摘要：
Current assessments of urban forest carbon storage were missing or largely underestimating their values due to limited spatial resolution. In this study, combining field plot measurements and satellite imagery, a wall-to-wall forest biomass map were generated at a very high spatial resolution (5 m) over urban areas in Wuhan City, China. Specifically, a series of characteristic metrics were extracted from Jilin-1 satellite images, including multispectral reflectances, vegetation indices, and texture features. The estimations of forest aboveground biomass from three machine learning models were evaluated at sampled field plot level. Results demonstrated that the random forest model achieved the highest accuracy using the leave-one-out cross-validation method, with a test set RMSE of 31.84 Mg/ha. However, discrepancies were observed in low biomass areas due to variations in vegetation species, leading to overestimation of lower values.
摘要：
Current assessments of urban forest carbon storage were missing or largely underestimating their values due to limited spatial resolution. In this study, combining field plot measurements and satellite imagery, a wall-to-wall forest biomass map were generated at a very high spatial resolution (5 m) over urban areas in Wuhan City, China. Specifically, a series of characteristic metrics were extracted from Jilin-1 satellite images, including multispectral reflectances, vegetation indices, and texture features. The estimations of forest aboveground biomass from three machine learning models were evaluated at sampled field plot level. Results demonstrated that the random forest model achieved the highest accuracy using the leave-one-out cross-validation method, with a test set RMSE of 31.84 Mg/ha. However, discrepancies were observed in low biomass areas due to variations in vegetation species, leading to overestimation of lower values.
摘要：
The Three Parallel Rivers Basin (TPRB) is a global biodiversity hotspot in the southeast of Qinghai-Tibet Plateau. The vegetation ecosystem has undergone significant changes due to global environmental changes, necessitating the long-term and fine-scale monitoring. The Hi-GLASS FVC product, derived from Landsat 8 data, has a fine spatial resolution of 30 m, but spatial gaps caused by clouds and shadows are prevalent. To address this issue, a 16-day, 30 m resolution FVC dataset was generated from 2000 to 2018 for the TPRB by fusing Hi-GLASS FVC and GLASS FVC time-series data. Combining the annual average FVC and growing-season average FVC, trend analysis of vegetation cover was conducted at two different spatial resolutions (30m and 500m) using the Sen's slope and Mann-Kendall test at a 95% confidence level. The results indicated that more areas exhibited significant improvements in vegetation than degradation. The improvements were characterized by the increase of the annual average FVC as well as the growing-season FVC for two decades. This study provides scientific supports for the development of ecological conservation plans in the TPRB region.
作者机构：
[Wang, Zihao; Zhong, Dantong; Song, Dan-Xia] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.;[Wang, Zihao; Zhong, Dantong; Song, Dan-Xia] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Hubei, Peoples R China.
会议名称：
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议时间：
JUL 17-22, 2022
会议地点：
Kuala Lumpur, MALAYSIA
会议主办单位：
[Wang, Zihao;Song, Dan-Xia;Zhong, Dantong] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.^[Wang, Zihao;Song, Dan-Xia;Zhong, Dantong] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Hubei, Peoples R China.
会议论文集名称：
IEEE International Symposium on Geoscience and Remote Sensing IGARSS
关键词：
FVC;Landsat;Sentinel;data fusion
摘要：
Fractional vegetation cover (FVC) is an important indicator reflecting changes in the Earth's ecosystem, as it is essential for simulating growth processes and modeling land surfaces. At present, there have been several FVC products available on the global scale using a variety of satellite data with different retrieval methods. Compared with other FVC products, the Landsat-based FVC is able to describe global vegetation cover at a resolution of 30 m with long time series, which can better represent vegetation cover information with more spatial details. However, the revisit cycle of Landsat satellite is 16 days, resulting in poor performance of Landsat in temporal continuity. In this study, the Landsat-based FVC was enhanced by combining normalized the Sentinel-2 data and filling in some of the missing dates. By applying different temporal reconstruction methods, the temporal continuity of 30 m FVC was significantly improved, and the strengths and weaknesses of each method were also discussed.
