ISPRS International Journal of Geo-Information

Editorial

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17 pages, 302 KiB

Open AccessEditorial

Global Ambitions, Local Contexts: Alternative Ways of Knowing the World

by Karin Pfeffer and Yola Georgiadou

ISPRS Int. J. Geo-Inf. 2019, 8(11), 516; https://doi.org/10.3390/ijgi8110516 - 15 Nov 2019

Cited by 7 | Viewed by 3780

Abstract

In this Special Issue, we bring together contributions from authors in the scientific discipline Geo-Information Science who engaged with the question: How does Geo-Information Science contribute to the development of Sustainable Development Goals (SDG) indicators? The editorial to the Special Issue situates the [...] Read more.

In this Special Issue, we bring together contributions from authors in the scientific discipline Geo-Information Science who engaged with the question: How does Geo-Information Science contribute to the development of Sustainable Development Goals (SDG) indicators? The editorial to the Special Issue situates the individual contributions in a broader social science debate, which critically examines the quantification of global policy goals and its effects on how we know and govern the world. We put forward concepts of ‘measuring the world’ and a brief history of the Geo-Information Science discipline, including its dominant positivist paradigm as well as scholarly debates that reflected on and shifted that paradigm. Given the global policy focus of the SDGs, we also briefly discuss policy science paradigms. We analyze the individual articles with regard to their contribution to the SDG indicator development trajectory. We also show how alternative ways of knowing and governing the world complement the dominant positivist paradigm. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

Research

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19 pages, 1889 KiB

Open AccessArticle

Principles and Applications of the Global Human Settlement Layer as Baseline for the Land Use Efficiency Indicator—SDG 11.3.1

by Michele Melchiorri, Martino Pesaresi, Aneta J. Florczyk, Christina Corbane and Thomas Kemper

ISPRS Int. J. Geo-Inf. 2019, 8(2), 96; https://doi.org/10.3390/ijgi8020096 - 18 Feb 2019

Cited by 108 | Viewed by 13729

Abstract

The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics describing the human presence on the planet that is based mainly on two quantitative factors: (i) the spatial distribution (density) of built-up structures and (ii) the spatial distribution (density) of [...] Read more.

The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics describing the human presence on the planet that is based mainly on two quantitative factors: (i) the spatial distribution (density) of built-up structures and (ii) the spatial distribution (density) of resident people. Both of the factors are observed in the long-term temporal domain and per unit area, in order to support the analysis of the trends and indicators for monitoring the implementation of the 2030 Development Agenda and the related thematic agreements. The GHSL uses various input data, including global, multi-temporal archives of high-resolution satellite imagery, census data, and volunteered geographic information. In this paper, we present a global estimate for the Land Use Efficiency (LUE) indicator—SDG 11.3.1, for circa 10,000 urban centers, calculating the ratio of land consumption rate to population growth rate between 1990 and 2015. In addition, we analyze the characteristics of the GHSL information to demonstrate how the original frameworks of data (gridded GHSL data) and tools (GHSL tools suite), developed from Earth Observation and integrated with census information, could support Sustainable Development Goals monitoring. In particular, we demonstrate the potential of gridded, open and free, local yet globally consistent, multi-temporal data in filling the data gap for Sustainable Development Goal 11. The results of our research demonstrate that there is potential to raise SDG 11.3.1 from a Tier II classification (manifesting unavailability of data) to a Tier I, as GHSL provides a global baseline for the essential variables called by the SDG 11.3.1 metadata. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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23 pages, 3822 KiB

Open AccessFeature PaperArticle

Access or Accessibility? A Critique of the Urban Transport SDG Indicator

by Mark Brussel, Mark Zuidgeest, Karin Pfeffer and Martin van Maarseveen

ISPRS Int. J. Geo-Inf. 2019, 8(2), 67; https://doi.org/10.3390/ijgi8020067 - 30 Jan 2019

Cited by 56 | Viewed by 11059

Abstract

Progress towards the UN Sustainable Development Goals (SDGs) is being evaluated through the use of indicators. Despite the importance of these indicators, the academic community has done little in terms of a critical reflection on their choice, relevance, framing and operationalization. This holds [...] Read more.

