Remote Sensing Commons^™

High Resolution, Annual Maps Of Field Boundaries For Smallholder-Dominated Croplands At National Scales, Lyndon D. Estes, Su Ye, Lei Song, Boka Luo, J. Ronald Eastman, Zhenhua Meng, Qi Zhang, Dennis Mcritchie, Stephanie R. Debats, Justus Muhando, Angeline H. Amukoa, Brian W. Kaloo, Jackson Makuru, Ben K. Mbatia, Isaac M. Muasa, Julius Mucha, Adelide M. Mugami, Judith M. Mugami, Francis W. Muinde, Fredrick M. Mwawaza, Jeff Ochieng, Charles J. Oduol, Purent Oduor, Thuo Wanjiku, Joseph G. Wanyoike, Ryan B. Avery, Kelly K. Caylor

Geography

Mapping the characteristics of Africa’s smallholder-dominated croplands, including the sizes and numbers of fields, can provide critical insights into food security and a range of other socioeconomic and environmental concerns. However, accurately mapping these systems is difficult because there is 1) a spatial and temporal mismatch between satellite sensors and smallholder fields, and 2) a lack of high-quality labels needed to train and assess machine learning classifiers. We developed an approach designed to address these two problems, and used it to map Ghana’s croplands. To overcome the spatio-temporal mismatch, we converted daily, high resolution imagery into two cloud-free composites (the …

Probabilistic Tracking Of Annual Cropland Changes Over Large, Complex Agricultural Landscapes Using Google Earth Engine, Sitian Xiong, Priscilla Baltezar, Morgan A. Crowley, Michael Cecil, Stefano C. Crema, Eli Baldwin, Jeffrey A. Cardille, Lyndon Estes

Geography

Cropland expansion is expected to increase across sub-Saharan African (SSA) countries in the next thirty years to meet growing food needs across the continent. These land transformations will have cascading social and ecological impacts that can be monitored using novel Earth observation techniques that produce datasets complementary to national cropland surveys. In this study, we present a flexible Bayesian data synthesis workflow on Google Earth Engine (GEE) that can be used to fuse optical and synthetic aperture radar data and demonstrate its ability to track agricultural change at national scales. We adapted the previously developed Bayesian Updating of Land Cover …

Assessment Of Empirical And Semi-Analytical Algorithms Using Modis-Aqua For Representing In-Situ Chromophoric Dissolved Organic Matter (Cdom) In The Bering, Chukchi, And Western Beaufort Seas Of The Pacific Arctic Region, Melishia I. Santiago, Karen E. Frey

Geography

We analyzed a variety of satellite-based ocean color products derived using MODIS-Aqua to investigate the most accurate empirical and semi-analytical algorithms for representing in-situ chromophoric dissolved organic matter (CDOM) across a large latitudinal transect in the Bering, Chukchi, and western Beaufort Seas of the Pacific Arctic region. In particular, we compared the performance of empirical (CDOM index) and several semi-analytical algorithms (quasi-analytical algorithm (QAA), Carder, Garver-Siegel-Maritorena (GSM), and GSM-A) with field measurements of CDOM absorption (aCDOM) at 412 nanometers (nm) and 443 nm. These algorithms were compared with in-situ CDOM measurements collected on cruises during July 2011, 2013, 2014, 2015, …

Effects Of Bark Beetle Outbreaks On Forest Landscape Pattern In The Southern Rocky Mountains, U.S.A., Kyle C. Rodman, Robert A. Andrus, Cori L. Butkiewicz, Teresa B. Chapman, Nathan S. Gill, Brian J. Harvey, Dominik Kulakowski, Niko J. Tutland, Thomas T. Veblen, Sarah J. Hart

Geography

Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a cru-cial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data …

Change Points Detected In Decadal And Seasonal Trends Of Outlet Glacier Terminus Positions Across West Greenland, Ashley V. York, Karen E. Frey, Sadegh Jamali, Sarah B. Das

