Environmental changes in biodiversity hotspot ecosystems ofSouth Ecuador: RESPonse and feedback effECTs (FOR2730)

Dataset ID:	1445
Last updated:	2016-02-22
Dataset creators:	Santiago Ochoa Moreno
Contact:	Carola Paul
Temporal coverage:	2013-03-15 00:00:00 - 2013-03-15 00:00:00
Geographic coverage:	Reserva Laipuna
Abstract:	Abstract:
Additional info:	--- Additional info:
Keywords:	\| land use \| land-use change \| land change modelling \| Agroforestry \| Laipuna \| land use change \| sustainable land use \| land-use \| dry forest \| agriculture \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

1. Entity:

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Entity name:	Socio-economic interview data from Laipuna
Entity type:	dataTable
Attributes:	Date and Time (datetime) (Unitless) household members (hhmember) (Unitless) Area of the plot (PlotArea) [Square meter] Establishment costs (landuse_est_cost) [US-Dollar] Production costs (prod_costs) [US-Dollar] gender (gender) (Unitless) age (age) (Unitless) incomec (incomec) (Unitless)

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Land use/land cover map of South Ecuador 2001

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Dataset ID:	1039
Last updated:	2011-11-09
Dataset creators:	Hanna Meyer Boris Thies Jörg Bendix
Contact:	Boris Thies Jörg Bendix Hanna Meyer
Temporal coverage:	2001-11-03 00:00:00 - 2001-11-03 00:00:00
Geographic coverage:	Loja-Zamora
Abstract:	The map shows land use/land cover (LUC) of the Lo... Abstract: 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.
Additional info:	The classification is based on the Landsat ETM+ i... Additional info: 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.
Keywords:	\| land use \| Loja \| land cover \| landsat \| remote sensing \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	classification2001
Entity type:	spatialRaster (2195 x 2649)
Attributes:	land use (Land_use) (Unitless)

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Landcover soft classification Ecuador (15 classes)

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Dataset ID:	706
Last updated:	2009-10-26
Dataset creators:	Dietrich Göttlicher
Contact:	Dietrich Göttlicher
Temporal coverage:	2001-11-03 18:33:00 - 2001-11-03 18:33:00
Geographic coverage:	Landsat subset south ecuador (podocarpus) for soft classification
Abstract:	Abstract:
Additional info:	Creating a classification with landsat ETM+. Prep... Additional info: 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 class 1 = Kammlage 1900-2100 class 2 = Subparamo > 2700 class 3 = Kammlagen > 2500 (gestört) class 4 = Hanglage > 2600 class 5 = Weide class 6 = vegetationslos (Strasse) class 7 = ehemalige Weide (Sukzession) class 8 = Hanglage 2200-2600 class 9 = Hanglage 1800-2100 class 10 = Kammlage 2100-2300 class 11 = Adlerfarn (Sukzession) class 12 = Kammlage > 2300 class 13 = Weide mit Busch und Waldresten class 14 = Rutschung class 15 = Wasser
Keywords:	\| land use \| raster \| classification \| landsat \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	likelihood class 1 (location on a ridge 1900-2100 masl)
Entity info:	one of 15 classes
Entity type:	spatialRaster (449 x 450)
Attributes:	land use (Land_use) (Unitless)

2. Entity:

Entity name:	likelihood class 2 (Subparamo > 2700 masl)
Entity info:	one of 15 classes
Entity type:	spatialRaster (449 x 450)
Attributes:	land use (Land_use) (Unitless)

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Landcover classification Ecuador (15 classes)

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Dataset ID:	705
Last updated:	2009-10-23
Dataset creators:	Dietrich Göttlicher
Contact:	Dietrich Göttlicher
Temporal coverage:	2001-11-03 17:34:00 - 2001-11-03 17:35:00
Geographic coverage:	Landsat subset south ecuador (podocarpus)
Abstract:	Abstract:
Additional info:	Creating a classification with landsat ETM+. Prep... Additional info: 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
Keywords:	\| land use \| raster \| classification \| landsat \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	landsat classification ecuador 15 classes
Entity type:	spatialRaster (2424 x 3546)
Attributes:	land use (Land_use) (Unitless)

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Prototype land-use model Laipuna

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Dataset ID:	1448
Last updated:	2016-03-23
Dataset creators:	Santiago Ochoa Moreno Carola Paul Thomas Knoke
Contact:	Carola Paul
Temporal coverage:	2013-03-23 00:00:00 - 2016-03-23 00:00:00
Geographic coverage:	Laipuna
Abstract:	Abstract:
Additional info:	--- Additional info:
Keywords:	\| land use \| forest and open land \| land change modelling \| land use change \| land diversification \| land use modeling \| land cover change \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

