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Special Issue "Remote Sensing in Support of Environmental Policy"

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 July 2011)

Special Issue Editor

Guest Editor
Dr. Audrey L. Mayer

Department of Social Sciences & School of Forest Resources and Environmental Sciences, Michigan Technological University, 209 AOB, Social Sciences 1400 Townsend Dr. Houghton, MI 49931, USA
Website | E-Mail
Phone: 906-487-3448
Interests: landscape ecology; land use land cover change; biodiversity assessment; biodiversity conservation; remote sensing for environmental policy; conservation policy; large scale impacts of individual decisions; sustainability science; sustainability assessment

Special Issue Information

Dear Colleagues,

Remotely sensed data are increasingly used (with varying success) for the monitoring and regulation of existing environmental policies, particularly those that occur at scales over which site visits are prohibitive. These policies govern deforestation and carbon balances, air and water pollution, urban sprawl and loss of agricultural land, and habitat destruction of threatened species, to name a few. As environmental degradation is made more visible and quantifiable, remote sensing data may also generate support for new policies. This issue will cover: the strengths and weaknesses of the existing use of remote sensing data in policy creation, implementation, evaluation, and enforcement; future advances in technology and applications; and unresolved issues including scale mismatch between available data and policy boundaries, legal implications (such as for private property rights), and the tenuous support for space programs that underpin all remote sensing efforts.

Dr. Audrey L. Mayer
Guest Editor

Keywords

  • carbon emissions
  • compliance
  • conservation
  • deforestation
  • environmental monitoring and assessment
  • environmental policy
  • law
  • pollution
  • regulation
  • remote sensing
  • satellite images
  • scale
  • space program

Published Papers (10 papers)