Geography

We investigated the change in terminus position between 1985 and 2015 of 17 marine-terminating glaciers that drain into Disko and Uummannaq Bays, West Greenland, by manually digitizing over 5000 individual frontal positions from over 1200 Landsat images. We find that 15 of 17 glacier termini retreated over the study period, with ~80% of this retreat occurring since 2000. Increased frequency of Landsat observations since 2000 allowed for further investigation of the seasonal variability in terminus position. We identified 10 actively retreating glaciers based on a significant positive relationship between glaciers with cumulative retreat >300 m since 2000 and their average …

Accounting For Training Data Error In Machine Learning Applied To Earth Observations, Arthur Elmes, Hamed Alemohammad, Ryan Avery, Kelly Caylor, J. Ronald Eastman, Lewis Fishgold, Mark A. Friedl, Meha Jain, Divyani Kohli, Juan Carlos Laso Bayas, Dalton Lunga, Jessica L. Mccarty, Robert Gilmore Pontius, Andrew B. Reinmann, John Rogan, Lei Song, Hristiana Stoynova, Su Ye, Zhuang Fang Yi, Lyndon Estes

Geography

Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system dynamics and create continuous and categorical maps of biophysical properties and land cover, especially based on recent advances in machine learning (ML). ML models typically require large, spatially explicit training datasets to make accurate predictions. Training data (TD) are typically generated by digitizing polygons on high spatial-resolution imagery, by collecting in situ data, or by using pre-existing datasets. TD are often assumed to accurately represent the truth, but in practice almost always have error, stemming from (1) sample design, and (2) sample collection errors. The latter is …

An Evaluation Of Sentinel-1 And Sentinel-2 For Land Cover Classification, Aaron Meneghini

Sustainability and Social Justice

This study evaluates Sentinel-1 and Sentinel-2 remotely sensed images for tropical land cover classification. The dual polarized Sentinel-1 VV and VH backscatter images and four 10-meter multispectral bands of Sentinel-2 were used to create six land cover classification images across two study areas along the border of the Bolivian Pando Department and the Brazilian state of Acre. Results indicate that Sentinel-2 multispectral bands possess a higher overall performance in delineating land cover types than the Sentinel-1 backscatter bands. Sentinel-1 backscatter bands delineated land cover types based on their surficial properties but did not facilitate the separation of similarly textured classes. …

Sentinel-1 Slc Processing: Summer Internship With Clark Labs, Lei Tang

Sustainability and Social Justice

My summer internship with Clark Labs was mainly focused on technological and methodological exploration of Sentinel-1 SLC data, under the direct supervision of James Toledano. The main responsibilities of my internship were understanding theory and science behind Sentinel-1, utilizing the SNAP toolbox to determine the proper imagery processing steps in order to distinguish the land structure clearly. 36 testing on different combination of acquisition modes, speckle filters and time gap were conducted during that time.

I would highly recommend this internship to other GISDE students. The dynamic nature of the GISDE program provides students with the opportunity to be able …

Aiddata Gis International Fellowship: Ghana West-Africa, Jason N. Ready

Sustainability and Social Justice

My internship, or fellowship as it was commonly referred to, was funded by a non-profit organization out of Williamsburg Virginia called AidData. This fellowship took place in in the country of Ghana, West-Africa beginning in May of 2016 and continued for 14 weeks with 40 hours each week. The objective of this internship was to provide in-depth training on the use of geographic Information Systems to Private and Public sectors within the country to allow for increased efficiency, and transparency through data visualization. In accordance with the requirement of Clark Universities GISDE master’s program this paper will delve into the …

Land Change Modeler Application: Summer Internship With Clark Labs, Nan Ding, Siqi Cheng

Sustainability and Social Justice

This paper is a description of our internship with Clark Labs in the summer of 2015. We worked as research assistants in the Land Change Modeler Application (App) project. This project aimed to display the land cover changes in the United States from 2001 to 2010, show the vulnerability in 48 states and predict changes from the yaer 2050. Our responsibility was to extract eight variables (slope, elevation, surface water, roads, high intensity land, protected areas, county subdivisions, and cultivated crops) in TerrSet, and use them in several models to test the accuracy of prediction.

