scholarly journals The value of OpenStreetMap Historical Contributions as a Source of Sampling Data for Multi‑temporal Land Use/Cover Maps

2019 ◽  
Vol 8 (3) ◽  
pp. 116 ◽  
Author(s):  
Cláudia M. Viana ◽  
Luis Encalada ◽  
Jorge Rocha
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rural Areas ◽  
Urban Areas ◽  
Coverage Area ◽  
Training Samples ◽  
Spatial Coverage ◽  
Multi Temporal ◽  
One Year ◽  
Thematic Accuracy

OpenStreetMap (OSM) is a free, open-access Volunteered geographic information (VGI) platform that has been widely used over the last decade as a source for Land Use Land Cover (LULC) mapping and visualization. However, it is known that the spatial coverage and accuracy of OSM data are not evenly distributed across all regions, with urban areas being likelier to have promising contributions (in both quantity and quality) than rural areas. The present study used OSM data history to generate LULC datasets with one-year timeframes as a way to support regional and rural multi-temporal LULC mapping. We evaluated the degree to which the different OSM datasets agreed with two existing reference datasets (CORINE Land Cover and the official Portuguese Land Cover Map). We also evaluated whether our OSM dataset was of sufficiently high quality (in terms of both completeness accuracy and thematic accuracy) to be used as a sampling data source for multi-temporal LULC maps. In addition, we used the near boundary tag accuracy criterion to assesses the fitness of the OSM data for producing training samples, with promising results. For each annual dataset, the completeness ratio of the coverage area for the selected study area was low. Nevertheless, we found high thematic accuracy values (ranged from 77.3% to 91.9%). Additionally, the training samples thematic accuracy improved as they moved away from the features’ boundaries. Features with larger areas (> 10 ha), e.g., Agriculture and Forest, had a steadily positive correlation between training samples accuracy and distance to feature boundaries

scholarly journals Analyses of Nocturnal Temperature Cooling-Rate Response to Historical Local-Scale Urban Land-Use/Land Cover Change

2011 ◽  
Vol 50 (9) ◽  
pp. 1872-1883 ◽  
Author(s):  
Winston T. L. Chow ◽  
Bohumil M. Svoma
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Cooling Rate ◽  
Rural Areas ◽  
Urban Areas ◽  
Local Scale ◽  
Urban Land Use ◽  
Cooling Rates ◽  
Near Surface ◽  
Over Time

AbstractUrbanization affects near-surface climates by increasing city temperatures relative to rural temperatures [i.e., the urban heat island (UHI) effect]. This effect is usually measured as the relative temperature difference between urban areas and a rural location. Use of this measure is potentially problematic, however, mainly because of unclear “rural” definitions across different cities. An alternative metric is proposed—surface temperature cooling/warming rates—that directly measures how variations in land-use and land cover (LULC) affect temperatures for a specific urban area. In this study, the impact of local-scale (<1 km2), historical LULC change was examined on near-surface nocturnal meteorological station temperatures sited within metropolitan Phoenix, Arizona, for 1) urban versus rural areas, 2) areas that underwent rural-to-urban transition over a 20-yr period, and 3) different seasons. Temperature data were analyzed during ideal synoptic conditions of clear and calm weather that do not inhibit surface cooling and that also qualified with respect to measured near-surface wind impacts. Results indicated that 1) urban areas generally observed lower cooling-rate magnitudes than did rural areas, 2) urbanization significantly reduced cooling rates over time, and 3) mean cooling-rate magnitudes were typically larger in summer than in winter. Significant variations in mean nocturnal urban wind speeds were also observed over time, suggesting a possible UHI-induced circulation system that may have influenced local-scale station cooling rates.

scholarly journals DYNAMICS OF SPATIO-TEMPORAL URBAN EXPANSION IN SOUTH WEST DELHI REGION: A GEO-SPATIAL APPROACH FOR URBAN DISASTER MANAGEMENT

