Project number: 10-SPA1192-02 
Project Investigator: Dr. Naif Alajlan
Period: Jan 2012- Jun 2014

 

Team members:

• Yacoub bazi
• Haikel Hichri
• Salim Malek

Project Summary:

Palm trees cultivation continues to be the major agricultural cop of Saudi Arabia. The government considers palm trees as a national symbol and dates as critical for national food security. The availability of precise information about palm tree farms in an appropriate time interval is very relevant for a large number of socio-economic decisions. 

This research project, proposes to develop a set of remote sensing technologies for monitoring palm tree farms in Saudi Arabia. In particular, it aims at proposing innovative methods to address four issues of major interest to palm farmers. These are: 1) palm tree counting; 2) palm crop forecasting; 3) change detection; and 4) multitemporal classification for updating land-cover maps. 

To support the goals of the NPST program in the strategic technology are of space and aeronautics, this project aims at reaching the following targets: 
1) Contributing in the increase of exploitation of remote sensing data in agricultural and crop management applications of potential interest to local private and public agricultural institutions; and 
2) Contributing in the evolvement of remote sensing research area in Saudi Arabia. 

This project is important for the field of palm tree cultivation in Saudi Arabia and other countries, because:

 

1.      It Offers great opportunities to the modernization of the procedures of farming palm trees in Saudi Arabia. The findings could be extended to monitor other important agricultural products, such as mango, olive trees, and others.

2.      It improves the effectiveness of the incentive programs provided by the government to support and manage the huge number of palm trees in the kingdom (approximately 23 million).

3.      It improves the quality of dates and date products.

4.      It promotes the remote sensing area at both academic and research levels, and contribute to its beneficial use in the economy of the country.

5.      It consolidate Saudi academic and research know-how on the rapidly evolving area of remote sensing and precision farming.

Project progress:
 

 

 

Objectives	Phases	Tasks	Status (Completed, Ongoing, Planned, Modified *, Discontinued*)	Percentage of achievement
O1: Tree counting and O2: Palm crop forecasting and O3: Change detection O4: Multitemporal classification for updating land-cover maps	1	T 1.1 Site identification and RS data purchasing	Completed	100%
		T 1.2 Data preparation	Completed	100%
		T 1.3 Update of the literature	Completed	100%
		T 1.4. System structure of PalmWatch	Completed	100%
		T 1.5 Method and algorithm Design	Completed	100%
		T 1.6 Technical and coordination meeting	Completed	100%
		T 1.7 Progress report writing	Completed	100%
O1: Tree counting and O3: Change detection	2	T 2.1 Software implementation	Completed	100%
		T 2.2 Experimental validation	Completed	100%
		T 2.3 Results dissemination	Completed	100%
		T 2.4 Technical and coordinating meeting	Completed	100%
		T 2.5 Progress report writing	Completed	100%
O2: Palm crop forecasting and O4: multitemporal classification for updating land-cover maps	3	T 3.1 Software implementation	Completed	100%
		T 3.2 Experimental validation	Completed	100%
		T 3.3 Technical and coordinating meeting	Completed	100%
		T 3.4 Progress report writing	Completed	100%
O2: Palm crop forecasting and O4: multitemporal classification for updating land-cover maps	4	T 4.1 Results dissemination	Completed	100%
		T 4.2 Software and system architecture refinement	Completed	100%
		T 4.3 Technical and coordinating meeting	Completed	100%
		T 4.4 Final report writing	Completed	100%

 

 

 

 

Where the phases are as outlined in the original proposal are as follows:

 

PHASE I: Methodological development and RS data purchasing

Task 1.1 Methodological development

Task 1.2 RS data purchasing

Task 1.3 Progress report writing

PHASE 2: Implementation (tree counting and change detection)

Task 2.1 Software implementation

Task 2.2 Experimental validation

Task 2.3 Results dissemination

Task 2.4 Technical and coordinating meeting

Task 2.5 Progress report writing

PHASE 3: Implementation (forecasting and multitemporal classification)

Task 3.1: Software implementation

Task 3.2: Experimental validation

Task 3.3: Technical and coordinating meeting

Task 3.4: Progress report writing

PHASE 4: RS system refinement

Task 4.1 Results dissemination

Task 4.2 Software and system architecture refinement

Task 4.3 Technical and coordinating meeting

Task 4.4 Final report writing

 

Project contributions to knowledge:

 

The contributions of the project can summarized as follows:

 

1.     The project proved the feasibility of a system for palm tree counting and monitoring using satellite images or UAV images.

2.     Developed successfully new system for the remote monitoring of palm tree farms, which includes :

·       Palm tree counting module which provides a web based GUI, which enables interested public and private parties to use this service. Through the web portal they can get more information about the research findings of this project and request the service of palm tree counting from us. The website can be accessed at http://www.alisr.com/projects/palm_watch

·       Palm forecasting module: to predict the date palm production in a palm field

·       Change detection module to detect changes in palm field between two acquisition dates  due to incorrect farming or due to switching to another crop.

·       Multitemporal classification module for classifying images acquired at different times and different fields into palm and no-palm classes.

