Chapter Contents (Back)
> Deforestation. More general changes: See also Forest Change Evaluation, Change Detection, Temporal Analysis.

Lee, H.,
Mapping Deforestation and Age of Evergreen Trees by Applying a Binary Coding Method to Time-Series Landsat November Images,
GeoRS(46), No. 11, November 2008, pp. 3926-3936.

Arai, E., Shimabukuro, Y., Pereira, G., Vijaykumar, N.,
A Multi-Resolution Multi-Temporal Technique for Detecting and Mapping Deforestation in the Brazilian Amazon Rainforest,
RS(3), No. 9, September 2011, pp. 1943-1956.
DOI Link 1203

Mello, M.P., Vieira, C.A.O., Rudorff, B.F.T., Aplin, P., Santos, R.D.C., Aguiar, D.A.,
STARS: A New Method for Multitemporal Remote Sensing,
GeoRS(51), No. 4, April 2013, pp. 1897-1913.

Mello, M.P.[Marcio Pupin], Martins, F.S.R.V.[Flora S.R.V.], Sato, L.Y.[Luciane Y.], Cantinho, R.Z.[Roberta Z.], Aguiar, D.A.[Daniel A.], Rudorff, B.F.T.[Bernardo F.T.], Santos, R.D.C.[Rafael D.C.],
Spectral-Temporal Analysis by Response Surface applied to detect deforestation in the Brazilian Amazon,

Souza, Jr., C.M.[Carlos M.], Siqueira, J.V.[João V.], Sales, M.H.[Marcio H.], Fonseca, A.V.[Antônio V.], Ribeiro, J.G.[Júlia G.], Numata, I.[Izaya], Cochrane, M.A.[Mark A.], Barber, C.P.[Christopher P.], Roberts, D.A.[Dar A.], Barlow, J.[Jos],
Ten-Year Landsat Classification of Deforestation and Forest Degradation in the Brazilian Amazon,
RS(5), No. 11, 2013, pp. 5493-5513.
DOI Link 1312

Chen, F.L.[Fu-Long], Guo, H.D.[Hua-Dong], Ishwaran, N.[Natarajan], Zhou, W.[Wei], Yang, R.X.[Rui-Xia], Jing, L.H.[Lin-Hai], Chen, F.[Fang], Zeng, H.C.[Hong-Cheng],
Synthetic Aperture Radar (SAR) Interferometry for Assessing Wenchuan Earthquake (2008) Deforestation in the Sichuan Giant Panda Site,
RS(6), No. 7, 2014, pp. 6283-6299.
DOI Link 1408

Reiche, J.[Johannes], de Bruin, S.[Sytze], Hoekman, D.[Dirk], Verbesselt, J.[Jan], Herold, M.[Martin],
A Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation Detection,
RS(7), No. 5, 2015, pp. 4973-4996.
DOI Link 1506

He, T.[Tian], Shao, Q.[Quanqin], Cao, W.[Wei], Huang, L.[Lin], Liu, L.[Lulu],
Satellite-Observed Energy Budget Change of Deforestation in Northeastern China and its Climate Implications,
RS(7), No. 9, 2015, pp. 11586.
DOI Link 1511

Lu, M.[Meng], Pebesma, E.[Edzer], Sanchez, A.[Alber], Verbesselt, J.[Jan],
Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series,
PandRS(117), No. 1, 2016, pp. 227-236.
Elsevier DOI 1605

Qamer, F.M.[Faisal Mueen], Shehzad, K.[Khuram], Abbas, S.[Sawaid], Murthy, M.[MSR], Xi, C.[Chen], Gilani, H.[Hammad], Bajracharya, B.[Birendra],
Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan,
RS(8), No. 5, 2016, pp. 385.
DOI Link 1606

Hamunyela, E.[Eliakim], Verbesselt, J.[Jan], de Bruin, S.[Sytze], Herold, M.[Martin],
Monitoring Deforestation at Sub-Annual Scales as Extreme Events in Landsat Data Cubes,
RS(8), No. 8, 2016, pp. 651.
DOI Link 1609

