scholarly journals Adaptability Evaluation of Human Settlements in Chengdu Based on 3S Technology

2021 ◽  
Author(s):  
Wende Chen ◽  
kun zhu ◽  
QUN WU ◽  
Yankun CAI ◽  
Yutian LU ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Development Planning ◽  
Residential Environment ◽  
Vegetation Coverage ◽  
High Grade ◽  
Human Settlement ◽  
Human Settlements ◽  
Suitability Index ◽  
Correlation Degree

Abstract Taking Chengdu as the research object, the natural eco-environmental factors such as topography, climate, vegetation, land use and vegetation cover were selected, together with human disturbance factors such as traffic and GDP, and the index weights were calculated by AHP. Based on 3S technology, projection transformation, remote sensing interpretation, information extraction and analysis are carried out, and evaluation model of Chengdu's residential environment adaptability is constructed, which reflects the zoning and spatial distribution characteristics of Chengdu's residential environment adaptability. The results show that: 1) The adaptability index of Chengdu's human settlement environment is between 15.98 and 76.75, and the suitability of human settlement environment is gradually decreasing from the middle to the east and west of Chengdu, and most areas are restricted by human production activities and natural conditions. 2) According to the actual situation, the suitability index can be divided into High-grade suitable areas (284.36 km2, 2.01%), relatively High-grade suitable areas (1802.13 km2, 12.71%), moderately suitable areas (3721.49 km2, 26.24%) and low suitable areas (3731.49 km2, 26.31%). 3) The correlation degree between the spatial distribution of Chengdu population and each index factor is as follows: per capita GDP> topographic relief > temperature and humidity > vegetation coverage > traffic network density > land use > hydrological factors. 4) There is a good correlation between Chengdu human settlements suitability index and the current population density grid layer, and its correlation coefficient is 0.7326. 5) The leading impact indicators of human settlements in different regions are different. The results show that the natural environment conditions in Chengdu are superior and the ecological environment quality is relatively stable, but the human settlement suitability index in the southeast and Longmenshan areas of Chengdu is relatively low. Therefore, in the future development planning of Chengdu, it is necessary to combine the actual environmental conditions and resource carrying capacity, and rationally carry out urban optimization and beautiful countryside construction.

scholarly journals Spatial differentiation of comprehensive suitability sustainable development for urban human settlements based on GIS：A case study of Liaoning Province, China

2021 ◽  
Author(s):  
Yingying Guan ◽  
Xueming Li ◽  
Songbo Li ◽  
Shenzhen Tian
Keyword(s):  
Spatial Distribution ◽  
Theoretical Basis ◽  
Spatial Differentiation ◽  
Liaoning Province ◽  
Human Settlement ◽  
Human Settlements ◽  
Suitability Index ◽  
Social And Economic Development ◽  
Urban Human Settlements

Abstract The comprehensive suitability of regional human settlements is of great significance to the development and spatial distribution of regional human settlements and regional social and economic development. In this study, based on the traditional evaluation of the natural suitability of the human settlements, this study adds humanistic indicators to comprehensively evaluate the suitability of the human settlements in Liaoning, China. In particular, we sought to uncover the spatial differentiation law of the comprehensive suitability of these settlements and its correlations with population density and GDP density, provide a theoretical basis for urban human settlements planning and governance. The main conclusions were as follows: (1) the natural suitability index in Liaoning Province presents the law of longitudinal spatial differentiation from northeast to southwest, which follows the direction of the mountains; (2) the highest to lowest humanistic suitability indexes were as follows: the central, eastern, and western regions; (3) the highest to lowest spatial differentiations of the comprehensive suitability of the human settlements were as follows: the central and coastal, eastern, and western regions;(4) the spatial distribution of population–economy density in Liaoning Province was basically consistent with the spatial distribution of the comprehensive suitability index of human settlements, The population economy is concentrated in the areas with the best and moderate human settlements. Ultimately, we found that the distributions of population–economy and human settlement suitability were relatively coordinated and that highly suitable land was already fully utilized.

scholarly journals Identification of Dominant Factors Affecting Soil Erosion and Water Yield within Ecological Red Line Areas

2020 ◽  
Vol 12 (3) ◽  
pp. 399 ◽  
Author(s):  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Huan Wang ◽  
Liyuan Zuo
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Water Yield ◽  
Land Use Type ◽  
Functional Areas ◽  
Red Line

Soil conservation and water retention are important metrics for designating key ecological functional areas and ecological red line (ERL) areas. However, research on the quantitative identification of dominant environmental factors in different ecological red line areas remains relatively inadequate, which is unfavorable for the zone-based management of ecological functional areas. This paper presents a case study of Beijing’s ERL areas. In order to objectively reflect the ecological characteristics of ERL areas in Beijing, which is mainly dominated by mountainous areas, the application of remote sensing data at a high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations as well as soil erosion and water yield were calculated using the revised universal soil loss equation (RUSLE) and integrated valuation of ecosystem services and tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type, and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing’s ERL areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different ERL areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing’s ERL areas, explaining greater than 30% of its spatial heterogeneity. Land use type could explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various ERL areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in ERL areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ERL areas. Thus, in efforts to enhance ERL protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ERL areas.

