cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.902
title: A dataset for infrared image dim-small aircraft target detection and tracking under ground / air background
title: 地/空背景下红外图像弱小飞机目标检测跟踪数据集

description: Dim-small target detection and tracking in infrared images is the main research content for long-range precision strike, aerospace defense confrontation, battlefield intelligence and reconnaissance. However, the simulation infrared data is not perfect and measured data lacks of samples in areas of infrared target detection and recognition. In response to this situation, we focus dim-small target detection and tracking of low altitude flying target, and provide a group of data for one or multiple fixed-wing UAV targets via outfield recording and post data processing. The data acquisition scenario covers sky background and complex field background. Dataset includes 22 image sequences, 30 trajectories, 16177 frames and 16944 targets. Each target correspond a label location in the image, and each image sequence correspond a label file. This dataset can serve researches on infrared target characteristics, dim-small object detection and precision guidance. Dataset in detail: http://www.csdata.org/p/387/.
description: Dim-small target detection and tracking in infrared images is the main research content for long-range precision strike, aerospace defense confrontation, battlefield intelligence and reconnaissance. However, the simulation infrared data is not perfect and measured data lacks of samples in areas of infrared target detection and recognition. In response to this situation, we focus dim-small target detection and tracking of low altitude flying target, and provide a group of data for one or multiple fixed-wing UAV targets via outfield recording and post data processing. The data acquisition scenario covers sky background and complex field background. Dataset includes 22 image sequences, 30 trajectories, 16177 frames and 16944 targets. Each target correspond a label location in the image, and each image sequence correspond a label file. This dataset can serve researches on infrared target characteristics, dim-small object detection and precision guidance. Dataset in detail: http://www.csdata.org/p/387/.
DOI: 10.57760/sciencedb.820
title: A dataset of the Aral Sea periphery during 2000 – 2015
title: 2000–2015年咸海边界数据集

description: Based on an automatic water extraction method and correctness procedure, we obtained the 32 series of Aral Sea coastlines during 2000–2015 were obtained in this research through modification and validation by making use of high-frequency MODIS data. This dataset can be used to delineate the tempo-spatial dynamics of the different Areal Sea areas and is benefit for analyzing the effect of human activities and environment in the current century.
description: Based on an automatic water extraction method and correctness procedure, we obtained the 32 series of Aral Sea coastlines during 2000–2015 were obtained in this research through modification and validation by making use of high-frequency MODIS data. This dataset can be used to delineate the tempo-spatial dynamics of the different Areal Sea areas and is benefit for analyzing the effect of human activities and environment in the current century.
DOI: 10.57760/sciencedb.745
title: An image dataset for field crop disease identification
title: 大田作物病害识别研究图像数据集

description: The dataset contains 15 disease images of rice, wheat and maize, each of which corresponds to a folder. Concretely, there are 6 folders of rice diseases, including bacterial blight of rice, rice false smut, rice blast, rice brown spot, rice sheath blight and rice bacterial leaf streak; 5 folders of wheat diseases, including wheat powdery mildew, wheat head blight, wheat spindle streak mosaic virus, gerlachia nivalis and wheat leaf rust; and 4 folders of maize diseases, including corn northern leaf blight, southern corn rust, corn southern leaf blight and corn rust. Each folder contains the original JPG files named by pipeline number of the disease image and the intro.txt file which introduces the basic information of the disease and its control methods. This dataset contains 17 624 high quality JPG image data.
description: The dataset contains 15 disease images of rice, wheat and maize, each of which corresponds to a folder. Concretely, there are 6 folders of rice diseases, including bacterial blight of rice, rice false smut, rice blast, rice brown spot, rice sheath blight and rice bacterial leaf streak; 5 folders of wheat diseases, including wheat powdery mildew, wheat head blight, wheat spindle streak mosaic virus, gerlachia nivalis and wheat leaf rust; and 4 folders of maize diseases, including corn northern leaf blight, southern corn rust, corn southern leaf blight and corn rust. Each folder contains the original JPG files named by pipeline number of the disease image and the intro.txt file which introduces the basic information of the disease and its control methods. This dataset contains 17 624 high quality JPG image data.
DOI: 10.57760/sciencedb.80
title: Soil Type Database of Tibet—Based on the Second National Soil Survey
title: 西藏土种志—基于第二次土壤普查数据集