Progress towards the UN Sustainable Development Goals (SDGs) is being evaluated through the use of indicators. Despite the importance of these indicators, the academic community has done little in terms of a critical reflection on their choice, relevance, framing and operationalization. This holds for many SDG domains, also for the urban sector domain of target 11. To partially address this void, we aim to critically review the UN methodology for the urban access indicator, SDG indicator 11.2. In discussing its conceptual framing against the background of paradigm shifts in transportation planning, we argue that this indicator has a number of shortcomings. The most important one is that it is supply oriented and measures access to transportation infrastructure, rather than accessibility to activity locations. As an alternative, we develop two accessibility indicators that show substantial variation in accessibility across geographical areas. We implement all indicators for the city of Bogotá in Colombia, using a geo-information based approach. Our results show that SDG indicator 11.2 fails to represent the transport reality well. Its supply oriented focus neglects transport demand, oversimplifies the transport system and hides existing inequalities. Moreover, it does not provide useful evidence for targeting new interventions. The proposed accessibility indicators provide a more diverse, complete and realistic picture of the performance of the transport system. These indicators also capture the large spatial and socio-economic inequalities and can help to target improvements in urban transportation. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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11 pages, 2247 KiB

Open AccessArticle

A Spatial Analysis Framework to Monitor and Accelerate Progress towards SDG 3 to End TB in Bangladesh

by Ente Rood, Ahmadul Hasan Khan, Pronab Kumar Modak, Christina Mergenthaler, Margo Van Gurp, Lucie Blok and Mirjam Bakker

ISPRS Int. J. Geo-Inf. 2019, 8(1), 14; https://doi.org/10.3390/ijgi8010014 - 29 Dec 2018

Cited by 15 | Viewed by 5982

Abstract

Global efforts to end the tuberculosis (TB) epidemic by 2030 (SDG3.3) through improved TB case detection and treatment have not been effective to significantly reduce the global burden of the TB epidemic. This study presents an analytical framework to evaluate the use of [...] Read more.

Global efforts to end the tuberculosis (TB) epidemic by 2030 (SDG3.3) through improved TB case detection and treatment have not been effective to significantly reduce the global burden of the TB epidemic. This study presents an analytical framework to evaluate the use of TB case notification rates (CNR) to monitor and to evaluate TB under-detection and under-diagnoses in Bangladesh. Local indicators of spatial autocorrelation (LISA) were calculated to assess the presence and scale of spatial clusters of TB CNR across 489 upazilas in Bangladesh. Simultaneous autoregressive models were fit to the data to identify associations between TB CNR and poverty, TB testing rates and retreatment rates. CNRs were found to be significantly spatially clustered, negatively correlated to poverty rates and positively associated to TB testing and retreatment rates. Comparing the observed pattern of CNR with model-standardized rates made it possible to identify areas where TB under-detection is likely to occur. These results suggest that TB CNR is an unreliable proxy for TB incidence. Spatial variations in TB case notifications and subnational variations in TB case detection should be considered when monitoring national TB trends. These results provide useful information to target and prioritize context specific interventions. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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21 pages, 2675 KiB

Open AccessArticle

Ratio of Land Consumption Rate to Population Growth Rate—Analysis of Different Formulations Applied to Mainland Portugal

by Rita Nicolau, João David, Mário Caetano and José M. C. Pereira

ISPRS Int. J. Geo-Inf. 2019, 8(1), 10; https://doi.org/10.3390/ijgi8010010 - 27 Dec 2018

Cited by 54 | Viewed by 8283

Abstract

This paper presents a methodological approach for the assessment of the indicator 11.3.1: “Ratio of Land Consumption Rate to Population Growth Rate” proposed by the United Nations (UN), discussing the definitions and assumptions that support the indicator quantification, and analysing the results provided [...] Read more.