摘要：
A dense point cloud with rich and realistic texture is generated from multiview images using dense reconstruction algorithms such as Multi View Stereo (MVS). However, its spatial precision depends on the performance of the matching and dense reconstruction algorithms used. Moreover, outliers are usually unavoidable as mismatching of image features. The lidar point cloud lacks texture but performs better spatial precision because it avoids computational errors. This paper proposes a multiresolution patch-based 3D dense reconstruction method based on integrating multiview images and the laser point cloud. A sparse point cloud is firstly generated with multiview images by Structure from Motion (SfM), and then registered with the laser point cloud to establish the mapping relationship between the laser point cloud and multiview images. The laser point cloud is reprojected to multiview images. The corresponding optimal level of the image pyramid is predicted by the distance distribution of projected pixels, which is used as the starting level for patch optimization during dense reconstruction. The laser point cloud is used as stable seed points for patch growth and expansion, and stored by the dynamic octree structure. Subsequently, the corresponding patches are optimized and expanded with the pyramid image to achieve multiscale and multiresolution dense reconstruction. In addition, the octree's spatial index structure facilitates parallel computing with highly efficiency. The experimental results show that the proposed method is superior to the traditional MVS technology in terms of model accuracy and completeness, and have broad application prospects in high-precision 3D modeling of large scenes.
作者机构：
[Zhou, Jie; Liu, Xuan; Cui, Yilin; Xiong, Xuqian] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan, Peoples R China.;[Zhou, Jie; Liu, Xuan; Cui, Yilin; Xiong, Xuqian] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.;[Jia, Li; Lu, Jing] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China.;[Zhou, Jie] Delft Univ Technol, Delft, Netherlands.
会议名称：
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议时间：
JUL 17-22, 2022
会议地点：
Kuala Lumpur, MALAYSIA
会议主办单位：
[Zhou, Jie;Liu, Xuan;Xiong, Xuqian;Cui, Yilin] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan, Peoples R China.^[Zhou, Jie;Liu, Xuan;Xiong, Xuqian;Cui, Yilin] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.^[Jia, Li;Lu, Jing] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China.^[Zhou, Jie] Delft Univ Technol, Delft, Netherlands.
会议论文集名称：
IEEE International Symposium on Geoscience and Remote Sensing IGARSS
关键词：
vegetation anomalies;uncertainty;EO-based vegetation products;Vegetation Condition Index
摘要：
Satellite-based Earth Observation systems archived a variety of vegetation products during the last 50 years, which can reveal regional to global ecosystem dynamics across diverse spatiotemporal scales. The anomaly metrics such as Vegetation Condition Index (VCI) defined by comparing the current vegetation growth condition to historical average status based on long-term EO-based vegetation products were widely used to delineate abnormal vegetation variation exerted by either climatic or anthropogenic factors (e.g., droughts, wildfires). However, currently available long-term vegetation products may differ from each other in terms of sensors (observational platform or spectral bands), biophysical definitions (e.g., NDVI, EVI, LAI, and VOD), spatiotemporal resolution, as well as the time-spans, which results in inconsistency across these vegetation products. Taking the VCI as an example, this study evaluated the uncertainty of vegetation anomalies detected based on different vegetation products over the middle reach of the Yangtze River by explicitly considering the effect of sensors, biophysical definitions, and time-spans. The preliminary results showed that VCI derived from NDVI products from different sensors (AVHRR vs. MODIS) induced significant inconsistent anomalies over most landscapes. The differences resulting from products with different biophysical definitions (NDVI vs. EVI, LAI, and VOD) are much lower than those from different sensors but still significant over specific areas. As for the time-spans, the 20-year NDVI based VCI presented a considerable reduction in variance over the study area on average compared to VCI calculated based on 5-year NDVI. In summary, caution should be taken when applying EO-based vegetation products for vegetation anomalies mapping, especially for quantitative assessment.
作者机构：
[Liu, Lanfa; Zhou, Baitao] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.;[Liu, Lanfa; Zhou, Baitao] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.;[Liu, Guiwei] China Railway Design Corp, Tianjin, Peoples R China.;[Lian, Duan] China Railway Guangzhou Grp Co Ltd, Guangzhou, Peoples R China.;[Zhang, Rongchun] Nanjing Univ Posts & Telecommun, Sch Geog & Biol Informat, Nanjing 210023, Peoples R China.
