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Journal articles on the topic 'Land use, Urban – Malawi'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Gondwe, James, Mtafu Zeleza A. Manda, and Dominic Kamlomo. "Discriminatory land use planning and flood risk management in Karonga Town, Malawi." Journal of Human Sciences 14, no. 4 (October 30, 2017): 3343. http://dx.doi.org/10.14687/jhs.v14i4.4706.

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This study examines how discriminatory land use planning predisposes the low income residents to flood disaster risks in Karonga town, Malawi. Using a qualitative research design, in-depth interviews were conducted with ten government and non government institutions engaged in land use planning and disaster risk management and traditional leaders. The study showed that theoretical aims of land use planning to improve the living environment remain partial and in certain cases exacerbate risks posed by floods because the planning tool divides the urban landscape into formal and informal spaces. Such separation which coincided with incomes levels forced the marginalised and urban poor to occupy flood-prone areas While literature on flood control promotes an integrated approach to flood risk management, land use planning practice is singled out as a regulatory measure which ironically not only fails to meet the needs, but also increases vulnerability to flood risks, of the urban poor residents. The study further revealed that land use planning has failed to reduce flood disaster risks in informal spaces because it is not compatible with the needs of the urban poor.

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2

Mawenda, John, Teiji Watanabe, and Ram Avtar. "An Analysis of Urban Land Use/Land Cover Changes in Blantyre City, Southern Malawi (1994–2018)." Sustainability 12, no. 6 (March 18, 2020): 2377. http://dx.doi.org/10.3390/su12062377.

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Rapid and unplanned urban growth has adverse environmental and social consequences. This is prominent in sub-Saharan Africa where the urbanisation rate is high and characterised by the proliferation of informal settlements. It is, therefore, crucial that urban land use/land cover (LULC) changes be investigated in order to enhance effective planning and sustainable growth. In this paper, the spatial and temporal LULC changes in Blantyre city were studied using the integration of remotely sensed Landsat imageries of 1994, 2007 and 2018, and a geographic information system (GIS). The supervised classification method using the support vector machine algorithm was applied to generate the LULC maps. The study also analysed the transition matrices derived from the classified map to identify prominent processes of changes for planning prioritisation. The results showed that the built-up class, which included urban structures such as residential, industrial, commercial and public installations, increased in the 24-year study period. On the contrary, bare land, which included vacant lands, open spaces with little or no vegetation, hilly clear-cut areas and other fallow land, declined over the study period. This was also the case with the vegetation class (i.e., forests, parks, permanent tree-covered areas and shrubs). The post-classification results revealed that the LULC changes during the second period (2007–2018) were faster compared to the first period (1994–2007). Furthermore, the results revealed that the increase in built-up areas systematically targeted the bare land and avoided the vegetated areas, and that the vegetated areas were systematically cleared to bare land during the study period (1994–2018). The findings of this study have revealed the pressure of human activities on the land and natural environment in Blantyre and provided the basis for sustainable urban planning and development in Blantyre city.

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3

Chimaimba, Frank B., Dalitso Kafumbata, Tembo Chanyenga, and Sosten Chiotha. "Urban tree species composition and diversity in Zomba city, Malawi: Does land use type matter?" Urban Forestry & Urban Greening 54 (October 2020): 126781. http://dx.doi.org/10.1016/j.ufug.2020.126781.

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4

Caceres, Noelia, and Francisco G. Benitez. "Supervised Land Use Inference from Mobility Patterns." Journal of Advanced Transportation 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/8710402.

