scholarly journals Land cover change modelling in Hyrcanian forests, Northern Iran: a landscape pattern and transformation analysis perspective

2018 ◽  
Vol 44 (2) ◽  
pp. 743 ◽  
Author(s):  
S.J. Shooshtari ◽  
K. Shayesteh ◽  
M. Gholamalifard ◽  
M. Azari ◽  
J.I. López-Moreno
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Timber Harvest ◽  
Water Yield ◽  
Hyrcanian Forest ◽  
Northern Iran ◽  
Territorial Planning ◽  
Spatio Temporal ◽  
Shape Complexity ◽  
Land Cover Maps

The main objective of this study is to analyze the spatio-temporal changes in land cover and land use, (1984–2010), as well to simulate future land cover for 2030 in the Neka River Basin, including the Hyrcanian forest, in northern Iran. For this purpose, we used detailed land cover maps for the years 1984, 2001 and 2010. The results showed that the highest deforestation occurred in the boundaries between forest and agriculture areas between 1984 and 2010. Comparing the observed and predicted land cover in 2010 yielded agreement of 96.41%. From 1984 to 2010, landscape metrics showed that the forest area evolved to more fragmentation, with less shape complexity and less connectivity. Projections for the future are consistent with observed changes for the Neka landscape, with a tendency to continue disaggregating and increasing diversity in a number of different patch types. Between 2010 and 2030, we observed the arrival of new crops, rangelands, and urban areas within the remaining areas of homogeneous forest. Changes in the Hyrcanian forest will cause alteration in ecosystem services, such as erosion control, water yield, timber harvest, and ground water reservation. Results of this work may represent a useful tool to provide strategies and territorial planning for sustainable management of the fragile Hyrcanian forest ecosystems in the Neka Basin. 

scholarly journals Spatio-Temporal Super-Resolution Land Cover Mapping Based on Fuzzy C-Means Clustering

2018 ◽  
Vol 10 (8) ◽  
pp. 1212 ◽  
Author(s):  
Xiaohong Yang ◽  
Zhong Xie ◽  
Feng Ling ◽  
Xiaodong Li ◽  
Yihang Zhang ◽  
...  
Keyword(s):  
Land Cover ◽  
Spatial Pattern ◽  
Spatial Resolution ◽  
Super Resolution ◽  
Land Cover Mapping ◽  
Fuzzy C Means Clustering ◽  
Land Cover Map ◽  
Spatio Temporal ◽  
Fine Resolution ◽  
Land Cover Maps

Super-resolution land cover mapping (SRM) is a method that aims to generate land cover maps with fine spatial resolutions from the original coarse spatial resolution remotely sensed image. The accuracy of the resultant land cover map produced by existing SRM methods is often limited by the errors of fraction images and the uncertainty of spatial pattern models. To address these limitations in this study, we proposed a fuzzy c-means clustering (FCM)-based spatio-temporal SRM (FCM_STSRM) model that combines the spectral, spatial, and temporal information into a single objective function. The spectral term is constructed with the FCM criterion, the spatial term is constructed with the maximal spatial dependence principle, and the temporal term is characterized by the land cover transition probabilities in the bitemporal land cover maps. The performance of the proposed FCM_STSRM method is assessed using data simulated from the National Land Cover Database dataset and real Landsat images. Results of the two experiments show that the proposed FCM_STSRM method can decrease the influence of fraction errors by directly using the original images as the input and the spatial pattern uncertainty by inheriting land cover information from the existing fine resolution land cover map. Compared with the hard classification and FCM_SRM method applied to mono-temporal images, the proposed FCM_STSRM method produced fine resolution land cover maps with high accuracy, thus showing the efficiency and potential of the novel approach for producing fine spatial resolution maps from coarse resolution remotely sensed images.

scholarly journals Investigating the rank-size relationship of urban areas using land cover maps

2008 ◽  
Vol 35 (17) ◽  
Author(s):  
Tsuguki Kinoshita ◽  
Etsushi Kato ◽  
Koki Iwao ◽  
Yoshiki Yamagata
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Size Relationship ◽  
Relationship Of ◽  
Land Cover Maps

