Use of hyperspectral and multi-angle CHRIS Proba image for land

87 Pages·2008·2.45 MB·English

Universit(cid:224) degli Studi di Tor Vergata Roma
Facolt(cid:224) di Ingegneria
Dipartimento di Informatica Sistemi e Produzione
Ph.D. Geoinformation Programme
Use of hyperspectral and
multi-angle CHRIS Proba image
for land cover maps generation
Tesi di Laurea di
Riccardo Duca
Relatore: Prof. Fabio Del Frate
Sessione di laurea Maggio 2008
Contents
List of Acronymous 1
Abstract 3
1 Introduction 5
1.1 From multi-spectral to hyper-spectral imagery: the evolution
of the optical sensors . . . . . . . . . . . . . . . . . . . . . . . 5
1.2 Aim of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 Organization of the dissertation . . . . . . . . . . . . . . . . . 9
2 CHRIS Proba acquisitions over Frascati and Tor Vergata 11
2.1 The Proba-1 mission and the small hyperspectral CHRIS . . . 11
2.2 The test area of Frascati and Tor Vergata . . . . . . . . . . . 13
2.3 Acquisitions in mode 3 spectral con(cid:28)guration . . . . . . . . . . 16
2.4 Data used for the work . . . . . . . . . . . . . . . . . . . . . . 18
3 Pre-application processing 21
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2 Black pixel removal . . . . . . . . . . . . . . . . . . . . . . . . 21
3.3 The stripes noise in the optical images . . . . . . . . . . . . . 23
3.4 Destriping based on the histogram modi(cid:28)cation . . . . . . . . 24
Contents ii
3.5 Destriping based on the (cid:28)ltering in the frequency spatial domain 26
3.6 The atmospheric correction . . . . . . . . . . . . . . . . . . . 34
3.7 The geo-recti(cid:28)cation . . . . . . . . . . . . . . . . . . . . . . . 36
4 The production of land cover and land use maps 38
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2 Preliminary multi-angular analysis . . . . . . . . . . . . . . . 39
4.3 The neural networks classi(cid:28)cation . . . . . . . . . . . . . . . . 48
4.4 Classi(cid:28)cation of hyperspectral CHRIS nadir imagery . . . . . 49
4.5 Classi(cid:28)cation of hyperspectral multi-angular CHRIS imagery . 54
4.6 Further potentiality given by the merging of multi-temporal
and multi-angular images . . . . . . . . . . . . . . . . . . . . . 58
4.7 Comparison between ETM+ and CHRIS . . . . . . . . . . . . 65
5 Conclusions 71
Bibliography 74
Curriculum Vitae 78
Conferences, Publications and Seminars . . . . . . . . . . . . . . . 79
List of Figures
2.1 (a) PROBA satellite, (b) CHRIS sensor . . . . . . . . . . . . . 12
2.2 Multi-angle acquisition during the target overpass . . . . . . . 14
2.3 (a) Maps of the area of interest (from Google Maps), (b) VHR
Quickbird image over the same area . . . . . . . . . . . . . . . 15
2.4 (a)CHRISmode3bandsallocation,(b)LandsatETM+bands
allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.5 VHR Quickbird images with the vineyards polygons . . . . . . 20
3.1 Example of rows with black pixels, one along the bottom edge
and the other inside the scenario . . . . . . . . . . . . . . . . 22
3.2 Exampleofpowerspectruma(cid:27)ectedbystriped(left)andpower
spectrum after the correction (right) . . . . . . . . . . . . . . 28
3.3 Image acquired over the Lybian desert (band 1): (a) original
image a(cid:27)ected and disequalized by the presence of stripes, (b)
the same image after the destriping . . . . . . . . . . . . . . . 30
3.4 (a) Band 1 of CHRIS image acquired on 30 January 2007
a(cid:27)ected by stripes, (b) the same image after detriping . . . . . 31
3.5 (a) CHRIS image of 30 January 2007, (b) area a(cid:27)ected by
residual stripes close to a cumulus of clouds, (c) the same area
mitigated by the use of the bright pixels masking . . . . . . . 32
3.6 Tampa Bay (USA), missing correction close to the coast line . 32
List of Figures iv
3.7 E(cid:27)ects of adjacency correction. Particular before the correc-
tion (on the left) and after the correction (on the right) . . . . 36
4.1 Tor Vergata University campus: (a) true color composition
using band 8, band 4, band 2, (b) RGB angular composition
using band 10 and FZA-36, FZA0 and FZA36, (c) RGB angu-
lar composition using band 10 and FZA0, FZA36 and FZA55 41
4.2 Fieldsofmaize: (a)Truecolorcompositionusingband8, band
4, band 2, (b) RGB angular composition using band 10, (c)
very high resolution image . . . . . . . . . . . . . . . . . . . . 42
4.3 (a) multi-angular re(cid:29)ectance for a row vineyard, (b) multi-
angular re(cid:29)ectance for a corn (cid:28)eld . . . . . . . . . . . . . . . . 44
4.4 (a)multi-angularre(cid:29)ectancefordenseforest,(b)multi-angular
re(cid:29)ectance for uncultivated areas . . . . . . . . . . . . . . . . 45
4.5 (a) multi-angular re(cid:29)ectance for urban residential buildings,
(b) multi-angular re(cid:29)ectance for industrial and commercial
units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.6 (a)multi-angularre(cid:29)ectancedarkasphaltedsurface,(b)multi-
angular re(cid:29)ectance for bright asphalted surfaces . . . . . . . . 47
4.7 SSE vs. the number of units for hidden layers . . . . . . . . . 51
4.8 (a) Image over Tor Vergata Campus extracted from the ac-
quisition of 28th February 2006, (b) clssi(cid:28)ed map in seven
classes: dark asphalt, bright asphalt, urban buildings, indus-
trial/commercial units (withe), bare soil, green vegetated ar-
eas, forest and permanent crops . . . . . . . . . . . . . . . . . 52
