scholarly journals Forest-Cover Increase Does Not Trigger Forest-Fragmentation Decrease: Case Study from the Polish Carpathians

2018 ◽  
Vol 10 (5) ◽  
pp. 1472 ◽  
Author(s):  
Jacek Kozak ◽  
Elżbieta Ziółkowska ◽  
Peter Vogt ◽  
Monika Dobosz ◽  
Dominik Kaim ◽  
...  
Keyword(s):  
Forest Fragmentation ◽  
Forest Cover ◽  
Polish Carpathians

scholarly journals Land development pressure on peri-urban forests: A case study in the Regional Municipality of York

2000 ◽  
Vol 76 (2) ◽  
pp. 247-250 ◽  
Author(s):  
D. Puric-Mladenovic ◽  
W. A. Kenney ◽  
F. Csillag
Keyword(s):  
Remote Sensing ◽  
Key Words ◽  
Forest Fragmentation ◽  
Patch Size ◽  
Forest Cover ◽  
Land Development ◽  
High Rate ◽  
Forest Patches ◽  
Key Words Development

Forests patches and forest fragmentation were quantified for seven area municipalities within the Regional Municipality of York for the period from 1975 to 1988. This quantification made it possible to determine the extent of forest changes in space and time. In 1988, forest cover shrank to 30%–50% of its 1975 extent. At the same time, the number of forest patches doubled or tripled and mean patch size and the area of interior (based on a 100 m wide edge) declined indicating a high rate of forest fragmentation. Key words: development, fragmentation, remote sensing, forest

scholarly journals Spatial Analysis of the Drivers, Characteristics, and Effects of Forest Fragmentation

2021 ◽  
Vol 13 (6) ◽  
pp. 3246
Author(s):  
Zoe Slattery ◽  
Richard Fenner
Keyword(s):  
Forest Fragmentation ◽  
Forest Fires ◽  
Geographical Information ◽  
Agricultural Expansion ◽  
Forest Patches ◽  
Mato Grosso ◽  
Remote Imaging ◽  
Landscape Characteristics ◽  
High Level

Building on the existing literature, this study examines whether specific drivers of forest fragmentation cause particular fragmentation characteristics, and how these characteristics can be linked to their effects on forest-dwelling species. This research uses Landsat remote imaging to examine the changing patterns of forests. It focuses on areas which have undergone a high level of a specific fragmentation driver, in particular either agricultural expansion or commodity-driven deforestation. Seven municipalities in the states of Rondônia and Mato Grosso in Brazil are selected as case study areas, as these states experienced a high level of commodity-driven deforestation and agricultural expansion respectively. Land cover maps of each municipality are created using the Geographical Information System software ArcGIS Spatial Analyst extension. The resulting categorical maps are input into Fragstats fragmentation software to calculate quantifiable fragmentation metrics for each municipality. To determine the effects that these characteristics are likely to cause, this study uses a literature review to determine how species traits affect their responses to forest fragmentation. Results indicate that, in areas that underwent agricultural expansion, the remaining forest patches became more complex in shape with longer edges and lost a large amount of core area. This negatively affects species which are either highly dispersive or specialist to core forest habitat. In areas that underwent commodity-driven deforestation, it was more likely that forest patches would become less aggregated and create disjunct core areas. This negatively affects smaller, sedentary animals which do not naturally travel long distances. This study is significant in that it links individual fragmentation drivers to their landscape characteristics, and in turn uses these to predict effects on species with particular traits. This information will prove useful for forest managers, particularly in the case study municipalities examined in this study, in deciding which species require further protection measures. The methodology could be applied to other drivers of forest fragmentation such as forest fires.

scholarly journals Geospatial Serverless Computing: Architectures, Tools and Future Directions

2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey
Keyword(s):  
Big Data ◽  
Forest Cover ◽  
Mineral Resources ◽  
Hyperspectral Data ◽  
Real Time Analysis ◽  
First Case ◽  
Amazon Web Services ◽  
Aws Lambda ◽  
Physical Features

Several real-world applications involve the aggregation of physical features corresponding to different geographic and topographic phenomena. This information plays a crucial role in analyzing and predicting several events. The application areas, which often require a real-time analysis, include traffic flow, forest cover, disease monitoring and so on. Thus, most of the existing systems portray some limitations at various levels of processing and implementation. Some of the most commonly observed factors involve lack of reliability, scalability and exceeding computational costs. In this paper, we address different well-known scalable serverless frameworks i.e., Amazon Web Services (AWS) Lambda, Google Cloud Functions and Microsoft Azure Functions for the management of geospatial big data. We discuss some of the existing approaches that are popularly used in analyzing geospatial big data and indicate their limitations. We report the applicability of our proposed framework in context of Cloud Geographic Information System (GIS) platform. An account of some state-of-the-art technologies and tools relevant to our problem domain are discussed. We also visualize performance of the proposed framework in terms of reliability, scalability, speed and security parameters. Furthermore, we present the map overlay analysis, point-cluster analysis, the generated heatmap and clustering analysis. Some relevant statistical plots are also visualized. In this paper, we consider two application case-studies. The first case study was explored using the Mineral Resources Data System (MRDS) dataset, which refers to worldwide density of mineral resources in a country-wise fashion. The second case study was performed using the Fairfax Forecast Households dataset, which signifies the parcel-level household prediction for 30 consecutive years. The proposed model integrates a serverless framework to reduce timing constraints and it also improves the performance associated to geospatial data processing for high-dimensional hyperspectral data.

