Advances in Detecting and Understanding Land Surface Phenology

Dear Colleagues,

Land surface phenology (LSP) quantifies the seasonal dynamics of vegetated land surfaces in satellite pixels using remote sensing data. As phenological variations have strong impacts on ecosystems (e.g., productivity, carbon and water cycles, and interactions among species) and human health (e.g., allergenic pollen exposure), LSP has been largely investigated at local to global scales in recent decades. Unlike ground-observed species-specific phenology, LSP varies with both climate changes (e.g., temperature, precipitation, and photoperiod) and land surface changes caused by natural disturbances (e.g., wildfires, weather extremes, and species invasion) and human activities (urbanization, deforestation, and crop rotation). Moreover, the scaling effect arising from the heterogeneity of the landscape impedes cross-scale matching and ground-based validation of LSP. Recently, the development of new satellite sensors (e.g., Sentinel, PlanetScope), data fusion techniques, and LSP retrieval algorithms has advanced LSP detection at finer resolutions and improved the understanding of the scaling effect and LSP dynamics corresponding to both climate changes and land surface changes across ecosystems. In addition, efforts have been made to apply LSP to map vegetation (e.g., crop) types and to monitor LSP in near-real time which could support agriculture management such as irrigation and fertilization schedules and yield prediction. Thus, this Special Issue aims to collect studies that address the latest developments in the detection, understanding, and application of LSP. Specifically, we are inviting submissions on topics including, but not limited to:

• New algorithms and remote sensors for LSP detection;
• Multi-sensor data fusion techniques for LSP detection;
• LSP dynamics responding to climate and land surface changes;
• Spatial patterns and drivers of LSP variations across spatial scales;
• Ground-based validation and cross-scale comparisons of LSP;
• Near-real-time monitoring of LSP and its applications (e.g., agriculture and forestry management).

Dr. Jianmin Wang
Dr. Xiaoyang Zhang
Guest Editors

Manuscript Submission Information

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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.

• land surface phenology
• climate change
• land use and land cover change
• scaling effect
• data fusion
• near-real-time monitoring