• Tidak ada hasil yang ditemukan

DAFTAR PUSTAKA. Arsyad, S., 1989, Konservasi Tanah dan Air. Penerbit IPB Press, Dargama, Bogor

N/A
N/A
Protected

Academic year: 2022

Membagikan "DAFTAR PUSTAKA. Arsyad, S., 1989, Konservasi Tanah dan Air. Penerbit IPB Press, Dargama, Bogor"

Copied!
11
0
0

Teks penuh

(1)

234 DAFTAR PUSTAKA

Abuelgasim, A.A., Ross,W.D., Gopal, S., Woodcock,C.E., 1999, Change Detection Using Adaptive Fuzzy Neural Networks: Environmental Damage Assesment After the Gulf War. Remote Sensing of Enviroment 70, 208 – 223

Alexakis, D.D., Hadjimitsis,D.G., Agapiou., 2013, Integrated Use of Remote Sensing,GIS and Precipitation Data for The Assesment of Soil Erosion Rate In the Catchment Area of "Yialias" in Cyprus. Atmospheric Research (131):

108-124.

Ambar, S., 1986, Aspek Vegetasi dan Tataguna Lahan dalam Proses Erosi di Daerah Tampung Waduk Jatiluhur, Jawa Barat. Disertasi Matematika dan Ilmu Pengetahuan Alam, UNPAD, Bandung.

Amore, E., Modica, C., Nearing, M.A., Santoro, V.C., 2004, Scale Effect in USLE and WEPP Application for Soil Erosion Computation from Three Sicilian Basins. J.Hydrology (293):100-114

Ardizzone, F., Cardinali, M., Carrara, A., Guzzeti, F., Reichenbach, P., 2001, .Impact of Mapping Errors on The Reliability of Landslide Hazard Map. Natural Hazard and Earth System Science 2, 3 – 14

Arif, N., 2011. Kajian Jaringan Saraf Tiruan dalam Klasifikasi Lahan Kritis Berbasis Citra Alos, Tesis, Fakultas Geografi Universits Gadjah Mada,Yogyakarta

Aronoff, S., 1989. Geographic Information Systems: A Management Perspective, WDL Publication, Ottawa, Canada

Arsyad, S., 1989, Konservasi Tanah dan Air. Penerbit IPB Press, Dargama, Bogor Asdak, C., 2010, Hidrologi dan Pengelolaan Daerah Aliran Sungai. Gadjah Mada

University Press

Asis, A., Omasa, K., 2007, Estimation of Vegetation Parameter for Modeling Soil Erosion Using Linear Spectral Mixture Analysis of Landsat ETM Data.

ISPRS Journal of Photogrametry & Remote Sensing 62, pp.309-324.

Assouline, S., Ben-Hur, M., 2006, Effect of Rainfall Intensity and Slope Gradient on The Dynamics of Interill Erosion During Soil Surface Sealing”. Catena 66 : 211 – 220.

(2)

235 Atkinson, P.M., Tatnall, A.R.L., 1997, Neural Networks in Remote Sensing.

International Journal of Remote Sensing, 18(4), pp. 699-709

Bandyopadya., Pal., 2007, Classification and Learning Using Genetic Algorithms Applications in Bioinformatics and Web Intelligence, Springer,Newyork.

Banuwa, I. S., 2013, Erosi, Kencana Prenada Media Group, Jakarta

Bergsma, E., 2008, Erosion by Rain: Its Subprocesses and Diagnostic Micro- topographic Features. International Institute for Geo-Information Science and Earth Observation (ITC), Enschede. The Netherlands.

Bredeweg, B., Linnebank, F., Bouwer, A., Liem, J, 2009, Garph3-Workbench for Qualitative Modelling and Simulation. Ecological Informatics (4): 263–281.

Bosco, C., de Rigo, D., Dewitte, O., 2014, Visual Validation of the e-RUSLE Model Applied at The Pan-European Scale. Scientific Topics Focus 1,MRI- 11a13,Maieutika Research Initiative. DOI:10.6084/m9.figshare.844627.