description: The data from Soil types database of Tibet is based on the Second National Soil Survey, China Science Publishing in 1994,is one of the summary of Tibet land resources survey. The primary coverage of Soil types database including the distribution of soil type, the area, the main characters, the land-use and the product performance. On the basis of a series of standardization work, an ER data model was constructed which included the relation between location and soil type, and the classification relation according to Genetic Soil Classification of China. It results in a data product which contains 181 typical profiles,709 soil horizons and physical chemical properties. The database is widely used for land degradation assessments, environmental impact studies, soil carbon reserves studies, and as a soil-based data to guide agricultural production.
description: The data from Soil types database of Tibet is based on the Second National Soil Survey, China Science Publishing in 1994,is one of the summary of Tibet land resources survey. The primary coverage of Soil types database including the distribution of soil type, the area, the main characters, the land-use and the product performance. On the basis of a series of standardization work, an ER data model was constructed which included the relation between location and soil type, and the classification relation according to Genetic Soil Classification of China. It results in a data product which contains 181 typical profiles,709 soil horizons and physical chemical properties. The database is widely used for land degradation assessments, environmental impact studies, soil carbon reserves studies, and as a soil-based data to guide agricultural production.
DOI: 10.57760/sciencedb.877
title: Water-Heat-Carbon fluxes of the typical irrigated agro-ecosystem in North China Plain (2007-2018)
title: 2007-2018华北平原典型灌溉农田生态系统水热碳通量数据集

description: Based on micrometeorology, the Eddy Covariance System (EC) has become one of the standard observation methods for the exchange of CO2 and water heat flux between terrestrial ecosystems and the atmosphere. The dataset includes all the flux data accumulated in Luancheng Agro-ecosystem experimental station of the Chinese Academy of Sciences from the Eddy Covariance System, which spans from October 2007 to September 2018 and covers 11 consecutive crop years. Its underlying surface is Winter wheat - summer maize rotation cropping system, which belongs to the typical high yield agroecological type in North China Plain and has strong representativeness. The network observation, quality control and storage process of this dataset strictly abide by ChinaFLUX data management technology system to make sure the reliability. The EC flux data provide important support for the study of crop field water balance and typical cropping system adjustment in the North China Plain, the mechanism of ecosystem carbon & water coupling cycles and crop growth model simulation.
description: Based on micrometeorology, the Eddy Covariance System (EC) has become one of the standard observation methods for the exchange of CO2 and water heat flux between terrestrial ecosystems and the atmosphere. The dataset includes all the flux data accumulated in Luancheng Agro-ecosystem experimental station of the Chinese Academy of Sciences from the Eddy Covariance System, which spans from October 2007 to September 2018 and covers 11 consecutive crop years. Its underlying surface is Winter wheat - summer maize rotation cropping system, which belongs to the typical high yield agroecological type in North China Plain and has strong representativeness. The network observation, quality control and storage process of this dataset strictly abide by ChinaFLUX data management technology system to make sure the reliability. The EC flux data provide important support for the study of crop field water balance and typical cropping system adjustment in the North China Plain, the mechanism of ecosystem carbon & water coupling cycles and crop growth model simulation.
DOI: 10.57760/sciencedb.88
title: Native database in China--based on the second national soil soil survey data sets
title: 中国土种数据库——基于第二次土壤普查的全国性土壤数据集