1. Entity:

Entity name:	Prototype land-use modelling approach Laipuna
Entity info:	Mechanistic land-use modelling approach for calculating compensation payments for preserving forests in Laipuna
Entity type:	otherEntity

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Land use/land cover map of South Ecuador 1987

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Dataset ID:	1038
Last updated:	2011-11-07
Dataset creators:	Hanna Meyer Boris Thies Jörg Bendix
Contact:	Boris Thies Jörg Bendix Hanna Meyer
Temporal coverage:	1987-01-01 00:00:00 - 1997-12-31 00:00:00
Geographic coverage:	Loja-Zamora
Abstract:	The map shows land use/land cover (LUC) of the Lo... Abstract: 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.
Additional info:	The map is available in UTM 17S (WGS 84) projecti... Additional info: 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.
Keywords:	\| land use \| Loja \| land cover \| landsat \| remote sensing \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	classification1987
Entity type:	spatialRaster (2195 x 2649)
Attributes:	land use (Land_use) (Unitless)

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Dynamic of bioelements in soils along a landuse gradient

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Dataset ID:	605
Last updated:	2009-06-29
Dataset creators:	Frank Haubrich Juan Ignacio Burneo Valdivieso
Contact:	Frank Haubrich Franz Makeschin
Temporal coverage:	2004-09-15 00:00:00 - 2005-11-06 11:02:00
Geographic coverage:	Loma_Chamusquin-ECSF-Sabanilla
Abstract:	PHD-Thesis Burneo, Juan Ignacio: "Dynamic of bioe... Abstract: PHD-Thesis Burneo, Juan Ignacio: "Dynamic of bioelements in soils along a landuse gradient in the tropical mountainuous rain forest of Southern Ecuador"
Additional info:	--- Additional info:
Keywords:	\| soil characteristics \| land use \| pasture \| succession \| forest \| chemical elements \| nutrients \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

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Entity name:	elements of a landuse gradient
Entity type:	dataTable
Attributes:	ID of the sample (SampleID) (Unitless) ID of the plot (PlotID) (Unitless) land use (Land_use) (Unitless) pH of soil H2O (PHs_H2O) [Unitless] pH of soil CaCl2 (PHs_CaCl2) [Unitless] Total nitrogen of soil (TNs) [Gram per kilogram] Soil organic carbon (OCs) [Gram per kilogram] Bulk density (Bd) [Gram per cubic centimeter] extractable H (ECEC_H) [Microequivalent per gram] extractable Na (ECEC_Na) [Microequivalent per gram] extrectable Ca (ECEC_Ca) [Microequivalent per gram] extractable Mg (ECEC_Mg) [Microequivalent per gram] extractable Al (ECEC_Al) [Microequivalent per gram] extractable Fe (ECEC_Fe) [Microequivalent per gram] extractable Mn (ECEC_Mn) [Microequivalent per gram] effective cation exchange capacity (ECEC) [Microequivalent per gram] Total element Aluminum of soil (TE_Al) [Gram per kilogram] Total element Calcium of soil (TE_Ca) [Gram per kilogram] Thickness of the horizon (Horizon_thickness) [Meter] Total Cu (TE_Cu) [Milligram per kilogram] Total element Iron of soil (TE_Fe) [Gram per kilogram] Soil depth (Zs) [Meter] Total element Potassium of soil (TE_K) [Gram per kilogram] Total element Magnesium of soil (TE_Mg) [Gram per kilogram] Total element Manganese of soil (TE_Mn) [Gram per kilogram] Total Na (TE_Na) [Milligram per kilogram] Total P (TE_P) [Milligram per kilogram] Total Ti (TE_Ti) [Milligram per kilogram] Total V (TE_V) [Milligram per kilogram] Total Zn (TE_Zn) [Milligram per kilogram] Date and Time (datetime) (Unitless)

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Predicted land use/land cover maps of South Ecuador 2010-2100

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Dataset ID:	1040
Last updated:	2011-11-09
Dataset creators:	Hanna Meyer Boris Thies Jörg Bendix
Contact:	Boris Thies Jörg Bendix Hanna Meyer
Temporal coverage:	2010-01-01 00:00:00 - 2100-12-01 23:59:00
Geographic coverage:	Loja-Zamora
Abstract:	These maps provide projected land use/land cover ... Abstract: 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.
Additional info:	The maps are available in UTM 17S (WGS 84) projec... Additional info: 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.
Keywords:	\| land use \| Loja \| land cover \| land-use change \| land change modelling \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

