Two-Dimensional Ground Deformation Monitoring in Shanghai Based on SBAS and MSBAS InSAR Methods

Shanghai has experienced the greatest land subsidence in China in the past sixty years and produced undesirable environmental impact. However, horizontal ground deformation has not been understood yet. Therefore ground deformation monitoring together with the analysis of its driving forces are critical for geo-hazards early-warning, city planning and sustainable urbanization in Shanghai. In this paper, two-dimensional ground deformation monitoring was performed in Shanghai with SBAS and MSBAS InSAR methods. Twenty-nine Multi-Look Fine 6 （MF6） Radarsat-2 SLC data acquired during 2011-2013 were used to derive vertical ground deformation. Meanwhile, six descending Multi-Look Fine 6 （MF6） and four ascending Multi-Look Fine 2 （MF2） spanning April to August, 2008, were used to derive vertical and horizontal ground deformation during the observation period. The results indicate that vertical and horizontal deformations in 2008 were not homogeneously distributed in different districts ranging from 0-2 cm/year. Vertical deformation rate during 2011-2013 were decreased to less than 1 cm/year in most district of Shanghai area. Activities from groundwater exploitation and rapid urbanization are responsible for most of the ground deformation in Shanghai. Thus, future ground deformation in vertical and horizontal directions should be warranted.

A new method for generating a clear-sky Landsat composite for cropland from cloud-contaminated Landsat-7 and Landsat-8 images

A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period.It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable.Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing.The advantages of the method include(1)avoiding complicated atmospheric corrections but with reliable surface reflectance results,(2)being insensitive to errors induced by image coregistration uncertainties between Landsat and MODIS images,(3)avoiding the lack of samples for the regression analysis using the full Landsat scenes(rather than overlay regions),and(4)enhancing cloud/shadow detection.The composite image has MODIS-like surface reflectance,thus making MODIS algorithms applicable for retrieving biophysical parameters.The method was automatically implemented on a set of 13 cloud-contaminated(>39%)Landsat-7(Scan-Line CorrectorOff)and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba,Canada.The result was a 95.8%cloud-free image.The method can also substantially increase the usage of cloudcontaminated Landsat data.

Number and nest-site selection of breeding black-necked cranes over the past 40 years in the Longbao Wetland Nature Reserve,Qinghai,China

Black-necked crane(Grus nigricollis,BNC),facing serious threats from human activities and habitat variations,is an endangered species classified as vulnerable under the revised IUCN Red List.In this article,we investigated and analyzed the population and nesting microhabitat of BNCs in the Longbao National Nature Reserve(NNR)from 1978 to 2016,and found the number of BNCs increased from 24 in 1978 to 216 in 2016.This establishment of the Longbao NNR represented the activities of protecting endangered animal species are effective.However,the land cover classification results of Landsat images showed that the marsh wetland,which was the BNC’s primary habitat,decreased during 1978–2016,while artificial buildings increased,which affected the habitat of BNCs.The increase in average temperature over the past 40 years has also had an impact on the number of BNCs.BNCs preferred to nest in marsh wetlands or on islands with open water or star-like distributions through observation.The results of the principal component analysis showed that the nearest distance between nests and habitat type were the primary factors influencing nesting site selection.To protect BNC,we suggest decreasing wetland fragmentation,reducing habitat degradation and providing an undisturbed habitat.