23.2.7 Greenhouse Detection, Plastic Mulch Detection and Analysis

Chapter Contents (Back)
Greenhouses. Plastic Mulch. Junk plastid:
See also Plastic Litter, Ocean Plastic, Beach Litter.

Aguera, F.[Francisco], Aguilar, F.J.[Fernando J.], Aguilar, M.A.[Manuel A.],
Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses,
PandRS(63), No. 6, November 2008, pp. 635-646.
Elsevier DOI 0811
QuickBird; IKONOS; Texture; Land use BibRef

Carvajal, F., Crisanto, E., Aguilar, F.J., Aguera, F., Aguilar, M.A.,
Greenhouses Detection Using an Artificial Neural Network with a Very High Resolution Satellite Image,
PDF File. 0607

Aguilar, M.A.[Manuel A.], Aguilar, F.J.[Fernando J.], Agüera, F.[Francisco],
Assessing Geometric Reliability of Corrected Images from Very High Resolution Satellites,
PhEngRS(74), No. 12, December 2008, pp. 1551-1560.
WWW Link. 0804
Validation of two theoretical models for estimating the reliability of geometric accuracies measured as Root Mean Square Error over corrected single images from QuickBird and Ikonos imagery. BibRef

Aguilar, M.A.[Manuel A.], Vallario, A.[Andrea], Aguilar, F.J.[Fernando J.], Lorca, A.G.[Andrés García], Parente, C.[Claudio],
Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain,
RS(7), No. 6, 2015, pp. 7378.
DOI Link 1507

Hasituya, Chen, Z.X.[Zhong-Xin], Wang, L.M.[Li-Min], Liu, J.[Jia],
Selecting Appropriate Spatial Scale for Mapping Plastic-Mulched Farmland with Satellite Remote Sensing Imagery,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704

Hasituya, Chen, Z.X.[Zhong-Xin], Wang, L.M.[Li-Min], Wu, W.B.[Wen-Bin], Jiang, Z.W.[Zhi-Wei], Li, H.[He],
Monitoring Plastic-Mulched Farmland by Landsat-8 OLI Imagery Using Spectral and Textural Features,
RS(8), No. 4, 2016, pp. 353.
DOI Link 1604

Hasituya, Chen, Z.X.[Zhong-Xin],
Mapping Plastic-Mulched Farmland with Multi-Temporal Landsat-8 Data,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706

Hasituya, Chen, Z.X.[Zhong-Xin], Li, F.[Fei], Hongmei,
Mapping Plastic-Mulched Farmland with C-Band Full Polarization SAR Remote Sensing Data,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802

Hao, P.Y.[Peng-Yu], Chen, Z.X.[Zhong-Xin], Tang, H.J.[Hua-Jun], Li, D.D.[Dan-Dan], Li, H.[He],
New Workflow of Plastic-Mulched Farmland Mapping using Multi-Temporal Sentinel-2 data,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906

Lu, L.Z.[Li-Zhen], Tao, Y.[Yuan], Di, L.P.[Li-Ping],
Object-Based Plastic-Mulched Landcover Extraction Using Integrated Sentinel-1 and Sentinel-2 Data,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Nemmaoui, A.[Abderrahim], Aguilar, M.A.[Manuel A.], Aguilar, F.J.[Fernando J.], Novelli, A.[Antonio], Lorca, A.G.[Andrés García],
Greenhouse Crop Identification from Multi-Temporal Multi-Sensor Satellite Imagery Using Object-Based Approach: A Case Study from Almería (Spain),
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Aguilar, M., Pozo, J.L., Aguilar, F.J., Gracia, A.M., Fernandez, I., Sanchez-Hermosilla, J., Negreiros, J.,
Application Of Close-range Photogrammetry And Digital Photography Analysis For The Estimation Of Leaf Area Index In A Greenhouse Tomato Culture,
PDF File. 1006

Aguilar, M.A.[Manuel A.], Bianconi, F.[Francesco], Aguilar, F.J.[Fernando J.], Fernández, I.[Ismael],
Object-Based Greenhouse Classification from GeoEye-1 and WorldView-2 Stereo Imagery,
RS(6), No. 5, 2014, pp. 3554-3582.
DOI Link 1407

