Solution of export coefficients of nitrogen from different land-use patterns based on Bayesian analysis

2013 ◽  
Vol 68 (3) ◽  
pp. 632-640 ◽  
Author(s):  
Mei Liu ◽  
Jun Lu
Keyword(s):  
Land Use ◽  
Probability Distribution ◽  
River System ◽  
Quality Model ◽  
Land Use Patterns ◽  
Dry Land ◽  
K Value ◽  
Barren Land ◽  
Posterior Probability Distribution ◽  
Use Patterns

The export coefficient model has been applied worldwide to the estimation of non-point source (NPS) pollution. Determining the export coefficients (ECs) from each pollution source and different space–time progressions is problematic because of uncertainty in the ECs of nitrogen from different land-use patterns. Bayesian theory uses the prior probability distribution and likelihood data to generate a posterior probability distribution. The total nitrogen (TN) ECs and stream loss rates K (d−1) for five land-use patterns were estimated by combining published results with monthly data for ChangLe River system for 2004–08. After 104 iterations, the results had small Markov chain Monte Carlo errors and convergence was obtained. Average TN ECs for the entire watershed were 26.1 ± 8.8, 70.3 ± 9.4, 41.7 ± 6.9, 8.9 ± 1.6 and 6.2 ± 0.5 kg ha−1 yr−1 for paddy field, dry land, residential land, woodland and barren land with coefficients of variation (CVs) of 16.9, 6.31, 8.91, 13.3 and 27.9% among sub-catchments respectively. The average K value was 0.33 d−1 with a CV of 11.3%. Estimated ECs, K and the coupling water quality model were used to predict the years 2008 and 2009; the results validated the model. This Bayesian model can determine ECs using prior knowledge and monitored data, overcoming the problems of the regression model. The model facilitates explicit consideration of uncertainty in NPS management.

The influence of land use patterns on water quality at multiple spatial scales in a river system

2013 ◽  
Vol 28 (20) ◽  
pp. 5259-5272 ◽  
Author(s):  
Guoqiang Wang ◽  
Yinglan A ◽  
Zongxue Xu ◽  
Shurong Zhang
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Spatial Scales ◽  
River System ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Multiple Spatial Scales

scholarly journals Socioeconomic characteristics of communities utilizing land in forest areas in the Maros Watershed

2021 ◽  
Vol 886 (1) ◽  
pp. 012028
Author(s):  
Chaerunnisa Ekasari ◽  
Roland Barkey ◽  
Chairil A ◽  
Munajat Nursaputra ◽  
Septian Perdana Putra Pahar
Keyword(s):  
Land Use ◽  
River Basin ◽  
Forest Products ◽  
Forest Area ◽  
Land Use Patterns ◽  
Forest Protection ◽  
Dry Land ◽  
Area Function ◽  
Use Patterns

Abstract The community has used the land throughout the area without exception in the forest area. The function of forest areas also varies based on the biophysical conditions of a land. The Maros River Basin has a complex forest area function ranging from production forest, protection forest to conservation forest (National Park). In addition, the Maros watershed also has its own uniqueness in the form of a karst ecosystem and biodiversity. This requires information related to activities, and the role of forests for people who use land in forest areas to meet their daily needs. Based on this, this study aims to analyze land use patterns, and socio-economic characteristics of the people in the Maros River Basin. This analysis begins with spot image analysis, and land use interpretation. The second analysis conducts detailed observations of land use in the field based on the results of land use interpretations that indicate community activities in forest areas. The last analysis is the socio-economic conditions, and the influence of the role of the forest on the community in using land in the forest area. The results of the analysis show that each area function is dominated by land use patterns in the form of dry land mixed with shrubs, rice fields, plantations, plantation forests, and secondary forests. Land use in the form of dry land mixed with shrubs is used as seasonal crops such as corn and horticulture. The use of plantation land, the community gets results in the form of candlenut and coffee. The use of plantation forest land is used to obtain pine resin, while the community uses the secondary forest as non-timber forest products such as honey bees and bamboo. The level of education of people who use forest areas is still low and the average income from the use of these areas is Rp. 1,372,679, - lower than the minimum wage in South Sulawesi Province.

scholarly journals The Interaction Relationship between Land Use Patterns and Socioeconomic Factors Based on Wavelet Analysis: A Case Study of the Black Soil Region of Northeast China

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1237
Author(s):  
Yue Wang ◽  
Ge Song ◽  
Wenying Li
Keyword(s):  
Land Use ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Socioeconomic Factors ◽  
Social Progress ◽  
Land Use Intensity ◽  
Land Use Patterns ◽  
Dry Land ◽  
Use Patterns ◽  
The Impact

