A Novel Land Cover Classification Map Based on a MODIS Time-Series in Xinjiang, China

Lu, Linlin; Kuenzer, Claudia; Guo, Huadong; Li, Qingting; Long, Tengfei; Li, Xinwu

doi:10.3390/rs6043387

Cited by 23 publications

(16 citation statements)

References 36 publications

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“…The entire area can be divided to northern and southern parts by Tianshan Mountains. The land is mainly covered by grassland and sandy desert [37][38][39]. Forest scatters within high mountains and along rivers.…”

Section: Study Areamentioning

confidence: 99%

Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring

Kuenzer

Wang

et al. 2015

Remote Sensing

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Understanding the spatial and temporal dynamics of vegetation is essential in drylands. In this paper, we evaluated three vegetation indices, namely the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Enhanced Vegetation Index (EVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Surface-Reflectance Product in the Xinjiang Uygur Autonomous Region, China (XUAR), to assess index time series' suitability for monitoring vegetation dynamics in a dryland environment. The mean annual VI and its variability were generated and analyzed from the three VI time series for the period 2001-2012 across XUAR. Two phenological metrics, start of the season (SOS) and end of the season (EOS), were detected and compared for each vegetation type. The mean annual VI images showed similar spatial patterns of vegetation conditions with varying magnitudes. The EVI exhibited high uncertainties in sparsely vegetated lands and forests. The phenological metrics derived from the three VIs are consistent for most vegetation types, with SOS and EOS generated from NDVI showing the largest deviation.

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Section: Study Areamentioning

confidence: 99%

Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring

Kuenzer

Wang

et al. 2015

Remote Sensing

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“…In addition to being timely and cost effective [18], satellite based monitoring enables a transparent and reliable [19] means to monitor forest cover conditions. Although errors in the interpretation of spectral response and human bias exist [20,21], remote sensing remains to play key role in identifying and estimating deforested and reforested areas [22,23]. In the Himalayas, the application of remote sensing was introduced in the mid-1980s [24] to identify and analyze the Land Use Land Cover (LULC) pattern [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan

et al. 2016

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Abstract:The Himalayan mountain forest ecosystem has been degrading since the British ruled the area in the 1850s. Local understanding of the patterns and processes of degradation is desperately required to devise management strategies to halt this degradation and provide long-term sustainability. This work comprises a satellite image based study in combination with national expert validation to generate sub-district level statistics for forest cover over the Western Himalaya, Pakistan, which accounts for approximately 67% of the total forest cover of the country. The time series of forest cover maps (1990, 2000, 2010) reveal extensive deforestation in the area. Indeed, approximately 170,684 ha of forest has been lost, which amounts to 0.38% per year clear cut or severely degraded during the last 20 years. A significant increase in the rate of deforestation is observed in the second half of the study period, where much of the loss occurs at the western borders along with Afghanistan. The current study is the first systematic and comprehensive effort to map changes to forest cover in Northern Pakistan. Deforestation hotspots identified at the sub-district level provide important insight into deforestation patterns, which may facilitate the development of appropriate forest conservation and management strategies in the country.

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“…In XUAR, large areas of deserts and bare rocks have high spectral responses in short-wavelength infrared (SWIR) band [34]. Water usually has low reflectance along the spectrum.…”

Section: Modis-based Water Body Extractionmentioning

confidence: 99%

MODIS-Derived Spatiotemporal Changes of Major Lake Surface Areas in Arid Xinjiang, China, 2000–2014

Wang

et al. 2015

Water

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Inland water bodies, which are critical freshwater resources for arid and semi-arid areas, are very sensitive to climate change and human disturbance. In this paper, we derived a time series of major lake surface areas across Xinjiang Uygur Autonomous Region (XUAR), China, based on an eight-day MODIS time series in 500 m resolution from 2000 to 2014. A classification approach based on water index and dynamic threshold selection was first developed to accommodate varied spectral features of water pixels at different temporal steps. The overall classification accuracy for a MODIS-derived water body is 97% compared to a water body derived using Landsat imagery. Then, monthly composites of water bodies were derived for the months of April, July, and September to identify seasonal patterns and inter-annual dynamics of 10 major lakes (>100 km 2 ) in XUAR. Our results indicate that the changing trends of surface area of major lakes varied across the region. The surface areas of the Ebinur and Bosten Lakes showed a significant shrinking trend. The Ulungur-Jili Lake remained relatively stable during the entire period. OPEN ACCESSWater 2015, 7 5732For mountain lakes, the Barkol Lake showed a decreasing trend in April and July, but the Sayram Lake showed a significant expanding trend in September. The four plateau lakes exhibited significant expanding trends in all three seasons except for Arkatag Lake in July. The shrinking of major lakes reflects severe anthropogenic impacts due to agricultural and industrial needs, in addition to the impact of climate change. The pattern of lake changes across the XUAR can provide insight into the impact of climate change and human activities on regional water resources in this arid and semi-arid region.

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A Novel Land Cover Classification Map Based on a MODIS Time-Series in Xinjiang, China

Cited by 23 publications

References 36 publications

Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring

Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring

Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan

MODIS-Derived Spatiotemporal Changes of Major Lake Surface Areas in Arid Xinjiang, China, 2000–2014

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