scholarly journals Critical Commentary: Need for an Integrated Deprived Area “Slum” Mapping System (IDeAMapS) in LMICs

2019 ◽  
Author(s):  
Dana Thomson ◽  
Monika Kuffer ◽  
Gianluca Boo ◽  
Beatrice Hati ◽  
Tais Grippa ◽  
...  
Keyword(s):  
Urban Areas ◽  
Informal Settlement ◽  
Social Characteristics ◽  
Multiple Sources ◽  
Neighborhood Deprivation ◽  
Household Level ◽  
The People ◽  
Critical Commentary ◽  
Deprived Neighborhoods

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This diverse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.

scholarly journals Critical Commentary: Need for an Integrated Deprived Area “Slum” Mapping System (IDeAMapS) in LMICs

2019 ◽  
Author(s):  
Dana Thomson ◽  
Monika Kuffer ◽  
Gianluca Boo ◽  
Beatrice Hati ◽  
Tais Grippa ◽  
...  
Keyword(s):  
Urban Areas ◽  
Informal Settlement ◽  
Social Characteristics ◽  
Multiple Sources ◽  
Neighborhood Deprivation ◽  
Household Level ◽  
The People ◽  
Critical Commentary ◽  
Deprived Neighborhoods

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This diverse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.

scholarly journals Need for an Integrated Deprived Area “Slum” Mapping System (IDeAMapS) in LMICs

2020 ◽  
Author(s):  
Dana Thomson ◽  
Monika Kuffer ◽  
Gianluca Boo ◽  
Beatrice Hati ◽  
Tais Grippa ◽  
...  
Keyword(s):  
Urban Areas ◽  
Informal Settlement ◽  
Social Characteristics ◽  
Multiple Sources ◽  
Neighborhood Deprivation ◽  
Household Level ◽  
The People ◽  
Deprived Neighborhoods ◽  
Human Interpretation

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This diverse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.

scholarly journals Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs)

2020 ◽  
Vol 9 (5) ◽  
pp. 80 ◽  
Author(s):  
Dana R. Thomson ◽  
Monika Kuffer ◽  
Gianluca Boo ◽  
Beatrice Hati ◽  
Tais Grippa ◽  
...  
Keyword(s):  
Urban Areas ◽  
Informal Settlement ◽  
Social Characteristics ◽  
Visual Interpretation ◽  
Middle Income ◽  
Household Level ◽  
Middle Income Countries ◽  
The People ◽  
Low And Middle Income

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human (visual) interpretation and machine classification of air or spaceborne imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of public services. We summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making across Low- and Middle-Income Countries (LMICs). We suggest that machine learning models be extended to incorporate social area-level covariates and regular contributions of up-to-date and context-relevant field-based classification of deprived urban areas.

scholarly journals Sharing-Based Co-Housing Categorization. A Structural Overview of the Terms and Characteristics Used in Urban Co-Housing

2020 ◽  
Vol 48 (3-4) ◽  
pp. 331-355
Author(s):  
Annamária Babos ◽  
Julianna Szabó ◽  
Annamária Orbán ◽  
Melinda Benkő
Keyword(s):  
Urban Areas ◽  
Urban Housing ◽  
Research Field ◽  
Social Dimension ◽  
Social Characteristics ◽  
Shared Space ◽  
The Social ◽  
Social Fields ◽  
Urban Housing Development

The European urban areas are growing fast, with many contemporary housing forms. Among these, co-housing forms related to sharing have become a key issue for urban housing development. These housing forms are analysed (their physical and social characteristics or effects) in more and more publications, without a common terminology of this interdisciplinary research field. In our study, based on the overview of existing definitions, characteristics we introduce a comprehensive sharing based categorization that could be valuable for terms and projects, as well. With the note, that the social dimension of sharing methods would not exist without the physical ones, because in co-housing the shared space is the basic criteria. In this paper, we focus on three groups of the social fields of sharing related to housing: the shared creation, the shared tenure, and the shared activities. We conclude the structural approach of our overview unravels new perspectives for the classification of housing forms. Based on our categorization and methodology, we recommend the development of a sharing based scalable classification that measures projects consistent and comparable.Összefoglaló. A városias, beépített területek aránya Európa szerte folyamatosan növekszik, ennek következtében kortárs városi lakhatási formák is teret nyernek. A megosztáshoz kötődő, úgynevezett co-housing formák a kortárs városi lakófejlesztések jelentős részét képzik. Éppen ezért egyre több elemzés és publikáció születik a témában (például a fizikai és társadalmi jellemzőikről vagy azok hatásairól), azonban a lakhatás kutatási területén nincs egyetértés a kifejezések és definíciók használatában. A következő tanulmányban egy, a lakhatási formákat megosztás alapján rendszerező kategorizáció kerül bemutatásra, melynek elméleti és gyakorlati haszna is lehet. A kategorizáció a meglévő kifejezésekre, definíciókra és jellemzőkre egyaránt épít. A co-housing lakhatás alapvető feltétele a – változó méretű és minőségű – megosztott tér, így a társadalmi dimenziók minden esetben kötődnek egy fajta tériséghez is. A lakhatási formákban jelenlévő társadalmi és fizikai dimenziók együttes vizsgálata nem képezi jelen kutatás tárgyát, a társadalmi típusúakra koncentrál: a megosztott létrehozásra, tulajdonlásra és a tevékenységekre. Megállapítható, hogy a kutatás során alkalmazott rendszerezett áttekintés új irányvonalakra mutatott rá a lakhatási formák osztályozásának területén. A tanulmányban tárgyalt megosztás-alapú kategorizálásra és módszertanra alapozva egy, a megosztásra épülő és skálázható osztályozás kidolgozása javasolt, melyben a projektek mérése és összehasonlítása egységes módon történhet.