The internship is a great …

Remote Sensing Specialist Summer Internship At Geoadaptive Llc., Zehan Li

Sustainability and Social Justice

This paper describes my summer internship experience during the summer of 2015, as a requirement toward my master's degree. I worked as a full-time remote sensing specialist at GeoAdaptive LLC., which locates at downtown Boston. My work covers a variety ranging from providing technical support like data collecting and visualization to other research groups at the firm, to conducting a pioneer project regrading the large scale drought monitoring using publicly available data. As someone who learnt a great deal and valued this experience greatly, I would love to recommend this internship to other fellow GISDE students when they take on …

Land Change Modeler Application:Summer Internship With Clark Labs, Siqi Cheng, Nan Ding

Sustainability and Social Justice

This paper is a description of our internship with Clark Labs in the summer of 2015. We worked as research assistants in the Land Change Modeler Application (App) project. This project aimed to display the land cover changes in the United States from 2001 to 2010, show the vulnerability in 48 states and predict changes from the yaer 2050. Our responsibility was to extract eight variables (slope, elevation, surface water, roads, high intensity land, protected areas, county subdivisions, and cultivated crops) in TerrSet, and use them in several models to test the accuracy of prediction.

The internship is a great …

Forest Baseline And Deforestation Map Of The Dominican Republic Through The Analysis Of Time Series Of Modis Data, Florencia Sangermano, Leslie Bol, Pedro Galvis, Raymond E. Gullison, Jared Hardner, Gail S. Ross

Geography

Deforestation is one of the major threats to habitats in the Dominican Republic. In this work we present a forest baseline for the year 2000 and a deforestation map for the year 2011. Maps were derived from Moderate Resolution Imaging Radiometer (MODIS) products at 250. m resolution. The vegetation continuous fields product (MOD44B) for the year 2000 was used to produce the forest baseline, while the vegetation indices product (MOD13Q1) was used to detect change between 2000 and 2011. Major findings based on the data presented here are reported in the manuscript "Habitat suitability and protection status of four species …

Mapping Licit And Illicit Mining Activity In The Madre De Dios Region Of Peru, Arthur Elmes, Josué Gabriel Yarlequé Ipanaqué, John Rogan, Nicholas Cuba, Anthony J. Bebbington

Geography

Since the early 2000s, the Madre de Dios Region of southern Peru has experienced rapid expansion of both licit and illicit mining activities, in the form of artisanal and small-scale mining (ASM). ASM typically takes place in remote, inaccessible locations and is therefore difficult to monitor in situ. This paper explores the utility of Landsat-5 imagery via decision tree classification to determine ASM locations in Madre de Dios. Spectral mixture analysis was used to unmix Landsat imagery, using WorldView and QuickBird l imagery to aid spectral endmember selection and validate AMS maps. The ASM maps had an overall area-weighted accuracy …

Global Trends In Seasonality Of Normalized Difference Vegetation Index (Ndvi), 1982-2011, J. Ronald Eastman, Florencia Sangermano, Elia A. Machado, John Rogan, Assaf Anyamba

Geography

A 30-year series of global monthly Normalized Difference Vegetation Index (NDVI) imagery derived from the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g archive was analyzed for the presence of trends in changing seasonality. Using the Seasonal Trend Analysis (STA) procedure, over half (56.30%) of land surfaces were found to exhibit significant trends. Almost half (46.10%) of the significant trends belonged to three classes of seasonal trends (or changes). Class 1 consisted of areas that experienced a uniform increase in NDVI throughout the year, and was primarily associated with forested areas, particularly broadleaf forests. Class 2 consisted of areas experiencing …

Ice Sheet Record Of Recent Sea-Ice Behavior And Polynya Variability In The Amundsen Sea, West Antarctica, Alison S. Criscitiello, Sarah B. Das, Matthew J. Evans, Karen E. Frey, Howard Conway, Ian Joughin, Brooke Medley, Eric J. Steig

