Assessment of soil total phosphorus storage in a complex topography along China's southeast coast based on multiple mapping scales

Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literature employ a single or narrow range of soil databases, which largely overlooks the impact of utilizing multiple mapping scales in estimating soil TP, especially in hilly topographies. In this study, Fujian Province, a subtropical hilly region along China’s southeast coast covered by a complex topographic environment, was taken as a case study. The influence of the mapping scale on soil TP storage (TPS)estimation was analyzed using six digital soil databases that were derived from 3 082 unique soil profiles at different mapping scales, i.e., 1:50 000 (S5),1:200 000 (S20), 1:500 000 (S50), 1:1 000 000 (S100), 1:4 000 000 (S400), and 1:10 000 000 (S1000). The regional TPS in the surface soil (0–20 cm) based on the S5, S20, S50, S100, S400, and S1000 soil maps was 20.72, 22.17, 23.06, 23.05, 22.04, and 23.48 Tg, respectively, and the corresponding TPS at0–100 cm soil depth was 80.98, 80.71, 85.00, 84.03, 82.96, and 86.72 Tg, respectively. By comparing soil TPS in the S20 to S1000 maps to that in the S5map, the relative deviations were 6.37%–13.32%for 0–20 cm and 0.33%–7.09%for 0–100 cm. Moreover, since the S20 map had the lowest relative deviation among different mapping scales as compared to S5, it could provide additional soil information and a richer soil environment than other smaller mapping scales. Our results also revealed that many uncertainties in soil TPS estimation originated from the lack of detailed soil information, i.e., representation and spatial variations among different soil types. From the time and labor perspectives, our work provides useful guidelines to identify the appropriate mapping scale for estimating regional soil TPS in areas like Fujian Province in subtropical China or other places with similar complex topographies. Moreover, it is of tremendous importance to accurately estimate soil TPS to ensure ecosystem stability and sustainable agricultural development, especially for regional decision-making and management of phosphate fertilizer application amounts.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable

The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.

Equality Testing for Soil Grid Unit Resolutions to Polygon Unit Scales with DNDC Modeling of Regional SOC Pools

Matching soil grid unit resolutions with polygon unit map scales is important to minimize the uncertainty of regional soil organic carbon(SOC) pool simulation due to their strong influences on the modeling.A series of soil grid units at varying cell sizes was derived from soil polygon units at six map scales,namely,1:50 000(C5),1:200 000(D2),1:500 000(P5),1:1 000 000(N1),1:4 000 000(N4) and 1:14 000 000(N14),in the Taihu Region of China.Both soil unit formats were used for regional SOC pool simulation with a De Nitrification-DeC omposition(DNDC) process-based model,which spans the time period from 1982 to 2000 at the six map scales.Four indices,namely,soil type number(STN),area(AREA),average SOC density(ASOCD) and total SOC stocks(SOCS) of surface paddy soils that were simulated by the DNDC,were distinguished from all these soil polygon and grid units.Subjecting to the four index values(IV) from the parent polygon units,the variations in an index value(VIV,%) from the grid units were used to assess its dataset accuracy and redundancy,which reflects the uncertainty in the simulation of SOC pools.Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pools,matching their respective soil polygon unit map scales.With these optimal raster resolutions,the soil grid units datasets can have the same accuracy as their parent polygon units datasets without any redundancy,when VIV < 1% was assumed to be a criterion for all four indices.A quadratic curve regression model,namely,y = – 0.80 × 10^(–6)x^2 + 0.0228 x + 0.0211(R^2 = 0.9994,P < 0.05),and a power function model R? = 10.394?^(0.2153)(R^2 = 0.9759,P < 0.05) were revealed,which describe the relationship between the optimal soil grid unit resolution(y,km) and soil polygon unit map scale(1:10 000x),the ratio(R?,%) of the optimal soil grid size to average polygon patch size(?,km^2) and the ?,with the highest R^2 among different mathematical regressions,respectively.This knowledge may facilitate the grid partitioning of regions during the investigation and simulation of SOC pool dynamics at a certain map scale,and be referenced to other landscape polygon patches' mesh partition.

Interactive Generalization on Large-Scale Topographical Map Supported by a Database Platform

This paper makes astudy on the interactive digital gener-alization, where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure, which are done by human andcomputer, respectively. And an inter-active map generalization environmentfor large scale topographic map is thendesigned and realized. This researchfocuses on: ① the significance of re-searching an interactive map generali-zation environment, ② the features oflarge scale topographic map and inter-active map generalization, ③ the con-struction of map generalization-orien-ted database platform.

