scholarly journals URBAN EXPANSION: A GEO-SPATIAL APPROACH FOR TEMPORAL MONITORING OF LOSS OF AGRICULTURAL LAND

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1349-1355 ◽  
Author(s):  
N. S. Sumari ◽  
Z. Shao ◽  
M. Huang ◽  
C. A. Sanga ◽  
J. L. Van Genderen
Keyword(s):  
Remote Sensing ◽  
Population Dynamics ◽  
Population Growth ◽  
Agricultural Landscape ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Earth Observation ◽  
Geospatial Data ◽  
Detection Methods ◽  
Logistic Growth

This paper presents some preliminary results from research on monitoring the urban growth of Shenzhen in China. Agriculture is still the pillar of national economies in many countries including China. Thus, agriculture contributes to population growth. Population growth follows either exponential or logistic growth models. These models can be examined using a time-series of geospatial data, mainly historical earth observation imagery from satellites such as LANDSAT. Such multitemporal data may provide insights into settlement analysis as well as on population dynamics and hence, quantify the loss of agricultural land. In this study, LANDSAT data of ten dates, at approximately five yearly intervals from 1977 to 2017 were used. The remote sensing techniques used for analysis of data for 40 years were image selection, then followed by geometric and radiometric corrections and mosaicking. Also, classification, remote sensing image fusion, and change detection methods were used. This research extracted the information on the amount, direction, and speed of urbanization, and hence, the number of hectares of agricultural land lost due to urban expansion. Several specific elements were used in the descriptive model of landscape changes and population dynamics of the city of Shenzhen in China. These elements are: i) quantify the urban changes, from a small town (37.000 people in the early 1970’s) to the megalopolis of around 20 million habitants today. ii) Examining the rate of urban extension on the loss of agricultural landscape and population growth. iii) The loss of food production was analysed against the economic growth in the region. iv) The aspects of loss of agricultural land, area of built-up urban land, and increase in population are studied quantitatively, by the temporal analysis of earth observation geospatial data. The experimental results from this study show that the proposed method is effective in determining loss of agricultural land in any city due to urbanization. It can be used by town planner and other stakeholders such as land surveyors and agriculture experts to mitigate the mushrooming of unplanned settlements in many town / villages and loss of land for agriculture which might cause problems in food security.

Urban Expansion and Loss of Agricultural Land: A Remote Sensing Based Study of Shirpur City, Maharashtra

2017 ◽  
Vol 6 (1) ◽  
pp. 2097-2102
Author(s):  
Yogesh Mahajan ◽  
◽  
Shrikant Mahajan ◽  
Bharat Patil ◽  
Sanjay Kumar Patil ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Agricultural Land ◽  
Urban Expansion

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals THE EFFECT OF POPULATION DYNAMICS ON FOREST COVER IN DARO LEBU WEREDA, WEST HARARGHE ZONE, OROMIA REGION, ETHIOPIA

2021 ◽  
Vol 9 (3) ◽  
pp. 78-96
Author(s):  
Delelegy Legese ◽  
Alemayehu Diriba Roba
Keyword(s):  
Population Dynamics ◽  
Population Growth ◽  
Forest Cover ◽  
Agricultural Land ◽  
Data Gathering ◽  
Sampling Technique ◽  
Target Population ◽  
Economic Transformation ◽  
Fuel Wood ◽  
Human Encroachment

Forest is one of renewable land properties which endowed with numerous resources that are valuable to man. The quality of the environment is constantly losing its status due to increase in population size in most countries of the world. The general objective of this study was to assess the effect of population dynamics on forest cover in West Hararghe Zone in general and Daro Labu Wereda (DLW) in particular. Systematic random sampling technique was used to select the target population of this study whose total number was 364 households from four kebeles of DLW. Questionnaire, interview, FGD and satellite imagery used as data gathering tools for this study. The quantitative data of this study were analyzed using descriptive statistics and the qualitative data were discussed and interpreted through narration. As the result in this study a mixed method was used. This study is triangulation study in its design. The study was found out that population dynamics had contributed a lot to deforestation of the wereda under the study through agricultural land expansion, settlement, fuel wood gathering and illegal tree cutting. Thus due to  population growth, lack of alternative livelihood approach, ruthless profit making, lack of economic transformation human encroachment and lack of alternative sources of energy. Population growth had contributed greatly to forest deforestation especially as it affected the forest covers. The major findings were observed that expansion for cultivated and settlement LULC classes rapidly increased from1973 to 2013 on the contrary forest and shrub lands decreased in DLW due to population dynamics and human encroachment in the forest cover. Therefore, there is an urgent need with government for the various stakeholders in environmental resource management to provide mechanism that can prevent the forest cover from further reduction in the study area.

