Chlorophyll Content Estimation of Ginkgo Seedlings Based on Deep Learning and Hyperspectral Imagery DOI Open Access
Zilong Yue, Qilin Zhang,

Xingzhou Zhu

и другие.

Forests, Год журнала: 2024, Номер 15(11), С. 2010 - 2010

Опубликована: Ноя. 14, 2024

Accurate estimation of chlorophyll content is essential for understanding the growth status and optimizing cultivation practices Ginkgo, a dominant multi-functional tree species in China. Traditional methods based on chemical analysis determining are labor-intensive time-consuming, making them unsuitable large-scale dynamic monitoring high-throughput phenotyping. To accurately quantify Ginkgo seedlings under different nitrogen levels, this study employed hyperspectral imaging camera to capture canopy images throughout their annual periods. Reflectance derived from pure leaf pixels was extracted construct set spectral parameters, including original reflectance, logarithmic first derivative along with index combinations. A one-dimensional convolutional neural network (1D-CNN) model then developed estimate content, its performance compared four common machine learning methods, Gaussian Process Regression (GPR), Partial Least Squares (PLSR), Support Vector (SVR), Random Forest (RF). The results demonstrated that 1D-CNN outperformed others spectra, achieving higher CV-R2 lower RMSE values (CV-R2 = 0.80, 3.4). Furthermore, incorporating combinations enhanced model’s performance, best 0.82, 3.3). These findings highlight potential strengthening estimations, providing strong technical support precise fertilization management seedlings.

Язык: Английский

Effectiveness Trade-Off Between Green Spaces and Built-Up Land: Evaluating Trade-Off Efficiency and Its Drivers in an Expanding City DOI Creative Commons

Xinyu Dong,

Yanmei Ye, Tao Zhou

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(2), С. 212 - 212

Опубликована: Янв. 9, 2025

Urban expansion encroaches on green spaces and weakens ecosystem services, potentially leading to a trade-off between ecological conditions socio-economic growth. Effectively coordinating the two elements is essential for achieving sustainable development goals at urban scale. However, few studies have measured urban–ecological linkage in terms of trade-off. In this study, we propose framework by linking degraded land use efficiency from return investment perspective. Taking rapidly expanding city as case comprehensively quantified four aspects: heat island, flood regulating service, habitat quality, carbon sequestration. These were assessed 1 km2 grids, along with same spatial We employed slack-based measure model evaluate applied geo-detector method identify its driving factors. Our findings reveal that while Zhengzhou’s periphery over past decades, inner showed improvement island Trade-off exhibited an overall upward trend during 2000–2020, despite initial declines some areas. Interaction detection demonstrates significant synergistic effects pairs drivers, such Normalized Difference Vegetation Index building height, number patches patch cohesion index built-up land, q-values 0.298 0.137, respectively. light spatiotemporal adaptive management strategies. The could serve guidance assist decision-makers planners monitoring context expansion.

Язык: Английский

Процитировано

0
Quantifying the relative importance of natural and human factors on vegetation dynamics in China’s western frontiers during 2010-2021 DOI
Wenyang Shi, Ping Lü, Haoxuan Yang

и другие.

Environmental Research, Год журнала: 2025, Номер unknown, С. 121120 - 121120

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Towards ecological security: Two-thirds of China’s ecoregions experienced a decline in habitat quality from 1992 to 2020 DOI Creative Commons
Qiang Xue, Yang Zhang,

Qingmin Zhang

и другие.

Ecological Indicators, Год журнала: 2025, Номер 172, С. 113275 - 113275

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Potential construction area identification of the transboundary national park bridging ecology, society and economics: A case study of Mount Everest region DOI
Yu Hu, Xinyue Hu

Journal of Environmental Management, Год журнала: 2025, Номер 381, С. 125190 - 125190

Опубликована: Апрель 6, 2025

Язык: Английский

Процитировано

0
Exploring the Spatiotemporal Changes and Driving Forces of Ecosystem Services of Zhejiang Coasts, China, Under Sustainable Development Goals DOI
Shu Zhang,

Chao Sun,

Yixin Zhang

и другие.

Chinese Geographical Science, Год журнала: 2024, Номер 34(4), С. 647 - 661

Опубликована: Июль 17, 2024

Язык: Английский

Процитировано

3
Incorporating Ecosystem Service Trade-Offs and Synergies with Ecological Sensitivity to Delineate Ecological Functional Zones: A Case Study in the Sichuan-Yunnan Ecological Buffer Area, China DOI Creative Commons

Peipei Miao,

Cansong Li, Baichuan Xia

и другие.

