The Impact of the Environment upon the Spatial Distribution of Population and Land Values

Floods are the highest-impact natural disasters. In agricultural basins, anthropogenic features are significant factors in controlling flood and erosion. A hydrological-hydraulic-erosion diagnosis is necessary in order to choose the most relevant action zones and to make recommendations for alternative land uses and cultivation practices in order to control and reduce floods and erosion. This chapter first aims to provide an overview of the flow processes represented in the various possible choices of model structure and refinement. It then focuses on the impact of the spatial distribution and temporal variation of hydrological soil properties in farmed basins, representing their effects on the modelled water and sediment flows. Research challenges and leads are then tackled, trying to identify the conditions in which sufficient adequacy exists between site data and modelling strategies.

Download Full-text

Measuring spatial allocative efficiency in basketball

Journal of Quantitative Analysis in Sports ◽

10.1515/jqas-2019-0126 ◽

2020 ◽

Vol 16 (4) ◽

pp. 271-289

Author(s):

Nathan Sandholtz ◽

Jacob Mortensen ◽

Luke Bornn

Keyword(s):

Spatial Distribution ◽

Hierarchical Model ◽

Opportunity Cost ◽

Allocative Efficiency ◽

Bayesian Hierarchical Model ◽

National Basketball Association ◽

Spatial Context ◽

Bayesian Hierarchical ◽

The Impact

AbstractEvery shot in basketball has an opportunity cost; one player’s shot eliminates all potential opportunities from their teammates for that play. For this reason, player-shot efficiency should ultimately be considered relative to the lineup. This aspect of efficiency—the optimal way to allocate shots within a lineup—is the focus of our paper. Allocative efficiency should be considered in a spatial context since the distribution of shot attempts within a lineup is highly dependent on court location. We propose a new metric for spatial allocative efficiency by comparing a player’s field goal percentage (FG%) to their field goal attempt (FGA) rate in context of both their four teammates on the court and the spatial distribution of their shots. Leveraging publicly available data provided by the National Basketball Association (NBA), we estimate player FG% at every location in the offensive half court using a Bayesian hierarchical model. Then, by ordering a lineup’s estimated FG%s and pairing these rankings with the lineup’s empirical FGA rate rankings, we detect areas where the lineup exhibits inefficient shot allocation. Lastly, we analyze the impact that sub-optimal shot allocation has on a team’s overall offensive potential, demonstrating that inefficient shot allocation correlates with reduced scoring.

Download Full-text

A Pandemic of Violence? The Impact of COVID-19 on Conflict

Peace Economics Peace Science and Public Policy ◽

10.1515/peps-2020-0050 ◽

2020 ◽

Vol 26 (3) ◽

Cited By ~ 1

Author(s):

Sara M.T. Polo

Keyword(s):

Spatial Distribution ◽

Real Time ◽

Case Studies ◽

Armed Conflict ◽

Event Data ◽

Social Unrest ◽

Johns Hopkins University ◽

The World ◽

Political Advantage ◽

The Impact

AbstractThis article examines the impact and repercussions of the COVID-19 pandemic on patterns of armed conflict around the world. It argues that there are two main ways in which the pandemic is likely to fuel, rather than mitigate, conflict and engender further violence in conflict-prone countries: (1) the exacerbating effect of COVID-19 on the underlying root causes of conflict and (2) the exploitation of the crisis by governments and non-state actors who have used the coronavirus to gain political advantage and territorial control. The article uses data collected in real-time by the Armed Conflict Location & Event Data Project (ACLED) and the Johns Hopkins University to illustrate the unfolding and spatial distribution of conflict events before and during the pandemic and combine this with three brief case studies of Afghanistan, Nigeria, and Libya. Descriptive evidence shows how levels of violence have remained unabated or even escalated during the first five months of the pandemic and how COVID-19-related social unrest has spread beyond conflict-affected countries.