Aguilar, M.A.[Manuel A.], Nemmaoui, A.[Abderrahim], Novelli, A.[Antonio], Aguilar, F.J.[Fernando J.], Lorca, A.G.[Andrés García],
Object-Based Greenhouse Mapping Using Very High Resolution Satellite Data and Landsat 8 Time Series,
RS(8), No. 6, 2016, pp. 513.
DOI Link 1608
Finding particular kinds of buildings. BibRef

Aguilar, M.A., Vicente, R., Aguilar, F.J., Fernández, A., Saldaña, M.M.,
Optimizing Object-based Classification In Urban Environments Using Very High Resolution Geoeye-1 Imagery,
AnnalsPRS(I-7), No. 2012, pp. 99-104.
DOI Link 1209

Justus, F.[Faith], Yu, D.[Danlin],
Spatial Distribution of Greenhouse Commercial Horticulture in Kenya and the Role of Demographic, Infrastructure and Topo-Edaphic Factors,
IJGI(3), No. 1, 2014, pp. 274-296.
DOI Link 1404

Aguilar, M.A., Aguilar, F.J., Lorca, A.G.[A. García], Guirado, E., Betlej, M., Cichon, P., Nemmaoui, A., Vallario, A., Parente, C.,
Assessment Of Multiresolution Segmentation For Extracting Greenhouses From Worldview-2 Imagery,
ISPRS16(B7: 145-152).
DOI Link 1610

Yang, D.[Dedi], Chen, J.[Jin], Zhou, Y.[Yuan], Chen, X.[Xiang], Chen, X.H.[Xue-Hong], Cao, X.[Xin],
Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index,
PandRS(128), No. 1, 2017, pp. 47-60.
Elsevier DOI 1706
Medium, spatial, resolution, data BibRef

Shi, T.Y.[Tian-Yang], Xu, Q.Z.[Qi-Zhi], Zou, Z.X.[Zheng-Xia], Shi, Z.W.[Zhen-Wei],
Automatic Raft Labeling for Remote Sensing Images via Dual-Scale Homogeneous Convolutional Neural Network,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
Aquatic farming. (Not really greenhouses.) BibRef

Yao, Y.[Yao], Wang, S.X.[Shi-Xin],
Evaluating the Effects of Image Texture Analysis on Plastic Greenhouse Segments via Recognition of the OSI-USI-ETA-CEI Pattern,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902

Xiong, Y.K.[Yuan-Kang], Zhang, Q.L.[Qing-Ling], Chen, X.[Xi], Bao, A.[Anming], Zhang, J.Y.[Jie-Yun], Wang, Y.J.[Yu-Juan],
Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link 1909

Yang, Q.C.[Qin-Chen], Liu, M.[Man], Zhang, Z.T.[Zhi-Tao], Yang, S.Q.[Shu-Qin], Ning, J.F.[Ji-Feng], Han, W.T.[Wen-Ting],
Mapping Plastic Mulched Farmland for High Resolution Images of Unmanned Aerial Vehicle Using Deep Semantic Segmentation,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909

Liu, C.A.[Chang-An], Chen, Z.X.[Zhong-Xin], Wang, D.[Di], Li, D.D.[Dan-Dan],
Assessment of the X- and C-Band Polarimetric SAR Data for Plastic-Mulched Farmland Classification,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903

Ou, C.[Cong], Yang, J.Y.[Jian-Yu], Du, Z.R.[Zhen-Rong], Liu, Y.M.[Yi-Ming], Feng, Q.L.[Quan-Long], Zhu, D.[Dehai],
Long-Term Mapping of a Greenhouse in a Typical Protected Agricultural Region Using Landsat Imagery and the Google Earth Engine,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001

Wong, L.[Leslie], Vien, B.S.[Benjamin Steven], Ma, Y.[Yue], Kuen, T.[Thomas], Courtney, F.[Frank], Kodikara, J.[Jayantha], Chiu, W.K.[Wing Kong],
Remote Monitoring of Floating Covers Using UAV Photogrammetry,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
covered anaerobic lagoons (CAL) at wastewater treatment plants. BibRef

Jakovljevic, G.[Gordana], Govedarica, M.[Miro], Alvarez-Taboada, F.[Flor],
A Deep Learning Model for Automatic Plastic Mapping Using Unmanned Aerial Vehicle (UAV) Data,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005

