DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Responses to Amendments and Arguments
The amendments filed 09/26/2025 have been entered. Claims 1 and 2 are amended. Claims 1-3 remain pending in the application.
Applicant's argument and amendments filed 09/26/2025 with respect to
the rejection of claims 1-3 directed to a judicial exception under 35 U.S.C. 101 have been fully considered but are not persuasive.
On pages 7-17 of Applicant’s response, Applicant alleges that the currently presented claims are directed to patent-eligible subject matter because they recite a specific, practical application that improves the technological field of large-scale remote sensing and forestry surveying, rather than being directed to an abstract idea. … The claimed method defines a specific and ordered set of rules for transforming raw, disparate remote sensing data into a technically valuable, high-precision forest height map. … This ordered combination of specific rules is not a mathematical formula in the abstract. … The claim does not seek to preempt any mathematical algorithm itself, but rather protects a specific, practical application of these computational steps within a defined technological process. … The sheer scale and complexity of the claimed method place it far beyond the practical capabilities of human cognition. … Just as in Example 39, the claimed method here requires the use of a computer not merely for speed, but to perform tasks that are practically impossible for a human to execute. Therefore, the claims are not directed to a mental process. … Applicant respectfully submits that the claimed invention is not directed to a method of organizing human activity because the problem it solves is an inherently technological one that has no pre-computer, human-activity analog. … This is a classic problem of technical data fusion and interpolation, not a method of organizing human behavior. … The currently presented Claim 1 directly addresses this technical problem with a specific, technical solution. … Instead, it recites: A large-scale forest height remote sensing retrieval method, … using a satellite-borne photon counting LiDAR system … In conclusion, the claimed method stands in stark contrast to judicial exceptions for organizing human activity, which typically involve managing commercial relationships or social interactions. … Applicant respectfully submits that the same reasoning from the Office's analysis of Example 39 applies with equal force to the currently presented claims: … For the foregoing reasons, Applicant submits that the currently presented claims are not directed to a mathematical concept, a mental process, or a method of organizing human activity. Because the claims are not directed to any judicial exception, the § 101 analysis should conclude at Step 2A. The claims are patent-eligible. … The claimed method is not merely an abstract calculation ending in a number. Instead, it produces a tangible data product-the high-precision tree height spatial distribution map-that serves as a technical tool to guide subsequent, real-world actions in the field of forestry and environmental management. … By producing a specific, improved data structure that is inextricably tied to these practical, real-world applications, the claimed method integrates any alleged abstract idea into a practical application that provides "significantly more." … Therefore, even if the claims were viewed as being directed to an abstract idea, they are patent-eligible under Step 2B of the Alice/Mayo framework. … Ultimately, the claimed invention is not an isolated algorithm but a complete, end-to-end solution. It begins with a physical-world challenge-the technical difficulty of accurately measuring vast, inaccessible forests-and, through an innovative technological process, delivers a solution that feeds directly back into the management of that physical world.
The Examiner respectfully disagrees.
The additional elements of the “processor” and the “satellite-borne photon counting LiDAR system” are high level of generalities recited to merely perform a generic computer function of a generic computer component, because the claims do not recite their specific structure/features themselves configured to perform the claimed invention related to the steps of, for example, acquiring data and preprocessing data as well as do not add meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment to transform the judicial exception into patent-eligible subject matter. Note that, under the broadest reasonable interpretation, the limitation of “preprocessing, by a processor, the ICESAT-2 tree height data preprocessing the ICESAT-2 tree height data by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center” is indicative of a mathematical concept/relationship which is related to a data process, because the operation related to “by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center” is indicative of a mathematical calculation to thereby obtain the mathematical results (i.e., the tree height data and the longitude and latitude coordinate of the corresponding spot center). (See MPEP 2106.04. (a)(2)). Therefore, the Examiner maintains the claims are ineligible. (See the modified rationale presented below).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The current 35 USC 101 analysis is based on the current guidance (Federal Register vol. 79, No. 241. pp. 74618-74633). The analysis follows several steps. Step 1 determines whether the claim belongs to a valid statutory class. Step 2A prong 1 identifies whether an abstract idea is claimed. Step 2A prong 2 determines whether any abstract idea is integrated into a practical application. If the abstract idea is integrated into a practical application the claim is patent eligible under 35 USC 101. Last, step 2B determines whether the claims contain something significantly more than the abstract idea. In most cases the existence of a practical application predicates the existence of an additional element that is significantly more.