Stratification approach for forest cover type and landuse mapping using IRS-1A LISS-II data — A case study

1994 ◽  
Vol 22 (1) ◽  
pp. 21-29 ◽  
Author(s):  
S. Sudhakar ◽  
R. K. Das ◽  
D. Chakraborty ◽  
B. K. Bardhan Roy ◽  
A. K. Raha ◽  
...  
Keyword(s):  
Forest Cover ◽  
Forest Cover Type ◽  
Cover Type

scholarly journals Monitoring Land Cover Changes in the Disaster-Prone Area: A Case Study of Cangkringan Sub-District, the Flanks of Mount Merapi, Indonesia

2017 ◽  
Vol 31 (2) ◽  
pp. 209-219 ◽  
Author(s):  
Ronggo Sadono ◽  
Hartono Hartono ◽  
Mochammad Maksum Machfoedz ◽  
Setiaji Setiaji
Keyword(s):  
Land Cover ◽  
Forest Cover ◽  
Land Cover Changes ◽  
Annual Crops ◽  
The North ◽  
Detection Analysis ◽  
Prone Area ◽  
Cover Class ◽  
Forest Cover Types

Volcanic eruption is one of the natural factors that affect land cover changes. This study aimed to monitor land cover changes using a remote sensing approach in Cangkringan Sub-district, Yogyakarta, Indonesia, one of the areas most vulnerable to Mount Merapi eruption. Three satellite images, dating from 2001, 2006 and 2011, were used as main data for land cover classification based on a supervised classification approach. The land cover detection analysis was undertaken by overlaying the classification results from those images. The results show that the dominant land cover class is annual crops, covering 40% of the study area, while the remaining 60% consists of forest cover types, dryland farming, paddy fields, settlements, and bare land. The forests were distributed in the north, and the annual crops in the middle of the study area, while the villages and the rice fields were generally located in the south. In the 2001–2011 period, forests were the most increased land cover type, while annual crops decreased the most, as a result of the eruption of Mount Merapi in 2010. Such data and information are important for the local government or related institutions to formulate Detailed Spatial Plans (RDTR) in the Disaster-Prone Areas (KRB).

Resilient pastures and sediment: a case study in Hawke's Bay

2021 ◽  
Vol 17 ◽  
Author(s):  
Dave Read
Keyword(s):  
Forest Cover ◽  
Single Species ◽  
Independent Research ◽  
Bare Ground ◽  
Hill Country ◽  
Regulatory Issue ◽  
Sediment Loss ◽  
Return On Capital

For many hill-country farms sediment will be a bigger regulatory issue than nitrates over the next decade. A dense, resilient pasture can reduce the risk of insidious sediment loss. Any ecosystem that relies on a few species is fragile. Sowing a single species leads to repeated re-sowing and increasing bare ground to remove competition, increasing the risk of sediment flows. An important issue during regulatory consultation will be establishing a natural, pre-human baseline for forest cover and documenting more recent changes in sediment flows. Hill country cropping and pasture renewal is incompatible with resilient pasture. This is a farmer’s perspective on a diverse and persisting hill country pasture-based system that can make a good return on capital without re-grassing or fodder cropping. Funding of independent research on pasture and fodder systems is essential if farmers are to make good decisions.

Landscape fragmentation

2010 ◽  
Author(s):  
Ned Horning ◽  
Julie A. Robinson ◽  
Eleanor J. Sterling ◽  
Woody Turner ◽  
Sacha Spector
Keyword(s):  
Forest Fragmentation ◽  
Landscape Metrics ◽  
Forest Cover ◽  
Remotely Sensed ◽  
Clear Understanding ◽  
Remotely Sensed Data ◽  
Deforestation Rates ◽  
Habitat Conversion ◽  
Conservation Organizations ◽  
Total Core Area

