scholarly journals Land Use Land Cover Change and its Pathways in Sidin VDC, Panchthar District, Nepal

2018 ◽  
Vol 11 ◽  
pp. 77-94 ◽  
Author(s):  
Prem Sagar Chapagain ◽  
Mohan Kumar Rai ◽  
Basanta Paudel
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Time Series Data ◽  
Household Survey ◽  
Human Interaction ◽  
Series Data ◽  
Land Use Land Cover ◽  
Important Indicator

Land use/land cover situation is an important indicator of human interaction with environment. It reflects both environmental situation and the livelihood strategies of the people in space over time. This paper has attempted to study the land use/ land cover change of Sidin VDC, in the Koshi River basin in Nepal, based on maps and Remote sensing imageries (RS) data and household survey using structured questionnaires, focus group discussion and key informant interview. The study has focused on analysis the trend and pathways of land use change by dividing the study area into three elevation zones – upper, middle and lower. The time series data analysis from 1994-2004-2014 show major changes in forest and agricultural land. The dominant pathways of change is from forest to agriculture and forest to shrub during 1994-2004 and agriculture to forest during 2004-2014. The development of community forest, labor migration and labor shortage are found the major causes of land use change.The Geographical Journal of NepalVol. 11: 77-94, 2018

scholarly journals Land Cover Change Detection Using Object-Based Classification Technique: A Case Study Along The Kosi River, Bihar

2014 ◽  
Vol XL-8 ◽  
pp. 839-843 ◽  
Author(s):  
M. Modi ◽  
R. Kumar ◽  
G. Ravi Shankar ◽  
T.R. Martha
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Time Series Data ◽  
Feature Space ◽  
Series Data ◽  
Land Use Land Cover ◽  
Shape Context ◽  
Object Property ◽  
Object Based ◽  
Remote Sensing Techniques

Land use/land cover (LULC) is dynamic in nature and can affect the ability of land to sustain human activities. The Indo-Gangetic plains of north Bihar in eastern India are prone to floods, which have a significant impact on land use / land cover, particularly agricultural lands and settlement areas. Satellite remote sensing techniques allow generating reliable and near-realtime information of LULC and have the potential to monitor these changes due to periodic flood. Automated methods such as object-based techniques have better potential to highlight changes through time series data analysis in comparison to pixel-based methods, since the former provides an opportunity to apply shape, context criteria in addition to spectral criteria to accurately characterise the changes. In this study, part of Kosi river flood plains in Supaul district, Bihar has been analysed to identify changes due to a flooding event in 2008. Object samples were collected from the post-flood image for a nearest neighbourhood (NN) classification in an object-based environment. Collection of sample were partially supported by the existing 2004–05 database. The feature space optimisation procedure was adopted to calculate an optimum feature combination (i.e. object property) that can provide highest classification accuracy. In the study, for classification of post-flood image, best class separation was obtained by using distance of 0.533 for 28 parameters out of 34. Results show that the Kosi flood has resulted in formation of sandy riverine areas.

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 FATE OF AGRICULTURAL AREAS OF KAILALI DISTRICT OF NEPAL: A TEMPORAL LAND USE LAND COVER CHANGE (LUCC) ANALYSIS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1601-1606
Author(s):  
◽  
L. Thapa ◽  
D. P. Shukla
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Data ◽  
Management Practices ◽  
Agricultural Land ◽  
Local Population ◽  
Google Earth ◽  
Series Data ◽  
Land Use Land Cover ◽  
Land Resources

Abstract. Changes of agricultural land into non-agricultural land is the main issue of increasing population and urbanization. The objective of this paper is to identify the various land resources and its changes into other Land Use Land Cover (LULC) type. LANDSAT satellite data for 1990, 2000, 2010 and 2018 years of Kailali district Nepal was acquired for supervised LULC mapping and change analysis using ENVI 5.4 software. Sentinel-2 and Google earth satellite data were used for the accuracy assessment of the LULC map. The time-series data analysis from 1990–2000–2010–2018 shows major changes in vegetation and agriculture. The changes in LULC show that settlement and bare land is continuously increasing throughout these years. The change in land use and land cover during the period of 1990–2018 shows that the settlement area is increased by 204%; and agriculture is decreased by 57%. The fluctuating behavior of vegetation, agriculture and water bodies in which the areas decrease and increase over the selected periods is due to natural calamities and migration of the local population. This shows that human influence on the land resources is accelerating and leading to a deterioration of agricultural land. Thus effective agricultural management practices and policies should be carried out at the government level for minimizing land resources degradation by the human-induced impact.

Land use/land cover (LULC) classification with MODIS time series data and validation in the Amur River Basin

2011 ◽  
Vol 32 (1) ◽  
pp. 9-15 ◽  
Author(s):  
Kaishan Song ◽  
Zongmin Wang ◽  
Qingfeng Liu ◽  
Dianwei Liu ◽  
V. V. Ermoshin ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
River Basin ◽  
Time Series Data ◽  
Series Data ◽  
Amur River Basin ◽  
Land Use Land Cover ◽  
Amur River ◽  
The Amur River

scholarly journals A Study of Diffusion Equation-Based Land-Use/Land-Cover Change Simulation

2021 ◽  
Vol 10 (6) ◽  
pp. 383
Author(s):  
Min Jin ◽  
Ruyi Feng ◽  
Lizhe Wang ◽  
Jining Yan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Diffusion Equation ◽  
Land Cover Change ◽  
Change Process ◽  
Urban Land ◽  
Urban Land Use ◽  
Series Data ◽  
Land Cover Changes ◽  
Land Use Land Cover