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This paper addresses the relationship between land use and mobility patterns. Since each particular zone directly feeds the global mobility once acting as origin of trips and others as destination, both roles are simultaneously used for predicting land uses. Specifically this investigation uses mobility data derived from mobile phones, a technology that emerges as a useful, quick data source on people’s daily mobility, collected during two weeks over the urban area of Malaga (Spain). This allows exploring the relevance of integrating weekday-weekend trip information to better determine the category of land use. First, this work classifies patterns on trips originated and terminated in each zone into groups by means of a clustering approach. Based on identifiable relationships between activity and times when travel peaks appear, a preliminary categorization of uses is provided. Then, both grouping results are used as input variables in a K-nearest neighbors (KNN) classification model to determine the exact land use. The KNN method assumes that the category of an object must be similar to the category of the closest neighbors. After training the models, the findings reveal that this approach provides a precise land use categorization, yielding the best accuracy results for the major categories of land uses in the studied area. Moreover, as a result, the weekend data certainly contributes to finding more precise land uses as those obtained by just weekday data. In particular, the percentage of correctly predicted categories using both weekday and weekend is around 80%, while just weekday data reach 67%. The comparison with actual land uses also demonstrates that this approach is able to provide useful information, identifying zones with a specific clear dominant use (residential, industrial, and commercial), as well as multiactivity zones (mixed). This fact is especially useful in the context of urban environments where multiple activities coexist.

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5

Ngwira, Susan, and Teiji Watanabe. "An Analysis of the Causes of Deforestation in Malawi: A Case of Mwazisi." Land 8, no. 3 (March 15, 2019): 48. http://dx.doi.org/10.3390/land8030048.

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Deforestation is recognized as a major driver of the loss of biodiversity and ecosystem services. It also disturbs natural processes such as biogeochemical, hydrological, and ecological cycles. In Malawi, deforestation is estimated to be responsible for the loss of 33,000 hectares per year, and is mainly attributed to agriculture expansion, tobacco growing, and excessive use of biomass. However, little research has been conducted at either the local level or that of forests located on customary land. This research aimed to identify and analyze the underlying driving factors associated with the proximate factors of agriculture expansion, tobacco growing, and brick burning in Mwazisi. Landsat images for 1991, 2004, and 2017 were downloaded from the United States Geological Survey website and used to analyze changes in forest cover. Interviews with households (n = 399) and Natural Resource Committee members, a focus group discussion with key officers, and observations were conducted during field data collection in 2017. The results of the land cover analysis showed that forest covered 66% of the study area in 1991, and by 2017 it had decreased to 45.8%. Most households depend on wood from customary land forests for tobacco curing (69%) and brick burning (68%). Furthermore, 47.6% of the households have expanded their agriculture land by approximately 0.57 hectares during the past 15 years. The interview survey and the focus group discussion identified that the underlying driving factors towards these anthropogenic activities are: (a) population growth, (b) poverty, (c) expensive alternative building materials, (d) lack of awareness, (e) lack of resources, (f) lack of commitment from the tobacco companies, and (g) market system of the cash crops grown in the area. In conclusion, a set of economic, institutional, social, and demographic factors, which are associated with imbalanced relationship between rural and urban areas, underpin agriculture expansion, tobacco growing, and brick burning, and have thereby contributed to the decline of the forest cover in Mwazisi, Malawi.

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6

Gomo, Fortune Faith, Christopher Macleod, John Rowan, Jagadeesh Yeluripati, and Kairsty Topp. "Supporting better decisions across the nexus of water, energy and food through earth observation data: case of the Zambezi basin." Proceedings of the International Association of Hydrological Sciences 376 (February 1, 2018): 15–23. http://dx.doi.org/10.5194/piahs-376-15-2018.

