Specific Land Use Research Articles

Three‐stage assessment of parcel area quality

The most important spatial attributes of any cadastral parcel are the coordinates of its boundary points, which define the extent of property rights. The derivative of the boundaries is the area of the parcel, which, in Poland, is determined based on the coordinates of the boundary points satisfying certain conditions. It is essential that the data entered into the real estate cadastre describing the areas of the parcels are of sufficiently high quality. For this reason, the authors of this research paper propose a three‐stage assessment of the quality of the area of cadastral parcels. The first stage involves analysis of the standardised values of selected attributes of the boundary points entered into the cadastral database, describing the accuracy of their position, the source of data capture, and the monumentation method. This forms the basis for evaluating the quality level of individual boundary points throughout the entire study area. Taking the geometry of the parcel into account, this information is used to determine the quality of the data on the areas of individual parcels, which forms the second stage of the analysis. The third and final stage consists in determining the global coefficient for the quality of areas of parcels in the study area. Such an approach provides a wide range of possibilities, both for carrying out unit control procedures and for comparing the quality of spatial data on parcel areas between individual cadastral districts or areas with a specific land use. The results of the analyses carried out on the research objects, i.e., on two cadastral districts located in southern Poland, have confirmed that the proposed method may also prove useful for other purposes. It is also a universal tool that can be adapted for use in other countries.

A GIS based method to calculate regionalized land use characterization factors for life cycle impact assessment using LANCA®

Land is used and modified in its natural function for the cultivation of food and energy crops, for infrastructure and other production purposes. Despite their global significance, land use impacts are still rarely addressed, although methods for integrating land use into Life Cycle Assessment (LCA) have been developed recently. This paper describes the development and calculation of regionalized characterization factors based on the LANCA® (Land Use Indicator Value Calculation in Life Cycle Assessment) method to be integrated into LCA using a geo information system (GIS). With the publication of the LANCA® characterization factors (Bos et al. 2016), land use impacts can be assessed at the country level. However, soil parameters as well as climatic conditions change on a small scale and are very site-specific. Therefore, there is a need for regionalized characterization factors. After a literature review, we describe the development of the five LANCA® indicators. Afterwards we present the conceptual framework for the calculation of GIS-based characterization factors and apply this framework to two examples, the indicators of mechanical filtration and physicochemical filtration. Finally, we apply the characterization factors in a case study. The region-specific characterization factors are calculated in a GIS environment yielding a map with values for mechanical filtration and physicochemical filtration per grid cell for various land use types. A case study shows that land use impacts fluctuate due to site-specific conditions such as pedological, topographical and climatic conditions. It can be shown that our calculation of regionalized characterization factors in global maps is feasible and facilitates an area’s potential for causing lower environmental impacts for a certain land use compared to other areas. Remaining challenges are related to input data quality, the comprehensibility of the results to practitioners that are not land use experts and the technical restrictions of LCA database and software providers. Through the presented regionalization of the LANCA® framework, a necessary prerequisite to method advancement is met as also region-specific characterization factors can now be calculated. In comparison to the published country-specific characterization factors in Bos et al. (2016), the developed regional GIS-based characterization factors are far more advantageous especially for large countries. Nevertheless, it has to be noted that an LCA including the evaluation of land use does not replace methods and tools like environmental impact assessment. When deciding on a preferable location for a specific land use nature conservation, geographical, geological and building law aspects must also be taken into account.

Evenki of River Basin Olyokma: Resettlement and Land Use in the XXI Century

The relevance of the study is due to the need to study the characteristics of the resettlement of the local Evenki group of the Olekma River Basin, which influenced the modern land use and economic and cultural relations of Evenki living now in the Olekminsky District of the Republic of Sakha (Yakutia), the Kalarsky and Tungiro-Olekminsky Districts of the Trans-Baikal Territory and the Tyndinsky District of Amur region. The article focuses on the study of the Evenki population dynamics based on a comparative analysis of the materials of the censuses of the 20th century. For comparison, current data on the number of Evenks in their areas of residence according to the 2010 census are given. An analysis of archival sources showed that changes in the resettlement of Evenk clans occurred simultaneously with changes in the administrative-territorial division. Factographic materials found in the National Archives of the Republic of Sakha (Yakutia) confirm that when deciding on the administrative-territorial structure, the opinions and proposals of the local population were taken into account. Author’s maps were compiled, which allowed a spatial analysis of the distribution of the population and the forms of organization of the Evenki economy. It was found out that each region has its own specific land use determined by administrative decisions and regional policies.

