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Platform data

Overview

Detailed view

Creating a classification with landsat ETM+. Preprocessing includes: 
Reprojection: Idrisi Import / Reproject, Projection: UTM 17 South (30 m pixel size)
Subsetting: Idrisi Window, min x : 684990, max x : 758010, min y: 9493010, max y: 9601610
Geometric correction: ERDAS Imagine 8.6, Geometric model: Landsat
Reference: Landsat Geocover datasets (1986, 2000, orthorectified), Digital elevation model: SRTM data, Ground Control Points: 152, Control Point Error : (X) 12.68 (Y) 13.42 (Total) 18.46 (<1 pixel), Subsetting: min x: 684990, max x: 757710,min y: 9493010, max y: 9599390
Atmospheric correction: Idrisi Atmosc (Cost model), Year: 2001, Month: 11, Day: 03, GMT: 15.00, Sun elevation:  61.8568494
Band Center (Cm) DN haze Offset Gain
1 0.485 27 -0.73807 0.11807
2 0.56 19 -0.76098 0.12098
3 0.66 12 -0.59425 0.09425
4 0.83 6 -0.60693 0.09693
5 1.65 3 -0.11912 0.01912
7 2.215 5 -0.04165 0.00665

Topographic correction: 
Statistical-empirical approach
Idrisi Hillshade
Digital elevation model: SRTM data
Sun elevation: 61.8568494
Sun azimuth: 114.5874861

CLASSIFICATION:
Step 1) Maximum likelihood classifier with 19 different training sites
Step 2) Post-classification merging to 15 and 10 classes

Land cover classification of the San Francisco valley using a QuickBird scene of October 22, 2010. 
The classification includes the following classes:(1) forest, (2) pasture, (3) bracken fern, (4) non-vegetated, and (5) subpáramo.

These maps provide projected land use/land cover (LUC) of the Loja-Zamora region for every 10 years from 2010 until 2100. They consist of 6 LUC classes: Forest, Subparamo, Paramo, Pasture, Urban and Water.
The maps were created by modelling LUC change (LUCC) using information of past changes derived by remotely sensed data and several explanatory variables (e. g distance from streets). A training period of 14 years between 1987 and 2001 was chosen. Special focus was on forest development patterns. A change detection of the training period provided the basis for predictive LUCC modelling. The modelling procedure consisted of a combination of Markov chain analysis (MCA) for quantitative modelling and multi-layer perceptron (MLP) for revealing potential locations of change. A multi-objective land allocation (MOLA) served as final integration step.

The maps are available in UTM 17S (WGS 84) projection. 
Input data for the model were two LUC Classifications from 1987 and 2001 (Meyer et al. 2011), a SRTM 90m digital elevation model (DEM), GIS-Layers of streets, villages and rivers in the study area and a GIS layer which contained the borders of the Podocarpus national park (Instituto Geográfico Militar Ecuador).
The modelled LUCC were urbanisation, deforestation and reforestation. Explanatory variables of LUCC were elevation, aspect, slope, distance from streets, distance from rivers, distance from Loja, distance from villages and distance from forest edges. The variable ?distance from forest edges? was dynamic. Therefore LUCC was not modelled directly until 2100 but with recalculation steps every 10 years. Consequently, the procedure steps 3 to 5 were accomplished for every 10 years. The Step 1 was only for some parts accomplished every 10 years.

More detailed information about the methodology used here to predict LUCC can be found in (Meyer 2010)

References:

Instituto Geográfico Militar Ecuador: Data of basically geographic featrures (rivers, roads, cities, administrative borders). Given to Rollenbeck, R. in 2002 for scientific use.)

Meyer, H. (2010): Predicting land use/land cover changes in a tropical mountain forest of Ecuador for future SVAT prediction. A modelling approach and result validation based on GIS and remotely sensed data Marburg University, bachelor thesis. 

Meyer H. , Thies B. , and Bendix J. (2011): Land use/land cover map of South Ecuador 1987 . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1038) from DFG-FOR816dw. 

Meyer H. , Thies B. , and Bendix J. (2011): Land use/land cover map of South Ecuador 2001 . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1039) from DFG-FOR816dw.

The map shows land use/land cover (LUC) of the Loja-Zamora region in 1987. It consists of 6 LUC classes: Forest, Subparamo, Paramo, Pasture, Urban and Water. The classification is mainly based on a Landsat TM image from 1987/03/26. However, since it features high cloudiness, a composite of 8 further images around the year 1987 was used for filling the gaps.

The map is available in UTM 17S (WGS 84) projection. 
The basis for the classification was the Landsat Scene LT50100631987085XXX02 (accessed in New Earth explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/) from 1987/03/26. The following TM scenes were used for filling the clouded areas of 1987: 
-1985/03/20 (LT50100631985079AAA04)
-1986/12/04 (LT50100631986338XXX03)
-1986/11/02 (LT50100631986306XXX09)
-1989/12/28 (LT50100631989362XXX02)
-1990/03/02 (LT50100631990061XXX02)
-1998/07/14 (LT50100631998195XXX01)
-1998/08/15 (LT50100631998227XXX01)
-1998/12/21 (LT50100631998355XXX01)

The procedure steps 1-5 were accomplished for each of the 9 Landsat images.

The satellite images were acquired in the following dates: 28.12.1975, 19.12.1980, 26.03.1987, 31.10.2000, and 03.11.2001.

The classifications of 1975 and 1980 have the following classes: (1) cloud and cloud-shadow mask, (2) subpáramo, (3) forest, (4) burnt, (5) non-vegetated, and (6) bracken and pasture.
The classifications of 1987, 2000, and 2001 have the following classes: (1) cloud and cloud-shadow mask, (2) subpáramo, (3) forest, (4) burnt, (5) non-vegetated, and (6) bracken, and (7) pasture.

classes:
1 Non-vegetated
2 Bracken
3 Forest
4 Pasture
5 Mask: clouds, cloud-shadows, and subpáramo vegetation

The map shows land use/land cover (LUC) of the Loja-Zamora region in 2001. It consists of 6 LUC classes: Forest, Subparamo, Paramo, Pasture, Urban and Water. The classification is based on a Landsat ETM+ image from 2011/11/03.

The classification is based on the Landsat ETM+ image LE70100632001307EDC00 from 2011/11/03 (accessed in New Earth explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/). The same image was already classified by Göttlicher (2009). The difference to the classification of Göttlicher is that the scene was created for land change modelling (Meyer et al. 2011b). Therefore it was very important that especially forest and non forest could be distinguished perfectly and that the classification is comparable to a second classification of 1987 (Meyer et al. 2011). The classification of 2001 by Göttlicher was classified using expert knowledge. It was not possible to reconstruct detailed classes for the corresponding 1987 scene. Therefore this new classification of 2001 was necessary for a comparison to 1987.
The classification of Göttlicher (2009) is recommended if information of current and detailed LUC is needed. For analysis with focus on the contrast of grassland/forest distribution or for change detection matters we recommend using this new classification. 


citation: 
Göttlicher D. (2009): Landcover classification Ecuador (10 classes). Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=704) from DFG-FOR816dw

Meyer H. , Thies B. , and Bendix J. (2011): Land use/land cover map of South Ecuador 1987 . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1038) from DFG-FOR816dw. 

Meyer H. , Thies B. , and Bendix J. (2011b): Predicted land use/land cover maps of South Ecuador 2010-2100 . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1040) from DFG-FOR816dw.