Bouaziz, M., Leidig, M., Gloaguen, R., 2011, Optimal Parameter Selection for Qualitative Regional Erosion Risk Monitoring:A Remote Sensing Study of SE Ethiopia. Geoscience Frontiers 2(2):237-245

Chen, Y.R., Chen, J.W, Hsieh, S.C., Ni, P.N., 2013, The Application of Remote Sensing Technology to The Interpretation of LU for Rainfall – Induced Landslide Based on Genetic Algorithm and Artificial Neural Network, IEEE Earth Observations and remote Sensing, Vol.2 (2): 87 – 95

Chen, T., Niu, R., Li, P., Zhang, L., Du, B., 2010, Regional Soil Erosion Risk Mapping Using RUSLE,GIS and Remote Sensing: A Case Study in Miyun Watershed, North China. J. Environ Earth Sci. DOI: 10.1007/s12665-010- 0715-z

Clark, R, 1980, Erosion Condition Classification System. Bureau of Land Management Library, U.S Department of Interior, Denver, Colorado

Conforti, M., Pascale, S., Robustelli, G., Sdao, F., 2014. Evaluation of Prediction Capability of The Artificial Neural Networks for Mapping Landslide Susceptibility in the Turbolo River Catchment (northern Calabria, Italy).

Catena 113, pp. 236-250.

Congalton, R, G., Green, K., 2009, Assessing the Accuracy of Remotely Sensed Data:Principles and Practices. CRC Press

(3)

236 Conoscenti, C., Angileri S., Cappadonia, C., Rotigliano, E., Agnesi, V., Marker, M., 2014, Gully Erosion Susceptibility Assessment by Means og GIS-based Logistic Regression: A Case of Sicily (Italy), Geomorphology 204: 399 - 411 Dabral, P.P., Baituhuri, N., Pandey, A., 2008, Soil Erosion Assessment in A Hilly Catchment of North Eastern India Using USLE,GIS and Remote Sensing.Water Resource Manage 22:1783-1798

Danoedoro, P., 2012, Pengantar Penginderaan Jauh Digital. Andi.Yogyakarta De Jang, S.M. 1994. Application of Reflective Remote Sensing for Land Degradation

Studies in A Mediterranean Enviroment. Utrecht: Netherlands Geographical Studies, University of Uttrecht

De la Rosa, D., de la Mayol, F., Lozano, S., 1999. An Expert System/Neural Network Model (impelERO) for Evaluating Agricultural Soil Erosion in Andalucia Region, Southern Spain. Agriculture, Ecosystem and Environment 73:211- 226.

De la Rosa, D., Diepen, C.A., 2002. Qualitative and Quantitative Land Evaluation, in 1.5. Land Use and Land Cover, in Encyclopedia of Life Support System (EOLSS-UNESCO), Eolss Publishers. Oxford, UK. [http://www.eolss.net]

Departemen Kehutanan., 1998, Pedoman Penyusunan Rencana Teknik Lapangan Rehabilitasi Lahan dan Konservasi Tanah Daerah Aliran Sungai. Direktorat jenderal Reboisasi dan Rehabilitasi Lahan, Jakarta

Devatha, C. P., Deshpande, V., Renukaprasad, M.S., 2015, Estimation of Soil Loss Using USLE Model for Kulhan Watershed, Chattisgarh-A Case Study.

J.Aquatic Procedia:1429-1436

Dibyosaputro, S., 1992, Longsorlahan di Daerah Kecamatan Kokap Kabupaten Kulonprogo Daerah Istimewa Yogyakarta. Laporan Penelitian, Fakultas Geografi UGM. Yogyakarta

Dibyosaputro, S., 2012, Pola Persebaran Keruangan Erosi Permukaan Sebagai Respon Lahan terhadap Hujan di Daerah Aliran Sungai Secang, Kabupaten Kulonprogo, Daerah Istimewa Yogyakarta, Disertasi Fakultas Geografi UGM, Yogyakarta

Erencin, Z. 2000. C-Factor Mapping Using RS and GIS, A Case Study of Lom Sak/Lom Kao, Thailand, Geographisches Institut der Justus-Liebig- Universitat Giessen

(4)

237 Eweg, H.PA, Van Lammeren, R., Deurloo, H., Woldai, Z., 1998, Analysing Degradation and Rehabilitation for Sustainable Land Management in The Highlands of Ethiopia, Land Degradation & Development, Vol.9

Farhan, Y.,Zregat, D., Farhan, I., 2013, Spatial Estimation of Soil Erosion Risk using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan, Journal of Water Resource and Protection (5):

1247 - 1261

Farrokhzad, F., Barrari, Choobbasti, A.J., Ibsen, L.B., 2011, Neural Network-Based Model For Landslide Susceptibility and Soil Longitudinal Profile Analyses:Two Case Studies.Journal of African Earth Science, 61 (2011) 349- 357.

