An integrated approach for prioritization of reservoir catchment using remote sensing and geographic information system techniques

This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning.     

Soil erosion assessment in Rangit catchment,India through a process-based model in the geospatial environment

The accurate assessment of soil erosion in the spatial environment can give valuable input in designing reservoirs and for preparing watershed management action plans. Rangit River in northeastern India is affected by severe soil erosion, causing reduction in its reservoir capacity. The main aim of the paper is to estimate the soil erosion in the Rangit catchment, India through a process-based soil erosion model that integrates remote sensing and field data in the geospatial domain, and also to identify the problem areas for further watershed management action plans. Various topographic parameters that were derived from land use, soil texture and a digital elevation model were used for the estimation of soil erosion. The Morgan, Morgan and Finny model was used to compute soil erosion. Based on the drainage pattern, the catchment was divided into eight sub-catchments for detailed study. Annual soil erosion was estimated for four years from 2002 to 2005 using the corresponding year’s meteorological data. Estimated soil erosion was compared with the field data in each year and found very good correlation.     

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km²) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16 t ha⁻¹ a⁻¹. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.     

Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets

Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem.     

基于遥感和GIS的水土流失因子信息提取与分级定标研究--以攀枝花市为例

以攀枝花市为例,主要选用美国陆地卫星2003年的Landsat-7 ETM+遥感数据、1∶10万地形图,运用ERDAS/IMAG INE遥感图像处理软件及M apG IS软件提取对水土流失影响较大的植被覆盖度、地形坡度、沟谷密度、土地利用类型等因子;根据中华人民共和国行业标准《土壤侵蚀分类分级标准》(SL 190-96),建立攀枝花市水土流失强度面蚀分级指标,为进一步水土流失监测研究提供科学依据。     

煤炭开采对泥河小流域土地利用及景观格局的影响

以淮南煤矿区泥河小流域1987、1994、2000、2006、2009、2013、2017年7期多源遥感影像为数据源,结合纹理和光谱特征,利用支持向量机（SVM）对遥感影像进行分类,在此基础上分析了煤炭开采对泥河小流域近30年土地利用和景观格局变化的影响。结果表明：煤炭开采影响下流域的土地利用变化最显著的特征是耕地和建设用地的相互转变及耕地向塌陷水体的转变,30年间塌陷水体和建设用地分别增加了2 281.05、14 741.73 hm²,耕地减少了15 044.67 hm²。采煤驱动下,流域景观格局变化特征体现在以2006年为转折点,前期呈现破碎化、不规则化、异质化和低连通性变化的特征,之后呈现连续化、规则化、均衡化及高连通性变化的特征。建设用地、耕地和塌陷水体经历了不断破碎化到景观逐渐完善的过程;耕地、建设用地和自然水体斑块形状较为复杂;耕地优势性逐渐减弱,最大斑块指数由79.706 0降为38.745 5,塌陷水体和建设用地的优势性增强。     

Prediction of soil loss differences and sediment accumulation at the Nilufer creek watershed,Turkey, using multiyear satellite data in a GIS

This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km^?2 y^?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area.     

基于GIS_RS技术的厦门同安区土地利用变化研究

随着经济建设的发展,各省市的土地利用类型均发生了十分显著的变化.及时、有效地监测土地资源的变化趋势,有利于土地资源的持续发展与规划.通过对厦门市同安区1998年和2008年两个时期的TM遥感影像进行解译分析,得到其土地利用数据,结合GIS技术分析土地利用的转移情况及其产生原因,为厦门市同安区的土地资源开发及对生态环境的建设提供参考依据.     

Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California

Observing dynamic change patterns and higher-order complexities from remotely sensed images is warranted, but the main challenges include image inconsistency, plant phenological differences, weather variations, and difficulties of incorporating natural conditions into automatic image processing. In this study, we proposed a new algorithm and demonstrated it by producing 2002–2008 and 2010 land-cover maps in heterogeneous Southern California based on an existing 2009 land-cover map. The new algorithm improves the baseline land-cover map quality by discarding potential bad land-cover pixels and dividing each land-cover type into several subclasses. Time series Landsat images were used to detect changed and unchanged areas between baseline year and target year t. Subsequently, for each individual year t, each pixel that was identified as unchanged inherited the baseline classification. Otherwise, each pixel in the changed areas was classified by a similar surrogate majority classifier. The demonstration results in Southern California showed that the land-cover temporal pattern captured the observed successional stages of the ecosystem very well. The accuracy assessment had an overall classification accuracies ranging from 81% to 86% and overall kappa coefficients ranging from 0.79 to 0.83.     

