scholarly journals Forest cover monitoring of Bara district (Nepal) using remote sensing and geographic information systems

1970 ◽  
Vol 20 (1) ◽  
pp. 30-36
Author(s):  
CM Kandel ◽  
M Caetano ◽  
P Cabral
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Area ◽  
Geographical Information ◽  
Forest Cover Change ◽  
Change Analysis ◽  
Spatial Metrics ◽  
Land Cover Maps

This study uses Landsat TM of 1989 and ETM+ of 1999 and 2005 imagery to evaluateforest cover dynamics during 1989-2005 in the Bara district of Nepal. The aim of thestudy was to analyse the extent and trend of forest cover dynamics, spatial pattern offorest and their driving forces. Forest cover change analysis was performed using objectorientedclassification approach applying a standard nearest neighbour algorithm to classifythe image in recognition. The overall classification accuracies were 85.71% and 88.23%for the year 1999 and 2005, respectively. Land cover maps were produced with sevenland cover categories and were further reclassified as forest and non-forest areas toanalyse the forest cover dynamics. Post-classification and time series analysis were carriedout to detect the changes. Spatial metrics were computed for detecting the spatial patternof forest. The classifications suggested that the amount of forest land had decreased by11.56% during 1989-2005. Spatial metrics revealed that forest area has been fragmentedand deforested with an annual rate of 0.72%. The overall result demonstrates that forestarea has experienced a significant shrinkage and mostly transferred into agricultural andbare land. Expected change for the year 2021 was projected using Markov Chain Analysis(MCA). The MCA result showed that forest area would decrease by 8.5% in the period of2005-2021.Key words: Forest cover dynamics; geographical information systems; landsat; remotesensing; spatial metricsDOI: 10.3126/banko.v20i1.3506Banko Janakari, Vol. 20, No. 1 pp.30-36

scholarly journals Forest Cover Change Analysis Using Remote Sensing Techniques in Madhupur Sal Forest of Bangladesh

2018 ◽  
Vol 10 (2) ◽  
pp. 73-78
Author(s):  
MA Salam ◽  
MAT Pramanik
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Resources ◽  
Forest Monitoring ◽  
Forest Damage ◽  
Landsat 8 ◽  
Forest Cover Change ◽  
Change Analysis ◽  
Sal Forest

Deforestation, degradation, damages, transformation and over exploitation of forests are the common problem in different parts of the world. Timely monitoring and assessment of forest resources may help to address and identify the above mentioned problems and thus proper guidance may be given the forest resources manager for rational planning and management of forests. Apart from the conventional methods of forest monitoring, remote sensing with its unique capability of synoptic viewing, real time and repetitive nature offers a potential tool for monitoring and evaluation of forest resources and hence remote sensing technology has been successfully used in various studies like forest inventory, monitoring of forest cover changes and forest damage assessment. In the present research forest cover change analysis in ‘Madhupur Sal Forest’ located in central part of Bangladesh has been investigated using satellite remote sensing data and spatial analysis. Transformation of ‘Sal forest’ to other landuse has been studied using the Landsat MSS (Multi Spectral Scanner) data of 1973 and Landsat 8 OLI (Operational Land Imager) data of 2015. Driving forces behind the transformation of ‘Sal forest’ has also been investigated through GPS (Global Positioning System) based ground verification and interview with the people living in the locality.J. Environ. Sci. & Natural Resources, 10(2): 73-78 2017

scholarly journals Understanding Current and Future Fragmentation Dynamics of Urban Forest Cover in the Nanjing Laoshan Region of Jiangsu, China

2020 ◽  
Vol 12 (1) ◽  
pp. 155 ◽  
Author(s):  
Wenjuan Shen ◽  
Xupeng Mao ◽  
Jiaying He ◽  
Jinwei Dong ◽  
Chengquan Huang ◽  
...  
Keyword(s):  
Land Cover ◽  
Markov Model ◽  
Forest Cover ◽  
Urban Forest ◽  
Detection Algorithm ◽  
Forest Area ◽  
Spatiotemporal Pattern ◽  
Forest Cover Change ◽  
Forest Interior ◽  
Land Cover Maps