Fathillah, S.S., 2012, Penilaian Tingkat Bahaya Erosi, Sedimentasi, dan Kemampuan Serta Kesesuaian Lahan Kelapa Sawit Untuk Penatagunaan Lahan DAS Tenggarong, Kabupaten Kutai Kartanegara. Disertasi Fakultas Kehutanan, UGM Yogyakarta

Fausett, L., 1994, Fundamentals Of Neural Networks Architectures, Algorithms, and Applications, Prentice-Hall, New Jersey

Fisher, P., Arnot, C., Wadsworth, R., Wellens, J., 2006. Detecting Change in Vague Interpretations of Landscapes. Ecological Informatics 1, 163 - 178

Foster, G.R., 1996, Process-based Modelling of Soil Erosion By Water on Agricultural Land, In: J.Boardman, I.D.L.Foster and Dearing (Editors) Soil Erosion on Agricultural Land. Willey, Chichester, pp. 429 - 445

Glade, T., Anderson, M., Crozier, M.J., 2006, Landslide Hazard and Risk. John Willy

& Sons, Sussex

Gonzalez, A.M.R., 2008, Soil Erosion Calculation Using Remote Sensing and GIS in Rio Grande de Arecibo Watershed, Puerto Rico, ASPRS Annual Conference Gunadi, S., Sartohadi, J., Hadmoko, D.S., Hardiatmo, H.C., Giyarsih, S.R., 2004,

Tingkat Bahaya Longsor di Kecamatan Samigaluh dan daerah Sekitarnya, Kabupaten Kulonprogo, Propinsi daerah Istimewa Yogyakarta.Tim Peneliti Pusat Studi Bencana (PSBA) Universitas Gadjah Mada,Yogyakarta.

Gutman, G., Ignatov, A., 1998, The Derivation of The Green Vegetation Fraction from NOAA/AVHRR Data for Use in Numerical Weather Prediction Models.

International Journal of Remote Sensing 19 (8),1533-1543

Gupta, R.P., Kanungo, D.P., Arora, M.K., Sarkar, S., 2008, Approaches for Comparative Evaluation of Raster GIS-Based Landslide Susceptibility

(5)

238 Zonation Maps. International Journal of Applied Earth Observation and Geoinformation 10:330-341

Hall, O., Hay, G.J., 2003, A Multiscale Object-Spesific Approach to Digital Change Detection.International Journal of Applied Earth Observation and Geoinformation 4, 311 – 327.

Hardjowigeno, S., Widiatmaka., 2007, Evaluasi Kesesuaian Lahan & Perencanaan Tataguna Lahan, Gadjah Mada University Press

Haupt R, L and Haupt, S.E., 2004, Practical Genetic Algorithms (second edition.

Pearson Education, Canada

Heuvelink, G.B.M., 1993, .Error Propagation in Quantitative Spatial Modelling:

Application in Geographical Information Systems, Gedrukt door Drukkerij Elinkwijk, Utrecht, 151 pp.

Horton, R.E.,1945, Erosional Development of Streams and Their Drainage Basins:

Hydrological Approach to Quantitative Morphology. Geol.Soc.Bull. 56:275- 243

Im, J., Jensen, J.R., 2005, A Change Detection Model Based on Neighborhood Correlation Image Analysis and Decission Tree Classification. Remote Sensing of Enviroment 99, 326 – 340.

Jabro, J.D., Stevens, W.B., Iversen, W.M., Evans R.G., 2010. Tillage Depth Effects on Soil Physical Properties, Sugarbeet Yield, and Sugarbeet Quality.