Land, Год журнала: 2024, Номер 13(9), С. 1503 - 1503

Опубликована: Сен. 16, 2024

Enhancing regional ecosystem stability and managing land resources effectively requires identifying ecological function zones understanding the factors that influence them. However, most current studies have primarily focused on service bundles, paying less attention to trade-offs, synergies, sensitivity, leading a more uniform approach functional zoning. This study aimed analyze describe spatial temporal patterns of four essential services, including water yield (WY), net primary productivity (NPP), soil conservation (SC), habitat quality (HQ), in Sichuan-Yunnan buffer area over period from 2005 2019. Spatial overlay analysis was used assess bundles define zones. Geographic detectors were then applied identify drivers variation these The findings showed progressive improvement functions within zone. Between 2019, NPP, conservation, all demonstrated positive trends, while HQ displayed declining trend. There significant heterogeneity distinct functions, with general decrease southwest northeast, particularly NPP HQ. Trade-offs evident between WY northeast east regions. Ecological sensitivity decreased northeast. Regions higher situated southwestern region, their distribution pattern comparable high quality. categorized areas into various types, human production settlement zones, ecologically vulnerable transition accounting for 17.28%, 22.30%, 7.41%, 53.01% total area, respectively. environmental factor affecting zoning identified as precipitation, main social variables activity population density. enhances supports sustainable development offering important guidance

Язык: Английский

Процитировано

1
Multi-scenario simulation and optimization of habitat quality under karst desertification management DOI Creative Commons
Xiang Li, Shunmin Zhang, Xiaona Li

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Окт. 31, 2024

Introduction Investigation of the evolutionary trend habitat quality in karst and rocky desertification zones is crucial for enhancing ecological security conservation. Methods Analysis land use statistics from years 2000, 2010, 2020, changes (HQ) (LULC) between 2000 2020 were analyzed using Huize County Yunnan Province as an example. The InVEST FLUS models applied to simulate LULC under different scenarios 2030 2040 assess spatial gradients at each timepoint factors influencing them. Results findings indicated that (1) predominant types are grassland woodland, experiencing most significant growth urbanized areas, main sources which paddy fields high-cover grassland. (2) was average displayed a consistent decline. distribution pattern indicates low HQ urban high outskirts, south-west, north-east. In all four scenarios, predominantly decreases areas regions with dense concentration built-up land. (3) Habitat primarily affected by type use, NDVI being secondary determinant. Discussion environment must be restored safeguarded focus on priorities harmonious development scenarios. This study provides methodological lessons ecorestoration policymakers karstic desertification.

Язык: Английский

Процитировано

1
Conservation effects of transboundary protected areas on mitigating anthropogenic pressure across China's borders DOI
Li An, Lei Shen,

Shuai Zhong

и другие.

Resources Conservation and Recycling, Год журнала: 2024, Номер 212, С. 107976 - 107976

Опубликована: Окт. 22, 2024

Язык: Английский

Процитировано

0
Chlorophyll Content Estimation of Ginkgo Seedlings Based on Deep Learning and Hyperspectral Imagery DOI Open Access
Zilong Yue, Qilin Zhang,

Xingzhou Zhu

и другие.

Forests, Год журнала: 2024, Номер 15(11), С. 2010 - 2010

Опубликована: Ноя. 14, 2024

Accurate estimation of chlorophyll content is essential for understanding the growth status and optimizing cultivation practices Ginkgo, a dominant multi-functional tree species in China. Traditional methods based on chemical analysis determining are labor-intensive time-consuming, making them unsuitable large-scale dynamic monitoring high-throughput phenotyping. To accurately quantify Ginkgo seedlings under different nitrogen levels, this study employed hyperspectral imaging camera to capture canopy images throughout their annual periods. Reflectance derived from pure leaf pixels was extracted construct set spectral parameters, including original reflectance, logarithmic first derivative along with index combinations. A one-dimensional convolutional neural network (1D-CNN) model then developed estimate content, its performance compared four common machine learning methods, Gaussian Process Regression (GPR), Partial Least Squares (PLSR), Support Vector (SVR), Random Forest (RF). The results demonstrated that 1D-CNN outperformed others spectra, achieving higher CV-R2 lower RMSE values (CV-R2 = 0.80, 3.4). Furthermore, incorporating combinations enhanced model’s performance, best 0.82, 3.3). These findings highlight potential strengthening estimations, providing strong technical support precise fertilization management seedlings.

Язык: Английский

Процитировано

0