scholarly journals Mapping woody plant community turnover with space‐borne hyperspectral data – a case study in the Cerrado

2018 ◽  
Vol 5 (1) ◽  
pp. 107-115
Author(s):  
Pedro J. Leitão ◽  
Marcel Schwieder ◽  
Fernando Pedroni ◽  
Maryland Sanchez ◽  
José R. R. Pinto ◽  
...  
2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey

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.


2021 ◽  
Author(s):  
Kathryn E. Barry ◽  
Stefan A. Schnitzer

AbstractOne of the central goals of ecology is to determine the mechanisms that enable coexistence among species. Evidence is accruing that conspecific negative density dependence (CNDD), the process by which plant seedlings are unable to survive in the area surrounding adults of their same species, is a major contributor to tree species coexistence. However, for CNDD to maintain diversity, three conditions must be met. First, CNDD must maintain diversity for the majority of the woody plant community (rather than merely specific groups). Second, the pattern of repelled recruitment must increase in with plant size. Third, CNDD must occurs across life history strategies and not be restricted to a single life history strategy. These three conditions are rarely tested simultaneously. In this study, we simultaneously test all three conditions in a woody plant community in a North American temperate forest. We examined whether the different woody plant growth forms (shrubs, understory trees, mid-story trees, canopy trees, and lianas) at different ontogenetic stages (seedling, sapling, and adult) were overdispersed – a spatial pattern indicative of CNDD – using spatial point pattern analysis across life history stages and strategies. We found that there was a strong signal of overdispersal at the community level. However, this pattern was driven by adult canopy trees. By contrast, understory plants, which can constitute up to 80% of temperate forest plant diversity, were not overdispersed as adults. The lack of overdispersal suggests that CNDD is unlikely to be a major mechanism maintaining understory plant diversity. The focus on trees for the vast majority of CNDD studies may have biased the perception of the prevalence of CNDD as a dominant mechanism that maintains community-level diversity when, according to our data, CNDD may be restricted largely to trees.


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