CONTRIBUIÇÃO HIDROSSEDIMENTOLÓGICA DAS ESTRADAS RURAIS EM BACIAS HIDROGRÁFICAS COM PEQUENAS E MÉDIAS PROPRIEDADES

Os estudos hidrossedimentológicos abordam as contribuições da agricultura,do meio urbano e das demais ocupações da terra, entretanto as estradasrurais inseridas nas bacias hidrográficas dificilmente são observadas comocontribuição específica ou potencialmente contributiva. Desse modo, osobjetivos deste estudo foram simular diferentes cenários e características paraas estradas rurais e, assim, avaliar o fluxo de águas e sedimentos em bacias comagricultura familiar localizadas no sul do Brasil. Para isso, utilizou‑se o modelohidrológico soil and water assessment tool (SWAT). Na etapa de calibraçãoda vazão para a bacia do Ribeirão Concórdia, obtiveram‑se o coeficientede Nash-Sutcliffe (COE) de 0,76 e, para a validação, o coeficiente de 0,78.Na bacia do Rio Camboriú, a calibração alcançou COE de 0,67. Na calibraçãoe validação sedimentológica na bacia do Ribeirão Concórdia, obteve-se COEde 0,82 e de 0,68, respectivamente. Na bacia do Rio Camboriú, a calibraçãosedimentológica atingiu coeficiente de 0,59. Quando comparada com ocenário sem as estradas, a inserção de estradas rurais como uso específicoda terra (cenário calibrado) resultou em aumento de 6,3% na vazão e de8,8% nos sedimentos transportados na bacia do Ribeirão Concórdia. Na baciado Rio Camboriú, houve diferenças inferiores a 0,4%. Portanto, mesmoapresentando uma pequena área dentro da bacia, as estradas rurais podeminterferir na vazão e no volume de sedimentos transportados.

Responses of landscape structure to the ecological restoration programs in the farming-pastoral ecotone of Northern China

Ecological restoration programs (ERPs) have been conducted in China since 2000 to improve ecological conditions, particularly in the farming-pastoral ecotone of Northern China. Few have studied the effects of ERPs on landscape structure. Taking West Liaohe River Basin (WLRB) as a case study, we explored how landscape dynamics were altered before and after ERPs from 1990 through 2015 by using multi-temporal Landsat TM images. We analyzed the effects of ERPs on landscape structure by exploring the relationships between landscape features and land cover change (LCC). The results indicate that dramatic changes in land cover and landscape structure occurred before and after ERPs implementation. During 2000–2015 woodlands increased with a sharper annual growth, grasslands reclamation slowed down and was restricted, whereas more croplands were converted to grasslands and woodlands. ERPs decreased landscape fragmentation and increased landscape diversity, due mostly to the portion and spatial configures of croplands, grasslands and woodlands. Landscape fragmentation was significantly correlated with mean patch size of grasslands (r = −0.677, p < 0.0001) and woodlands (r = −0.515, p < 0.0001), as well as patch number ratio of croplands to the sum of grasslands and woodlands (r = −0.414, p < 0.01). Additionally, landscape diversity had a significant negative correlation with the areal ratio of grasslands (r = −0.345, p < 0.001). Our findings indicate that the LCCs were in agreement with ERPs' key goals. The changes in landscape structure in WLRB, however, were not expected from the ERPs design. Given the importance of landscape structure in human vulnerability to environment, it seemed that EPRs from the central government should not only regulate specific land use but also focus on the health and sustainability of the landscapes. Explicit function-based local landscape management should be taken into account for the future through better design and implementations of ERPs.

