scholarly journals Monitoring of Urban Growth Patterns in Rapidly Growing Bahir Dar City of Northwest Ethiopia with 30 year Landsat Imagery Record

2020 ◽  
Vol 9 (9) ◽  
pp. 548 ◽  
Author(s):  
Mengistie Kindu ◽  
Daniela Angelova ◽  
Thomas Schneider ◽  
Martin Döllerer ◽  
Demel Teketay ◽  
...  
Keyword(s):  
Urban Growth ◽  
Forest Cover ◽  
Accuracy Assessment ◽  
Landsat Imagery ◽  
Local Level ◽  
Northwest Ethiopia ◽  
Growth Patterns ◽  
Bahir Dar ◽  
Change Analysis ◽  
Rapid Reduction

Monitoring urban growth patterns is an important measure to improve our understanding of land use/land cover (LULC) changes and a central part in the proper development of any city. In this study, we analyzed the changes over a period of 30 years (1985–2015) in Bahir Dar, one of the rapidly growing cities of northwest Ethiopia. Satellite images of Landsat TM (1985, 1995, and 2008), and OLI (2015) were used. The classification was carried out using the object-based image analysis technique and a change analysis was undertaken using post-classification comparison in GIS as a novel framework. An accuracy assessment was conducted for each reference year. Eight LULC types were successfully captured with overall accuracies ranging from 88.3% to 92.9% and a Kappa statistic of 0.85 to 0.92. The classification result revealed that cropland (66%), water (12.5%), and grassland (6%) were the dominant LULC types with a small share of areas covered by built-up areas (2.4%) in 1985. In 2015, cropland and water continued to be dominant followed by built-up areas. The change result shows that a rapid reduction in natural forest cover followed by grassland and wetland occurred between the first (1985–1995), second (1995–2008), and third (2008–2015) study periods. On the contrary, build-ups increased in all three periods by 9.3%, 121.3%, and 44.8%, respectively. Although the conversion between the LULC classes varied substantially, analysis of the 30-year change matrix revealed that about 31% was subject to intensive change between the classes. Specifically, the built-up area has increased by 250.5% during the study years. The framed approach used in this research is a good repeatable example of how to assess and monitor urban growth at the local level, by combining remote sensing and GIS technologies. Further study is suggested to investigate detailed drivers, consequences of changes, and future options.

scholarly journals Characterizing Spatial Variations of Urban Growth Patterns in Beijing, China through Spatial Analysis and Geovisualization

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Ting Liu ◽  
Xiaojun Yang
Keyword(s):  
Spatial Analysis ◽  
Urban Growth ◽  
Local Level ◽  
Theory Development ◽  
Spatial Variations ◽  
Growth Patterns ◽  
Capital City ◽  
Landscape Pattern Metrics ◽  
Urban Core ◽  
Ecological Conservation

<p><strong>Abstract.</strong> As the capital city and one of the largest cities of China, Beijing has experienced rapid urban growth in the past several decades. Despite the numerous research efforts of monitoring the spatiotemporal urban growth patterns in Beijing, there is a lack of consensus and comparable results for theory development or decision-making.</p><p>This paper presents a systematic approach of characterizing urban growth patterns in Beijing through spatial analysis and geovisualization. Specifically, we focus on characterizing the different dimensions of urban growth across scales, including density, continuity, direction, and centrality (Galster et al. 2001). We first derive general land cover information in Beijing from satellite imagery for the years of 1998, 2008, and 2018. The urban extent of Beijing is extracted for each year to be used for further analysis. We then characterize the urban growth patterns through various geovisualization and spatial analysis techniques at both the metropolitan level and the local/cell level (Table 1).</p><p>At the metropolitan level, we present the general trends of urban growth patterns in Beijing through landscape pattern metrics and spatial statistics. In addition, we compare the measurements of density, continuity and direction across the four functional zones in Beijing, i.e., urban core, extensive urban, new urban, and ecological conservation zone. The result reveals the regional variations and the underlying processes of urban growth in the Beijing metropolitan area. At the local level, we measure the spatial variations of urban growth patterns using a GIS-based moving windows analysis. As the moving window passes over the landscape, each calculated metrics is returned to the focal cell. This creates a surface representation of the selected metrics, which enables the creation of a contour map. The distribution of the contours delineates the spatial variations of urban growth at a finer scale. The developed approach can be applied to urban studies of other geographic areas, which will eventually lead to a comparative study of urban development.</p>

scholarly journals Using Geospatial Analysis to Map Forest Change in New Hampshire: 1996–Present

2020 ◽  
Vol 118 (6) ◽  
pp. 598-612
Author(s):  
Heather Grybas ◽  
Russell G Congalton ◽  
Andrew F Howard
Keyword(s):  
Land Cover ◽  
New Hampshire ◽  
Forest Cover ◽  
Landsat Imagery ◽  
The State ◽  
Forest Cover Change ◽  
Forest Change ◽  
Change Analysis ◽  
Land Cover Map ◽  
Forest Use

