From California to Cambodia - Surface Water Mapping Using Cloud-Based Remote Sensing (by Christopher Soulard, USGS Research Geographer)
Patterns in the Landscape – Analyses of Cause and Effect
How is land changing in the United States?
Why is land changing in the United States?
Understanding the rates and causes of land-use/land-cover (LULC) change helps answer questions about what, where, how, and why the Earth’s surface is changing. Land-surface change results from human activities or natural processes like floods, droughts, and wildfires, and many of these change processes are observable in satellite imagery. The growing historical catalog of satellite images allows scientists to study past LULC changes to better understand where and why changes occur and how human and natural systems respond to them.
The mission of the PLACE (Patterns in the Landscape – Analyses of Cause and Effect) project is to inform land managers, planners, and researchers about historical and current changes to human and natural environments. PLACE focuses on floods, droughts, and fires, which are increasing in severity, extent, and frequency around the globe. Our work is based on the idea that understanding what drives these disturbance events is a necessary step for identifying management practices that can mitigate the negative human and ecological impacts.

Our research is characterized by the following three themes:
Landscape Monitoring
PLACE develops imagery-based approaches to identify and monitor the occurrence of land-cover/land-use change across the United States from 1985-present.
Our publications demonstrate the wide range of monitoring efforts in the PLACE portfolio, as well as how we tailor approaches to different study areas and research questions. We start with a thorough review of existing LULC change products to identify gaps in knowledge and to determine the most efficient way forward. The analysis strategy may involve accuracy assessments, visual checks, or the comparison of satellite-derived measures of change to ground-based sources (like stream gages). We often test the efficacy of fusing LULC characterization datasets. For example, combining information on fire extents, tree heights, and tree type can be used to estimate biomass loss resulting from fire events. We perform analyses across a wide range of spatial scales, from regional extents like California’s Central Valley to national efforts covering the conterminous US. These different perspectives allow us to analyze how rates and causes vary in diverse regions throughout the country. We often use ecological regions or watersheds to separate heterogenous regions We rely on cloud-computing and high-performance computation systems to access thousands of satellite images and supply the processing power to create map time series at weekly, monthly, and annual scales. We constantly seek incremental improvements in map accuracy by testing both well-established methods as well as newer machine learning approaches. In many cases, land-cover change products can effectively tell the story about how floods, droughts, and wildfires shape the landscape. The comparative analysis of imagery before, during, and after the events is key to understanding ecological response in conjunction with climate-mediated effects. We regularly look to changes in surface water or vegetation condition to better understand how disturbances are operating to change landscapes. Connecting the “how” to the “why” leads to our next theme.

Causes of Disturbance and Recovery
PLACE explores how climate, human activities, abiotic characteristics, and past disturbances interact to shape the regional variability and magnitude of landscape change. Quantifying the underlying factors that contribute to these sorts of processes helps us understand why landscape changes occur. In the next few years, we will primarily focus on the influence of climatic drivers on select disturbance (flood, drought, and fire) and recovery processes. We are actively working with academic partners on developing robust geostatistical linkages between climate and water, wetland, and fire change patterns.
Impacts of Disturbance
PLACE is involved in investigations related to the ecological and socioeconomic impacts of landscape disturbances and subsequent recovery processes in the United States. The goal is to provide information to stakeholders for enhancing hazard preparedness, quantifying ecological effects, and anticipating the LULC composition of future landscapes.

Two current areas of concentration comprise this objective:
- The investigation of the socioeconomic risks associated with flooding in agricultural areas
- The investigation of wildfire impact on future burn severity potential, smoke emissions, and the character of vegetative recovery
- By looking at how fire intensity varies according to land cover type and number of previous burns, we aim to identify locations where land cover composition is at risk of changing, apply regional recovery signals to identify resiliency across the study area, and shed light on what degree of disturbance leads to different recovery pathways.
Below are data or web applications associated with this project.
Classification of crop types in central California from 2005 - 2020
Wetlands in the state of Arizona
National Surface Water Maps using Daily MODIS Satellite Data for the Conterminous United States, 2003-2019
DSWEmod surface water map composites generated from daily MODIS images - California
Spatially-explicit land-cover scenarios of federal lands in the northern Great Basin, 2018-2050
Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires
Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA
Data on influence of atmospheric rivers on vegetation productivity and fire patterns in the southwestern US
Below are multimedia items associated with this project.
Using Google Earth Engine to Generate Monthly-to-Weekly Maps of Surface Water
Our topic will be "Using Google Earth Engine to Generate Monthly-to-Weekly Maps of Surface Water." The presenter will be Chris Soulard with the USGS Western Geographic Science Center. Abstract: Satellite images allow scientists to study past land-use/land-cover (LULC) changes to better understand where and why changes have occurred across the landscape. The PLACE (Patterns in the Landscape –...
From California to Cambodia - Surface Water Mapping Using Cloud-Based Remote Sensing (by Christopher Soulard, USGS Research Geographer)
Below are publications associated with this project.
The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning
Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands☆
Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019
DSWEmod - The production of high-frequency surface water map composites from daily MODIS images
Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States
Application of empirical land-cover changes to construct climate change scenarios in federally managed lands
Implementation of a surface water extent model in Cambodia using cloud-based remote sensing
Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires
Landsat time series assessment of invasive annual grasses following energy development
Integrating stream gage data and Landsat imagery to complete time-series of surface water extents in Central Valley, California
Spatial patterns of meadow sensitivities to interannual climate variability in the Sierra Nevada
Removing rural roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011
Below are partners associated with this project.
Understanding the rates and causes of land-use/land-cover (LULC) change helps answer questions about what, where, how, and why the Earth’s surface is changing. Land-surface change results from human activities or natural processes like floods, droughts, and wildfires, and many of these change processes are observable in satellite imagery. The growing historical catalog of satellite images allows scientists to study past LULC changes to better understand where and why changes occur and how human and natural systems respond to them.
The mission of the PLACE (Patterns in the Landscape – Analyses of Cause and Effect) project is to inform land managers, planners, and researchers about historical and current changes to human and natural environments. PLACE focuses on floods, droughts, and fires, which are increasing in severity, extent, and frequency around the globe. Our work is based on the idea that understanding what drives these disturbance events is a necessary step for identifying management practices that can mitigate the negative human and ecological impacts.

