Sustainable Management of Bannerghatta National Park, India, with the Insights in Land Cover Dynamics

2019 ◽  
Vol 8 (2) ◽  
pp. 118-131 ◽  
Author(s):  
T. V. Ramachandra ◽  
Bharath Setturu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
National Parks ◽  
Sustainable Management ◽  
National Park ◽  
Forest Cover ◽  
Environmental Changes ◽  
Buffer Zone ◽  
Change Analysis ◽  
Rapid Economic Growth

The ecosystem of health and natural resource management is influenced by the social, political, economic system and institutional framework in a region. Rapid economic growth in Bangalore and its environs in recent decades has resulted in environmental changes in Bannerghatta National Park (BNP) and its buffer (of 5 km). Land use land cover (LULC) change analysis with a modelling technique such as cellular automata (CA)-Markov was used for quantitatively exploring forest cover transitions. The analysis of LULC dynamics has revealed loss of vegetation cover from 85.78 per cent to 66.37 per cent (1973–2015) and severe environmental stress. The region has lost moist deciduous cover, from 26.1 per cent to 13.8 per cent, and witnessed an increase in horticulture, from 8.5 per cent to 11 per cent (1973–2015). The visualization of likely land use in 2027 indicates the loss of forest cover from 41.38 per cent to 35.59 per cent with an increase in urban area from 4.49 per cent to 9.62 per cent (with new residential and commercial layouts in the buffer zone of BNP in violation of the eco-sensitive zone norms as per Section 5(1) of Environment Protection Act 1986). The study provides insights for developing an appropriate planning framework towards conservation and the sustainable management of ecologically sensitive national parks.

scholarly journals Dynamics of land use and land cover in a Mexican national park

2017 ◽  
Vol 23 (3) ◽  
pp. 87-99
Author(s):  
Maria del Rosario Pineda-López ◽  
Ernesto Ruelas Inzunza ◽  
Lázaro Rafael Sánchez-Velásquez ◽  
Marco A. Espinoza Guzmán ◽  
Alberto Rojo Alboreca ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
National Parks ◽  
National Park ◽  
Forest Cover ◽  
Natural Protected Areas ◽  
Micro Scale ◽  
Rates Of Change ◽  
Local Stakeholders ◽  
Use Categories

To understand the dynamics of land cover at the Parque Nacional Cofre de Perote, the rates of change in land use were compared at two different scales during the period 1995-2004. At the meso scale, these patterns were studied throughout the entire Parque Nacional Cofre de Perote, which is one of the 60 priority mountains of Mexico, and an important natural protected area of the country located in the state of Veracruz. At a micro scale, the work was focused in ejido El Conejo, located within the boundaries of this national park. Federal government digital orthophotos were used to determine changes in nine categories of land use. In both, the meso- and micro-scale, it was found that the predominant land cover categories are agriculture and forest. The probabilities of land cover change at both scales are low and essentially the same for most land use categories, reflecting both small gains in forest cover park-wide as well as the effectiveness of the ejido in managing natural resources within the park. The authors consider that the findings of the study may be applicable to the broader situation of national parks in Mexico and, finally, the importance of integrating local stakeholders in the management of natural protected areas is discussed.

Implications of Land Use/Land Cover Change in the Buffer Zone of a National Park in the Tropical Andes

2006 ◽  
Vol 38 (2) ◽  
pp. 238-252 ◽  
Author(s):  
Damion B. Kintz ◽  
Kenneth R. Young ◽  
Kelley A. Crews-Meyer
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
National Park ◽  
Buffer Zone ◽  
Land Use Land Cover ◽  
Tropical Andes

scholarly journals Assessing and preventing deforestation in Kayan Mentarang National Park, North Kalimantan Province, Indonesia

2021 ◽  
Vol 921 (1) ◽  
pp. 012024
Author(s):  
A K M Ginting Monthe ◽  
R Padjung ◽  
P Dale
Keyword(s):  
Land Use ◽  
Land Cover ◽  
National Parks ◽  
National Park ◽  
Agricultural Land ◽  
Mitigation Measures ◽  
Specific Recommendation ◽  
Landsat Images ◽  
Deforestation Rate ◽  
The Government

Abstract National parks in Indonesia are valuable assets for the next generations. The urgency to maintain and protect their existence from land degradation and deforestation is an obligation. Moreover, deforestation is the most severe threat to biodiversity. In Kalimantan, deforestation is happening and usually leads to economic loss and poverty. Despite this habitat loss, our ability to quantify deforestation in certain areas to improve mitigation measures, meet the needs of agricultural land, and increases local communities’ resilience and ensure that their customary rights. This study aims to provide models to assess the deforestation rate in Kayan Mentarang National Park and give recommendation action based on existing Land Use Zonation. To achieve this aim, firstly Landsat images was obtained and analysed to produce land use and land cover classification. However, cloud coverage in this area is more than 30% which is too difficult to classify the land cover area. This research use alternative resources from JAXA to generate deforestation map at study area. Then compile this map into map of Land Use Zonation of KMNP to provide specific location of deforestation occurrence. The result showed that deforestation rate at KMNP is low, around 3% and the Traditional Zone has the biggest amount of deforestation occurrence; 18.727 hectare. This finding would give information to the government of KMNP to accelerate empowerment program among indigenous people in term of utilizing their customary land in this zone. Moreover, this research suggest the best practical way to evaluate deforestation occurrence in KMNP area followed by specific recommendation of each land use zonation of KMNP.

