Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Qinghan Dong"'
Autor:
Ilina Kamenova, Milen Chanev, Petar Dimitrov, Lachezar Filchev, Bogdan Bonchev, Liang Zhu, Qinghan Dong
Publikováno v:
Remote Sensing, Vol 16, Iss 7, p 1144 (2024)
The aim of this study is to predict and map winter wheat yield in the Parvomay municipality, situated in the Upper Thracian Lowland of Bulgaria, utilizing satellite data from Sentinel-2. The main crops grown in the research area are winter wheat, rap
Externí odkaz:
https://doaj.org/article/9acb1173471c4b3894e8df50869696b0
Autor:
Xiaoxuan Liu, Le Yu, Qinghan Dong, Dailiang Peng, Wenbin Wu, Qiangyi Yu, Yuqi Cheng, Yidi Xu, Xiaomeng Huang, Zheng Zhou, Dong Wang, Lei Fang, Peng Gong
Publikováno v:
PeerJ, Vol 8, p e9835 (2020)
The Northeast China Plain is one of the major grain-producing areas of China because of its fertile black soil and large fields adapted for agricultural machinery. It has experienced some land-use changes, such as urbanization, deforestation, and wet
Externí odkaz:
https://doaj.org/article/1e5dceadc59f42758b179ef795755827
Autor:
Jinlong Fan, Pierre Defourny, Xiaoyu Zhang, Qinghan Dong, Limin Wang, Zhihao Qin, Mathilde De Vroey, Chunliang Zhao
Publikováno v:
Remote Sensing, Vol 13, Iss 22, p 4641 (2021)
Agricultural landscapes are characterized by diversity and complexity, which makes crop mapping at a regional scale a top priority for different purposes such as administrative decisions and farming management. Project 32194 of the Dragon 4 Program w
Externí odkaz:
https://doaj.org/article/8683e9f60a9c4bfa9755897279a855ae
Autor:
Petar Dimitrov, Qinghan Dong, Herman Eerens, Alexander Gikov, Lachezar Filchev, Eugenia Roumenina, Georgi Jelev
Publikováno v:
Remote Sensing, Vol 11, Iss 11, p 1370 (2019)
This paper presents the results of a sub-pixel classification of crop types in Bulgaria from PROBA-V 100 m normalized difference vegetation index (NDVI) time series. Two sub-pixel classification methods, artificial neural network (ANN) and support ve
Externí odkaz:
https://doaj.org/article/1f3b67b632414ad2a802ae5c310735d2
Publikováno v:
Remote Sensing, Vol 11, Iss 4, p 455 (2019)
Vegetation indices, such as the normalized difference vegetation index (NDVI) or enhanced vegetation index (EVI) derived from remote sensing images, are widely used for crop classification. However, vegetation index profiles for different crops with
Externí odkaz:
https://doaj.org/article/906ca918f44f49a3aed66886e100a30a
Publikováno v:
Sensors, Vol 17, Iss 11, p 2638 (2017)
Image classifications, including sub-pixel analysis, are often used to estimate crop acreage directly. However, this type of assessment often leads to a biased estimation, because commission and omission errors generally do not compensate for each ot
Externí odkaz:
https://doaj.org/article/ab65573533df4f1f9096f2674f0b82b4
Publikováno v:
Cybergeo (2003)
Multitemporal Landsat7-ETM+ imagery and supplementary field survey data was used to establish a crop and land use map for an area of ±20 000 km² of Sanjiang Plain in China’s north-eastern province Heilongjiang. The “field-based” map is based
Externí odkaz:
https://doaj.org/article/ad99d314d7304f8a917b266dc99d0251
Autor:
Bingfang Wu, Miao Zhang, Hongwei Zeng, Fuyou Tian, Andries B Potgieter, Xingli Qin, Nana Yan, Sheng Chang, Yan Zhao, Qinghan Dong, Vijendra Boken, Dmitry Plotnikov, Huadong Guo, Fangming Wu, Hang Zhao, Bart Deronde, Laurent Tits, Evgeny Loupian
Publikováno v:
National Science Review. 10
Building a more resilient food system for sustainable development and reducing uncertainty in global food markets both require concurrent and near-real-time and reliable crop information for decision making. Satellite-driven crop monitoring has becom
Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 3, Iss 4, Pp 110-117 (2020)
Agricultural monitoring is essential for adequate management of food production and distribution. Crop land and crop type classification, using remote sensing time series, form an important tool to capture the agricultural production information. The
Autor:
Mathilde De Vroey, Xiaoyu Zhang, Qinghan Dong, Jinlong Fan, Pierre Defourny, Chunliang Zhao, Zhihao Qin, Limin Wang
Publikováno v:
Remote Sensing, Vol 13, Iss 4641, p 4641 (2021)
Agricultural landscapes are characterized by diversity and complexity, which makes crop mapping at a regional scale a top priority for different purposes such as administrative decisions and farming management. Project 32194 of the Dragon 4 Program w