Geography

[1] Our understanding of past sea-ice variability is limited by the short length of satellite and instrumental records. Proxy records can extend these observations but require further development and validation. We compare methanesulfonic acid (MSA) and chloride (Cl-) concentrations from a new firn core from coastal West Antarctica with satellite-derived observations of regional sea-ice concentration (SIC) in the Amundsen Sea (AS) to evaluate spatial and temporal correlations from 2002-2010. The high accumulation rate (∼39 g·cm-2·yr-1) provides monthly resolved records of MSA and Cl-, allowing detailed investigation of how regional SIC is recorded in the ice-sheet stratigraphy. Over the period 2002-2010 …

Satellite-Based Estimates Of Antarctic Surface Meltwater Fluxes, Luke D. Trusel, Karen E. Frey, Sarah B. Das, Peter Kuipers Munneke, Michiel R. Van Den Broeke

Geography

This study generates novel satellite-derived estimates of Antarctic-wide annual (1999-2009) surface meltwater production using an empirical relationship between radar backscatter from the QuikSCAT (QSCAT) satellite and melt calculated from in situ energy balance observations. The resulting QSCAT-derived melt fluxes significantly agree with output from the regional climate model RACMO2.1 and with independent ground-based observations. The high-resolution (4.45 km) QSCAT-based melt fluxes uniquely detect interannually persistent and intense melt (>400 mm water equivalent (w.e.) year-1) on interior Larsen C Ice Shelf that is not simulated by RACMO2.1. This supports a growing understanding of the importance of a föhn effect in …

Antarctic Surface Melting Dynamics: Enhanced Perspectives From Radar Scatterometer Data, L. D. Trusel, K. E. Frey, S. B. Das

Geography

Antarctic ice sheet surface melting can regionally influence ice shelf stability, mass balance, and glacier dynamics, in addition to modulating near-surface physical and chemical properties over wide areas. Here, we investigate variability in surface melting from 1999 to 2009 using radar backscatter time series from the SeaWinds scatterometer aboard the QuikSCAT satellite. These daily, continent-wide observations are explored in concert with in situ meteorological records to validate a threshold-based melt detection method. Radar backscatter decreases during melting are significantly correlated with in situ positive degree-days as well as meltwater production determined from energy balance modeling at Neumayer Station, East Antarctica. …

Spatial And Interannual Variability Of Dissolved Organic Matter In The Kolyma River, East Siberia, Observed Using Satellite Imagery, Claire G. Griffin, Karen E. Frey, John Rogan, Robert M. Holmes

Geography

The Kolyma River basin in northeastern Siberia, the sixth largest river basin draining to the Arctic Ocean, contains vast reserves of carbon in Pleistocene-aged permafrost soils. Permafrost degradation, as a result of climate change, may cause shifts in riverine biogeochemistry as this old source of organic matter is exposed. Satellite remote sensing offers an opportunity to complement and extrapolate field sampling of dissolved organic matter in this expansive and remote region. We develop empirically based algorithms that estimate chromophoric dissolved organic matter (CDOM) and dissolved organic carbon (DOC) in the Kolyma River and its major tributaries in the vicinity of …

Detection Of The Timing And Duration Of Snowmelt In The Hindu Kush-Himalaya Using Quikscat, 2000-2008, Prajjwal K. Panday, Karen E. Frey, Bardan Ghimire

Geography

The Hindu Kush-Himalayan (HKH) region holds the largest mass of ice in Central Asia and is highly vulnerable to global climate change, experiencing significant warming (0.21 ± 0.08 °C/decade) over the past few decades. Accurate monitoring of the timing and duration of snowmelt across the HKH region is important, as this region is expected to experience further warming in response to increased greenhouse gas forcing. Despite the many advantages and applications of satellite-derived radar scatterometer data shown for capturing ice and snow melt dynamics at high latitudes, similar comprehensive freeze/thaw detection studies at lower latitudes (including the HKH region) are …