This paper presents a methodological approach for the assessment of the indicator 11.3.1: “Ratio of Land Consumption Rate to Population Growth Rate” proposed by the United Nations (UN), discussing the definitions and assumptions that support the indicator quantification, and analysing the results provided by different formulations applied to mainland Portugal, at the municipality level. Due to specific limitations related to the actual formula proposed by the UN (LCRPGR) for the computation of the indicator, an alternative formulation derived from Land Use Efficiency (LUE) was explored. Considering that the land to which the indicator refers may be described by specific classes represented in Land Cover Land Use (LCLU) maps, in the estimation of the land consumption rate we tested two LCLU datasets: Corine Land Cover and COS—the Portuguese LCLU reference map. For the estimation of the population growth rate, prior allocation of inhabitants to the areas where people are most likely to reside was deemed necessary, using a dasymetric mapping technique based on LCLU information. The results obtained for 2007–2011 and 2011–2015 showed, in most municipalities, an increase in the urban area and a decrease in urban population, leading to negative values both in LCRPGR and LUE in most of the territory. Clearly, LUE performed better than LCRPGR in what urban development monitoring and urban area dynamics trends are concerned. Furthermore, LUE was much easier to interpret. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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18 pages, 1186 KiB

Open AccessArticle

The Impact of Urban Inequalities on Monitoring Progress towards the Sustainable Development Goals: Methodological Considerations

by Philipp Ulbrich, João Porto de Albuquerque and Jon Coaffee

ISPRS Int. J. Geo-Inf. 2019, 8(1), 6; https://doi.org/10.3390/ijgi8010006 - 26 Dec 2018

Cited by 25 | Viewed by 12368

Abstract

There is much discussion regarding the Sustainable Development Goals’ (SDGs) capacity to promote inclusive development. While some argue that they represent an opportunity for goal-led alignment of stakeholders and evidence-based decision-making, other voices express concerns as they perceive them as a techno-managerial framework [...] Read more.

There is much discussion regarding the Sustainable Development Goals’ (SDGs) capacity to promote inclusive development. While some argue that they represent an opportunity for goal-led alignment of stakeholders and evidence-based decision-making, other voices express concerns as they perceive them as a techno-managerial framework that measures development according to quantitatively defined parameters and does not allow for local variation. We argue that the extent to which the positive or negative aspects of the SDGs prevail depends on the monitoring system’s ability to account for multiple and intersecting inequalities. The need for sub-nationally (urban) representative indicators poses an additional methodological challenge—especially in cities with intra-urban inequalities related to socio-spatial variations across neighbourhoods. This paper investigates the extent to which the SDG indicators’ representativeness could be affected by inequalities. It does so by proposing a conceptual framing for understanding the relation between inequalities and SDG monitoring, which is then applied to analyse the current methodological proposals for the indicator framework of the “urban SDG,” Goal 11. The outcome is a call for (1) a more explicit attention to intra-urban inequalities, (2) the development of a methodological approach to “recalibrate” the city-level indicators to account for the degree of intra-urban inequalities, and (3) an alignment between methodologies and data practices applied for monitoring SDG 11 and the extent of the underlying inequalities within the city. This would enable an informed decision regarding the trade-off in indicator representativeness between conventional data sources, such as censuses and household surveys, and emerging methods, such as participatory geospatial methods and citizen-generated data practices. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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15 pages, 4224 KiB

Open AccessCommunication

Challenges of Mapping Sustainable Development Goals Indicators Data

by Menno Jan Kraak, Britta Ricker and Yuri Engelhardt

ISPRS Int. J. Geo-Inf. 2018, 7(12), 482; https://doi.org/10.3390/ijgi7120482 - 17 Dec 2018

Cited by 29 | Viewed by 9864

Abstract

The global population is growing at an incomprehensible rate and with it come complex environmental consequences that often result in social injustices. The United Nations has established a set of Sustainable Development Goals (SDGs) in an attempt to ameliorate inequality and promise safety [...] Read more.

The global population is growing at an incomprehensible rate and with it come complex environmental consequences that often result in social injustices. The United Nations has established a set of Sustainable Development Goals (SDGs) in an attempt to ameliorate inequality and promise safety for the masses. To reach these goals, a set of indicators have been identified and their associated data for each country are publicly available to measure how close each country is to each goal. Multifaceted social and environmental processes that are difficult to understand are causing threats to these goals. Maps help reduce complexity. Now, arguably anyone with access to the Internet and time can make a map. However, not all maps are effective accurate communication vessels. Well-designed maps tell a story that truthfully represents the data available. Here we present a synthesis of the cartographic workflow pointing out specific considerations necessary when mapping SDG indicators. Along the way we illustrate the cartographic workflow as it relates to visualizing SDG indicators. Common mapping pitfalls are described and a range of suggestions to avoid them are also offered. Map makers have a unique opportunity to use these data to illuminate and communicate injustices that are documented therein to inspire creative localized solutions to eradicate inequality. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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20 pages, 335 KiB

