Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

Bagan, Hasi; Millington, Andrew; Takeuchi, Wataru; Yamagata, Yoshiki

doi:10.1002/ldr.3692

Cited by 12 publications

(7 citation statements)

References 61 publications

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“…Lark et al (2020), Wang (2020) and Zheng et al (2019) all indicated that the compensated cropland was generally less productive but had a greater irrigation intensity and ecological cost. Therefore, cropland expansion and displacement are among the most important factors for deforestation and biodiversity loss (Bagan et al, 2020; Ordway et al, 2017; Sheng et al, 2022; Xiong et al, 2021). Several studies have considered cropland displacement as an indirect impact of urban land expansion (Ke et al, 2018; Yang et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Telecoupling indirect ecological impacts of urban expansion in China from the perspective of the food trade

Jia

Jiao

et al. 2023

Land Degrad Dev

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A comprehensive evaluation of the ecological cost of urban expansion is crucial for preventing ecosystem degradation and improving ecosystem governance. However, the indirect impacts of urban expansion through cropland displacement are grossly underestimated, particularly the spillover effects on distant regions. This study proposed a telecoupling framework for the total indirect ecological losses (TIEL) of urban expansion. It was divided into the near losses (NIEL) and distant losses (DIEL), depending on whether cropland displacement occurs inside or outside the region. An inter‐provincial network of DIEL can also be constructed by ecological impact embodied in food trade with other regions. We found that approximately 80% of urban expansion occurred on croplands, which caused indirect loss of 86,586 km2 of ecological land through cropland displacement in China during 2000–2019. The total indirect ecological losses were 8.4 times greater than direct losses at the average of all provinces. Food trade induced more serious indirect ecological losses owing to the higher yield difference between encroached cropland import regions and new cropland in export regions. The proportion of DIEL in TIEL was more than 50% in developed regions such as Beijing, Shanghai, Tianjin, and Jiangsu. The distant impacts of urban expansion in the eastern coastal provinces were mainly transferred to north‐eastern China and the rest of the world. This study identified the teleconnection between local urban development and distant environments and infromed inter‐regional ecological compensation policies to mitigate regional inequalities.

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Section: Introductionmentioning

confidence: 99%

“…Therefore, cropland expansion and displacement are among the most important factors for deforestation and biodiversity loss (Bagan et al, 2020;Ordway et al, 2017;Sheng et al, 2022;Xiong et al, 2021). Several studies have considered cropland displacement as an indirect impact of urban land expansion (Ke et al, 2018;Yang et al, 2020).…”

mentioning

confidence: 99%

Telecoupling indirect ecological impacts of urban expansion in China from the perspective of the food trade

Jia

Jiao

et al. 2023

Land Degrad Dev

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“…In terms of crop classification, some early studies chose to fuse the images during the growth periods of crops [23]; later, the time-series data obtained during crop growth were found to be able to fully reflect the phenological features of different crops and their changes in different physical and chemical parameters and indicators [24], and also to contribute greatly to improving accuracy in crop classification [25]. It is therefore popular for research [26][27][28] to use the data fusion method of calculating the median reflectance or index median of time-series images [29].…”

Section: Introductionmentioning

confidence: 99%

Crop Mapping in the Sanjiang Plain Using an Improved Object-Oriented Method Based on Google Earth Engine and Combined Growth Period Attributes

Zhang²,

Luo

et al. 2022

Remote Sensing

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In recent years, the scale of rural land transfer has gradually expanded, and the phenomenon of non-grain-oriented cultivated land has emerged. Obtaining crop planting information is of the utmost importance to guaranteeing national food security; however, the acquisition of the spatial distribution of crops in large-scale areas often has the disadvantages of excessive calculation and low accuracy. Therefore, the IO-Growth method, which takes the growth stage every 10 days as the index and combines the spectral features of crops to refine the effective interval of conventional wavebands for object-oriented classification, was proposed. The results were as follows: (1) the IO-Growth method obtained classification results with an overall accuracy and F1 score of 0.92, and both values increased by 6.98% compared to the method applied without growth stages; (2) the IO-Growth method reduced 288 features to only 5 features, namely Sentinel-2: Red Edge1, normalized difference vegetation index, Red, short-wave infrared2, and Aerosols, on the 261st to 270th days, which greatly improved the utilization rate of the wavebands; (3) the rise of geographic data processing platforms makes it simple to complete computations with massive data in a short time. The results showed that the IO-Growth method is suitable for large-scale vegetation mapping.

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“…To achieve a suitable resolution for LCZ classification, the common approach to generate LCZ maps is to preprocess the remote sensing images by resampling or to post-process the classified LCZ maps by resampling. Considering the different spatial resolutions of LCZ maps and LST data, as an alternative, the grid-cell-based method has been found to be a powerful tool for linking data at different spatial resolutions; it enables the user to fine-tune an analysis of data from multiple sources and to strike a compromise between the need for details and the feasibility of computations [50,51].…”

Section: Introductionmentioning

confidence: 99%

Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China

et al. 2021

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Local climate zone (LCZ) maps have been used widely to study urban structures and urban heat islands. Because remote sensing data enable automated LCZ mapping on a large scale, there is a need to evaluate how well remote sensing resources can produce fine LCZ maps to assess urban thermal environments. In this study, we combined Sentinel-2 multispectral imagery and dual-polarized (HH + HV) PALSAR-2 data to generate LCZ maps of Nanchang, China using a random forest classifier and a grid-cell-based method. We then used the classifier to evaluate the importance scores of different input features (Sentinel-2 bands, PALSAR-2 channels, and textural features) for the classification model and their contribution to each LCZ class. Finally, we investigated the relationship between LCZs and land surface temperatures (LSTs) derived from summer nighttime ASTER thermal imagery by spatial statistical analysis. The highest classification accuracy was 89.96% when all features were used, which highlighted the potential of Sentinel-2 and dual-polarized PALSAR-2 data. The most important input feature was the short-wave infrared-2 band of Sentinel-2. The spectral reflectance was more important than polarimetric and textural features in LCZ classification. PALSAR-2 data were beneficial for several land cover LCZ types when Sentinel-2 and PALSAR-2 were combined. Summer nighttime LSTs in most LCZs differed significantly from each other. Results also demonstrated that grid-cell processing provided more homogeneous LCZ maps than the usual resampling methods. This study provided a promising reference to further improve LCZ classification and quantitative analysis of local climate.

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Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

Cited by 12 publications

References 61 publications

Telecoupling indirect ecological impacts of urban expansion in China from the perspective of the food trade

Telecoupling indirect ecological impacts of urban expansion in China from the perspective of the food trade

Crop Mapping in the Sanjiang Plain Using an Improved Object-Oriented Method Based on Google Earth Engine and Combined Growth Period Attributes

Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China

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