Simulating Stakeholder-Based Land-Use Change Scenarios and Their Implication on Above-Ground Carbon and Environmental Management in Northern Thailand

Lippe, Melvin; Hilger, Thomas; Sudchalee, Sureeporn; Wechpibal, Naruthep; Jintrawet, Attachai; Cadisch, Georg

doi:10.3390/land6040085

Cited by 11 publications

(8 citation statements)

References 38 publications

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“…Some models project changes by analyzing socio-economic and environmental drivers together (Veldkamp and Verburg, 2004). There is a need to integrate model results into landscape planning because environmental management is a typical purpose (Lippe et al 2017;Convertino and Valverde Jr., 2013). It is useful to know the implications of an extrapolation of recent trends so that decision-makers can understand the trajectory of the system.…”

Section: Introductionmentioning

confidence: 99%

Intensity Analysis and the Figure of Merit’s components for assessment of a Cellular Automata – Markov simulation model

Varga

Pontius

Singh

et al. 2019

Ecological Indicators

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Some popular metrics to evaluate land change simulation models are misleading. Therefore, land change scientists have called for the development of methods to evaluate various aspects of modelling applications. This article answers the call by giving novel methods to compare three types of land change: 1) reference change during the calibration time interval, 2) simulation change during the validation time interval, and 3) reference change during the validation time interval. We compare these changes by using Intensity Analysis' three levels and the Figure of Merit's four components: Misses, Hits, Wrong Hits and False Alarms. We illustrate the concepts by applying a Cellular Automata -Markov land change model to a case study in northeast Hungary. We used reference maps of five land categories to calibrate the model during 2000-2006, then to validate the simulation during 2006-2012. Intensity Analysis' time interval level shows that the simulation change and the reference change decelerated from 2000-2006 to 2006-2012. Intensity Analysis' category level shows that the simulation losses were less than what a pure Markov chain would have dictated. Intensity Analysis' transition level shows that the model's Markov algorithm simulated correctly that the gain of Forest targeted Agriculture and Wetland. The Figure of Merit's components reveals more allocation error than quantity error. Our collection of metrics show that more error derived from the Cellular Automata algorithm than from the Markov algorithm. We recommend that scientists use Intensity Analysis and the Figure of Merit's components to reveal various fundamental aspects of modelling applications.

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Section: Introductionmentioning

confidence: 99%

Intensity Analysis and the Figure of Merit’s components for assessment of a Cellular Automata – Markov simulation model

Varga

Pontius

Singh

et al. 2019

Ecological Indicators

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“…In mountainous regions, agricultural expansion and forest loss often result in serious environmental degradation (e.g. Sidle et al, 2006;Bruun, Neergaard, Lawrence, & Ziegler, 2009;Kitchaicharoen, Suebpongsang, & Sangchyoswat, 2015;Lippe et al, 2017). The loss of the protective function of forests in sheltering soil surfaces and anchoring soil and rocks can trigger landslides, soil erosion, and reductions in water quality (Bruun et al, 2009;Sidle et al, 2006).…”

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confidence: 99%

Accelerating forest loss in Southeast Asian Massif in the 21st century: A case study in Nan Province, Thailand

Zeng

Gower

Wood

2018

Global Change Biology

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Farmers are carving a new agricultural frontier from the forests in the Southeast Asian Massif (SAM) in the 21st century, triggering significant environment degradation at the local scale; however, this frontier has been missed by existing global land use and forest loss analyses. In this paper, we chose Thailand's Nan Province, which is located in the geometric center of SAM, as a case study, and combined high resolution forest cover change product with a fine-scale land cover map to investigate land use dynamics with respect to topography in this region. Our results show that total forest loss in Nan Province during 2001-2016 was 66,072 ha (9.1% of the forest cover in 2000), and that the majority of this lost forest (92%) had been converted into crop (mainly corn) fields by 2017. Annual forest loss is significantly correlated with global corn price (p < 0.01), re-confirming agricultural expansion as a key driver of forest loss in Nan Province. Along with the increasing global corn price, forest loss in Nan Province has accelerated at a rate of 2,616 ± 730 ha per decade (p < 0.01). Global corn price peaked in 2012, in which year annual forest loss also reached its peak (7,523 ha); since then, the location of forest loss has moved to steeper land at higher elevations. Spatially, forest loss driven by this smallholder agricultural expansion emerges as many small patches that are not recognizable even at a moderate spatial resolution (e.g. 300 m). It explains how existing global land use/cover change products have missed the widespread and rapid forest loss in SAM. It also highlights the importance of high-resolution observations to evaluate the environmental impacts of agricultural expansion and forest loss in SAM, including, but not limited to, the impacts on the global carbon cycle, regional hydrology, and local environmental degradation.

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“…For examples, the effects of land-use changes on HQ and landscape patterns were obtained using CA-Markov and CLUE-s model [17]. Lippe et al [23] predicted the land-use changes and evaluated their impacts on above-ground carbon and environmental control in the north of Thailand by the combination of the Dyna-CLUE model and carbonstock accounting procedure. Adhikari et al [24] used Dyna-CLUE and the SWAT model to simulate land-use scenarios and their implication on groundwater recharge in the Ho Chi Minh City, Vietnam.…”

Section: Introductionmentioning

confidence: 99%

Strategies to Mitigate the Deteriorating Habitat Quality in Dong Trieu District, Vietnam

Shen

Lai

2022

Land

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Dong Trieu district is a vital connection for territorial ecological security and human welfare between Hanoi (the capital of Vietnam) and Quang Ninh province. Therefore, habitat quality (HQ) is of extraordinary importance to the area’s sustainable development. The ArcGIS platform, Dyna-CLUE, and InVEST models were utilized in this study to assess the spatial and temporal transformations of land use and the changes of HQ in 2030 under various scenarios, with intentions to find strategies that may mitigate the HQ’s deteriorating trend in the district. Simulated results indicated that, assuming the development is maintained as usual, the average HQ of the District at 2030 could diminish by 0.044 from that of 2019 (a four-times decrease compared to the previous decade). Cases comprised of four basic scenarios, including development as usual, built-up expansion slowdown, forest protection emphasized, and agricultural land conversion, were used to identify potential strategies to mitigate the deteriorating trend. Simulated results revealed that keeping the built-up expansion rate lower than 100 ha y−1, the deforestation rate lower than 20 ha y−1, and preferring orchards over agricultural land conversion is required to limit the drop in HQ to within 0.01 in the next decade. Other than the existing population growth control policy, new guidelines such as (1) changing urban expansion type from outward to upward to control the built-up expansion rate, (2) substituting forest-harming industries to forest-preservation industries to reduce deforestation rate, (3) encouraging orchards preferred over agricultural land conversion to increase incomes while maintaining higher habitat quality, (4) practicing better farming technologies to improve crop production and to alleviate potential food security issues due to considerable reduction in cropland, and (5) promoting Green Infrastructure and the Belt and Road Initiative to increase urban green cover and raise residents’ income should be considered in designing the new mitigation strategies.

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Simulating Stakeholder-Based Land-Use Change Scenarios and Their Implication on Above-Ground Carbon and Environmental Management in Northern Thailand

Cited by 11 publications

References 38 publications

Intensity Analysis and the Figure of Merit’s components for assessment of a Cellular Automata – Markov simulation model

Intensity Analysis and the Figure of Merit’s components for assessment of a Cellular Automata – Markov simulation model

Accelerating forest loss in Southeast Asian Massif in the 21st century: A case study in Nan Province, Thailand

Strategies to Mitigate the Deteriorating Habitat Quality in Dong Trieu District, Vietnam

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