174 related articles for article (PubMed ID: 34202705)
41. Improved random forest classification model combined with C5.0 algorithm for vegetation feature analysis in non-agricultural environments.
Wang T
Sci Rep; 2024 May; 14(1):10367. PubMed ID: 38710709
[TBL] [Abstract][Full Text] [Related]
42. Extraction of
Shi Y; Zhang P; Wang Z
Sensors (Basel); 2024 Feb; 24(5):. PubMed ID: 38475077
[TBL] [Abstract][Full Text] [Related]
43. Sophisticated Vegetation Classification Based on Feature Band Set Using Hyperspectral Image.
Shang K; Zhang X; Sun Yan-li ; Zhang LF; Wang SD; Zhuang Z
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Jun; 35(6):1669-76. PubMed ID: 26601388
[TBL] [Abstract][Full Text] [Related]
44. The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models.
Jamil M; Rehman H; Saqlain Zaheer M; Tariq A; Iqbal R; Hasnain MU; Majeed A; Munir A; Sabagh AE; Habib Ur Rahman M; Raza A; Ajmal Ali M; Elshikh MS
Sci Rep; 2023 Nov; 13(1):19867. PubMed ID: 37963968
[TBL] [Abstract][Full Text] [Related]
45. Huanglongbing (citrus greening) detection using visible, near infrared and thermal imaging techniques.
Sankaran S; Maja JM; Buchanon S; Ehsani R
Sensors (Basel); 2013 Feb; 13(2):2117-30. PubMed ID: 23389343
[TBL] [Abstract][Full Text] [Related]
46. [The new method monitoring crop water content based on NIR-Red spectrum feature space].
Cheng XJ; Xu XG; Chen TE; Yang GJ; Li ZH
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Jun; 34(6):1542-7. PubMed ID: 25358162
[TBL] [Abstract][Full Text] [Related]
47. Off-Nadir Hyperspectral Sensing for Estimation of Vertical Profile of Leaf Chlorophyll Content within Wheat Canopies.
Kong W; Huang W; Casa R; Zhou X; Ye H; Dong Y
Sensors (Basel); 2017 Nov; 17(12):. PubMed ID: 29168757
[TBL] [Abstract][Full Text] [Related]
48. [Impacts of different alkaline soil on canopy spectral characteristics of overlying vegetation].
Jia KL; Zhang JH
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Mar; 34(3):782-6. PubMed ID: 25208412
[TBL] [Abstract][Full Text] [Related]
49. Gray level co-occurrence matrix (GLCM) texture based crop classification using low altitude remote sensing platforms.
Iqbal N; Mumtaz R; Shafi U; Zaidi SMH
PeerJ Comput Sci; 2021; 7():e536. PubMed ID: 34141878
[TBL] [Abstract][Full Text] [Related]
50. Detection of wheat
Zhang H; Huang L; Huang W; Dong Y; Weng S; Zhao J; Ma H; Liu L
Front Plant Sci; 2022; 13():1004427. PubMed ID: 36212329
[TBL] [Abstract][Full Text] [Related]
51. Estimation of Crop Growth Parameters Using UAV-Based Hyperspectral Remote Sensing Data.
Tao H; Feng H; Xu L; Miao M; Long H; Yue J; Li Z; Yang G; Yang X; Fan L
Sensors (Basel); 2020 Feb; 20(5):. PubMed ID: 32120958
[TBL] [Abstract][Full Text] [Related]
52. Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms.
Liu T; Liu X; Liu M; Wu L
Sensors (Basel); 2018 Dec; 18(12):. PubMed ID: 30558149
[TBL] [Abstract][Full Text] [Related]
53. Remote Sensing Imagery Data Analysis Using Marine Predators Algorithm with Deep Learning for Food Crop Classification.
Almasoud AS; Mengash HA; Saeed MK; Alotaibi FA; Othman KM; Mahmud A
Biomimetics (Basel); 2023 Nov; 8(7):. PubMed ID: 37999176
[TBL] [Abstract][Full Text] [Related]
54. Crop Nitrogen Retrieval Methods for Simulated Sentinel-2 Data Using In-Field Spectrometer Data.
Perich G; Aasen H; Verrelst J; Argento F; Walter A; Liebisch F
Remote Sens (Basel); 2021 Jun; 13(12):2404. PubMed ID: 36082363
[TBL] [Abstract][Full Text] [Related]
55. Improving the estimation accuracy of rapeseed leaf photosynthetic characteristics under salinity stress using continuous wavelet transform and successive projections algorithm.
Wang J; Tian T; Wang H; Cui J; Shi X; Song J; Li T; Li W; Zhong M; Zhang W
Front Plant Sci; 2023; 14():1284172. PubMed ID: 38130483
[TBL] [Abstract][Full Text] [Related]
56. [Measurement of sown area of safflower based on PCA and texture features classification and remote sensing imagery].
Na RH; Zheng JH; Guo BL; Sen BT; Shi MH; Sun ZQ; Jia XG; Li XJ
Zhongguo Zhong Yao Za Zhi; 2013 Nov; 38(21):3681-6. PubMed ID: 24494554
[TBL] [Abstract][Full Text] [Related]
57. [Spectral characteristics of Pinus tabulaeformis canopy with different damaged rates of needle leaf in western Liaoning Province, Northeast China].
Feng R; Zhang YS; Yu WY; Wu JW; Wang PJ; Ji RP; Che YS; Zhu YN
Ying Yong Sheng Tai Xue Bao; 2012 Jul; 23(7):1774-80. PubMed ID: 23173448
[TBL] [Abstract][Full Text] [Related]
58. Mapping Fire Severity in Southwest China Using the Combination of Sentinel 2 and GF Series Satellite Images.
Zhang X; Fan J; Zhou J; Gui L; Bi Y
Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904694
[TBL] [Abstract][Full Text] [Related]
59. [Study on the Determination of the Maturity Level of Tobacco Leaf Based on In-Situ Spectral Measurement].
Diao H; Wu YM; Yang YH; Ouyang J; Li JH; Lao CL; Xu XY
Guang Pu Xue Yu Guang Pu Fen Xi; 2016 Jun; 36(6):1826-30. PubMed ID: 30052400
[TBL] [Abstract][Full Text] [Related]
60. Assessing the role of SWIR band in detecting agricultural crop stress: a case study of Raichur district, Karnataka, India.
Swathandran S; Aslam MAM
Environ Monit Assess; 2019 Jun; 191(7):442. PubMed ID: 31203445
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]