Multitemporal SAR images for monitoring cultivation systems using case-based reasoning

This paper demonstrates that multitemporal satellite SAR images are most suitable for monitoring the rapid changes of cultivation systems in a subtropical region. A new method is proposed by applying case-based reasoning (CBR) techniques to the classification of SAR images. Stratified sampling is carried out to collect the cases so that the variations of backscatters within a class can be appropriately captured. The use of discrete cases can conveniently represent the internal changes of a class under complicated situations, such as spatial changes in soil conditions and terrain features. These spatial variations are difficult to represent by using rules or mathematical equations. The proposed method has better classification performance than supervised classification methods in the study area. The case library is reusable for time-independent classification when the SAR images are acquired at the same time of the crop growth cycles for different years. The proposed method has been tested in the Pearl River Delta in South China.     

基于PS-InSAR技术的廊坊市地面沉降监测研究

随着城市化进程的加速发展,地面沉降危害不断加剧。以廊坊市城区为示范研究区,选取近5 a的ENVISat卫星ASAR数据,采用永久散射体干涉测量(PS-InSAR)技术,提取廊坊市城区2003~2007年时间序列地面沉降形变信息,并对廊坊市地面沉降空间分布特征进行初步分析。研究结果表明:廊坊市城区年平均沉降速率在-19.2~18.7mm/a之间变化,沉降中心主要分布在城区北部地区,对城市基础设施及施工建设产生严重影响。     

Monitoring by Remote Sensing of Habitat Quality Changes in Xianyang City

With the accelerating process of society,economy and urbanization,land use and landscape changes have gradually become important to make effects on regional habitat quality.It is necessary to further investigate those two effects,the result of which can provide a scientific basis for regional habitat conservation and reasonable utilization of land,then will be of great importance in habitat protection and development of the region.In this paper,the study area was located in Xianyang city,Shaanxi Province,which had the frequent human activities and obvious land use changes.Based on the classification of land use data which interpreted by remote sensing,supported by ArcGIS software,the land use transfer matrix of Xianyang from 2000 to 2010 was analyzed.Landscape metrics were calculated by the Fragstats software,which represented for the landscape pattern changes and spatial characteristics.The InVEST model was selected to evaluate habitat quality in study area.The habitat quality changes was monitored.The results indicate that the integrated land use dynamics of Xianyang city is 2.34%,and the changes of land use rate is slow.The main transition from cultivated land and grassland to forest and construction land,which cause the area of first two land use types reduced,and the latter two types increased.The degree of fragmentation and the complexity of structure in landscape are higher than before.Habitat quality improved slightly,and its overall spatial pattern is that central and north areas are relatively higher than the south.Area percentage of excellent,good and poor grades increase,while the habitat quality of medium grade significantly decline.Among 14 districts and counties of habitat quality in Xianyang city,Xunyi County is the best,and the improved magnitude of Liquan county is the most significant.The main driving force of habitat quality change is the transform of land use pattern.Therefore,the relevant departments of Xianyang city should continue to implement the ecological protection measures,and increase the intensity about the protection and management of environment.Thereby to promote the coordinated sustainable development of land use and habitats.     

DGPS在土地利用调查中的应用——以昆明市呈贡县大渔村小流域土地利用调查为例

利用Trimble GeoExplorer3 DGPS对昆明市呈贡县滇池面山大渔村的土地利用现状，按二级分类的要求进行了调查，调查结果认为：DGPS完全可以满足高标准、高要求土地利用调查的需要，而且省工，省时，省力，速度快，精度高。     

基于MAPGIS的城市地价动态监测管理系统的实现

现阶段地价动态监测工作基本依赖手工进行,仅仅停留在对监测数据的计算上,没有考虑利用GIS技术,工作周期长,严重影响着地价监测工作的科学性和高效率.本文设计开发一个基于GIS的城市地价动态监测信息系统,旨在实现对地价数据的有效管理和充分利用,提高地价监测和更新工作准确性、科学性和实时性,还分析了各个功能的设计与实现,例如工程管理功能、地价监测功能、地价分析与预警功能等.     

Agricultural land-use change in Brazilian Amazônia between 1980 and 1995: Evidence from integrated satellite and census data

As cropland and pasture have replaced forest and cerrado in Brazilian Amazônia, concern has mounted over the effects of changing the biogeochemical and hydrological properties of one of the world's great storehouses of biomass and biodiversity. Although much recent effort has focused on the location, effects, and causes of deforestation and cerrado conversion, much less is known about the basin-wide spatial distribution and density of the land use following conversion for crops or pasture.In this paper, we use census and satellite records to develop maps of the distribution and abundance of major agricultural land uses across 4.5×10⁸ ha of Brazilian Amazônia in 1980 and 1995. Results indicate an overall expansion of 7.0×10⁶ ha in total agricultural area in Brazilian Amazônia between 1980 and 1995. The net change during this period is estimated for three different land-use types: croplands (an increase of 0.8×10⁶ ha), natural pastures (a decrease of 8.4×10⁶ ha), and planted pastures (an increase of 14.7×10⁶ ha). These estimates, the first spatially explicit quantifications of agricultural land-use activities in 1980 and 1995 across Brazilian Amazônia, are shown to be consistent with the results of applying a land use change and secondary regrowth model to published deforestation rates for the period.The resulting time slices, presented for each land-use category at 5-min (∼9 km) spatial resolution, allow for the quantification of land-use changes in this region for biogeochemical, demographic and economic models. Several foci of agricultural change existed within Brazilian Amazônia during this period: in the state of Pará, cropland was lost and planted pasture increased markedly; in Mato Grosso, both cropland and planted pasture increased; in Rondônia, planted pasture replacing forest was the primary route to agricultural expansion.     

