影响土地持续利用的环境要素遥感分析——-以1:25万武汉图幅为例

本文以LandsatTM图像为主信息源,对研究区内影响土地持续利用的自然环境要素地貌、地表土壤质地、温度、湿润度和地势进行了遥感判读。在综合分析制约区域内部土地资源持续利用的环境问题基础上,提出了土地利用与环境相互协调的发展途径。     

影响土地持续利用的环境要素遥感分析———以1∶25万武汉图幅为例

本文以ＬａｎｄｓａｔＴＭ图像为主信息源，对研究区内影响土地持续利用的自然环境要素地貌、地表土壤质地、温度、湿润度和地势进行了遥感判读。在综合分析制约区域内部土地资源持续利用的环境问题基础上，提出了土地利用与环境相互协调的发展途径     

城乡生态质量对经济快速增长区建设用地扩张的响应——以合肥为例北大核心CSCD

21世纪以来,中国经济增长促进了城市化进程的快速发展,也在一定程度上带来一系列环境问题。本文以合肥为例,选用2002、2010、2020年的Landsat系列影像,利用改进的遥感生态指数(MRSEI),并引入城市扩张强度、城市重心转移模型等,探讨了城乡生态变化对建设用地扩张的响应。结果表明:2002—2020年合肥市主城区与周边乡镇生态环境质量总体呈恶化趋势,其中周边乡镇MRSEI均值由2002年的0.747下降至2020年的0.495,降幅为33.7%,主城区MRSEI均值由2002年的0.669下降至2020年的0.491,降幅为28.73%;周边乡镇生态质量下降幅度高于主城区,建设用地扩张强度大于主城区,生态破损更为严重。生态环境恶化区域主要由主城区向周边乡镇放射性分布,生态环境变好的区域主要集中在老城区周围,而城市扩张的区域与MRSEI评价结果显示的生态环境恶化区域基本重合,生态环境变化与城市建设用地扩张强度呈明显的负相关关系。     

基于遥感影像的武汉市2003～2015年城区扩张及驱动力分析

以Landsat TM/OLI遥感影像为数据源,将武汉市土地利用分类情况主要分为建成区、植被、水体三类.通过统计对比2003～2015年的各类土地面积变化发现,武汉市建成区的面积呈逐年增加的趋势.结合分析各类统计数据得出影响武汉市城区扩张的驱动力因子中,地理环境、交通因素和人口因素为其扩张的基础条件,经济结构的转变是推动主城区向外扩张的内在动力,宏观规划政策的调控起着外在的引导作用.     

土地利用的遥感识别方法研究

土地利用状况是区域规划、农作物合理布局、生态环境保护、流域水文模型建立、防洪救灾等的重要依据。本文探讨了利用不同时相陆地卫星TM信息及其植被指数(NDVI)识别土地利用类型的四种方法：①TM最佳波段组合的彩色合成解译法；②TM最佳波段组合的混合聚类法；③不同时相NDW.图的彩色合成解译法；④不同时相NDVI图的混合聚类法。通过在安徽省滁县试验区的应用表明,四种方法联合使用可有效地识别土地利用类型。     

2012-2015年中缅油气管道重要节点土地利用/覆被时空变化分析

"中缅油气管道"是我国陆上第三大能源通道,该项目的建设将改变其沿线周边的土地利用/覆盖现状,同时对沿线地区的自然环境和社会经济发展产生重要影响。本文选取中缅油气管道沿线的国内11个重要节点和缅甸境内4个重要节点作为研究区,以2012年和2015年2期Landsat7 ETM+和Landsat8 OLI影像数据作为数据源,利用决策树分类算法提取2012年和2015年2期中缅油气管道沿线重要节点的土地利用/覆被信息,分析2012年和2015年2个时期的中缅油气管道沿线15个重要节点土地利用/覆被的时空变化。研究结果表明：①15个节点中,除德宏芒市、保山隆阳区、缅甸若开邦外,其他11个节点的土地覆被变化均在20%左右;②15个节点中,最主要的土地覆被变化为植被和裸土的相互转换,其次为其他土地覆被类型向建筑的转换;③由于中缅油气管道项目的辐射作用,带动当地经济发展,改变当地的经济作物结构,因此造成大量的植被和裸土的相互转换,并造成建筑用地需求增加,出现大量的其他地表覆被类型向建筑的转换。     

