MORERA: Latest Earth Observation system to translate Big Data to agriculture

被引:1
|
作者
Alvaro, Angel [1 ]
Sobrino, Jose [2 ]
Mira, Concepcion [3 ]
Gonzalez-Dugo, Victoria [4 ]
Belenguer, Tomas [5 ]
Cifuentes, Andres [6 ]
Moreno, Javier [7 ]
机构
[1] Thales Alenia Space, 7 PTM, Madrid 28760, Spain
[2] Univ Valencia, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain
[3] TEPRO, Avda San Francisco Javier 24,3a Planta, Seville 41018, Spain
[4] IAS CSIC, C Alameda Obispo S-N, Cordoba 14004, Spain
[5] INTA, Carretera Ajalvir,KM 4, Madrid 28850, Spain
[6] ASE Opt, Carrer Cerdanya 44, El Prat De Llobregat 08820, Barcelona, Spain
[7] LIDAX, C Antonio Alonso Martin 1, Madrid 28860, Spain
来源
REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XXIII | 2021年 / 11856卷
关键词
Earth Observation; software-defined; evapotranspiration; Freeform; cubesat; catadioptric; telecentric; Artificial Intelligence; Machine learning; Big data; Agriculture; efficient irrigation;
D O I
10.1117/12.2596842
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
The MORERA program has recently been selected as one of the "Missions Science and Innovation" from the Spanish CDTI, an innovative program targeting solutions for deep social problems through innovation. The main Spanish industry is Agriculture (11% GDP), but this sector is threatened by climate change, as 34% of the Spanish irrigated surface is considered out of balance. Difficulty of providing useful and fully processed information to the end-users for supporting their decisions severely affect the optimization of the resources. Well informed decisions optimize resources and costs, maximizing productivity. To solve this problem, MORERA involves in a unique project the complete value chain, from sensor to user, thanks to a solid consortium, and it is based on three pillars: Final personalized irrigation requirements that will be directly provided to the user using a mobile device. Artificial intelligence techniques will be used to combine all relevant data to build a final watering recommendation. A compact and highly specific freeform optical instrument will be used to estimate evapotranspiration data at farm level with required TIR bandwidth and spatial resolution. Since no present instrument fulfills these requirements, it will be developed in the framework of the project. The MORERA concept can be extrapolated to many remote sensing applications, and to take advantage of this, it has been conceived as a modular system, where each module may be adapted with minor impact. This first system is focused on providing precise irrigation and fertilization recommendations, as well as self-learning yield estimations.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] The Big Data Processing Platform for Intelligent Agriculture
    Huang, Jintao
    Zhang, Lichen
    GREEN ENERGY AND SUSTAINABLE DEVELOPMENT I, 2017, 1864
  • [22] Visualisation of Big Data in Agriculture and Rural Development
    Jedlicka, Karel
    Charvat, Karel
    2018 IST-AFRICA WEEK CONFERENCE (IST-AFRICA), 2018,
  • [23] Towards a training data model for artificial intelligence in earth observation
    Yue, Peng
    Shangguan, Boyi
    Hu, Lei
    Jiang, Liangcun
    Zhang, Chenxiao
    Cao, Zhipeng
    Pan, Yinyin
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2022, 36 (11) : 2113 - 2137
  • [24] CANDELA: A CLOUD PLATFORM FOR COPERNICUS EARTH OBSERVATION DATA ANALYTICS
    Rolland, Jean-Francois
    Castel, Fabien
    Haugommard, Anne
    Aubrun, Michelle
    Yao, Wei
    Dumitru, Corneliu Octavian
    Datcu, Mihai
    Bylicki, Michal
    Tran, Ba-Huy
    Aussenac-Gillles, Nathalie
    Comparot, Catherine
    Trojahn, Cassia
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 3104 - 3107
  • [25] BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Machine learning and data mining advance predictive big data analysis in precision animal agriculture
    Morota, Gota
    Ventura, Ricardo V.
    Silva, Fabyano F.
    Koyama, Masanori
    Fernando, Samodha C.
    JOURNAL OF ANIMAL SCIENCE, 2018, 96 (04) : 1540 - 1550
  • [26] Earth observation satellite data receiving, processing system and data sharing
    Guo, Huadong
    Liu, Jianbo
    Li, An
    Zhang, Jianguo
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2012, 5 (03) : 241 - 250
  • [27] EARTH OBSERVATION RETRIEVAL AND CLASSIFICATION ALGORITHMS FOR AGRICULTURE
    Mattia, Francesco
    Balenzano, Anna
    Satalino, Giuseppe
    Lovergine, Francesco
    Palmisano, Davide
    Nutini, Francesco
    Boschetti, Mirco
    Verza, Giorgia
    Rinaldi, Michele
    Ruggieri, Sergio
    Pio De Santis, Angelo
    Ciavarella, Francesco
    Paredes Gomez, Vanessa
    Nafria Garcia, David Alfonso
    Tapete, Deodato
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 1428 - 1431
  • [28] Examining the Impact of Incorporating Big Data Analytics in Agriculture
    Thandekkattu, Salu George
    Vajjhala, Narasimha Rao
    Dzarma, Hyelda
    ADVANCES IN INFORMATION COMMUNICATION TECHNOLOGY AND COMPUTING, AICTC 2021, 2022, 392 : 47 - 54
  • [29] A comparative study of big data use in Egyptian agriculture
    Sayed A. Sayed
    Amira S. Mahmoud
    Eslam Farg
    Amany M. Mohamed
    Ahmed M. Saleh
    Mohamed A. E. AbdelRahman
    Marwa Moustafa
    Hisham M. AbdelSalam
    Sayed M. Arafat
    Journal of Electrical Systems and Information Technology, 10 (1)
  • [30] Earth observation and geospatial big data management and engagement of stakeholders in Hungary to support the SDGs
    Mihaly, Szabolcs
    Remetey-Fulopp, Gabor
    Kristof, Daniel
    Czinkoczky, Anna
    Palya, Tamas
    Pasztor, Laszlo
    Rudan, Pal
    Szabo, Gyorgy
    Zentai, Laszlo
    BIG EARTH DATA, 2021, 5 (03) : 306 - 351