Distribution and abundance of Aphanomyces euteiches in agricultural soils: effect of land use type, soil properties, and crop management practices

Aphanomyces euteiches is a soil-borne pathogen that causes root rot in susceptible pulse crops. Although widespread across Canada, A. euteiches was not reported in Saskatchewan until 2012. The distribution of this pathogen across the Canadian prairies is unknown and it is unclear whether it is native to the region. The objective of this study was to conduct a survey of A. euteiches across the major agricultural soils of Saskatchewan, Canada to determine its distribution and to assess the relative importance of factors related to its distribution and possible spread across the province. Soil samples were collected from lentil and pea fields and their associated roadside ditches, as well as from native and tame rangelands. Soil samples were analyzed using a quantitative polymerase chain reaction (qPCR) assay to detect and quantify the presence of A. euteiches. In addition, root rot severity was assessed on affected pea and lentil plants, and the physical and chemical properties of the soils were measured. A. euteiches was present across all land use (i.e., annual cropland, roadside ditches, and rangeland) and soil types in Saskatchewan. A. euteiches abundance was highest in samples collected from annually cropped fields. Within annual cropland, A. euteiches abundance was higher in pea fields than lentil fields. Soil moisture, total and organic carbon, and total nitrogen were positively correlated to A. euteiches abundance in field and roadside soils. Based on this survey, A. euteiches is wide-spread across all the major agricultural regions of Saskatchewan and is not limited to specific soil or land use types. The frequent detection of A. euteiches in native rangeland indicates it is likely native to Saskatchewan. The significant relationship between A. euteiches gene abundance and disease severity in pea fields indicates that the qPCR assay may be a useful indicator for predicting the potential for certain agricultural soils to cause A. euteiches root rot in pea crops.

Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge (1985–2009) and monthly suspended sediment load data (1985–2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation’s standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha−1year−1 on riparian lowlands of the Xinjiang main channel to 33 ton ha−1year−1 on mountain highlands, with a basin-wide mean of 19 ton ha−1year−1. The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha−1year−1). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25° were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.

Spatial Regression Analysis of Pedestrian Crashes Based on Point-of-Interest Data

Pedestrian safety has recently been considered as one of the most serious issues in the research of traffic safety. This study aims at analyzing the spatial correlation between the frequency of pedestrian crashes and various predictor variables based on open source point-of-interest (POI) data which can provide specific land use features and user characteristics. Spatial regression models were developed at Traffic Analysis Zone (TAZ) level using 10,333 pedestrian crash records within the Fifth Ring of Beijing in 2015. Several spatial econometrics approaches were used to examine the spatial autocorrelation in crash count per TAZ, and the spatial heterogeneity was investigated by a geographically weighted regression model. The results showed that spatial error model performed better than other two spatial models and a traditional ordinary least squares model. Specifically, bus stops, hospitals, pharmacies, restaurants, and office buildings had positive impacts on pedestrian crashes, while hotels were negatively associated with the occurrence of pedestrian crashes. In addition, it was proven that there was a significant sign of localization effects for different POIs. Depending on these findings, lots of recommendations and countermeasures can be proposed to better improve the traffic safety for pedestrians.

A Framework to Evaluate Land Take Control Policy Efficiency in Friuli Venezia Giulia, Italy

The development of effective policies against land take should be based on a deep knowledge of the specific land use dynamics and their determinants in a regional context. To this end, the traditional quantitative land use change analyses need to be integrated with a more accurate spatial and qualitative evaluation of the effects of the land use zoning of municipal land development plans and of the connected supplementary regulations (e.g., local building regulations). Land take limitation policies in Italy are largely based on the definition of quantitative thresholds for new development zones, while ignoring all those undeveloped zones that have been assigned building rights codes by plans of which the knowledge could largely impact policies. This paper attempted to define a conceptual framework of analysis which integrates a land use change assessment with an analysis in a Geographic Information System (GIS) environment of the spatial distribution of normative zones. The method was tested on the Friuli Venezia Giulia region (north-east Italy)—a territory that has experienced rapid growth in recent decades—by analyzing the spatial impact of the recently promulgated regional laws on land take control, the explicit and specific purpose of which was to limit commercial and industrial land use in the whole region. The soil sealing data were analyzed by performing a cross-comparison with the building rights permissions data, thus achieving a comprehensive evaluation of the past and predicted land take for commercial and industrial uses. Results demonstrated that the expected land take will exceed the past urbanization rate, highlighting a substantial inefficacy of the promulgated regional laws in promoting local land take control. The main innovations of this study relate to the definition of a newer qualitative methodology for framing an efficient decision-making supporting system, while helping to achieve the long-term sustainability of policies.

