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Research and application of flood detention modeling for ponds and small reservoirs based on remote sensing data

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Science China(Technological Sciences) 2011年第8期54卷 2138-2144页

作者： CAO MingLiang ZHOU HuiCheng ZHANG Chi ZHANG AiJing LI HuiYun YANG Yang School of Hydraulic Engineering Dalian University of Technology Dalian 116024 China Sichuan Provincial Investigation Design & Research Institute of Water Conservancy & Hydropower Chengdu 610072 China

This paper proposes a method of small reservoir flood detention modeling that utilizes data from the American land resources satellite Landsat TM/ETM+. Precipitation and potential evapotranspiration are taken as the control conditions in this method on the basis of basin terrain classification. The objective of this method is to solve the question of a small-scale water conservancy project’s influence on flood forecasting precision, which can be used in the basin with multitudinous small reservoirs in the upstream region and can help estimate non-runoff data for small reservoir runoff. Taking the 20060826 flood as an example, the flood detention quantity of 19 small reservoirs is modeled. The results show that the absolute error of the total flood detention quantity is 0.2×10 4 m 3 , and the relative error is 0.12%. The flood detention quantity of small reservoirs in the entire basin is then modeled using this method, and the primary flood forecasting model is adjusted. After adjustment, the precision is significantly improved, with the relative error decreasing from 31.8% to 10.1%.

关键词： remote sensing data small reservoir flood detention modeling

An improved coverage-oriented retrieval algorithm for large-area remote sensing data

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International Journal of Digital Earth 2022年第1期15卷 606-625页

作者： Xuejing Yan Shibin Liu Wei Liu Qin Dai Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China University of Chinese Academy of Sciences BeijingPeople’s Republic of China

With the rapid development of satellite technology,the amount of remote sensing data and demand for remote sensing data analysis over large areas are greatly ***,it is necessary to quickly filter out an optimal dataset from massive dataset to support various remote sensing ***,with the improvements in temporal and spatial resolution,remote sensing data have become fragmented,which brings challenges to data *** present,most data service platforms rely on the query engines to retrieve *** results still have a large amount of data with a high degree of overlap,which must be manually selected for further *** process is very labour-intensive and *** paper proposes an improved coverage-oriented retrieval algorithm that aims to retrieve an optimal image combination with the minimum number of images closest to the imaging time of interest while maximized covering the target *** retrieval efficiency of this algorithm was analysed by applying different implementation practices:Arcpy,PyQGIS,and *** experimental results confirm the effectiveness of the algorithm and suggest that the GeoPandas-based approach is most advantageous when processing large-area data.

关键词： remote sensing data large-area data retrieval optimal image combination

Modeling and predicting dengue fever cases in key regions of the Philippines using remote sensing data

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Asian Pacific Journal of Tropical Medicine 2019年第2期12卷 60-66页

作者： Maria Ruth B.Pineda-Cortel Benjie M.Clemente Pham Thi Thanh Nga Department of Medical Technology Faculty of PharmacyUniversity of Santo Tomas Research Center for the Natural and Applied Sciences University of Santo Tomas The Graduate School University of Santo Tomas Vietnam National Space Center Vietnam Academy of Science and Technology

Objective: To correlate climatic and environmental factors such as land surface temperature, rainfall, humidity and normalized difference vegetation index with the incidence of dengue to develop prediction models for the Philippines using remote-sensing ***: Timeseries analysis was performed using dengue cases in four regions of the Philippines and monthly climatic variables extracted from Global Satellite Mapping of Precipitation for rainfall, and MODIS for the land surface temperature and normalized difference vegetation index from *** dataset during the period of study was utilized in Autoregressive Integrated Moving Average models to predict dengue incidence in the four regions being ***: The best-fitting models were selected to characterize the relationship between dengue incidence and climate *** predicted cases of dengue for January to December 2015 period fitted well with the actual dengue cases of the same *** also showed significantly good linear regression with a square of correlation of 0.869 5 for the four regions ***: Climatic and environmental variables are positively associated with dengue incidence and suit best as predictor factors using Autoregressive Integrated Moving Average *** finding could be a meaningful tool in developing an early warning model based on weather forecasts to deliver effective public health prevention and mitigation programs.

关键词： Dengue fever Climate change remote sensing data Autoregressive Integrated Moving Average models

Establishment of Winter Wheat Regional Simulation Model Based on remote sensing data and Its Application

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Acta meteorologica Sinica 2006年第4期20卷 447-458页

作者：马玉平王石立张黎侯应雨庄立伟王馥棠 Chinese Academy of Meteorological Sciences National Meteorological Center

Accurate crop growth monitoring and yield forecasting are significant to the food security and the sustainable development of agriculture. Crop yield estimation by remote sensing and crop growth simulation models have highly potential application in crop growth monitoring and yield forecasting. However, both of them have limitations in mechanism and regional application, respectively. Therefore, approach and methodology study on the combination of remote sensing data and crop growth simulation models are concerned by many researchers. In this paper, adjusted and regionalized WOFOST （World Food Study） in North China and Scattering by Arbitrarily Inclined Leaves-a model of leaf optical PROperties SPECTra （SAIL-PROSFPECT） were coupled through LAI to simulate Soil Adjusted Vegetation Index （SAVI） of crop canopy, by which crop model was re-initialized by minimizing differences between simulated and synthesized SAVI from remote sensing data using an optimization software （FSEOPT）. Thus, a regional remote-sensingcrop-simulation-framework-model （WSPFRS） was established under potential production level （optimal soil water condition）. The results were as follows： after re-initializing regional emergence date by using remote sensing data, anthesis, and maturity dates simulated by WSPFRS model were more close to measured values than simulated results of WOFOST; by re-initializing regional biomass weight at turn-green stage, the spatial distribution of simulated storage organ weight was more consistent with measured yields and the area with high values was nearly consistent with actual high yield area. This research is a basis for developing regional crop model in water stress production level based on remote sensing data.

