data server of the
platform during all the project life time for demonstration purposes. However,
since some datasets are commercial ones, they will have access restrictions.

##  3.2 SUC2_Vineyard

This sub-use case aims at assessing the damage level in vineyards caused by
natural hazards such as frost and hail. For this purpose, the following
datasets were identified for this sub-use case:

• Since the assessment of vineyards damage needs to be done as soon as the
event happens, Sentinel 2 images will be used for this use case.

Please note the deviation of this section when compared to the first version
of this document. The use of VHR satellite images will be challenging as it
requires programming the acquisition before and after a natural disaster,
which is difficult if not impossible.

###  3.2.1 Dataset reference and name  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Summary**

</th> </tr>  
<tr>  
<td>

Sentinel-2

</td>  
<td>

Sentinel-2 satellite images are optical datasets produced as part of the EU
Copernicus program.

These data are collected from Sentinel-2 mission that comprises a
constellation of two polar-orbiting satellites.

Images coming from Sentinel-2 mission are characterized with a rich spectral
resolution (13 bands), a high spatial resolution (10m panchromatic band) and a
high acquisition frequency (5 days in cloudfree conditions). Hence, they are
very suitable for monitoring variability in land surface.

The datasets are in ESA SAFE format and contain inside one tile with all
spectral bands.

</td> </tr> </table>

###  3.2.2 Dataset description  
  
<table>  
<tr>  
<th>

**ROI**

</th>  
<th>

**Dataset**

</th>  
<th>

**Description**

</th> </tr>  
<tr>  
<td>

_Bordeaux vineyards_

</td>  
<td>

_Sentinel-2_

</td>  
<td>

  * _Period: two Images, the first one was acquired on 19 th  April 2017 and the second image on the 29  th  April 2017 (after and before a frost event). _

  

  * _Surface: 1233 km 2  . _

  

  * _Coordinates: xMin,yMin -0.374589,44.5206 : xMax,yMax 0.0949954,44.7976 (WGS84)._

  

  * _S2 tilles: 30TYQ._

  

</td> </tr> </table>

###  3.2.3 Standards and metadata  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Standards**

</th>  
<th>

**Metadata**

</th> </tr>  
<tr>  
<td>

Sentinel-2

_https://sentinel.esa.int/web/sentinel/userguides/sentinel-2-msi/data-formats_

</td>  
<td>

13 JPEG2000 images, one for each band.

</td>  
<td>

XML file

</td> </tr> </table>

###  3.2.4 Data Sharing

Sentinel-2 data are free of charge and can be downloaded from Copernicus Open
Access Hub upon subscription.

###  3.2.5 Archiving and preservation

All the data described above will be conserved on the data server of the
platform during all the project life time for demonstration purposes. However,
since some datasets are commercial ones, they will have access restrictions.

##  3.3 SUC  1  _ Forest-Disaster

This case concerns occurring disasters in forests (windfalls) on the example
of RDLP Toruń in 2017. The study plans to analyze the extent of the occurrence
of the disaster, study the area and extent of damage. An analysis of the
activities carried out by the forestry services in the areas affected by the
disaster is also carried out.

Satellite images acquired using different sensors can be used for this sub-use
case.

  * Sentinel-2 and Sentinel 1 datasets will be used to change detection layer with information about areas that were affected by windthrow. For this purpose, Sentinel satellites appear to be adequate solution, as they provide large area coverage and frequent 5 days revisit time. 

  

  * VHR satellites (like SPOT 6/7, GeoEye-1) will be used to verify the results of the change detection algorithms. 

  

  * The initial use of high-resolution data has been changed due to limited access to VHR data and the time-consuming adaptation of algorithms to each type of satellite data. 3.3.1 Dataset reference and name 

  

  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Summary**

</th> </tr>  
<tr>  
<td>

Sentinel-1

</td>  
<td>

First satellite in Copernicus Program with C-SAR instrument which can operate
in four imaging modes with different resolution (down to 25m). The mission is
composed of two satellites, sharing the same orbital plane.

</td> </tr>  
<tr>  
<td>

Setninel-2

</td>  
<td>

Sentinel-2 satellite images are optical datasets gathered within the EU
Copernicus program.

The Sentinel-2 mission from which the data originates consists of a
constellation of two satellites orbiting the Earth. Characteristics of
Sentinel-2 based images are: rich spectral resolution (13 bands), a high
spatial resolution (10m panchromatic band) and a high acquisition frequency (5
days in cloud-free conditions).

</td> </tr>  
<tr>  
<td>

Pleiades

</td>  
<td>

Pleiades are two satellites operated by CNES (Space Agency of France). They
provide high resolution data for panchromatic band (0.7 m) and multispectral
bands (2.8m).

</td> </tr>  
<tr>  
<td>

GeoEye -1

</td>  
<td>

GeoEye-1 captures optical images since 2008. Data resolution from this
satellite for the panchromatic band is below 1 meter and for the multispectral
below 2 m. It has high revisit time for 40° latitude target.