Abstract New Hampshire’s forests are vitally important to the state’s economy; however, there are indications that the state is experiencing a continuous loss in forest cover. We sought to investigate forest cover trends in New Hampshire. A baseline trend in forest cover between 1996 and 2010 was established using National Oceanic and Atmospheric Administration Coastal Change Analysis Program land cover data. A land cover map was then generated from Landsat imagery to extend the baseline trend to 2018. Results show that the state has experienced a continual decline in forest cover with the annual net loss steadily increasing from 0.14% between 1996 and 2001 to 0.27% between 2010 and 2018. Additionally, the more urbanized counties in southern New Hampshire are experiencing some of the greatest rates of net forest loss, most likely because of urbanization and agricultural expansion. This study demonstrated an effective methodology for tracking forest cover change and will hopefully inform future forest use policies.

scholarly journals Land Use and Land Cover Change Analysis Using GIS and Remote Sensing in The Case of Kersa District, Jimma Zone, Oromia Region, Ethiopia

2021 ◽  
Author(s):  
Nigus Tekleselassie Tsegaye
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
Natural Forest ◽  
Landsat 8 ◽  
Change Analysis ◽  
Object Based

Abstract Background: Land use and land cover change is driven by human actions and also drives changes that limit availability of products and services for human and livestock, and it can undermine environmental health as well. Therefore, this study was aimed at understanding land use and land cover change in Kersa district over the last 30 years. Time-series satellite images that included Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS, which covered the time frame between 1990-2020, were used to determine the change in land use and land cover using object based classification.Results: The object based classification result revealed that in 1990 TM Landsat imagery, natural forest (16.07%), agroforestry (9.21%), village (12.03%), urban (1.93%), and agriculture (60.76%) were identified. The change result showed a rapid reduction in natural forest cover of 25.04%, 9.15%, and 23.11% occurred between (1990-2000), (2000-2010), and (2010-2020) study periods, respectively. Similarly agroforestry decreased by 0.88% and 63.9% (2000-2010) and (2010-2020), respectively. The finding indicates the increment of agricultural land, village, and urban, while the natural forest and agroforestry cover shows a declining trend.Conclusions: The finding implies that there was a rapid land use and land cover change in the study area. This resulted in loss of natural resource and biodiversity. Overall, proper and integrated approach in implementing policies and strategies related to land use and land cover management should be required in kersa district.

scholarly journals MAPPING AND CHANGE ANALYSIS IN MANGROVE FOREST BY USING LANDSAT IMAGERY

2016 ◽  
Vol III-8 ◽  
pp. 109-116 ◽  
Author(s):  
T. T. Dan ◽  
C. F. Chen ◽  
S. H. Chiang ◽  
S. Ogawa
Keyword(s):  
Accuracy Assessment ◽  
Landsat Imagery ◽  
Atmospheric Correction ◽  
Central Africa ◽  
Quantitative Information ◽  
Native People ◽  
Change Analysis ◽  
The West ◽  
West And Central Africa ◽  
The Sundarbans

Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i) to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii) to identify change of mangrove using Landsat data. The data were processed through four main steps: (1) data pre-processing including atmospheric correction and image normalization, (2) image classification using supervised classification approach, (3) accuracy assessment for the classification results, and (4) change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km&lt;sup&gt;2&lt;/sup&gt; of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

scholarly journals MAPPING AND CHANGE ANALYSIS IN MANGROVE FOREST BY USING LANDSAT IMAGERY

2016 ◽  
Vol III-8 ◽  
pp. 109-116
Author(s):  
T. T. Dan ◽  
C. F. Chen ◽  
S. H. Chiang ◽  
S. Ogawa
Keyword(s):  
Accuracy Assessment ◽  
Landsat Imagery ◽  
Atmospheric Correction ◽  
Central Africa ◽  
Quantitative Information ◽  
Native People ◽  
Change Analysis ◽  
The West ◽  
West And Central Africa ◽  
The Sundarbans

Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i) to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii) to identify change of mangrove using Landsat data. The data were processed through four main steps: (1) data pre-processing including atmospheric correction and image normalization, (2) image classification using supervised classification approach, (3) accuracy assessment for the classification results, and (4) change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km<sup>2</sup> of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

scholarly journals Patterns of Population and Urban Growth in Southwest Europe: 1920-2010

2017 ◽  
Vol 43 (6) ◽  
pp. 1021-1040 ◽  
Author(s):  
Cathy Chatel ◽  
Mateu Morillas-Torné ◽  
Albert Esteve ◽  
Jordi Martí-Henneberg
Keyword(s):  
Regression Model ◽  
Social Organization ◽  
Iberian Peninsula ◽  
Urban Growth ◽  
Local Level ◽  
Population Data ◽  
Population Geography ◽  
Urbanization Process ◽  
Geographic Factors ◽  
Population Concentration

This work seeks to measure, locate, and explain changes in the distribution of population and urban growth in the territory formed by France, Italy, and the Iberian Peninsula between 1920 and 2010. This is based on population data of more than fifty-six thousand local units obtained from population censuses: the Geokhoris database that we built. Our starting viewpoint is that it is only possible to understand the extent of the urbanization process within the context of the evolution of all of the municipalities. The description of the distribution and growth of population at the local level shows the population concentration in the various urban agglomerations, and, since 1970, a relative deconcentration and extension of the cities. Within this context, a regression model helped us to identify the geographic factors that correlate with these fundamental transformations in population geography, which were also indicative of new forms of social organization within the territory.

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