吉林省通榆县土壤有机碳储量及时空分布研究

利用土地利用类型法,在解译通榆县1989年、2000年和2004年TM遥感影像获得土地利用数据的基础上,结合第二次土壤普查数据与1998年、2006年和2007年的实地采样测试数据,估算了3个年份土壤有机碳储量,并分析了其时空分布.人类活动导致了耕地、草地的退化以及盐碱地、沙地面积的增加,成为土壤有机碳储量变化的主要驱动因素.研究结果表明,3个年份 0～100cm的土壤有机碳储量分别为 4931.91±86.90×10^4t,4708.51±86.86×10^4t和 4874.33±88.73×10^4t,15年间减少了约57.58×10^4t; 0～20cm的有机碳储量分别为 1390.36±9.16×10^4t,1342.32±12.54×10^4t和 1378.97±13.26×10^4,约减少了11.39×10^4t.研究区土壤有机碳储量在1989年到2000年间显著减少,在2000年到2004年间有所增加.有机碳密度较高的区域集中在西北部的湿地附近,较低的地区分布在中西部.有机碳密度较高区域的面积呈整体减少趋势,有机碳密度较低区域的面积则呈增加趋势.

Rocky Desertification Risk Zone Delineation in Karst Plateau Area:A Case Study in Puding County,Guizhou Province

Karst rocky desertification is a geo-ecological problem in Southwest China. The rocky desertification risk zone delineation could be used as a guide for the regional and hierarchical rocky desertification management and prevention. We chose the middle and lower reaches of the Houzhai underground basin on the karst plateau in Puding County, Guizhou Province, China as the study area and selected land use type, elevation, slope, aspect, lithology and settlement buffer as the main driving factors of the rocky desertification. The potential risk of rocky desertification was quantifed with the factor-weights union method and statistical analysis method. Five grades of rocky desertification risk were delineated based on Geographic Information System. The extremely low, low, moderate, high and extremely high rocky desertification risk zones accounted for 5.01%, 44.17%, 33.92%, 15.59% and 1.30%, respectively. As a whole, the rocky desertification risk level was moderate because the area of low and moderate rocky desertification risk zones occupied 78.09% of the study area. However, more than half of the area （about 50.81%） was predicted to have moderate rocky desertification risk and above, indicating that the study area was subject to rocky desertification. Rocky desertification risk was higher in the southeast and lower in the northwest of the study area. Distinct differences in the distribution of rocky desertification risk zones corresponding to different factors have been found.

A land use-based spatial analysis method for human health risk assessment of heavy metals in soil and its application in Zhuzhou City, Hunan Province, China

A land use- and geographical information system-based framework was presented for potential human health risk analysis using soil sampling data obtained in Zhuzhou City, Hunan Province, China. The results show that heavy metal content in soil significantly differs among different land use types. In total, 8.3% of the study area has a hazard index(HI) above the threshold of 1.0. High HIs are recorded mainly for industrial areas. Arsenic((29)87%) and the soil ingestion pathway(about 76%) contribute most to the HI. The mean standardized error and root-mean-square standardized error data indicate that the land use-based simulation method provides more accurate estimates than the classic method, which applies only geostatistical analysis to entire study area and disregards land use information. The findings not only highlight the significance of industrial land use, arsenic and the soil ingestion exposure pathway, but also indicate that evaluating different land use-types can spatially identify areas of greater concern for human health and better identify health risks.

Non-Algorithmically Integrating Land Use Type with Spatial Interpolation of Surface Soil Nutrients in an Urbanizing Watershed

Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.

Estimates of Soil Organic Carbon Stocks in Zhejiang Province of China Based on 1:50000 Soil Database Using the PKB Method

Soil organic carbon(SOC) is an important component of farming systems and global carbon cycle. Accurately estimating SOC stock is of great importance for assessing soil productivity and modeling global climate change. A newly built 1:50 000 soil database of Zhejiang Province containing 2 154 geo-referenced soil profiles and a pedological professional knowledge-based(PKB) method were used to estimate SOC stock up to a depth of 100 cm for the Province. The spatial patterns of SOC stocks stratified by soil types,watershed(buffer analysis), topographical factors, and land use types were identified. Results showed that the soils in Zhejiang covered an area of 100 740 km2 with a total SOC stock of 831.49 × 106 t and a mean SOC density of 8.25 kg m-2, excluding water and urban areas. In terms of soil types, red soils had the highest SOC stock(259.10 × 106t), whereas mountain meadow soils contained the lowest(0.15 × 106t). In terms of SOC densities, the lowest value(5.11 kg m-2) was found in skel soils, whereas the highest value(45.30 kg m-2) was observed in mountain meadow soils. Yellow soils, as a dominant soil group, determined the SOC densities of different buffer zones in Qiantang River watershed because of their large area percentage and wide variation of SOC density values.The area percentages of various soil groups significantly varied with increasing elevation or slope when overlaid with digital elevation model data, thus influencing the SOC densities. The highest SOC density was observed under grassland, whereas the lowest SOC density was identified under unutilized land. The map of SOC density(0–100 cm depth) and the spatial patterns of SOC stocks in the Province would be helpful for relevant agencies and communities in Zhejiang Province, China.

基于RS和GIS技术城市热岛效应的研究进展

随着城市化进程的快速发展,城市环境也在发生变化,城镇化的加剧使城市中的温度变化尤为明显,城市热岛效应逐渐受到关注。本文通过对国内外学者对热岛效应的研究状况进行概述,并对城市热岛效应研究采用的部分相关技术、手段进行了归纳。通过地表反演法,下载两期的Land Sat数据,对数据进行处理得到数据分类,可以看出夏季的气温变得非常高,夏季的城市热岛效应非常明显;通过地面观测法进行观测,可以比较出各个城市热岛效应的特征及其分布规律;通过土地利用类型解译法来研究土地类型与城市热岛效应的关系;通过归一化法等方法来对城市热岛效应进行研究和概括。