Special Issue "Remote Sensing for Crop Mapping"
Deadline for manuscript submissions: 1 May 2021.
Interests: remote sensing, cropland, crowdsourcing, mapping uncertainty, climate change, agricultural monitoring
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Interests: agricultural production system, climate change, crop yield mapping, crop model, precision nitrogen management, ecosystem service
Interests: smart agriculture, agricultural system, crop mapping, climate change
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Interests: farming system, remote sensing, land use change, spatial analysis, food policy, cropping system
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. Qiong Hu
Dr. Zhenong Jin
Dr. Wenbin Wu
Dr. Liangzhi You
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 papers will be 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 2200 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.
- remote sensing
- crop mapping
- crop types
- field size
- farming system
- land use change
- spatial analysis
- smallholder agriculture