The country of Vietnam has long been recognized as an important region for biodiversity (Sterling et al. 2006). High-profile discoveries in the 1990s of many species new to science including large ones such as the Saola (Pseudoryx nghetinhensis), an 85 kg basal member of the cattle subfamily Bovinae and the first new genus of large land-dwelling mammal described since the okapi (Okapia johnstoni) in 1901, have focused the attention of national and international conservation organizations on Vietnam and surrounding countries in mainland Southeast Asia (Hurley et al. in prep.). Conservation action for these endemic, endangered species relies on a clear understanding of trends in habitat conversion. To track deforestation rates through time in Vietnam, Meyfroidt and Lambin (2008) combined remotely sensed data with landscape metrics such as number of patches, mean patch size, mean proximity index, and total core area index. They tested their analyses across a variety of land cover studies including those using Advanced Very High Resolution Radiometer (AVHRR), Landsat, SPOT, and MODIS data sources. They found that forest cover decreased nationally from the 1980s to the 1990s and then showed an increase between 1990 and 2000, due to plantation forests as well as natural forest regeneration. However, the effects of this forest transition on fragmentation metrics noted above differed across the country. For instance, in some places, such as central Vietnam where forest cover is relatively large and well connected, reforestation led to a decrease in forest fragmentation and secondary forests recovered rapidly. However in others, such as areas in the north where forest fragmentation dates back centuries and forests have therefore long been isolated, reforestation did not seem to have an impact on continued fragmentation and habitat loss. In this chapter we detail the importance of fragmentation and landscape metrics to ecology and conservation, outlining when and where remotely sensed data can help in these analyses. We then discuss a subset of fragmentation metrics and point to some challenges in processing fragmentation data. We provide examples of composition and connectivity metrics illuminated with examples from the remote sensing literature.

Interdependent effects of climate variability and forest cover change on streamflow dynamics: a case study in the Upper Umvoti River Basin, South Africa

2019 ◽  
Vol 19 (7) ◽  
pp. 1963-1971
Author(s):  
Karen Lebek ◽  
Cornelius Senf ◽  
David Frantz ◽  
José A. F. Monteiro ◽  
Tobias Krueger
Keyword(s):  
South Africa ◽  
Climate Variability ◽  
River Basin ◽  
Forest Cover ◽  
Forest Cover Change

scholarly journals Mapping Landslide Prediction through a GIS-Based Model: A Case Study in a Catchment in Southern Italy

Geosciences ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 309
Author(s):  
Federico Valerio Moresi ◽  
Mauro Maesano ◽  
Alessio Collalti ◽  
Roy C. Sidle ◽  
Giorgio Matteucci ◽  
...  
Keyword(s):  
Forest Cover ◽  
Shallow Landslides ◽  
Susceptibility Map ◽  
Infinite Slope ◽  
South Italy ◽  
Physically Based ◽  
Root Strength ◽  
Forested Areas ◽  
Forest Mountain

Shallow landslides are an increasing concern in Italy and worldwide because of the frequent association with vegetation management. As vegetation cover plays a fundamental role in slope stability, we developed a GIS-based model to evaluate the influence of plant roots on slope safety, and also included a landslide susceptibility map. The GIS-based model, 4SLIDE, is a physically based predictor for shallow landslides that combines geological, topographical, and hydrogeological data. The 4SLIDE combines the infinite slope model, TOPMODEL (for the estimation of the saturated water level), and a vegetation root strength model, which facilitates prediction of locations that are more susceptible for shallow landslides as a function of forest cover. The aim is to define the spatial distribution of Factor of Safety (FS) in steep-forested areas. The GIS-based model 4SLIDE was tested in a forest mountain watershed located in the Sila Greca (Cosenza, Calabria, South Italy) where almost 93% of the area is covered by forest. The sensitive ROC analysis (Receiver Operating Characteristic) indicates that the model has good predictive capability in identifying the areas sensitive to shallow landslides. The localization of areas at risk of landslides plays an important role in land management activities because landslides are among the most costly and dangerous hazards.

scholarly journals Regional assessment of forest effect on watershed hydrology: Slovakia as a case study  405

2013 ◽  
Vol 59 (No. 10) ◽  
pp. 405-415
Author(s):  
HlásnyT ◽  
SitkováZ ◽  
I. Barka
Keyword(s):  
Water Regime ◽  
Forest Cover ◽  
Stand Density ◽  
Watershed Hydrology ◽  
Natural Conditions ◽  
Tree Species Composition ◽  
Weak Limits ◽  
Spring Area ◽  
Regulatory Capacity

Recently, the importance of forest effect on watershed hydrology has been increasingly recognized due to an elevated threat of floods and expected alterations of water regime in watersheds induced by climate change. We assessed the trade-off between natural conditions of 61 basic watersheds in Slovakia and expected water-regulatory capacity of forest in these watersheds. A multi-criteria decision-making scheme was proposed to calculate a coefficient for each watershed indicating the need to regulate its water regime as given by natural conditions, and another coefficient indicating the magnitude of forest water-regulatory capacity given by forest structure and distribution. Factors indicating the forest water-regulatory capacity were extent of forest cover, forest fragmentation and distribution in watersheds relative to the spring area, forest stand density and vertical structure, and tree species composition. The results indicate that the present structure and distribution of forests in Slovakia has potential to moderately regulate the water regime at the scale of basic watersheds. We identified critical watersheds where natural conditions imply the unfavourable water regime and/or the forest water-regulatory capacity is weak. Limits of forest effect on watershed hydrology and caveats for interpreting the presented findings are discussed. 

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