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 Spatio-Temporal Analysis of Active Fires over China during 2003–2016

2020 ◽  
Vol 12 (11) ◽  
pp. 1787
Author(s):  
Xikun Wei ◽  
Guojie Wang ◽  
Tiexi Chen ◽  
Daniel Fiifi Tawia Hagan ◽  
Waheed Ullah
Keyword(s):  
Land Cover ◽  
Seasonal Variations ◽  
Urban Areas ◽  
Atmospheric Environment ◽  
Economic Losses ◽  
Change Analysis ◽  
Land Cover Types ◽  
North East ◽  
Spatio Temporal

Fire is a common circumstance in the world. It causes direct casualties and economic losses, and also brings severe negative influences on the atmospheric environment. In the background of climate warming and rising population, it is important to understand the fire responses regarding the spatio-temporal changes. Thus, a long-term change analysis of fires is needed in China. We use the remote sensed MOD14A1/MYD14A1 fire products to analyze the seasonal variations and long-term trends, based on five main land cover types (forest, cropland, grassland, savannas and urban areas). The fires are found to have clear seasonal variations; there are more fires in spring and autumn in vegetated lands, which are related to the amount of dry biomass and temperature. The fire numbers have significantly increased during the study period, especially from spring to autumn, and those have decreased in winter. The long-term fire trends are different when delineated into different land cover types. There are significant increasing fire trends in grasslands and croplands in North, East and Northeast China during the study period. The urban fires also show increasing trends. On the contrary, there are significant decreasing fire trends in forests and savannas in South China where it is most densely vegetated. This study provides an overall analysis of the spatio-temporal fire changes from satellite products, and it may help to understand the fire risk in the changing climate for a better risk management.

scholarly journals Highlighting the Sustainability Implications of Urbanisation: A Comparative Analysis of Two Urban Areas in Ghana

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 300 ◽  
Author(s):  
Kwasi Anarfi ◽  
Ross A. Hill ◽  
Chris Shiel
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Tenure ◽  
Urban Areas ◽  
Local Level ◽  
Population Data ◽  
Temporal Analysis ◽  
Resource Extraction ◽  
Market Forces ◽  
Spatio Temporal

Ghana is urbanising rapidly, and over half of the country’s population have lived in urban areas since 2010. Although research has proliferated to explore Ghana’s urbanisation, there is a dearth of research that holistically explores the wider sustainability implications of urbanisation, offers comparative perspectives in the context of large and smaller urban areas, and provides a perspective of local level urbanisation in the context of resource extraction (mining). This study comparatively assesses two urban areas in Ghana (Kumasi and Obuasi), by conducting a spatio-temporal analysis of land cover change through remote sensing and by analysing demographic change through a synthesis of published population data, in order to highlight the sustainability implications of urbanisation. The results show that urbanisation has been rapid, and has resulted in changes in land cover and demography in Kumasi and Obuasi. The sustainability implications of urbanisation are identified to include limited economic opportunities, socio-spatial segregation, and destruction of natural vegetation. The evidence in this study provides insights into urbanisation in Ghana, and suggests that the positive sustainability impacts of urbanisation may be eroded by how factors such as market forces and land tenure interact at the local level.

scholarly journals Spatio-Temporal Sub-Pixel Land Cover Mapping of Remote Sensing Imagery Using Spatial Distribution Information From Same-Class Pixels

2020 ◽  
Vol 12 (3) ◽  
pp. 503
Author(s):  
Li ◽  
Chen ◽  
Foody ◽  
Wang ◽  
Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Spatial Resolution ◽  
Temporal Frequency ◽  
Land Cover Mapping ◽  
Remote Sensing Images ◽  
Ancillary Data ◽  
Data Set ◽  
Spatio Temporal ◽  
Land Cover Maps