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Abstract. The water–energy–food (WEF) nexus has been promoted in recent years as an intersectional concept designed to improve planning and regulatory decision-making across the three sectors. The production and consumption of water, energy and food resources are inextricably linked across multiple spatial scales (from the global to the local), but a common feature is competition for land which through different land management practices mediates provisioning ecosystem services. The nexus perspective seeks to understand the interlinkages and use systems-based thinking to frame management options for the present and the future. It aims to highlight advantage and minimise damaging and unsustainable outcomes through informed decisions regarding trade-offs inclusive of economic, ecological and equity considerations. Operationalizing the WEF approach is difficult because of the lack of complete data, knowledge and observability – and the nature of the challenge also depends on the scale of the investigation. Transboundary river basins are particularly challenging because whilst the basin unit defines the hydrological system this is not necessarily coincident with flows of food and energy. There are multiple national jurisdictions and geopolitical relations to consider. Land use changes have a profound influence on hydrological, agricultural, energy provisioning and regulating ecosystem services. Future policy decisions in the water, energy and food sectors could have profound effects, with different demands for land and water resources, intensifying competition for these resources in the future. In this study, we used Google Earth Engine (GEE) to analyse the land cover changes in the Zambezi river basin (1.4 million km2) from 1992 to 2015 using the European Space Agency annual global land cover dataset. Early results indicate transformative processes are underway with significant shifts from tree cover to cropland, with a 4.6 % loss in tree cover and a 16 % gain in cropland during the study period. The changes were found to be occurring mainly in the eastern (Malawi and Mozambique) and southern (Zimbabwe and southern Zambia) parts of the basin. The area under urban land uses was found to have more than doubled during the study period gearing urban centres increasingly as the foci for resource consumption. These preliminary findings are the first step in understanding the spatial and temporal interlinkages of water, energy and food by providing reliable and consistent evidence spanning the local, regional, national and whole transboundary basin scale.

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7

Tione, Sarah E., and Stein T. Holden. "Urban proximity, demand for land and land shadow prices in Malawi." Land Use Policy 94 (May 2020): 104509. http://dx.doi.org/10.1016/j.landusepol.2020.104509.

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8

Jagger, Pamela, and Carolina Perez-Heydrich. "Land use and household energy dynamics in Malawi." Environmental Research Letters 11, no. 12 (November 28, 2016): 125004. http://dx.doi.org/10.1088/1748-9326/11/12/125004.

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9

Wei, Yehua. "Urban land use transformation and determinants of urban land use size in China." GeoJournal 30, no. 4 (August 1993): 435–40. http://dx.doi.org/10.1007/bf00807224.

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10

Marsal-Llacuna, Maria-Lluïsa, and Maria-Beatriz López-Ibáñez. "Smart Urban Planning: Designing Urban Land Use from Urban Time Use." Journal of Urban Technology 21, no. 1 (January 2, 2014): 39–56. http://dx.doi.org/10.1080/10630732.2014.884385.

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11

Esparza, Adrian, and Grant Ian Thrall. "Land Use and Urban Form." Economic Geography 64, no. 3 (July 1988): 291. http://dx.doi.org/10.2307/144081.

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12

Tang, Yunbin. "Urban land use in China." Land Use Policy 6, no. 1 (January 1989): 53–63. http://dx.doi.org/10.1016/0264-8377(89)90007-0.

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13

Heikkonen, Jukka, and Aristide Varfis. "Land Cover/Land Use Classification of Urban Areas." International Journal of Pattern Recognition and Artificial Intelligence 12, no. 04 (June 1998): 475–89. http://dx.doi.org/10.1142/s0218001498000300.

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This paper proposes a method for remote sensing based land cover/land use classification of urban areas. The method consists of the following four main stages: feature extraction, feature coding, feature selection and classification. In the feature extraction stage, statistical, textural and Gabor features are computed within local image windows of different sizes and orientations to provide a wide variety of potential features for the classification. Then the features are encoded and normalized by means of the Self-Organizing Map algorithm. For feature selection a CART (Classification and Regression Trees) based algorithm was developed to select a subset of features for each class within the classification scheme at hand. The selected subset of features is not attached to any specific classifier. Any classifier capable of representing possible skewed and multi-modal feature distributions can be employed, such as multi-layer perceptron (MLP) or k-nearest neighbor (k-NN). The paper reports experiments in land cover/land use classification with the Landsat TM and ERS-1 SAR images gathered over the city of Lisbon to show the potentials of the proposed method.

