Monitoring the built-up environment of Shanghai on the street-block level using SAR and volunteered geographic information

ABSTRACT

In this geo-statistical analysis of change detection, we illustrate the evolution of the built-up environment in Shanghai at the street-block level. Based on two TerraSAR-X image stacks with 36 and 15 images, covering the city centre of Shanghai for the time period from 2008 to 2015, a set of coherence images was created using a small baseline approach. The road network from Open Street Map, a volunteered geographic information product, serves as the input dataset to create street-blocks. A street-block is surrounded by roads and resembles a ground parcel, a real estate property – a cadastral unit. The coherence information is aggregated to these street-blocks for each observation and the variation is analysed over time. An analysis of spatial autocorrelation reveals clusters of similar behaviours. The result is a detailed map of Shanghai highlighting areas of change. We argue that the aggregation and grouping of synthetic aperture radar coherence image information to real-world entities (street-blocks) is comprehensible and relevant to the urban planning process. Therefore, this research is a contribution to the community of urban planners, designers, and government agencies who want to monitor the development of the urban landscape.     

A hierarchical spatiotemporal adaptive fusion model using one image pair

ABSTRACT

Image fusion techniques that blend multi-sensor characteristics to generate synthetic data with fine resolutions have generated great interest within the remote sensing community. Over the past decade, although many advances have been made in the spatiotemporal fusion models, there still remain several shortcomings in existing methods. In this article, a hierarchical spatiotemporal adaptive fusion model (HSTAFM) is proposed for producing daily synthetic fine-resolution fusions. The suggested model uses only one prior or posterior image pair, especially with the aim being to predict arbitrary temporal changes. The proposed model is implemented in two stages. First, the coarse-resolution image is enhanced through super-resolution based on sparse representation; second, a pre-selection of temporal change is performed. It then adopts a two-level strategy to select similar pixels, and blends multi-sensor features adaptively to generate the final synthetic data. The results of tests using both simulated and actual observed data show that the model can accurately capture both seasonal phenology change and land-cover-type change. Comparisons between HSTAFM and other developed models also demonstrate our proposed model produces consistently lower biases.     

高分辨率遥感影像的深度学习变化检测方法

为提升高分辨率遥感影像的变化检测精度,提出一种利用深度学习的变化检测方法。在预处理的基础上,利用顾及邻域信息的改进变化矢量分析算法和灰度共生矩阵算法获取影像间光谱和纹理变化,并通过设置自适应采样区间提取最可能的变化和未变化区域样本。构建并训练包含标签层的高斯伯努利深度限制玻尔兹曼机模型,以提取变化和未变化区域深层特征,从而有效辨别变化区域。通过WorldView-3与Pléiades-1影像的试验表明本文方法在变化检测精度方面优于对比方法。     

基于遥感影像的土地动态变化监测

土地利用/覆盖变化是目前研究全球及区域环境的一个重要领域,在城镇化加速的今天,城镇的土地利用格局也发生了飞速的变化。本文通过其一研究区内的Landsat TM遥感影像进行处理,获取了2007~2016年10个时相土地利用/覆盖信息,通过不同的预测模型对监测到的数据进行处理及比较,根据相应的最优预测方法预测了2017~2019年南昌市各土地类型的数据,由此研究并探讨了南昌市土地利用/覆盖的时空格局变化。     

丹江口水库面积季节变化遥感监测

基于2014年2月19日、2014年6月7日和2014年10月8日的三景资源三号卫星影像分别作为春季、夏季和秋季的代表,以河南省内的丹江口水库为研究区域,采用面向对象的遥感影像监督分类方法进行影像的分割和分类,提取出遥感影像中的水体,并结合南水北调中线工程对水域面积和周围地物的影响对这3个时期的影像进行比较和分析,得出这3个时期水域面积的变化数据。     

基于SWAT模型的细河流域土地利用/覆被变化对径流影响的研究

土地利用/覆被变化对细河流域的水文过程影响显著。为研究不同土地利用/覆被情景对流域水文要素的影响情况,本文构建了适用于细河流域的SWAT分布式水文模型,并拟算出不同情景下的流域多年平均月径流量、多年平均地表径流深度、多年平均蒸发量以及多年平均土壤侧流。模拟结果显示:当流域农林用地增加时,平均月径流量增加了8.40%;当建设用地增加时,平均月径流量减少了4.11%;当旱地及其他未利用地增加时,平均月径流量减少了1.93%。综上所述,细河流域农林用地变化对径流产量的影响相对最大,其增加导致径流量增加;旱地及其他未利用对径流产量的影响相对最小,建设用地和旱地及其他未利用地的增加导致径流量减少。     

Total evaporation estimation for accurate water accounting purposes: an appraisal of various available estimation methods

The estimation of total evaporation is fundamental for water accounting, considering its influence on water availability. Moreover, the current increase in water consumption (e.g. in sub-Saharan Africa and the world over), land cover/use changes, deteriorating water quality and the climate change projections in most regions of the world underscore the need to understand water loss. So far, different approaches have been developed and implemented in estimating the variations of total evaporation, with varying accuracies. The aim of this work was therefore, to provide a review of these different approaches for estimating total evaporation, as well as a detailed discussion of their strengths and weaknesses. Findings from this review have shown that total evaporation estimates derived, using ground-based meteorological and micro-meteorological methods are inadequate for representing its large-scale spatial variations. On the other hand, remote sensing technology, which acquires data at different resolutions (i.e. radiometric, spectral, spatial and temporal), provides timely, up-to-date and relatively accurate spatial estimates of total evaporation over large geographic coverage, for sustainable and effective water accounting, which is key for well-informed and improved management of water resources at both catchment and regional scales. In this regard, more details on the remote sensing-based methods of estimating total evaporation are provided, especially considering the robust technological advancements and its potential in characterizing earth features over time and space. This work has also managed to identify research gaps and challenges in the accurate estimation of total evaporation, using remote sensing, especially with the emergence of more advanced sensors and the characteristics of the landscape.     

基于RS与GIS技术的变更图斑自动识别方法研究

基于RS与GIS技术的土地利用变更图斑自动识别方法,即"以遥感正射影像图为基础,以地理信息和地物反射光谱为判别依据"的变更信息识别方法,能够尽量避免传统利用遥感影像分类技术进行地物变更识别存在的不足。本文通过对距离算法的改良,有效利用遥感数据的实时性和丰富性,在地理信息系统的支持下,提高了对地物变更地块的识别精度。     

基于物方影像匹配的DEM聚类变化检测

提出了DEM的变化检测问题,采用了基于密度的聚类分析方法对匹配所得的初始变化区域进行分析,实现了地表高程变化区域的检测.     

石屏县土地更新调查的影像解译结果分析

利用2005年SPOT-5高分辨率卫星影像,运用RS、GIS、GPS等新的技术手段,分析、提取了石屏县土地利用变化信息。结果显示,石屏县新的土地控制面积为3 041.37km2,与2004年变更调查统相比较,现有辖区面积增加0.53km2。土地利用类型以农业用地为主,面积达25.40 536×104hm2,占总土地面积的83.53%。通过以高分辨率卫星影像进行更新调查,有效掌握石屏县土地利用状况和动态变化,查清土地利用结构,调整土地供应,有效利用土地资源提供了翔实的基础资料和科学依据。