The 35 USC 101 analysis between each element of claims and its combination is presented in the table below
Claim number and elements
Judicial exception (Step 2A Prong one)
Practical application (Step 2A Prong two)/ Significantly more (Step 2B)
Claim 1
Step 1: Yes, statutory class
Step 2A Prong two: No / Step 2B: No
A large-scale forest height remote sensing retrieval method, the method comprising:
Step2A Prong one: Yes
step 1: acquiring Ice, Cloud and land Elevation Satellite (ICESAT-2) tree height data using a satellite-borne photon counting LiDAR system, Landsat data, Shuttle Radar Topography Mission (SRTM) data, Worldclim data, forest type data and ecological zoning data within a target zone, and preprocessing, by a processor, the ICESAT-2 tree height data preprocessing the ICESAT-2 tree height data by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center;
abstract idea
mathematical concept
“acquiring ~” is insignificant extra-solution activities to collect data which are used to perform abstract idea itself.
“a processor” and “a satellite-borne photon counting LiDAR system” are high level of generalities recited to merely perform a generic computer function of a generic computer component.
“preprocessing, …, the ICESAT-2 tree height data ~ by removing … to obtain high-precision tree height data ~” is a math process and/or data processing.
step 2: carrying out, by the processor, georeferencing on the processed Landsat data, SRTM data, Worldclim data, forest type data and ecological zoning image data and the high-precision tree height data to generate a first data set;
abstract idea
mathematical concept
“carrying out ~” is a math process and/or data processing to generate a first data set.
step 3: calculating, by the processor, spectral features, terrain features and climatic factor features of an image according to the first data set, and combining the calculated features with the ecological zoning data and the forest type data to obtain a second data set, thereby improving an accuracy of prediction;
abstract idea
mathematical concept
“calculating ~ and combining ~” is a math process.
wherein, in step 3, the spectral features of a Landsat image comprise six original spectral wavebands B2, B3, B4, B5, B6 and B7, an normalized differential vegetation index (NDVI), a difference vegetation index (DVI), a ratio vegetation index (RVI), a soil-adjusted vegetation index (SAVI), an enhanced vegetation index (EVI), a leaf area index (LAI), a tasseled cap brightness TCB, a tasseled cap greenness TCG, a tasseled cap wetness TCW, a Contrast texture, a Dvar texture and an Inertia texture;
the terrain features of SRTM comprise a terrain altitude DEM, a slope, an aspect, and hill shades under the solar azimuth angles of 00, 600, 1200, 1800, 2400 and 3000;
the climatic factor features of Worldclim comprise 19 biologically-related climatic factors biol-biol9;
thus, the finally-obtained second data set comprises a total of 48 features consisting of the ecological zoning data, 18 spectral features, 9 terrain features, 19 climatic factors and the forest type data;
abstract idea
mathematical concept
“the spectral features” is a mathematical value/amount/factor indicative of spectral wavebands.
“an normalized differential vegetation index (NDVI), a difference vegetation index (DVI), a ratio vegetation index (RVI), a soil-adjusted vegetation index (SAVI), an enhanced vegetation index (EVI), a leaf area index (LAI), a tasseled cap brightness TCB, a tasseled cap greenness TCG, a tasseled cap wetness TCW, a Contrast texture, a Dvar texture and an Inertia texture” are indicative of mathematical values/amounts/factors.
“the terrain features of SRTM” and “the climatic factor features of Worldclim” are mathematical value/amounts.
step 4: extracting, by the processor, eigenvalues of a same geographical location from the second data set by using the latitude and longitude coordinate of the corresponding spot center corresponding to the ICESAT-2 tree height data, and combining the extracted eigenvalues with the tree height data to generate training data;
abstract idea
mathematical concept
“extracting eigenvalues ~ and combining ~” is a math process to generate a mathematical result (i.e., training data).
step 5: constructing, by the processor, a random forest model covering a large zone as an ecological zoning tree height retrieval model, and dividing the obtained training data into a training sample and a verification sample, wherein the training sample is used to train the model, and the verification sample is used to verify the model; and
abstract idea
mathematical concept
“constructing a random forest model ~ and dividing ~” is a math process.