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14

Haack, Barry, Ron Mahabir, and John Kerkering. "Remote sensing-derived national land cover land use maps: a comparison for Malawi." Geocarto International 30, no. 3 (September 4, 2014): 270–92. http://dx.doi.org/10.1080/10106049.2014.952355.

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15

Pond, Bruce, and Maurice Yeates. "RURAL/URBAN LAND CONVERSION II: IDENTIFYING LAND IN TRANSITION TO URBAN USE." Urban Geography 15, no. 1 (January 1, 1994): 25–44. http://dx.doi.org/10.2747/0272-3638.15.1.25.

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16

KIM, June young, Satoshi HAGISHIMA, Akira OHGAI, Noboru IWAO, and Shigeyuki KUROSE. "ANALYSIS OF URBAN LAND USE STRUCTURE USING LAND USE TRANSITION MATRIX." Journal of Architecture, Planning and Environmental Engineering (Transactions of AIJ) 424 (1991): 69–78. http://dx.doi.org/10.3130/aijax.424.0_69.

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17

Chirwa, Wiseman Chijere. "Land use and extension services at Wovwe Rice Scheme, Malawi." Development Southern Africa 19, no. 2 (June 2002): 307–27. http://dx.doi.org/10.1080/03768350020013543.

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18

TASHIRO, YOICHI. "Urban Agriculture and Planned Land Use." JOURNAL OF RURAL PLANNING ASSOCIATION 17, no. 2 (1998): 157–61. http://dx.doi.org/10.2750/arp.17.157.

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19

Saphores, Jean-Daniel. "Environment, Land Use and Urban Policy." Transportation Research Part A: Policy and Practice 37, no. 2 (February 2003): 183–86. http://dx.doi.org/10.1016/s0965-8564(02)00037-x.

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20

Peiser, Richard. "Environment, land use and urban policy." Regional Science and Urban Economics 30, no. 6 (December 2000): 719–23. http://dx.doi.org/10.1016/s0166-0462(00)00049-1.

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21

Batty, M., and P. A. Longley. "The Morphology of Urban Land Use." Environment and Planning B: Planning and Design 15, no. 4 (December 1988): 461–88. http://dx.doi.org/10.1068/b150461.

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22

Rossi-Hansberg, Esteban. "Optimal urban land use and zoning." Review of Economic Dynamics 7, no. 1 (January 2004): 69–106. http://dx.doi.org/10.1016/s1094-2025(03)00056-5.

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23

Plaza, Krystyna. "URBAN LAND USE MANAGEMENT IN POLAND." International Journal of Public Administration 24, no. 2 (January 30, 2001): 197–209. http://dx.doi.org/10.1081/pad-100000551.

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24

Monroe, Charles B., and Wayne Attoe. "Transit, Land Use, and Urban Form." Geographical Review 79, no. 4 (October 1989): 481. http://dx.doi.org/10.2307/215123.

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25

Wernstedt, Kris, and Robert Hersh. "Urban Land Use and Superfund Cleanups." Journal of Urban Affairs 20, no. 4 (December 1998): 459–74. http://dx.doi.org/10.1111/j.1467-9906.1998.tb00432.x.

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26

Fang, Fang, Xiaohui Yuan, Lu Wang, Yuanyuan Liu, and Zhongwen Luo. "Urban Land-Use Classification From Photographs." IEEE Geoscience and Remote Sensing Letters 15, no. 12 (December 2018): 1927–31. http://dx.doi.org/10.1109/lgrs.2018.2864282.

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27

Simmie, James, Simon Olsberg, and Christopher Tunnell. "Urban containment and land use planning." Land Use Policy 9, no. 1 (January 1992): 36–46. http://dx.doi.org/10.1016/0264-8377(92)90033-s.

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28

Koroso, Nesru H., Jaap A. Zevenbergen, and Monica Lengoiboni. "Urban land use efficiency in Ethiopia: An assessment of urban land use sustainability in Addis Ababa." Land Use Policy 99 (December 2020): 105081. http://dx.doi.org/10.1016/j.landusepol.2020.105081.

