Sensor Data Resolution via Land-Water Footprint Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for improving soil moisture data resolution, such as DisPATCh, achieve only a 1kmx1km resolution, which is insufficient for local field applications and is limited by the use of coarse scale soil moisture data and additional optical satellite information, particularly in coastal areas and under clouding conditions.
Innovation Solution
A method that combines coarse sensor footprint temperature brightness measurements with high-resolution land-water maps to distinguish between land and water types within the same sensor footprint, allowing for improved resolution of 100mx100m without requiring additional optical satellite data, by processing satellite data to derive additional ellipses and weighting brightness temperatures based on footprint contributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DisPATCh algorithm is used to disaggregate soil moisture observations using high-resolution soil temperature data, then the resolution is improved from coarse satellite data to 1kmx1km, but the resolution is still too coarse for local field applications
Solution Approach 1:
The patent segments the sensor footprint into multiple smaller areas corresponding to different land and water types. By dividing the coarse 1kmx1km footprint into finer segments (100mx100m), the method enables local field applications while maintaining the benefits of disaggregation. This segmentation allows temperature brightness measurements to be attributed to specific land-water type combinations within the footprint.
Solution Approach 2:
The patent applies local quality by creating area fractions specific to each land and water type within sensor footprints. Instead of treating the entire footprint uniformly, the method assigns different temperature brightness characteristics to different local areas based on their land-water type classification. This enables differentiated resolution improvement for coastal versus inland areas.
2Measurement precision
If additional optical satellite information (e.g., from MODIS) is used like the DisPATCh algorithm, then resolution can be improved, but the method is limited during clouding conditions and has limited use along coastlines
Solution Approach 1:
The patent introduces a land-water type map as an intermediary element that bridges the gap between coarse sensor data and fine-resolution applications. This map serves as a mediator that provides structural information about the footprint composition without requiring additional optical satellite observations. The intermediary enables resolution improvement while maintaining reliability under clouding conditions.
Solution Approach 2:
The patent creates a simplified representation (copy) of the physical footprint structure through the land-water type map. Instead of relying on complex optical satellite data to characterize the footprint, the method uses a simplified land-water classification map that captures the essential structural information needed for disaggregation. This copying approach avoids the limitations of optical data while preserving the necessary spatial information.
3Adaptability or versatility
If coarse scale soil moisture data from space agencies is used, then data availability is maintained, but the data is of limited use along coastlines and close to large waterbodies
Solution Approach 1:
The patent adds a new dimension of analysis by incorporating land-water type classification into the disaggregation process. Instead of solely relying on the spatial disaggregation achieved by DisPATCh, the method introduces a categorical dimension (land vs. water types) that enables differentiated interpretation of temperature brightness measurements. This dimensional enhancement makes the data applicable to coastal areas where the interaction between land and water creates distinct thermal signatures.
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
The invention relates to a system (51) for improving the spatial resolution of sensor data. The system comprises at least one receiver (53) and at least one processor (55). The at least one receiver (53) is configured to receive a sensor data set and a map. Each element of the sensor data set comprises a sensor footprint identifier allowing a sensor footprint to be identified and a brightness temperature measured for the sensor footprint. The map defines for each of a plurality of geographical areas whether it belongs to one of the first class and the second class. The first class represents a land type and the second class represents a water type. The geographical area is smaller than the sensor footprint. The at least one processor (55) is configured to determine for each element of the sensor data set received using the at least one receiver (53) a brightness temperature for each of at least two classes including the first class and the second class based on the map received using the at least one receiver (53) and to determine a brightness temperature for a specific geographical area of the map based on brightness temperatures associated with a plurality of footprints if the specific geographical area belongs to the first class and based on a brightness temperature determined for the second class if the specific geographical area belongs to the second class. Each of the plurality of footprints covers the specific geographical area.