A Remote Sensing and GIS Integrated Study on Assessment of Change in Land Use and Loss of Agricultural Land due to Urbanization – A Case Study of Nashik City

2021 ◽  
Vol 9 (8) ◽  
pp. 3055-3063
Author(s):  
Dipti Bakare
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Rapid Change ◽  
Remote Sensing And Gis ◽  
Suitability Analysis ◽  
The World

Abstract: Urbanization may be a process having a serious impact ashore use characteristics. Basically, as an impression of urbanization, the world is observed with rapid change within the land use character of agricultural land. Generally, the agricultural land is employed for various development activities like industrial establishments, residential colonies and other urban infrastructure during the method of urbanization. it's necessary to possess a periodical assessment of land use change for the developing populated area , which helps to make a decision the longer term expansion strategies for the world. Nashik city is located in the state of Maharashtra in the western part of India. It is one of the most dynamic cities of India with a rapid growth rate due to migration from various parts of Maharashtra. The Nashik city is presently spread over an area of 264.15 sq. km. with a periodical increase in municipal corporation boundary during the last few decades. As a result of urbanization and expansion of municipal corporation limits, the city has undergone drastic changes in land use character. In this study, land-use change is quantified for the existing six zones of Nashik city during the last 30 years using remote sensing and GIS. The study has analysed the relationship between urban expansion and the loss of agricultural land because of an increase in a built-up area and other land use. The study present excellent scenario for land use change during the year 1991, 2001, 2011 and 2020. This can surely guide the development strategies for the study area of Nashik. Also the study can be extended for conducting a suitability analysis to assess future change of land use based on various criteria. Keywords: Land use, Remote sensing, GIS, Supervised classification, Urbanization, Agricultural land loss

scholarly journals Using Earth Observation for Monitoring SDG 11.3.1-Ratio of Land Consumption Rate to Population Growth Rate in Mainland China

2020 ◽  
Vol 12 (3) ◽  
pp. 357 ◽  
Author(s):  
Yunchen Wang ◽  
Chunlin Huang ◽  
Yaya Feng ◽  
Minyan Zhao ◽  
Juan Gu
Keyword(s):  
Growth Rate ◽  
Sustainable Development ◽  
Population Growth ◽  
Urban Areas ◽  
Population Growth Rate ◽  
Consumption Rate ◽  
Urban Expansion ◽  
Mainland China ◽  
Earth Observation ◽  
Land Consumption

Urban sustainable development has attracted widespread attention worldwide as it is closely linked with human survival. However, the growth of urban areas is frequently disproportionate in relation to population growth in developing countries; this discrepancy cannot be monitored solely using statistics. In this study, we integrated earth observation (EO) and statistical data monitoring the Sustainable Development Goals (SDG) 11.3.1: “The ratio of land consumption rate to the population growth rate (LCRPGR)”. Using the EO data (including China’s Land-Use/Cover Datasets (CLUDs) and the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data) and census, we extracted the percentage of built-up area, disaggregated the population using the geographically weighted regression (GWR) model, and depicted the spatial heterogeneity and dynamic tendency of urban expansion and population growth by a 1 km × 1 km grid at city and national levels in mainland China from 1990 to 2010. Then, the built-up area and population density datasets were compared with other products and statistics using the relative error and standard deviation in our research area. Major findings are as follows: (1) more than 95% of cities experienced growth in urban built-up areas, especially in the megacities with populations of 5–10 million; (2) the number of grids with a declined proportion of the population ranged from 47% in 1990–2000 to 54% in 2000–2010; (3) China’s LCRPGR value increased from 1.69 in 1990–2000 to 1.78 in 2000–2010, and the land consumption rate was 1.8 times higher than the population growth rate from 1990 to 2010; and (4) the number of cities experiencing uncoordinated development (i.e., where urban expansion is not synchronized with population growth) increased from 93 (27%) in 1990–2000 to 186 (54%) in 2000–2010. Using EO has the potential for monitoring the official SDGs on large and fine scales; the processes provide an example of the localization of SDG 11.3.1 in China.

scholarly journals Analyzing Urban Growth Pattern and Driving Factors Using Remote Sensing and GIS: A Case Study of Banepa Municipality, Nepal

2020 ◽  
Vol 20 (1) ◽  
pp. 9-18
Author(s):  
Rabina Twayana ◽  
Sijan Bhandari ◽  
Reshma Shrestha
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Growth ◽  
Growth Pattern ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Urban Land ◽  
Driving Factors ◽  
Rapid Urbanization ◽  
The Impact

Nepal is considered one of the rapidly urbanizing countries in south Asia. Most of the urbanization is dominated in large and medium cities i.e., metropolitan, sub-metropolitan, and municipalities. Remote Sensing and Geographic Information System (GIS) technologies in the sector of urban land governance are growing day by day due to their capability of mapping, analyzing, detecting changes, etc. The main aim of this paper is to analyze the urban growth pattern in Banepa Municipality during three decades (1992-2020) using freely available Landsat imageries and explore driving factors for change in the urban landscape using the AHP model. The Banepa municipality is taken as a study area as it is one of the growing urban municipalities in the context of Nepal. The supervised image classification was applied to classify the acquired satellite image data. The generated results from this study illustrate that urbanization is gradually increasing from 1992 to 2012 while, majority of the urban expansion happened during 2012-2020, and it is still growing rapidly along the major roads in a concentric pattern. This study also demonstrates the responsible driving factors for continuous urban growth during the study period. Analytical Hierarchy Process (AHP) was adopted to analyze the impact of drivers which reveals that, Internal migration (57%) is major drivers for change in urban dynamics whereas, commercialization (25%), population density (16%), and real estate business (5%) are other respective drivers for alteration of urban land inside the municipality. To prevent rapid urbanization in this municipality, the concerned authorities must take initiative for proper land use planning and its implementation on time. Recently, Nepal Government has endorsed Land Use Act 2019 for preventing the conversion of agricultural land into haphazard urban growth.