融合不精准先验知识的Landsat 8 OLI影像深度学习分类方法

遥感影像解译是获得土地利用和土地覆盖（LULC）信息最为重要的途径之一,而自动化分类是提高LULC信息获取效率的关键。实际场景中包含大量不精准的先验知识,提取并融合其中的可用知识能进一步提高影像分类方法的精度、自动化率和规模应用能力。基于上述情况,提出了一种融合不精准先验知识的Landsat 8 OLI影像深度学习分类方法。该方法可自动规避先验知识中的不精准单元,在图斑约束空间内实现了分类样本的自动化区域选择和特征提取,并获得了高置信度知识,然后利用这些分类样本训练深度残差网络,从而实现大区域影像的精确分类。以常州市新北区为例进行实验,选用该区域2009年土地利用现状数据作为先验数据,2014年Landsat 8 OLI影像作为待分类影像。实验结果表明,所提方法可融合不精准先验知识,对大面积连片LULC信息分类精确,主要地类图斑界限准确,全图分类图斑精度达到了88.7%,Kappa系数为0.842。该方法能配合深度学习方法实现高精度Landsat 8 OLI遥感影像分类。     

基于劈窗算法的Landsat 8影像地表温度反演

陆地表面温度（LST）是表征地表能量交换和地面特征的重要指标,目前遥感技术逐渐成为区域和全球尺度上LST反演的一种便捷工具,而采样不同算法及不同影像的热红外遥感LST反演研究层出不穷,其中基于Landsat数据的反演成果尤为突出。文章利用劈窗算法对Landsat 8遥感影像进行地表温度反演,对比探讨了根据经验值与借助MODIS热红外数据两种不同方式的LST反演结果,并进行北京市热红外波段辐射亮度温度比较,针对地表温度分级进行统计,分析了当地地表温度分布趋势。结果表明：劈窗算法下Landsat 8数据的反演温度更接近实际温度,精度较高且优于MODIS产品;北京市地表温度空间分布格局受地物结构与反射率所制约,高温区主要集中分布于中东部,中低温区分布与林地及水体分布结构较为吻合。     

基于PS-InSAR的天津地区沉降监测及分析

城市地面沉降监测是保障城市安全建设和健康发展的重要手段之一,而传统的沉降监测方法无法大尺度反映地面形变信息。针对近几年天津地区出现大面积沉降现象,利用Sentinel-1A数据基于永久散射体干涉测量技术开展城区大范围沉降监测研究并分析了地面沉降原因。结果表明：近年来天津地区多处出现地面沉降,严重沉降区集中天津的武清区、北辰区以及郊区乡镇结合区域的王庆坨镇、胜芳镇、左各庄镇、静海镇以及大寺镇,其最大沉降漏斗位于王庆坨镇,沉降速率为-63.2 mm/a。经分析发现天津地面沉降与地下水过度开采、大型工业区的迁移和建设以及活动断裂带地质活动有关。     

Reprocessing the MODIS Leaf Area Index products for land surface and climate modelling

Land surface and climate modelling requires continuous and consistent Leaf Area Index (LAI). High spatiotemporal resolution and long-time record data are more in demand nowadays and will continue to be in the future. MODIS LAI products meet these requirements to some degree. However, due to the presence of cloud and seasonal snow cover, the instrument problems and the uncertainties of retrieval algorithm, the current MODIS LAI products are spatially and temporally discontinuous and inconsistent, which limits their application in land surface and climate modelling. To improve the MODIS LAI products on a global scale, we considered the characteristics of the MODIS LAI data and made the best use of quality control (QC) information, and developed an integrated two-step method to derive the improved MODIS LAI products effectively and efficiently on a global scale. First, we used the modified temporal spatial filter (mTSF) method taking advantage of background values and QC information at each pixel to do a simple data assimilation for relatively low quality data. Then we applied the post processing-TIMESAT (A software package to analyze time-series of satellite sensor data) Savitzky-Golay (SG) filter to get the final result. We implemented the method to 10 years of the MODIS Collection 5 LAI data. In comparison with the LAI reference maps and the MODIS LAI data, our results showed that the improved MODIS LAI data are closer to the LAI reference maps in magnitude and also more continuous and consistent in both time-series and spatial domains. In addition, simple statistics were used to evaluate the differences between the MODIS LAI and the improved MODIS LAI.