Open AccessArticle

Measuring Inequality of Opportunity in Access to Quality Basic Education: A Case Study in Florida, US

by Lydia M. Prieto, Johannes Flacke, Jonathan Aguero-Valverde and Martin Van Maarseveen

ISPRS Int. J. Geo-Inf. 2018, 7(12), 465; https://doi.org/10.3390/ijgi7120465 - 29 Nov 2018

Cited by 7 | Viewed by 5841

Abstract

Providing all children equal access to essential services, such as primary education, has been set as a priority in the Sustainable Development Goals (SDG)’ agenda during the last two decades. Yet the Global Education Monitoring report in 2016 reveals that wide disparities between [...] Read more.

Providing all children equal access to essential services, such as primary education, has been set as a priority in the Sustainable Development Goals (SDG)’ agenda during the last two decades. Yet the Global Education Monitoring report in 2016 reveals that wide disparities between the rich and the poor persist in access to education of high quality. This study uses the Human Opportunity Index (HOI) to examine the equality of opportunity in access to basic education of high quality. By using enrollment and admission data from a case study in a large school district in the US in 2015/2016, this research evaluates the capacity of the HOI, in order to reveal disparities in access to school opportunities and examines how much of this inequality is explained by families’ pre-determined circumstances. The way of analyzing equality is by disaggregating applications’ data into circumstance groups, according to gender, geography, race/ethnicity, and other criteria. To capture the contribution of each circumstance to inequality of opportunity, the Shapley decomposition method is used. Findings show that the HOI is capable of systematically monitoring and examining existing admission policies and identifying inequality problems. Furthermore, the analysis of the contribution of each circumstance group can reveal admission criteria that have the potential to harm the educational opportunities for children. This assessment should provide valuable insights into the capability of the indicators to reveal where policy intervention is necessary and supply points of view on how policy can be improved. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

16 pages, 269 KiB

Open AccessCommunication

How to Contextualize SDG 11? Looking at Indicators for Sustainable Urban Development in Germany

by Florian Koch and Kerstin Krellenberg

ISPRS Int. J. Geo-Inf. 2018, 7(12), 464; https://doi.org/10.3390/ijgi7120464 - 29 Nov 2018

Cited by 90 | Viewed by 14705

Abstract

Agenda 2030 pursues a universal approach and identifies countries in the Global South and in the Global North that are in need of transformation toward sustainability. Therefore, countries of the Global North such as Germany have signed the commitment to implement the Sustainable [...] Read more.

Agenda 2030 pursues a universal approach and identifies countries in the Global South and in the Global North that are in need of transformation toward sustainability. Therefore, countries of the Global North such as Germany have signed the commitment to implement the Sustainable Development Goals (SDGs). However, the SDGs need to be “translated” to the specific national context. Existing sustainability indicators and monitoring and reporting systems need to be adjusted as well. Our paper evaluates how three different initiatives translated SDG 11 (“Make cities and human settlements inclusive, safe, resilient, and sustainable”) to the German context, given the specific role of cities in contributing to sustainable development. These initiatives included the official ‘National Sustainable Development Strategy’ of the German Government, a scientific initiative led by the ‘German Institute for Urban Affairs’, and a project carried out by the ‘Open Knowledge Foundation’, a non-governmental organization (NGO). This article aims to analyze how global goals addressing urban developments are contextualized on a national level. Our findings demonstrate that only a few of the original targets and indicators for SDG 11 are used in the German context; thus, major adjustments have been made according to the main sustainability challenges identified for Germany. Furthermore, our results show that the current contextualization of SDG 11 and sustainable urban development in Germany are still ongoing, and more changes and commitments need to be made. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

34 pages, 3278 KiB

Open AccessArticle

Characterizing Data Ecosystems to Support Official Statistics with Open Mapping Data for Reporting on Sustainable Development Goals

by Marc Van den Homberg and Iryna Susha

ISPRS Int. J. Geo-Inf. 2018, 7(12), 456; https://doi.org/10.3390/ijgi7120456 - 24 Nov 2018

Cited by 27 | Viewed by 9979

Abstract

Reporting on the Sustainable Development Goals (SDGs) is complex given the wide variety of governmental and NGO actors involved in development projects as well as the increased number of targets and indicators. However, data on the wide variety of indicators must be collected [...] Read more.