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29

Kalua, Amos. "Urban Residential Building Energy Consumption by End-Use in Malawi." Buildings 10, no. 2 (February 18, 2020): 31. http://dx.doi.org/10.3390/buildings10020031.

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Buildings account for about 40% of the global energy consumption and this energy demand is projected to continue growing over the next few decades. Residential buildings are responsible for over 60% of this consumption pattern with commercial buildings being responsible for the remainder. While residential building energy consumption constitutes about 20% of the total consumption in the developed world, it constitutes up to more than 50% in the sub-Sahara African region. The growing consumption of energy has raised concerns over the impacts on the environment, supply difficulties, and depletion of resources. In efforts toward addressing these concerns, the need for effective management of energy resources and adequate planning for energy infrastructure cannot be overemphasized within the building industry in general and the residential building sector in particular. Toward this end, it is necessary to ensure that high quality and high-resolution information on the consumption of energy in buildings is made available. Unfortunately, in many countries within the sub-Sahara African region, building energy consumption information is hardly ever readily available. This study seeks to make a contribution toward this facet of the literature at the greater regional level in general and particularly, in Malawi, a country located in the southern part of Africa. With a grounding in the context of urban residential buildings, the study identifies the key energy end-uses, investigates the proportional mixes of the end-uses and the energy sources and, finally, establishes the periodical per capita energy consumption amounts for the end-uses and the typical residential building unit.

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30

Subudhi, A. P., N. D. Sharma, and Debajit Mishra. "Use of Landsat Thematic Mapper for urban land use/land cover mapping." Journal of the Indian Society of Remote Sensing 17, no. 3 (September 1989): 85–99. http://dx.doi.org/10.1007/bf02995834.

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31

Weiner, Dan, Sam Moyo, Barry Munslow, and Phil O'Keefe. "Land Use and Agricultural Productivity in Zimbabwe." Journal of Modern African Studies 23, no. 2 (June 1985): 251–85. http://dx.doi.org/10.1017/s0022278x00000173.

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Given a continuation of current trends, with increasing population growth and declining food production, Southern Africa (excluding South Africa) which could nearly feed itself during 1979–81, will be only 64 per cent self-sufficient by the turn of the century. Zimbabwe has a particularly important rôle to play in trying to prevent such a disaster. It is by far the most important exporter of food and cash crops in the region, and has been allocated the task of co-ordinating a food-security strategy for the nine member-states of the Southern African Development Co-ordination Conference, namely Angola, Botswana, Lesotho, Malawi, Mozambique, Swaziland, Tanzania, Zambia, and Zimbabwe.

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32

Jack, B. Kelsey. "Private Information and the Allocation of Land Use Subsidies in Malawi." American Economic Journal: Applied Economics 5, no. 3 (July 1, 2013): 113–35. http://dx.doi.org/10.1257/app.5.3.113.

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Efficient targeting of public programs is difficult when the cost or benefit to potential recipients is private information. This study illustrates the potential of self-selection to improve allocational outcomes in the context of a program that subsidizes tree planting in Malawi. Landholders who received a tree planting contract as a result of bidding in an auction kept significantly more trees alive over a three year period than did landholders who received the contract through a lottery. The gains from targeting on private information through the auction represent a 30 percent cost savings per surviving tree for the implementing organization. (JEL D04, D44, D82, O13, Q24, Q28)

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33

Chavula, Geoffrey, Patrick Brezonik, and Marvin Bauer. "Land Use and Land Cover Change (LULC) in the Lake Malawi Drainage Basin, 1982-2005." International Journal of Geosciences 02, no. 02 (2011): 172–78. http://dx.doi.org/10.4236/ijg.2011.22018.

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34

Han, Wenjing, Xiaoling Zhang, and Xian Zheng. "Land use regulation and urban land value: Evidence from China." Land Use Policy 92 (March 2020): 104432. http://dx.doi.org/10.1016/j.landusepol.2019.104432.