Simulating and predicting the development and changes in urban land change can provide valuable references for the sustainable development of cities. However, the change process of urban land-use/land-cover is a complex process involving multiple factors and multiple relationships. This dilemma makes it very challenging to accurately simulate the results and to make predictions. In response to this problem, we started with the physical characteristics of the land-use/land-cover change process and constructed a diffusion equation to simulate and predict urban land-use/land-cover changes. The diffusion equation is used to describe the diffusion characteristics of the land-use/land-cover change process, which helps to understand the urban land-use/land-cover change process. The experimental results show that (1) the diffusion equation we constructed can simulate urban land-use/land-cover changes, (2) the simulation process of the model is not limited by the time interval of the time series data itself, and (3) the model only requires one parameter without other constraints.

scholarly journals Seasonal land use land cover change and the drivers in Kafta-Sheraro National Park, Tigray, Ethiopia

2021 ◽  
Author(s):  
Fitsum Temesgen ◽  
Bikila Warkineh ◽  
Alemayehu Hailemicael
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
National Park ◽  
Vegetation Index ◽  
Local Community ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Cultivated Land

AbstractKafta-sheraro national park (KSNP) is one of the homes of the African elephant has experienced extensive destruction of woodland following regular land use & land cover change in the past three decades, however, up to date, data and documentation detailing for these changes are not addressed. This study aims to evaluate the land use land cover change and drivers of change that occurred between 1988 and 2018. Landsat 5(TM), Landsat7 (ETM+), and Landsat 8 (OLI/TIRs) imagery sensors, field observation, and socio-economic survey data were used. The temporal and spatial Normalized difference vegetation index (NDVI) was calculated and tested the correlation between NDVI and precipitation/temperature. The study computed a kappa coefficient of the dry season (0.90) and wet season (0.845). Continuous decline of woodland (29.38%) and riparian vegetation (47.11%) whereas an increasing trend of shrub-bushland (35.28%), grassland (43.47%), bareland (27.52%), and cultivated land (118.36 km2) were showed over thirty years. More results showed bare land was expanded from wet to drier months, while, cultivated land and grazing land increased from dry to wet months. Based on the NDVI result high-moderate vegetation was decreased by 21.47% while sparse & non-vegetation was expanded by 19.8% & 1.7% (36.5 km2) respectively. Settlement & agricultural expansion, human-induced fire, firewood collection, gold mining, and charcoal production were the major proximate drivers that negatively affected the park resources. Around KSNP, the local community livelihood depends on farming, expansion of agricultural land is the main driver for woodland dynamics/depletion and this leads to increase resources competition and challenges for the survival of wildlife. Therefore, urgent sustainable conservation of park biodiversity via encouraging community participation in conservation practices and preparing awareness creation programs should be mandatory.

scholarly journals Time-Series analysis of MODIS NDVI data along with ancillary data for Land use/Land cover mapping of Uttarakhand

2014 ◽  
Vol XL-8 ◽  
pp. 1491-1500 ◽  
Author(s):  
S. K. Patakamuria ◽  
S. Agrawal ◽  
M. Krishnaveni
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
National Parks ◽  
Vegetation Index ◽  
Time Series Data ◽  
Series Data ◽  
Wide Field ◽  
Land Use Land Cover ◽  
Ancillary Data

Land use and land cover plays an important role in biogeochemical cycles, global climate and seasonal changes. Mapping land use and land cover at various spatial and temporal scales is thus required. Reliable and up to date land use/land cover data is of prime importance for Uttarakhand, which houses twelve national parks and wildlife sanctuaries and also has a vast potential in tourism sector. The research is aimed at mapping the land use/land cover for Uttarakhand state of India using Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The study also incorporated smoothening of time-series plots using filtering techniques, which helped in identifying phenological characteristics of various land cover types. Multi temporal Normalized Difference Vegetation Index (NDVI) data for the year 2010 was used for mapping the Land use/land cover at 250m coarse resolution. A total of 23 images covering a single year were layer stacked and 150 clusters were generated using unsupervised classification (ISODATA) on the yearly composite. To identify different types of land cover classes, the temporal pattern (or) phenological information observed from the MODIS (MOD13Q1) NDVI, elevation data from Shuttle Radar Topography Mission (SRTM), MODIS water mask (MOD44W), Nighttime Lights Time Series data from Defense Meteorological Satellite Program (DMSP) and Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) data were used. Final map product is generated by adopting hybrid classification approach, which resulted in detailed and accurate land use and land cover map.

scholarly journals Land use/land cover change assessment of Mohana watershed (Far-Western Nepal) using GIS and remote sensing

2021 ◽  
Vol 6 (3) ◽  
pp. 320-328
Author(s):  
Suraj Prasad Bist ◽  
Rabindra Adhikari ◽  
Raju Raj Regmi ◽  
Rajan Subedi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Water Bodies ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land ◽  
Gis And Remote Sensing

The present study was conducted in the Mohana watershed of Far-western Nepal to assess land use land cover change. The study has used ArcGIS and three Landsat images - Landsat TM (1999), Landsat ETM+ (2009), and Landsat OLI (2019) – to analyze land use the land cover change of the watershed. The change matrix technique was used for change detection analysis. The study area was classified into five classes; forest, agriculture, built-up, water bodies, and barren lands. The study has found that among the five identified classes forest and build-up increased positively from 45.40 % to 51.51 % - forest cover and 11.26 % to 19. 85 % - build-up respectively. Similarly, agricultural land and water bodies initially increased but after 2009 both land cover areas decreased to 23.79 % and 0.73 % from 31.38 % and 0.97 % in 2009 respectively. Barren land decreased from 15.37% to 4.12% over the last 20 years. This study might support land-use planners and policymakers to adopt the best suitable land use management option for the Mohana watershed.

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