Reporting on the Sustainable Development Goals (SDGs) is complex given the wide variety of governmental and NGO actors involved in development projects as well as the increased number of targets and indicators. However, data on the wide variety of indicators must be collected regularly, in a robust manner, comparable across but also within countries and at different administrative and disaggregated levels for adequate decision making to take place. Traditional census and household survey data is not enough. The increase in Small and Big Data streams have the potential to complement official statistics. The purpose of this research is to develop and evaluate a framework to characterize a data ecosystem in a developing country in its totality and to show how this can be used to identify data, outside the official statistics realm, that enriches the reporting on SDG indicators. Our method consisted of a literature study and an interpretative case study (two workshops with 60 and 35 participants and including two questionnaires, over 20 consultations and desk research). We focused on SDG 6.1.1. (Proportion of population using safely managed drinking water services) in rural Malawi. We propose a framework with five dimensions (actors, data supply, data infrastructure, data demand and data ecosystem governance). Results showed that many governmental and NGO actors are involved in water supply projects with different funding sources and little overall governance. There is a large variety of geospatial data sharing platforms and online accessible information management systems with however a low adoption due to limited internet connectivity and low data literacy. Lots of data is still not open. All this results in an immature data ecosystem. The characterization of the data ecosystem using the framework proves useful as it unveils gaps in data at geographical level and in terms of dimensionality (attributes per water point) as well as collaboration gaps. The data supply dimension of the framework allows identification of those datasets that have the right quality and lowest cost of data extraction to enrich official statistics. Overall, our analysis of the Malawian case study illustrated the complexities involved in achieving self-regulation through interaction, feedback and networked relationships. Additional complexities, typical for developing countries, include fragmentation, divide between governmental and non-governmental data activities, complex funding relationships and a data poor context. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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13 pages, 3918 KiB

Open AccessArticle

From a Vegetation Index to a Sustainable Development Goal Indicator: Forest Trend Monitoring Using Three Decades of Earth Observations across Switzerland

by Erica Honeck, Roberto Castello, Bruno Chatenoux, Jean-Philippe Richard, Anthony Lehmann and Gregory Giuliani

ISPRS Int. J. Geo-Inf. 2018, 7(12), 455; https://doi.org/10.3390/ijgi7120455 - 24 Nov 2018

Cited by 22 | Viewed by 5620

Abstract

Forests represent important habitats for species and provide multiple ecosystem services for human well-being. Preserving forests and other terrestrial ecosystems has become crucial to halt desertification, land degradation, and biodiversity loss worldwide, and is also one of the Sustainable Development Goals (SDGs) to [...] Read more.

Forests represent important habitats for species and provide multiple ecosystem services for human well-being. Preserving forests and other terrestrial ecosystems has become crucial to halt desertification, land degradation, and biodiversity loss worldwide, and is also one of the Sustainable Development Goals (SDGs) to be achieved by 2030. Remote sensing could greatly contribute to measuring progress toward SDGs by providing consistent and repetitive coverage of large areas, as well as information in various wavelengths, which facilitates the monitoring of environmental trends at various scales. This paper focuses on SDG indicator 15.1.1—“Forest area as a percentage of total land area” to demonstrate the potential of Earth Observation Data Cubes for SDGs. The approach presented here uses Landsat Analysis Ready Data (ARD) stored in the Swiss Data Cube, and offers a complementary method to ground-based approaches to monitor Switzerland’s forest extent based on the Normalized Difference Vegetation Index (NDVI). The proposed method performs time-series analyses to extract a forest/non-forest map and a graph representing the trend of SDG 15.1.1 indicator over time. Preliminary results suggest that this approach can identify similar forest extent and growth patterns to observed trends, and can therefore help monitor progress toward the selected SDG indicator more effectively. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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16 pages, 2593 KiB

Open AccessArticle

Toward Model-Generated Household Listing in Low- and Middle-Income Countries Using Deep Learning

by Robert Chew, Kasey Jones, Jennifer Unangst, James Cajka, Justine Allpress, Safaa Amer and Karol Krotki

ISPRS Int. J. Geo-Inf. 2018, 7(11), 448; https://doi.org/10.3390/ijgi7110448 - 16 Nov 2018

Cited by 8 | Viewed by 4373

Abstract

While governments, researchers, and NGOs are exploring ways to leverage big data sources for sustainable development, household surveys are still a critical source of information for dozens of the 232 indicators for the Sustainable Development Goals (SDGs) in low- and middle-income countries (LMICs). [...] Read more.