Accurate acquisition of the spatiotemporal distribution of urban forests and fragmentation (e.g., interior and intact regions) is of great significance to contributing to the mitigation of climate change and the conservation of habitat biodiversity. However, the spatiotemporal pattern of urban forest cover changes related with the dynamics of interior and intact forests from the present to the future have rarely been characterized. We investigated fragmentation of urban forest cover using satellite observations and simulation models in the Nanjing Laoshan Region of Jiangbei New Area, Jiangsu, China, during 2002–2023. Object-oriented classification-based land cover maps were created to simulate land cover changes using the cellular automation-Markov chain (CA-Markov) model and the state transition simulation modeling. We then quantified the forest cover change by the morphological change detection algorithm and estimated the forest area density-based fragmentation patterns. Their relationships were built through the spatial analysis and statistical methods. Results showed that the overall accuracies of actual land cover maps were approximately 83.75–92.25% (2012–2017). The usefulness of a CA-Markov model for simulating land cover maps was demonstrated. The greatest proportion of forest with a low level of fragmentation was captured along with the decreasing percentage of fragmented area from 81.1% to 64.1% based on high spatial resolution data with the window size of 27 pixels × 27 pixels. The greatest increase in fragmentation (3% from 2016 to 2023) among the changes between intact and fragmented forest was reported. However, intact forest was modeled to have recovered in 2023 and restored to 2002 fragmentation levels. Moreover, we found 58.07 km2 and 0.35 km2 of interior and intact forests have been removed from forest area losses and added from forest area gains. The loss rate of forest interior and intact area exceeded the rate of total forest area loss. However, their approximate ratio (1) implying the loss of forest interior and intact area would have slight fragmentation effects on the remaining forests. This analysis illustrates the achievement of protecting and restoring forest interior; more importantly, excessive human activities in the surrounding area had been avoided. This study provides strategies for future forest conservation and management in large urban regions.

scholarly journals FOREST COVER CHANGE ANALYSIS IN INNER MONGOLIA USING REMOTE SENSING DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 1951-1954
Author(s):  
S. Xie ◽  
J. Gong ◽  
X. Huang
Keyword(s):  
Protected Area ◽  
Inner Mongolia ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Shape Index ◽  
Forest Area ◽  
Forest Cover Change ◽  
Forest Change ◽  
Change Analysis ◽  
Forest Patches

Forest is the lung of the earth, and it has important effect on maintaining the ecological balance of the whole earth. This study was conducted in Inner Mongolia during the year 1990–2015. Land use and land cover data were used to obtain forest cover change of Inner Mongolia. In addition, protected area data, road data, ASTER GDEM data were combined with forest cover change data to analyze the relationship between them. Moreover, patch density and landscape shape index were calculated to analyze forest change in perspective of landscape aspect. The results indicated that forest area increased overall during the study period. However, a few cities still had a phenomenon of reduced forest area. Results also demonstrated that the construction of protected area had positive effect on protecting forest while roads may disturbed forest due to human activities. In addition, forest patches in most of cities of Inner Mongolia tended to be larger and less fragmented. This paper reflected forest change in Inner Mongolia objectively, which is helpful for policy making by government.

Analysis of dynamic changes in the urbanization of Xixian National New Area and its driving forces

2018 ◽  
Vol 28 (9) ◽  
pp. 1181-1189
Author(s):  
Yue Chang ◽  
Kang Hou ◽  
Xuxiang Li ◽  
Yue Zhang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Driving Forces ◽  
Geographical Location ◽  
Geographical Information ◽  
Location Factors ◽  
Dynamic Changes ◽  
Construction Land

This study analysed the dynamic changes and driving forces in the urbanization from 1997 to 2016 of Xixian, a national new development area in Xi’an City, by using geographical information systems and remote sensing. The results showed that farmland was the main land use type from 1997 to 2004. However, the construction land occupied the largest area from 2011 to 2016. There was a significant expansion in the construction land area (33.24%), unused land (91.10%) and woodland (37.59%) from 1997 to 2016. In addition, in the period from 1997 to 2016, the water body, grassland and farmland were reduced by 52.52%, 31.73% and 23.84%, respectively. The increasing area of construction land was the inevitable result of urbanization. The terrain, policy and geographical location factors are the main driving forces for changes in the land use and urbanization. The planning of Xixian National New Area’s building environment should be linked and connected with the Xi’an main districts. The findings confirmed the applicability and effectiveness of the combined method of geographical information systems and remote sensing for revealing the notable spatio-temporal features in the dynamic changes in the land use and land cover throughout different time periods of Xixian.

scholarly journals An Assessment of Forest Cover Change and Its Driving Forces in the Syrian Coastal Region during a Period of Conflict, 2010 to 2020

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 191
Author(s):  
Mohamed Ali Mohamed
Keyword(s):  
Forest Fires ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Resources ◽  
Climatic Conditions ◽  
Forest Area ◽  
Forest Cover Change ◽  
Landsat Images ◽  
Syrian Coast ◽  
Coast Region