Aguilar, M.Á.[Manuel Ángel], Jiménez-Lao, R.[Rafael], Nemmaoui, A.[Abderrahim], Aguilar, F.J.[Fernando José], Koc-San, D.[Dilek], Tarantino, E.[Eufemia], Chourak, M.[Mimoun],
Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006

Jiménez-Lao, R.[Rafael], Aguilar, F.J.[Fernando J.], Nemmaoui, A.[Abderrahim], Aguilar, M.A.[Manuel A.],
Remote Sensing of Agricultural Greenhouses and Plastic-Mulched Farmland: An Analysis of Worldwide Research,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008

Feng, Z.Y.[Zi-Yi], Huang, G.H.[Guan-Hua], Chi, D.C.[Dao-Cai],
Classification of the Complex Agricultural Planting Structure with a Semi-Supervised Extreme Learning Machine Framework,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011

Lin, J.H.[Jin-Huang], Jin, X.O.[Xia-Obin], Ren, J.[Jie], Liu, J.P.[Jing-Ping], Liang, X.Y.[Xin-Yuan], Zhou, Y.K.[Yin-Kang],
Rapid Mapping of Large-Scale Greenhouse Based on Integrated Learning Algorithm and Google Earth Engine,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104

Aguilar, M.A.[Manuel A.], Jiménez-Lao, R.[Rafael], Aguilar, F.J.[Fernando J.],
Evaluation of Object-Based Greenhouse Mapping Using WorldView-3 VNIR and SWIR Data: A Case Study from Almería (Spain),
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106

Sun, H.R.[Hao-Ran], Wang, L.[Lei], Lin, R.[Rencai], Zhang, Z.[Zhen], Zhang, B.Z.[Bao-Zhong],
Mapping Plastic Greenhouses with Two-Temporal Sentinel-2 Images and 1D-CNN Deep Learning,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107

Ma, A.L.[Ai-Long], Chen, D.Y.[Ding-Yuan], Zhong, Y.F.[Yan-Fei], Zheng, Z.[Zhuo], Zhang, L.P.[Liang-Pei],
National-scale greenhouse mapping for high spatial resolution remote sensing imagery using a dense object dual-task deep learning framework: A case study of China,
PandRS(181), 2021, pp. 279-294.
Elsevier DOI 2110
Deep learning, Greenhouse mapping, Object extraction, Semantic segmentation, Dense objects BibRef

Zhang, X.P.[Xiao-Ping], Cheng, B.[Bo], Chen, J.F.[Jin-Fen], Liang, C.B.[Chen-Bin],
High-Resolution Boundary Refined Convolutional Neural Network for Automatic Agricultural Greenhouses Extraction from GaoFen-2 Satellite Imageries,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112

Ibrahim, E.[Elsy], Gobin, A.[Anne],
Sentinel-2 Recognition of Uncovered and Plastic Covered Agricultural Soil,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112

Ou, C.[Cong], Yang, J.Y.[Jian-Yu], Du, Z.R.[Zhen-Rong], Zhang, T.T.[Ting-Ting], Niu, B.[Bowen], Feng, Q.L.[Quan-Long], Liu, Y.M.[Yi-Ming], Zhu, D.[Dehai],
Landsat-Derived Annual Maps of Agricultural Greenhouse in Shandong Province, China from 1989 to 2018,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112

Liu, A.[Anhua], Xu, D.[Demin], Henke, M.[Michael], Zhang, Y.[Yue], Li, Y.M.[Yi-Ming], Liu, X.[Xingan], Li, T.[Tianlai],
Determination of the Optimal Orientation of Chinese Solar Greenhouses Using 3D Light Environment Simulations,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202

Cao, Y.[Yinxia], Huang, X.[Xin],
A coarse-to-fine weakly supervised learning method for green plastic cover segmentation using high-resolution remote sensing images,
PandRS(188), 2022, pp. 157-176.
Elsevier DOI 2205
Weakly supervised learning, Green plastic cover segmentation, Image-level label, High-resolution remote sensing BibRef

Helman, D.[David], Yungstein, Y.[Yehuda], Mulero, G.[Gabriel], Michael, Y.[Yaron],
High-Throughput Remote Sensing of Vertical Green Living Walls (VGWs) in Workplaces,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208