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

2019 ◽  
Vol 8 (2) ◽  
pp. 96 ◽  
Author(s):  
Michele Melchiorri ◽  
Martino Pesaresi ◽  
Aneta Florczyk ◽  
Christina Corbane ◽  
Thomas Kemper
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Spatial Distribution ◽  
Distribution Density ◽  
Census Data ◽  
Spatial Information ◽  
Human Settlement ◽  
Land Use Efficiency ◽  
Multi Temporal ◽  
Use Efficiency

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.

Environmental Suitability Evaluation for Human Settlements in Arid Inland River Basin — A Case Study on the Shiyang River Basin

2012 ◽  
Vol 518-523 ◽  
pp. 4874-4884
Author(s):  
Wei Wei ◽  
Pei Ji Shi ◽  
Jun Zhao ◽  
Xu Feng Wang ◽  
Xue Ping Wang
Keyword(s):  
Spatial Pattern ◽  
River Basin ◽  
Residential Environment ◽  
General Nature ◽  
Slope Aspect ◽  
Badain Jaran Desert ◽  
Human Settlement ◽  
Human Settlements ◽  
Environmental Suitability ◽  
Shiyang River Basin

The paper selects slope, aspect, Relief Degree of Land Surface, land use, vegetation index, hydrology, transportation density and climate as evaluation indexes and sets up the Human Settlements Environmental Index (HEI) model to evaluate the environmental suitability for Human Settlements in Shiyang river basin. Through using spatial analysis technology of GIS such as spatial overlay analysis, buffer analysis and density analysis to establish the spatial situation of nature suitability and spatial pattern for human settlement. The Results showed that: the index of nature suitability for human settlement in Shiyang river basin was between 17.13 and 84.32. In general, nature suitability for human settlement decreased from southwest to northeast. Saw from area pattern, the suitable region mainly distributed in Minqin oasis, Wuwei oasis and Changning basin, which accounting for about1080.01 km2, 2.59% of the total area. Rather and comparatively suitable region mainly distributed around the county in Gulang, Yongchang and north of Tianzhu, which accounting for about1100.30 km2.The common suitable region mainly distributed outside of the county inYongchang, Jinchuan and most area of Minqin county, which accounting for about 23328.04km2, 56.08% of the total area. The unsuitable region mainly distributed upstream and north of river, which accounting for about 9937.60 km2, 23.89% of the total area. Meanwhile, the least suitable region distributed around the Qilian Mountain which covered by snow and cold desert and the intersecting area between Tenger Desert and Badain Jaran Desert. The total area was about 6154.05 km2, which accounting for 14.79% of the total area. Suitable regions for human inhabitance mainly distributed around rivers in the form of ribbons and batches, while others are scattered. Their distribution pattern was identical with the residential spatial pattern. In addition, the relationships between HEI and some factors were also analyzed. There was a clear logarithm correlation between situation of residential environment and population, that is, the correlation coefficient between evaluation value and population density reached 0.851. There was also positive correlation between situation of residential environment and economics, which reached 0.845 between evaluation value of residential environment and GDP. Results also showed the environment was out of bearing the existing population in Shiyang river basin. Spatial distribution of population was profoundly affected by severe environment such as the expanded deserts, the wavy terrains, and the changeful climate. Surface water shortage and slowly economic growth was the bottleneck of nature suitability for human settlement in Shiyang river basin. So according to these problems and various planning, some of residential parts need to relocate in order to improve situation of residential environment.

CLUE-S Model-Based Simulation of Land Use Dynamic Variation in Yangzhou Urban

2013 ◽  
Vol 347-350 ◽  
pp. 3247-3251
Author(s):  
Li Wang ◽  
Xi Min Cui ◽  
De Bao Yuan ◽  
Yi Zhao ◽  
Xue Qian Hong
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Urban Area ◽  
Urban Space ◽  
Development Planning ◽  
Model Parameters ◽  
Gis Technology ◽  
Simulation Accuracy ◽  
S Model ◽  
Land Use Maps

Land Use/Cover Change (LUCC) is a commonly concerned issue. The CLUE-S model was applied to Yangzhou urban area in this paper to simulate the land use spatial distribution in the urban area from 2003 to 2010. Combined with RS & GIS technology, three periods of remote sensing images were firstly preprocessed and three periods of land-use maps were obtained by means of object-oriented method. Then, corresponding model parameters were defined in the CLUE-S model to obtain the spatial distribution of land use of Yangzhou urban in 2003~2010. After that, the extracted and the simulated land use maps in 2007 were compared to evaluate the simulation accuracy. CLUE-S model can be used to simulate the distribution pattern of the development of smaller-scale regional urban space, to provide guidance for the smaller scale urban development planning, and is worthy of popularization and application of land use and land cover change model.