</td> </tr>  
<tr>  
<td>

**ROI**

</td>  
<td>

**Dataset**

</td>  
<td>

**Description**

</td> </tr>  
<tr>  
<td>

_Torun_1 and Torun_2_

</td>  
<td>

_Sentinel-1_

</td>  
<td>

  * _Period: Images acquired just before 12.08.2017 and after_

  

  * _Surface: 860 km2._

  

  * _Coordinates: xMin,yMin 17.2997, 53.651802 : xMax,yMax_

  

_17.810054, 53.888559 (WGS84)_

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

•

</td>  
<td>

_S2 tile: 33UXV and 34UCE_

</td> </tr>  
<tr>  
<td>

_Sentinel-2_

</td>  
<td>

•

</td>  
<td>

_Period: Images acquired just before 12.08.2017 and after_

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

•

</td>  
<td>

_Surface: 860 km2._

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

•

</td>  
<td>

_Coordinates: xMin,yMin 17.2997, 53.651802 : xMax,yMax_

_17.810054, 53.888559 (WGS84)_

</td> </tr>  
<tr>  
<td>

_Torun_2_

</td>  
<td>

_GeoEye-1_

</td>  
<td>

• •

•

</td>  
<td>

_Period: Images acquired just before 12.08.2017 Surface: 700 km2._

_Coordinates: xMin,yMin 17.409115, 53.651802 : xMax,yMax 17.810054, 53.888559
(WGS84)_

</td> </tr>  
<tr>  
<td>

_Pleiades_

</td>  
<td>

•

</td>  
<td>

_Period: Images acquired just after 12.08.2017_

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

•

</td>  
<td>

_Surface: 700 km2._

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

•

</td>  
<td>

_Coordinates: xMin,yMin 17.409115, 53.651802 : xMax,yMax_

_17.810054, 53.888559 (WGS84)_

</td> </tr> </table>

###  3.3.3 Standards and metadata  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Standards**

</th>  
<th>

**Metadata**

</th> </tr>  
<tr>  
<td>

Sentinel-1  _https://earth.esa.int/web/sent_ _inel/technical-guides/sentinel-_

_1-sar/products-_

_algorithms/level-1-productformatting_

</td>  
<td>

Image data are stored in a Geotiff format.

</td>  
<td>

XML file,

geotiff SAR image &

GTiff image

</td> </tr>  
<tr>  
<td>

Sentinel-2  _https://sentinel.esa.int/web/se_ _ntinel/user-
guides/sentinel-2msi/data-formats_

</td>  
<td>

13 JPEG2000 images, one for each band.

</td>  
<td>

XML file

</td> </tr>  
<tr>  
<td>

Pleiades

_https://www.intelligenceairbusds.com/en/8723pleiades-and-
spot-6-7-formatdelivery_

</td>  
<td>

2 JPEG2000 images, one for the B,G,R and NIR bands at 2 m spatial resolution
and the other for the panchromatic band at 0.5 m spatial resolution.

</td>  
<td>

XML file

</td> </tr>  
<tr>  
<td>

GeoEye-1  _https://www.euspaceimaging._ _com/about/satellites/geoeye1/_

</td>  
<td>

2 GEOTIF images, one panchromatic and second multispectral (B, G, R and NIR).

</td>  
<td>

XML file

</td> </tr> </table>

###  3.3.4 Data Sharing

Data collected from Copernicus program: Sentinel-1 and Sentinel-2 can be
download from Copernicus Open Access Hub.

Pleiades and GeoEye-1 originated data are distributed on commercial licence
and can only be accessed by project partners.

###  3.3.5 Archiving and preservation

The datasets mentioned above will be stored on the platforms data server while
project life cycle.

However, due to the commercial license to use certain data, access to certain
data sets will be limited.

##  3.4 SUC4_ Forest-Health

This case concerns tree stand analyses during the bark beetle invasion in
Białowieża. The analyses will include both large-scale and low-scale studies
of forest condition.

The following datasets were identified for this sub-use case:

• Satellite images with a large number of bands in the VNIR and SWIR range
will be useful (e.g. Sentinel-2)

Independent data for validation was obtained for this scenario and for that
reason VHR data was not used and acquired.

###  3.4.1 Dataset reference and name  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Summary**

</th> </tr>  
<tr>  
<td>

Sentinel-1

</td>  
<td>

First satellite in Copernicus Program with C-SAR instrument which can operate
in four imaging modes with different resolution (down to 25 m). The mission is
composed of two satellites, sharing the same orbital plane.

</td> </tr>  
<tr>  
<td>

Setninel-2

</td>  
<td>

Sentinel-2 satellite images are optical datasets gathered within the EU
Copernicus program.