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 373-379
Author(s):  
N. Sharma ◽  
A. Kaur ◽  
P. Bose
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Natural Resources ◽  
Land Cover Change ◽  
Rural Areas ◽  
Urban Areas ◽  
Urban Expansion ◽  
Urban Disaster ◽  
Spatio Temporal ◽  
The Impact

<p><strong>Abstract.</strong> Constantly increasing population and up-scaling economic growth has certainly contributed to fast-paced urban expansion, but simultaneously, as a result, has developed immense pressure on our natural resources. Among other unfavorable consequences, this has led to significant changes in the land use and land cover patterns in megacities all across the globe. As the impact of uncontrolled and unplanned development continues to alter life patterns, it has become imperative to study severe problems resulting from rapid development and leading to environmental pollution, disruptions in ecological structures, ever increasing pressure on natural resources and recurring urban disasters This paper presents an approach to address these challenges using geospatial data to study the land use and land cover change and the patterns and processes of urban growth. Spatio-temporal changes in land-use/land-cover were assessed over the years using multi-date high resolution satellite data. The land use classification was conducted using visual image interpretation technique wherein, study area was categorized into five different classes based on NRSC classification system namely agricultural, built-up, urban green (forest), and fallow land and water bodies. Post-classification change detection technique was used for the assessment of land-cover change and transition matrices of urban expansion were developed to quantify the changes. The results show that the city has been expanding majorly in its borders, where land masses have been converted from agriculture based rural areas to urban structures. An increase in the built-up category was observed with the transformation of agricultural and marginal land with an approximate change of 8.62% in the peri-urban areas. Urban areas are becoming more densely populated and open barren lands are converted into urban areas due to over population and migration from the rural areas of Delhi and thus increasing threat towards urban disaster. Conservation and sustainable management of various natural resources is recommended in order to minimize the impact of potential urban disasters.</p>

scholarly journals Quantification of Land Cover Changes in Sub-urban Areas of Pekanbaru City

2021 ◽  
Vol 887 (1) ◽  
pp. 012020
Author(s):  
F. Firmansyah ◽  
A. B. Raharja
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rural Areas ◽  
Economic Activity ◽  
Urban Areas ◽  
The Road ◽  
On The Road ◽  
Urban And Rural Areas ◽  
High Level ◽  
Two Stages

Abstract Morphologically, land cover, urban and rural areas have different characteristics. It is the same as Pekanbaru City area that has unique characteristics including its surrounding regencies. However, the high level of land demand caused by increasing economic activity, high natural and non-natural population growth, makes the morphology of land cover in urban and rural areas unclear. Empirically this beginning to be considered common in urban areas that have a role as a strategic point or center of economic activity, but one of the concerns is the development of unplanned and dominating areas in a space that later create a more fragile environmental conditions in suburban areas. This study aimed to identify changes in land cover and assess the level of conformity of land use in the suburbs of Pekanbaru City. This study used a description method with two stages, (1). Identifying land cover using temporal images, (2). Analyze the level of conformity of land use. The results showed that there are four patterns of land cover change in the suburbs of Pekanbaru City, especially on the road axis connecting the surrounding area. These developments indicate nonconformity of land use which has an impact on the loss of protected land and productive plantation land in the suburbs of Pekanbaru City.

scholarly journals A Spatiotemporal Assessment of Land Use and Land Cover Changes in Peri-Urban Areas: A Case Study of Arshaly District, Kazakhstan

2020 ◽  
Vol 12 (4) ◽  
pp. 1556 ◽  
Author(s):  
Onggarbek Alipbeki ◽  
Chaimgul Alipbekova ◽  
Arnold Sterenharz ◽  
Zhanat Toleubekova ◽  
Meirzhan Aliyev ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Area ◽  
Urban Areas ◽  
Agricultural Land ◽  
Arable Land ◽  
Multispectral Images ◽  
Multi Temporal ◽  
The Republic

In this study, the spatiotemporal dynamics of land use and land cover (LULC) were evaluated in the peri-urban area of the Arshaly district, which borders the capital of the Republic of Kazakhstan. Landsat multispectral images were used to study the changes in LULC. The analysis of LULC dynamics was carried out using supervised classification with a multi-temporal interval (1998, 2008, and 2018). During the study period, noticeable changes occurred in LULC. There was an increase in the area of arable land and forests and a reduction in the pastures. There was a sharp increase in the built-up area; that is, there was an intensification of land use through an increase in the share of arable land as well as the transformation of agricultural land for development. However, in general, the influence of urban sprawl in this peri-urban area has so far been accompanied by only a slight focus on its sustainable development.