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35

Burnett, Perry. "SECTOR LAND USE AND INDUSTRIAL MIX IN URBAN LAND ALLOCATION." Review of Urban & Regional Development Studies 24, no. 1-2 (March 2012): 35–50. http://dx.doi.org/10.1111/j.1467-940x.2012.00187.x.

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36

Myint, Soe W., Elizabeth A. Wentz, and Sam J. Purkis. "Employing Spatial Metrics in Urban Land-use/Land-cover Mapping." Photogrammetric Engineering & Remote Sensing 73, no. 12 (December 1, 2007): 1403–15. http://dx.doi.org/10.14358/pers.73.12.1403.

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37

MacDonald, John M., and Robert J. Stokes. "Gentrification, Land Use, and Crime." Annual Review of Criminology 3, no. 1 (January 13, 2020): 121–38. http://dx.doi.org/10.1146/annurev-criminol-011419-041505.

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Over the past twenty years, many US cities have seen urban revitalization and population changes associated with an increased desire for urban living among the affluent. As inner-city neighborhoods become gentrified, they are more likely to witness the construction of new buildings and homes, the conversion of industrial spaces to mixed-used developments, expanded access to mass transit, and the arrival of coffee shops and other urban amenities. In this review, we take stock of what is known about the impact of gentrification and land-use changes on neighborhood crime. We summarize research conducted since the period of urban revitalization that started in the 1990s as well as studies that have a quasi-experimental design. We find that gentrification and associated changes to land use tend to reduce crime in neighborhoods. Our findings are tempered by the need for greater conceptual clarity on how to measure when a neighborhood has gentrified and a clearer examination of the spatial displacement of crime. We conclude with a discussion on the need for criminologists to partner with urban planners to study how changes in the land use of cities can be made to generate crime reductions that benefit all places and, finally, detail some promising directions for future research.

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38

Lu, Dengsheng, and Qihao Weng. "Use of impervious surface in urban land-use classification." Remote Sensing of Environment 102, no. 1-2 (May 2006): 146–60. http://dx.doi.org/10.1016/j.rse.2006.02.010.

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39

Ritsema van Eck, Jan, and Eric Koomen. "Characterising urban concentration and land-use diversity in simulations of future land use." Annals of Regional Science 42, no. 1 (July 25, 2007): 123–40. http://dx.doi.org/10.1007/s00168-007-0141-7.

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40

Burns, Elizabeth K. "LAND USE PLANNING AND URBAN SPATIAL STRUCTURE." Urban Geography 9, no. 2 (March 1988): 209–16. http://dx.doi.org/10.2747/0272-3638.9.2.209.

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41

Anugraha, Adindha, Hone-Jay Chu, and Muhammad Ali. "Social Sensing for Urban Land Use Identification." ISPRS International Journal of Geo-Information 9, no. 9 (September 15, 2020): 550. http://dx.doi.org/10.3390/ijgi9090550.

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The utilization of urban land use maps can reveal the patterns of human behavior through the extraction of the socioeconomic and demographic characteristics of urban land use. Remote sensing that holds detailed and abundant information on spectral, textual, contextual, and spatial configurations is crucial to obtaining land use maps that reveal changes in the urban environment. However, social sensing is essential to revealing the socioeconomic and demographic characteristics of urban land use. This data mining approach is related to data cleaning/outlier removal and machine learning, and is used to achieve land use classification from remote and social sensing data. In bicycle and taxi density maps, the daytime destination and nighttime origin density reflects work-related land uses, including commercial and industrial areas. By contrast, the nighttime destination and daytime origin density pattern captures the pattern of residential areas. The accuracy assessment of land use classified maps shows that the integration of remote and social sensing, using the decision tree and random forest methods, yields accuracies of 83% and 86%, respectively. Thus, this approach facilitates an accurate urban land use classification. Urban land use identification can aid policy makers in linking human activities to the socioeconomic consequences of different urban land uses.