Download Full-text

Spatial distribution patterns of soil total phosphorus influenced by climatic factors in China’s forest ecosystems

Scientific Reports ◽

10.1038/s41598-021-84166-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jie Zhu ◽

Anchi Wu ◽

Guoyi Zhou

Keyword(s):

Spatial Distribution ◽

Forest Ecosystems ◽

Climatic Factors ◽

Critical Role ◽

Effect Of Temperature ◽

P Concentration ◽

Single Effect ◽

The Impact ◽

P Distribution ◽

Total P

AbstractPhosphorus (P) is an important element in terrestrial ecosystems and plays a critical role in soil quality and ecosystem productivity. Soil total P distributions have undergone large spatial changes as a result of centuries of climate change. It is necessary to study the characteristics of the horizontal and vertical distributions of soil total P and its influencing factors. In particular, the influence of climatic factors on the spatial distribution of soil total P in China’s forest ecosystems remain relatively unknown. Here, we conducted an intensive field investigation in different forest ecosystems in China to assess the effect of climatic factors on soil total P concentration and distribution. The results showed that soil total P concentration significantly decreased with increasing soil depth. The spatial distribution of soil total P increased with increasing latitude and elevation gradient but decreased with increasing longitude gradient. Random forest models and linear regression analyses showed that the explanation rate of bioclimatic factors and their relationship with soil total P concentration gradually decreased with increasing soil depths. Variance partitioning analysis demonstrated that the most important factor affecting soil total P distribution was the combined effect of temperature and precipitation factor, and the single effect of temperature factors had a higher explanation rate compare with the single effect of precipitation factors. This work provides a new farmework for the geographic distribution pattern of soil total P and the impact of climate variability on P distribution in forest ecosystems.

Download Full-text

Spatial Dependence Evaluation of Agricultural Technical Efficiency—Based on the Stochastic Frontier and Spatial Econometric Model

Sustainability ◽

10.3390/su13052708 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2708

Author(s):

Ziqi Yin ◽

Jianzhai Wu

Keyword(s):

Spatial Distribution ◽

Technical Efficiency ◽

Spatial Dependence ◽

Stochastic Frontier ◽

Hebei Province ◽

Agricultural Technology ◽

Agricultural Product ◽

Spatial Econometric ◽

Frontier Analysis ◽

The Impact

In recent years, through the implementation of a series of policies, such as the delimitation of major grain producing areas and the construction of advantageous and characteristic agricultural product areas, the spatial distribution of agriculture in China has changed significantly; however, research on the impact of such changes on the efficiency of agricultural technology is still lacking. Taking 11 cities in Hebei Province as the research object, this study examines the spatial dependence of regional agricultural technical efficiency using the stochastic frontier analysis and spatial econometric analysis. The results show that the improvement in agricultural technical efficiency is evident in all cities in Hebei Province from 2008 to 2017, but there is scope for further improvement. Industrial agglomeration has statistical significance in improving the efficiency of agricultural technology. Further, there is an obvious spatial correlation and difference in agricultural technical efficiency. Optimizing the spatial distribution of agricultural production, promoting the innovation, development, and application of agricultural technology, and promoting the expansion of regional elements can contribute to improving agricultural technical efficiency.

Download Full-text

Coastal Mangrove Response to Marine Erosion: Evaluating the Impacts of Spatial Distribution and Vegetation Growth in Bangkok Bay from 1987 to 2017

Remote Sensing ◽

10.3390/rs12020220 ◽

2020 ◽

Vol 12 (2) ◽

pp. 220 ◽

Cited By ~ 2

Author(s):

Han Xiao ◽

Fenzhen Su ◽

Dongjie Fu ◽

Qi Wang ◽

Chong Huang

Keyword(s):

Spatial Distribution ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Mangrove Ecosystem ◽

Early Growth ◽

Growth Stages ◽

Human Disturbances ◽

Vegetation Growth ◽

Two Parameters ◽

The Impact

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.

Download Full-text

Exploring the use of gpr and satellite-based snow data for snowmelt runoff predictions

10.5194/egusphere-egu21-14972 ◽

2021 ◽

Author(s):

Ilaria Clemenzi ◽

David Gustafsson ◽

Jie Zhang ◽

Björn Norell ◽

Wolf Marchand ◽

...

Keyword(s):

