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Special Issue "Remote Sensing of Urban Agriculture and Land Cover"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: 25 October 2017

Special Issue Editors

Guest Editor
Prof. Dr. James Campbell

Geography Department, 220 Stanger Street, 115 Major Williams Hall, Virginia Tech, Blacksburg, VA 24061, USA
Website | E-Mail
Phone: 540.231.5841
Interests: agricultural systems (crop rotation, tillage assessment, yield estimation); soil variability; land use/land cover change; coastal reclamation; urban systems (microclimates, impervious surfaces, drainage)
Co-Guest Editor
Dr. Tammy Parece

Department of Social and Behavioral Sciences Lowell Heiny Hall (LHH 409), Colorado Mesa University, 1100 North Avenue, Grand Junction, Colorado 81501, USA
Website | E-Mail
Interests: urban agriculture; urban ecosystems; geography education; spatial analysis of urban landscapes changes; urban impacts on natural environments; geospatial technology education

Special Issue Information

Dear Colleagues,

Worldwide, as cities grow, both in area and in population, they encounter challenges that inhibit efficient administration and planning. Urbanization is characterized by complex mixtures of physical structures with fragments of open land that together form the fabric of the urban landscape. Such systems vary greatly with respect to scale, distance, and time, forming dynamic patterns that challenge conventional strategies for mapping, inventory, and analysis. Therefore, city governments are challenged to acquire accurate and timely data that permit assessment of needs for supporting urban infrastructure and the city’s population.

Urban agriculture has become increasingly significant in advancing the health, social fabric, and environments of urban neighborhoods. While remote sensing, in its many forms, provides one of the most effective tools for mapping, monitoring and analyzing the urban landscape to understand the nature and behavior of urban systems, its application in evaluating the potential of urban agriculture and similar land uses are limited. Remote sensing offers the capability to examine urban agriculture over time and space, and to inform our understanding of its role in supporting urban systems. Current advances in technologies and analytical strategies provide opportunities to advance our understanding of urban systems.

This Special Issue will focus upon research that investigates applications of remote sensing analysis to better understand the character and dynamic behavior of urban ecosystems. Specifically, this Special Issue focuses upon applications of remote sensing for analysis of topics such as urban agriculture, urban land use, and urban ecology. We encourage submission of original research that examines temporal dimensions of the urban landscape, applies ecological perspectives, or seeks to connect social/economic dimensions with observed landscape change.

The editors seek original manuscripts that investigate, review, and synthesize recent research focusing upon urban agriculture and urban land use employing the full range of remote sensing technologies and analytical techniques.

Contributions may include, but are not limited to:

Urban land cover/land use change
Urban agriculture
Thermal behavior of urban landscapes
Phenology of urban landscapes
Urban hydrology
Green infrastructure
Reclamation of abandoned/degraded urban lands

Dr. James Campbell
Dr. Tammy Parece
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 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 monthly 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 1600 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.

Published Papers (1 paper)

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Research

Open AccessArticle A Modified Multi-Source Parallel Model for Estimating Urban Surface Evapotranspiration Based on ASTER Thermal Infrared Data
Remote Sens. 2017, 9(10), 1029; doi:10.3390/rs9101029
Received: 24 August 2017 / Revised: 29 September 2017 / Accepted: 2 October 2017 / Published: 7 October 2017
PDF Full-text (16310 KB) | HTML Full-text | XML Full-text
Abstract
To date, little attention has been given to remote sensing-based algorithms for inferring urban surface evapotranspiration. A multi-source parallel model based on ASTER data was one of the first examples, but its accuracy can be improved. We therefore present a modified multi-source parallel
[...] Read more.
To date, little attention has been given to remote sensing-based algorithms for inferring urban surface evapotranspiration. A multi-source parallel model based on ASTER data was one of the first examples, but its accuracy can be improved. We therefore present a modified multi-source parallel model in this study, which has made improvements in parameterization and model accuracy. The new features of our modified model are: (1) a characterization of spectrally heterogeneous urban impervious surfaces using two endmembers (high- and low-albedo urban impervious surface), instead of a single endmember, in linear spectral mixture analysis; (2) inclusion of an algorithm for deriving roughness length for each land surface component in order to better approximate to the actual land surface characteristic; and (3) a novel algorithm for calculating the component net radiant flux with a full consideration of the fraction and the characteristics of each land surface component. HJ-1 and ASTER data from the Chinese city of Hefei were used to test our model’s result with the China–ASEAN ET product. The sensitivity of the model to vegetation and soil fractions was analyzed and the applicability of the model was tested in another built-up area in the central Chinese city of Wuhan. We conclude that our modified model outperforms the initial multi-source parallel model in accuracy. It can obtain the highest accuracy when applied to vegetation-dominated (vegetation proportion > 50%) areas. Sensitivity analysis shows that vegetation and soil fractions are two important parameters that can affect the ET estimation. Our model is applicable to estimate evapotranspiration in other urban areas. Full article
(This article belongs to the Special Issue Remote Sensing of Urban Agriculture and Land Cover)
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