The generation of land cover maps with both fine spatial and temporal resolution would aid the monitoring of change on the Earth’s surface. Spatio-temporal sub-pixel land cover mapping (STSPM) uses a few fine spatial resolution (FR) maps and a time series of coarse spatial resolution (CR) remote sensing images as input to generate FR land cover maps with a temporal frequency of the CR data set. Traditional STSPM selects spatially adjacent FR pixels within a local window as neighborhoods to model the land cover spatial dependence, which can be a source of error and uncertainty in the maps generated by the analysis. This paper proposes a new STSPM using FR remote sensing images that pre- and/or post-date the CR image as ancillary data to enhance the quality of the FR map outputs. Spectrally similar pixels within the locality of a target FR pixel in the ancillary data are likely to represent the same land cover class and hence such same-class pixels can provide spatial information to aid the analysis. Experimental results showed that the proposed STSPM predicted land cover maps more accurately than two comparative state-of-the-art STSPM algorithms.

scholarly journals Evaluating the reliability of time series land cover maps by exploiting the hidden Markov model

2020 ◽  
Author(s):  
Guang Yang ◽  
Shenghui Fang ◽  
Wenbing Gong ◽  
Yaolong Zhao ◽  
Mengyu Ge
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Satellite Remote Sensing ◽  
Hidden Markov ◽  
Joint Probability ◽  
Classification Performance ◽  
Remote Sensing Images ◽  
Temporal Relationships ◽  
Spatio Temporal ◽  
Land Cover Maps

Abstract Time series land cover maps are important materials for the work related to land use and land cover change. Satellite remote sensing images prove advantageous in fast mapping with low cost. In most time series land cover products yielded by the satellite remote sensing images, a number of illogical transitions exist between different time phases. The time series land cover products cannot exactly reflect the real land cover types and land cover changes for each pixel. The accuracy evaluation based on the limited ground truth cannot well guide the users because the reliability of different pixels of the land cover products is unknown. A generic model for the reliability evaluation of time series land cover products should be developed based on a strong theoretical frame. In order to better guide the use of the land cover products, this paper proposed an approach to evaluate the reliability of time series land cover products by exploiting the joint probability of hidden Markov model (HMM), in which the classification performance and the spatio-temporal relationships were taken into account. We applied the proposed evaluation method on the time series land cover maps of Poyang Lake Eco-economic Region in China. The reliability of the land cover products was presented by the grading of the joint probability of HMM. The results effectively reflected the classification performance, the spatio-temporal relationships and even the quality of the data source.

scholarly journals First comprehensive quantification of annual land use/cover from 1990 to 2020 across mainland Vietnam

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Duong Cao Phan ◽  
Ta Hoang Trung ◽  
Van Thinh Truong ◽  
Taiga Sasagawa ◽  
Thuy Phuong Thi Vu ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Environmental Changes ◽  
Wetland Loss ◽  
Interdisciplinary Studies ◽  
Data Sets ◽  
Automatic Production ◽  
The Sustainable Development ◽  
Spatio Temporal

AbstractExtensive studies have highlighted a need for frequently consistent land cover information for interdisciplinary studies. This paper proposes a comprehensive framework for the automatic production of the first Vietnam-wide annual land use/land cover (LULC) data sets (VLUCDs) from 1990 to 2020, using available remotely sensed and inventory data. Classification accuracies ranged from 85.7 ± 1.3 to 92.0 ± 1.2% with the primary dominant LULC and 77.6 ± 1.2% to 84.7 ± 1.1% with the secondary dominant LULC. This confirmed the potential of the proposed framework for systematically long-term monitoring LULC in Vietnam. Results reveal that despite slight recoveries in 2000 and 2010, the net loss of forests (19,940 km2) mainly transformed to croplands over 30 years. Meanwhile, productive croplands were converted to urban areas, which increased approximately ten times. A threefold increase in aquaculture was a major driver of the wetland loss (1914 km2). The spatial–temporal changes varied, but the most dynamic regions were the western north, the southern centre, and the south. These findings can provide evidence-based information on formulating and implementing coherent land management policies. The explicitly spatio-temporal VLUCDs can be benchmarks for global LULC validation, and utilized for a variety of applications in the research of environmental changes towards the Sustainable Development Goals.

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