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Reliable and accurate rice mapping using synthetic aperture radar (SAR) in cloudy and rainy areas is essential for achieving the United Nations Sustainable Development Goal 2 of 2030. An interpretable deep learning SAR rice area mapping method is proposed in this letter to suppress the interference of wetlands and other land covers to multitemporal SAR rice area mapping and improve the accuracy and confidence of the “black box” deep learning model results. Combining the temporal backscattering coefficients and interferometric coherence, three interpretable temporal features are extracted to effectively distinguish rice. Then, the explainable feature-aware network (XFANet), which can provide the learned importance weights of the normalization methods as self-interpretation, is constructed, and the pixel-wise gradient-weighted class activation mapping (PGCAM) post-hoc interpretation method is introduced to interpret the feature variation within the model. The experimental results in the Kampong Chhang and Kampong Chham provinces of Cambodia show that the proposed three interpretable features well suppressed the wetland disturbance to rice. With high interpretability, the overall accuracy (OA) of XFANet reaches 93.43%. [ABSTRACT FROM AUTHOR]

Purpose – Fewer researchers have investigated the climatic and economic drivers of land-use change simultaneously and the interplay between drivers. This paper aims to investigate the nonlinear and interaction effects of price and climate variables on the rice acreage in high-latitude regions of China. Design/methodology/approach – This study applies a multivariate adaptive regression spline to characterize the effects of price and climate expectations on rice acreage in high-latitude regions of China from 1992 to 2017. Then, yield expectation is added into the model to investigate the mechanism of climate effects on rice area allocation. Findings – The results of importance assessment suggest that rice price, climate and total agricultural area play an important role in rice area allocation, and the importance of temperature is always higher than that of precipitation, especially for minimum temperature. Based on the estimated hinge functions and coefficients, it is found that total agricultural area has strong nonlinear and interaction effects with climate and price as forms of third-order interaction. However, the order of interaction terms reduces to second order after absorbing the expected yield. Additionally, the marginal effects of driven factors are calculated at different quantiles. The total area shows a positive and increasing marginal effect with the increase of total area. But the positive impact of price on the rice area can only be observed when price reached 50% or higher quantiles. Climate variables also show strong nonlinear marginal effects, and most climatic effects would disappear or be weakened once absorbing the expected rice yield. Expected yield is an efficient mechanism to explain the correlation between crop area and climate variables, but the impact of minimum temperature cannot be completely modeled by the yield expectation. Originality/value – To the best of the authors’ knowledge, this is the first study to examine the nonlinear response of land-use change to climate and economic in high-latitude regions of China using the machine learning method.

The areas of northern Thailand rely heavily on water management by Muang Fai irrigation systems. Outstanding features of these typical systems include public participation and acceptance of regulations established by Muang Fai irrigation management; however, the knowledge and application of modern technologies should be promoted in these systems in collaboration with traditional water management. In this study, remote sensing was applied to analyse plant phenology to estimate the planting dates and farming sizes through Sentinel-2 imagery. CROPWAT 8.0 was also used to analyse the crop water requirements in different periods to enable the water management committee to determine the water quantity needed in each period throughout the area. The greatest water amounts were needed by plants during the dry season in March and April each year. In addition, the researcher team adopted strengths, weaknesses, opportunities and threats (SWOT) analysis to establish guidelines for the potential enhancement of Muang Fai irrigation systems suited to the current social contexts and environment. [ABSTRACT FROM AUTHOR]

Ordinary least squares and seemingly unrelated regression procedures were used to analyze the impacts of changes in rice prices and production costs on Jambi rice planted area. Regional response models were estimated over the 1986-2013 period. Supply-inducing prices of rice were estimated as a function of effective rice support prices and average market prices. Expected production costs per hectare were estimated using lagged actual total variable cash production expenses per hectare. Estimated short-run price and production cost elasticity were found to be inelastic at the regional level. However, the magnitudes of the production cost elasticity were found to be greater than the price elasticity. Estimated longrun elasticity at the Jambi level was inelastic for changes in price but elastic for changes in production costs. Although area response varied across regions, similar relationships were found between price and production cost elasticity.

Ordinary least squares and seemingly unrelated regression procedures were used to analyze the impacts of changes in rice prices and production costs on Jambi rice planted area. Regional response models were estimated over the 1986-2013 period. Supply-inducing prices of rice were estimated as a function of effective rice support prices and average market prices. Expected production costs per hectare were estimated using lagged actual total variable cash production expenses per hectare. Estimated short-run price and production cost elasticity were found to be inelastic at the regional level. However, the magnitudes of the production cost elasticity were found to be greater than the price elasticity. Estimated longrun elasticity at the Jambi level was inelastic for changes in price but elastic for changes in production costs. Although area response varied across regions, similar relationships were found between price and production cost elasticity. [ABSTRACT FROM AUTHOR]