“a random forest model” and “an ecological zoning tree height retrieval model” are mathematical algorithms.
step 6: estimating, by the processor, a spatially-continuous forest height of an entire research zone by using the ecological zoning tree height retrieval model trained in step 5 to obtain a tree height spatial distribution map, so as to realize a rapid and high-precision estimation for a continuous forest height mapping.
abstract idea
mathematical concept
“estimating ~” is a math process.
Claims 1-3 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-3 are directed to an abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as addressed below and presented in the above table.
Step 2A: Prong One
Regarding Claim 1, the limitations recited in Claim 1, as drafted, are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mathematical calculations and/or the mind, as presented in the above table. Nothing in the claim elements precludes the step from practically being performed in the mind and/or the mathematical calculations. For example, “preprocessing, by a processor, the ICESAT-2 tree height data preprocessing the ICESAT-2 tree height data by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center” in the context of this claim may encompass mathematical calculations and/or data processing itself, because the step of preprocessing is indicative of the mathematical calculation related to “by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center” to thereby obtain the mathematical results (i.e., the tree height data and the longitude and latitude coordinate of the corresponding spot center). (See MPEP 2106.04. (a)(2)).
For example, “step 2: carrying out, by the processor, georeferencing on the processed Landsat data, SRTM data, Worldclim data, forest type data and ecological zoning image data and the high-precision tree height data to generate a first data set” and “step 3: calculating, by the processor, spectral features, terrain features and climatic factor features of an image according to the first data set, and combining the calculated features with the ecological zoning data and the forest type data to obtain a second data set, thereby improving an accuracy of prediction, wherein, in step 3, the spectral features of a Landsat image comprise six original spectral wavebands B2, B3, B4, B5, B6 and B7, an normalized differential vegetation index (NDVI), a difference vegetation index (DVI), a ratio vegetation index (RVI), a soil-adjusted vegetation index (SAVI), an enhanced vegetation index (EVI), a leaf area index (LAI), a tasseled cap brightness TCB, a tasseled cap greenness TCG, a tasseled cap wetness TCW, a Contrast texture, a Dvar texture and an Inertia texture; the terrain features of SRTM comprise a terrain altitude DEM, a slope, an aspect, and hill shades under the solar azimuth angles of 00, 600, 1200, 1800, 2400 and 3000; the climatic factor features of Worldclim comprise 19 biologically-related climatic factors biol-biol9; thus, the finally-obtained second data set comprises a total of 48 features consisting of the ecological zoning data, 18 spectral features, 9 terrain features, 19 climatic factors and the forest type data” in the context of this claim may encompass mathematical calculations and/or data processing in a manner of performing data processing and/or mathematical calculations by georeferencing on the collected data to thereby generate a processed data set (i.e., the first data set), calculate the features based the generated data set and combine the calculated features (i.e., mathematical concept) with another data to calculate the second data set (i.e., mathematical result). The “spectral features” is indicative of a mathematical value/amount/factor indicative of spectral wavebands. The “normalized differential vegetation index (NDVI)”, the “difference vegetation index (DVI)”, the “ratio vegetation index (RVI)”, the “soil-adjusted vegetation index (SAVI)”, the “enhanced vegetation index (EVI)”, the “leaf area index (LAI)”, the “tasseled cap brightness TCB”, the “tasseled cap greenness TCG”, the “tasseled cap wetness TCW”, the “Contrast texture”, the “Dvar texture” and the “Inertia texture” are indicative of mathematical values/amounts/factors.
Similarly, “step 4: extracting, by the processor, eigenvalues of a same geographical location from the second data set by using the latitude and longitude coordinate of the corresponding spot center spot center corresponding to the ICESAT-2 tree height data, and combining the extracted eigenvalues with the tree height data to generate training data” in the context of this claim may encompass mathematical calculations by calculating or inferring training data to extract the eigenvalues of a same geographical location and combining the extracted eigenvalues with the tree height data which are indicative of mathematical calculations and/or data processing itself.
