Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

Savannahs are heterogeneous environments with an important role in supporting biodiversity and providing essential ecosystem services. Due to extensive land use/cover changes and subsequent land degradation, the provision of ecosystems services from savannahs has increasingly declined over recent years. Mapping the extent and the composition of savannah environments is challenging but essential in order to improve monitoring capabilities, prevent biodiversity loss and ensure the provision of ecosystem services. Here, we tested combinations of Sentinel-1 and Sentinel-2 data from three different seasons to optimise land cover mapping, focusing in the Ngorongoro Conservation Area (NCA) in Tanzania. The NCA has a bimodal rainfall pattern and is composed of a combination savannah and woodland landscapes. The best performing model achieved an overall accuracy of 86.3 ± 1.5% and included a combination of Sentinel-1 and 2 from the dry and short-dry seasons. Our results show that the optical models outperform their radar counterparts, the combination of multisensor data improves the overall accuracy in all scenarios and this is particularly advantageous in single-season models. Regarding the effect of season, models that included the short-dry season outperform the dry and wet season models, as this season is able to provide cloud free data and is wet enough to allow for the distinction between woody and herbaceous vegetation. Additionally, the combination of more than one season is beneficial for the classification, specifically if it includes the dry or the short-dry season. Combining several seasons is, overall, more beneficial for single-sensor data; however, the accuracies varied with land cover. In summary, the combination of several seasons and sensors provides a more accurate classification, but the target vegetation types should be taken into consideration.

Download Full-text

Selawik National Wildlife Refuge land cover mapping project users guide

10.3133/70159184 ◽

1988 ◽

Keyword(s):

Land Cover ◽

Land Cover Mapping ◽

National Wildlife Refuge ◽

Wildlife Refuge

Download Full-text

Remote Sensing for Monitoring the Mountaintop Mining Landscape: Applications for Land Cover Mapping at the Individual Mine Complex Scale

10.33915/etd.6180 ◽

2015 ◽

Author(s):

Aaron E. Maxwell

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Land Cover Mapping ◽

The Individual ◽

Mountaintop Mining ◽

Complex Scale

Download Full-text

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

10.21523/gcj5.18020204 ◽

2019 ◽

Vol 2 (2) ◽

pp. 87-99

Author(s):

Shiva Pokhrel ◽

Chungla Sherpa

Keyword(s):

Land Use ◽

Land Cover ◽

Vegetation Index ◽

National Level ◽

Climate Mitigation ◽

Land Use Land Cover ◽

Conservation Area ◽

Barren Land ◽

Wide Range ◽

Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

Download Full-text

Optical and Radar Data Analysis for Land Use Land Cover Mapping in Peru

10.21523/gcj1.19030102 ◽

2019 ◽

Vol 3 (1) ◽

pp. 14-27

Author(s):

Barry Haack ◽

Ron Mahabir

Keyword(s):

Land Use ◽

Land Cover ◽

Window Size ◽

Radar Data ◽

Optical Data ◽

Land Cover Mapping ◽

Land Use Land Cover ◽

Texture Image ◽

Site Class ◽

Spectral Signatures

This analysis determined the best individual band and combinations of various numbers of bands for land use land cover mapping for three sites in Peru. The data included Landsat Thematic Mapper (TM) optical data, PALSAR L-band dual-polarized radar, and derived radar texture images. Spectral signatures were first obtained for each site class and separability between classes determined using divergence measures. Results show that the best single band for analysis was a TM band, which was different for each site. For two of the three sites, the second best band was a radar texture image from a large window size. For all sites the best three bands included two TM bands and a radar texture image. The original PALSAR bands were of limited value. Finally upon further analysis it was determined that no more than six bands were needed for viable classification at each study site.

Download Full-text