Communications in Soil Science and Plant Analysis, 41:908 – 916

Jain, S.K., Kumar, S., Varghese, J., 2001, Estimation of Soil Erosion for a Hymalayan Watershed Using GIS Technique. Water Resour Manage 15:41-54 Jensen, J.R., 1996. Introductionary Digital Image Processing : A Remote Sensing

Perspective, London:Prentice Hall

Jorgensen, S.E., Bendorrichio, G, G., 2001, Fundamentals of Ecological Modelling, 3rd edition. Elsevier Science, Oxford

Kamaludin, H., Lihan, T., Rahman, Z.A., Mustapha, M.A., Idris, W.M.R., Rahim, S.A., 2013, Intergration of Remote Sensing, RUSLE and GIS to Model Potential Soil Loss and Sediment Yield (SY). Hydrol. Earth Syst. Sci. Discuss, 10, 4567 - 4569

Kefi, M., Yoshiro, K., Setiawan, Y., Zayani, K., Boufaroua, M., 2011, Assessment of The Effect of Vegetation on Soil Erosion Risk By Water : A Case of Study of

(6)

239 The Batta Watershed in Tunisia. Environ Earth Sci 64: 707 – 719.

Doi://10.1007/s12665-10-0891-x

Kim, H. S., 2006. Soil Erosion Modelling Using RUSLE and GIS on The IMHA Watershed, South Korea, Thesis, Colorado State University

Kim, M., Gilley, J.E., 2008. Artificial Neural Network Estimation of Soil Erosion and Nutrient Concentrations in Runoff From Land Application Areas. Comput.

Electron. Agric. doi://10.1016/j.compag.2008.05.021

Kusumadewi, S., 2003, Artificial Intelligence (Teknik dan Aplikasinya), Graha Ilmu.Yogyakarta

Kusumandari, A., 2012, Penanganan Konservasi Tanah dan Air Berbasis Unit Ekologis di Sub DAS Ngrancah, KulonProgo. Disertasi, Fakultas Kehutanan UGM, Yogyakarta.

Lakitan, B., 2002, Dasar-Dasar Klimatologi. PT. Raja Grafindo Persada. Jakarta Lee, E.M., Jones, D.K.C., 2004, Landslide Risk Assessment. Thomas Toldford,

London

Lee, S. (2004). ―Soil erosion assessment and its verification using the universal soil loss equation and geographic information system: A case study at Boun, Korea.‖ Environmental Geology, 45, 457–465

Lees, B., 1996, Sampling Strategies for Machine Learning Using GIS.Enviromental Modeling: Progress and Research Issues

Li, J., Heap A,D., 2011, A Review of Comparative Studies of Spatial Interpolation Methods in Environmental Sciences: Performance and Impact Factors.

Ecological Informatics 6:228 – 241

Liao, Z., Wang, B., Xia, X., Hannam, P.M., 2012, Enviromental Emergency Decission Support System Based on Artificial Neural Network. Safety Science 50, pp. 150-163

Lillesand, T.M., Kiefer, R.W., Chipman, J.W., 2007, Remote Sensing and Image Interpretation, Sixth Edition. John Wiley and Sons, New York

Linden, V.P., 1980, Introduction to Principles of Erosion and the Application of Some Soil Conservation Measures (Unplished Lecture Notes). Yogyakarta.

Fakultas Geografi UGM

Liu, Q., Wu, G., Chen, J., Zhou, G., 2012, Interpretation Artificial Neural Network in Remote Sensing Image Classification. IEEE

(7)

240 Malingreau, J.P. 1981. A Land Cover/Land Use Classification For Indonesia. The Indonesia Journal Geography. Vol.II. No.41. Faculty of Geography, Gadjah Mada University.

May, L., Place, C., 2005, A GIS-based Model of Soil Erosion and Transport.

Freshwater Forum 23, 48-61

Mas, J, F., 2003. Mapping Landuse/cover in Tropical Coastal Area Using Satallite Sensor Data, GIS and Artificial Neural Network. Estuarine, Coastal and Shelf Science, Vol.59, Issue 2, 219 – 230

McCool, D.K., Brown, L.C., Foster, G.R,1989. Revised Slope Length Factor for The Universal Soil Loss Equation. Transaction of ASAE 32 (5), 1571 – 1576 McCool, D.K.,Foster, G.R., Renard, K.G., Yoder, D.C., Weesie, G.A. 1995.

