Long Term Data Preservation and applications of Nimbus 7 - Coastal Zone Color Scanner dataset

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1 . Introduction 
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This work analyzes  the problem of  the preservation, storage and exploitation 
of dataset resulting by Remote Sensing / Earth Observation satellite-based 
missions. The question is  treated  with respect to the data relating to the 
NASA ‘s  historical mission NIMBUS 7- CZCS (Coastal Zone Color Scanner) 
launched in 1978 and operational until 1986.   
It will be evaluated also the possibility to utilize  such data for environmental 
applications of remote sensing doing a comparison with most recent data 
derived from a current or recent Earth Observation mission. 
The first step to perform, once completed the recovery of all the datasets 
available in ESA, “third parts” and worldwide acquisition stations archives 
consists in creating a data-inventory in accordance to the European LTDP 
Common Guidelines  on the treatment and preservation of historical missions 
datasets. 
This document, in fact, together  with the PDSC - Preserved Data Set Content on 
the Earth Observation preserved dataset content, describes all the 
requirements that the database/inventory should have. Thanks to this 
properties the inventory should be modelled with appropriate interface, 
accessibility and reliability features so that to maintain the capability to 
exploit in every moment the information and the dataset contained in the 
database. 
Once specified the database requirements, it is possible to proceed to the 
screening of the data found in most disparate places. This information must 
comply with the specifications of the database and in it properly placed. 
In this way any future user, at various levels of knowledge, (from a basic user 
level, where the database will contain the greatest number of information
Introduction 
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necessary to exploit the data, to more advanced user levels where information 
relating to the software and hardware  processing  and on their size and other 
technical specifications will be redundant) can utilize the information for a 
long time and possibly even act to preserve them further with less difficulty 
than the present. 
The activity carried out in this thesis is part of the ESA Program LTDP-Long 
Term Data Preservation which involves several historical Earth Observation 
missions like Nimbus 7- CZCS , SEASAT–SAR,  HCMM (Heat Capacity 
Mapping  Mission),  IRS P3-MOS, JERS and others. 
For each of these mission the work to put in place should be: 
 Complete dataset recovery.
 Retrieval of all the possible documentation concerning the format of
data at various levels.
 Search and retrieval of any useful information about the mission.
 Inventory of all the data recovered.
 Re-creation of a Software/Hardware processing chain dedicated to
reprocess and exploit all the dataset recovered for further applications
of remote sensing and environmental studies.
 Creation of a Handbook describing all the process of mission recovery
useful  for further users to avoid the current problems of data
exploitation.
This  is what it has been done  with the Nimbus 7- CZCS dataset  in the present 
thesis.  
A further step to complete the LTDP mission recovery process should be to 
make available the products already processed from the dataset in a database 
freely accessible online by users. This latter task would have been too difficult 
to be achieved herein. In any case this aspect is very important to fully recover 
the scientific contribution of the mission.
Introduction 
 
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The most difficult part in the recovery of a mission is undoubtedly the 
creation or re-creation of the processor/software chain that can read and 
manage the dataset retrieved. 
The hardware on which the software worked to process the data very often 
are  obsolete and have been decommissioned and almost always lost. The data 
processing was discontinued and the whole skills employed in the data 
exploitation were erased by the time passing. It is also very hard to find even 
the people who worked on the processing of those data. 
CZCS and SEASAT , for example, are two NASA missions launched in 1978 by 
the GSFC Goddard Space Flight Centre (CZCS) and JPL Jet Propulsion 
Laboratory(SEASAT).  
Sometimes it is necessary even to look for information from those who 
worked on the data at the time of their acquisition, if they are still available. 
A valuable help is often given by the documentation retrieved for each 
mission, because in it is contained most of the useful information for the 
reading of the data and the use of the old processors. 
Any aspect of those listed above should not be disregarded in an LTDP 
approach. Indeed, it would be very impossible and useless to plan a mission 
recovery without taking into account all aspects related to the consolidation 
and the inventory of the dataset recovered, or worse without creating a 
valuable  software chain for further use and processing of data. Only when all 
the dataset is recovered and can be properly processed and exploited in an 
easy accessible software chain and the products can available from all the 
possible users it will be possible to assert that the mission recovery is 
completed. 
This work started studying the case of the two NASA Earth Observation 
missions NIMBUS 7-CZCS and SEASAT SAR and also trying to recover data 
from other “Historical Missions” like HCMM, IRS P3-MOS, JERS, NOAA AVHRR, 
SPOT 1, etc. It was possible to find satisfactory dataset and documentation 
with only the first two. Later the work performed concerned primarily the 
consolidation, exploitation and processing of the CZCS dataset.
Introduction 
 
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In the activities  performed in this thesis there is also  a scientific aspect even 
if is a simple and basic remote sensing application to demonstrate the 
possibility to properly utilize the dataset recovered from the mission. 
In particular it is applied one of the basis characteristic of the Coastal Zone 
Color Scanner sensor : the measurement of the chlorophyll content in sea 
waters. Once made this environmental survey for a given geographical area, 
through measures concerning the period when the mission was still operative 
(November 1978-June 1986), it is performed a comparison between  these 
data and  those obtained  from a similar most recent mission of the same 
typology (ENVISAT-MERIS). 
This is a way to demonstrate the usefulness of preserving and exploit the data 
relating to pioneering missions decades old. 
It were retrieved several CZCS datasets in this LTDP mission recovery activity, 
both in the ESA-ESRIN NAS (Network Attached Storage) and in the INSA-
Maspalomas acquisition station, which acquired a number of CZCS passages 
after a certain moment. In this way the present analysis ended up with a 
rather heterogeneous dataset comprising data at various levels: 
 