会议名称：
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议时间：
JUL 17-22, 2022
会议地点：
Kuala Lumpur, MALAYSIA
会议主办单位：
[Liu, Lanfa;Zhou, Baitao] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.^[Liu, Lanfa;Zhou, Baitao] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.^[Liu, Guiwei] China Railway Design Corp, Tianjin, Peoples R China.^[Lian, Duan] China Railway Guangzhou Grp Co Ltd, Guangzhou, Peoples R China.^[Zhang, Rongchun] Nanjing Univ Posts & Telecommun, Sch Geog & Biol Informat, Nanjing 210023, Peoples R China.^[Zhang, Rongchun] Nanjing Univ Posts & Telecommun, Sch Commun & Informat Engn, Nanjing 210023, Peoples R China.
会议论文集名称：
IEEE International Symposium on Geoscience and Remote Sensing IGARSS
关键词：
YOLO;model ensemble;plastic waste;railway
摘要：
A rapidly increasing amount of plastic waste not only cause serious environmental issues but also pose a considerable threat to the rail transportation. It is important to monitor the intrusion of floating plastics into the railway area. In this article, we propose to detect plastic waste using You Only Look Once-v5 (YOLO-v5) algorithm and model ensemble through surveillance cameras installed along railway lines. Experiments on the size of YOLO-v5 model were carried out to find the optimal size to detect plastics. The model with large size (YOLOv5l) outperformed with an overall accuracy (OA) of 82.6% and mean Average Precision (mAP) of 0.822. Two ensemble modelling strategies were implemented considering different size combination of YOLO-v5 models including 1) nano, small and medium sizes; 2) nano, small, medium and large sizes. The latter one achieved the best result with the OA equal to 85.4% and the mAP equal to 0.834. The results indicate that YOLO-based ensemble model can effectively improve the performance of detection plastic waste using surveillance cameras and the acquired knowledge has great potential to UAV- and satellite-based high-resolution imagery.
摘要：
The El Nino-Southern Oscillation (ENSO), as one of the main factors driving extreme climate events, exerts a major influence on interannual climate variability around the world. However, ENSO effects on vegetation, especially regarding the extent, intensity, direction, are not well understood. Here, we characterize and compare the variability in vegetation response to ENSO across China and Australia and explore their underlying mechanisms. Results show that the spatial extent of ENSO-sensitive vegetation differed between China and Australia and across land cover types. For both China and Australia, the intensity and direction of vegetation anomalies were closely related to the type of ENSO events. In particular, vegetation anomalies to the Central-Pacific (CP) type ENSO events were stronger than that to the Eastern-Pacific (EP) type events of the same intensity and generally responded in an opposite way, resulting from different controls of CP-type and EP-type ENSO on precipitation and temperature. Our fmdings highlight the diverse response of vegetation triggered by different types of ENSO in China and Australia, which can improve our understanding of ENSO impacts on ecosystems in the northern and southern hemispheres.
作者机构：
[Liu, Lanfa; Zhou, Baitao] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.;[Liu, Lanfa; Zhou, Baitao] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Yi, Xuefeng] Hohai Univ, Sch Earth Sci & Engn, Nanjing 211100, Peoples R China.
会议名称：
24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow
会议时间：
JUN 06-11, 2022
会议地点：
Nice, FRANCE
会议主办单位：
[Liu, Lanfa;Zhou, Baitao] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.^[Liu, Lanfa;Zhou, Baitao] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.^[Yi, Xuefeng] Hohai Univ, Sch Earth Sci & Engn, Nanjing 211100, Peoples R China.
会议论文集名称：
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
关键词：
Crowdsourced Data;Street-Level Imagery;Object Detection;Point of Interest;Deep Learning
摘要：
Point-of-interest (POI) data contains rich semantic and spatial information, having a wide range of applications including land use, transport planning and driving navigation. However, urban POI mapping traditionally requires a lot of manpower and material resources, which only few institutions or enterprises can afford to. With the increasing amount of street-level imagery, it is possible to directly extract POI-related information from such data and automatically map the distribution of urban POIs. In the pilot study, we mainly focused on extracting POIs from billboards in street-level imagery. Firstly, the you only look once (YOLO) algorithm was considered to locate billboards in the imagery, then an optical character recognition (OCR) model was adopted to extract POI-related semantic information from the detected billboard, and finally the extracted semantic text was further processed to obtain POI results. The preliminary study shows that it is a promising way of mapping urban POIs from crowdsourced street-level data using deep learning techniques.
