TY - CHAP
T1 - Key issues in incorporating proximal and remote sensor data into farm decision-making
AU - Simões, Manuela
AU - Sousa, Adélia M. O.
AU - Silva, José R. Marques da
AU - Serrano, João
AU - Shahidian, Shakib
AU - Silveira, Duarte Lobo da
AU - Gonçalves, Ana Cristina
AU - Caldinhas, Maria João P.
AU - Cruz, Vasco Fitas da
AU - Júnior, Arilson J. de Oliveira
AU - Souza, Silvia R. Lucas de
AU - Coelho, Diogo R.
AU - Lourenço, Patrícia
AU - Baptista, Fátima F.
N1 - info:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F05183%2F2020/PT#
Funding information:
Funding: This work was funded by National Funds through FCT (Foundation for Science and Technology) under the Project UIDB/05183/2020.
© Burleigh Dodds Science Publishing Limited, 2024. All rights reserved.
PY - 2024/4/23
Y1 - 2024/4/23
N2 - This chapter presents five study cases on the application of smart technologies in farming and forestry systems. The first of these study cases presents the results of a long-term study to calibrate a Grassmaster II capacitance probe to estimate pasture productivity in the Mediterranean Montado ecosystem. The second case study presents a methodology for identifying yield zones within an olive grove based on Sentinel-2 satellite data. The third case study provides an overview of different remote sensing sensors, data and methodologies used for estimating forest biomass. The fourth case study assesses the carbon footprint of horticultural crops such as potato, onion, carrot, melon and watermelon. The final case study focuses on precision livestock farming, specifically a mobile application focused on thermal comfort.
AB - This chapter presents five study cases on the application of smart technologies in farming and forestry systems. The first of these study cases presents the results of a long-term study to calibrate a Grassmaster II capacitance probe to estimate pasture productivity in the Mediterranean Montado ecosystem. The second case study presents a methodology for identifying yield zones within an olive grove based on Sentinel-2 satellite data. The third case study provides an overview of different remote sensing sensors, data and methodologies used for estimating forest biomass. The fourth case study assesses the carbon footprint of horticultural crops such as potato, onion, carrot, melon and watermelon. The final case study focuses on precision livestock farming, specifically a mobile application focused on thermal comfort.
U2 - http://dx.doi.org/10.19103/AS.2023.0132.04
DO - http://dx.doi.org/10.19103/AS.2023.0132.04
M3 - Chapter
SN - 978 1 80146 382 9
SP - 39
EP - 74
BT - Smart farms
A2 - Sorensen, Claus Gron
PB - Burleigh Dodds Science Publishing, Cambridge, UK
CY - Cambridge, UK
ER -