scholarly journals A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images

2019 ◽  
Vol 11 (19) ◽  
pp. 5266 ◽  
Author(s):  
Fernando Chapa ◽  
Srividya Hariharan ◽  
Jochen Hack
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Cover ◽  
Urban Areas ◽  
Google Earth ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Wide Range ◽  
True Color ◽  
Land Cover Maps

Urbanization nowadays results in the most dynamic and drastic changes in land use/land cover, with a significant impact on the environment. A detailed analysis and assessment of this process is necessary to take informed actions to reduce its impact on the environment and human well-being. In most parts of the world, detailed information on the composition, structure, extent, and temporal changes of urban areas is lacking. The purpose of this study is to present a methodology to produce high-resolution land use/land cover maps by the use of free software and satellite imagery. These maps can help to understand dynamic urbanizations processes to plan, design, and coordinate sustainable urban development plans, especially in areas with limited resources and advancing environmental degradation. A series of high-resolution true color images provided by Google Earth Pro were used to do initial classifications with the Semi-Automatic Classification Plug-in in QGIS. Afterwards, a new methodology to improve the classification by the elimination of shadows and clouds, and a reduction of misclassifications through superimposition was applied. The classification was carried out for three urban areas in León, Nicaragua, with different degrees of urbanization for the years 2009, 2015, and 2018. Finally, the accuracy of the classification was analyzed using randomly defined validation polygons. The results are three sets of high-resolution land use/land cover maps of the initial and the improved classification, showing the detailed structures and temporal dynamics of urbanization. The average accuracy of classification reaches 74%, but up to 85% for the best classification. The results clearly identify advancing urbanization, the loss of vegetation and riparian zones, and threats to urban ecosystems. In general, the level of detail and simplicity of our methodology is a valuable tool to support sustainable urban management, although its application is not limited to these areas and can also be employed to track changes over time, providing therefore, relevant information to a wide range of decision-makers.

scholarly journals An Assessment of Changes the Land Use Land Cover and Impact of the It Park at Talwade Pune On the Nearby Villages

2020 ◽  
pp. 172-179
Author(s):  
Ujjwala Khare ◽  
Prajakta Thakur
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rapid Growth ◽  
Urban Areas ◽  
Satellite Images ◽  
Ground Truth ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Tertiary Sector ◽  
Land Cover Maps

<p>The expansion of urban areas is common in metropolitan cities in India. Pune also has experienced rapid growth in the fringe areas of the city. This is mainly on account of the development of the Information Technology (IT) Parks. These IT Parks have been established in different parts of Pune city. They include Hinjewadi, Kharadi, Talwade and others like the IT parks in Magarpatta area. The IT part at Talwade is located to close to Pune Nashik Highway has had an impact on the villages located around it. The surrounding area includes the villages of Talwade, Chikhli, Nighoje, Mahalunge, Khalumbre and Sudumbre.</p> <p>The changes in the land use that have occurred in areas surrounding Talwade IT parks during the last three decades have been studied by analyzing the LANDSAT images of different time periods. The satellite images of the 1992, 2001 and 2011 were analyzed to detect the temporal changes in the land use and land cover.</p> <p>This paper attempts to study the changes in land use / land cover which has taken place in these villages in the last two decades. Such a study can be done effectively with the help of remote sensing and GIS techniques. The tertiary sector has experienced a rapid growth especially during the last decade near the IT Park. The occupation structure of these villages is also related to the changes due to the development of the IT Park.</p> <p>The land use of study area has been analysed using the ground truth applied to the satellite images at decadal interval. Using the digital image processing techniques, the satellite images were then classified and land use / land cover maps were derived. The results show that the area under built-up land has increased by around 14 per cent in the last 20 years. On the contrary, the land under agriculture, barren, pasture has decreased significantly.</p>

scholarly journals A 30-meter resolution national urban land-cover dataset of China, 2000–2015

2019 ◽  
Author(s):  
Wenhui Kuang ◽  
Shu Zhang ◽  
Xiaoyong Li ◽  
Dengsheng Lu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Urban Land ◽  
Google Earth ◽  
Urban Environments ◽  
Urban Land Use ◽  
Environmental Research ◽  
Urban Land Cover