Department of Defense/ Interagency Workshop on Technologies to Address Soil on Department of Defense Lands. San Antanio, TX, June 11 – 15, 1995

McCoy, R.M., 2005, Field Method in Remote Sensing. New York: The Guilford Press Melchiorre, C., Matteuci, M., Azzoni, A. ,Zanchi, A., 2008, Artificial Neural Networks and Cluster Analysis in Landslide Susceptibility Zonation.

Geomorphology 94, pp. 379-400, 2008

Menteri Pertanian, 1980. Keputusan Menteri Pertanian No.837/Kpts/Um/1980 Tentang Kriteria dan Tata Cara Penetapan Hutan Lindung

Miller, O., Pikaz, A., Averbuch, A., 2005, Object Based Change Detection in A Pair of Gray-Level Images. Pattern Recognition 38, 1976 – 1992.

Morgan, R.P.C., 1995, Soil Erosion and Conservation, 2nd Edition. Longman Group, Ltd., London, 198 p.

Morgan, R. P. C., Quinton, J. N., Smith, R. E., Govers, G., Poesen, J. W. A., Auerswald, K., Chisci, G., Torri, D., Styczen, E., 1998. The European Soil Erosion Model (EUROSEM) : A Dynamic Approach For Predicting Sediment Transport From Fields and Small Catchments. Earth Surf. Process and Landforms 23. 527 – 544

Munir, R., 2002, Algoritma dan Pemrograman dalam Bahasa Pascal dan C, Informatika. Bandung

Munir, R., 2004, Pengolahan Citra Digital dengan Pendekatan Algoritmik.

Informatika Bandung.

(8)

241 Montana, D.J., Davis, L., 1989, Training Feedforward Neural Network using Genetic Algorithms, BBN Systems and Technologies Corp.10 Mouiton St.Cambridge,MA

Mulligan, M., Wainwright., 2004, Enviromental Modelling:Finding Simplicity in Complexity. John Wiley & Sons, Ltd.

Nearing, M.A., L.J.Lane., V.L.Lopes., 1994, Modelling Soil Erosion.In:Lal,R.(Ed).

Soil Erosion Methods. Soil and Water Conservation Society.Florida.p:127- 158.

Parveen, R., Kumar, U., 2012, Integrated Approach of Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) for Soil Loss Risk Assessment in Upper South Koel Basin, Kharkhand. J.Geographic Information System,4,588-596

Patil, R.J., Sharma, S.K. 2013. Remote Sensing and GIS Based Modeling of Crop/Cover Management Factor (C) of USLE in Shakker River Watershed.

International Conference on Chemical, Agricultural and Medical Sciences (CAMS-2013), Malaysia

Pradhan, B., Lee, S., 2007, Utilization of Optical Remote Sensing Data and GIS Tools for Regional Landslide Hazard Analysis Using an Artificial Neural Network Model. Earth Science Frontiers, 14 (6):143 – 152.

Pradhan, B., Lee, S., Buchroitner, M.F., 2010, A GIS-Based Backpropagation Neural Network Model And Its Cross-Application and Validation for Landslide for Susceptibility Analyses. Computers, Environment and Urban Systems 34:216-235.

Prasannakumar, V., Vijith, H., Geetha, N., 2012, Estimation of Soil Erosion Risk Within a Small Mountainous Sub-Watershedin Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and Geo-Information Technology.

Geoscience Frontiers 3(2):209-215.

Prasasti, I., Carolita, I., Ramdani, A.E., Risdiyanto, I., 2012, Kajian Pemanfaatan Data ALOS PALSAR dalam Pemetaan Kelembaban Tanah.Vol.9(2):102 – 113.

Purnomo, M.H., dan Kurniawan, A., 2006, Supervised Neural Networks, Graha Ilmu, Yogyakarta

Purnomojati, L., 2016. Evaluasi Water Yield (Hasil Air) Melalui Pemodelan Hidrologi dan Skenario PL (Kasus Di DAS Serang, Kulonprogo). Tesis Fakultas Geografi UGM. Yogyakarta

(9)

242 Purwadhi, S.H., Sanjoto, T.H., 2009, Pengantar Interpretasi Citra Penginderaan Jauh. Lembaga Penerbangan dan Antariksa Nasional dan Jurusan Geografi Universitas Negeri Semarang.