Analysis of the application of an advanced classifier algorithm to ultra-high resolution unmanned aerial aircraft imagery – a neural network approach

ABSTRACT Mapping the existing land use is the essential activity in the management of an area, especially in densely urbanized areas. Knowing the development, amount, and extent of specific land use will be very helpful in management activities. The availability of geospatial data acquisition technology such as unmanned aerial systems (UAS) is currently beneficial for monitoring and inventory activities. Geospatial data with ultra-high resolution are now easily obtained using UAS. This study evaluated the performance of advanced classification algorithms on ultra-high-resolution UAS aerial imagery data based on the different number of regions of interest (ROIs) with two different algorithms, namely, Multilayer Perceptron (MLP) and Radial Basis Function Neural Network (RBFNN). Evaluation was carried out regarding both the performance of computing time and accuracy. The final result shows that the number of ROIs affects the results of classification accuracy as well as the computing time. The MLP algorithm provides inconsistent accuracy but fast computing time, while the RBFNN algorithm provides consistent accuracy with slow computing time. The MLP algorithm is suitable if the researcher prioritizes the computational speed performance, but if the researcher prioritizes the accuracy, the RBFNN algorithm is the best choice.

Contextualizing Mangrove Forest Deforestation in Southeast Asia Using Environmental and Socio-Economic Data Products

Research Highlights: This paper provides an alternative approach to contextualize mangrove forest loss by integrating available environmental and socio-economic data sets and products. Background and Objectives: Mangrove forest ecosystems grow in brackish water especially in areas exposed to accumulation of organic matter and tides. This forest type is widely distributed in tropical and subtropical coastal areas. Recent studies have revealed that the mangrove forest ecosystem had significantly degraded due to Land Use and Cover Changes (LUCC) in the recent past. Therefore, contribution of mangrove deforestation drivers has to be assessed to ensure a comprehensive analysis for ecosystem conservation and restoration and facilitate decision making. Materials and Methods: Firstly, a correlation analysis was conducted between individual data products and mangrove deforestation. Each data product was associated with the Dominant Land Use of Deforested Mangrove Patches data for 2012. Next, calculations were performed for specific data combinations to estimate the contributions of anthropogenic factors to mangrove deforestation. Results: In general, our study revealed that 22.64% of the total deforested area was converted into agriculture, 5.85% was converted into aquaculture, 0.69% was converted into infrastructure, and 16.35% was not converted into any specific land use class but was still affected by other human activities. Conclusions: We discovered that the percentage of land affected by these anthropogenic factors varied between countries and regions. This research can facilitate trade-off analysis for natural resources and environmental sustainability policy studies. Diverse management strategies can be evaluated to assess the trade-offs between preserving mangrove forests for climate change mitigation and transforming them for economic purposes.

Multi-criteria Decision-Making Approaches to Agricultural Land Suitability Classification of Malda District, Eastern India