Integration of remote sensing and GIS in monitoring the dynamics of land cover in Oroba-Kibos catchment area, Kenya

Land cover in Kenya is in a state of fl ux at different spatial and temporal scales. This compromises environmental integrity and socioeconomic stability of the population hence increasing their vulnerability to the externalities of environmental change. The Oroba-Kibos catchment area in western Kenya is one locality where rapid land use changes have taken place over the last 30 years. The shrubs, swamps, natural forests and other critical ecosystems have been converted on the altar of agriculture, human settlement, fuel wood and timber. This paper presents the results of a study that aimed at providing spatially-explicit information for effective remedial response through (a) Mapping the land cover; (b) Identifying the spatial distribution of land cover changes; (c) Determining the nature, rates and magnitude of the land cover changes, and; (d) Establishing the drivers of land use leading to land cover changes in Oroba-Kibos catchment area. Bi-temporal Landsat TM imagery, fi eld observation, household survey and ancillary data were obtained. Per-fi eld classifi cation of the Landsat TM imagery was performed in a GIS and the resultant land cover maps assessed using the fi eld observation data. Post-classifi cation comparison of the maps was then done to detect changes in land cover that had occurred between 1994 and 2008. SPSS was used to analyze the household survey data and attribute the detected land cover changes to their causes. The fi ndings showed that 9 broad classes characterize the catchment area including the natural forests, swamps, natural water bodies, woodlands, shrublands, built-up lands, grasslands, bare lands and croplands. Croplands are dominant and accounted for about 65% (57122 ha) of the total land in 1994, which increased at the rate of 0.89% to 73% (64772 ha) in 2008, while natural water bodies has the least spatial coverage accounting for about 0.6% (561 ha) of the total land in 1994, which diminished at the rate of 3.57% to 0.3% (260 ha) in 2008. Climate, altitude, access and rights to land, demographic changes, poverty, political governance, market availability and economic returns are the interacting mix of proximate and underlying factors that drive the land cover changes in Oroba-Kibos catchment area.     

Modelling for prediction of global deforestation based on the growth of human population

Deforestation due to ever-increasing activities of the growing human population has been an issue of major concern for the global environment. It has been especially serious in the last several decades in the developing countries. A population-deforestation model has been developed by the authors to relate the population density with the cumulative forest loss, which is defined and computed as the total forest loss until 1990 since prior to human civilisation. NOAA-AVHRR-based land cover map and the FAO forest statistics have been used for 1990 land cover. A simulated land cover map, based on climatic data, is used for computing the natural land cover before the human impacts. With the 1990 land cover map as base and using the projected population growth, predictions are then made for deforestation until 2025 and 2050 in both spatial and statistical forms.     

安徽省含山县土地整理耕地质量评价及其变化研究

土地整理是改善土地利用条件,提高土地质量的有效措施,对土地整理后的耕地质量进行评价是土地整理重要工作之一。从耕地质量的内涵和土地整理项目的基本要求出发,选取耕地自然条件和耕地利用条件2个基本因素和12个影响因子,将特尔斐法与层次分析法相结合,确定各因子权重,构建基于土地整理的耕地质量评价指标体系。以安徽省含山县铜闸镇土地整理项目为例,采用传统的土壤调查与3S技术相结合的方法,分析土地整理复垦过程中耕地质量时空格局变化,得出整理前、后耕地质量的级别变化。研究结果表明,通过土地整理,研究区的耕地质量空间分布和级别发生了很大变化,整理后一级、二级、三级质量的土地比整理前分别增加了7.20%,11.95%和0.65%,四级、五级则分别减少了15.65%和4.16%,整理后的耕地质量总体水平是整理前的1.291倍。     

基于遥感和GIS的环境敏感性分区研究

文章在对邹城区域生态环境状况进行分析和判别的基础上,确定了邹城环境敏感性单因子及分级依据。利用SRTM3数据,提取了邹城区域高程分级和坡度数据;利用TM遥感影像,通过监督分类和和人机交互解译方法提取植被要素和土地利用/覆被数据。结合收集到的矿产资源、自然保护及风景区及采煤塌陷风险分布专题信息建立敏感性分析数据库,使用ARCGIS平台进行空间叠加分析,得到邹城区域环境敏感性分区图。发现邹城区域重度敏感区主要分布在坡度较大、易发生水土流失地区以及山地;中度敏感区主要包括地下水源地、贡献较大的水体、自然保护区和部分塌陷风险较大的区域;轻度敏感区多为天然及人工林地。对于不同敏感级别的地区应有针对性地采取保护性开发,并在土地利用中尽量避免对重度及中度敏感区的干预。最后指出了应用RS和GIS空间信息技术进行敏感性分区的作用和意义。     

基于GIS与虚拟现实的土地利用总体规划仿真展示平台设计

土地利用总体规划的合理编制与实施,需要开放的技术平台提高公众参与度。集成应用地理信息系统(geographic information system,GIS)、虚拟现实(virtual reality,VR)及触摸屏等技术,探索了建设开放的土地利用总体规划展示平台,以直观、形象及简洁的形式向公众展现了专业的规划工作内容。研究表明:二、三维地理信息技术可与触觉等虚拟现实融合,实现了跨领域的技术创新的集成应用,创造了仿真的土地利用总体规划展示环境,实现了"图、文、数、声"一体化呈现。该平台突破传统纸质张贴形式的局限,推动了"开门"规划的实现,为提升政府部门公共服务职能提供了可借鉴的技术手段。     

Effects of prediction accuracy of the proportion of vegetation cover on land surface emissivity and temperature using the NDVI threshold method