Purwadhi, S.H., 2001, Interpretasi Citra Digital, Grasindo. Jakarta

Puspitaningrum., 2006, Pengantar Jaringan Saraf Tiruan,Andi Offset, Yogyakarta Rahim, S.E., 2006, Pengendalian Erosi Tanah dalam Rangka Pelestarian

Lingkungan Hidup. Penerbit Bumi Aksara, Jakarta

Renard, K., Foster, G.R., Weesies, G.A., Porter, J.P., 1991. Revised Universal Soil Loss Equation. Journal of Soil and water Conservation, 46: 30 33.

Renard, K.G., Freimund, J.R., 1994, Using Monthly Precipitation Data to Estimate The R-Factor in The Revised USLE. J.Hydrology.157,287 – 306.

Renard, K.G., G.R. Foster, G.A. Weesies, D.K. McCool., D.C. Yoder, coordinators, 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning With The Revised Universal Soil Loss Equation (RUSLE). U.S. Department of Agriculture, Agriculture Handbook No. 703, 404 pp.

Rosqvist, T. 2003. On the use of expert judgment in the qualification of risk assessment. VTT Industrial Systems.

Saavedra, C., 2005, Estimating Spatial Patterns of Soil erosion and Deposition in the Andean Region Using Geo-Information Techniques: A Case Study in Cochabamba, Bolivia. Dissertation, ITC & Wageningen University 2005 Santoso, H.B., 2012, Arahan Penggunaan Lahan Optimal Berdasarkan Aspek

Biofisik dan Kebutuhan Minimal Lahan Pertanian untuk Pengendalian Erosi di Das Serang. Tesis, Fakultas Kehutanan UGM. Yogyakarta

Seixas, M.J., Nunes, JP., Lourenco, P., Lobo, F., Condado., 2005, Genetic Land – Modelling Landuse Change Using Evolutionary Algorithms, ERSA Conference Papers. Diakses pada http://www.ersa.org [03 Maret 2014]

Skidmore, 2002. Enviromental Modelling with GIS and Remote Sensing. Taylor &

France

Soenarmo, S.H., 2009, Penginderaan Jauh dan Pengenalan Sistem Informasi Geografis untuk Bidang Ilmu Kebumian. ITB Bandung

Song, H., Xu, R., Ma, Y., Li, G., 2013, Classification of ETM+ Remote Sensing Image Based on Hybrid Algorithm of Genetic Algorithm and Backpropagation Neural Network, Hindawi Publishing Corporation,

(10)

243

Mathematical Problems Engineering Vol. 2013.

http://dx.doi.org/10.1155/2013/719756

Sonneveld, B.G.J.S., Keyzer, M.A., Albersen, P.J., 2001, A Non Parametric Analysis of Qualitative and Quantitative Data for Erosion Modeling: A Case Study for Ethiopia. Suistaining the Global Farm, pp.979-993

Sonneveld, B.G.J.S., Keyzar, M.A., Stroosnijder, L., 2011, Evaluating Quantitative and Qualitative: An Application for Nationwide Water Erosion Assesment in Ethiopia. Enviromental Modelling &Software (26):1161-1170

Stocking, M., Murnaghan, N., 2000, Land Degradation-Guidelines For Field Assessment. Overseas Development Group, University of East Anglia, Norwich UK

Sucipto, 2007, Analisis Erosi Yang Terjadi di Lahan Karena Pengaruh Kepadatan Tanah. Wahana Teknik Sipil Vol.12 No.1 April 2007:51-60

Sudheer, K.P., Gowda, P., Chaubey, I., Howell, T., 2010, Artificial Neural Network Approach for mapping Contrasting Tillage Practices. Remote Sens, 2, 579 – 590. http://dx.doi.org/10.3390/rs2020579

Sulistyo, B., 2011, Penginderaan Jauh Digital: Terapannya dalam Pemodelan Erosi Berbasis Raster, Lokus Tiara Wacana Group

Sutanto., 1994, Penginderaan Jauh (Jilid 1). Gadjah Mada University Press.

Yogyakarta

Sutanto.,1994, Penginderaan Jauh (Jilid II). Gadjah Mada University Press.

Yogyakarta

Sutanto, R., 2005, Dasar-Dasar Ilmu Tanah: Konsep dan Kenyataan. Kanisius.

Yogyakarta

Tong, X., Zhang, X., 2007, Neural Network Classification with Optimization By Genetic 6752, Geoinformatics 2007.