Fu, C.H.[Chen-Hao], Cheng, L.[Lei], Qin, S.[Shujing], Tariq, A.[Aqil], Liu, P.[Pan], Zou, K.[Kaijie], Chang, L.W.[Li-Wei],
Timely Plastic-Mulched Cropland Extraction Method from Complex Mixed Surfaces in Arid Regions,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208

Feng, J.N.[Jun-Ning], Wang, D.L.[Dong-Liang], Yang, F.[Fan], Huang, J.[Jing], Wang, M.H.[Ming-Hao], Tao, M.F.[Meng-Fan], Chen, W.[Wei],
PODD: A Dual-Task Detection for Greenhouse Extraction Based on Deep Learning,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210

Chen, Z.C.[Zheng-Chao], Wu, Z.M.[Zhao-Ming], Gao, J.X.[Ji-Xi], Cai, M.Y.[Ming-Yong], Yang, X.[Xuan], Chen, P.[Pan], Li, Q.[Qingting],
A Convolutional Neural Network for Large-Scale Greenhouse Extraction from Satellite Images Considering Spatial Features,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210

Zhang, T.[Tao], Tang, B.H.[Bo-Hui], Huang, L.[Liang], Chen, G.[Guokun],
Rice and Greenhouse Identification in Plateau Areas Incorporating Sentinel-1/2 Optical and Radar Remote Sensing Data from Google Earth Engine,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212

Yao, Y.[Yao], Wang, S.X.[Shi-Xin],
Effects of Atmospheric Correction and Image Enhancement on Effective Plastic Greenhouse Segments Based on a Semi-Automatic Extraction Method,
IJGI(11), No. 12, 2022, pp. xx-yy.
DOI Link 2301

Senel, G.[Gizem], Aguilar, M.A.[Manuel A.], Aguilar, F.J.[Fernando J.], Nemmaoui, A.[Abderrahim], Goksel, C.[Cigdem],
Unraveling Segmentation Quality of Remotely Sensed Images on Plastic-Covered Greenhouses: A Rigorous Experimental Analysis from Supervised Evaluation Metrics,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301

Chen, D.Y.[Ding-Yuan], Ma, A.[Ailong], Zheng, Z.[Zhuo], Zhong, Y.F.[Yan-Fei],
Large-scale agricultural greenhouse extraction for remote sensing imagery based on layout attention network: A case study of China,
PandRS(200), 2023, pp. 73-88.
Elsevier DOI 2306
Precision agriculture, Large-scale greenhouse extraction, Layout attention, Sparse background, Dense foreground, Remote sensing imagery BibRef

Li, J.[Jie], Wang, H.[Hui], Wang, J.L.[Jin-Liang], Zhang, J.P.[Jian-Peng], Lan, Y.C.[Yong-Cui], Deng, Y.C.[Yun-Cheng],
Combining Multi-Source Data and Feature Optimization for Plastic-Covered Greenhouse Extraction and Mapping Using the Google Earth Engine: A Case in Central Yunnan Province, China,
RS(15), No. 13, 2023, pp. 3287.
DOI Link 2307

Mo, Y.[Yan], Zhou, W.T.[Wan-Ting], Chen, W.[Wei],
Extracting Plastic Greenhouses from Remote Sensing Images with a Novel U-FDS Net,
RS(15), No. 24, 2023, pp. 5736.
DOI Link 2401

Yildirima, M.Z., Ozcan, C.,
Extraction of Greenhouse Areas with Image Processing Methods in Karabuk Province,
DOI Link 1805

Demir, N., Eryilmaz, Y.E., Oy, S.,
Post-hurricane Damage Assessment On Greenhouse Fields With Use Of Sar Data,
DOI Link 1805

Coslu, M., Sonmez, N.K., Koc-San, D.,
Object-based Greenhouse Classification From High Resolution Satellite Imagery: A Case Study Antalya-turkey,
ISPRS16(B7: 183-187).
DOI Link 1610

Koc-San, D., Sonmez, N.K.,
Plastic And Glass Greenhouses Detection And Delineation From Worldview-2 Satellite Imagery,
ISPRS16(B7: 257-262).
DOI Link 1610

Kang, J.M., Baek, S.H., Jung, K.Y.,
Analysis on the Utility of Satellite Imagery for Detection of Agricultural Facility,
DOI Link 1209
E.g. greenhouses. BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Classification for Crops, Analysis of Production, Specific Crops, Specific Plants .

Last update:May 23, 2024 at 14:31:23