description: 来源于全国第二次土壤普查汇总成果的中国土种数据库覆盖了上世纪80年代我国主要土种的分布、面积、主要性状、土地利用和生产性能，包括2473个典型剖面、8751个发生层及物理化学性质。该数据库由9张表组成：土种基本信息表、典型剖面景观表、典型剖面理化性质表、统计剖面理化性质表、省名表、县市名表、地点与土种关系表、土类表和亚类表。
description: 来源于全国第二次土壤普查汇总成果的中国土种数据库覆盖了上世纪80年代我国主要土种的分布、面积、主要性状、土地利用和生产性能，包括2473个典型剖面、8751个发生层及物理化学性质。该数据库由9张表组成：土种基本信息表、典型剖面景观表、典型剖面理化性质表、统计剖面理化性质表、省名表、县市名表、地点与土种关系表、土类表和亚类表。
DOI: 10.57760/sciencedb.883
title: A water monitoring dataset of Sanjiang Plain Experimental Station of Wetland Ecology, Chinese Academy of Sciences from 2005 to 2015
title: 2005–2015年中国科学院三江平原沼泽湿地生态试验站水分监测数据集

description: The dataset named Sanjiang Station Water Monitoring Dataset from 2005 to 2015 consists of three xlsx file, including groundwater level, Water depth of Marsh Wetland and Water Surface evaporation data of Sanjiang Station.
description: The dataset named Sanjiang Station Water Monitoring Dataset from 2005 to 2015 consists of three xlsx file, including groundwater level, Water depth of Marsh Wetland and Water Surface evaporation data of Sanjiang Station.
DOI: 10.57760/sciencedb.904
title: Dataset of high temperature extremes over major land areas of the Belt and Road during 1979-2018
title: Dataset of high temperature extremes over major land areas of the Belt and Road during 1979-2018

description: In this paper, we focus on the major land areas of the Belt and Road (BR) Initiative and produce a dataset of high temperature extremes including three subdatasets of hot days, hot nights and combined hot extremes based on different thresholds for hot days, hot nights and combined hot extremes using Climate Prediction Center (CPC) gridded daily temperature data at a resolution of 0.5° during 1979-2018. Hot days are defined as the days during which daily maximum surface air temperature (Tmax) ≥ 28℃, 30℃, 32℃, 35℃, 38℃, or 40℃ in a specific year while hot nights occur with daily minimum surface air temperature (Tmin) ≥ 20℃, 25℃, or 30℃. The combined hot extremes are computed when Tmax ≥ 30℃ and Tmin ≥ 20℃, Tmax ≥ 35℃ and Tmin ≥ 25℃ or Tmax ≥ 40℃ and Tmin ≥ 30℃. The validation with China Meteorological Administration (CMA) data over eastern China for the period of 1979-2011 indicates that the dataset can capture the spatial distribution and magnitude of hot temperature extremes well.
description: In this paper, we focus on the major land areas of the Belt and Road (BR) Initiative and produce a dataset of high temperature extremes including three subdatasets of hot days, hot nights and combined hot extremes based on different thresholds for hot days, hot nights and combined hot extremes using Climate Prediction Center (CPC) gridded daily temperature data at a resolution of 0.5° during 1979-2018. Hot days are defined as the days during which daily maximum surface air temperature (Tmax) ≥ 28℃, 30℃, 32℃, 35℃, 38℃, or 40℃ in a specific year while hot nights occur with daily minimum surface air temperature (Tmin) ≥ 20℃, 25℃, or 30℃. The combined hot extremes are computed when Tmax ≥ 30℃ and Tmin ≥ 20℃, Tmax ≥ 35℃ and Tmin ≥ 25℃ or Tmax ≥ 40℃ and Tmin ≥ 30℃. The validation with China Meteorological Administration (CMA) data over eastern China for the period of 1979-2011 indicates that the dataset can capture the spatial distribution and magnitude of hot temperature extremes well.
DOI: 10.57760/sciencedb.934
title: A Global Terrestrial Ecosystem Respiration Dataset (2001-2010) Based on MODIS Land Surface Temperature and Vegetation Indices
title: A Global Terrestrial Ecosystem Respiration Dataset (2001-2010) Based on MODIS Land Surface Temperature and Vegetation Indices

