Monthly Archives: February 2016

Esri Releases Drone2Map for ArcGIS

Drone2Map for ArcGIS, released on February 24 by Esri, is a stand-alone desktop app for processing imagery collected by drones. Check out the Drone2Map FAQ and an interesting presentation (Working With Drone Data In ArcGIS) by Tony Mason of Esri. Interested users can visit esri.com/drone2map for more information.

Q: Is Drone2Map for ArcGIS going to be an ArcGIS Extension?
A: No. It is a stand-alone 64-bit Windows desktop app that will run alongside ArcMap and ArcGIS Pro.

Q: What does Drone2Map for ArcGIS do?
A: Drone2Map for ArcGIS is a desktop app that turns raw still imagery from drones into  stunning information products in ArcGIS. Now, with drone hardware becoming more accessible, you can create 2D and 3D maps of features and areas.

Q: Can Drone2Map for ArcGIS be used to make 3D models?
A: Yes, Drone2Map for ArcGIS will produce 3D colorized point clouds in LAS format as well as 3D textured meshes for use in ArcGIS Desktop and Web Apps.

Q: Does the Drone2Map for ArcGIS work only with a specific type of drone?
A: Drone2Map for ArcGIS is designed to be generic for all drones. What is important is that the drone collects certain types of metadata. At a very minimum, this metadata needs to include Latitude, Longitude, and Altitude. The addition of orientation, focal length and pixel size of the sensor will greatly improve results. Many commercially available drones have this capability and automatically add this information to the image metadata.

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R script for updating student grades on Blackboard

This might be of interest to some of you teaching large enrollment courses and using scantrons for quizzes/exams. I developed a script using R programming language to automatically extract scores from ITS test scoring results and upload the grades to Blackboard.

The script needs two CSV format input files: the student info file from Blackboard (Full Grade Center -> Work Offline – Download) and the ITS test scoring results (convert the Excel file to CSV). It takes less than one second to get the results.

Feel free to let me know if you have any questions.

########################################

BBfile <- file.choose()  #”roster.csv”    ### The file downloaded from Blackboard
ITSfile <- file.choose()   #”result.csv”   ### The file received from ITS scantron results

# BBfile <- “roster.csv”
# ITSfile <- “result.csv”
output <- “score.csv”
scale.factor <- 1  ### scale factor multiplied by the scantron results.
### Extract students’ fullname from Blackboard roster
roster <- read.csv(BBfile,header = TRUE,stringsAsFactors = FALSE)
str(roster)
roster$firstname = as.character(lapply(strsplit(as.character(roster$First.Name), split=” “), “[“, 1))
roster$fullname <- tolower(paste(roster$Last.Name,roster$firstname,sep=””))
### read the ITS results
df <- read.csv(ITSfile,stringsAsFactors = FALSE)
df <- df[nchar(gsub(” “,””,df$X))>0,]
df <- df[!is.na(as.numeric(df$X.5)),c(“X”,”X.2″)]
colnames(df) <- c(“Name”,”Score”)
df$Score <- as.numeric(df$Score) * scale.factor
str(df)
### extract student names from ITS results

lastname <- as.character(lapply(strsplit(as.character(df$Name), split=” “), “[“, 1))
firstname <- as.character(lapply(strsplit(as.character(df$Name), split=” “), “[“, 2))
df$fullname  <- tolower(paste(lastname,firstname,sep = “”))
### match student names from Blackboard and ITS
m.x <- merge(roster,df,by = “fullname”,all.x = TRUE)
fix(m.x)
m.x$raw <- m.x$Score / scale.factor
### save the results to csv file
write.csv(m.x,output,na = “”,row.names = FALSE)
m.y <- merge(roster,df,by = “fullname”,all.x = TRUE,all.y = TRUE)
m.y.sub <- m.y[is.na(m.y$Last.Name), ]
score <- read.csv(output,header = TRUE,stringsAsFactors = FALSE)
summary(score)

########################################

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