Predicting land surface energy budgets requires precise information of land surface emissivity (LSE) and land surface temperature (LST). LST is one of the essential climate variables as well as an important parameter in the physics of land surface processes at local and global scales, while LSE is an indicator of the material composition. Despite the fact that there are numerous publications on methods and algorithms for computing LST and LSE using remotely sensed data, accurate prediction of these variables is still a challenging task. Among the existing approaches for calculating LSE and LST, particular attention has been paid to the normalised difference vegetation index threshold method (NDVI^THM), especially for agriculture and forest ecosystems. To apply NDVI^THM, knowledge of the proportion of vegetation cover (P_V) is essential. The objective of this study is to investigate the effect of the prediction accuracy of the P_V on the estimation of LSE and LST when using NDVI^THM. In August 2015, a field campaign was carried out in mixed temperate forest of the Bavarian Forest National Park, in southeastern Germany, coinciding with a Landsat-8 overpass. The P_V was measured in the field for 37 plots. Four different vegetation indices, as well as artificial neural network approaches, were used to estimate P_V and to compute LSE and LST. The results showed that the prediction accuracy of P_V improved using an artificial neural network (R²_CV = 0.64, RMSE_CV = 0.05) over classic vegetation indices (R²_CV = 0.42, RMSE_CV = 0.06). The results of this study also revealed that variation in the accuracy of the estimated P_V affected calculation results of the LSE. In addition, our findings revealed that, though LST depends on LSE, other parameters should also be taken into account when predicting LST, as more accurate LSE results did not increase the prediction accuracy of LST.     

陆地表层覆盖变化对地表反照率影响的四国对比

陆表覆盖变化影响地表特征从而改变地表能量平衡是理解人类活动对全球气候变化影响的关键环节。选择国际气候谈判主要国家的美国、印度和巴西作为中国的对比国,对比分析不同国别、不同气候带典型陆表覆盖类型的地表反照率时空差异,进而模拟开垦和城市化等陆表覆盖变化对反照率的影响差异。结果表明：(1) 2000年—2015年,中国、美国的地表反照率年际变化存在明显的气候带空间分异特征,中国干旱半干旱区和美国中低纬湿润区表现出降低趋势,而中国亚热带湿润和美国高纬与中部干旱区则表现出明显的升高趋势,印度的地表反照率年际变化呈微弱下降趋势,而巴西为微弱上升趋势。(2)无雪覆盖时,耕地、林地、草地和人造地表反照率具有夏高、冬低的时间变化特征,干旱半干旱区反照率明显高于湿润区。4种类型的国别差异体现在,中国亚热带湿润区地表反照率均以上升为主,干旱半干旱区则相反;美国除耕地在干旱区呈较强的升高趋势外,其余类型基本为降低趋势;印度均表现为降低趋势;巴西则表现为略微升高趋势。(3)与无雪覆盖相比,有雪覆盖时不同陆表覆盖类型地表反照率均有所提高,林地提高幅度最小,约0.06—0.26,耕地提高最大,约为0.17—0.38,且中国林地反照率提高幅度略高于美国。(4)原陆表覆盖为林地时,开垦和城镇化均导致地表反照率升高,且干旱区升高幅度高于湿润区,湿润区的升高幅度随纬度降低而减弱;为草地时,开垦主要在巴西、印度和中、美亚热带湿润区引起地表反照率升高。而城镇化引起的反照率变化则受到原有地表覆盖、季节和气候背景影响存在较复杂的国别和气候带差异。     

地图学与地理信息系统学科硕士研究生培养现状分析

地图学与地理信息系统专业是地理学下的二级学科,但已超出了地理学的学科研究范畴。本文在充分调研国内高校该学科培养现状的基础上,对研究生教育的教学理念、教学方法、培养目标、课程设置、实验教学和实践环节、师资队伍、研究生创新能力的培养等方面进行探讨和分析,并提出学科重点建设内容,对学科的研究生培养具有指导意义。     

基于RS和GIS的农作物估产方法研究进展

实时获取农作物长势及产量等信息对于现代农业的发展具有重要意义。近年来,随着遥感技术(remote sensing,RS)和地理信息系统(geographic information system,GIS)广泛应用于农作物估产领域,相继出现了一些较为实用的估产方法,主要有结合辅助数据的估产方法、基于植被指数的估产方法、基于特定模型的估产方法和基于农作物估产平台(软件)的开发等。其中,基于植被指数的估产方法又分为单一和多植被指数估产2类方法。在对近年来该领域大量文献深入研究的基础上,着重就几类热点方法展开论述,并对每类方法的优势和缺陷进行了评述,最后对该领域需要进一步研究的方向进行了探讨和展望,以期为后续研究提供参考。     

陇东先秦遗址多光谱遥感与遗址预测模型研究

考古遗址预测模型(SPM)在考古学研究和文化资源管理中有着广泛的应用,但传统的构建方法过度依赖数字高程模型(DEM),对多光谱遥感数据的应用较少.本项研究以陇东黄土高原地区的区域考古调查为例,利用第三次全国文物普查数据、商业DEM数据和Landsat 8 OLI多光谱遥感数据,构建3种考古遗址预测模型(DEM模型、多光...