Prediction of Regional Forest Soil Nutrients Based on Gaofen-1 Remote Sensing Data
نویسندگان
چکیده
The study on the spatial distribution of forest soil nutrients is important not only as a reference for understanding factors affecting variability, but also rational use resources and establishment virtuous cycle ecosystems. rapid development remote sensing satellites provides an excellent opportunity to improve accuracy prediction models. This aimed explore utility Gaofen-1 (GF-1) satellite in mapping model Luoding City, Yunfu Guangdong Province, Southeast China. We used 1000 m resolution coarse-resolution map represent overall regional nutrient status, 12.5 terrain-hydrology variables reflect detailed nutrients, 8 surface vegetation status build artificial neural network (ANN) models full variable ANNs, respectively. objects were alkali-hydro-nitrogen (AN), available phosphorus (AP), potassium (AK), organic matter (OM) at five depths (0–20, 20–40, 40–60, 60–80, 80–100 cm). results showed that full-variable ANN was better than indicating reflecting can nutrients. had different effectiveness depths. In upper layers (0–20 20–40 cm), more useful AN, AP, OM, between 10%–14% (R2), less effective AK 8% 6% (R2). deep (40–60, improvement all significant, 3 RMSE ROA ± 5% decreased with depth soil. Remote ANNs (coarse maps + variables) further demonstrated predictive power data decreases depth. Compared terrain-hydrological variables, perform 0–20 cm, rapidly conclusion, integration could strongly (0–40 cm) NDVI, green band, types best predictors. addition, area rich AN while AP are scarce. Therefore, health, attention should be paid monitoring managing AK, OM levels.
منابع مشابه
Multi-Frame Super-Resolution of Gaofen-4 Remote Sensing Images
Gaofen-4 is China's first geosynchronous orbit high-definition optical imaging satellite with extremely high temporal resolution. The features of staring imaging and high temporal resolution enable the super-resolution of multiple images of the same scene. In this paper, we propose a super-resolution (SR) technique to reconstruct a higher-resolution image from multiple low-resolution (LR) satel...
متن کاملAir temperature estimation based on environmental parameters using remote sensing data
This study is aimed at estimating monthly mean air temperature (Ta) using the MODIS Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), latitude, altitude, slope gradient and land use data during 2001-2015. The results showed that despite some spatial similarities between annual spatial patterns of Ta and LST, their variations are significantly different, so that the...
متن کاملextraction of soil salinity zone in arid and semi arid regional using of remote sensing data (case study: darab township)
introduction soil salinity and expansion tts it, in the arid and semi-arid areas is including environmental issues that in recent years attention has been due to population growth and the need to utilizeland. in order to human was tried that using of different techniques determined salinity area between remote sensing data in recent years have provided relatively accurate results as a source of...
متن کاملResearch of Forest Classification Based on Remote Sensing Image
The forest plays an important role in regulating climate and improving ecological carrying capacity. In view of heterogeneous mixed young afforestation, the object-based classification on rules method is used to identify the types of planted forest, combined with spectrum, texture and shape characteristics information. ESP tool was applied to obtain the best segmentation scale and the rule set ...
متن کاملForest Fire Potential Modeling and Simulation of its Extension Using Remote Sensing Data and GIS: (A Protected Area of Arasbaran)
Forest fire models are generally used in different aspects of fire management and are helpful in understanding and prediction of fire behavior. Forest fires cause a significant damage for public property by destroying a large tract of forest. This helps fire fighters to focus on an area with greater risk and to develop better substructure for fire fighter training and ultimately to plan fire-f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Forests
سال: 2021
ISSN: ['1999-4907']
DOI: https://doi.org/10.3390/f12111430