Exploring the spatial and temporal dynamics of land use in Xizhuang watershed of Yunnan, southwest China

Xu, Jianchu; XiHui, Ai; Xi-qing, Deng

doi:10.1016/j.jag.2005.06.008

Cited by 23 publications

(3 citation statements)

References 10 publications

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“…Since we wanted to classify Landsat imagery as early as 1986, when no adequate reference data to train a supervised classifier was available, we used a hybrid of unsupervised and supervised techniques combined with knowledge-based interpretation (figure 2; see description of Yunnan and detailed methods in supplementary (available online at stacks.iop.org/ERL/17/014003/mmedia)). We first defined nine land cover classes in the province using a combination of field observations, expert knowledge coupled with visual inspection of high-resolution imagery from Google Earth (www.google.com/earth/desktop, accessed on 5 July 2019) (Olofsson et al 2014), and existing land cover maps (Liu et al 2003, 2010, 2014b, Xu et al 2005, Diallo et al 2009, Zhao et al 2012, Lu et al 2015, Ning et al 2018, Zhang et al 2019a, Su et al 2020. We defined nine land cover classes, comprised of non-vegetated classes, namely water bodies (WATs), snowed regions (SNO), and built-up and bare rock areas (BURs); non-natural vegetation areas, namely croplands (CROs), tree plantations (TRPs), and bare ground (BAG); and natural vegetation areas, which are forests (FOR), which have closed tree canopies, and two savanna classes, which have open canopies: grassy, sparse-canopied PRKs and denser-canopied WDLs.…”

Section: Generating Land Cover Maps and Detecting Inter-decadal Changesmentioning

confidence: 99%

“…The province might also continue to observe an uptick in stable forest cover, as China continues its existing programs to conserve and expand forests (Chen et al 2019). Policies affecting Yunnan include the sloping land conversion program (SLCP) to prevent cultivation on land with slopes steeper than 25 • (Xu et al 2005), and the GTGP established in 1999 to restore natural ecosystems through the return of former croplands back to forests or savannas (Chen et al 2019). A good policy model for savannas could be the SLCP, as our drivers analysis showed that steeper slopes did in fact contribute positively to PRK and WDL conversion from farmlands and non-vegetation areas.…”

Section: Conservation Recommendationsmentioning

confidence: 99%

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Greater loss and fragmentation of savannas than forests over the last three decades in Yunnan Province, China

Lapuz

Jaojoco

Reyes

et al. 2021

Environ. Res. Lett.

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Yunnan Province, southwest China, has a monsoonal climate suitable for a mix of fire-driven savannas and fire-averse forests as alternate stable states, and has vast areas with savanna physiognomy. Presently, savannas are only formally recognised in the dry valleys of the region, and a no-fire policy has been enforced nationwide since the 1980s. Misidentification of savannas as forests may have contributed to their low protection level and fire-suppression may be contributing to vegetation change towards forest states through woody encroachment. Here, we present an analysis of vegetation and land-use change in Yunnan for years 1986, 1996, 2006, and 2016 by classifying Landsat imagery using a hybrid of unsupervised and supervised classification. We assessed how much savanna area had changed over the three decades (area loss, fragmentation), and of this how much was due to direct human intervention versus vegetation transition. We also assessed how climate (mean annual temperature, aridity), landscape accessibility (slope, distance to roads), and fire had altered transition rates. Our classification yielded accuracy values of 77.89%, 82.16%, 94.93%, and 86.84% for our four maps, respectively. In 1986, savannas had the greatest area of any vegetation type in Yunnan at 40.30%, whereas forest cover was 30.78%. Savanna coverage declined across the decades mainly due to a drop in open parkland savannas, while forest cover remained stable. Savannas experienced greater fragmentation than forests. Savannas suffered direct loss of coverage to human uses and to woody encroachment. Savannas in more humid environments switched to denser vegetation at a higher rate. Fire slowed the rate of conversion away from savanna states and promoted conversion towards them. We identified remaining savannas in Yunnan that can be considered when drafting future protected areas. Our results can inform more inclusive policy-making that considers Yunnan’s forests and savannas as distinct vegetation types with different management needs.

