scholarly journals Application of Time Series Landsat Images to Examining Land-use/Land-cover Dynamic Change

2012 ◽  
Vol 78 (7) ◽  
pp. 747-755 ◽  
Author(s):  
Dengsheng Lu ◽  
Scott Hetrick ◽  
Emilio Moran ◽  
Guiying Li
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Dynamic Change ◽  
Land Use Land Cover ◽  
Landsat Images

scholarly journals Perceived Human-Induced Causes of Landslide in Chattogram Metropolitan Area in Bangladesh

2021 ◽  
Author(s):  
Zia Ahmed ◽  
A H M Belayeth Hussain ◽  
Mufti Nadimul Quamar Ahmed ◽  
Rafiul Alam ◽  
Hafiz-Al Rezoan ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Metropolitan Area ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Weak Soil ◽  
Landsat Images ◽  
Level Of Education ◽  
Steep Hill

Abstract This study investigates Land Use Land Cover changes in the Chattogram metropolitan area, the second largest city in Bangladesh. Using a questionnaire survey of 150 local inhabitants, the study explores perceived human-induced causes of landslides. Using time series Landsat images this study also analyzes Land Use Land Cover changes from 1990 to 2020. The analysis reveals built-up area extended rapidly during 1990 to 2020. In 1990, total built up area was 82.13km², which in 30 years, stood at 451.34km². Conversely, total vegetative area decreased rapidly. In 1990, total vegetation area was 364.31km², which reduced to 130.44 km² in 2020. The survey respondents identified extensive rainfall, hill cutting, steep hill, and weak soil texture as several reasons for landslide. Findings show that age and experience of facing landslide are two significant predictors to explain whether excessive hill cutting is solely responsible for landslide. Level of education and experience of facing landslide are statistically significant in explaining building infrastructure as solitary cause to landslide. Gender, age and income of the respondents significantly explain deforestation as the only responsible for landslide. Finally, gender, level of education, and income of the respondents significantly explain only excessive sand collection causes landslide.

scholarly journals Characterizing Land Use/Land Cover Using Multi-Sensor Time Series from the Perspective of Land Surface Phenology

2019 ◽  
Vol 11 (14) ◽  
pp. 1677 ◽  
Author(s):  
Lan H. Nguyen ◽  
Geoffrey M. Henebry
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Land Surface ◽  
Quadratic Model ◽  
Observation Data ◽  
Land Use Land Cover ◽  
Land Surface Phenology ◽  
Land Cover Map ◽  
Phenological Metrics

Due to a rapid increase in accessible Earth observation data coupled with high computing and storage capabilities, multiple efforts over the past few years have aimed to map land use/land cover using image time series with promising outcomes. Here, we evaluate the comparative performance of alternative land cover classifications generated by using only (1) phenological metrics derived from either of two land surface phenology models, or (2) a suite of spectral band percentiles and normalized ratios (spectral variables), or (3) a combination of phenological metrics and spectral variables. First, several annual time series of remotely sensed data were assembled: Accumulated growing degree-days (AGDD) from the MODerate resolution Imaging Spectroradiometer (MODIS) 8-day land surface temperature products, 2-band Enhanced Vegetation Index (EVI2), and the spectral variables from the Harmonized Landsat Sentinel-2, as well as from the U.S. Landsat Analysis Ready Data surface reflectance products. Then, at each pixel, EVI2 time series were fitted using two different land surface phenology models: The Convex Quadratic model (CxQ), in which EVI2 = f(AGDD) and the Hybrid Piecewise Logistic Model (HPLM), in which EVI2 = f(day of year). Phenometrics and spectral variables were submitted separately and together to Random Forest Classifiers (RFC) to depict land use/land cover in Roberts County, South Dakota. HPLM RFC models showed slightly better accuracy than CxQ RFC models (about 1% relative higher in overall accuracy). Compared to phenometrically-based RFC models, spectrally-based RFC models yielded more accurate land cover maps, especially for non-crop cover types. However, the RFC models built from spectral variables could not accurately classify the wheat class, which contained mostly spring wheat with some fields in durum or winter varieties. The most accurate RFC models were obtained when using both phenometrics and spectral variables as inputs. The combined-variable RFC models overcame weaknesses of both phenometrically-based classification (low accuracy for non-vegetated covers) and spectrally-based classification (low accuracy for wheat). The analysis of important variables indicated that land cover classification for this study area was strongly driven by variables related to the initial green-up phase of seasonal growth and maximum fitted EVI2. For a deeper evaluation of RFC performance, RFC classifications were also executed with several alternative sampling scenarios, including different spatiotemporal filters to improve accuracy of sample pools and different sample sizes. Results indicated that a sample pool with less filtering yielded the most accurate predicted land cover map and a stratified random sample dataset covering approximately 0.25% or more of the study area were required to achieve an accurate land cover map. In case of data scarcity, a smaller dataset might be acceptable, but should not smaller than 0.05% of the study area.

