Disentangling the numbers behind agriculture-driven tropical deforestation

F Pendrill, TA Gardner, P Meyfroidt, UM Persson… - Science, 2022 - science.org
Tropical deforestation continues at alarming rates with profound impacts on ecosystems,
climate, and livelihoods, prompting renewed commitments to halt its continuation. Although it …

[HTML][HTML] Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review

CM Viana, D Freire, P Abrantes, J Rocha… - Science of the total …, 2022 - Elsevier
Agriculture provides the largest share of food supplies and ensures a critical number of
ecosystem services (eg, food provisioning). Therefore, agriculture is vital for food security …

Mapping global lake dynamics reveals the emerging roles of small lakes

X Pi, Q Luo, L Feng, Y Xu, J Tang, X Liang, E Ma… - Nature …, 2022 - nature.com
Lakes are important natural resources and carbon gas emitters and are undergoing rapid
changes worldwide in response to climate change and human activities. A detailed global …

The digital and sustainable transition of the agri-food sector

S Abbate, P Centobelli, R Cerchione - Technological Forecasting and …, 2023 - Elsevier
According to recent trends, food production must double by 2050 to meet the world's
growing population's expected demand. To achieve this goal, agri-food companies have …

Applications of remote sensing in precision agriculture: A review

RP Sishodia, RL Ray, SK Singh - Remote sensing, 2020 - mdpi.com
Agriculture provides for the most basic needs of humankind: food and fiber. The introduction
of new farming techniques in the past century (eg, during the Green Revolution) has helped …

Technological revolutions in smart farming: Current trends, challenges & future directions

V Sharma, AK Tripathi, H Mittal - Computers and Electronics in Agriculture, 2022 - Elsevier
With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …

A review of ensemble learning algorithms used in remote sensing applications

Y Zhang, J Liu, W Shen - Applied Sciences, 2022 - mdpi.com
Machine learning algorithms are increasingly used in various remote sensing applications
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …

Recent advances of hyperspectral imaging technology and applications in agriculture

B Lu, PD Dao, J Liu, Y He, J Shang - Remote Sensing, 2020 - mdpi.com
Remote sensing is a useful tool for monitoring spatio-temporal variations of crop
morphological and physiological status and supporting practices in precision farming. In …

Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects

J Wang, M Bretz, MAA Dewan, MA Delavar - Science of The Total …, 2022 - Elsevier
Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …

[HTML][HTML] Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

K Berger, M Machwitz, M Kycko, SC Kefauver… - Remote sensing of …, 2022 - Elsevier
Remote detection and monitoring of the vegetation responses to stress became relevant for
sustainable agriculture. Ongoing developments in optical remote sensing technologies have …