4.9 Multi-angular classi(cid:28)cation related to 28th February 2006 . . . 56
List of Figures v
4.10 (a) VHR images of the commercial and residential area near
Tor Vergata campus, (b) the same area acquired by CHRIS,
(c) classi(cid:28)cation using the nadir image of 28th February 2006,
multi-angular classi(cid:28)cation of the same acquisition . . . . . . . 57
4.11 (a) acquisition of October the 28th, (b) acquisition of August
the 19th and (c) acquisition of October the 9th . . . . . . . . 59
4.12 (a)multi-temporalre(cid:29)ectanceforvineyards,(b)multi-temporal
re(cid:29)ectance for corn (cid:28)elds . . . . . . . . . . . . . . . . . . . . . 61
4.13 (a)multi-temporalclassi(cid:28)cation,(b)multi-temporalandmulti-
angularclassi(cid:28)cation.Darkasphalt,brightasphalt,urbanbuild-
ings, industrial/commercial units (withe), uncultivated, Oth-
ers permanent crops, Vineyards, Corn, Others agricultural ar-
eas, masked areas (clouds and shadows) . . . . . . . . . . . . . 63
4.14 (a) CHRIS acquisition of 19th 2006, (b) ETM+ acquisition of
19th August 2004 . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.15 (a) classi(cid:28)cation related to CHRIS acquisition of 19th 2006,
(b) classi(cid:28)cation related to ETM+ acquisition of 19th August
2004. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.16 Signature extracted for urban buildings, vineyard, unculti-
vated: (a) CHRIS signature, (b) ETM+ signature. The values
represents re(cid:29)ectances resclated between -1 and 1 . . . . . . . 69
4.17 (a) VHR image over one area not correctly classi(cid:28)ed in the
CHRIS classi(cid:28)cation, (b) CHRIS image, (c) ETM+ image . . 70
List of Tables
2.1 Spectral con(cid:28)guration of CHRIS Mode 3 (values expressed in
nm) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2 CHRIS Proba acquisition available for the area of Frascati and
Tor Vergata. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.1 Global statistical analysis performed for the image of 30 Jan-
uary 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.2 Signi(cid:28)cant inputs for the radiative simulations . . . . . . . . . 35
4.1 Confusionmatrixrelatedtotheclassi(cid:28)cationofthe28thFebru-
ary 2006 FZA0 . . . . . . . . . . . . . . . . . . . . . . . . . . 53
4.2 Improvement for the classi(cid:28)cation phase reached by the use of
multi-angle information . . . . . . . . . . . . . . . . . . . . . . 56
4.3 Confusionmatrixforthemulti-temporalclassi(cid:28)cation(3dates)
of the nadir images. The reported values are in % . . . . . . . 64
4.4 Improvements obtained with the use of multi-angle and multi-
temporal acquisitions . . . . . . . . . . . . . . . . . . . . . . . 64
4.5 ImprovementsobtainedusingtheCHRISproductwithrespect
to ETM+ image . . . . . . . . . . . . . . . . . . . . . . . . . . 68
List of acronymous
AATSR: Advanced Along-Track Scanning Radiometer
ADEOS: ADvanced Earth Observation Satellite
AERONET: Aerosol Robotic Network
AMTIS: Airborne Multi-angle TIR/VNIR Imaging System
AVHRR: Advanced Very High Resolution Radioneter
CHRIS: Compact High Resolution Images Spectrometer
CNR: Consiglio Nazionale delle Ricerche
DAISEX: Digital AIrborne Sectrometer EXperiment
ESA: European Space Agency
ETM+: Enhanced Thematic Mapper
FFT: Fast Fourier Tranform
FZA: Fly by Zenith Angle
GCP: Ground Control Point
GIS: Geographic Information System
GLCF: Global Land Cover Facility
HRC: High Resolution Camera
MERIS: Medium Resolution Imaging Spectrometer
MISR: Multi-angle Imaging SpectroRadiometer
MODIS: Moderate resolution Imaging Spectroradiometer
MZA: Minimum Zenith Angle
List of acronymous 2
POLDER: POLarization and Directionality of the Earth’s Re(cid:29)ectances
SPOT: SystŁm Pour l’Observation de la Terre
SWIR: Short Wave Infra Red
TOA: Top Of Atmosphere
VHR: Very High Resolution
Abstract
In the last decades, many satellite missions have marked the history of the
optical remote sensing, providing a wide choice of products for every kind of
application and investigation. The Proba-1 program can not be compared
in importance and budget to the very important missions like Landsat and
SPOT, but the innovations introduced in the payload design have attracted
the attention of principal investigators and scientists since the beginning.
The new spectral con(cid:28)guration of its high resolution sensor CHRIS can rep-
resent an innovation for the wide family of the optical instruments. In fact
CHRIS is one of the (cid:28)rst experiments, as well as NASA Hyperion, concern-
ing the developing of the expensive hyperspectral technology for the satellite
environment. Moreover, the innovative solutions for the autonomous orbit
maintaining and navigation, permit to the spacecraft di(cid:30)cult manoeuvres
and multi-angular acquisitions during the target overpass. The result is an
extraordinary and unique database of hyperspectral and multi-directional
images acquired several times during the years over prede(cid:28)ned test sites.
This research work proposes a complete treatment of the CHRIS products
since the radiometric and geometric correction till the classi(cid:28)cation process-
ing. Phases like destriping, atmospheric corrections, spectral adjacency com-
pensation and ortho-recti(cid:28)cation have been performed and developed. Sev-
eral classi(cid:28)cation exercises have been proposed with the aim of evaluating