In Syria, 76% of the forests are located in the Syrian coast region. This region is witnessing a rapid depletion of forest cover during the conflict that broke out in mid-2011. To date, there have been no studies providing accurate, reliable, and comprehensive data on the qualitative and quantitative aspects of forest change dynamics and the underlying drivers behind this change. In this study, changes in the dynamics of forest cover and its density between 2010 and 2020 were detected and analyzed using multi-temporal Landsat images. This study also analyzed the relationship between changes in forest cover and selected physical and socio-demographic variables associated with the drivers of change. The results revealed that the study area witnessed a significant decrease in the total forest area (31,116.0 ha, 24.3%) accompanied by a considerable decrease in density, as the area of dense forests decreased by 11,778.0 ha (9.2%) between 2010 and 2020. The change in forest cover was driven by a variety of different factors related to the conflict. The main drivers were changes in economic and social activities, extensive exploitation of forest resources, frequent forest fires, and weakness of state institutions in managing natural resources and environmental development. Forest loss was also linked to the expansion of cultivated area, increase in population and urban area. Fluctuating climatic conditions are not a major driver of forest cover dynamics in the study area. This decrease in forest area and density reflects sharp shifts in the natural environment during the study period. In the foreseeable future, it is not possible to determine whether the changes in forest cover and its density will be permanent or temporary. Monitoring changes in forest cover and understanding the driving forces behind this change provides quantitative and qualitative information to improve planning and decision-making. The results of this study may draw the attention of decision-makers to take immediate actions and identify areas of initial intervention to protect current the forests of the Syrian coast region from loss and degradation, as well as develop policies for the sustainable management of forest resources in the long term.

scholarly journals Assessment of Forest Cover Change of Dang, an Inner Terai District of Nepal

2019 ◽  
Vol 1 (1) ◽  
pp. 40-51
Author(s):  
Yam Bahadur K.C.
Keyword(s):  
Land Cover ◽  
Supervised Classification ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Land ◽  
Forest Cover Change ◽  
Change Analysis ◽  
Landsat Tm Image ◽  
Tm Image ◽  
Dense Forest

This study analyzed the dynamics of changes of forest cover classes in the inner Terai District Dang, Nepal, based on Landsat Thematic Mapper (TM) images from two different years, viz., 1990 and 2011. Forest cover change analysis was performed through the analysis of a classified Landsat TM image using supervised classification. The overall classification accuracy for seven different land cover classes considered in this study were 80.37% and 80.56% for years 1990 and 2011, respectively. These classified images were further reclassified as forest and non-forest to analyze forest cover dynamics effectively using the post classification change detection. The results indicated that during 1990-2011, the total spatial areal coverage of forest land converted into other land cover was 20612 ha (shrub-land), 8571 ha (agriculture), and 2787 ha (others) non-forest classes. A significant portion of non-forest classes was also converted into forest (e.g., 11433 ha of shrubland, 5663 ha of agriculture, and 5581 ha of other non forest classes). Sand and water bodies remained more or less constant during this period. While forest cover was estimated to be disappearing at the rate of 0.2% per year, dense forest appears to be converting into a sparse forest at the rate of 0.1% per year. Future study to assess the causes and driving forces of forest cover change in Nepal should get guidance from this study on where to target interventions.

PROBLEMATIC ISSUES OF THE GEOGRAPHIC INFORMATION SYSTEMS USE IN SOCIO-HYGIENIC MONITORING AND RISK-BASED SUPERVISION

2019 ◽  
pp. 31-36 ◽  
Author(s):  
Е.М. Studenikina ◽  
Yu.I. Stepkin ◽  
O.V. Klepikov ◽  
I.V. Kolnet ◽  
L.V. Popova
Keyword(s):  
Information Systems ◽  
Technology Implementation ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Electronic Library ◽  
Information Portal ◽  
Software Products ◽  
Stage Of Development ◽  
Software Product ◽  
Information Systems Use

The paper considers the problematic issues of the geographical information systems (GIS) use in the sociohygienic monitoring (SHM). We analyzed scientific and practical publications on this subject that are freely available on the largest Russian information portal of scientific electronic library eLIBRARY.RU during 2014- 2018, which allowed us to formulate the principles of organization and requirements for effective operation of geographic and information systems in the socio-hygienic monitoring. An analysis of the implementation of these principles at the present stage of development for the socio-hygienic monitoring system is presented, the results of which were used in formulating priority tasks in the area of geographic and information technology implementation into socio-hygienic monitoring and risk-based planning of control and supervisory measures: to determine the necessary level of detail and an information list depicted on electronic maps for the implementation of risk-based control planning; to provide organizational and regulatory and methodological support for the hierarchical principle of GIS within Rospotrebnadzor operating on a single software product of domestic developers for organizations and institutions; to work out the need to combine GIS with similar systems of other departments involved in the data collection of social and hygienic monitoring (Rosstat, Roshydromet, Rosprirodnadzor, Ministry of Health, etc.) to enable automated data export and import; to solve staffing issues to ensure customization and subsequent GIS operation; to provide budget funding for the purchase of licensed software products for GIS in SHM, preferably of Russian developers.

Sign in / Sign up

Export Citation Format

Share Document