Remote Sensing ◽

Spatial Distribution ◽

Data Assimilation ◽

Snow Water Equivalent ◽

Distribution Model ◽

Accurate Estimation ◽

Snowmelt Runoff ◽

Snow Water ◽

Snow Distribution ◽

The Impact

<p>Snow in the mountains is the result of the interplay between meteorological conditions, e.g., precipitation, wind and solar radiation, and landscape features, e.g., vegetation and topography. For this reason, it is highly variable in time and space. It represents an important water storage for several sectors of the society including tourism, ecology and hydropower. The estimation of the amount of snow stored in winter and available in the form of snowmelt runoff can be strategic for their sustainability. In the hydropower sector, for example, the occurrence of higher snow and snowmelt runoff volumes at the end of the spring and in the early summer compared to the estimated one can substantially impact reservoir regulation with energy and economical losses. An accurate estimation of the snow volumes and their spatial and temporal distribution is thus essential for spring flood runoff prediction. Despite the increasing effort in the development of new acquisition techniques, the availability of extensive and representative snow and density measurements for snow water equivalent estimations is still limited. Hydrological models in combination with data assimilation of ground or remote sensing observations is a way to overcome these limitations. However, the impact of using different types of snow observations on snowmelt runoff predictions is, little understood. In this study we investigated the potential of assimilating in situ and remote sensing snow observations to improve snow water equivalent estimates and snowmelt runoff predictions. We modelled the seasonal snow water equivalent distribution in the Lake &#214;veruman catchment, Northern Sweden, which is used for hydropower production. Simulations were performed using the semi-distributed hydrological model HYPE for the snow seasons 2017-2020. For this purpose, a snowfall distribution model based on wind-shelter factors was included to represent snow spatial distribution within model units. The units consist of 2.5x2.5 km<sup>2</sup> grid cells, which were further divided into hydrological response units based on elevation, vegetation and aspect. The impact on the estimation of the total catchment mean snow water equivalent and snowmelt runoff volume were evaluated using for data assimilation, gpr-based snow water equivalent data acquired along survey lines in the catchment in the early spring of the four years, snow water equivalent data obtained by a machine learning algorithm and satellite-based fractional snow cover data. Results show that the wind-shelter based snow distribution model was able to represent a similar spatial distribution as the gpr survey lines, when assessed on the catchment level. Deviations in the model performance within and between specific gpr survey lines indicate issues with the spatial distribution of input precipitation, and/or need to include explicit representation of snow drift between model units. The explicit snow distribution model also improved runoff simulations, and the ability of the model to improve forecast through data assimilation.</p>

Download Full-text

A Quantitative Evaluation of the Multiple Narratives of the Recent Sahelian Regreening*

Weather Climate and Society ◽

10.1175/wcas-d-15-0012.1 ◽

2016 ◽

Vol 8 (1) ◽

pp. 67-83 ◽

Cited By ~ 6

Author(s):

Mimi Stith ◽

Alessandra Giannini ◽

John del Corral ◽

Susana Adamo ◽

Alex de Sherbinin

Keyword(s):

Spatial Distribution ◽

Population Density ◽

Environmental Change ◽

Burkina Faso ◽

Social Dimensions ◽

Adaptation To Climate Change ◽

Southern Central ◽

Second Category ◽

The Impact

Abstract A spatial analysis is presented that aims to synthesize the evidence for climate and social dimensions of the “regreening” of the Sahel. Using an independently constructed archival database of donor-funded interventions in Burkina Faso, Mali, Niger, and Senegal in response to the persistence of drought in the 1970s and 1980s, the spatial distribution of these interventions is examined in relation to population density and to trends in precipitation and in greenness. Three categories of environmental change are classified: 1) regions at the northern grassland/shrubland edge of the Sahel where NDVI varies interannually with precipitation, 2) densely populated cropland regions of the Sahel where significant trends in precipitation and NDVI decouple at interannual time scales, and 3) regions at the southern savanna edge of the Sahel where NDVI variation is independent of precipitation. Examination of the spatial distribution of environmental change, number of development projects, and population density brings to the fore the second category, covering the cropland areas where population density and regreening are higher than average. While few, regions in this category coincide with emerging hotspots of regreening in northern Burkina Faso and southern central Niger known from case study literature. In examining the impact of efforts to rejuvenate the Sahelian environment and livelihoods in the aftermath of the droughts of the 1970s and 1980s against the backdrop of a varying and uncertain climate, the transition from desertification to regreening discourses is framed in the context of adaptation to climate change.

Download Full-text

Recent Sea Ice Decline Did Not Significantly Increase the Total Liquid Freshwater Content of the Arctic Ocean

Journal of Climate ◽

10.1175/jcli-d-18-0237.1 ◽

2018 ◽

Vol 32 (1) ◽

pp. 15-32 ◽

Cited By ~ 11

Author(s):

Qiang Wang ◽

Claudia Wekerle ◽

Sergey Danilov ◽

Dmitry Sidorenko ◽

Nikolay Koldunov ◽

...

Keyword(s):

Spatial Distribution ◽

Sea Ice ◽

Arctic Ocean ◽

Ocean Circulation ◽

General Circulation ◽

The Arctic ◽

Sea Ice Decline ◽

The Arctic Ocean ◽

Eurasian Basin ◽

The Impact

Abstract The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.

Download Full-text