Cálculo de cuenca vertiente con ArcGIS

Descripción del módulo hidrológico de Spatial Analysis de ArcGIS 10.

Ejercicio de Análisis de Redes con Network Analysis de ArcGIS 10.

Ejercicio de Análisis de Redes con Network Analysis de ArcGIS 10

Iniciación a Spatial Analysis con ArcGIS 10

Iniciación a las herramientas de Spatial Analysis de ArcGIS 10.

Aprendiendo a utilizar Model Builder de ArcGIS en español

Pequeño manual de introducción a Model Builder en ArcGIS para la automatización de flujos de trabajo.

An ArcGIS Tool for Modeling the Climate Envelope with Feed-Forward ANN

This paper is about the development and the application of an ESRI ArcGIS tool which implements multi-layer, feed-forward artificial neural network (ANN) to study the climate envelope of species. The supervised learning is achieved by backpropagation algorithm. Based on the distribution and the grids of the climate (and edaphic data) of the reference and future periods the tool predicts the future potential distribution of the studied species. The trained network can be saved and loaded. A modeling result based on the distribution of European larch (Larix decidua Mill.) is presented as a case study.

GIS layers of seafloor characteristics in the Azores region (North Atlantic), links to files in ArcGIS format

Inventory of some important datasets related to the physical characteristics of the seafloor surrounding the Azores Archipelago. The objective is to ensure that our compilation is readily available for any researchers interested in this type information but also to support institutions responsible for the management and conservation of local resources.

Inventory of thermo-erosional valleys and streams in three ice-rich permafrost lowlands adjacent to the Laptev Sea, with links to maps in ArcGIS format

This dataset provides an inventory of thermo-erosional landforms and streams in three lowland areas underlain by ice-rich permafrost of the Yedoma-type Ice Complex at the Siberian Laptev Sea coast. It consists of two shapefiles per study region: one shapefile for the digitized thermo-erosional landforms and streams, one for the study area extent. Thermo-erosional landforms were manually digitized from topographic maps and satellite data as line features and subsequently analyzed in a Geographic Information System (GIS) using ArcGIS 10.0. The mapping included in particular thermo-erosional gullies and valleys as well as streams and rivers, since development of all of these features potentially involved thermo-erosional processes. For the Cape Mamontov Klyk site, data from Grosse et al. [2006], which had been digitized from 1:100000 topographic map sheets, were clipped to the Ice Complex extent of Cape Mamontov Klyk, which excludes the hill range in the southwest with outcropping bedrock and rocky slope debris, coastal barrens, and a large sandy floodplain area in the southeast. The mapped features (streams, intermittent streams) were then visually compared with panchromatic Landsat-7 ETM+ satellite data (4 August 2000, 15 m spatial resolution) and panchromatic Hexagon data (14 July 1975, 10 m spatial resolution). Smaller valleys and gullies not captured in the maps were subsequently digitized from the satellite data. The criterion for the mapping of linear features as thermo-erosional valleys and gullies was their clear incision into the surface with visible slopes. Thermo-erosional features of the Lena Delta site were mapped on the basis of a Landsat-7 ETM+ image mosaic (2000 and 2001, 30 m ground resolution) [Schneider et al., 2009] and a Hexagon satellite image mosaic (1975, 10 m ground resolution) [G. Grosse, unpublished data] of the Lena River Delta within the extent of the Lena Delta Ice Complex [Morgenstern et al., 2011]. For the Buor Khaya Peninsula, data from Arcos [2012], which had been digitized based on RapidEye satellite data (8 August 2010, 6.5 m ground resolution), were completed for smaller thermo-erosional features using the same RapidEye scene as a mapping basis. The spatial resolution, acquisition date, time of the day, and viewing geometry of the satellite data used may have influenced the identification of thermo-erosional landforms in the images. For Cape Mamontov Klyk and the Lena Delta, thermo-erosional features were digitized using both Hexagon and Landsat data; Hexagon provided higher resolution and Landsat provided the modern extent of features. Allowance of up to decameters was made for the lateral expansion of features between Hexagon and Landsat acquisitions (between 1975 and 2000).

Mapped distribution of intertidal habitats in Australia between 1999 and 2014, link to data in ArcGIS format (29 MB)

Shorebirds have declined severely across the East Asian-Australasian Flyway. Many species rely on intertidal habitats for foraging, yet the distribution and conservation status of these habitats across Australia remain poorly understood. Here, we utilised freely available satellite imagery to produce the first map of intertidal habitats across Australia. We estimated a minimum intertidal area of 9856 km**2, with Queensland and Western Australia supporting the largest areas. Thirty-nine percent of intertidal habitats were protected in Australia, with some primarily within marine protected areas (e.g. Queensland) and others within terrestrial protected areas (e.g. Victoria). In fact, three percent of all intertidal habitats were protected both by both marine and terrestrial protected areas. To achieve conservation targets, protected area boundaries must align more accurately with intertidal habitats. Shorebirds use intertidal areas to forage and supratidal areas to roost, so a coordinated management approach is required to account for movement of birds between terrestrial and marine habitats. Ultimately, shorebird declines are occurring despite high levels of habitat protection in Australia. There is a need for a concerted effort both nationally and internationally to map and understand how intertidal habitats are changing, and how habitat conservation can be implemented more effectively.

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.