 

3.     Published three (3) papers in top ISI remote sensing journals, and five (5) papers in international conferences.

4.     Developed a method for general estimation problems based on Gaussian process regression. This method is also suitable for date palm crop estimation. The results has been published in IEEE Transactions on Geoscience and remote sensing, 2012 (IF: 3.47)   

5.     Developed a method for interactive change detection in VHR images (published in IEEE Geoscience and remote sensing letters, 2014 (IF: 1.82)).

6.     Developed two methods for counting palm trees in VHR and UAV images, respectively. The second method related to UAV has been accepted recently for publication in the IEEE journal  of selected topics in applied earth observation and remote sensing (IF: 2.87). These two methods are also suitable for the Multitemporal classification module.

7.     Published a summary about the project at the college of computer and information sciences newsletter (which was distributed by hardcopy and by email) to inform students and faculty at the college about the project. This has helped attract four (4) undergrad students who ended up performing two (2) undergraduate projects in the topic of the research project besides an M.Sc student.

8.     We have invited Dr. Farid Melgani, the consultant, to give a seminar at King Saud University about the latest advanced in remote sensing and its applications. This helped attract several graduate students who are interested to do their graduate studies in remote sensing.

9.     Organized a workshop for result dissemination, and getting feedback from the community.

 

Project outcomes:

Algorithms and software packages:

1) RS Palm tree farm database collection
2) Estimation algorithm for crop forecasting
3) Change detection module
4) Palm tree counting Web portal  


Journal publications:
 

1.      Malek, Y. Bazi, N. Alajlan, H. Hichri, and F. Melgani, “Efficient framework for palm tree detection in UAV images”, IEEE Journal selected topics in applied earth observation and remote sensing (JSTARS) (IF: 2.87).  (accepted), 2014.    

            Click here to view paper in PDF

 

2.      Haikel AlHichri, Yakoub Bazi, Naif Alajlan, and Salim Malek, "Interactive segmentation for change detection in multispectral remote-sensing images," IEEE Geoscience Remote Sensing Letters, vol. 10, no. 2, pp. 298-302, March 2013. (IF: 1.56).  

Link:  http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6244846&contentType=Journals+%26+Magazines&sortType%3Ddesc_p_Publication_Year%26searchField%3DSearch_All%26queryText%3DAlajlan

 

3.      Yakoub Bazi, Naif Alajlan, and Farid Melgani, "Improved estimation of water chlorophyll concentration with semisupervised Gaussian process regression," IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 7, pp. 2733-2743, July 2012. (IF: 3.47)

Link:

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6122062&contentType=Journals+%26+Magazines&sortType%3Ddesc_p_Publication_Year%26searchField%3DSearch_All%26queryText%3DAlajlan

        4.     H. Hichri,  Y. Bazi,  N. Alajlan,  N. Ammour,  and S. Malek, , Clustering of Hypersectral images with an ensemble method based on fuzzy c-means and Markov random fields, Arab Journal of Science and Engineering, vol. 39, no. 9, P 3747-3757, May 2014 (ISSN 1319-8025). 

http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=2&SID=Q2d98m7TzLmalBAqLfW&page=1&doc=2

 

Conference Publications:

5.      H. Hichri “SIFT-ELM Approach for unsupervised change detection in VHR images," IEEE- IGARSS-2014, Quebec city, Canada, July 2014.

 

http://www.igarss2014.org/Papers/PublicSessionIndex3.asp?Sessionid=1267

 

6.      S. Malek, Y. Bazi, N. Ajlan, H. Hichri, “An automatic Approach for palm tree counting in UAV images," IEEE- IGARSS-2014, Quebec city, Canada, , July 2014.

 

               http://www.igarss2014.org/Papers/viewpapers.asp?papernum=3813

 

7.      Alajlan, Naif, "Classification of VHR Images Based on SVM and Multiobjective Evolutionary Optimization," Computational Science and Computational Intelligence (CSCI), 2014 International Conference on , vol.1, no., pp.194,198, 10-13 March 2014

8.      Naif Alajlan, Yakoub Bazi, Haikel Hichri, and Essam Othman, "Robust classification of hyperspectral images based on the combination of supervised and unsupervised learning paradigm," Proc. of the IEEE International Geoscience and Remote Sensing Symposium IGARSS-2012, pp. 1417-1420, Munich, Germany, July 2012.

Link:

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6351270&contentType=Conference+Publications&sortType%3Ddesc_p_Publication_Year%26searchField%3DSearch_All%26queryText%3DAlajlan

 

9.      Haikel Hichri, Yakoub Bazi, Naif Alajlan, and Sayed M. Ahmad, "Interactive change detection techniques in multitemporal multispectral remote-sensing images," Proc. of the IEEE International Geoscience and Remote Sensing Symposium IGASS-2012, pp. 6173-6176, Munich, Germany, July 2012.

Link:

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6352666&contentType=Conference+Publications&sortType%3Ddesc_p_Publication_Year%26searchField%3DSearch_All%26queryText%3DAlajlan

 

 Awards:

 

1) Silver medal in

The Malaysia tech Invention Expo (www.mte.com.my)

Mar 2012

Contact Us

For information about the project, contact:

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