The Validity of Open-Source Elevations for Different Topographic Map Scales and Geomatics Applications

This paper presents an analysis of four open-source Global Digital Elevation Models (GDEMs) and compares them on two topographic profiles (nearly flat, and hills regions) for mapping and geomatics applications. The chief intention is to investigate if GDEMs-based heights, contour intervals, slopes, and topographic profiles are valid for all map scales of topographic mapping, which constitutes a major issue in mapping activities. Two case studies, the Nile delta in Egypt and Makkah city in Saudi Arabia, have been utilized to represent flat and moderate-topography patterns. The investigated GDEMs include the most-recent released models: ASTER v.3, ACE 2, SRTMGL1 v.3, and NASADEM_HGT v.1 released in 2019 and 2020 with spatial resolutions of 1 and 3 arc seconds. Available accurate Ground Control Points (GCP) consist of 540 stations in the Nile delta and 175 stations in Makkah. Based on the available datasets in two study areas, it has been found that the accuracy of investigated GDEMs over known checkpoints ranges from ±2.5 and ±5.1 meters in the Nile delta region, while it varies between ±5.1 and ±8.0 meters in the Makkah area. That indicates that the utilization of GDEMs in topographic mapping differs significantly between flat and hilly spatial regions. Therefore, it is recommended to avoid using GDEMs for developing topographic maps of scale 1:25,000 or larger in flat regions and map scale 1:50,000 or larger in hilly regions. Additionally, the accomplished results showed that all GDEM-based slopes do not match with the actual slopes from known GCP over cross section’s length up to 30 kilometers. Thus, it is concluded that GDEMs are not the appropriate heights’ source for topographic mapping at medium and large map scales, and could not be utilized for topographic profiling in precise engineering and geomatics applications.

Effects of Finer Scale Soil Survey and Land-Use Classification on SWAT Hydrological Modelling Accuracy in Data-Poor Study Areas

The limited availability of high-quality spatial data often limits the development of hydrological modelling in developing countries. Hydrological models with data at different scales may generate large uncertainties in modelling outputs. This study analysed the accuracy of four SWAT built models that combine soil and land use/land cover (LULC) data at the scale of 1:250,000 and 1:100,000 in a basin of Mexico. SWAT model allowed determining that large-scale maps produced better results than data from small-scale. Sensitivity analysis with different soil data was less than LULC data. However, the small-scale can be used for exploratory purposes when testing SWAT performance.

Problems on Scales and Maps

Imaging that there is a part of the map of Sentosa Island.It reasonably represents the rela- tive positions of interest.The scale shown at the bottom centre of this map gives a measure of the ratio of the distance on the map to the actural distance. In this case,4 cm on the map represents 1 km.since a scale can be expressed in a ratio form, we have:

Clinical, brain electric earth map, endothelin and transcranial ultrasonic Doppler findings after hyperbaric oxygen treatment for severe brain injury

目的 探讨高压氧治疗重型颅脑损伤的疗效及机制。方法 重型颅脑损伤患者 35例为治疗组 ,2 0例为对照组 ,观察高压氧治疗前后临床 (GCS)、脑电地形图 (BEAM)、血内皮素 (ET)、经颅多普勒超声 (TCD)及预后 (GOS)的变化。结果 治疗组患者经高压氧治疗后临床 (GCS)、脑电地形图及预后均明显改善 ,与对照组相比有统计学意义。高压氧治疗 1个疗程后 ,治疗组血内皮素由 91 2 4± 12 18ng/L下降到 6 8 88± 14 37ng/L(P <0 0 1) ;经颅多普勒超声示大脑中动脉Vm也由 6 4 2± 4 8cm/s下降到 51 6± 4 2cm/s(P <0 0 1) ;同时 ,大脑中动脉VsPI也明显下降。统计学有显著性意义 (P <0 0 1)。结论 高压氧治疗能够明显改善重型颅脑损伤患者的临床、脑电地形图及预后 ,并且通过降低急性期血内皮素、改善大脑中动脉血流速度及血管阻力来改善重型颅脑损伤后脑血管痉挛及脑缺血缺氧。同时 ,降低颅内压是高压氧治疗重度颅脑损伤的重要机制之一。