scholarly journals Land-Use Change in New Moscow: First Outcomes after Five Years of Urbanization

2019 ◽  
Vol 12 (4) ◽  
pp. 24-34 ◽  
Author(s):  
Viacheslav I. Vasenev ◽  
Alexey M. Yaroslavtsev ◽  
Ivan I. Vasenev ◽  
Sofiya A. Demina ◽  
Elvira A. Dovltetyarova
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Spectral Resolution ◽  
Environmental Changes ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Fallow Lands ◽  
Forested Areas ◽  
New Moscow

Urbanization coincides with remarkable environmental changes, including conversion of natural landscapes into urban. Moscow megapolis is among the largest urbanized areas in Europe. An ambitious New Moscow project expanded the megapolis on extra 1500 km2 of former fallow lands, croplands and forests. The research aimed to monitor land use changes in New Moscow between 1989 and 2016 years. Landsat 5 and Landsat 8 images (30 m spectral resolution) and Sentinel – 2 images (10 m spectral resolution) were analyzed. All the images were collected for the similar summer period (from June to August). The images were preprocessed and classified by Semi-Automatic Classification Plugin in open source QGIS software to derive land cover maps. The following land cover classes were identified: water, built-up areas, bare soils, croplands and forested areas, and the total area covered by each class was estimated. The following land-use change pathways were reported: 1) reduction of the forested areas by 2.5% (almost 2000 ha) between 1989 and 1998; 2) partial reforestation (more than 1000 ha) and abandonment of croplands (more than 3000 ha) between 1998 and 2010 and 3) intensive urbanization (more than 11000 ha) between 2010 and 2016. New build-up areas and infrastructures were constructed on former forested areas and croplands. Although, some uncertainties in the absolute estimates are expected due to the classification errors, the general urbanization trend can be clearly distinguished as a principal outcome after the five years of New Moscow project.

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

scholarly journals Remote Sensing Application for Exploring Land Use and Land Cover Dynamics in and Around Chatra Wetland, English Bazar, West Bengal

2021 ◽  
Vol 9 (1) ◽  
pp. 15-27
Author(s):  
Saleha Jamal ◽  
Md Ashif Ali
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Changes ◽  
United States Geological Survey ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Erdas Imagine ◽  
Landsat 7 ◽  
Vegetation Water

Wetlands are often called as biological “supermarket” and “kidneys of the landscape” due to their multiple functions, including water purification, water storage, processing of carbon and other nutrients, stabilization of shorelines and support of aquatic lives. Unfortunately, although being dynamic and productive ecosystem, these wetlands have been affected by human induced land use changes. India is losing wetlands at the rate of 2 to 3 per cent each year due to over-population, direct deforestation, urban encroachment, over fishing, irrigation and agriculture etc (Prasher, 2018). The present study tries to investigate the nature and degree of land use/land cover transformation, their causes and resultant effects on Chatra Wetland. To fulfil the purpose of the study, GIS and remote sensing techniques have been employed. Satellite imageries have been used from United States Geological Survey (USGS) Landsat 7 Enhanced Thematic Mapper plus and Landsat 8 Operational Land Imager for the year 2003 and 2018. Cloud free imageries of 2003 and 2018 have been downloaded from USGS (https://glovis.usgs.gov/) for the month of March and April respectively. Image processing, supervised classificationhas been done in ArcGis 10.5 and ERDAS IMAGINE 14. The study reveals that the settlement hasincreased by about 90.43 per cent in the last 15 years around the Chatra wetland within the bufferzone of 2 Sq km. Similarly agriculture, vegetation, water body, swamp and wasteland witnessed asignificant decrease by 5.94 per cent, 57.69 per cent, 26.64 per cent 4.52 per cent and 55.27 per centrespectively from 2003 to 2018.

scholarly journals Global Transition Rules for Translating Land-use Change (LUH2) To Land-cover Change for CMIP6 using GLM2

2019 ◽  
Author(s):  
Lei Ma ◽  
George C. Hurtt ◽  
Louise P. Chini ◽  
Ritvik Sahajpal ◽  
Julia Pongratz ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Human Impacts ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Transition Rule ◽  
The Relationship ◽  
Earth System Models

Abstract. Information on historical land-cover change is important for understanding human impacts on the environment. Over the last decade, global models have characterized historical land-use changes, but few have been able to relate these changes with corresponding changes in land-cover. Utilizing the latest global land-use change data, we make several assumptions about the relationship between land-use and land-cover change, and evaluate each scenario with remote sensing data to identify optimal fit. The resulting transition rule can guide the incorporation of land-cover information within earth system models.