Our research is characterized by the following three themes:
Landscape Monitoring
PLACE develops imagery-based approaches to identify and monitor the occurrence of land-cover/land-use change across the United States from 1985-present.
Our publications demonstrate the wide range of monitoring efforts in the PLACE portfolio, as well as how we tailor approaches to different study areas and research questions. We start with a thorough review of existing LULC change products to identify gaps in knowledge and to determine the most efficient way forward. The analysis strategy may involve accuracy assessments, visual checks, or the comparison of satellite-derived measures of change to ground-based sources (like stream gages). We often test the efficacy of fusing LULC characterization datasets. For example, combining information on fire extents, tree heights, and tree type can be used to estimate biomass loss resulting from fire events. We perform analyses across a wide range of spatial scales, from regional extents like California’s Central Valley to national efforts covering the conterminous US. These different perspectives allow us to analyze how rates and causes vary in diverse regions throughout the country. We often use ecological regions or watersheds to separate heterogenous regions We rely on cloud-computing and high-performance computation systems to access thousands of satellite images and supply the processing power to create map time series at weekly, monthly, and annual scales. We constantly seek incremental improvements in map accuracy by testing both well-established methods as well as newer machine learning approaches. In many cases, land-cover change products can effectively tell the story about how floods, droughts, and wildfires shape the landscape. The comparative analysis of imagery before, during, and after the events is key to understanding ecological response in conjunction with climate-mediated effects. We regularly look to changes in surface water or vegetation condition to better understand how disturbances are operating to change landscapes. Connecting the “how” to the “why” leads to our next theme.

Causes of Disturbance and Recovery
PLACE explores how climate, human activities, abiotic characteristics, and past disturbances interact to shape the regional variability and magnitude of landscape change. Quantifying the underlying factors that contribute to these sorts of processes helps us understand why landscape changes occur. In the next few years, we will primarily focus on the influence of climatic drivers on select disturbance (flood, drought, and fire) and recovery processes. We are actively working with academic partners on developing robust geostatistical linkages between climate and water, wetland, and fire change patterns.
Impacts of Disturbance
PLACE is involved in investigations related to the ecological and socioeconomic impacts of landscape disturbances and subsequent recovery processes in the United States. The goal is to provide information to stakeholders for enhancing hazard preparedness, quantifying ecological effects, and anticipating the LULC composition of future landscapes.

Two current areas of concentration comprise this objective:
- The investigation of the socioeconomic risks associated with flooding in agricultural areas
- The investigation of wildfire impact on future burn severity potential, smoke emissions, and the character of vegetative recovery
- By looking at how fire intensity varies according to land cover type and number of previous burns, we aim to identify locations where land cover composition is at risk of changing, apply regional recovery signals to identify resiliency across the study area, and shed light on what degree of disturbance leads to different recovery pathways.
Below are data or web applications associated with this project.
Classification of crop types in central California from 2005 - 2020
Wetlands in the state of Arizona
National Surface Water Maps using Daily MODIS Satellite Data for the Conterminous United States, 2003-2019
DSWEmod surface water map composites generated from daily MODIS images - California
Spatially-explicit land-cover scenarios of federal lands in the northern Great Basin, 2018-2050
Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires
Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA
Data on influence of atmospheric rivers on vegetation productivity and fire patterns in the southwestern US
Below are multimedia items associated with this project.
Using Google Earth Engine to Generate Monthly-to-Weekly Maps of Surface Water
Our topic will be "Using Google Earth Engine to Generate Monthly-to-Weekly Maps of Surface Water." The presenter will be Chris Soulard with the USGS Western Geographic Science Center. Abstract: Satellite images allow scientists to study past land-use/land-cover (LULC) changes to better understand where and why changes have occurred across the landscape. The PLACE (Patterns in the Landscape –...
From California to Cambodia - Surface Water Mapping Using Cloud-Based Remote Sensing (by Christopher Soulard, USGS Research Geographer)
From California to Cambodia - Surface Water Mapping Using Cloud-Based Remote Sensing (by Christopher Soulard, USGS Research Geographer)
Below are publications associated with this project.
The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning
Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands☆
Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019
DSWEmod - The production of high-frequency surface water map composites from daily MODIS images
Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States
Application of empirical land-cover changes to construct climate change scenarios in federally managed lands
Implementation of a surface water extent model in Cambodia using cloud-based remote sensing
Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires
Landsat time series assessment of invasive annual grasses following energy development
Integrating stream gage data and Landsat imagery to complete time-series of surface water extents in Central Valley, California
Spatial patterns of meadow sensitivities to interannual climate variability in the Sierra Nevada
Removing rural roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011
Below are partners associated with this project.