Remote sensing change detection for ecological monitoring in United States protected areas

Willis, Katherine S.

doi:10.1016/j.biocon.2014.12.006

Cited by 210 publications

(136 citation statements)

References 97 publications

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“…QB is more often used as a 'ground truth' dataset in ecological studies (Willis 2015) and somewhat less often for high-level analysis (such as spectral unmixing) because of its broadband spectral resolution. It is worth noting that there is no conceptual reason why SMA cannot be applied to any type of calibrated, multispectral imagery.…”

Section: Limitations Of Remotely Sensed Data For Inferring Burn Severitymentioning

confidence: 99%

Indicators of burn severity at extended temporal scales: a decade of ecosystem response in mixed-conifer forests of western Montana

Lewis

Hudak

Robichaud

et al. 2017

Int. J. Wildland Fire

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Abstract. We collected field and remotely sensed data spanning 10 years after three 2003 Montana wildfires to monitor ecological change across multiple temporal and spatial scales. Multiple endmember spectral mixture analysis was used to create post-fire maps of: char, soil, green (GV) and non-photosynthetic ( Initial estimates of char and NPV from the HS images were significantly correlated with their ground-measured counterparts (r ¼ 0.60 (P ¼ 0.03) and 0.68 (P ¼ 0.01) respectively), whereas HS GV and Landsat GV were correlated with canopy GV (r ¼ 0.75 and 0.70 (P ¼ 0.003) respectively). HS imagery had stronger direct correlations with all classes of fine-scale ground data than Landsat and also had stronger predictive correlations with 10-year canopy data (r ¼ 0.65 (P ¼ 0.02) to 0.84 (P ¼ 0.0003)). There was less than 5% understorey GV cover on the sites initially, but by 2013, it had increased to nearly 60% regardless of initial condition. The data suggest it took twice as long for understorey GV and NPV to replace char and soil as primary ground cover components on the highburn-severity sites compared with other sites.

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Section: Limitations Of Remotely Sensed Data For Inferring Burn Severitymentioning

confidence: 99%

Indicators of burn severity at extended temporal scales: a decade of ecosystem response in mixed-conifer forests of western Montana

Lewis

Hudak

Robichaud

et al. 2017

Int. J. Wildland Fire

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“…By doing a review of many studies, in the context of ecological monitoring, Willis (2015) suggested that change detection has historically been used to look at changes in land use/land cover and disturbance using binary comparisons contrasting conditions during two discrete time periods. In assessing changes in environmental changes, NDVI is a commonly used indicator, especially for monitoring plant phenology changes.…”

Section: Methodsmentioning

confidence: 99%

“…Remote sensing data enables the identification, delineating, and monitoring of pollution sources and affected areas, including derelict land, and changes in surface land use and to water bodies (Charou et al 2010). Remote sensing allows for costand time-efficient monitoring of landscapes vital to the conservation of natural resources, ecosystems, and biodiversity (Willis 2015). Taking into account the advantages possessed by the use of remote sensing data, the authors are interested to use remote sensing methods to monitor the environmental damage caused by mining activities in Indonesia.…”

Section: Introductionmentioning

confidence: 99%

DETECTING THE AREA DAMAGE DUE TO COAL MINING ACTIVITIES USING LANDSAT MULTITEMPORAL (Case Study: Kutai Kartanegara, East Kalimantan)

suwarsono

Haryani²,

Prasasti³

et al. 2018

IJReSES

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Abstract. Coal is one of the most mining commodities to date, especially to supply both national and international energy needs. Coal mining activities that are not well managed will have an impact on the occurrence of environmental damage. This research tried to utilize the multitemporal Landsat data to analyze the land damage caused by coal mining activities. The research took place at several coal mine sites in East Kalimantan Province. The method developed in this research is the method of change detection. The study tried to know the land damage caused by mining activities using NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), NDWI (Normalized Difference Water Index) and GEMI (Global Environment Monitoring Index) parameter based change detection method. The results showed that coal mine area along with the damage that occurred in it can be detected from multitemporal Landsat data using NDSI value-based change detection method.The area damage due to coal mining activities can be classified into high, moderate, and low classes based on the mean and standard deviation of NDSI changes (ΔNDSI). The results of this study are expected to be used to support government efforts and mining managers in post-mining land reclamation activities.

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“…Comprehensive analyses of FH have been conducted based on LandTrend and LandSat Time Series (LTS) [392][393][394][395][396]. Comprehensive information and reviews of remote-sensing change detection and ecological monitoring can be found in [397,398].…”

Section: Monitoring Stress On Vegetation In Fes With Rsmentioning

confidence: 99%

Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

et al. 2016

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Anthropogenic stress and disturbance of forest ecosystems (FES) has been increasing at all scales from local to global. In rapidly changing environments, in-situ terrestrial FES monitoring approaches have made tremendous progress but they are intensive and often integrate subjective indicators for forest health (FH). Remote sensing (RS) bridges the gaps of these limitations, by monitoring indicators of FH on different spatio-temporal scales, and in a cost-effective, rapid, repetitive and objective manner. In this paper, we provide an overview of the definitions of FH, discussing the drivers, processes, stress and adaptation mechanisms of forest plants, and how we can observe FH with RS. We introduce the concept of spectral traits (ST) and spectral trait variations (STV) in the context of FH monitoring and discuss the prospects, limitations and constraints. Stress, disturbances and resource limitations can cause changes in FES taxonomic, structural and functional diversity; we provide examples how the ST/STV approach can be used for monitoring these FES characteristics. We show that RS based assessments of FH indicators using the ST/STV approach is a competent, affordable, repetitive and objective technique for monitoring. Even though the possibilities for observing the taxonomic diversity of animal species is limited with RS, the taxonomy of forest tree species can be recorded with RS, even though its accuracy is subject to certain constraints. RS has proved successful for monitoring the impacts from stress on structural and functional diversity. In particular, it has proven to be very suitable for recording the short-term dynamics of stress on FH, which cannot be cost-effectively recorded using in-situ methods. This paper gives an overview of the ST/STV approach, whereas the second paper of this series concentrates on discussing in-situ terrestrial monitoring, in-situ RS approaches and RS sensors and techniques for measuring ST/STV for FH.

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Remote sensing change detection for ecological monitoring in United States protected areas

Cited by 210 publications

References 97 publications

Indicators of burn severity at extended temporal scales: a decade of ecosystem response in mixed-conifer forests of western Montana

Indicators of burn severity at extended temporal scales: a decade of ecosystem response in mixed-conifer forests of western Montana

DETECTING THE AREA DAMAGE DUE TO COAL MINING ACTIVITIES USING LANDSAT MULTITEMPORAL (Case Study: Kutai Kartanegara, East Kalimantan)

Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

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