scholarly journals Land Use/Land Cover Changes in the Tlemcen Region (Algeria) and Classification of Fragile Areas

2021 ◽  
Vol 13 (14) ◽  
pp. 7761
Author(s):  
Abdelkader Bardadi ◽  
Zahira Souidi ◽  
Marianne Cohen ◽  
Mohamed Amara
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Fires ◽  
National Park ◽  
Forest Cover ◽  
Land Use Land Cover ◽  
K Nearest Neighbor ◽  
Landsat Images ◽  
Mountain Areas

The Tlemcen region is characterized by very diverse and steep areas exposed to gravity hazards, especially in high and medium mountain areas. Tlemcen National Park was chosen for this study, the main objective of which is to map fragile areas in close relation to reduced vegetation cover due to land-use changes and forest fires. Multi-source data were used to monitor land use/land cover (LULC)patterns in the study area between 1987 and 2017. The methodology is based on an object-oriented classification of the Landsat images, using the K nearest neighbor method for mapping the major LULC classes at the national park level. The results show that LULC is constantly changing in the study area. In 1987, the landscape was made up of (16.5%) oak forests (holm oak, cork oak, zean oak) and Aleppo pine, which then deteriorated following repeated fires in the nineties to barely represent 7.22% of the surface in 1995, followed by a fast forest reclamation, with the forest area doubling in 10 years (13.46% of the area in 2005), and a near stabilization of the forest cover in 2017 with 14.68% of the area. These mutations are mainly due to fluctuations in anthropogenic action. Despite past declines and disturbances, the current forested area in the Tlemcen area represents significant forest capital classified as a national park to be protected and developed.

scholarly journals Land Use and Land Cover Change Analysis Using GIS and Remote Sensing in The Case of Kersa District, Jimma Zone, Oromia Region, Ethiopia

2021 ◽  
Author(s):  
Nigus Tekleselassie Tsegaye
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
Natural Forest ◽  
Landsat 8 ◽  
Change Analysis ◽  
Object Based

Abstract Background: Land use and land cover change is driven by human actions and also drives changes that limit availability of products and services for human and livestock, and it can undermine environmental health as well. Therefore, this study was aimed at understanding land use and land cover change in Kersa district over the last 30 years. Time-series satellite images that included Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS, which covered the time frame between 1990-2020, were used to determine the change in land use and land cover using object based classification.Results: The object based classification result revealed that in 1990 TM Landsat imagery, natural forest (16.07%), agroforestry (9.21%), village (12.03%), urban (1.93%), and agriculture (60.76%) were identified. The change result showed a rapid reduction in natural forest cover of 25.04%, 9.15%, and 23.11% occurred between (1990-2000), (2000-2010), and (2010-2020) study periods, respectively. Similarly agroforestry decreased by 0.88% and 63.9% (2000-2010) and (2010-2020), respectively. The finding indicates the increment of agricultural land, village, and urban, while the natural forest and agroforestry cover shows a declining trend.Conclusions: The finding implies that there was a rapid land use and land cover change in the study area. This resulted in loss of natural resource and biodiversity. Overall, proper and integrated approach in implementing policies and strategies related to land use and land cover management should be required in kersa district.

scholarly journals Spatio-temporal analysis of urban sprawl and land use / land cover changes in a suburb of Lagos and Ogun metropolises, Nigeria (1986-2014)

2020 ◽  
Vol 22 (1) ◽  
pp. 27-42
Author(s):  
O.H. Adedeji ◽  
C.O. Adeofun ◽  
O.O. Tope-Ajayi ◽  
M.O. Ogunkola
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Sprawl ◽  
Forest Cover ◽  
Temporal Analysis ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Change Analysis ◽  
Spatio Temporal ◽  
Light Forest

Urban sprawl and land use / land cover changes in a suburb of Lagos, Nigeria were assessed using Landsat TM 1984 and 2000 and Landsat OLI of 2014. Five broad land use and land cover classes i.e. built-up area, bare ground, water body, thick forest and light forest were identified and mapped. Thick forest had the largest coverage of 8537.72 hectares (67.52%) of the land cover while built-up was just 1075.99 hectares (8.51 %).Between 1984 and 2014 built up areas gained 6423.38 hectares (59.31 % increase) compared to 8612.09 hectares loss by thick forest cover. A post-classification change analysis from 1984 to 2014 reveals that thick and light forest types had the highest net losses because of conversion to other uses, especially built-up. Urbanization and subsequent urban sprawl is a major factor of land degradation leading to rapid losses of non-urban land uses, especially in the urban fringes. Keywords: Land use/land cover change; change detection; remote sensing; GIS; urbanisation

scholarly journals Investigating impact of land-use and land cover changes on hydro-ecological balance using GIS: insights from IIT Bombay, India