Abstract. Accurate urban land-cover datasets are essential for mapping urban environments. However, a series of national urban land-cover data covering more than 15 years that characterizes urban environments is relatively rare. Here we propose a hierarchical principle on remotely sensed urban land-use/cover classification for mapping intra-urban structure/component dynamics. China's Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness, green surface, waterbody and bare land conditions in cities. A new data subset called CLUD-Urban is created from 2000 to 2015 at five-year intervals with a medium spatial resolution (30 m). The first step is a prerequisite to extract the vector boundaries covered with urban areas from CLUD. A new method is then proposed using logistic regression between urban impervious surface area (ISA) and the annual maximum Normalized Difference Vegetation Index (NDVI) value retrieved from Landsat images based on a big-data platform with Google Earth Engine. National ISA and urban green space (UGS) fraction datasets for China are generated at 30-meter resolution with five-year intervals from 2000 to 2015. The overall classification accuracy of national urban areas is 92 %. The root mean square error values of ISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that the total urban area of China was 6.28 × 104 km2 in 2015, with average fractions of 70.70 % and 26.54 % for ISA and UGS, respectively. The ISA and UGS increased between 2000 and 2015 with unprecedented annual rates of 1,311.13 km2/yr and 405.30 km2/yr, respectively. CLUD-Urban can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and urban dwellers' environments. CLUD-Urban can be applied in future researches on urban environmental research and practices in the future. The datasets can be downloaded from https://doi.org/10.5281/zenodo.2644932.

Reviewing the Pertinence of Sentinel-1 SAR for Urban Land Use Land Cover Classification

2020 ◽  
Vol 11 (5) ◽  
pp. 529-535
Author(s):  
Dan Abudu ◽  
Nigar Sultana Parvin ◽  
Geoffrey Andogah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Cover Classification ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Sensing Technology

Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets.

scholarly journals Land Use Change and Urban Ecosystem Services: A Case Study of Urban Wetlands in a Rapidly Sprawling City in the Highlands of Chiapas, Mexico

2019 ◽  
Vol 9 (1) ◽  
pp. 67
Author(s):  
Vera Camacho-Valdez ◽  
Eva M. Tello-Alcaide ◽  
Allen Wootton ◽  
Emmanuel Valencia-Barrera
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Ecosystem Service ◽  
Google Earth ◽  
Land Use Land Cover ◽  
Urban Wetlands ◽  
Rapid Urbanization ◽  
Wide Range ◽  
The Impact

Urban wetlands provide a wide range of ecosystem services that are important for human-well-being. Despite their social and environmental importance, the degradation of urban wetlands continues mainly due to land use changes induced by rapid urbanization. Estimating the impact of these changes on ecosystem services is crucial to support the decision-making process of city planners at different levels. In this study, the spatial extents of the urban wetlands of San Cristobal de Las Casas, Chiapas, Mexico were determined for the years 2001 and 2018 in order to relate the spatial changes between these years with the provision and economic value of ecosystem services. Google Earth and SPOT imagery were used to evaluate land use/land cover changes while international coefficients were used to assess the value of the ecosystem services by category. Findings reveal a 7.3% decrease in the urban wetland area and a 12.5% increase of urban areas during the study period. The ecosystem service valuation shows that the total value flow decreased around $5 million (2007 USD) during the 17-year period, mainly due to decreases in the potential for regulating and cultural services. The use of freely available land use/land cover data together with global ecosystem service estimates reduce the cost of ground data collection and provides quick and reliable information that could help decision makers with land use planning in the context of data-scarce regions.

scholarly journals OBJECT ORIENTED CLASSIFICATION AND FEATURE EXTRACTION FOR PARTS OF EAST DELHI USING HYBRID APPROACH

2018 ◽  
Vol XLII-5 ◽  
pp. 749-754
Author(s):  
P. Kumar ◽  
S. Ravindranath ◽  
K. G. Raj
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Cover ◽  
Satellite Data ◽  
Urban Land ◽  
Urban Land Use ◽  
Data Sets ◽  
Land Use Land Cover ◽  
Master Plans ◽  
Very High

<p><strong>Abstract.</strong> Rapid urbanization of Indian cities requires a focused attention with respect to preparation of Master Plans of cities. Urban land use/land cover from very high resolution satellite data sets is an important input for the preparation of the master plans of the cities along with extraction of transportation network, infrastructure details etc. Conventional classifiers, which are pixel based do not yield reasonably accurate urban land use/land cover classification of very high resolution satellite data (usually merged images of Panchromatic &amp;amp; Multispectral). Object Based Image Classification techniques are being used to generate urban land use maps with ease which is GIS compatible while using very high resolution satellite data sets. In this study, Object Based Image Analysis (OBIA) has been used to create broad level urban Land Use / Land Cover (LU/LC) map using high resolution ResourceSat-2 LISS-4 and Cartosat-1 pan-sharpened image on the study area covering parts of East Delhi City. Spectral indices, geometric parameters and statistical textural methods were used to create algorithms and rule sets for feature classification. A LU/LC map of the study area comprising of 4 major LU/LC classes with its main focus on separation of barren areas from built up areas has been attempted. The overall accuracy of the result obtained is estimated to be approximately 70%.</p>

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

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
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