Analyzing the interaction between land use patterns (LUPs) and socioeconomic factors (SEFs) could provide a basis for regional land spatial planning and management decisions in the future. In this study, population, gross domestic product (GDP) and land use intensity were selected to explain the relationship between SEFs and LUPs. The study designed a new method of sample line acquisition for wavelet analysis, and identified the interaction grid scales of LUP changes with SEFs in 1991, 2005 and 2019 by using cross wavelet transform analysis (XWT). Wavelet transform coherent analysis (WTC) was used to reveal the interaction direction and impact strength between LUPs and SEFs. The results showed that: (1) There were two ranges of 2978–5008 m and 24,400–29,738 m in which the grid scales showing interaction between LUPs and SEFs (population, GDP and land use intensity) from 1991 to 2019 were overlapping. (2) The interaction direction between LUPs and SEFs from 1991 to 2019 was almost negative on all sample lines, while the interaction directions of the middle sample line of population and GDP from 1991 to 2019, the end sample line of GDP in 2019, and the start sample line of land use intensity in 1991 were positive. (3) Dry land, grassland and construction land were most affected by SEFs, followed by paddy fields, forest land and other land, and the least affected were water areas during 1991 to 2019. The impact of population and GDP on LUPs was reduced, while the impact of land use intensity on LUPs was increased from 1991 to 2019. Overall, population, GDP and land use intensity were the important SEFs in the changes of LUPs, and were important factors for social progress and economic development.

scholarly journals Haiti has more forest than previously reported: land change 2000–2015

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9919
Author(s):  
Ose Pauleus ◽  
T. Mitchell Aide
Keyword(s):  
Land Use ◽  
International Institutions ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Google Earth ◽  
Land Change ◽  
Land Use Patterns ◽  
Forest Patches ◽  
Barren Land ◽  
Use Patterns

Estimates of forest cover have important political, conservation, and funding implications, but methods vary greatly. Haiti has often been cited as one of the most deforested countries in the world, yet estimates of forest cover range from <1% to 33%. Here, we analyze land change for seven land cover classes (forest, shrub land, agriculture/pasture, plantation, urban/infrastructure, barren land, and water) between 2000 and 2015 using Landsat imagery (30 m resolution) in the Google Earth Engine platform. Forest cover was estimated at 26% in 2000 and 21% in 2015. Although forest cover is declining in Haiti, our quantitative analysis resulted in considerably higher forest cover than what is usually reported by local and international institutions. Our results determined that areas of forest decline were mainly converted to shrubs and mixed agriculture/pasture. An important driver of forest loss and degradation could be the high demand for charcoal, which is the principal source of cooking fuel. Our results differ from other forest cover estimates and forest reports from national and international institutions, most likely due to differences in forest definition, data sources, spatial resolution, and methods. In the case of Haiti, this work demonstrates the need for clear and functional definitions and classification methods to accurately represent land use/cover change. Regardless of how forests are defined, forest cover in Haiti will continue to decline unless corrective actions are taken to protect remaining forest patches. This can serve as a warning of the destructive land use patterns and can help us target efforts for better planning, management, and conservation.

Conducting “Siteless Survey”: Results from Coastal New England

1993 ◽  
Vol 14 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Jordan E. Kerber
Keyword(s):  
Land Use ◽  
New England ◽  
Rhode Island ◽  
Careful Consideration ◽  
Archaeological Survey ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Statistical Validity ◽  
Survey Results ◽  
Survey Strategy

Selecting an effective archaeological survey takes careful consideration given the interaction of several variables, such as the survey's goals, nature of the data base, and budget constraints. This article provides justification for a “siteless survey” using evidence from a project on Potowomut Neck in Rhode Island whose objective was not to locate sites but to examine the distribution and density of prehistoric remains to test an hypothesis related to land use patterns. The survey strategy, random walk, was chosen because it possessed the advantages of probabilistic testing, as well as the ease of locating sample units. The results were within the limits of statistical validity and were found unable to reject the hypothesis. “Siteless survey” may be successfully applied in similar contexts where the distribution and density of materials, as opposed to ambiguously defined sites, are sought as evidence of land use patterns, in particular, and human adaptation, in general.

scholarly journals Modeling Community-Scale Natural Resource Use in a Transboundary Southern African Landscape: Integrating Remote Sensing and Participatory Mapping

2021 ◽  
Vol 13 (4) ◽  
pp. 631
Author(s):  
Kyle D. Woodward ◽  
Narcisa G. Pricope ◽  
Forrest R. Stevens ◽  
Andrea E. Gaughan ◽  
Nicholas E. Kolarik ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Resource Use ◽  
Training Data ◽  
Systems Science ◽  
Participatory Mapping ◽  
Land Use Patterns ◽  
Modeling Framework ◽  
Use Patterns ◽  
Human Habitation

Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas.

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