GEO-IMAGERY MANAGEMENT AND STATISTICAL PROCESSING IN A REGIONAL CONTEXT USING OPEN DATA CUBE U.Otamendi I.Azpiroz M.QuartulliI.Olaizola

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GEO-IMAGERY MANAGEMENT AND STATISTICAL PROCESSING

IN A REGIONAL CONTEXT USING OPEN DATA CUBE

U.Otamendi, I.Azpiroz, M.Quartulli,I.Olaizola

Vicomtech Foundation

Basque Research and Technology Alliance (BRTA)

Donostia-San Sebasti´

an, 20009, Spain

F.J.Perez, D.Alda, X.Garitano

HAZI Foundation

Granja Modelo

Arkaute, 01192, Spain

ABSTRACT

We propose a methodology to manage and process remote

sensing and geo-imagery data for non-expert users. The pro-

posed system provides automated data ingestion and manip-

ulation capability for analytical data-driven purposes. In this

paper, we describe the technological basis of the proposed

method in addition to describing the tool architecture, the in-

herent data ﬂow, and its operation in a speciﬁc use case to

provide statistical summaries of Sentinel-2 regions of inter-

est corresponding to the cultivation polygonal areas located

in the Basque Country (ES).

Index Terms—Open Data Cube, Sentinel, data exploita-

tion, management, storage

1. INTRODUCTION

The use of high spatial resolution optical imagery for land use

and land cover change mapping [1, 2, 3] has generated a high

demand for efﬁcient geo-imagery storage, processing, and

management infrastructures [4]. In response to that request,

The Committee on Earth Observation Satellites (CEOS) has

founded the Open Data Cube (ODC) initiative [5], publish-

ing a free and open geospatial exploitation tool [6]. Large

Spatio-temporal Earth Observation (EO) data volumes are

rapidly processed through metadata indexing and ingestion

procedures, providing an efﬁcient tool to query remote sens-

ing data. The main drawback of implementing an ODC-based

environment for geo-imagery management and analytics is

that it requires an investment in hardware, as well as an

initial effort on conﬁguring the system with the considered

metadata and product descriptions. Several contributions [6]

address data governance issues in terms of the use of cloud

environment tools such as Google Earth Engine (GEE) [7].

GEE provides a cloud environment, where the analysis of

georeferenced data (Earth observation satellites, weather, and

climate data) is possible with limited data management ef-

fort. This has resulted in an efﬁcient and widely used tool

for tasks that range from querying and synchronizing cli-

mate reanalysis datasets to the exploitation of georeferenced

measurements for e.g. land use analysis [8] or to improve

existent plant phenology models [9]. A possible alternative

to GEE lies in initiatives such as ODC, which allow local

institutions to undertake geo-imagery data management and

analysis directly.

The ability to rapidly generate local statistics for a time

series of remote sensing images represents a valuable asset

for geo-imagery exploitation for rapid mapping. The pos-

sibility to routinely perform this generation in a completely

automated manner and in terms that are familiar to a domain

expert such as a forester or an agronomist represents an added

value point. In particular, the capability to translate the mea-

surements available in remote sensing image products in the

format of a multi-resolution tile pyramid allows the informa-

tion to be queried by simply specifying a spatial region and

a temporal interval of interest and a set of collections to con-

sider as sources. The possibility for the domain expert analyst

to deal with pre-processed, pre-organized, and pre-tiled infor-

mation content, allows them to focus on the intended applica-

tion without having to cope with speciﬁcities of the original

data that stem from the way those were collected.

In this sense, the main goal of the current contribution is

to describe and introduce a geo-imagery data management,

processing, and exploitation service. This service integrates a

methodology intended to provide statistical summaries of re-

gions of interest corresponding to geo-polygonal data. The

service is oriented to geospatial data analysts with limited

knowledge of remote sensing technology.

In what follows, we present in detail the problem to solve,

focusing on the processing of geo-polygons in ODC for the

extraction of geo-spatial statistics. We describe the imple-

mented architecture, detailing its main components. We pro-

ceed by presenting the imagery characteristics for static and

time-dependent products. In addition, we have veriﬁed the

performance of the service using Sentinel-2 imagery to ana-

lyze an approximated quantity of 20000 areas of interest lo-

cated in the Basque Country (ES).

arXiv:2210.01470v1 [cs.CV] 4 Oct 2022

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GEO-IMAGERYMANAGEMENTANDSTATISTICALPROCESSINGINAREGIONALCONTEXTUSINGOPENDATACUBEU.Otamendi,I.Azpiroz,M.Quartulli,I.OlaizolaVicomtechFoundationBasqueResearchandTechnologyAlliance(BRTA)Donostia-SanSebasti´an,20009,SpainF.J.Perez,D.Alda,X.GaritanoHAZIFoundationGranjaModeloArkaute,01192,SpainABSTRACTWep...

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GEO-IMAGERY MANAGEMENT AND STATISTICAL PROCESSING IN A REGIONAL CONTEXT USING OPEN DATA CUBE U.Otamendi I.Azpiroz M.QuartulliI.Olaizola

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