scholarly journals Implications of trade network structure and population dynamics for food security and equality

2021 ◽  
Author(s):  
Kathyrn R Fair ◽  
Chris Bauch ◽  
Madhur Anand
Keyword(s):  
Land Use ◽  
Population Dynamics ◽  
Food Security ◽  
Population Growth ◽  
Human Population ◽  
Agricultural Land ◽  
Displacement Effect ◽  
Trade Networks ◽  
Natural Land ◽  
Per Capita

Given trade's importance to maintaining food security, it is crucial to understand the relationship between human population growth, land use, food supply, and trade. We develop a metapopulation model coupling human population dynamics to agricultural land use and food production in "patches" (regions and countries) connected via trade networks. Patches that import sparingly or fail to adjust their demand sharply in response to changes in food per capita experience food insecurity. They fall into a feedback loop between increasing population growth and decreasing food per capita, particularly if they are peripheral to the network. A displacement effect is also evident; patches that are more central and/or import more heavily preserve their natural land states. Their reliance on imports means other patches must expand their agricultural land. These results emphasize that strategies for improving food security and equality must account for the combined effects of network topology and patch-level characteristics.

scholarly journals Open-Sourced Remote Sensing Data Management with the Irish Earth Observation (IEO) Python Module

2018 ◽  
Author(s):  
Guy Serbin ◽  
Stuart Green
Keyword(s):  
Remote Sensing ◽  
Vegetation Indices ◽  
Analytical Data ◽  
Remote Sensing Data ◽  
Earth Observation ◽  
Geospatial Data ◽  
Data Sets ◽  
Sensing Data ◽  
Local Use ◽  
Global Systems

Many remote sensing analytical data products are most useful when they are in an appropriate regional or national projection, rather than globally based projections like Universal Transverse Mercator (UTM) or geographic coordinates, i.e., latitude and longitude. Furthermore, leaving data in the global systems can create problems, either due to misprojection of imagery because of UTM zone boundaries, or because said projections are not optimised for local use. We developed the open-source Irish Earth Observation (IEO) Python module to maintain a local remote sensing data library for Ireland. This pure Python module, in conjunction with the IEOtools Python scripts, utilises the Geospatial Data Abstraction Library (GDAL) for its geoprocessing functionality. At present, the module supports only Landsat TM/ETM+/OLI/TIRS data that have been corrected to surface reflectance using the USGS/ESPA LEDAPS/ LaSRC Collection 1 architecture. This module and the IEOtools catalogue available Landsat data from the USGS/EROS archive, and includes functions for the importation of imagery into a defined local projection and calculation of cloud-free vegetation indices. While this module is distributed with default values and data for Ireland, it can be adapted for other regions with simple modifications to the configuration files and geospatial data sets.

Remote Sensing for Spatio-temporal Mapping of Land surface temperature and Surface Energy Fluxes in the Bouregreg-Chaouia Region of Morocco

2021 ◽  
Vol 2 (1) ◽  
pp. 23-35
Author(s):  
Abdelouhed Farah ◽  
Ahmed Algouti ◽  
Abdellah Algouti ◽  
Mohammed Ifkirne ◽  
Abdellatif Rafik
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Spatial Data ◽  
Land Surface ◽  
Agricultural Land ◽  
New Technologies ◽  
Urban Expansion ◽  
Environmental Parameters ◽  
Landsat 8 ◽  
The Impact

In recent decades, the Bouregreg Chaouia region has been subject to urban growth and a reduction in agricultural land in this region, which has changed its environmental variables and made it vulnerable to climate change. This work raises the spatiotemporal monitoring of land use and certain environmental parameters (vegetation cover, albedo, surface temperature from 1987 to 2015 by exploring intelligent spatial data in the region. The remote sensing products were computed from Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 Oli/TIRS images obtained during the dry seasons 1987, 2000 and 2015. The results showed a reduction in NDVI vegetation index (∼0.86 in 1987 to ∼0. 56 in 2000 to ∼ 0.54 in 2015) and with an increase in surface albedo (0.51 in 1987 to 0.52 in 2000 to 0. 69 in 2015), temperature (∼67°C in 1987 to 54°C in 2000 to 40°C in 2015) and to understand the impact of urbanization on the variation of environmental parameters, the evolution of the built-up area has been followed as a determining factor. However, it recorded 3.27% surface area in 1987 to 7.45% in 2000 to 28.18% in 2015. Indeed, the contribution of new technologies (GIS and remote sensing) is essential for better management and monitoring of the impact of urban expansion on the state of the environment. The results obtained remain so promising and highlight the contribution and feasibility of intelligent spatial data to assess the evolution of the urban environment on a large scale.

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