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Section: Generating Land Cover Maps and Detecting Inter-decadal Changesmentioning

confidence: 99%

Section: Conservation Recommendationsmentioning

confidence: 99%

Greater loss and fragmentation of savannas than forests over the last three decades in Yunnan Province, China

Lapuz

Jaojoco

Reyes

et al. 2021

Environ. Res. Lett.

View full text Add to dashboard Cite

show abstract

“…And despite the often documented inferiority in classification success, maximum likelihood classification is still one of the most widely used classification algorithms (Jensen, 2005), most likely also due to advantages in data handling and processing times (Paola and Schowengerdt, 1995). Therefore, many applied landscape-scale studies and land use/land cover research rely on these standard classification approaches (Brandt and Townsend, 2006;Cushman and Wallin, 2000;Jianchu et al, 2005;Joy et al, 2003;Ruiz-Luna and Berlanga-Robles, 2003). In contrast, advanced approaches are primarily limited to methodological studies for optimising the classification process, often using only very limited sample sizes (Fassnacht et al, 2006;Foody, 2001;Kavzoglu and Mather, 2003;Kavzoglu and Reis, 2008;Ouyang and Ma, 2006;Paola and Schowengerdt, 1997;Yemefack et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Classifiers vs. input variables—The drivers in image classification for land cover mapping

Heinl

Walde

Tappeiner

et al. 2009

International Journal of Applied Earth Observation and Geoinfor

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Response of hydrological processes to land‐cover and climate changes in Kejie watershed, south‐west China

Xu²,

Luo

et al. 2009

Hydrological Processes

169

106

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Abstract:Land-cover/climate changes and their impacts on hydrological processes are of widespread concern and a great challenge to researchers and policy makers. Kejie Watershed in the Salween River Basin in Yunnan, south-west China, has been reforested extensively during the past two decades. In terms of climate change, there has been a marked increase in temperature. The impact of these changes on hydrological processes required investigation: hence, this paper assesses aspects of changes in land cover and climate. The response of hydrological processes to land-cover/climate changes was examined using the Soil and Water Assessment Tool (SWAT) and impacts of single factor, land-use/climate change on hydrological processes were differentiated. Land-cover maps revealed extensive reforestation at the expense of grassland, cropland, and barren land. A significant monotonic trend and noticeable changes had occurred in annual temperature over the long term. Long-term changes in annual rainfall and streamflow were weak; and changes in monthly rainfall (May, June, July, and September) were apparent. Hydrological simulations showed that the impact of climate change on surface water, baseflow, and streamflow was offset by the impact of land-cover change. Seasonal variation in streamflow was influenced by seasonal variation in rainfall. The earlier onset of monsoon and the variability of rainfall resulted in extreme monthly streamflow. Land-cover change played a dominant role in mean annual values; seasonal variation in surface water and streamflow was influenced mainly by seasonal variation in rainfall; and land-cover change played a regulating role in this. Surface water is more sensitive to land-cover change and climate change: an increase in surface water in September and May due to increased rainfall was offset by a decrease in surface water due to land-cover change. A decrease in baseflow caused by changes in rainfall and temperature was offset by an increase in baseflow due to land-cover change.

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Exploring the spatial and temporal dynamics of land use in Xizhuang watershed of Yunnan, southwest China

Cited by 23 publications

References 10 publications

Greater loss and fragmentation of savannas than forests over the last three decades in Yunnan Province, China

Greater loss and fragmentation of savannas than forests over the last three decades in Yunnan Province, China

Classifiers vs. input variables—The drivers in image classification for land cover mapping

Response of hydrological processes to land‐cover and climate changes in Kejie watershed, south‐west China

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