15 GEOG245 Tutorial8. Wetland management on the radar. Wetland management on the radar Danube Delta interferogram 11 June 2015 An ESA project focuses on exploiting satellite radar data to monitor wetlands for sustainable water management.
Step by Step: Flood Hazard Mapping. A.
Workflow for the Creation of CN Grid in ArcMap 1. Step by Step: Recommended Practice drought monitoring (ENVI 4.8) Data Preparation/Pre-processing: A.
Data preparation Step 1: Recalculating from MVC values to NDVI value range. ArcGIS 10 official Tutorials PDF. GIS Lounge - Maps and GIS. ENVI Tutorials. Step by Step: Recommended Practice Flood Mapping. 3.
Binarization 3.1 To separate water from non-water a threshold can be selected. For this, we will analyse the histogram of the filtered backscatter coefficient. On the left side panel select the Colour Manipulation tab. The histogram of the backscatter coefficient will show up and one might need to use the logarithmic display. From GIS to Remote Sensing: Estimation of Land Surface Temperature with Landsat Thermal Infrared Band: a Tutorial Using the Semi-Automatic Classification Plugin for QGIS. This post is a tutorial for the estimation of Land Surface Temperature using a Landsat image acquired over Paris (France), using the Semi-Automatic Classification Plugin for QGIS, which allows for supervised classifications.
Before the tutorial, please watch the following video that illustrates the study area and provides very useful information about thermal infrared images, and their application (footage courtesy of European Space Agency/ESA). Also, a brief description of the area that we are going to classify is available here. As shown in the previous video, the study area is covered by the urban surfaces, vegetation and agricultural fields. The thermal infrared band is particularly useful for assessing the temperature difference between the city and the surrounding rural areas, and studying the urban heat island phenomenon. We are going to classify a Landsat 8 image acquired in September 2013 (available from the U.S. Download and resampling of MODIS images - spatial-analyst.net. His article explains how to automate download, mosaicking, resampling and import of MODIS product to a GIS.
We focus on the one of the most known MODIS products for terrestrial environmental applications: the Enhanced Vegetation Index (EVI), which is the improved NDVI (Huete et al., 2002; see the complete list of MODIS products). EVI corrects distortions in the reflected light caused by the particles in the air as well as the ground cover below the vegetation. Efficiently download and process MODIS data with R. # The ProjectMODIS function is a wrapper for the LPDAAC-developed MODIS Rrojection Tool (MRT) which can resample, subset and reproject HDF data # and convert them to geoTIFFS.
This goes without saying but the mosacing and reprojection components of the function will only work if MRT is installed. # Download MRT from LPDAAC here: ProjectMODIS <- function(fname='tmp.file',hdfName,output.name,MRTLoc,UL="",LR="",resample.method='NEAREST_NEIGHBOR',projection='UTM', Google Earth & Google Maps Archives - Monde Geospatial - Geomatics.