While governments, researchers, and NGOs are exploring ways to leverage big data sources for sustainable development, household surveys are still a critical source of information for dozens of the 232 indicators for the Sustainable Development Goals (SDGs) in low- and middle-income countries (LMICs). Though some countries’ statistical agencies maintain databases of persons or households for sampling, conducting household surveys in LMICs is complicated due to incomplete, outdated, or inaccurate sampling frames. As a means to develop or update household listings in LMICs, this paper explores the use of machine learning models to detect and enumerate building structures directly from satellite imagery in the Kaduna state of Nigeria. Specifically, an object detection model was used to identify and locate buildings in satellite images. In the test set, the model attained a mean average precision (mAP) of 0.48 for detecting structures, with relatively higher values in areas with lower building density (mAP = 0.65). Furthermore, when model predictions were compared against recent household listings from fieldwork in Nigeria, the predictions showed high correlation with household coverage (Pearson = 0.70; Spearman = 0.81). With the need to produce comparable, scalable SDG indicators, this case study explores the feasibility and challenges of using object detection models to help develop timely enumerated household lists in LMICs. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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21 pages, 2296 KiB

Open AccessArticle

The Elephant in the Room: Informality in Tanzania’s Rural Waterscape

by Jesper Katomero and Yola Georgiadou

ISPRS Int. J. Geo-Inf. 2018, 7(11), 437; https://doi.org/10.3390/ijgi7110437 - 8 Nov 2018

Cited by 4 | Viewed by 6440

Abstract

Informality is pervasive in Tanzania’s rural waterscape, but not acknowledged by development partners (donors and beneficiaries), despite persistent warnings by development scholars. Informality is thus the proverbial elephant in the room. In this paper, we examine a case of superior rural water access [...] Read more.

Informality is pervasive in Tanzania’s rural waterscape, but not acknowledged by development partners (donors and beneficiaries), despite persistent warnings by development scholars. Informality is thus the proverbial elephant in the room. In this paper, we examine a case of superior rural water access in two geographical locales—Hai and Siha districts—in Tanzania, where actors not only acknowledge, but actively harness informality to provide access to water to rural populations. We employ concepts from organization and institutional theory to show that when informal programs and related informal sanctions/rewards complement their formal counterparts, chances for achieving the Sustainable Development Goals (SDG) target 6.1 ‘By 2030, achieve universal and equitable access to safe and affordable drinking water for all’ are significantly increased. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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26 pages, 4271 KiB

Open AccessArticle

From Global Goals to Local Gains—A Framework for Crop Water Productivity

by Megan Leigh Blatchford, Poolad Karimi, W.G.M. Bastiaanssen and Hamideh Nouri

ISPRS Int. J. Geo-Inf. 2018, 7(11), 414; https://doi.org/10.3390/ijgi7110414 - 25 Oct 2018

Cited by 28 | Viewed by 6441

Abstract

Crop water productivity (CWP) has become a recognised indicator in assessing the state of Sustainable Development Goals (SDG) 6.4—to substantially increase water use efficiency. This indicator, while useful at a global scale, is not comprehensive at a local scale. To fill this gap, [...] Read more.

Crop water productivity (CWP) has become a recognised indicator in assessing the state of Sustainable Development Goals (SDG) 6.4—to substantially increase water use efficiency. This indicator, while useful at a global scale, is not comprehensive at a local scale. To fill this gap, this research proposes a CWP framework, that takes advantage of the spatio-temporal availability of remote sensing, that identifies CWP goals and sub-indicators specific to the needs of the targeted domain. Three sub-indicators are considered; (i) a global water productivity score (GWPS), (ii) a local water productivity score (LWPS) and (iii) a land and water use productivity score (YWPS). The GWPS places local CWP in the global context and focuses on maximised CWP. The LWPS differentiates yield zones, normalising for potential product, and focuses on minimising water consumption. The YWPS focuses simultaneously on improving land and water productivity equally. The CWP framework was applied to potato in the West Bank, Palestine. Three management practices were compared under each sub-indicator. The case study showed that fields with high and low performance were different under each sub-indicator. The performance associated with different management practices was also different under each sub-indicator. For example, a winter rotation had a higher performance under the YWPS, the fall rotation had a higher performance under the LWPS and under the GWPS there was little difference. The results showed, that depending on the basin goal, not only do the sub-indicators required change, but also the management practices or approach required to reach those basin goals. This highlights the importance of providing a CWP framework with multiple sub-indicators, suitable to basin needs, to ensure that meeting the SDG 6.4 goal does not jeopardise local objectives. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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13 pages, 2069 KiB