scholarly journals STUDY OF LAND USE CHANGES AND ITS RELATIONSHIP WITH TEMPERATURE AND DENGUE FEVER IN 2003 AND 2016 OVER JAKARTA PROVINCE USING LANDSAT 7+ETM AND LANDSAT 8 OLI

2018 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Risya Lailarahma ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Surface Temperature ◽  
Dengue Fever ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Land Use Changes ◽  
Water Infiltration ◽  
Landsat 8 ◽  
Temperature Changes

Land use changes over Jakarta caused by urbanization affected the increasing of infrastructure and decreasing vegetation from 2003 to 2016. This condition reduced water infiltration and caused inundation when heavy rainfall coming. Then Aedes aegypti would breed.and increased which brought dengue fever desease. This study was about analyzing the land use change in Jakarta Province using Landsat image, and its relationship with land surface temperature and dengue fever distribution. The effects of land use change also analysed by this study which including the effects from temperature and dengue fever that analysed by indices of land use in Jakarta at 2003 and 2016. The temperature analysis could be obtained by TIR band in Landsat and using some algortitma which calculated in band math of ENVI software. Vegetation index value’s average decreased from 0.652 in 2003 to 0.647 2016 in 2016. Built up index value’s average increased from -0.03 in 2003 to -0.02 in 2016. While Bareland index value’s average decreased from 0.16 in 2003 to -0.46 in 2016. Land surface temperature increased 3?C from 2003 to 2016. Vegetation area decreased 27.929 ha, bare land area decreased 6.012 ha, while built up area increased 34.278 ha from 2003 to 2016. Increasing of land surface temperature proportional to increasing dengue fever patients 1.187 patients. Increasing of land surface temperature increasing dengue fever cases 1.187 patients. To review and monitor more about the relationship between landuse changes and temperature changes required image with high resolution so that the results obtained more accurate. Complete data of dengue fever per subdistricts also required to analyse further more about relationship between landuse changes, temperature changes, and dengue fever.

scholarly journals Land use Land Cover Mapping using Modified Ant Colony Optimization Technique

2020 ◽  
Vol 9 (4) ◽  
pp. 100-106
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Ant Colony Optimization ◽  
Classification Accuracy ◽  
Environmental Changes ◽  
Optimization Technique ◽  
Unsupervised Classification ◽  
Ant Colony ◽  
Landsat 8 ◽  
Land Use Land Cover

Land use Land cover classification is an important aspect for managing natural resources and monitoring environmental changes. Urban expansion becomes one of the major challenges for the administrator. The LANDSAT 8 images are processed using the open source GRASS (Geographic Resource Analysis Support System). Unsupervised classification technique based on Ant Colony Optimization (ACO) algorithm has been modified and proposed as Modified Ant Colony Optimization (MACO) for LULC classification. In order to improve the classification accuracy of the proposed algorithm, we have combined spatial, spectral and texture features to extract more information of homogeneous land surface. The classification accuracy of the proposed algorithm has been compared with other unsupervised classification methods such as k-means, ISODATA and ACO algorithms. The overall classification accuracy of proposed unsupervised MACO algorithm has been increased by 11.24 %, 8.24% for open space and water bodies class, respectively as compared to ACO algorithm.

scholarly journals LAND USE/LAND COVER CHANGE DETECTION USING MULTI–TEMPORAL SATELLITE DATASET: A CASE STUDY IN ISTANBUL NEW AIRPORT

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 17-22 ◽  
Author(s):  
D. Akyürek ◽  
Ö. Koç ◽  
E. M. Akbaba ◽  
F. Sunar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Changes ◽  
Satellite Image ◽  
The Black Sea ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Environmental Consequences ◽  
Transportation Capacity ◽  
Sentinel 2A

<p><strong>Abstract.</strong> In recent years, especially in metropolitan cities such as Istanbul, the emerging needs of the increasing population and demand for better air transportation capacity have led to big environmental changes. One of them is originated due to the construction of the new airport (Istanbul Grand Airport &amp;ndash; IGA), located on the Black Sea coast on the European side of Turkey and expected as “The biggest hub in Europe” by the early 2020s. The construction has five phases and first construction phase is scheduled to finish up by the end of 2018. With an advanced space technologies including remote sensing, environmental consequences due to Land Use/Land Cover changes (LULC) can be monitored and determined efficiently. The aim of this paper is to analyse LULC changes especially in the forest areas and water bodies by using two different satellite image dataset. In this context, supervised classification method and different spectral indices are applied to both Landsat-8 (2013&amp;ndash;2017) and Sentinel 2A (2015&amp;ndash;2017) image datasets to demonstrate the total and annual changes during the construction of the first phase. The efficiency of two datasets is outlined by comparison of the output thematic map accuracies.</p>

scholarly journals Land Use and Land Cover Change in Khorezm, Uzbekistan

2021 ◽  
Vol 227 ◽  
pp. 01002
Author(s):  
Sherzod Rakhmonov ◽  
Uktam Umurzakov ◽  
Kosimdjon Rakhmonov ◽  
Iqbol Bozarov ◽  
Ozodbek Karamatov
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Bare Soil ◽  
Aral Sea ◽  
Landsat 8 ◽  
Urban And Regional Planning ◽  
Saline Land