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Aman Srivastava ◽  
Pennan Chinnasamy
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Runoff ◽  
Forest Cover ◽  
Google Earth ◽  
Negative Consequences ◽  
Ecological Stability ◽  
Barren Land ◽  
Ecological Balance ◽  
Lulc Changes

AbstractThe present study, for the first time, examined land-use land cover (LULC), changes using GIS, between 2000 and 2018 for the IIT Bombay campus, India. Objective was to evaluate hydro-ecological balance inside campus by determining spatio-temporal disparity between hydrological parameters (rainfall-runoff processes), ecological components (forest, vegetation, lake, barren land), and anthropogenic stressors (urbanization and encroachments). High-resolution satellite imageries were generated for the campus using Google Earth Pro, by manual supervised classification method. Rainfall patterns were studied using secondary data sources, and surface runoff was estimated using SCS-CN method. Additionally, reconnaissance surveys, ground-truthing, and qualitative investigations were conducted to validate LULC changes and hydro-ecological stability. LULC of 2018 showed forest, having an area cover of 52%, as the most dominating land use followed by built-up (43%). Results indicated that the area under built-up increased by 40% and playground by 7%. Despite rapid construction activities, forest cover and Powai lake remained unaffected. This anomaly was attributed to the drastically declining barren land area (up to ~ 98%) encompassing additional construction activities. Sustainability of the campus was demonstrated with appropriate measures undertaken to mitigate negative consequences of unwarranted floods owing to the rise of 6% in the forest cover and a decline of 21% in water hyacinth cover over Powai lake. Due to this, surface runoff (~ 61% of the rainfall) was observed approximately consistent and being managed appropriately despite major alterations in the LULC. Study concluded that systematic campus design with effective implementation of green initiatives can maintain a hydro-ecological balance without distressing the environmental services.

scholarly journals Pixel- vs. Object-Based Landsat 8 Data Classification in Google Earth Engine Using Random Forest: The Case Study of Maiella National Park

2021 ◽  
Vol 13 (12) ◽  
pp. 2299
Author(s):  
Andrea Tassi ◽  
Daniela Gigante ◽  
Giuseppe Modica ◽  
Luciano Di Martino ◽  
Marco Vizzari
Keyword(s):  
Land Cover ◽  
National Park ◽  
Time Window ◽  
Central Italy ◽  
Google Earth ◽  
Data Cube ◽  
Landsat 8 ◽  
Change Analysis ◽  
Object Based ◽  
Google Earth Engine

With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of the Maiella National Park (central Italy), useful for a future long-term LULC change analysis, this research aimed to develop a Landsat 8 (L8) data composition and classification process using Google Earth Engine (GEE). In this process, we compared two pixel-based (PB) and two object-based (OB) approaches, assessing the advantages of integrating the textural information in the PB approach. Moreover, we tested the possibility of using the L8 panchromatic band to improve the segmentation step and the object’s textural analysis of the OB approach and produce a 15-m resolution LULC map. After selecting the best time window of the year to compose the base data cube, we applied a cloud-filtering and a topography-correction process on the 32 available L8 surface reflectance images. On this basis, we calculated five spectral indices, some of them on an interannual basis, to account for vegetation seasonality. We added an elevation, an aspect, a slope layer, and the 2018 CORINE Land Cover classification layer to improve the available information. We applied the Gray-Level Co-Occurrence Matrix (GLCM) algorithm to calculate the image’s textural information and, in the OB approaches, the Simple Non-Iterative Clustering (SNIC) algorithm for the image segmentation step. We performed an initial RF optimization process finding the optimal number of decision trees through out-of-bag error analysis. We randomly distributed 1200 ground truth points and used 70% to train the RF classifier and 30% for the validation phase. This subdivision was randomly and recursively redefined to evaluate the performance of the tested approaches more robustly. The OB approaches performed better than the PB ones when using the 15 m L8 panchromatic band, while the addition of textural information did not improve the PB approach. Using the panchromatic band within an OB approach, we produced a detailed, 15-m resolution LULC map of the study area.

scholarly journals Impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand

2012 ◽  
Vol 7 (No. 1) ◽  
pp. 10-17 ◽  
Author(s):  
S. Wijitkosum
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
National Park ◽  
Land Use Changes ◽  
Influential Factors ◽  
Geographical Information ◽  
Adjacent Area ◽  
Erosion Risk ◽  
Study Results

Soil erosion has been considered as the primary cause of soil degradation since soil erosion leads to the loss of topsoil and soil organic matters which are essential for the growing of plants. Land use, which relates to land cover, is one of the influential factors that affect soil erosion. In this study, impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand, were investigated by applying remote sensing technique, geographical information system (GIS) and the Universal Soil Loss Equation (USLE). The study results revealed that land use changes in terms of area size and pattern influenced the soil erosion risk in Pa Deng in the 1990–2010 period. The area with smaller land cover obviously showed the high risk of soil erosion than the larger land cover did.

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