Entity name:	luc2010
Entity type:	spatialRaster (2195 x 2649)
Attributes:	land use (Land_use) (Unitless)

2. Entity:

Entity name:	luc2020
Entity type:	spatialRaster (2195 x 2649)
Attributes:	land use (Land_use) (Unitless)

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Site classification south Ecuador

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Dataset ID:	819
Last updated:	2010-06-02
Dataset creators:	Frank Haubrich
Contact:	Frank Haubrich
Temporal coverage:	2007-11-01 00:00:00 - 2008-07-18 00:00:00
Geographic coverage:	South Ecuador
Abstract:	Abstract:
Additional info:	--- Additional info:
Keywords:	\| Ecuador \| soil characteristics \| soil classification \| land use \| chemical elements \| soil texture \|
Intellectual rights:	FOR816 data user agreement

1. Entity:

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Entity name:	site classification C3.4
Entity type:	dataTable
Attributes:	ID of the sample (SampleID) (Unitless) Site name (Site_name) (Unitless) Soil horizon symbol after "world reference base" (Horizon_WRB) (Unitless) Minimum geographic latitude (geocoordinate_latitude_min) [Degree] Maximum geographic latitude (geocoordinate_latitude_max) [Degree] Minimum geographic longitude (geocoordinate_longitude_min) [Degree] Maximum geographic longitude (geocoordinate_longitude_max) [Degree] Height above mean sea level (geocoordinate_amsl) [Meter] pH of soil H2O (PHs_H2O) [Unitless] Total nitrogen of soil (TNs) [Gram per kilogram] Soil organic carbon (OCs) [Gram per kilogram] Soil texture sand content (Sand) [Unitless] Soil texture silt content (Silt) [Unitless] Soil texture clay content (Clay) [Unitless] Total element Aluminum of soil (TE_Al) [Gram per kilogram] Total element Calcium of soil (TE_Ca) [Gram per kilogram] Total element Iron of soil (TE_Fe) [Gram per kilogram] Total element Potassium of soil (TE_K) [Gram per kilogram] Total element Magnesium of soil (TE_Mg) [Gram per kilogram] Total element Manganese of soil (TE_Mn) [Gram per kilogram] Total Na (TE_Na) [Milligram per kilogram] Total P (TE_P) [Milligram per kilogram] Total Ti (TE_Ti) [Milligram per kilogram] Total Zn (TE_Zn) [Milligram per kilogram] extractable H (ECEC_H) [Microequivalent per gram] extractable Na (ECEC_Na) [Microequivalent per gram] extractable K (ECEC_K) [Microequivalent per gram] extrectable Ca (ECEC_Ca) [Microequivalent per gram] extractable Mg (ECEC_Mg) [Microequivalent per gram] extractable Al (ECEC_Al) [Microequivalent per gram] extractable Fe (ECEC_Fe) [Microequivalent per gram] extractable Mn (ECEC_Mn) [Microequivalent per gram] effective cation exchange capacity (ECEC) [Microequivalent per gram] Thickness of the horizon (Horizon_thickness) [Meter] Base saturation of soil (BS) [Percent] land use (Land_use) (Unitless) soil type (Soil_type) (Unitless) Date and Time (datetime) (Unitless)

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Prototype multifunctional land-use model Laipuna

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Dataset ID:	1625
Last updated:	2017-08-10
Dataset creators:	Carola Paul Thomas Knoke
Contact:	Carola Paul
Temporal coverage:	2017-08-10 00:00:00 - 2017-08-10 00:00:00
Geographic coverage:	Laipuna
Abstract:	Robust multifunctional land-use model for derivin... Abstract: Robust multifunctional land-use model for deriving multifunctional landscapes
Additional info:	See README in data for additional information on ... Additional info: See README in data for additional information on methodology
Keywords:	\| land use \| Laipuna \| agriculture \| Economics \| carbon balance \| food production \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

1. Entity:

Entity name:	Prototype land-use model Laipuna
Entity info:	Robut land-use optimization approach to explore trade-offs between different ecosystem functions and find compromise solutions
Entity type:	otherEntity

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Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)

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Environmental changes in biodiversity hotspot ecosystems of South Ecuador: RESPonse and feedback effECTs (FOR2730)

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Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)