Land suitability classification (LSC) is an approach of land evaluation, which measures the degree of appropriateness of land for a specific land use. LSC is governed by a myriad of factors at the local and regional level including physiographic, pedologic and a host of socioeconomic and infrastructural determinants. This has called for the application of different multi-criteria decision-making (MCDM) techniques in agricultural LSC. The present study has attempted and compared various MCDM-based agricultural LSCs for Malda District in Eastern India. The study is based on multiple parameters governing agriculture, considering not only the physiographic and pedological attributes (e.g., relief, slope, soil fertility, soil organic carbon, etc.) but also the socioeconomic ones (e.g., the percentage of people engaged in agriculture, cultivator–labor ratio, degree of electrification, etc.). Four major MCDM algorithms have been applied, i.e., composite ranks, composite Z-scores, analytical hierarchy process (AHP) and weighted principal component analysis (WPCA). The results were also compared with the crop productivity-based agricultural efficiency. It was observed that about 15.44% of the area of Malda District is highly suitable for agriculture, whereas limited suitability is displayed by about 12.68% of area. The remaining part falls under moderate and marginal suitability classes. Furthermore, WPCA and AHP are superior to the nonparametric techniques of MCDM, namely composite ranks and composite Z-score. Moreover, the results of WPCA are superior to those of AHP. Due to the inherent limitations of the AHP approach, this study proposes the use of WPCA in the domain of agricultural LSC.

What Planners Know

Problem, research strategy, and findings: To understand how local land use regulation affects housing development, many researchers have surveyed planners about their jurisdictions’ policies and practices. But researchers have not systematically assessed whether such surveys yield valid and reliable information. We provide such an assessment by analyzing nine surveys conducted between 1988 and 2018 in California, the state where concern about underproduction of housing has been most pronounced. Each survey attempted to inventory local land use regulations, and some surveys also queried planners about their subjective perceptions regarding constraints on housing development. We find strikingly different responses to similar inventory questions about specific land use regulations in two surveys conducted months apart in the same municipalities, casting doubt on the reliability of such measures. Regression analysis reveals that subjective survey measures concerning land supply and density restrictions predict subsequent housing production, unlike counts of purportedly objective measures. Comparing survey data with recently developed GIS data indicates planners identify land supply as a significant constraint on residential development in municipalities where a relatively low proportion of land is vacant or in agricultural use, while identifying regulatory restrictions as a constraint in jurisdictions with little land zoned for multifamily use.Takeaway for practice: Asking planners to identify which land use regulations their localities have “on the books” does not provide a clear measure of regulatory stringency. By contrast, municipal planners’ subjective perceptions may capture otherwise unmeasurable characteristics of local land use policy. Although planners’ subjective perceptions can provide a relatively holistic measure of local land use policy, they have limited value for policy prescription. Given the problems of survey-based measures, state and federal government agencies should collect, harmonize, and distribute data concerning local land use regulation, including zoning district designations. Fair housing assessment tools and regional planning processes could facilitate these activities.

The effects of spatial discretization on performances and parameters of urban hydrological model.

Selecting a proper spatial resolution for urban rainfall runoff modeling was not a trivial issue because it could affect the model outputs. Recently, the development of remote sensing technology and increasingly available data source had enabled rainfall runoff process to be modeled at detailed and microscales. However, the models with less complexity might have equally good performance with less model establishment and computation time. This study attempted to explore the impact of model spatial resolution on model performance and parameters. Models with different discretization degree were built up on the basis of actual drainage networks, urban parcels and specific land use. The results showed that there was very little difference in the total runoff volumes while peak flows showed obvious scale effects which could be up to 30%. Generally, model calibration could compensate the scale effect. The calibrated models with different resolution showed similar performances. The consideration of effective impervious area (EIA) as a calibration parameter marginally increased performance of the calibration period but also slightly decreased performance in the validation period which indicated the importance of detailed EIA identification.

High resolution hydrogeochemical survey and estimation of baseline concentrations of trace elements in surface water of the Itacaiúnas River Basin, southeastern Amazonia: Implication for environmental studies