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Research

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Open AccessArticle An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data
Remote Sens. 2012, 4(2), 404-423; doi:10.3390/rs4020404
Received: 21 December 2011 / Revised: 17 January 2012 / Accepted: 17 January 2012 / Published: 2 February 2012
Cited by 7 | PDF Full-text (1365 KB) | HTML Full-text | XML Full-text
Abstract
In France, in the peri-urban context, urban sprawl dynamics are particularly strong with huge population growth as well as a land crisis. The increase and spreading of built-up areas from the city centre towards the periphery takes place to the detriment of natural
[...] Read more.
In France, in the peri-urban context, urban sprawl dynamics are particularly strong with huge population growth as well as a land crisis. The increase and spreading of built-up areas from the city centre towards the periphery takes place to the detriment of natural and agricultural spaces. The conversion of land with agricultural potential is all the more worrying as it is usually irreversible. The French Ministry of Agriculture therefore needs reliable and repeatable spatial-temporal methods to locate and quantify loss of land at both local and national scales. The main objective of this study was to design a repeatable method to monitor land conversion characterized by artificial sprawl: (i) We used an object-based image analysis to extract artificial areas from satellite images; (ii) We built an artificial patch that consists of aggregating all the peripheral areas that characterize artificial areas. The “artificialized” patch concept is an innovative extension of the urban patch concept, but differs in the nature of its components and in the continuity distance applied; (iii) The diachronic analysis of artificial patch maps enables characterization of artificial sprawl. The method was applied at the scale of four departments (similar to provinces) along the coast of Languedoc-Roussillon, in the South of France, based on two satellite datasets, one acquired in 1996–1997 (Indian Remote Sensing) and the other in 2009 (RapidEye). In the four departments, we measured an increase in artificial areas of from 113,000 ha in 1997 to 133,000 ha in 2009, i.e., an 18% increase in 12 years. The package comes in the form of a 1/15,000 valid cartography, usable at the scale of a commune (the smallest territorial division used for administrative purposes in France) that can be adapted to departmental and regional scales. The method is reproducible in homogenous spatial-temporal terms, so that it could be used periodically to assess changes in land conversion rates in France as a whole. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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Open AccessArticle Remote Sensing Images in Support of Environmental Protocol: Monitoring the Sugarcane Harvest in São Paulo State, Brazil
Remote Sens. 2011, 3(12), 2682-2703; doi:10.3390/rs3122682
Received: 20 October 2011 / Revised: 9 December 2011 / Accepted: 9 December 2011 / Published: 13 December 2011
Cited by 24 | PDF Full-text (10014 KB) | HTML Full-text | XML Full-text
Abstract
Traditional manual sugarcane harvesting requires the pre-harvest burning practice which should be gradually banned by 2021 for most of São Paulo State, Brazil, on cultivated sugarcane land (terrain slope ≤12%) according to State Law number 11241. To forward the end of this practice
[...] Read more.
Traditional manual sugarcane harvesting requires the pre-harvest burning practice which should be gradually banned by 2021 for most of São Paulo State, Brazil, on cultivated sugarcane land (terrain slope ≤12%) according to State Law number 11241. To forward the end of this practice to 2014, a “Green Ethanol” Protocol was established in 2007. The present work aims at analyzing five years of continuous sugarcane harvest monitoring, based on remote sensing images, to evaluate the effectiveness of the Protocol, thus helping decision makers to establish public policies to meet the Protocol’s expected goals. During the last five crop years, sugarcane acreage expanded by 1.5 million ha, which was compensated by a correspondent increase in the green harvested land. However, no significant reduction was observed in the amount of pre-harvest burned land over the same period. Based on the current trend, this goal is likely to be achieved one or two years later (2015–2016), which will be five or six years ahead of 2021 as the goal in the State Law number 11241 states. We thus conclude that the“Green Ethanol” Protocol has been effective with a positive impact on the increase of GH, especially on recently expanded sugarcane fields. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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Open AccessArticle Exploring Land Use and Land Cover Effects on Air Quality in Central Alabama Using GIS and Remote Sensing
Remote Sens. 2011, 3(12), 2552-2567; doi:10.3390/rs3122552
Received: 30 September 2011 / Revised: 17 November 2011 / Accepted: 17 November 2011 / Published: 25 November 2011
Cited by 6 | PDF Full-text (1754 KB) | HTML Full-text | XML Full-text
Abstract
Air pollution has been a major topic of debate in highly developed areas over the last quarter century and therefore mitigation of poor air quality for health and environmental reasons has been a primary focus for local governments. Particulate matter, especially finer particles
[...] Read more.
Air pollution has been a major topic of debate in highly developed areas over the last quarter century and therefore mitigation of poor air quality for health and environmental reasons has been a primary focus for local governments. Particulate matter, especially finer particles (PM2.5), is detrimental to human health, and urban expansion is thought to be a contributing factor to enhanced levels of PM2.5. However, there is limited research on the connection between land use and land cover change (LULC) and PM2.5 emissions. Using high resolution LANDSAT imagery from the past 12 years along with ground observations of PM2.5 mass concentrations in the Birmingham, AL region, we explore the links between the PM2.5 mass concentrations and LULC trends. Utilization of GIS allowed us to seamlessly analyze county-based patterns of LULC change and PM2.5 concentrations and display them in an easy to interpret manner. We found a moderate-to-strong correlation between PM2.5 observations and the urban area surrounding monitoring sites in 1998 and 2010. We also discuss factors such as local climate and topography and EPA imposed standards that can confound these comparisons. Finally, we determine the next steps that are required to fully quantify the cause and effect between LULC and air quality. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
Open AccessArticle Tracking Environmental Compliance and Remediation Trajectories Using Image-Based Anomaly Detection Methodologies
Remote Sens. 2011, 3(11), 2384-2402; doi:10.3390/rs3112384
Received: 1 September 2011 / Revised: 1 November 2011 / Accepted: 1 November 2011 / Published: 7 November 2011
PDF Full-text (977 KB) | HTML Full-text | XML Full-text
Abstract
Recent interest in use of satellite remote sensing for environmental compliance and remediation assessment has been heightened by growing policy requirements and the need to provide more rapid and efficient monitoring and enforcement mechanisms. However, remote sensing solutions are attractive only to the
[...] Read more.
Recent interest in use of satellite remote sensing for environmental compliance and remediation assessment has been heightened by growing policy requirements and the need to provide more rapid and efficient monitoring and enforcement mechanisms. However, remote sensing solutions are attractive only to the extent that they can deliver environmentally relevant information in a meaningful and time-sensitive manner. Unfortunately, the extent to which satellite-based remote sensing satisfies the demands for compliance and remediation assessment under the conditions of an actual environmental accident or calamity has not been well documented. In this study a remote sensing solution to the problem of site remediation and environmental compliance assessment was introduced based on the use of the RDX anomaly detection algorithm and vegetation indices developed from the Tasseled Cap Transform. Results of this analysis illustrate how the use of standard vegetation transforms, integrated into an anomaly detection strategy, enable the time-sequenced tracking of site remediation progress. Based on these results credible evidence can be produced to support compliance evaluation and remediation assessment following major environmental disasters. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