Hydroponic Nutrient Control System Based on Internet of Things

2019 ◽  
Vol 13 (2) ◽  
Author(s):  
Herman Herman ◽  
Demi Adidrana ◽  
Nico Surantha ◽  
Suharjito Suharjito
Keyword(s):  
Urban Areas ◽  
Human Population ◽  
Mineral Water ◽  
Nearest Neighbor ◽  
Total Dissolved Solids ◽  
K Nearest Neighbor ◽  
Turn On ◽  
Nutrient Film Technique ◽  
Planting Method

The human population significantly increases in crowded urban areas. It causes a reduction of available farming land. Therefore, a landless planting method is needed to supply the food for society. Hydroponics is one of the solutions for gardening methods without using soil. It uses nutrient-enriched mineral water as a nutrition solution for plant growth. Traditionally, hydroponic farming is conducted manually by monitoring the nutrition such as acidity or basicity (pH), the value of Total Dissolved Solids (TDS), Electrical Conductivity (EC), and nutrient temperature. In this research, the researchers propose a system that measures pH, TDS, and nutrient temperature values in the Nutrient Film Technique (NFT) technique using a couple of sensors. The researchers use lettuce as an object of experiment and apply the k-Nearest Neighbor (k-NN) algorithm to predict the classification of nutrient conditions. The result of prediction is used to provide a command to the microcontroller to turn on or off the nutrition controller actuators simultaneously at a time. The experiment result shows that the proposed k-NN algorithm achieves 93.3% accuracy when it is k = 5.

scholarly journals A Study of UVER in Santiago, Chile Based on Long-Term In Situ Measurements (Five Years) and Empirical Modelling

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 368
Author(s):  
Lisdelys González-Rodríguez ◽  
Amauri Pereira de Oliveira ◽  
Lien Rodríguez-López ◽  
Jorge Rosas ◽  
David Contreras ◽  
...  
Keyword(s):  
Urban Areas ◽  
Solar Spectrum ◽  
Sun Exposure ◽  
Great Accuracy ◽  
In Situ Measurements ◽  
Uv Index ◽  
Empirical Modelling ◽  
The People

Ultraviolet radiation is a highly energetic component of the solar spectrum that needs to be monitored because is harmful to life on Earth, especially in areas where the ozone layer has been depleted, like Chile. This work is the first to address the long-term (five-year) behaviour of ultraviolet erythemal radiation (UVER) in Santiago, Chile (33.5° S, 70.7° W, 500 m) using in situ measurements and empirical modelling. Observations indicate that to alert the people on the risks of UVER overexposure, it is necessary to use, in addition to the currently available UV index (UVI), three more erythema indices: standard erythemal doses (SEDs), minimum erythemal doses (MEDs), and sun exposure time (tery). The combination of UVI, SEDs, MEDs, and tery shows that in Santiago, individuals with skin types III and IV are exposed to harmfully high UVER doses for 46% of the time that UVI indicates is safe. Empirical models predicted hourly and daily values UVER in Santiago with great accuracy and can be applied to other Chilean urban areas with similar climate. This research inspires future advances in reconstructing large datasets to analyse the UVER in Central Chile, its trends, and its changes.

Classification of hyperspectral data in urban areas

1998 ◽  
Author(s):  
Bing Zhang ◽  
Jiangui Liu ◽  
Xiangjun Wang ◽  
Changshan Wu
Keyword(s):  
Urban Areas ◽  
Hyperspectral Data

Sustainable Development of Tourism Choice - Eco-Tourism

2013 ◽  
Vol 448-453 ◽  
pp. 4445-4448
Author(s):  
Ming Chong Gu ◽  
Hong Liu
Keyword(s):  
Sustainable Development ◽  
Qualitative Analysis ◽  
Environmental Problems ◽  
Tourism Industry ◽  
Development Model ◽  
The Sustainable Development ◽  
The People ◽  
Domestic Tourism

Along with the development of society and economy, domestic tourism activities is rapidly increased, accompanied by increasing environmental problems brought by the tourism activities is becoming more and more brought to the attention of the people, if our country want to realize the sustainable development of tourism industry, we must replace the old development model to Eco-tourism to meet the needs of tourism and environment. Through qualitative analysis, this paper analyzed the characteristics of the Eco-tourism, and the classification of domestic ecological tourist resources to comb, and put forward some suggestions on developing Eco-tourism, hoping to provide a reference for the development of the domestic Eco-tourism.

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