作者机构：
[Zhou, Jie; Liu, Xuan; Cui, Yilin; Xiong, Xuqian] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan, Peoples R China.;[Zhou, Jie] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.
会议名称：
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议时间：
JUL 17-22, 2022
会议地点：
Kuala Lumpur, MALAYSIA
会议主办单位：
[Xiong, Xuqian;Zhou, Jie;Liu, Xuan;Cui, Yilin] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan, Peoples R China.^[Zhou, Jie] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.
会议论文集名称：
IEEE International Symposium on Geoscience and Remote Sensing IGARSS
关键词：
Drought;dynamic surface water;DWI
摘要：
Surface water presence on the earth is highly variable, closely coupled to regional hydro-climatological conditions. Meanwhile, the rapid increase of earth observation-based global surface water datasets provides valuable opportunities for evaluating inter-annual or seasonal surface water dynamics. This study investigated the potential of using long-term EO-based surface water products for regional drought monitoring. In particular, the dynamic of surface water over the middle reach of the Yangtze River from 1999 to 2020 was analyzed based on the GLAD product. Furthermore, we explored the linkage between surface water anomalies (i.e., Dynamic Water Index, DWI) and Standardized Precipitation Index (measured by SPI). The preliminary results showed that: (1) DWI was significantly coupled to 12-month SPI, which confirmed that dynamic surface water extent can be used as an indicator for hydrological drought; (2) The correlation between DWI and SPI (1-month, 3-month, 6-month, 12-month) in extreme wet climate was lower than in extreme drought climate; (3) It is challengeable to distinguish the difference in coupling strength between dynamic surface water and hydrological drought caused by DWI defined with different water types (i.e., all types versus seasonal water). Much more attention should be paid to evaluating the uncertainty of the new index caused by missing values across regions.
期刊：
MATEC Web of Conferences,2019年267:04018-null ISSN：2261-236X
通讯作者：
Yuan, Xuying
作者机构：
[Yuan, Xuying; Guo, Ying; Li, Chuyun; Chen, Qin; Wu, Yijin; Peng, Hongjie] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.;[Yuan, Xuying; Guo, Ying; Li, Chuyun; Chen, Qin; Wu, Yijin; Peng, Hongjie] Cent China Normal Univ, Urban & Environm Sci Coll, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Yuan, Xuying] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Urban & Environm Sci Coll, Wuhan 430079, Hubei, Peoples R China.
会议名称：
2nd AASRI International Conference on Intelligent Systems and Control (ISC)
会议时间：
DEC 27-29, 2018
会议地点：
Lima, PERU
会议主办单位：
[Yuan, Xuying;Li, Chuyun;Chen, Qin;Peng, Hongjie;Guo, Ying;Wu, Yijin] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.^[Yuan, Xuying;Li, Chuyun;Chen, Qin;Peng, Hongjie;Guo, Ying;Wu, Yijin] Cent China Normal Univ, Urban & Environm Sci Coll, Wuhan 430079, Hubei, Peoples R China.
会议论文集名称：
MATEC Web of Conferences
关键词：
Index system;Environmental quality;Environmental assessment
摘要：
The problems were analyzed about the environmental impact in the construction projects of water conservancy in China. Some relevant data and relevant guidelines were combined with the actual work which were referred to several environmental impact assessment reports. An index system was proposed about environmental impact assessment of ecological improvement project in Xishui River.