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 Ecological Connectivity in Agricultural Green Infrastructure:  Suggested Criteria for Fine Scale Assessment and Planning

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 807
Author(s):  
Simone Valeri ◽  
Laura Zavattero ◽  
Giulia Capotorti
Keyword(s):  
Land Cover ◽  
Green Infrastructure ◽  
Rural Areas ◽  
Urban Areas ◽  
Landscape Heterogeneity ◽  
Agricultural Landscapes ◽  
Spatial Pattern Analysis ◽  
Fine Scale ◽  
Unique Type

In promoting biodiversity conservation and ecosystem service capacity, landscape connectivity is considered a critical feature to counteract the negative effects of fragmentation. Under a Green Infrastructure (GI) perspective, this is especially true in rural and peri-urban areas where a high degree of connectivity may be associated with the enhancement of agriculture multifunctionality and sustainability. With respect to GI planning and connectivity assessment, the role of dispersal traits of tree species is gaining increasing attention. However, little evidence is available on how to select plant species to be primarily favored, as well as on the role of landscape heterogeneity and habitat quality in driving the dispersal success. The present work is aimed at suggesting a methodological approach for addressing these knowledge gaps, at fine scales and for peri-urban agricultural landscapes, by means of a case study in the Metropolitan City of Rome. The study area was stratified into Environmental Units, each supporting a unique type of Potential Natural Vegetation (PNV), and a multi-step procedure was designed for setting priorities aimed at enhancing connectivity. First, GI components were defined based on the selection of the target species to be supported, on a fine scale land cover mapping and on the assessment of land cover type naturalness. Second, the study area was characterized by a Morphological Spatial Pattern Analysis (MSPA) and connectivity was assessed by Number of Components (NC) and functional connectivity metrics. Third, conservation and restoration measures have been prioritized and statistically validated. Notwithstanding the recognized limits, the approach proved to be functional in the considered context and at the adopted level of detail. Therefore, it could give useful methodological hints for the requalification of transitional urban–rural areas and for the achievement of related sustainable development goals in metropolitan regions.

scholarly journals Cropland Abandonment in Slovakia: Analysis and Comparison of Different Data Sources

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Juraj Lieskovský ◽  
Dana Lieskovská
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Data ◽  
Data Sources ◽  
Communist Regime ◽  
Corine Land Cover ◽  
Cropland Area ◽  
Cropland Abandonment ◽  
Multi Temporal

This study compares different nationwide multi-temporal spatial data sources and analyzes the cropland area, cropland abandonment rates and transformation of cropland to other land cover/land use categories in Slovakia. Four multi-temporal land cover/land use data sources were used: The Historic Land Dynamics Assessment (HILDA), the Carpathian Historical Land Use Dataset (CHLUD), CORINE Land Cover (CLC) data and Landsat images classification. We hypothesized that because of the different spatial, temporal and thematic resolution of the datasets, there would be differences in the resulting cropland abandonment rates. We validated the datasets, compared the differences, interpreted the results and combined the information from the different datasets to form an overall picture of long-term cropland abandonment in Slovakia. The cropland area increased until the Second World War, but then decreased after transition to the communist regime and sharply declined following the 1989 transition to an open market economy. A total of 49% of cropland area has been transformed to grassland, 34% to forest and 15% to urban areas. The Historical Carpathian dataset is the more reliable long-term dataset, and it records 19.65 km2/year average cropland abandonment for 1836–1937, 154.44 km2/year for 1938–1955 and 140.21 km2/year for 1956–2012. In comparison, the Landsat, as a recent data source, records 142.02 km2/year abandonment for 1985–2000 and 89.42 km2/year for 2000–2010. These rates, however, would be higher if the dataset contained urbanisation data and more precise information on afforestation. The CORINE Land Cover reflects changes larger than 5 ha, and therefore the reported cropland abandonment rates are lower.

