Crop phenology refers to the date when a crop reaches a critical growth period. The main planting pattern in the North China Plain (NCP) is the rotation system of winter wheat and summer maize. Changes in the key phenological periods of winter wheat and summer maize reflect the response and adaptability of them to climatic conditions and production management measures. And the critical phenology dates are important parameters for evaluating crop growth status and irrigation water consumption in the NCP This study selected the winter wheat-summer maize stable planting area in the NCP. The GIMMS3g NDVI data from 1982 to 2015 was used. Multiple characteristis such as the maximum value, minimum value, slope, and percentage value of the curve were combined to extract phenology of winter wheat and summer maize: SOS (start of the season), PEAK (peak of the season), and EOS (end of the season). The extracted phenology was compared with the phenological records from the agro-meteorological stations. The R² was above 0.9, which was with high accuracy. (Details can be found in the reference) The phenological dataset can be applied to related researches about calculating the productivity of winter wheat and summer maize, evaluating the response of crops to climate change, and estimating irrigation water consumption in this region.
LEI Huimin
The North China Plain is an important food production area in China, with a large area of cropland and a complex planting structure. Accurately identifying the distribution of typical crops in this area and tracking the dynamic changes of planting structure are fundamental for detecting crop growth, evaluating crop irrigation water consumption and optimizing agricultural water resources allocation. This study used Fourier transform to obtatin the amplitudes and phases of the 0-5 harmonics of the MOD13Q1 NDVI data. Based on the field sample points and maximum likelihood supervised classification, the planting area of 6 typical crops (winter wheat-summer maize; winter wheat-rice; other double cropping systems; spring maize; cotton; other single cropping systems) in the North China Plain from 2001 to 2018 was identified. The identification results accuracy were evaluated through confusion matrix, comparison with the winter wheat planting area in the county-level statistical yearbook, and comparison with the proportion of winter wheat extracted by Landsat images, all of which showed good performance and high accuracy. The data can be applied to related research and analysis on crop production, irrigation water consumption estimation, and groundwater protection in the North China Plain.
LEI Huimin
The North China Plain (NCP), with an area of ~140,000 square kilometers, is among the most important agricultural producing bases in China. In addition to canal irrigation with surface water from the Yellow River, the NCP also needs much groundwater for intensive irrigation. Spatiotemporally continuous and daily evapotranspiration (ET) estimates of high spatial resolution could be valuable for improving our understanding of agricultural water consumption across the NCP, and also for improving water use efficiency for better agricultural water resource management practices over similar regions globally. This ET data set at 1 km spatial resolution and daily timescale across the NCP from Jan 2008 to Dec 2019 was generated using two source energy balance model (TSEB) and data fusion. The accuracy is generally comparable and even higher than published results, with our ET data set featuring spatiotemporal continuity and high spatial resolution for a decade. Furthermore, this data set and associated approaches are valuable for performing daily, monthly, seasonal, interannual, and trend analyses of ET in the NCP and similar regions globally.
ZHANG Caijin , LONG Di
This dataset was captured during the field investigation of the Qinghai-Tibet Plateau in June 2021 using uav aerial photography. The data volume is 3.4 GB and includes more than 330 aerial photographs. The shooting locations mainly include roads, residential areas and their surrounding areas in Lhasa Nyingchi of Tibet, Dali and Nujiang of Yunnan province, Ganzi, Aba and Liangshan of Sichuan Province. These aerial photographs mainly reflect local land use/cover type, the distribution of facility agriculture land, vegetation coverage. Aerial photographs have spatial location information such as longitude, latitude and altitude, which can not only provide basic verification information for land use classification, but also provide reference for remote sensing image inversion of large-scale regional vegetation coverage by calculating vegetation coverage.
LV Changhe, ZHANG Zemin
The data set was obtained from UAV aerial photography during the field investigation of the Qinghai Tibet Plateau in August 2020. The data size is 10.1 GB, including more than 11600 aerial photos. The shooting sites mainly include Lhasa, Shannan, Shigatse and other areas along the road, residential areas and surrounding areas. The aerial photos mainly reflect the local land use / cover type, facility agriculture distribution, grassland coverage and other information. The aerial photos have longitude, latitude and altitude information, which can provide better verification information for land use / cover remote sensing interpretation, and can also be used for vegetation coverage estimation, and provide better reference information for land use research in the study area.
LV Changhe, LIU Yaqun
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