Special Issue "Remotely Sensed Data and Climate Resilience"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 25 February 2021.

Special Issue Editor

Dr. Matteo Zampieri
Website
Guest Editor
European Commission, Joint Research Centre, Ispra, Italy
Interests: meteorology; climate change; land surface processes; resilience; food security; ecosystem services

Special Issue Information

Dear Colleagues,

I kindly invite you to submit a contribution to this Special Issue on “Remotely Sensed Data and Climate Resilience” in the journal Remote Sensing.

Climate change is one of the greatest challenges facing both society and natural ecosystems. It affects all socio-economic sectors and all populations, though the most severe effects are felt by poor and vulnerable communities. These are strongly reliant on agriculture and broader ecosystem services, yet have the least capacity to deal with the impacts of climate change and have the most limited access to climate change adaptation measures and strategies.

Assessing climate resilience of both natural and anthropic systems requires good-quality data and information, along with analytical tools and capacity, yet these are often lacking in many developing regions of the world.

Remotely sensed data has the capability to capture accurate, calibrated measurements with which to document, monitor, and describe various environmental attributes over a range of spatial and temporal resolutions.

 

This Special Issue focuses on the use of remotely sensed data to:

  1. Identify the vulnerability and assess the resilience of society, agricultural systems, and natural (terrestrial and marine) ecosystems to climate variability and extremes, either directly or by measuring variables related to resilience (habitat diversity and changes, temperature, biomass, water availability over land, etc.) at all scales, from global to local;
  2. Safeguard natural and anthropic systems by diagnosing the changes of resilience associated to slowly varying parameters such as land cover type, temperature, CO2, land surface water resources, sea ice, etc.;
  3. Generate knowledge targeted at supporting climate-resilient policy decisions and strategies for climate change adaptation, especially in regions where the capacity to generate scientific evidence for policymaking is scarce.

This Special Issue welcomes review papers, short communications on highly relevant emerging topics, and research articles analyzing remote sensing data such as from the European Space Agency's Climate Change Initiative and its dedicated instruments, such as Soil Moisture Ocean Salinity and the Copernicus Programme's satellites and services, also in concert with other climate and socio-economic data.

Manuscripts led by young scientists (under 35) can compete for the Remote Sensing & Resilience Grant by sending a pre-submission inquiry to the Guest Editor, who will share it with the Remote Sensing Editorial Office. The three best papers that are accepted for publication in this Special Issue will be granted free publication and open access. Winners will also be recognized in the Special Issue’s editorial.

Dr. Matteo Zampieri
Guest Editor

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.

Keywords

  • remote sensing
  • climate change
  • climate extremes
  • climate adaptation
  • NDVI
  • gross primary production
  • water resources
  • land-use change
  • resilience
  • sustainability
  • poverty and inequality

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Five Distinct Agricultural Cropland Products of South Asia for Food and Water Security Assessments and Management Derived using MODIS 250m Data
Authors: Murali Krishna Gumma
Affiliation: ICRISAT-IN, Hyderabad, India
Abstract: The Spatial distribution of cropland extents and crop intensity plays a significant role in sustainable agriculture development. Rapidly growing population puts enormous pressure on both the agriculture sector and the natural resources to meet present and future demand for food and nutritional security, especially in the South Asia region. The overarching goal of this research is to map the possible accurate major croplands based on Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data for South Asia by applying spectral matching techniques (SMTs) using rich and extensive gathered ground data. Four cropland products were produced for South Asia with this study: 1. crop extent: total agricultural area, 2) crop watering methods: irrigated versus rainfed, 3) cropping intensity: single, double and triple/continuous crops and 4) crop type: major crop types and others. Every 16-day MODIS 250 meter Normalized Difference Vegetation Index (NDVI) time-series data for one year (June 2014-May 2015) was classified with SMTs algorithms using an extensive set of ground data and interpreted high-resolution data. Accuracy assessments were calculated for cropland extent, crop intensity, crop watering methods crop type and overall classification accuracy using independent ground survey data. The overall classification accuracy was 76.59 percent, crop intensity was 85.32 percent, crop watering methods were 79.16 percent and croplands were 93.71 percent. These products were in close agreement with available National and sub-national level statistics. The above spatial information will help the decision-makers and policymakers about crops and their suitability in sustainable intensification of short duration legumes.