For example, “step 5: constructing, by the processor, a random forest model covering a large zone as an ecological zoning tree height retrieval model, and dividing the obtained training data into a training sample and a verification sample, wherein the training sample is used to train the model, and the verification sample is used to verify the model” and “step 6: estimating, by the processor, a spatially-continuous forest height of an entire research zone by using the ecological zoning tree height retrieval model trained in step 5 to obtain a tree height spatial distribution map, so as to realize a rapid and high-precision estimation for a continuous forest height mapping” in the context of this claim may encompass calculating or inferring the random forest model and the spatially-continuous forest height of the entire research zone by performing mathematical calculation to thereby obtain the tree height spatial distribution map (i.e., mathematical concept inferred by mathematical calculations). The “random forest model” and the “ecological zoning tree height retrieval model” are indicative of mathematical algorithms.
Step 2A: Prong Two
This judicial exception is abstract ideal itself and not integrated into a practical application. In particular, the specification details use of a processor to perform mathematical calculations of “preprocessing, by a processor, the ICESAT-2 tree height data preprocessing the ICESAT-2 tree height data by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center”, “step 2: carrying out, by the processor, georeferencing on the processed Landsat data, SRTM data, Worldclim data, forest type data and ecological zoning image data and the high-precision tree height data to generate a first data set”, “step 3: calculating, by the processor, spectral features, terrain features and climatic factor features of an image according to the first data set, and combining the calculated features with the ecological zoning data and the forest type data to obtain a second data set, thereby improving an accuracy of prediction, wherein, in step 3 …”, “step 4: extracting, by the processor, eigenvalues of a same geographical location from the second data set by using the latitude and longitude coordinate of the corresponding spot center spot center corresponding to the ICESAT-2 tree height data, and combining the extracted eigenvalues with the tree height data to generate training data”, “step 5: constructing, by the processor, a random forest model covering a large zone as an ecological zoning tree height retrieval model, and dividing the obtained training data into a training sample and a verification sample, wherein the training sample is used to train the model, and the verification sample is used to verify the model” and “step 6: estimating, by the processor, a spatially-continuous forest height of an entire research zone by using the ecological zoning tree height retrieval model trained in step 5 to obtain a tree height spatial distribution map, so as to realize a rapid and high-precision estimation for a continuous forest height mapping”. The limitation of “acquiring Ice, Cloud and land Elevation Satellite (ICESAT-2) tree height data using a satellite-borne photon counting LiDAR system, Landsat data, Shuttle Radar Topography Mission (SRTM) data, Worldclim data, forest type data and ecological zoning data within a target zone” is insignificant pre-solution activity necessary to merely gather data to be used for performing the abstract idea. See MPEP 2106.05(g). The additional elements of the “processor” and the “satellite-borne photon counting LiDAR system” are high level of generalities recited to merely perform a generic computer function of a generic computer component, because the claims do not recite their specific structure/features themselves configured to perform the claimed invention related to the steps of acquiring data and preprocessing data as well as do not add meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment to transform the judicial exception into patent-eligible subject matter. There is no showing of integration into a practical application such as an improvement to the functioning of a computer, or to any other technology or technical field, or use of a particular machine.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitation of “acquiring Ice, Cloud and land Elevation Satellite (ICESAT-2) tree height data using a satellite-borne photon counting LiDAR system, Landsat data, Shuttle Radar Topography Mission (SRTM) data, Worldclim data, forest type data and ecological zoning data within a target zone” is insignificant pre-solution activity to merely gather routine data to be used for performing the abstract idea. See MPEP 2106.05(g). As discussed above, with respect to integration of the abstract idea into a practical application, using a computer software to perform “preprocessing, by a processor, the ICESAT-2 tree height data preprocessing the ICESAT-2 tree height data by removing low-quality laser spot data to obtain high-precision tree height data and a longitude and latitude coordinate of a corresponding spot center”, “step 2: carrying out, by the processor, georeferencing on the processed Landsat data, SRTM data, Worldclim data, forest type data and ecological zoning image data and the high-precision tree height data to generate a first data set”, “step 3: calculating, by the processor, spectral features, terrain features and climatic factor features of an image according to the first data set, and combining the calculated features with the ecological zoning data and the forest type data to obtain a second data set, thereby improving an accuracy of prediction, wherein, in step 3 …”, “step 4: extracting, by the processor, eigenvalues of a same geographical location from the second data set by using the latitude and longitude coordinate of the corresponding spot center spot center corresponding to the ICESAT-2 tree height data, and combining the extracted eigenvalues with the tree height data to generate training data”, “step 5: constructing, by the processor, a random forest model covering a large zone as an ecological zoning tree height retrieval model, and dividing the obtained training data into a training sample and a verification sample, wherein the training sample is used to train the model, and the verification sample is used to verify the model” and “step 6: estimating, by the processor, a spatially-continuous forest height of an entire research zone by using the ecological zoning tree height retrieval model trained in step 5 to obtain a tree height spatial distribution map, so as to realize a rapid and high-precision estimation for a continuous forest height mapping” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept cannot provide statutory eligibility. Claim 1 is not patent eligible.
