Using MODIS NDVI phenoclasses and phenoclusters to characterize wildlife habitat

Mexican spotted owl as a case study

Serra J. Hoagland, Paul Beier, Danny Lee

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Most uses of remotely sensed satellite data to characterize wildlife habitat have used metrics such as mean NDVI (Normalized Difference Vegetation Index) in a year or season. These simple metrics do not take advantage of the temporal patterns in NDVI within and across years and the spatial arrangement of cells with various temporal NDVI signatures. Here we use 13 years of data from MODIS (Moderate Resolution Imaging Spectroradiometer) to bin individual MODIS pixels (5.3 ha) into phenoclasses, where each phenoclass consists of pixels with a particular temporal profile of NDVI, regardless of spatial location. We present novel procedures that assign sites to phenoclusters, defined as particular composition of phenoclasses within a 1 km radius. We apply these procedures to Mexican spotted owl (Strix occidentalis lucida) nesting locations in the Sacramento Mountain range in south-central New Mexico. Phenoclasses at owl nest sites and phenoclusters around owl nest sites differed from those at and around points randomly placed in forest types that are known to support nesting owls. Stand exam data showed that the phenoclasses associated with owl nest sites are dominated by Douglas-fir (Pseudotsuga menziesii) and white fir (Abies concolor). The availability of phenoclusters and phenoclasses on Mescalero Apache tribal lands differed from those on adjacent National Forest lands within the Sacramento Mountain, consistent with different elevations and forest management practices. Nonetheless owls predominately used the same phenoclasses and phenoclusters in both land ownerships. MODIS phenoclasses and phenoclusters offer a useful means of remotely identifying forest conditions suitable for wildlife. Because the remote sensing data are freely available and regularly updated, they can be part of a cost effective approach to monitor and assess forested wildlife habitat over large temporal and spatial scales.

Original languageEnglish (US)
JournalForest Ecology and Management
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

wildlife habitats
moderate resolution imaging spectroradiometer
Strigiformes
NDVI
MODIS
nest site
case studies
nesting sites
pixel
Pseudotsuga menziesii
remote sensing
tribal lands
Abies concolor
mountains
landownership
land ownership
forest management
national forests
satellite data
management practice

Keywords

  • Clustering
  • Land surface phenology
  • Mexican spotted owl
  • MODIS
  • NDVI
  • Phenoclasses
  • Tribal forest management

ASJC Scopus subject areas

  • Forestry
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

Cite this

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title = "Using MODIS NDVI phenoclasses and phenoclusters to characterize wildlife habitat: Mexican spotted owl as a case study",
abstract = "Most uses of remotely sensed satellite data to characterize wildlife habitat have used metrics such as mean NDVI (Normalized Difference Vegetation Index) in a year or season. These simple metrics do not take advantage of the temporal patterns in NDVI within and across years and the spatial arrangement of cells with various temporal NDVI signatures. Here we use 13 years of data from MODIS (Moderate Resolution Imaging Spectroradiometer) to bin individual MODIS pixels (5.3 ha) into phenoclasses, where each phenoclass consists of pixels with a particular temporal profile of NDVI, regardless of spatial location. We present novel procedures that assign sites to phenoclusters, defined as particular composition of phenoclasses within a 1 km radius. We apply these procedures to Mexican spotted owl (Strix occidentalis lucida) nesting locations in the Sacramento Mountain range in south-central New Mexico. Phenoclasses at owl nest sites and phenoclusters around owl nest sites differed from those at and around points randomly placed in forest types that are known to support nesting owls. Stand exam data showed that the phenoclasses associated with owl nest sites are dominated by Douglas-fir (Pseudotsuga menziesii) and white fir (Abies concolor). The availability of phenoclusters and phenoclasses on Mescalero Apache tribal lands differed from those on adjacent National Forest lands within the Sacramento Mountain, consistent with different elevations and forest management practices. Nonetheless owls predominately used the same phenoclasses and phenoclusters in both land ownerships. MODIS phenoclasses and phenoclusters offer a useful means of remotely identifying forest conditions suitable for wildlife. Because the remote sensing data are freely available and regularly updated, they can be part of a cost effective approach to monitor and assess forested wildlife habitat over large temporal and spatial scales.",
keywords = "Clustering, Land surface phenology, Mexican spotted owl, MODIS, NDVI, Phenoclasses, Tribal forest management",
author = "Hoagland, {Serra J.} and Paul Beier and Danny Lee",
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N2 - Most uses of remotely sensed satellite data to characterize wildlife habitat have used metrics such as mean NDVI (Normalized Difference Vegetation Index) in a year or season. These simple metrics do not take advantage of the temporal patterns in NDVI within and across years and the spatial arrangement of cells with various temporal NDVI signatures. Here we use 13 years of data from MODIS (Moderate Resolution Imaging Spectroradiometer) to bin individual MODIS pixels (5.3 ha) into phenoclasses, where each phenoclass consists of pixels with a particular temporal profile of NDVI, regardless of spatial location. We present novel procedures that assign sites to phenoclusters, defined as particular composition of phenoclasses within a 1 km radius. We apply these procedures to Mexican spotted owl (Strix occidentalis lucida) nesting locations in the Sacramento Mountain range in south-central New Mexico. Phenoclasses at owl nest sites and phenoclusters around owl nest sites differed from those at and around points randomly placed in forest types that are known to support nesting owls. Stand exam data showed that the phenoclasses associated with owl nest sites are dominated by Douglas-fir (Pseudotsuga menziesii) and white fir (Abies concolor). The availability of phenoclusters and phenoclasses on Mescalero Apache tribal lands differed from those on adjacent National Forest lands within the Sacramento Mountain, consistent with different elevations and forest management practices. Nonetheless owls predominately used the same phenoclasses and phenoclusters in both land ownerships. MODIS phenoclasses and phenoclusters offer a useful means of remotely identifying forest conditions suitable for wildlife. Because the remote sensing data are freely available and regularly updated, they can be part of a cost effective approach to monitor and assess forested wildlife habitat over large temporal and spatial scales.

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