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

ABSTRACT

For evaluating the progresses towards achieving the Sustainable Development Goals (SDGs), a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators. In this paper, we propose an improved methodology and a set of workflows for calculating SDGs indicators. The main improvements consist of using moderate and high spatial resolution satellite data and state-of-the-art deep learning methodology for land cover classification and for assessing land productivity. Within the European Network for Observing our Changing Planet (ERA-PLANET), three SDGs indicators are calculated. In this research, harmonized Landsat and Sentinel-2 data are analyzed and used for land productivity analysis and yield assessment, as well as Landsat 8, Sentinel-2 and Sentinel-1 time series are utilized for crop mapping. We calculate for the whole territory of Ukraine SDG indicators: 15.1.1 – ‘Forest area as proportion of total land area’; 15.3.1 – ‘Proportion of land that is degraded over total land area’; and 2.4.1 – ‘Proportion of agricultural area under productive and sustainable agriculture’. Workflows for calculating these indicators were implemented in a Virtual Laboratory Platform. We conclude that newly available high-resolution remote sensing products can significantly improve our capacity to assess several SDGs indicators through dedicated workflows.     

Identification and analysis of groundwater potential zones in Ken–Betwa river linking area using remote sensing and geographic information system

The use of remote sensing data with other ancillary data in a geographic information system (GIS) environment is useful to delineate groundwater potential zonation map of Ken–Betwa river linking area of Bundelkhand. Various themes of information such as geomorphology, land use/land cover, lineament extracted from digital processing of Landsat (ETM+) satellite data of the year 2005 and drainage map were extracted from survey of India topographic sheets, and elevation, slope data were generated from shuttle radar topography mission (SRTM) digital elevation model (DEM). These themes were overlaid to generate groundwater potential zonation (GWPZ) map of the area. The final map of the area shows different zones of groundwater prospects, viz., good (5.22% of the area), moderate (65.83% of the area) poor (15.31% of the area) and very poor (13.64% of area).     

Resolution vs. image quality in pre-tsunami imagery used for tsunami impact models in Aceh,Indonesia

Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Aceh, Indonesia. Previously, a Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30 m) images as well as a combination of 2003 and 2004 higher spatial resolution SPOT (10 m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualties and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using the new LCRs did not perform better than the original one. Particularly casualties models using 2002 LCRs performed better (δAIC > 2) than the more recent Landsat and SPOT counterparts. Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations). Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited.     

作物种植成数的遥感监测精度评价

以河南开封和山西太谷地区作为研究区域 ,选用LandsatTM作为农作物种植面积遥感监测的数据源。利用LandsatTM提取河南开封实验区 2 0 0 1年的夏季作物和山西太谷地区 2 0 0 3年秋季作物的作物种植成数。同时 ,利用IKONOS ,QuickBird高分辨率遥感影像 ,通过地面调查进行了地面作物填图和分类 ,同样得到实验区的农作物种植成数。最后通过两种结果对比 ,表明开封实验区夏季作物的监测精度达到 99%以上 ,太谷实验区秋季作物的监测精度达到 97%以上 ,由此推断 ,表明利用LandsatTM监测农作物种植成数的精度能够满足中国农情遥感监测的运行化要求     

三峡库区近30年土地利用时空变化特征分析

利用三峡库区1975年、1987年、1995年、2000年和2005年的遥感影像数据,提取各期土地利用图。以各期土地利用图为基础图件,利用G IS技术,分析了三峡库区各期土地利用类型的数量、空间分布及变化趋势,分析表明库区的耕地、林地和草地都在减少,库区近30年建设用地和河流水面的增加最为明显。同时引入土地利用变化的景观特征指数、土地利用变化速度、土地利用程度指数来总结三峡库区近30年来土地利用变化的主要时空变化特征。采用多种特征指数相结合的研究方法,有利于了解三峡库区土地利用变化的特征,可以进一步指导库区的土地利用规划,为库区的生态环境保护提供参考。     

近20年哈尔滨市呼兰区土地利用覆盖变化及驱动分析

本文基于哈尔滨市呼兰区1998—2018年Landsat TM影像数据和社会经济数据,通过ENVI、ArcMap等软件,采用监督分类、土地利用变化模型、典型相关分析法等方法,科学系统地分析了1998—2010、2010—2018、1998—2018年3个不同时段的土地利用覆盖变化特征,并对土地利用覆盖变化驱动因素进行了分析。结果表明,哈尔滨市呼兰区20年间呈居民地和水域面积增加、耕地变化不大、林草不断减少的土地利用覆盖变化格局,且前8年的变化速度和幅度大于后12年。该区土地利用覆盖变化的影响因素包括自然环境因素、社会经济因素及人口因素。     

Spatial and Temporal Dynamics of Urban Heat Island and Their Relationship with Land Cover Changes in Urbanization Process: A Case Study in Suzhou, China