Regarding Claims 2-3, the limitations are further directed to an abstract idea, as described in claim 1. The limitation of “step 1.1: collecting the Landsat data, the SRTM data, the Worldclim data and the forest type data within the target zone” and “collecting the ecological zoning data within the target zone to obtain a boundary range of each ecological zone, wherein N sub-ecological zones are comprised in total, carrying out category data re-encoding on each sub-ecological zone to obtain an ecological zone 1, an ecological zone 2, an ecological zone 3...an ecological zone N with corresponding codes 1, 2, 3..., N respectively” in Claim 2 is insignificant extra-solution activities to merely gather routine data by using the Google Earth Engine, which are used for performing abstract idea. (See paragraphs 0031-0034 of the instant application). The limitation of “step 1.2: employing a data quality layer in a cloud masking method CFmask to remove cloud and cloud shade pixels in the Landsat image to obtain high-quality Landsat data”, “step 1.3: resampling the SRTM data and the Worldclim data to be consistent with Landsat resolution”, “step 1.4: carrying out category data re-encoding on each category of the forest type data to obtain a forest type 1, a forest type 2, a forest type 3...... a forest type M with corresponding codes 1, 2, 3..., M respectively”, “step 1.5: acquiring the ICESAT-2 tree height data within the target zone, and employing terrain filtering, canopy height filtering and photon number filtering to remove low-quality laser spot data to obtain the high-precision tree height data and the longitude and latitude coordinate of the corresponding spot center” in the context of this claim may encompass calculating or inferring the forest types, the high-precision tree height data and the longitude and latitude coordinate of the corresponding spot center by performing mathematical calculations and/or computing data process such as the employing step, resampling step, the carrying out step, and the acquiring and employing step. For the reasons described above with respect to Claim 1, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
Citation of Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
SOLBERG SVEIN (WO 2016169699 A1) teaches determining mass change in a study area using remote sensing data, where first and second data sets of the area are retrieved, which datasets are obtained at respective first and second point of time and comprises respective first and second set of pixel data given by respective first and second wavelength, and each pixel comprised in the respective first and second set of pixel data corresponds to a subarea of the area and a value for each pixel comprised in the respective first and second set is indicative of an amount of mass in the subarea at the respective first and second points of time.
BRUMBY et al. (US 20200272625 A1) teaches evaluating, exploring, and predicting the status of regions of the planet through time in a manner of collecting relevant datasets, transforming datasets into dynamic datasets, selecting a region of interest, selecting factors of interest, producing an evaluation index for the region of interest, specifying targets and thresholds for the evaluation index, generating a visualization of the evaluation index for the region of interest; generating alerts when the evaluation index changes in specified ways, and reporting the status and trend of the region of interest using the evaluation index to thereby produce predictive models and maps from the time series indices, where the data transformation is optionally achieved with machine learning algorithms and training data to produce time series indices.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BYUNG RO LEE whose telephone number is (571)272-3707. The examiner can normally be reached on Monday-Friday 8:30am-4:00pm.
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/BYUNG RO LEE/Examiner, Art Unit 2858
/LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858