Open AccessArticle

Using Remote Sensing to Analyse Net Land-Use Change from Conflicting Sustainability Policies: The Case of Amsterdam

by Mendel Giezen, Stella Balikci and Rowan Arundel

ISPRS Int. J. Geo-Inf. 2018, 7(9), 381; https://doi.org/10.3390/ijgi7090381 - 19 Sep 2018

Cited by 28 | Viewed by 9692

Abstract

In order to achieve the ambitious Sustainable Development Goal #11 (Sustainable Cities and Communities), an integrative approach is necessary. Complex outcomes such as sustainable cities are the product of a range of policies and drivers that are sometimes at odds with each other. [...] Read more.

In order to achieve the ambitious Sustainable Development Goal #11 (Sustainable Cities and Communities), an integrative approach is necessary. Complex outcomes such as sustainable cities are the product of a range of policies and drivers that are sometimes at odds with each other. Yet, traditional policy assessments often focus on specific ambitions such as housing, green spaces, etc., and are blind to the consequences of policy interactions. This research proposes the use of remote sensing technologies to monitor and analyse the resultant effects of opposing urban policies. In particular, we will look at the conflicting policy goals in Amsterdam between the policy to densify, on the one hand, and, on the other hand, goals of protecting and improving urban green space. We conducted an analysis to detect changes in land-uses within the urban core of Amsterdam, using satellite images from 2003 and 2016. The results indeed show a decrease of green space and an increase in the built-up environment. In addition, we reveal strong fragmentation of green space, indicating that green space is increasingly available in smaller patches. These results illustrate that the urban green space policies of the municipality appear insufficient to mitigate the negative outcomes of the city’s densification on urban green space. Additionally, we demonstrate how remote sensing can be a valuable instrument in investigating the net consequences of policies and urban developments that would be difficult to monitor through traditional policy assessments. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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Review

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28 pages, 15767 KiB

Open AccessReview

The Scope of Earth-Observation to Improve the Consistency of the SDG Slum Indicator

by Monika Kuffer, Jiong Wang, Michael Nagenborg, Karin Pfeffer, Divyani Kohli, Richard Sliuzas and Claudio Persello

ISPRS Int. J. Geo-Inf. 2018, 7(11), 428; https://doi.org/10.3390/ijgi7110428 - 1 Nov 2018

Cited by 64 | Viewed by 9953

Abstract

The continuous increase in deprived living conditions in many cities of the Global South contradicts efforts to make cities inclusive, safe, resilient, and sustainable places. Using examples of Asian, African, and Latin American cities, this study shows the scope and limits of earth [...] Read more.

The continuous increase in deprived living conditions in many cities of the Global South contradicts efforts to make cities inclusive, safe, resilient, and sustainable places. Using examples of Asian, African, and Latin American cities, this study shows the scope and limits of earth observation (EO)-based mapping of deprived living conditions in support of providing consistent global information for the SDG indicator 11.1.1 “proportion of urban population living in slums, informal settlements or inadequate housing”. At the technical level, we compare several EO-based methods and imagery for mapping deprived living conditions, discussing their ability to map such areas including differences in terms of accuracy and performance at the city scale. At the operational level, we compare available municipal maps showing identified deprived areas with the spatial extent of morphological mapped areas of deprived living conditions (using EO) at the city scale, discussing the reasons for inconsistencies between municipal and EO-based maps. We provide an outlook on how EO-based mapping of deprived living conditions could contribute to a global spatial information base to support targeting of deprived living conditions in support of the SDG Goal 11.1.1 indicator, when uncertainties and ethical considerations on data provision are well addressed. Full article

(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))

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