关键词： crop growth simulation remote sensing data coupling model winter wheat North China

Mapping a Paleodrainage System of the Keriya River Using remote sensing data and Historical Materials

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Journal of Earth Science and Engineering 2012年第12期2卷 712-721页

作者： Lei Luo Xinyuan Wang Heng Cai Chao Li Wei Ji Key Laboratory of Digital Earth Sciences Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100094 China University of Chinese Academy of Sciences Beijing 100049 China International Centre on Space Technologies for Natural and Cultural Heritage under the auspices of UNESCO Beijing 100094 China

Keriya River, one of the ancient Four Green Corridors in the Tarim Basin, recording the changes of climate-environment and the ancient Silk Road of the region. According to the archaeological data, historical materials and paleoclimates information, its eeo-environment and climate have taken great changes since the 1.09 Ma B.P, especially during the recent 2,000 years, many famous ancient cities having been abandoned and the south route of the Silk Road has been moved southward. This study illustrates the capability of the remote sensing data （radar data, topographic data and optical images） and historical materials, in mapping the ancient drainage networks. A major paleodrainage system of Keriya River has linked the Kunlun Mountains to the Tienshan Mountains, possibly as far back as the early Pleistocene. The Keriya River will have important implications for not only the understanding of the paleoenvironments and paleoclimates of Tarim Basin from the early Pleistocene to the Holocene, but also the changes of the Silk Road.

关键词： remote sensing data historical materials paleochannel Keriya Tarim Basin Silk Road.

Dynamic of Chinas cultivated land and landcover changes of its typical regions based on remote sensing data

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Journal of Forestry Research 2001年第3期12卷 183-186,210页

作者：张佳华董文杰王长耀刘纪远姚凤梅中国科学院大气物理所全球变化东亚研究中心北京100029 中国科学院遥感应用研究所北京100101 北京林业大学生态工程学院北京100083

Using the multi-temporal Landsat data and survey data of national resources, the authors studied the dynamics of cultivated land and landcover changes of typical ecological regions in China. The results of investigation showed that the whole distribution of the cultivated land shifted to Northeast and Northwest China, and as a result, the ecological quality of cultivated land dropped down. The seacoast and cultivated land in the area of Yellow River Mouth expanded by an increasing rate of 0.73 kma-1, with a depositing rate of 2.1 kma-1. The desertification area of the dynamic of Horqin Sandy Land increased from 60.02% of the total land area in1970s to 64.82% in1980s but decreased to 54.90% in early 1990s. As to the change of North Tibet lakes, the water area of the Namu Lake decreased by 38.58 km2 from year 1970 to 1988, with a decreasing rate of 2.14 km2a-1.

关键词： remote sensing data Cultivated land Landcover change Typical ecological regions China

Establishing evaluation index system for desertification of Keerqin sandy land with remote sensing data

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Journal of Forestry Research 2005年第3期16卷 209-212页

作者： FAN Wen-yi ZHANG Wen-hua YU Su-fang LIU Dan Forestry College of Northeast Forestry University Hrbin 150040 P. R. China

Keerqin sand land is located in the transitional terrain between the Northeast Plain and Inner Mongolia （42°41′-45°15′N, 118°35′-123°30′ E） in Northeast China and it is seriously affected by desertification. According to the configuration and ecotope of the earths surface, the coverage of vegetation, occupation ratio of bare sandy land and the soil texture were selected as evaluation indexes by using the field investigation data. The evaluation index system of Keerqin sandy desertification was established by using remote sensing data. and the occupation ratio of bare sandy land was obtained by mixed spectrum model. This index system is validated by the field investioation data and results indicate that it is suitable for the desertification evaluation of *** Item： This study is supported by a grant from the National Natural Science Foundation of China （No. 30371192）

关键词： Sandy desertification Evaluation index system remote sensing data Keerqin sandy land Inner Mongolia

A Review of Disentangled Representation Learning for remote sensing data

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CAAI Artificial Intelligence Research 2022年第2期1卷 172-190页

作者： Mi Wang Huiwen Wang Jing Xiao Liang Liao State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430072China School of Computer Science Wuhan UniversityWuhan 430072China School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore

representation that can identify and isolate different potential variables hidden in the highdimensional *** representation learning can capture information about a single change factor and control it by the corresponding potential subspace,providing a robust representation for complex changes in the *** this paper,we first introduce and analyze the current status of research on disentangled representation and its causal mechanisms and summarize three crucial properties of disentangled ***,disentangled representation learning algorithms are classified into four categories and outlined in terms of both mathematical description and ***,the loss functions and objective evaluation metrics commonly used in existing work on disentangled representation are ***,the paper summarizes representative applications of disentangled representation learning in the field of remote sensing and discusses its future development.

关键词： disentangled representation learning latent representation remote sensing data deep learning

Spectrum spatial structure characteristic analysis of remote sensing alteration information and interference factors

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Journal of Central South University 2009年第4期16卷 647-652页

作者：杨自安彭省临朱谷昌石菲菲邹林张远飞 China Non-ferrous Metals Resource Geological Survey School of Geoscience and Environmental Engineering Central South University

Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.

关键词： remote sensing data alteration information background interference factor spectrum spatial structure scatter diagram