作者机构：
[Zheng, Chaolei; Hu, Guangcheng; Lu, J; Jia, L; Jia, Li; Lu, Jing] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.;[Zhou, Jie] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
会议名称：
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议时间：
JUL 28-AUG 02, 2019
会议地点：
Yokohama, JAPAN
会议主办单位：
[Lu, Jing;Jia, Li;Zheng, Chaolei;Hu, Guangcheng] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.^[Zhou, Jie] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
会议论文集名称：
IEEE International Symposium on Geoscience and Remote Sensing IGARSS
关键词：
Drought indices;EM-DAT;drought area;drought period
摘要：
This study quantitatively evaluated the performance of six global drought indices (the self-calibrating Palmer Drought Severity Index -scPDSI, the Standardized Precipitation-Evapotranspiration Index - SPEI, the Global Precipitation Climatology Centre Drought Index - GPCC_DI, the Multivariate Standardized Drought Index - MSDI, the Standardized Soil Moisture Index - SSI, and the Standardized Precipitation Index - SPI) over China using the drought records from the Emergency Events Database (EM-DAT) by developing two indicators of the monitored drought area percentage (MDAP) and the monitored drought period percentage (MDPP). The results showed that scPDSI, SPEI, GPCC_DI, and MSDI can capture drought events in China from 1980 to 2015 better than SPI and SSI, with MDAP of similar to 80% and MDPP of similar to 70% at optimal timescales, among which SPEI and MSDI is slightly better than scPDSI and GPCC_DI.
摘要：
The monthly nighttime light data observed by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor onboard the National Polar-orbiting Partnership (NPP) satellite are useful to assess human activities. However, noise in the VIIRS data and unstable power supply in many areas often limit its application in detecting anthropic activities. This study aims to develop a new method (i.e., Patches Denoising Method, PDM) to remove noise in the VIIRS monthly nighttime light data towards better information on anthropic activities. The new synthesized data were examined in the Sahel region where the intensity of nighttime light is often affected by unstable power supply. The results showed that the new data could capture more settlements correctly compared with the annual data released by the National Centers for Environmental Information (NCEI) of the National Oceanic and Atmospheric Administration (NOAA). This suggests that the Patches De-noising Method is a useful way to remove noise in the NPP-VIIRS monthly nighttime light data.
会议名称：
IEEE International Geoscience & Remote Sensing Symposium
会议时间：
JUL 23-28, 2017
会议地点：
Fort Worth, TX
会议主办单位：
[Zhou, Yuke;Niu, Shuli] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China.^[Xu, Lili] Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.^[Xu, Lili] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Hubei, Peoples R China.^Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resource & Environm Informat Syst, Beijing 100101, Peoples R China.
会议论文集名称：
IEEE International Symposium on Geoscience and Remote Sensing IGARSS
关键词：
Modis;GPP;carbon uptake;growing season length
摘要：
The Northern Hemisphere terrestrial ecosystems play a key role in the global carbon cycle and climate change. Satellite-derived dataset makes it be available of continuous estimates of Gross Primary Production (GPP) across Earth's entire vegetated land surface. The extended growing season length (GSL) and its impacts on carbon uptake is well documented in the literature, but how the amplitude of GPP (i. e., GPPmax) occurring in the vegetation growing peak contribute to the annual GPP is not understood well. Here we used Modis GPP dataset to explore the impacts of GSL and GPPmax on the developing trend of annual GPP. Our results indicate that GPPmax is more strongly correlated with annual GPP than GSL. These findings highlight the important contribution of maximum GPP to the annual GPP and suggest further studies are needed on the carbon uptake in the favorable growing season.
摘要：
Discriminating human-induced vegetation change is essential for sustainable managements of arid and semi-arid ecosystems. Residual Trends method (RESTREND), an effective quantitative method, has been widely used to discriminate human-induced vegetation changes in specific arid and semi-arid ecosystems. However, how to define homogeneous spatial neighborhood to determine reference pixel for estimating potential climate-solely-induced vegetation growth is still a challenge. This paper firstly detected vegetation dynamics in ArHorqin Banner of China from 2000 to 2014 by Mann-Kendall method, and then used RESTREND to profile human-induced changes. We optimized strategy in RESTREND by using statistical analysis and trajectory analysis to automatically define flexible homogeneous neighborhood. Results indicated that 18.6% of study area had significantly changes. Both climate change and human activities contributed to the changes. The influence of human activities on vegetation dynamics is more than climate change, and it was the main driver for vegetation decrease in study area.