scholarly journals A Disease Control-Oriented Land Cover Land Use Map for Myanmar

Data ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 63
Author(s):  
Dong Chen ◽  
Varada Shevade ◽  
Allison Baer ◽  
Jiaying He ◽  
Amanda Hoffman-Hall ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Population Distribution ◽  
Large Spatial Scale ◽  
The Public ◽  
Spatial Coverage ◽  
Vector Borne ◽  
Do So ◽  
Control And Eradication

Malaria is a serious infectious disease that leads to massive casualties globally. Myanmar is a key battleground for the global fight against malaria because it is where the emergence of drug-resistant malaria parasites has been documented. Controlling the spread of malaria in Myanmar thus carries global significance, because the failure to do so would lead to devastating consequences in vast areas where malaria is prevalent in tropical/subtropical regions around the world. Thanks to its wide and consistent spatial coverage, remote sensing has become increasingly used in the public health domain. Specifically, remote sensing-based land cover/land use (LCLU) maps present a powerful tool that provides critical information on population distribution and on the potential human-vector interactions interfaces on a large spatial scale. Here, we present a 30-meter LCLU map that was created specifically for the malaria control and eradication efforts in Myanmar. This bottom-up approach can be modified and customized to other vector-borne infectious diseases in Myanmar or other Southeastern Asian countries.

scholarly journals Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China

2013 ◽  
Vol 8 (1) ◽  
pp. 084596 ◽  
Author(s):  
Zhongchang Sun ◽  
Xinwu Li ◽  
Wenxue Fu ◽  
Yingkui Li ◽  
Dongsheng Tang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Surface Runoff ◽  
Urban Areas ◽  
Land Use Land Cover ◽  
Long Term Effects ◽  
Effects Of Land Use ◽  
Beijing China

scholarly journals PALSAR-2/ALOS-2 AND OLI/LANDSAT-8 DATA INTEGRATION FOR LAND USE AND LAND COVER MAPPING IN NORTHERN BRAZILIAN AMAZON

2018 ◽  
Vol 24 (2) ◽  
pp. 250-269 ◽  
Author(s):  
João Arthur Pompeu Pavanelli ◽  
João Roberto dos Santos ◽  
Lênio Soares Galvão ◽  
Maristela Xaud ◽  
Haron Abrahim Magalhães Xaud
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Brazilian Amazon ◽  
Landsat 8 ◽  
Array Type ◽  
Complex Landscape ◽  
Hybrid Classification ◽  
L Band ◽  
Thematic Accuracy ◽  
Better Than

Abstract: In northern Brazilian Amazon, the crops, savannahs and rainforests form a complex landscape where land use and land cover (LULC) mapping is difficult. Here, data from the Operational Land Imager (OLI)/Landsat-8 and Phased Array type L-band Synthetic Aperture Radar (PALSAR-2)/ALOS-2 were combined for mapping 17 LULC classes using Random Forest (RF) during the dry season. The potential thematic accuracy of each dataset was assessed and compared with results of the hybrid classification from both datasets. The results showed that the combination of PALSAR-2 HH/HV amplitudes with the reflectance of the six OLI bands produced an overall accuracy of 83% and a Kappa of 0.81, which represented an improvement of 6% in relation to the RF classification derived solely from OLI data. The RF models using OLI multispectral metrics performed better than RF models using PALSAR-2 L-band dual polarization attributes. However, the major contribution of PALSAR-2 in the savannahs was to discriminate low biomass classes such as savannah grassland and wooded savannah.

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