Wang, C.Y.[Chu-Yuan], Myint, S.W.[Soe W.],
Environmental Concerns of Deforestation in Myanmar 2001-2010,
RS(8), No. 9, 2016, pp. 728.
DOI Link 1610

Jin, Y.H.[Yi-Hua], Sung, S.Y.[Sun-Yong], Lee, D.K.[Dong Kun], Biging, G.S.[Gregory S.], Jeong, S.G.[Seung-Gyu],
Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest,
RS(8), No. 12, 2016, pp. 997.
DOI Link 1612

Lu, M.[Meng], Hamunyela, E.[Eliakim], Verbesselt, J.[Jan], Pebesma, E.[Edzer],
Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711

Bouvet, A.[Alexandre], Mermoz, S.[Stéphane], Ballère, M.[Marie], Koleck, T.[Thierry], Toan, T.L.[Thuy Le],
Use of the SAR Shadowing Effect for Deforestation Detection with Sentinel-1 Time Series,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809

Pedraza, C.[Carlos], Clerici, N.[Nicola], Forero, C.F.[Cristian Fabián], Melo, A.[América], Navarrete, D.[Diego], Lizcano, D.[Diego], Zuluaga, A.F.[Andrés Felipe], Delgado, J.[Juliana], Galindo, G.[Gustavo],
Zero Deforestation Agreement Assessment at Farm Level in Colombia Using ALOS PALSAR,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Picoli, M.C.A.[Michelle Cristina Araujo], Camara, G.[Gilberto], Sanches, I.[Ieda], Simões, R.[Rolf], Carvalho, A.[Alexandre], Maciel, A.[Adeline], Coutinho, A.[Alexandre], Esquerdo, J.[Julio], Antunes, J.[João], Begotti, R.A.[Rodrigo Anzolin], Arvor, D.[Damien], Almeida, C.[Claudio],
Big earth observation time series analysis for monitoring Brazilian agriculture,
PandRS(145), 2018, pp. 328-339.
Elsevier DOI 1811
Big earth observation data, Land use science, Satellite image time series, Crop expansion, Tropical deforestation BibRef

Helmer, E.H.[Eileen H.], Ruzycki, T.S.[Thomas S.], Wilson, B.T.[Barry T.], Sherrill, K.R.[Kirk R.], Lefsky, M.A.[Michael A.], Marcano-Vega, H.[Humfredo], Brandeis, T.J.[Thomas J.], Erickson, H.E.[Heather E.], Ruefenacht, B.[Bonnie],
Tropical Deforestation and Recolonization by Exotic and Native Trees: Spatial Patterns of Tropical Forest Biomass, Functional Groups, and Species Counts and Links to Stand Age, Geoclimate, and Sustainability Goals,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Espejo, J.C.[Jorge Caballero], Messinger, M.[Max], Román-Dañobeytia, F.[Francisco], Ascorra, C.[Cesar], Fernandez, L.E.[Luis E.], Silman, M.[Miles],
Deforestation and Forest Degradation Due to Gold Mining in the Peruvian Amazon: A 34-Year Perspective,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901

Mizuochi, H.[Hiroki], Hayashi, M.[Masato], Tadono, T.[Takeo],
Development of an Operational Algorithm for Automated Deforestation Mapping via the Bayesian Integration of Long-Term Optical and Microwave Satellite Data,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909

Reygadas, Y.[Yunuen], Jensen, J.L.R.[Jennifer L. R.], Moisen, G.G.[Gretchen G.],
Forest Degradation Assessment Based on Trend Analysis of MODIS-Leaf Area Index: A Case Study in Mexico,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911

Lin, Q.[Qinan], Huang, H.G.[Hua-Guo], Wang, J.X.[Jing-Xu], Huang, K.[Kan], Liu, Y.Y.[Yang-Yang],
Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911

Horch, A.[Abdelkader], Djemal, K.[Khalifa], Gafour, A.[Abdelkader], Taleb, N.[Nasreddine],
Supervised fusion approach of local features extracted from SAR images for detecting deforestation changes,
IET-IPR(13), No. 14, 12 December 2019, pp. 2866-2876.
DOI Link 1912

