Agriculture: Management, Disturbance, and Climate around the World Using the Google Earth Engine

Dear Colleagues,

Cloud computing has become increasingly useful in the remote sensing field because the number and size of publicly available datasets is dramatically increasing, which necessitates an enormous amount of disc storage and processing power to perform analysis. Increasingly, the Google Earth Engine (GEE) is being used to develop new data analysis methods and generate striking results that may otherwise not be possible. The use of GEE in research continues to advance science and helps us to test important hypotheses and address long-standing debates/issues.

The role of human activity and management in land use, land cover change, and agriculture has also become increasingly important in understanding how our natural world responds to the interaction of climate variability and management decisions. Given the emergence of a global economy and the rapid and anthropogenic-driven change in the composition of Earth’s atmosphere, ecosystems and agriculture are increasingly viewed as systems tightly coupled with human society. Natural systems are now often strongly coupled with social dynamics rather than being extraneous processes. A new focus has emerged to better understand not only why and how agricultural productivity and systems change, but what role human activity and management play in these socioecological systems in the context of climate change.

Remote sensing technology has recently advanced very rapidly. High spatial and temporal resolution optical, microwave, and infrared data from satellite and unmanned aerial vehicles (UAVs) are becoming more common and freely accessible. In addition to the traditional vegetation indices derived from optical data, we now have additional information on vegetation cover and canopy structure from lidar measurements, information on plant function with solar-induced chlorophyll fluorescence (SIF) retrievals, and canopy temperature from thermal infrared imaging. Multisensor and multisource data analysis has become easier to perform in cloud computing platforms such as GEE.

Here, we solicit manuscripts on the use of GEE and remote sensing data to address important topics in agriculture. Preference will be given to studies that consider the role of human activity, policy, and/or economics in agriculture; utilize multiple sensors; investigate climate, drought, disturbance, or atmosphere feedbacks on agricultural productivity or the carbon, water, and nutrient cycles; or apply lidar or SIF data in novel ways.

Potential agriculture-related topics for this Special Issue include but are not limited to:

• Satellite, UAV, eddy covariance, and in situ remote sensing;
• Human activity and management;
• Natural and human disturbances;
• Mapping or modeling changes in agricultural lands over space and time;
• Estimating and/or projecting productivity;
• Drivers of changes in agricultural lands and/or productivity;
• Feedbacks between changes in agriculture and the carbon, water, and nutrient cycles;
• Drought and flash drought;
• Climate change and variability;
• Multisensor and multisource data analysis;
• Solar-induced chlorophyll fluorescence;
• Lidar;
• Sustainability.

Dr. Russell Doughty
Dr. Rajen Bajgain
Dr. Jie Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Agricultural management and yield
• Socioecological and human systems
• Vegetation dynamics
• Photosynthesis, respiration, and net carbon exchange
• Carbon, water, and nutrient cycles
• Plantations
• Productivity
• Livestock
• Optical, lidar, and chlorophyll fluorescence remote sensing
• Climate variability
• Disturbance