One of the significant environmental consequences of urbanization is the urban heat island (UHI). In this paper, Landsat TM images of 1986 and 2004 were utilized to study the spatial and temporal variations of heat island and their relationships with land cover changes in Suzhou, a Chinese city which experienced rapid urbanization in past decades. Land cover classifications were derived to quantify urban expansions and brightness temperatures were computed from the TM thermal data to express the urban thermal environment. The spatial distributions of surface temperature indicated that heat islands had been largely broadened and showed good agreements with urban expansion. Temperature statistics of main land cover types showed that built-up and bare land had higher surface temperatures than natural land covers, implying the warming effect caused by the urbanization with natural landscape being replaced by urban areas. In addition, the spatial detail distributions of surface temperature were compared with the distribution of land cover by means of GIS buffer analysis. Results show remarkable show good correspondence between heat island variations with urban area expansions.     

长春地区地表温度异常遥感分析

热红外遥感是一项探测地热资源、植被覆盖、农作物估产等生态环境评价研究的重要技术。本次使用Landsat 7/ETM＋热红外波段（band 6）,基于单通道算法,对长春地区地表温度应用反演,从而为研究该区地热资源、土地覆盖、城市热岛效应及环境评价提供可靠的依据。研究表明,热红外遥感能够有效探测到地表温度异常,而引起其异常的原因有待我们就一步验证和深入研究。     

Quantitative monitoring of land use changes in relation to hydrology of Bhavani basin using remote sensing techniques — a case study

The paper summarises a part of the results of an on-going project for quantifying the land use changes in Bhavani basin (Geographic co-ordinates N lat 10°55′ - 11°45′,E Long. 76°30′ - 77°45′). Landsat and aerial data have been used in monitoring the dynamic changes in land use patterns. Visually interpreted Landsat MSS data of two different dates in conjunction with the historic data acquired from the Survey of India topographic maps and field data were used in this investigation. Also land use changes over two test-sites in the basin were studied using aerial photographs. During the study, it has been observed that a direct correlation exists between the rainfall and the area irrigated. The repetitive coverage of the satellite data are found to be quite remarkable, especially the 1:250,000 False Colour Composites (FCC) in assessing rapidly the temporal land use changes of a region at a cheaper cost.     

Effect of canal on land use/land cover using remote sensing and GIS

The monitoring of land use/land covers (LULCs) is an indispensable exercise for all those involved in executing policies to optimize the use of natural resources and minimize the ill impacts on the environment. The study here aims at analyzing the changes that occurred in LULC over a time span from 1990 to 2005 using multi date data of a part of Punjab. The digital data consisted of two sets of Landsat Thematic Mapper (TM) data and one set of IRS-1C data. Utilizing hybrid classification technique for interpretation and on field validation, it has been found that canal irrigation leads to changes in LULC as there is a change in cropping pattern as well as increase in water logged area.     

遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文)

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km² in 1990 to 3 794.9 km² in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China).     

Landsat卫星热红外数据地表温度遥感反演研究进展

作为驱动地表与大气之间能量交换的关键物理量,地表温度在众多领域中都发挥着重要作用,包括气候变化、环境监测、蒸散发估算以及地热异常勘探等。Landsat热红外数据因其时间连续性和高空间分辨率等特点被广泛应用于地表温度反演中。本文详细地介绍了Landsat热红外传感器及其可用的数据与产品的现状,梳理了2001年—2020年20年间基于Landsat热红外数据的地表温度遥感反演与应用的相关文献发表及互引情况,系统地综述了基于Landsat热红外数据的地表温度反演算法,包括基于辐射传输方程的算法、单窗算法、普适性单通道算法、实用单通道算法和分裂窗算法等。在此基础上,进一步介绍了每种算法的参数化方案,包括地表比辐射率和大气参数的估算方法。最后针对Landsat热红外数据地表温度遥感反演提出了未来可能的发展趋势与研究方向。     

基于Landsat TM数据的东莞市热岛效应研究

本文以东莞市为研究区域,利用1990年、1998年和2005年3期的Landsat TM数据,反演了东莞市地表温度。研究结果表明:①东莞市的高温区主要分布在建成区,低温区主要分布在水体和高植被覆盖区;②1990年到2005年,常温区面积明显减少,低温区面积大幅增加,高温区面积呈增加趋势;③从不同温度区间的转移分析来看,1990年至1998年、1998年至2005年两个时期,常温区发生转化的面积最大,其次是高温区;④地表温度与归一化植被指数都存在明显的负相关关系。     

On Urban Heat Island of Beijng Based on Landsat TM Data

IntroductionThe scientists have begun to retrieve land sur-face temperature (LST) fromsatellite data sincethe launch of TIROS-Ⅱin 60s of the 20th centu-ry . With the development of remote sensingtechnology and its application, more and moreLST retrieval …