A high resolution systematic geochemical mapping at regional-scale is considered to be the best available method to estimate geochemical baseline levels of trace elements in stream water, and is an essential part of environmental risk assessment. This methodology was applied in a project in the Itacaiúnas River Basin, southeastern Amazon, Brazil, which includes several mines of the Carajás Mineral Province (as part of the Itacaiúnas Geochemical Mapping and Background Project, ItacGMBP). A total of 1429 samples (including 55 duplicates) were collected in 2017 at 900 sites at one sample per microbasin, during both dry and rainy periods. The analyses of 34 elements were carried out using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). In general, the waters are slightly alkaline and are classified as mixed Ca-Na-HCO3 type, indicating that they are mainly influenced by silicate rock weathering. Most metal concentrations in the water are low, except Fe and Mn. Seasonality explains differences in metal concentrations, with higher values being obtained in the rainy season. Baseline threshold values (BTVs) were calculated separately for both seasons by employing different statistical methods: iterative 2σ and DF preferentially delivered a more restrictive or conservative levels, which can be represenative of the natural BTVs (NBTVs), considering as the least degraded with low or no significant level of anthropogenic influence; and 98th percentile provides the ambient BTVs (ABTVs), which consists of natural plus diffuse anthropogenic input in the defined area. The ABTVs of Fe and Mn significantly exceed the WHO (1998) and CONAMA 357/05 limits. Spatial distribution indicates that Fe and Mn are not strictly related to geologic setting, rather they are highly influenced by specific local land use as well as deep weathering of the catchment and intense leaching and run-off during the rainy season. However, higher Mn occurrence in the dry period results from redox cycling of Fe and Mn via biogeochemical processes. The ABTVs of Ni, Cr, and V are controlled by bedrock lithology (geologic setting), mainly associated with mafic-ultramafic rocks; Cu is associated with two large hydrothermally mineralized copper belts. The estimation of baseline levels of As, Se, and Pb were highly limited due to of the large number of samples with results less than detection limits, in this case the 95th percentile was used for their BTVs. Geochemical data as well as anomalous values for most of the metals indicate that anthropogenic influence from point sources is highly negligible in the basin, except at a few points, where high NO3- has been observed, probably due to more intense human and livestock activity. This study demonstrates that site-specific geochemical baseline assessment is a crucial factor when evaluating surficial water conditions in a large basin.

Unmanned Aerial Vehicle − Based Rangeland Monitoring: Examining a Century of Vegetation Changes

Rangelands comprise a large component of the terrestrial land surface and provide critical ecosystem services, but they are degrading rapidly. Long-term rangeland monitoring with detailed, nonsubjective, quantitative observations can be expensive and difficult to maintain over time. Unmanned aerial vehicles (UAVs) provide an alternative means to gather unbiased and consistent datasets with similar details to field-based monitoring data. Comparing summer 2017 UAV images with long-term plot measurements, we demonstrate that rangeland vegetation cover changes can be accurately quantified and estimate an increase in total absolute shrub/subshrub cover from 34% in 1935 to > 80% in 2017 in central Arizona. We recommend UAV image-based rangeland monitoring for land managers interested in a few specific and dominant species, such as the foundation species, indicator species, or invasive species that require targeted monitoring. Land managers can identify and continuously monitor trends in rangeland condition, health, and degradation related to specific land use policies and management strategies.

Identifying the effects of land use change on sediment export: Integrating sediment source and sediment delivery in the Qiantang River Basin, China

Dramatic land use change caused by the rapid economic development in China has impacted the sediment export dynamics in the large basin. However, how land use change affects sediment export is still poorly understood. This study provided an integrated analysis of the relationships in a “three-level” chain linked as follows: “land use change → changes in sediment source and sediment delivery → sediment export change” for a better understanding. It used the InVEST sediment delivery ratio (SDR) model to analyze the Qiantang River Basin (4.27 ∗ 104 km2), China. Sediment export change was examined from the two perspectives: the effects of land use change on sediment source and on sediment delivery. Correlations between changes in individual land use types and changes in sediment source and sediment delivery were identified. The results indicated that sediment export reduced from 1.69 t ha−1 yr−1 in 1990 to 1.22 t ha−1 yr−1 in 2015 because of the decreased sediment source and a weakened sediment delivery function. In the study area, the conversions of cropland to urban land (urbanization) and bare land to forestland (afforestation) were found to make the major contributions to reductions in soil loss and SDR, respectively. Furthermore, soil loss change resulted in the decreases in total value of sediment export and SDR change caused a large-scale spatial change in sediment export. Our hotspot analysis revealed that the Wuxi River watershed should be targeted for priority conservation to optimize land use/cover for reducing sediment export. This study demonstrates the benefits of taking a comprehensive approach to analyze the processes associated with sediment export change. These allow to improve sediment management and promote aquatic ecosystem health by providing specific future land use recommendations, aimed at source treatment and delivery interception.