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42

Romano, Bernardino, and Francesco Zullo. "Models of Urban Land Use in Europe." International Journal of Agricultural and Environmental Information Systems 4, no. 3 (July 2013): 80–97. http://dx.doi.org/10.4018/ijaeis.2013070105.

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The aim of this paper is to examine available homogenous data on urban conversion of land in Western European countries and determine whether they are suitable to make an international comparison between land policies and management behaviour at the local level. This paper provides some results obtained from currently available information, but it stresses major data production criticalities which hinder the performance of comparable and reliable overall statistical studies. Conclusions stress the need for greater detail in the production of primary data on the features and magnitude of territorial urbanisation in Europe, as the EEA is doing for main cities. Moreover, this paper includes some remarks on the contents of the preliminary documents of EU soil directive. In particular, it focuses on the issue of urban transformation thresholds over time, a topic that has already been tackled by some northern European countries, however using techniques which cannot be applied as they are to all other countries.

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43

Raman, Rewati, and Uttam Kumar Roy. "Taxonomy of urban mixed land use planning." Land Use Policy 88 (November 2019): 104102. http://dx.doi.org/10.1016/j.landusepol.2019.104102.

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44

Steurer, Miriam, and Caroline Bayr. "Measuring urban sprawl using land use data." Land Use Policy 97 (September 2020): 104799. http://dx.doi.org/10.1016/j.landusepol.2020.104799.

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45

Wagner, Peter, and Michael Wegener. "Urban Land Use, Transport and Environment Models." disP - The Planning Review 43, no. 170 (January 2007): 45–56. http://dx.doi.org/10.1080/02513625.2007.10556988.

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46

Godschalk, David R. "A Review of “Urban land use planning”." Journal of the American Planning Association 78, no. 1 (January 2012): 105–6. http://dx.doi.org/10.1080/01944363.2011.644195.

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47

Mincyte, Diana, Monica J. Casper, and CL Cole. "Sports, Environmentalism, Land Use, and Urban Development." Journal of Sport and Social Issues 33, no. 2 (April 6, 2009): 103–10. http://dx.doi.org/10.1177/0193723509335690.

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48

Song, Yan, Louis Merlin, and Daniel Rodriguez. "Comparing measures of urban land use mix." Computers, Environment and Urban Systems 42 (November 2013): 1–13. http://dx.doi.org/10.1016/j.compenvurbsys.2013.08.001.

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49

King, Gavin, Marek Roland-Mieszkowski, Timothy Jason, and Daniel G. Rainham. "Noise Levels Associated with Urban Land Use." Journal of Urban Health 89, no. 6 (June 16, 2012): 1017–30. http://dx.doi.org/10.1007/s11524-012-9721-7.

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Bondarev, Boris, Sergey Nosov, Oleg Antipov, and Lusine Papikian. "Urban land use planning within the system of sustainable urban development management." E3S Web of Conferences 110 (2019): 02001. http://dx.doi.org/10.1051/e3sconf/201911002001.

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Abstract:

Agricultural and forest lands near settlements are main reserve for expansion of urban areas. Thus, among 148.5 thousand hectares of lands added to Moscow city territory in 2012, 72.2 thousand hectares or 48% were occupied by agricultural and forest lands. Urban areas are characterized by excessively high intensity of land use, land depletion, deterioration in environmental quality and decline in sustainability of urban development. The paper presents the results of analysis of urban land use planning system in the interests of sustainable development of urban territories. The object of the study is the land that is part of Moscow, which is planned to be developed in the coming decades. The authors propose an algorithm for urban development of such areas, which takes into account the quality of land. Design calculations for areas under development were carried out for Shchapovskoye settlement in New Moscow as an example. In addition, the paper covers aspects of land management when developing agricultural land within cities. The authors developed a classification of agricultural land according to a criterion of “suitability for urban development”. The suggested classification has been applied to achieve the objectives of planning urban land use development, determining the order of construction on agricultural lands within the system of sustainable urban development management.

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