description: Here, we up-scaled a validated semi-empirical, yet physiologically-based, remote sensing model — Ensemble_all using MODIS land surface temperature (MOD11C2) , enhanced vegetation indices (MOD13C1) and land cover data (MCD12C1) and harvest a global terrestrial Reco data set (2001-2010). The temporal resolution of this data set is 1 month, the spatial resolution is 0.05°, scope of this data set 55°S to 65°N, 180°W to 180°E (the crop and natural vegetation mosaic is not included), and the time duration is from January 2001 to December 2010. Cross-validation with site observations, and with the Reco outputs from variable_Q10 model proposed by Yuan et al. (2011) and from a process model LPJ_S1 reveals that our Reco data set grasps Reco patterns at both temporal and spatial scales well in most ecosystems over the world.
description: Here, we up-scaled a validated semi-empirical, yet physiologically-based, remote sensing model — Ensemble_all using MODIS land surface temperature (MOD11C2) , enhanced vegetation indices (MOD13C1) and land cover data (MCD12C1) and harvest a global terrestrial Reco data set (2001-2010). The temporal resolution of this data set is 1 month, the spatial resolution is 0.05°, scope of this data set 55°S to 65°N, 180°W to 180°E (the crop and natural vegetation mosaic is not included), and the time duration is from January 2001 to December 2010. Cross-validation with site observations, and with the Reco outputs from variable_Q10 model proposed by Yuan et al. (2011) and from a process model LPJ_S1 reveals that our Reco data set grasps Reco patterns at both temporal and spatial scales well in most ecosystems over the world.
DOI: 10.57760/sciencedb.819
title: A dataset for the trade information during 2014 – 2017 of seven pilot carbon markets in China
title: 中国七大试点碳市场2014–2017年交易信息数据集

description: In the carbon market, the research on trade information is conducive to understanding the problems of information disclosure and information transmission in the formation of carbon price. The trading data during 2014 – 2017 of Shanghai, Beijing, Guangdong, Shenzhen, Hubei, Tianjin and Chongqing were collected from the official websites of seven pilot markets. To ensure the continuity of data, all non-trade dates were removed during the data collection process. This dataset contains comprehensive trade information such as daily transaction volume and daily transaction turnover of each pilot market. It can not only serve as data support for relevant researches such as the analysis of the relationship between volume and price and the research on the effectiveness of carbon market, but also provide experience and reference for the construction of the carbon market nationwide.
description: In the carbon market, the research on trade information is conducive to understanding the problems of information disclosure and information transmission in the formation of carbon price. The trading data during 2014 – 2017 of Shanghai, Beijing, Guangdong, Shenzhen, Hubei, Tianjin and Chongqing were collected from the official websites of seven pilot markets. To ensure the continuity of data, all non-trade dates were removed during the data collection process. This dataset contains comprehensive trade information such as daily transaction volume and daily transaction turnover of each pilot market. It can not only serve as data support for relevant researches such as the analysis of the relationship between volume and price and the research on the effectiveness of carbon market, but also provide experience and reference for the construction of the carbon market nationwide.
DOI: 10.57760/sciencedb.823
title: The ocean dynamic datasets of seafloor observation network experiment system at the South China Sea
title: 南海深海海底观测网试验系统海底动力观测数据集