Grings, F., Roitberg, E., Barraza, V.,
EVI Time-Series Breakpoint Detection Using Convolutional Networks for Online Deforestation Monitoring in Chaco Forest,
GeoRS(58), No. 2, February 2020, pp. 1303-1312.
Forestry, Time series analysis, MODIS, Remote sensing, Earth, Artificial satellites, Monitoring, Deforestation monitoring, time-series analysis BibRef

de Bem, P.P.[Pablo Pozzobon], de Carvalho Junior, O.A.[Osmar Abílio], Guimarães, R.F.[Renato Fontes], Gomes, R.A.T.[Roberto Arnaldo Trancoso],
Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003

Adarme, M.O.[Mabel Ortega], Feitosa, R.Q.[Raul Queiroz], Happ, P.N.[Patrick Nigri], Aparecido de Almeida, C.[Claudio], Gomes, A.R.[Alessandra Rodrigues],
Evaluation of Deep Learning Techniques for Deforestation Detection in the Brazilian Amazon and Cerrado Biomes From Remote Sensing Imagery,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003

Valle, D.[Denis], Hyde, J.[Jacy], Marsik, M.[Matthew], Perz, S.[Stephen],
Improved Inference and Prediction for Imbalanced Binary Big Data Using Case-Control Sampling: A Case Study on Deforestation in the Amazon Region,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004

Perazzoni, F.[Franco], Bacelar-Nicolau, P.[Paula], Painho, M.[Marco],
Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link 2006

Reinisch, E.C., Theiler, J., Ziemann, A.,
Identifying forest thinning using anomalous change detection on synthetic aperture radar data,
geophysical signal processing, radar imaging, remote sensing by radar, synthetic aperture radar, change detection BibRef

Pir Bavaghar, M., Ghazanfari, H., Rahimi, S.,
Comparison of Analytical Hierarchy Process and Fuzzy Method In Deforestation Risk Zoning,
DOI Link 1912

Johnson, B.A., Scheyvens, H., Samejima, H., Onoda, M.,
Characteristics Of The Remote Sensing Data Used In The Proposed Unfccc Redd+ Forest Reference Emission Levels (frels),
ISPRS16(B8: 669-672).
DOI Link 1610
FREL: forest reference emission levels. reducing emissions from deforestation/forest degradation. BibRef

Gao, Y., Ghilardi, A., Mas, J.F., Paneque-Galvez, J., Skutsch, M.,
Evaluation of Annual MODIS PTC Data for Deforestation and Forest Degradation Analysis,
ISPRS16(B2: 9-13).
DOI Link 1610

Chicas, S.D., Omine, K., Arevalo, B., Ford, J.B., Sugimura, K.,
Deforestation Along The Maya Mountain Massif Belize-guatemala Border,
ISPRS16(B8: 597-602).
DOI Link 1610

Mas, J.F., Pérez Vega, A., Andablo Reyes, A., Castillo Santiago, M.A., Flamenco Sandoval, A.,
Assessing Modifiable Areal Unit Problem in the Analysis of Deforestation Drivers Using Remote Sensing and Census Data,
DOI Link 1602

Naghdizadegan, M., Behifar, M., Mirbagheri, B.,
Spatial Deforestation Modelilng Using Cellular Automata (Case Study: Central Zagros Forests),
HTML Version. 1311

Vieira, C.A.O., Santos, N.T., Carneiro, A.P.S., Balieiro, A.A.S.,
Brazilian Amazonia Deforestation Detection Using Spatio-temporal Scan Statistics,
AnnalsPRS(I-2), No. 2012, pp. 51-55.
HTML Version. 1209

Thiel, C., Weise, C., Riedel, T., Schmullius, C.,
Object based classification of L-Band SAR data for the delineation of forest cover maps and the devection of deforestation,
PDF File. 0607

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Mangrove Analysis, Swamps, Coasts, Trees .

Last update:Oct 19, 2020 at 15:02:28