摘要：
This paper analyzes four practical change detection algorithms with Landsat-8 data on landslide mapping in the Kaikoura earthquake happened on November 14, 2016. Eleven band groups built from seven reflective bands of Landsat-8 data were used in the experiment. Total 21 change detection results based on various combinations of band groups and algorithms were obtained. The results were qualitatively and quantitatively analyzed based on manual interpretation and the ROC curve. It shows that all results have high false alarm rates and the accuracy varies for different combinations. Further analysis indicates that false alarms are those being easily affected by phenology factors and human activities, such as cropland, river, snow, and shadow etc. The high false alarm rate indicated by the ROC curve is additionally due to small but hard to avoid errors in the preparation of ground truths. Furthermore, change vector analysis offers plenty of information but does not directly enhance landslide. Based on above analysis, several possible ways to improve the change detection based landslide monitoring method are given at the end of the paper.
期刊：
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives,2016年41(B3):65-69 ISSN：1682-1750
通讯作者：
Li, C.
作者机构：
[Li, C.] Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei Province, Peoples R China.;[Li, C.; Liu, X. J.] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.;[Deng, T.] Cent China Normal Univ, Sch Fine Arts, Wuhan, Peoples R China.
通讯机构：
[Li, C.] K;[Li, C.] C;Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei Province, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.
会议名称：
23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)
会议时间：
JUL 12-19, 2016
会议地点：
Prague, CZECH REPUBLIC
会议主办单位：
[Li, C.] Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei Province, Peoples R China.^[Li, C.;Liu, X. J.] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.^[Deng, T.] Cent China Normal Univ, Sch Fine Arts, Wuhan, Peoples R China.
会议论文集名称：
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
关键词：
RFM;High-resolution satellite imagery;over-parameterization;overcorrection;stepwise regression;orthogonal distance regression;Fourier series fitting
摘要：
Over-parameterization and over-correction are two of the major problems in the rational function model (RFM). A new approach of optimized RFM (ORFM) is proposed in this paper. By synthesizing stepwise selection, orthogonal distance regression, and residual systematic error correction model, the proposed ORFM can solve the ill-posed problem and over-correction problem caused by constant term. The least square, orthogonal distance, and the ORFM are evaluated with control and check grids generated from satellite observation Terre (SPOT-5) high-resolution satellite data. Experimental results show that the accuracy of the proposed ORFM, with 37 essential RFM parameters, is more accurate than the other two methods, which contain 78 parameters, in cross-track and along-track plane. Moreover, the over-parameterization and over-correction problems have been efficiently alleviated by the proposed ORFM, so the stability of the estimated RFM parameters and its accuracy have been significantly improved.
作者：
Li, C.;Zhu, Y. J.;Li, G. E.;Zhu, Y. Q.;Li, R. H.;...
期刊：
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives,2016年41(B8):947-951 ISSN：1682-1750
通讯作者：
Wu, Y. J.
作者机构：
[Li, C.; Wu, Y. J.] Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei Province, Peoples R China.;[Li, C.; Zhu, Y. J.; Li, G. E.; Wu, Y. J.] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.;[Li, R. H.; Wang, L.] Changjiang Soil & Water Conservat Monitoring Ctr, Wuhan, Peoples R China.
通讯机构：
[Wu, Y. J.] K;[Wu, Y. J.] C;Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei Province, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.
会议名称：
23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)
会议时间：
JUL 12-19, 2016
会议地点：
Prague, CZECH REPUBLIC
会议主办单位：
[Li, C.;Wu, Y. J.] Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei Province, Peoples R China.^[Li, C.;Zhu, Y. J.;Li, G. E.;Wu, Y. J.] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.^[Li, R. H.;Wang, L.] Changjiang Soil & Water Conservat Monitoring Ctr, Wuhan, Peoples R China.
会议论文集名称：
International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences
关键词：
Soil and Water Loss;Intensity Estimation;Dynamic Interpretation;Spatial Analysis;Uncertainty;Quality Control
摘要：
Water and soil loss problems are serious in China, especially in the upper and middle reaches of big rivers. This paper dynamically observed water and soil loss in key control regions in Jialing River Basin. Based on remotely sensed images, the method used in this paper is a combination of field investigation and indoor artificial interpretation under the technologies of RS and GIS. The method was proven to be effective of improving the accuracy of interpreting. The result shows the land use types of the researched regions and how they changed among the previous years. Evaluation of water and soil conservation was made. This result can provide references for further policy-making and water and soil loss controlling.
