Land use and land cover (LULC) change detection using multi-temporal landsat imagery: A case study in Allah Valley Landscape in Southern, Philippines

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Research Paper 01/02/2018
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Land use and land cover (LULC) change detection using multi-temporal landsat imagery: A case study in Allah Valley Landscape in Southern, Philippines

Mark Daryl C. Janiola, George R. Puno
J. Bio. Env. Sci.12( 2), 98-108, February 2018.
Certificate: JBES 2018 [Generate Certificate]

Abstract

The widely used application on remote sensing using Landsat imagery is on monitoring changes. With the progressive dynamics of land cover change in the different parts of the world and especially in the Philippines at a fast rate, satellite remote sensing is playing an important role in mapping the spatial distribution and the temporal dynamics of land cover change. Feature extraction and change detection using Landsat imagery are an effective means of collecting information on temporal changes. Monitoring the extent of changes is critical for understanding environmental and socioeconomic impacts. The primary objectives of this study are to detect the temporal dynamics of LULC change in Allah valley landscape through integrating remote sensing and GIS in extracting and analyzing the spatial distribution of land cover changes from the year 1989 to 2002 and 2002 to 2015. Allah valley is more or less 261,000ha of valley landscape located specifically in the Provinces of South Cotabato and Sultan Kudarat in Mindanao and considered as watershed forest reserve under Proclamation No. 2455 by President Ferdinand Marcos. The valley landscape supports the existence of two watersheds namely Allah and Kapingkong Watershed. The detected land cover change in Allah valley using multi-temporal Landsat imagery posed a serious trend, by which forest resources are decreasing that is driven by the continuously increasing need for agricultural land, built-up areas, and industrial plantation expansion.

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Bouzekri S, Lasbet AA, Lachehab A. 2015. A New Spectral Index for Extraction of Built-up Area Using Landsat-8 Data. Journal of Indian Society Remote Sensing 868. www.infona.pl/ resource/bwmeta1.element. springer-doi-10_1007-S12524-015-0460-6

Chemura A. 2012. Determining Oil Palm Age From High Resolution Satellite Imagery. University of Twente. Published Masters Thesis 18.

Department of Agrarian Reform (DAR). 2006. Case Study on Production and Purchase Agreement: Kenram arns multipurpose cooperative (karbempco), mapantig arbs multipurpose cooperative (maparbempco), and kenram industrial development, incorporated (kidi) in isulan, sultan kudarat (Oil Palm). DAR-Policy and Strategic Research Service (PSRS) 3-4.

Dingal LN. 2005. Benefit and Linkage Development in the Philippine Tropical Fruits Sector 1-30.

Dingal LN. 2007. Agricultural Contracts in Mindanao: the Case of Banana and Pineapple. Discussion Paper Series No. 2007-24, 2.

Duong TD. 2004. An analysis of changes in land use patterns of northern areas of the Da River Basin using LANDSAT image processing [Ph.D. Thesis].Seoul: Seoul National University 2.

Haque I, Basak R. 2017. Land Cover Change Detection Using GIS and Remote Sensing Techniques: A Spatio-temporal Study on Tanguar Haor, Sunamganj, Bangladesh. The Egyptian Journal of Remote Sensing and Space Sciences 4. https://doi.org/10.1016/j.ejrs.2016.12.003

Hegazy IR, Kaloop MR. 2015. Monitoring Urban Growth and Land Use Change Detection with GIS and Remote Sensing Techniques in Daqahlia Governate Egypt. Internation Journal of Sustainable Built Environment 118-120. http://dx.doi.org/10.1016/j.ijsbe.

Janiola MD, Pelayo JL, Gacad JL. 2015. Distinguishing Urban Built-up and Bare Soil Features From Landsat 8 OLI Imagery Using Different Developed Band Indices. Asian Association on Remote Sensing 2.