Open AccessArticle Urban Sprawl Analysis and Modeling in Asmara, Eritrea
Remote Sens. 2011, 3(10), 2148-2165; doi:10.3390/rs3102148
Received: 10 August 2011 / Revised: 7 September 2011 / Accepted: 8 September 2011 / Published: 26 September 2011
Cited by 27 | PDF Full-text (696 KB) | HTML Full-text | XML Full-text
Abstract
The extension of urban perimeter markedly cuts available productive land. Hence, studies in urban sprawl analysis and modeling play an important role to ensure sustainable urban development. The urbanization pattern of the Greater Asmara Area (GAA), the capital of Eritrea, was studied. Satellite
[...] Read more.
The extension of urban perimeter markedly cuts available productive land. Hence, studies in urban sprawl analysis and modeling play an important role to ensure sustainable urban development. The urbanization pattern of the Greater Asmara Area (GAA), the capital of Eritrea, was studied. Satellite images and geospatial tools were employed to analyze the spatiotemporal urban landuse changes. Object-Based Image Analysis (OBIA), Landuse Cover Change (LUCC) analysis and urban sprawl analysis using Shannon Entropy were carried out. The Land Change Modeler (LCM) was used to develop a model of urban growth. The Multi-layer Perceptron Neural Network was employed to model the transition potential maps with an accuracy of 85.9% and these were used as an input for the ‘actual’ urban modeling with Markov chains. Model validation was assessed and a scenario of urban land use change of the GAA up to year 2020 was presented. The result of the study indicated that the built-up area has tripled in size (increased by 4,441 ha) between 1989 and 2009. Specially, after year 2000 urban sprawl in GAA caused large scale encroachment on high potential agricultural lands and plantation cover. The scenario for year 2020 shows an increase of the built-up areas by 1,484 ha (25%) which may cause further loss. The study indicated that the land allocation system in the GAA overrode the landuse plan, which caused the loss of agricultural land and plantation cover. The recommended policy options might support decision makers to resolve further loss of agricultural land and plantation cover and to achieve sustainable urban development planning in the GAA. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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Open AccessArticle Towards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter
Remote Sens. 2011, 3(7), 1308-1322; doi:10.3390/rs3071308
Received: 13 April 2011 / Revised: 21 June 2011 / Accepted: 22 June 2011 / Published: 29 June 2011
Cited by 28 | PDF Full-text (974 KB) | HTML Full-text | XML Full-text | Correction | Supplementary Files
Abstract
Spatial monitoring tools are necessary to respond to the threat of global biodiversity loss. At the European scale, remote sensing tools for NATURA 2000 habitat monitoring have been requested by the European Commission to fulfill the obligations of the EU Habitats Directive. This
[...] Read more.
Spatial monitoring tools are necessary to respond to the threat of global biodiversity loss. At the European scale, remote sensing tools for NATURA 2000 habitat monitoring have been requested by the European Commission to fulfill the obligations of the EU Habitats Directive. This paper introduces a method by which swath events in semi-natural grasslands can be detected from multi-temporal TerraSAR-X data. The investigated study sites represent rare and endangered habitats (NATURA 2000 codes 6410, 6510), located in the Döberitzer Heide nature conservation area west of Berlin. We analyzed a time series of 11 stripmap images (HH-polarization) covering the vegetation period affected by swath (June to September 2010) at a constant 11-day acquisition rate. A swath detection rule was established to extract the swath events for the NATURA 2000 habitats as well as for six contrasting pasture sites not affected by swath. All swath events observed in the field were correctly allocated. The results indicate the potential to allocate semi-natural grassland swath events to 11-day-periods using TerraSAR-X time series. Since the conservation of semi-natural grassland habitats requires compliance with specific swath management rules, the detection of swath events may thus provide new parameters for the monitoring of NATURA 2000 grassland habitats. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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Open AccessArticle Strategies for Incorporating High-Resolution Google Earth Databases to Guide and Validate Classifications: Understanding Deforestation in Borneo
Remote Sens. 2011, 3(6), 1157-1176; doi:10.3390/rs3061157
Received: 31 March 2011 / Revised: 20 May 2011 / Accepted: 24 May 2011 / Published: 3 June 2011
Cited by 16 | PDF Full-text (1262 KB) | HTML Full-text | XML Full-text
Abstract
International climate change mitigation initiatives such as REDD-plus have fuelled the need for forest monitoring efforts that focus especially on the carbon rich natural ecosystems that are found in the humid tropics. Such monitoring efforts must tackle challenges intrinsic to these regions, such
[...] Read more.
International climate change mitigation initiatives such as REDD-plus have fuelled the need for forest monitoring efforts that focus especially on the carbon rich natural ecosystems that are found in the humid tropics. Such monitoring efforts must tackle challenges intrinsic to these regions, such as high atmospheric contamination from particulates and persistent cloud cover. The emergence of new high-resolution platforms like Google Earth offers new potential scientific uses that can help meet these challenges. Using data from MODIS and detailed observation of Google Earth images, we have produced a yearly time series of deforestation hotspots for the island of Borneo for the 2000 to 2009 period. Our workflow and results demonstrate how multiple free data sources can be combined to greatly enhance the individual capacities of each. The methodology employed to produce this time series demonstrates simple, low-expense techniques that can be used to circumvent the obstacles that typically hinder systematic remote sensing in Borneo and other heavily clouded areas. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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Open AccessArticle The Soy Moratorium in the Amazon Biome Monitored by Remote Sensing Images
Remote Sens. 2011, 3(1), 185-202; doi:10.3390/rs3010185
Received: 16 November 2010 / Revised: 22 December 2010 / Accepted: 29 December 2010 / Published: 18 January 2011
Cited by 52 | PDF Full-text (1617 KB) | HTML Full-text | XML Full-text
Abstract
The Soy Moratorium is a pledge agreed to by major soybean companies not to trade soybean produced in deforested areas after 24th July 2006 in the Brazilian Amazon biome. The present study aims to identify soybean planting in these areas using the MOD13Q1
[...] Read more.
The Soy Moratorium is a pledge agreed to by major soybean companies not to trade soybean produced in deforested areas after 24th July 2006 in the Brazilian Amazon biome. The present study aims to identify soybean planting in these areas using the MOD13Q1 product and TM/Landsat-5 images followed by aerial survey and field inspection. In the 2009/2010 crop year, 6.3 thousand ha of soybean (0.25% of the total deforestation) were identified in areas deforested during the moratorium period. The use of remote sensing satellite images reduced by almost 80% the need for aerial survey to identify soybean planting and allowed monitoring of all deforested areas greater than 25 ha. It is still premature to attribute the recent low deforestation rates in the Amazon biome to the Soy Moratorium, but the initiative has certainly exerted an inhibitory effect on the soybean frontier expansion in this biome. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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Review