Title: Agro-climate services for resilient agriculture production: using the NDVI to forecast wheat phenological development on seasonal time scales
Authors: Ceglar, A.; Zampieri M; Weissteiner C. J.; Toreti A.; G. Ronchetti1
Affiliation: European Commission – Joint Research Centre, Ispra, Italy European Commission – Research Executive Agency, Bruxelles, Belgium
Abstract: Accurate simulation of the timing of sensitive crop phenological stages early enough in the growing season is of key importance to farmers to alleviate the impacts of unfavorable climate events on final crop yield, thereby increasing the resilience of crop production system. This study contributes to build the climate resilience in wheat production systems by developing a multi-level procedure to forecast in advance the wheat phenological development, focusing on the sensitive period between heading and flowering. The dynamic approach using phenological modeling and empirical procedure based on weather type prevalence are compared as two different methods to simulate phenological development. For this purpose, we evaluate the capability of the dynamic phenological model to simulate the dates of heading and flowering by using an independent NDVI dataset derived from remote sensing for validation. The timing of maximum NDVI is further used to improve the parameter values in dynamic phonological models. Seasonal re-forecasts for the period between 2000 and 2019 from COPERNICUS C3S are then used to drive both models for predicting the seasonal evolution of winter wheat phenological development. The predictability of phenological development is then discussed for both approaches and further insights are provided on the main climate drivers behind the interannual variability of the maximum NDVI occurrence. This study provides an important guideline on the development of agro-climate services that benefit from a seasonal climate forecast.

Title: Feedbacks of soil and vegetation and their role in compound hydro-meteorological events in Central Europe
Authors: Arianna Valmassoi; Jan D. Keller
Affiliation: University of Bonn, Germany
Abstract: Land-atmosphere coupling plays a key role in regulating and modulating atmospheric processes across multiple spatial and temporal scales. In this respect, self-intensification and self-propagation through the soil-atmosphere feedback are important processes for understanding the characteristics and variability of heatwaves and droughts. In this study, we investigate this relationship for Central Europe based on observational data. Previous studies found the relationship between soil moisture, potential evapotranspiration, and temperature to be crucial in quantifying the land-atmosphere feedback. We employ 20 years of high-resolution satellite observations from MODIS and ESA CCI for these parameters to investigate Spatio-temporal features of this feedback. Specifically, we examine the lag correlation between soil moisture and potential evapotranspiration, as well as the potential dependency on land use in order to identify hotspots in Central Europe where the coupling is a crucial part of the amplification or attenuation of heat waves and droughts. For these regions, the study includes a more in-depth analysis of the vegetation feedback under stress conditions during and after such a compound hydro-meteorological event.

Title: Heat stress risk evaluation from remotely sensed data and effect of crop diversity on the resilience of agricultural production.
Authors: Ceglar, A; Zampieri M.; Weissteiner C. J.; Toreti A.; G. Ronchetti
Affiliation: European Commission – Joint Research Centre, Ispra, Italy European Commission – Research Executive Agency, Bruxelles, Belgium
Abstract: Crops are especially sensitive to heat stress during flowering. This study employs a dataset of annual crop distribution in Europe derived by remotely sensed data. Observed surface temperature data is used to compute the frequency of heat events between heading and flowering for winter crops and at flowering for summer crops. The local share of the different crops is used to estimate the effects of crop diversity in reducing the risk of heat events at flowering, occurring at different times for the different years, and accounting for the annual variations of the crop distribution and flowering times as well.

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