This article depicts on discussions about land use and land cover change distribution in Khorezm province, Uzbekistan between 1987 and 2019. For the study Landsat 5 TM and Landsat 8 OLI respectively used to detect land use changes in the study area. Khorezm region affected by Aral Sea shrinkage having received salt wind from northeast of the region. Moreover, population increased within study period, making population density intense. Research is carried out to detect reflection of ecology and density in land use. RS techniques maximum likelihood employed to classify land use to generate land cover distribution map. In total seven class selected such as agricultural land, built up, bare land, lowland, saline land, sand and waterbody. The research of Khorezm region for 32 years has been thoroughly studied and found out that agricultural land, built up and saline land increased tremendously while lowland and bare soil are decreased accordingly. The result map can be used for decision makers and government bodies for future long term urban and regional planning.

scholarly journals LANDCOVER CHANGES IN COASTAL BUNGUS REGION OF KABUNG BAY, WEST SUMATRA FROM 200-2013 BASED ON GEOGRAPHIC INFORMATION SYSTEM APPLICATION

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Yulius Yulius ◽  
T A Tanto ◽  
M Ramdhan ◽  
A Putra ◽  
H L Salim
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landsat Imagery ◽  
Land Use Changes ◽  
Population Increase ◽  
Landsat 8 ◽  
West Sumatra ◽  
Landsat 7 ◽  
Southern City ◽  
Growing Region

ABSTRACT Bungus district of Kabung Bay is a growing region located at coastal zone of southern city of Padang, west sumatra. As a growing region, the Bungus district brings some impacts on population increase and degradation of environment quality. Therefore, it is needed an effort to identify land use changes and the distribution of land use in this region from the year of 2003 until 2013. This research used landsat 7 imagery in 2003 and landsat 8 imagery in 2013. The data were analysed descriptively using geographical informastion system. The result showd that (1) swamp land cover experienced the smallest land use change between 2003 until 2013 (0.02 ha/yr), meanwhile forest land use had the biggest change of about 224.8 ha/yr. The biggest addition of land cover belong to settlement area about 47.59 hectare, and the other hand occur on bush about -31.68 hectare. Keywords: Bungus district, landcover changes, Landsat imagery, GIS

scholarly journals Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

2020 ◽  
Vol 13 (7) ◽  
pp. 3203-3220 ◽  
Author(s):  
Lei Ma ◽  
George C. Hurtt ◽  
Louise P. Chini ◽  
Ritvik Sahajpal ◽  
Julia Pongratz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Carbon Emissions ◽  
Forest Cover ◽  
Land Use Changes ◽  
Change Models ◽  
Translation Rule

Abstract. Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation in land-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine) rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be 37.42×106 km2, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover.

scholarly journals An analysis of land use change and the workers’ perception towards changes from 2007 – 2017: A case in Nam Tu Liem District, Hanoi, Vietnam

2019 ◽  
Vol 35 (3) ◽  
Author(s):  
Pauline Violanda Hostalero ◽  
Nguyen Thi Ha
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Changes ◽  
The Self ◽  
The Other ◽  
Land Type ◽  
Bare Land ◽  
The Government

Land use change has been assessed widely using Remote Sensing (RS) and Geographic Information System (GIS) techniques. The analysis of land use change was done by detecting land cover change. A study about land cover change, along with the self-employed workers’ perception towards changes between 2007 and 2017 were carried out in Nam Tu Liem District, Hanoi, Vietnam. The result of the study shows that the built-up lands have increased and remained to be the dominant land cover types in 2017. The agriculture has been declining mainly due to conversion into built-up land. Other land type including water, bare land, and vegetation have shown slight changes throughout the years. Overall changes from 2007 to 2017 shown that built-up land gained the most and agriculture land lost the most. On the other hand, the perception study’s major findings indicate that about two-thirds (69%) of respondents are aware of changes. However, almost one-third (31%) are unaware of the said topic. There are several factors that may affect the awareness of self-employed workers which will be cursory discussed in the study. This study in Nam Tu Liem District is a first step to determine and understand the major driving factors and their impacts on the land use changes in the area. A detailed land use/cover change study and a larger population size for perception studies are recommended in order for the government to formulate policies to achieve sustainable development.      

Sign in / Sign up

Export Citation Format

Share Document