Analysis of Well Water Quality in the District of Pasir Puteh, Kelantan, Malaysia

This study was conducted to examine well water quality in areas of different land use in Pasir Puteh, Kelantan, Malaysia. A total of four water sampling locations were selected to represent specific land use types, including Pasir Puteh town (urban land use), Padang Pak Amat (industrial land use), Bukit Gedombak (landfill site) and Kampung Jelor (agricultural land use). Well water sampling was carried out twice, in March 2018 and April 2018. Water quality samples were analysed both in-situ and in the laboratory based on the Water Quality Index (WQI) as determined by the Malaysian Department of Environment (DOE). Water quality parameters analysed included Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), pH and Total Suspended Solids (TSS). The findings showed that although values of the six parameters observed did not exceed the specified standards, well water quality in all four types of land-use areas belonged to WQI Class III, with values ranging between 61.5 and 74.5. Class III quality indicates that the water should be treated first if it is to be used as drinking water supply. Well water quality in the area subject to agricultural land use exhibited the lowest WQI value of 61.5, reflecting the influence of local rice paddy activities. Continuous monitoring and immediate measures must therefore be undertaken, as these water sources remain exploited by locals for everyday use.

Decision Support System Module for Sustainable Land Development for Thailand: A Case of Chonburi Province

A decision support system (DSS) module for sustainable land development for Thailand: A case of Chonburi province was developed for decision makers based on available geographic information databases and overlaying techniques available on an internet network. Chonburi province in the Southeast Coast of Thailand was assigned as a special economic development zone or Eastern Economic Corridor (EEC) is a fast growing area for industrial and infrastructure developments causing land use conflicts between privates and governments that were observed elsewhere. Databases including administrative boundary, land resources, land uses, national policies and legislation aspects were integrated for land suitability, condition and limitation for land developments. The system employed ArcGIS Geo-processing service module available on the Central Relation Database that can be accessed via Web Services and RSS. The decision makers could access from the Web Browser and make decision under three conditions, by screening areas for specific land use types, analyzing land use limitations and conditions or for maximum land use benefits. The developed DSS module on land resources spatial analysis and legislation limitations would be a simple technological tool to preliminary and fast selection of proper land managements in the future and would be able to apply in other parts of the country.

The nature and spatial variability of lowland savanna soils: Improving the resolution of soil properties to support land management policy

AbstractA fresh approach is presented to address the increasingly urgent need for alternative land management strategies in savannas. We illustrate how fine‐scale information of soil characteristics can be used to enable a more precise delimitation of sites suitable for different forms of land stewardship, including agro‐pastoral activities, forestry, biodiversity and tourism. By collating data from previous soil surveys, and augmenting this with targeted new surveys, we produce the first national data set of soil properties for the lowland savannas of Belize. Most of these soils are typical of savanna soils worldwide, that is acidic (mean surface pH = 5.7), nutrient‐poor (mean surface total exchangeable bases [TEB] = 3.4 cmol kg−1) and coarse‐textured (mean surface clay = 13.0%). Nevertheless, there is a marked spatial variability across the country in these soil properties. Some soils exhibit unusually high subsurface clay fractions (max = 73%), whilst other sites have exceptionally high pH in lower horizons (max = 8.4). Cluster analysis is used to group sites with similar soil properties. Across 79 sites, there is a clear division between soils with high clay percentages and those with coarser textures. These are sub‐divided into five groups based on further differences in parent material, chemical properties and site characteristics. Mapping the locations of these groups enables more specific land use recommendations to be made. This ability to make targeted land use recommendations from fine‐scale soil information represents an advance over the previous national land use policy, where all savanna lands were considered unsuitable for any form of agriculture. This approach could be applied to marginal savannas worldwide.