Jing X. 2014. Modelling and Analyzing Land Use and Land Cover Change in Metropolitan Birmingham Area Using Landsat TM, OLI Data. The University of Alabama. Published MS Thesis 6-7.

Lillesand TM, Kiefer RW. 1994. Remote Sensing and Image Interpretation 4th edition, New York, John Wiley, and Sons 2-3.

Lu D, Mausel P, Brondizio E, Moran E. 2004. Change Detection Techniques. International Journal Remote Sensing 2. https://doi.org/10.1080/01431160 31000139863

Ministry of Economy, Trade and Industry (METI). 2017. Study on Infrastructure Development in Mindanao, Philippines 1-4, 9-11.

Moog FA. 2006. Country Pasture/Forage Resource Profiles: Philippines. Food and Agriculture Organization of the United Nations (FAO) 8-14.

Pohl C. 2012. Mapping Palm Oil Expansion Using SAR to Study The Impact on CO2 Cycle. International Remote Sensing and GIS Conference and Exhibition 5. http://iopscience.iop.org/DOI:10.1088/1755-1315/20/1/012012

Pohl C. 2014. Mapping Palm Oil Expansion Using SAR to Study the impact on the CO2 cycle. 7th IGRSM International Remote Sensing and GIS Conference and Exhibition. IOP Publishing 1-2.

Pol RC, Marvine B. 1996. Change detection in forest ecosystems with remote sensing digital imagery. Remote Sensing Reviews 207-234.

Proclamation No. 2455, S. 1985. Establishing as Watershed Forest Reservation for the Purpose of Protecting, Maintaining, or Improving its Water Yield and Providing A Restraining Mechanism for Inappropriate Forest Exploitation and Land-Use, A Parcel of Land In The Provinces of Sultan Kudarat and South Cotabato, Island of Mindanao, Philippines. Official Gazette Republic of the Philippines.

Rawat JS, Kumar M. 2015. Monitoring Land Use/Cover Change Using Remote Sensing and GIS Techniques: A case study of Hawalbagh block, District Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science 3. https://doi.org/ 10.1016/j.ejrs.2015.02.002

Regional Development Council XII (RDC XII). 2011. Soccsksargen Regional Development Plan 2011-2016: Establishing Its Role as the Sustainable Food Center of the South. National Economic and Development Authority Regional Office No. XII, 10-15.

Sader SA, Hayes DJ, Hepinstall JA, Coan M, Soza C. 2001. Forest change monitoring of remote biosphere reserve. International Journal of Remote Sensing 22(10), 1937-1950.

Shalaby A, Gad A. 2010. Urban Sprawl Impact Assessment on the Fertile Agricultural Land of Egypt Using Remote Sensing and Digital Soil Database, Case Study: Qalubiya Governate. National Authority for Remote Sensing and Space Sciences. Egypt 1-3. https://doi.org/10.1080/1747423X.2011.562928

Shodimu OO. 2016. Spatial Analysis of Land Cover Changes in the Grand Lake Meadows, New Brunswick. The University of New Brunswick. Published MS Thesis 2016, 1-20.

Song XP, Huang C, Sexton JO, Channan S, Townshend JR. 2014. Annual Detection of Forest Cover Loss Using Time Series Satellite Measurement of Percent Tree Cover. Remote Sensing 5. https://doi.org/10.3390/rs6098878

Tiongco MM, Espaldon MVO, Guzman LEde, Ancog RC, Quiray AE, Jaffee S, Frias J. 2015. Green Agriculture in the Philippines: An Old Wine in a New Bottle 6-11.

Torbick N, Ledoux L, Salas W, Zhao M. 2016. Regional Mapping of Plantation Extent Using Multisensor Imagery. Journal of Remote Sensing 1-2. https://doi.org/10.3390/rs8030236

Townshend JR, Justice CO. 1988. Selecting the Spatial Resolution of satellite Sensors Required for Global Monitoring of Land Transformations. International Journal of Remote Sensing 187-236.