Remote Sensing for Crop Mapping

Dear Colleagues,

In the last few decades, the advent of remote sensing (e.g., satellite and drones) has made it possible to assess and monitor the extent and status of cultivated land. Remote-sensing technologies are desirable because they have relatively low marginal cost; they provide higher levels of spatial resolution and sampling frequency compared to alternate approaches; are the only feasible data gathering mechanism in some locations with difficult or even no access; provide precise, automated repetition of data collection efforts; and can be combined with ground-based data collection to generate value-added products. Satellite imagery combined with ground-based data and spatial mapping tools can make an enormous difference to agricultural decision making at global, national, and local levels, by providing more timely and accurate information. Moreover, crop-type information is a critical input to cropping system models or integrated assessment models. To better understand our agroecosystem and guide policy making with these modeling tools, spatially explicit and detailed crop type maps are increasingly needed.

Furthermore, official datasets are becoming increasingly accessible. In particular, there have been many exciting activities in the last 5 years, and more and more national, regional, and global crop type datasets are being generated and shared. OneSoil, a startup in Minsk, Belarus, launches an interactive digital map of ag data including about 60 million fields across Europe and the United States, and data on more than 20 types of crops collected over the last three years (https://map.onesoil.ai/2018). Advances in remote sensing and the sen4agri project (http://www.esa-sen2agri.org/) have built a toolbox to map crop types using machine learnings (random forest) to classify Sentinel 2 images. More recent approaches also use radar data, e.g., from Sentinel 1, to classify crops. The proposed Special Issue will leverage these promising developments to share the latest methodological development of crop type mapping, particularly object/instance-based crop identification and agricultural productivity in complex, smallholder farming regions in the world. Articles covering but not limited to recent research on the following topics are invited to this Special Issues:

• Crop type/cropland mapping methods and algorithms;
• Mapping intercropping in smallholder farming systems;
• Mapping tree crops or specialty crops (avocado, coffee, and cocoa);
• Crop field size mapping/crop field boundary detection;
• Mapping and characterization of management practices in various cropping systems (crop rotation, intensity, tillage, etc.);
• Crop yield mapping and monitoring;
• Multi-source data fusion (satellite, census data, surveys, and local knowledge) for agricultural applications;
• Agricultural land use change analysis.

Dr. Steffen Fritz
Dr. Qiong Hu
Dr. Zhenong Jin
Dr. Wenbin Wu
Dr. Liangzhi You
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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.