IDENTIFYING INDUSTRIAL PROCESSES THROUGH VNIR-SWIR REFLECTANCE SPECTROSCOPY OF THEIR WASTE MATERIALS

被引:3
|
作者
Lothode, Maiwenn [1 ]
Carrere, Veronique [1 ]
Marion, Rodolphe
机构
[1] Univ Nantes, UMR CNRS 6112, LPG Nantes, F-44322 Nantes 3, France
关键词
Hyperspectral; Industrial wastes; Reflectance Spectroscopy; Spectral Derivation; MINERALS;
D O I
10.1109/IGARSS.2014.6947182
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Industries dump important amounts of wastes which must be characterized for estimating environmental quality and identifying industrial processes, which can they be related to some specific mineral combinations. Land disposal is an usual practice and allows for hyperspectral remote sensing characterization. Many studies have shown that spectroscopy is a powerful tool for mining waste minerals monitoring. Nevertheless, little has been done regarding the spectral features of industrial wastes. The aim of this study is to perform spectral measurements, in-situ and in the laboratory, of industrial wastes to extract their optical and spectral characteristics. This preliminary study will then be used for interpretation of hyperspectral images acquired over test sites. We focus here on two industrial sites because of their similarity in the visible and near infrared (VNIR) that can not be distinguished using color images only : (1) Neutralization Plant Seche-Ecoservice (France) and (2) Land disposal area of the Bauxite refinery Alteo-Environment. The spectral features of the spectrum are extracted using the first and the second derivative. With this preliminary study, we are able to conclude that imaging spectroscopy is an efficient tool for the characterization of such industrial wastes.
引用
收藏
页数:4
相关论文
共 40 条
  • [1] Logistic splicing correction for VNIR-SWIR reflectance imaging spectroscopy
    Grillini, Federico
    Thomas, Jean-Baptiste
    George, Sony
    [J]. OPTICS LETTERS, 2023, 48 (02) : 403 - 406
  • [2] Characterization of clay minerals and Fe oxides through diffuse reflectance spectroscopy (VNIR-SWIR)
    Bascones, A.
    Suarez, M.
    Ferrer-Julia, M.
    Garcia-Melendez, E.
    Colmenero-Hidalgo, E.
    Quiros, A.
    [J]. REVISTA DE TELEDETECCION, 2020, (55): : 49 - 57
  • [3] Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy
    Curcio, D.
    Ciraolo, G.
    D'Asaro, F.
    Minacapilli, M.
    [J]. FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES, 2013, 19 : 494 - 503
  • [4] Advantages of first-derivative reflectance spectroscopy in the VNIR-SWIR for the quantification of olivine and hematite
    Bou-Orm, Nadine
    AlRomaithi, Amna Abdulrahman
    Elrmeithi, Mariam
    Ali, Fatima Mohammad
    Nazzal, Yousef
    Howari, Fares M.
    Al Aydaroos, Fatima
    [J]. PLANETARY AND SPACE SCIENCE, 2020, 188
  • [5] Classification of soybean groups for grain yield and industrial traits using Vnir-Swir spectroscopy
    Santana, Dthenifer Cordeiro
    Seron, Ana Carina Candido
    Teodoro, Larissa Pereira Ribeiro
    de Oliveira, Izabela Cristina
    da Silva Junior, Carlos Antonio
    Baio, Fabio Henrique Rojo
    Itavo, Camila Celeste Branda Ferreira
    Itavo, Luis Carlos Vinhas
    Teodoro, Paulo Eduardo
    [J]. INFRARED PHYSICS & TECHNOLOGY, 2024, 139
  • [6] Identifying vehicles with VNIR-SWIR hyperspectral imagery: Sources of distinguishability and confusion
    Adler-Golden, Steve
    Sundberg, Robert
    [J]. IMAGING SPECTROMETRY XXI, 2016, 9976
  • [7] Relationship between reflectance and degree of polarization in the VNIR-SWIR: A case study on art paintings with polarimetric reflectance imaging spectroscopy
    Grillini, Federico
    Aksas, Lyes
    Lapray, Pierre-Jean
    Foulonneau, Alban
    Thomas, Jean-Baptiste
    George, Sony
    Bigue, Laurent
    [J]. PLOS ONE, 2024, 19 (05):
  • [8] Advances on Exploration Indicators of Mineral VNIR-SWIR Spectroscopy and Chemistry: A Review
    Zhou, Yan
    Wang, Tiangang
    Fan, Feipeng
    Chen, Shizhong
    Guo, Weimin
    Xing, Guangfu
    Sun, Jiandong
    Xiao, Fan
    [J]. MINERALS, 2022, 12 (08)
  • [9] VNIR-SWIR reflectance spectroscopy as a nondestructive technique for compositional determination of archaeological talc samples with a machine learning approach
    Ferrer-Julia, M.
    Quiros, A.
    Herrero-Alonso, D.
    Gonzalez, E.
    Garcia-Melendez, E.
    [J]. ARCHAEOLOGICAL AND ANTHROPOLOGICAL SCIENCES, 2024, 16 (07)
  • [10] Porosity, strength, and alteration - Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy
    Kereszturi, Gabor
    Heap, Michael
    Schaefer, Lauren N.
    Darmawan, Herlan
    Deegan, Frances M.
    Kennedy, Ben
    Komorowski, Jean-Christophe
    Mead, Stuart
    Rosas-Carbajal, Marina
    Ryan, Amy
    Troll, Valentin R.
    Villeneuve, Marlene
    Walter, Thomas R.
    [J]. EARTH AND PLANETARY SCIENCE LETTERS, 2023, 602