Monday, January 7, 2019

Welcome to our new students!

A very special (but belated) welcome to our 2018 Environmental Observation and Information (EOI) Program cohort, and my newest Master's students.  So excited you are here at UW-Madison!

The 2018-2019 EOI Master's cohort, pictured in June, 2018, while visiting the satellite data receivers on top of the Atmospheric, Oceanic, and Space Sciences Building at UW-Madison.

New paper in Remote Sensing

It is hard to believe that our paper on mapping boom crops in Mainland Southeast Asia has already been out for more than a year!  I loved pushing the limits of Landsat data to map some very complex crop transitions in this dynamic landscape... we are truly in the middle of a remote sensing data revolution.

Expansion of boom crops between 2000 and 2014 mapped for four selected Landsat footprints (125050; 125051; 126049; 126050) in Cambodia, Laos, Thailand, Vietnam.  For full text, please click here.

Tuesday, September 1, 2015

Caitlin Kontgis's paper published in Remote Sensing of Environment

PhD student Caitlin Kontgis has just published her work Mapping rice paddy extent and intensification in the Vietnamese Mekong River Delta with dense time stacks of Landsat data in the top journal in the field of remote sensing, Remote Sensing of Environment.  This work focuses on the development of a new change detection method involving dense time stacks of Landsat (30-m) satellite data to monitor changes in rice paddy area as well as shifts in the number of annual harvests for two time points (circa 2000, circa 2010) in the Mekong Delta.  The results suggest that  rice has intensified in the region from 2000 to 2010, with triple-cropped fields expanding from approximately 34% to 62% of rice paddy agriculture.

Make sure to take a look at this paper (available here) -- recent comments on the paper via the Elsevier website have highlighted that the novel use of Landsat data to monitor crop systems is a 'game-changer' for policy makers.  Exciting stuff!

In Kontgis et al. (2015), the location and extent of rice paddy in the Mekong River Delta were delineated using the confluence of NDWI standard deviation, EVI standard deviation, and EVI mean.

Sunday, January 18, 2015

New Remote Sensing of Environment publication available online

Our research Detecting change in urban areas at continental scales with MODIS data is now available in the January 2015 issue of of Remote Sensing of Environment (click here for more information).  This work demonstrates a new methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data.  We tested the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion, finding accuracies ranging from 70-95% at the country level.  A companion article describing the spatial and temporal trends in urban growth across the 15 countries, A new urban landscape in East-Southeast Asia, 2000-2010, has been accepted at Environmental Research Letters.