The Sentinel-2 mission from which the data originates consists of a
constellation of two satellites orbiting the Earth. Characteristics of
Sentinel-2 based images are: rich spectral resolution (13 bands), a high
spatial resolution (10m panchromatic band) and a high acquisition frequency (5
days in cloud-free conditions).

</td> </tr> </table>

###  3.4.2 Dataset description  
  
<table>  
<tr>  
<th>

**ROI**

</th>  
<th>

**Dataset**

</th>  
<th>

**Description**

</th> </tr>  
<tr>  
<td>

_Białowieża_

</td>  
<td>

_Sentinel-1_

</td>  
<td>

  * _Period: Images acquired from 2015 to 2018 in summer months_

  

  * _Surface: 385 km2._

  

  * _Coordinates: xMin,yMin 23.68852, 52.674583 : xMax,yMax_

  

_23.949071, 52.870889 (WGS84)_

  * _S2 tile: 34UFD_

  

</td> </tr>  
<tr>  
<td>

_Sentinel-2_

</td>  
<td>

  * _Period: Images acquired from 2015 to 2018 in summer months_

  

  * _Surface: 385 km2._

  

  * _Coordinates: xMin,yMin 23.68852, 52.674583 : xMax,yMax 23.949071, 52.870889 (WGS84)_

  

</td> </tr> </table>

###  3.4.3 Standards and metadata  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Standards**

</th>  
<th>

**Metadata**

</th> </tr>  
<tr>  
<td>

Sentinel-1  _https://earth.esa.int/web/sent_ _inel/technical-guides/sentinel-_

_1-sar/products-_

_algorithms/level-1-productformatting_

</td>  
<td>

Image data are stored in a Geotiff format.

</td>  
<td>

XML file,

geotiff SAR image &

GTiff image

</td> </tr>  
<tr>  
<td>

Sentinel-2  _https://sentinel.esa.int/web/se_ _ntinel/user-
guides/sentinel-2msi/data-formats_

</td>  
<td>

13 JPEG2000 images, one for each band.

</td>  
<td>

XML file

</td> </tr> </table>

###  3.4.4 Data Sharing

Data collected from Copernicus program: Sentinel-1 and Sentinel-2 can be
download from Copernicus Open Access Hub.

3.4.5 Archiving and preservation

The datasets mentioned above will be stored on the platforms data server while
project life cycle.

#  4 Additional datasets

As part of the datasets used in the project, this section provides information
about the use of Additional datasets (ADD) following the process stablished by
ESA through the Data Warehouse mechanism (DWH). Detailed information about the
project request and the use of ADD is available in deliverables D5.7 [5][10]
and D5.8 [12] respectively.

##  4.1 Request of additional datasets 2019

CANDELA project requested Additional datasets (ADD) for 2019. The official
request was included in the project deliverable D5.7 [5][10] (v1.0 submitted
in September 2018 and v2.0 submitted in February 2019). Below is presented the
final list of Additional datasets requested in February 2019.

**Figure**

**1**

**:**

**Consolidated Request February 2019 (D5.7)**

**[10]**

The project request was validated internally by the European Space Agency
(ESA) in August 2019 when the Agency published version 2.6[11] of the Data
Access Portfolio Document (DAP). As it is showed in Figure 2, the validation
included datasets requested for both versions of D5.7 [5][10].

**Figure**

**2**

**:**

**Assigned quota DAP version August 2019**

**[11]**

##  4.2 DWH use for 2019

The use of Additional datasets was reported in D5.8[12] following the two use
cases proposed in CANDELA:

  * Use case 1: Agriculture and Macro-economics (see deliverables [3][13]) 

  

  * Use case 2: Forest Health Monitoring (see deliverables [4][14]) 

  

D5.8[12] describes the use of ADD in the project focusing in the use for
validations purposes. Some examples include the use of VHR images obtained
from the DWH mechanism to validate using photo interpretation. In addition,
VHR images could also be used to verify the results obtained by machine
learning algorithms developed in the project. Sections 3 and 4 of the
aforementioned report D5.8[12] include detailed information of the use of
additional datasets in the project.

#  5 Conclusions

The second version of the DMP (this document) includes updated information of
the CANDELA DMP v1 released in December 2018[15].

The document describes the bold lines in the data management plan of CANDELA
project, including how to make the project data findable, accessible,
interoperable and reusable. As the CANDELA platform is not completed yet, more
details will emerge in the final DMP deliverable that better illustrate the
mechanism of data standards, storing, sharing, security and ingestion.

Main changes in this version are:

  * The project datasets described in section 3 have been updated including detailed information for each project use case. 

  

  * The needs for cataloguing on the data resulting from CANDELA processing services will be discussed internally between project partners. Section 2.1.5 has been added to stand out the current status of this issue. 

  

  * Section 4 has been updated including information about the Additional datasets requested and used by CANDELA. 

  

The next and final DMP (to be released in October 2020) will contain more
details about products and datasets produced using the analytic tools.