 L1 data acquired in Lannion (FR) and recovered in the ESRIN NAS. 
 L1 data acquired in Maspalomas (MP) and recovered in the ESRIN 
NAS. 
 L2 data acquired in Lannion (FR) and recovered in the ESRIN NAS. 
 L2 data acquired in Maspalomas (MP) and recovered in the ESRIN 
NAS. 
 L0 data acquired and recovered in Maspalomas. 
 L0 data acquired in Lannion and recovered in Maspalomas. 
 
Contents of the Thesis 
After this  introduction,  the second chapter of the thesis deals with the 
Remote Sensing, doing a basic discussion of its foundations such as the
Introduction 
 
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properties of the electromagnetic spectrum, sensors and platforms, the 
corrections and the typologies of data.  
The third chapter treats and illustrates in detail  the ESA Long Term Data 
Preservation program. 
The fourth part is a detailed description of the Nimbus7–CZCS mission and of 
the applications allowed by the instrument and its processors. 
The fifth chapter illustrates the internship in ESA-ESRIN and the activities 
carried out during the stage. 
The sixth part explains the dataset retrieval, its inventorying ad appraisal. 
The seventh part is a description of the current mission used as a reference 
for the validation of the CZCS dataset. 
The eighth chapter deals with describing the comparison between the data of 
CZCS and those of MERIS, which is the true scientific application conducted in 
the scope of this thesis. This comparison is performed using a Test of 
Significance. 
The last chapter describes the conclusions drawn from this work. 
 
SEASAT-SAR 
As already mentioned, at first it has been recovered also the dataset relating 
the mission SEASAT SAR, a synthetic-aperture radar sensor that monitored 
the global surface wave field and polar sea ice conditions, providing 
information also on ice caps, snow coverage and coastal regions. The mission 
operated only for 2 months in 1978 (August-October) before a massive short 
circuit in the satellite ended the mission. 
 
SEASAT was the first space borne synthetic aperture radar designed for Earth 
Observation. The aim of this mission was to collect data about sea-surface 
winds, sea-surface temperatures, wave heights, internal waves, ocean
Introduction 
 
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topography, coastal atmosphere. The system operated at L-Band with 100 km 
swath and a ground resolution of 25 m. 
There are also conspiracy theories about the end of this mission: the 
instrument was capable to detect the waves of the submerged military 
submarines and for this reason it would be deactivated.
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2.  Fundamentals of Remote Sensing 
 
 
2.1 Introduction 
 
Remote Sensing is a way to get information from objects that is based on the 
collection  and analysis of data without the instrument used to collect the data 
being in direct contact with the object. 
A Remote Sensing system consists of three elements: 
 A platform capable of supporting the instrument 
 An object to observe 
 An instrument or sensor to observe the target 
The object to observe could be the Earth or the space. Of course, in the our 
analysis we will consider Earth Observation only. 
In remote sensing energy emanating from the earth’s surface is measured 
using a sensor mounted on an aircraft or spacecraft platform. That 
measurement is used to construct an image of the landscape beneath the 
platform. The energy can be reflected sunlight so that the image recorded is, in 
many ways, similar to the view we would have of the earth’s surface from an 
aeroplane, although the wavelengths used in remote sensing are often outside 
the range of human vision.  As an alternative, the upwelling energy can be 
from the earth itself acting as a radiator because of its own temperature. 
Finally, the energy detected could be scattered from the earth as the result of 
some illumination by an artificial energy source such as a laser or radar 
carried on the platform.
Fundamentals of Remote Sensing 
 
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It is important  to note that the overall system is a complex one involving the 
scattering or emission of energy from the earth’s surface, followed by 
transmission through the atmosphere to instruments mounted on the remote 
sensing platform, transmission or carriage of data back to the earth’s surface 
after which it is then processed into image products ready for application by 
the user. 
We generally talk about the imagery recorded as image data since it is a 
primary data source from which we wish to extract usable information.  
 
 
Fig. 2.1 – Data flow in a remote sensing system 
One of the major beneficial characteristics of the image data acquired by 
sensors on aircraft or spacecraft platforms is that it is readily available in 
digital format. Spatially the data is composed of discrete picture elements, or
Fundamentals of Remote Sensing 
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pixels. Radiometrically it is quantised into discrete levels. Even data that is not 
recorded in digital form initially can be converted into discrete data by the use 
of digitising equipment. In the early days of remote sensing there was a 
significant amount of analogue data recorded; now most of the data is 
available directly in digital form. 
The great advantage of having data available digitally is that it can be 
processed by computer either for machine assisted information extraction or 
for enhancement of its visual qualities in order to make it more interpretable 
by a human analyst. 
Fig 2.2 Electromagnetic spectrum