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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: 30 April 2018

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 1800 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 (4 papers)

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Research

Open AccessArticle Impacts on the Urban Environment: Land Cover Change Trajectories and Landscape Fragmentation in Post-War Western Area, Sierra Leone
Remote Sens. 2018, 10(1), 129; doi:10.3390/rs10010129
Received: 25 October 2017 / Revised: 3 January 2018 / Accepted: 5 January 2018 / Published: 19 January 2018
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Abstract
An influential underlying driver of human-induced landscape change is civil war and other forms of conflict that cause human displacement. Internally displaced persons (IDPs) increase environmental pressures at their destination locations while reducing them at their origins. This increased pressure presents an environment
[...] Read more.
An influential underlying driver of human-induced landscape change is civil war and other forms of conflict that cause human displacement. Internally displaced persons (IDPs) increase environmental pressures at their destination locations while reducing them at their origins. This increased pressure presents an environment for increased land cover change (LCC) rates and landscape fragmentation. To test whether this hypothesis is correct, this research sought to understand LCC dynamics in the Western Area of Sierra Leone from 1976 to 2011, a period including pre-conflict, conflict, and post-conflict eras, using Landsat and SPOT satellite imagery. A trajectory analysis of classified images compared LCC trajectories before and during the war (1976–2000) with after the war (2003–2011). Over the 35-year period, the built-up land class rapidly increased, in parallel with an increase in urban and peri-urban agriculture. During the war, urban and peri-urban agriculture became a major livelihood activity for displaced rural residents to make the region food self-sufficient, especially when the war destabilised food production activities. The reluctance of IDPs to return to their rural homes after the war caused an increased demand for land driven by housing needs. Meanwhile, protected forest and other forest declined. A significant finding to emerge from this research is that landscape fragmentation increased in conjunction with declining forest cover while built-up areas aggregated. This has important implications for the region’s flora, fauna, and human populations given that other research has shown that landscape fragmentation affects the landscape’s ability to provide important ecosystem services. Full article
(This article belongs to the Special Issue Remote Sensing of Urban Agriculture and Land Cover)
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Figure 1

Open AccessArticle Urban Imperviousness Effects on Summer Surface Temperatures Nearby Residential Buildings in Different Urban Zones of Parma
Remote Sens. 2018, 10(1), 26; doi:10.3390/rs10010026
Received: 25 October 2017 / Revised: 14 December 2017 / Accepted: 21 December 2017 / Published: 24 December 2017
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Abstract
Rapid and unplanned urban growth is responsible for the continuous conversion of green or generally natural spaces into artificial surfaces. The high degree of imperviousness modifies the urban microclimate and no studies have quantified its influence on the surface temperature (ST) nearby residential
[...] Read more.
Rapid and unplanned urban growth is responsible for the continuous conversion of green or generally natural spaces into artificial surfaces. The high degree of imperviousness modifies the urban microclimate and no studies have quantified its influence on the surface temperature (ST) nearby residential building. This topic represents the aim of this study carried out during summer in different urban zones (densely urbanized or park/rural areas) of Parma (Northern Italy). Daytime and nighttime ASTER images, the local urban cartography and the Italian imperviousness databases were used. A reproducible/replicable framework was implemented named “Building Thermal Functional Area” (BTFA) useful to lead building-proxy thermal analyses by using remote sensing data. For each residential building (n = 8898), the BTFA was assessed and the correspondent ASTER-LST value (ST_BTFA) and the imperviousness density were calculated. Both daytime and nighttime ST_BTFA significantly (p < 0.001) increased when high levels of imperviousness density surrounded the residential buildings. These relationships were mostly consistent during daytime and in densely urbanized areas. ST_BTFA differences between urban and park/rural areas were higher during nighttime (above 1 °C) than daytime (about 0.5 °C). These results could help to identify “urban thermal Hot-Spots” that would benefit most from mitigation actions. Full article
(This article belongs to the Special Issue Remote Sensing of Urban Agriculture and Land Cover)
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Open AccessArticle Urban Sprawl and Adverse Impacts on Agricultural Land: A Case Study on Hyderabad, India
Remote Sens. 2017, 9(11), 1136; doi:10.3390/rs9111136
Received: 19 September 2017 / Revised: 2 November 2017 / Accepted: 3 November 2017 / Published: 7 November 2017
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Abstract
Many Indian capitals are rapidly becoming megacities due to industrialization and rural–urban emigration. Land use within city boundaries has changed dynamically, accommodating development while replacing traditional land-use patterns. Using Landsat-8 and IRS-P6 data, this study investigated land-use changes in urban and peri-urban Hyderabad
[...] Read more.
Many Indian capitals are rapidly becoming megacities due to industrialization and rural–urban emigration. Land use within city boundaries has changed dynamically, accommodating development while replacing traditional land-use patterns. Using Landsat-8 and IRS-P6 data, this study investigated land-use changes in urban and peri-urban Hyderabad and their influence on land-use and land-cover. Advanced methods, such as spectral matching techniques with ground information were deployed in the analysis. From 2005 to 2016, the wastewater-irrigated area adjacent to the Musi river increased from 15,553 to 20,573 hectares, with concurrent expansion of the city boundaries from 38,863 to 80,111 hectares. Opportunistic shifts in land-use, especially related to wastewater-irrigated agriculture, emerged in response to growing demand for fresh vegetables and urban livestock feed, and to easy access to markets due to the city’s expansion. Validation performed on the land-use maps developed revealed 80–85% accuracy. Full article
(This article belongs to the Special Issue Remote Sensing of Urban Agriculture and Land Cover)
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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
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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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