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 Spatio-temporal analysis of land use/land cover dynamics in Sokoto Metropolis using multi-temporal satellite data and Land Change Modeller

2020 ◽  
Vol 52 (3) ◽  
pp. 306
Author(s):  
Murtala Dangulla ◽  
Latifah Abd Manaf ◽  
Firuz Ramli Mohammad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Open Space ◽  
Urban Expansion ◽  
Land Use Land Cover ◽  
Land Change ◽  
Landsat Images ◽  
Green Area ◽  
Rate Of Increase ◽  
Green Areas

Urbanization is currently one of the most pressing environmental issues which cuts across all countries at unprecedented rates and intensities, with far reaching consequences on ecosystems, biodiversity and human wellbeing. This paper assessed urban expansion and land use/land cover changes in Sokoto metropolis, North-western Nigeria using Remote Sensing and GIS. Landsat images of 1990, 1999 and 2015 were processed for LULC classification and change detection using the Maximum Likelihood Classification, Post Classification Comparison techniques and the Land Change Modeler. The classification revealed five broad land cover classes which include Built-up Area, Farmland, Green Area, Open Space and Wetland/Water. The Built-up and Green areas continuously increased while Farmland and Open space decreased throughout the study period. The metropolis expanded radially at a faster rate between 1999 and 2015 with the highest rate of increase (1890.5ha per annum) recorded in the Built-up Area. This implies a doubling time of approximately 30 years at the expense of Farmland and Open space which may be completely exhausted in 40 and 29 years respectively. Infrastructural provision should thus align with the rate and direction of growth and where the Green Area is converted, replacement should be made to ensure continued supply and stability of the numerous ecosystem services green areas provide.

scholarly journals Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

2021 ◽  
Vol 13 (16) ◽  
pp. 3337
Author(s):  
Shaker Ul Din ◽  
Hugo Wai Leung Mak
Keyword(s):  
Land Use ◽  
Support Vector Machine ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

scholarly journals SATELLITE IMAGERY DRIVEN ASSESSMENT OF LAND USE LAND COVER, URBANIZATION AND SURFACE TEMPERATURE PATTERN DYNAMICS OVER TROPICAL MEGACITIES

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 313-320
Author(s):  
S. Verma ◽  
S. Agrawal ◽  
K. Dutta
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface ◽  
Temperature Pattern ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Pattern Dynamics ◽  
Spatio Temporal ◽  
Supervised Image Classification

Abstract. In most of the developing nations, fast paced urbanisation is going on. This has changed the spatial patterns of Land Use Land Cover (LULC) and Land Surface Temperature (LST) over time. Continual studies are required in this context to know these phenomena more clearly. This study is carried out to analyse the spatio-temporal changes in LULC, urbanisation and LST in the metropolitan cities of India namely Delhi and Bengaluru. Landsat images of TM and OLI sensors are taken for the years 2001, 2010 and 2020. The LULC layer is obtained through supervised image classification. Concentric circles at the interval of 2 km are drawn from the centroid of the study areas which are used to compute Shannon's entropy through zonal analysis of the reclassified LULC layer. The thermal band of the Landsat is used for the computation of LST. The results of both the study areas revealed 1) decline in the open land, vegetation and water body; 2) rampant growth of built-up and urban area which become more compact over the years; and 3) spread of the higher LST zones.

scholarly journals Drivers and dynamics of land use land cover in Ambung VDC of Tehrathum district, Nepal

2016 ◽  
Vol 26 (1) ◽  
pp. 90-96 ◽  
Author(s):  
D Pandey ◽  
B P Heyojoo ◽  
H Shahi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Group Discussion ◽  
Household Survey ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Severe Problem ◽  
Training Samples ◽  
Land Cover Maps

Land use and land cover change has immense impact on the global environment and ecosystem. Geospatial technologies are very important for monitoring these changes. This research aims to find out the land use land cover dynamics and drivers of Ambung VDC, Tehrathum district. The Landsat images of the year 1990 and 2013 were used for quantifying the changes. Household survey, key informant interview, focus group discussion, training samples collection and direct field observations were carried out to gather socio-economic and bio-physical data. Supervised classification was performed to prepare land cover maps. Change on land use was calculated by using post classification change detection. During 1990–2013, forest cover was found to have increased by 6.6%, agriculture decreased by 5.9% and others (barren, settlement, grass, rock and water bodies) decreased by 0.7%. The VDC was found to have severe problem of rapid drying of water resources in spite of the increase in forest cover, and so research should be carried out to find out the reason and solve the problem before it is too late.Banko JanakariA Journal of Forestry Information for NepalVol. 26, No. 1, Page:90-96, 2016

Sign in / Sign up

Export Citation Format

Share Document