Special Issue "Remote Sensing of Plant-Climate Interactions"
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 9830
Interests: remote sensing; plant ecophysiology; agriculture, forestry; plant phenotyping; spectroscopy and imaging spectroscopy; UAVs; machine learning; data fusion; data processing
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The remote sensing dynamic processes related to the plant–climate interactions, such as evapotranspiration (ET) and studies on the interface of plants and the atmosphere, including climate change impacts on plant physiological processes (heat, water stress, plant biogenic volatile emissions), are key to understanding the water balance, energy budget, feedback mechanisms, and productivity of the vegetation land surface moving forward. Improving accuracy in assessing these dynamic processes has implications for water management in precision agriculture practices, impact mitigation of extreme events, agricultural management practices, as well as larger-scale modeling of the Earth’s climate and weather owing to its impact on land surface–atmosphere interactions and soil water content. For example, remote sensing has enabled estimation of ET on a global scale at high space–time resolution. Various ET estimation techniques have also been developed for remote sensing products, but the accuracy of these algorithms varies with land cover, hydroclimate, terrain, seasonality, and the space and time scale of remote sensing data. Additionally, calibration and validation of these algorithms remains a challenge because of (1) the limited availability of ground-based calibration and validation data, (2) space–time scale discrepancy between footprints of available ground-based measurements techniques like eddy covariance towers, lysimeter methods, scintillometer methods, and remote sensing data, and (3) scale discrepancy between various inputs of ET and water and heat stress estimation algorithms and remote sensing data.
This Special Issue invites studies focused on improving estimates of all plant–climate interface interactions, including but not limited to evapotranspiration and other assessments of water and heat stress from remote sensing platforms (satellite, UAV, or proximal sensing) under varying hydroclimates and land-cover conditions. We especially encourage studies that (1) provide guidelines for improved parameterizations of different existing algorithms for remote sensing data under different hydroclimates, seasons, and land cover conditions, (2) use advanced techniques like machine learning, data assimilation, data fusion for utilizing various sources of ground-based data or multiple remote sensing platforms for estimating, calibrating, and validating remote sensing data and (3) assess the accuracy of different plant–climate interface algorithms with varying space–time scale remote sensing inputs. Multimodel comparisons and feedback mechanisms under different land-use land cover, seasons, and hydroclimates are also encouraged.
- Studies exploring the efficacy of different remote sensing-based products to compute water use efficiency and their comparison with water use efficiency products from platforms like ECOSTRESS are particularly invited;
- Monitoring and modeling agroclimatic interactions with cultivars at different scales, including applications in high throughput plant phenotyping and precision agriculture;
- Novel developments in software, sensors, platforms or methods towards assessing climate change impacts using different remote sensing approaches;
- Advances in image segmentation and classification for the study of specific traits related to plant–climate interactions and the soil–plant–atmosphere continuum;
- Integration of different scales of remote sensing measurements (e.g. satellite, UAV, ground-based measurements) towards further understanding scaling dynamics related to plant–climate interactions;
- Comparisons of long-term vegetation activity based on remote sensing data and field-based measurements (permanent plots, eddy covariance, tree-ring parameters);
- Remote sensing based smart apps for irrigation scheduling, phenotyping, and plant stress monitoring and their evolving role in a scenario of increased frequency of extreme events like flash droughts and floods.
Dr. Shawn C. Kefauver
Dr. Nandita Gaur
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.
- Plant ecophysiology
- Crop and soil science
- Agroforestry productivity
- Climate change
- Biogenic volatile organic compounds (BVOCs)
- High throughput plant phenotyping
- Precision agriculture
- Unmanned aerial vehicles (UAVs)
- Satellite remote sensing
- Proximal imaging
- Image data fusion
- Smart apps