Jump to: Research, Other

Open AccessReview Use of Remote Sensing to Support Forest and Wetlands Policies in the USA
Remote Sens. 2011, 3(6), 1211-1233; doi:10.3390/rs3061211
Received: 30 March 2011 / Revised: 24 May 2011 / Accepted: 31 May 2011 / Published: 14 June 2011
Cited by 11 | PDF Full-text (392 KB) | HTML Full-text | XML Full-text
Abstract
The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy
[...] Read more.
The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy implementation and evaluation has not been examined in much detail. Here we examine the use of remote sensing to support the implementation and enforcement of policies regarding the conservation of forests and wetlands in the USA. Specifically, we focus on the “Roadless Rule” and “Travel Management Rules” as enforced by the US Department of Agriculture Forest Service on national forests, and the “No Net Loss” policy and Clean Water Act for wetlands on public and private lands, as enforced by the US Environmental Protection Agency and the US Army Corps of Engineers. We discuss several national and regional examples of how remote sensing for forest and wetland conservation has been effectively integrated with policy decisions, along with barriers to further integration. Some of these barriers are financial and technical (such as the lack of data at scales appropriate to policy enforcement), while others are political. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)

Other

Jump to: Research, Review

Open AccessCorrection Correction on “Towards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter”
Remote Sens. 2012, 4(8), 2455-2456; doi:10.3390/rs4082455
Received: 28 June 2012 / Accepted: 28 June 2012 / Published: 15 August 2012
Cited by 1 | PDF Full-text (110 KB) | HTML Full-text | XML Full-text
Abstract
We found a mistake in the swath detection rule in Section 2.4 [1]. Specifically, the percent deviation calculation in the definition of the signal changes D1 and D2 and axiom A2 are altered. The correct version shall be: Consequently, the proposed
[...] Read more.
We found a mistake in the swath detection rule in Section 2.4 [1]. Specifically, the percent deviation calculation in the definition of the signal changes D1 and D2 and axiom A2 are altered. The correct version shall be: Consequently, the proposed rule for the detection of swath events consists of two axioms (A1 and A2) that need to be satisfied. For the signal backscatter (σ°) at a specific acquisition order number (k) of the acquired scene in the time series (N), the positive or negative signal changes in percent deviation for the first (D1) and second (D2) acquisition after a potential swath event are considered as: [...] Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)

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