Identification of Dominant Factors Affecting Soil Erosion and Water Yield within Key Ecological Functional Areas

2020 ◽  
Author(s):  
Jiangbo Gao ◽  
Yuan Jiang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Water Yield ◽  
Land Use Type ◽  
Functional Areas

<p>Soil conservation and water retention are important metrics for designating key ecological functional areas. However, research on the quantitative identification of dominant environmental factors in different ecological functional areas remains relatively inadequate, which is unfavorable for zone-based management of key ecological functional areas. This paper presents a case study of Beijing’s key ecological functional areas. In order to objectively reflect the ecological characteristics of key ecological functional areas in Beijing which is mainly dominated by mountainous areas, the application of remote sensing data about high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations, soil erosion and water yield were calculated using the Revised Universal Soil Loss Equation (RUSLE) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing’s key ecological functional areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different key ecological function areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing’s key ecological function areas, explaining greater than 30% of its spatial heterogeneity. Land use type can explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various key ecological functional areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in key ecological functional areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ecological functional areas. Thus, in efforts to enhance key ecological functional areas protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ecological functional areas.</p>

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

2018 ◽  
Author(s):  
Michele Melchiorri ◽  
Martino Pesaresi ◽  
Aneta J. Florczyk ◽  
Christina Corbane ◽  
Thomas Kemper
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Spatial Distribution ◽  
Distribution Density ◽  
Census Data ◽  
Spatial Information ◽  
Human Settlement ◽  
Land Use Efficiency ◽  
Multi Temporal ◽  
Use Efficiency

The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics and knowledge describing the human presence on the planet 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 factors are observed in the long-term temporal domain and per uniform surface units in order to support trends and indicators for monitoring the implementation of international framework agreements. The GHSL uses various input data including global, multi-temporal archives of fine-scale satellite imagery, census data, and volunteered geographic information. In this paper, we present the characteristics of GHSL information to demonstrate how original frameworks of data and tools rooted on Earth Observation could support Sustainable Development Goals monitoring. In particular, we demonstrate the reach of gridded, open and free, local yet globally consistent, multi-temporal data in filling the data gap for the Sustainable Development Goal 11. Our experiments produce a global estimate for the Land Use Efficiency indicator (SDG 11.3.1) for 10,000 urban centers, calculating the ratio of land consumption to population growth rate that took place between 1990 and 2015. The results of our research demonstrate that there is a potential to lift SDG 11.3.1 from a tier 2 as GHSL provides a global baseline for the essential variables called by the SDG 11.3.1 metadata.

scholarly journals Agroforestry Systems of the Tehuacán-Cuicatlán Valley: Land Use for Biocultural Diversity Conservation

Land ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 24
Author(s):  
Mariana Vallejo ◽  
M. Isabel Ramírez ◽  
Alejandro Reyes-González ◽  
Jairo López-Sánchez ◽  
Alejandro Casas
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Agroforestry Systems ◽  
World Heritage Site ◽  
Biocultural Diversity ◽  
Semiarid Region ◽  
Agricultural Land Use ◽  
Visual Interpretation ◽  
Natural Ecosystems ◽  
Human Settlements

The Tehuacán-Cuicatlán Valley, Mexico, is the semiarid region with the richest biodiversity of North America and was recently recognized as a UNESCO's World Heritage site. Original agricultural practices remain to this day in agroforestry systems (AFS), which are expressions of high biocultural diversity. However, local people and researchers perceive a progressive decline both in natural ecosystems and AFS. To assess changes in location and extent of agricultural land use, we carried out a visual interpretation of very-high resolution imagery and field work, through which we identified AFS and conventional agricultural systems (CAS) from 1995 to 2003 and 2012. We analyzed five communities, representative of three main ecological and agricultural zones of the region. We assessed agricultural land use changes in relation to conspicuous landscape features (relief, rivers, roads, and human settlements). We found that natural ecosystems cover more than 85% of the territory in each community, and AFS represent 51% of all agricultural land. Establishment and permanence of agricultural lands were strongly influenced by gentle slopes and the existence of roads. Contrary to what we expected, we recorded agricultural areas being abandoned, thus favoring the regeneration of natural ecosystems, as well as a 9% increase of AFS over CAS. Agriculture is concentrated near human settlements. Most of the studied territories are meant to preserve natural ecosystems, and traditional AFS practices are being recovered for biocultural conservation.

The sectoral and spatial distribution of multilateral aid for human settlements

1983 ◽  
Vol 7 (1-2) ◽  
pp. 103-127 ◽  
Author(s):  
Silvia Blitzer ◽  
Jorge E. Hardoy ◽  
David Satterthwaite
Keyword(s):  
Spatial Distribution ◽  
Human Settlements ◽  
Multilateral Aid
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