Tweddales, S.C., Eschlaeger , C.R., Seybold,W.F.2000. An Improved Method for Spatial Extrapolation of Vegetative Cover Estimates (ESLE/RUSLE C Factor) using LCTA and Remotely

Thornbury, William D. 1958. Principles Of Geomorphology. Fourth edition. New York: John Wiley & Sons, Inc

Utomo, W.H., 1994, Erosi dan Konservasi Tanah. IKIP Malang

(11)

244 Van der Knijff, J.M., Jones, R.J.A., Montanarella, L. 2000. Soil Erosion Risk

Assessment in Europe, European Soil Bureau

Veregin, H., 1999. Geographic Information System - Principles and Technical Issues, Vol. 1, Data Quality Parameters, John Wiley & Sons, Chapter 12, pp. 177 - 189

Vrieling, A., Sterk G., Vigiak O., 2006. Spatial Evaluation of Soil Erosion Risk In The West Usambara Muntains, Tanzania. Land Degradation 17: 301 – 319 Widarsih, S., 2012, Pendugaan Erosi, Kemampuan dan Kekritisan Lahanuntuk

rehabilitasi Sub DAS Tinalah, DAS Progo. Tesis. Fakultas Kehutanan UGM,Yogyakarta

Wilson, D.R., Martinez, T.R. 2001. The Need for Small Learning Rate on Large Problems. In Proceedings of The International Journal Conference on Netherlands : 115 – 119.

Wischmeier, W.H., Mannering, 1969. Soil and Water Management and Conservation, Division S-6, Relation of Soil Properties to its Erodibility, Soil Sci. Soc. Am. Proc, 33 (1969), pp. 131 - 137

Wischmeier, W.H., Smith,D.D., 1978, Predicting Rainfall Erosion Losses: Aguide to Conservation Planning. USDA, Agriculture Handbook 537. U.S.

Government Printing Office,Washington,DC.

Xiong, Y., Wang, R., Zhili., 2010, Etracting LU/LC of Mountains Area From RS Images Using ANN and Decision Tree Classification, IEEE Computer Society, International Symposium Intelligence Information Processing and Trusted Computing.

Xu, L., Xu, X., Meng, X, 2012, Risk Assesment of Soil Erosion in Different Rainfall Scenarios By RUSLE Model Coupled With Information Diffusion Model: A Case Study of Bohai Rim, China. Catena (100 ) 74-82

Ypsilantis, W.G, 2011, Upland soil erosion monitoring and assessment: An overview.

Tech Note 438. Bureau of Land Management, National Operations Center, Denver, CO

Yuan, H., Wiele, C.F., Khoram, S., 2009, .An Automatad Artificial Neural Network System for Land Use/Land Cover Classification from Landsat TM Imagery, Journal International of Remote Sensing

Referensi

Dokumen terkait

Pengaruh Pemberian Kompos Blotong terhadap Efisiensi Penggunaan Air dan Serapan Hara pada Tebu Lahan Kering (Saccharum officinarum L.).. Program Studi

Respon Pertumbuhan Tanaman Desmodium heterophyllum Willdd.C Dengan Pemberian Fungi Mikoriza Arbuskular (FMA) Pada Tanah Lahan Bekas Tambang Batubara Sawahlunto..

brackishwater ponds.  Agricultural

Principles of Soil Chemistry (Dasar-dasar Kimia Tanah, alih bahasa:.. Gadjah

Analisis Bencana Untuk Pengelolaan Daerah Aliran Sungai (DAS), Studi Kasus Kawasan Hulu DAS Comal.. Gadjah Mada

Perubahan Beberapa Sifat Fisika dan Kimia Ultisol Akibat Pemberian Pupuk Kompos dan Kapur Dolomit pada Lahan Berteras.. Asmar dan

Karakteristik Biofisik Habitat Pebeluran Penyu Hijau (Chelonia mydas) dan Interaksinya dengan Populasi Penyu Hijau yang Bertelur di Pantai Pangumbahan,

Proseding Seminar dan Lokakarya Nasional Strategi Penanganan Krisis Sumberdaya Lahan untuk Mendukung Kedaulatan Pangan dan Energi pada tanggal 22-23 Desember 2008.. Dilaksanakan