description: The ocean dynamic datasets of seafloor observation network experiment system at the South China Sea was completed in September 2016. This system provided energy supply and communication transmission channel through optical fiber composite power cable for the deep ocean observation platform, enabling multi-parameter, real-time and continuous ocean observation. The Subsea Dynamic Platform with CTD and ADCP was deployed in June 2017, and the collection of observation data was started from July 2017, including the collection of temperature, conductivity, water pressure from CTD and velocity from ADCP. Based on the raw observation data collected by ADCP and CTD sensors from July 2017 to December 2018, the data processing and quality control algorithm is adopted to remove outliers, add missing values, format the data and finally produce the dataset. The dataset provides basic data for oceanographic research.The dataset consists of 4 data files in total: 2017_ADCP_dataset.NC with data volume of 8.98 MB, 2018_ADCP_dataset.NC with data volume of 17.6 MB, 2017_CTD_dataset.NC with data volume of 29.5 MB, 2018_CTD_dataset.NC with data volume of 60.6 MB.
description: The ocean dynamic datasets of seafloor observation network experiment system at the South China Sea was completed in September 2016. This system provided energy supply and communication transmission channel through optical fiber composite power cable for the deep ocean observation platform, enabling multi-parameter, real-time and continuous ocean observation. The Subsea Dynamic Platform with CTD and ADCP was deployed in June 2017, and the collection of observation data was started from July 2017, including the collection of temperature, conductivity, water pressure from CTD and velocity from ADCP. Based on the raw observation data collected by ADCP and CTD sensors from July 2017 to December 2018, the data processing and quality control algorithm is adopted to remove outliers, add missing values, format the data and finally produce the dataset. The dataset provides basic data for oceanographic research.The dataset consists of 4 data files in total: 2017_ADCP_dataset.NC with data volume of 8.98 MB, 2018_ADCP_dataset.NC with data volume of 17.6 MB, 2017_CTD_dataset.NC with data volume of 29.5 MB, 2018_CTD_dataset.NC with data volume of 60.6 MB.
DOI: 10.57760/sciencedb.831
title: A long-term monitoring dataset of soil moisture content in black soil farmland during 2004–2015 under different management regimes in Hailun Agroecosystem Experimental Station, Chinese Academy of Sciences
title: 2004–2015年海伦站不同管理方式下黑土农田土壤含水量长期监测数据集

description: As a critical carrier of the material cycle of agricultural ecosystem, soil water has an important influence on crop growth and ecosystem function. Studies indicated that water is one of mainly limiting factors influencing agricultural productivity in black soil region of Northeast China. Soil moisture is an important indicator of the water environment of the terrestrial ecosystems of Chinese Ecosystem Research Network (CERN). Hailun Agroecosystem Experimental Station of Chinese Academy of Sciences (Hailun Station) is the only national station among China’s agricultural ecosystems engaged in the long-term monitoring, research, and demonstration of black soil region in Northeast China. In 1993, soil water observation field was set up by combining typical cropping regimes with fertilization regimes in Hailun Station, where long-term soil moisture monitoring and data collection has been carried. This data set is an assemblage of the long-term observation data of soil water content in soil profile under typical farmland management regimes from 2004 to 2015, which provides basic data support for the study of changes in water resources and agricultural sustainable development in the black soil region of Northeast China.
description: As a critical carrier of the material cycle of agricultural ecosystem, soil water has an important influence on crop growth and ecosystem function. Studies indicated that water is one of mainly limiting factors influencing agricultural productivity in black soil region of Northeast China. Soil moisture is an important indicator of the water environment of the terrestrial ecosystems of Chinese Ecosystem Research Network (CERN). Hailun Agroecosystem Experimental Station of Chinese Academy of Sciences (Hailun Station) is the only national station among China’s agricultural ecosystems engaged in the long-term monitoring, research, and demonstration of black soil region in Northeast China. In 1993, soil water observation field was set up by combining typical cropping regimes with fertilization regimes in Hailun Station, where long-term soil moisture monitoring and data collection has been carried. This data set is an assemblage of the long-term observation data of soil water content in soil profile under typical farmland management regimes from 2004 to 2015, which provides basic data support for the study of changes in water resources and agricultural sustainable development in the black soil region of Northeast China.
DOI: 10.34740/kaggle/dsv/4231132
title: Duplicate Value Calculator_ArcMap ESRI
DOI: 10.57760/sciencedb.859
title: A dataset of litter recovery amount and standing crop dynamics in a typical subtropical mixed evergreen and deciduous broadleaved forest (2009–2016)
title: 2009-2016年亚热带典型常绿落叶阔叶混交林凋落物回收量及现存量动态数据集

description: This dataset contains the litter recovery amount from January 2009 to December 2016 and litter standing crop from 2009 to 2016 of various plant organs in the typical subtropical mixed evergreen and deciduous broadleaved forests.
description: This dataset contains the litter recovery amount from January 2009 to December 2016 and litter standing crop from 2009 to 2016 of various plant organs in the typical subtropical mixed evergreen and deciduous broadleaved forests.